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N-710

Enhancing Healthcare Professional’s Role in Assessing and Monitoring Depression Levels Using PHQ 9 Depression Screening Tool

Facilitator:
Module # 5: Assignment # 1: Final Proposal Draft
Student:
Date:

A prevalent and crippling mental illness that affects millions of people globally is depression (Moitra et al., 2023). Its sneaky nature frequently goes unrecognized until its terrible consequences become apparent, affecting the victims, their families, communities, and larger social systems. It is becoming more and more important to provide early detection, continuing monitoring, and management as the prevalence of depression rises. How important it is to train medical staff to recognize, diagnose, and track depression in various healthcare settings is a recognized priority (Ford et al., 2020).
To improve healthcare practitioners’ comprehension and application of the Patient Health Questionnaire (PHQ-9) for clinical practice depression screening, this project intends to conduct an educational activity. Through highlighting the significance of prompt identification and treatment of depression, the initiative seeks to enhance patient outcomes.

Significance of the Practice Problem

Depression affects people of all ages, genders, socioeconomic statuses, and cultural origins; it has no borders. The World Health Organization (WHO) estimates that 264 million people worldwide suffer from depression, making it one of the main causes of disability worldwide (Goodwin et al., 2022). Even more, it is anticipated that the prevalence of depression will rise globally due to a number of variables, including socioeconomic inequality, the stigma associated with mental illness, and the long-lasting effects of the COVID-19 pandemic.
Crucial tactics for reducing the negative impacts of depression are early detection and intervention. Early diagnosis and treatment significantly enhance recovery rates, diminish symptom severity, and improve the overall quality of life for individuals grappling with depression (Blackstone et al., 2022).
Healthcare experts play a key role in the management of depression. They are frontline responders with the knowledge and power to evaluate, identify, and treat depression in a variety of healthcare settings, from general practice offices to inpatient mental health centers. Providing evidence-based interventions, identifying depression, and facilitating patient-centered care all depend on healthcare providers having the right information, abilities, and resources (Blackstone et al., 2022).
In the toolkit of healthcare providers, the Patient Health Questionnaire (PHQ-9) shows promise as a screening instrument for depression detection. The PHQ-9 is a short, self-administered questionnaire designed to evaluate the frequency and intensity of depressive symptoms, allowing medical professionals to determine whether or not a patient is depressed rapidly (Levis et al., 2019). Its ease of use, dependability, and validity make it a priceless tool for identifying those in danger and enabling prompt treatments.
Even with the importance of diagnosing and treating depression, medical practitioners still face several obstacles in their work. Inadequate mental health education and training, time restraints, stigma, and resource scarcity frequently make it difficult for them to treat depression in clinical practice successfully. Furthermore, because depression has many facets, treating it requires an integrated, multidisciplinary strategy that includes social, pharmaceutical, and psychological interventions (Cuijpers et al., 2020).
To address the growing demand for improved depression screening and treatment, a comprehensive training program aimed at medical professionals is suggested. This program aims to give medical professionals the necessary understanding, abilities, and self-assurance to evaluate, treat, and track depression levels in a variety of healthcare environments. The main screening instrument in this proposal is the Patient Health Questionnaire (PHQ-9), which is complemented by evidence-based therapies and continuous monitoring procedures.

PICOT Question

For healthcare providers (P), does an education program on the Patient Health Questionnaire 9 (PHQ9) (I), compared with no education program (C), increase knowledge on screening depression (O) over a period of 8 weeks (T)?

Hypothesis: It is hypothesized that through targeted education and training, licensed healthcare providers will demonstrate increased awareness, proficiency, and utilization of the PHQ-9 for screening depression in clinical practice. Furthermore, it is hypothesized that early detection and treatment of depression will lead to improved patient outcomes, reduced risk of complications, and ultimately enhanced quality of life.

Objectives

Objective 1: Assess the baseline knowledge level of licensed healthcare providers regarding depression screening using the Patient Health Questionnaire 9 (PHQ9) before implementing the education program.

Objective 2: Implement an educational program for licensed healthcare on the Patient Health Questionnaire 9 (PHQ9), focusing on understanding the tool’s administration, interpretation, and implications for depression screening.

Objective 3: Evaluate the effectiveness of the educational program by comparing the post-intervention knowledge level of licensed healthcare providers regarding depression screening using the PHQ9 with their baseline knowledge level, measured at the end of an 8-week period.

Theoretical Framework

Renowned author and leadership specialist John Kotter created the highly regarded Theory of Change, which offers a methodical framework for managing the organizational transition. Fundamentally, Kotter’s Theory of Change strongly emphasizes establishing a coalition that will lead, cultivating a culture of ongoing learning and adaptation, and generating a feeling of urgency. This idea can act as a guide for implementing successful educational programs and fostering long-lasting change when it comes to depression screening in primary care. This idea provides important direction for encouraging educational initiatives to improve primary care providers’ screening methods for depression.
The “8-Step Process for Leading Change,” based on John Kotter’s theory of change, provides a framework for managing organizational transformation. This model has been used for medical residence didactics and other medical applications (Haas et al., 2019). The principles of the Kotter model are:

Create a Sense of Urgency: Kotter stresses the need of giving stakeholders a compelling rationale for change to inspire action and combat complacency.

Form a Powerful Coalition: A guiding coalition is a broad group of prominent leaders and stakeholders committed to change. This coalition guides, supports, and funds change.

Create a Vision for Change: Kotter emphasizes the need for a compelling vision of the organization’s future. A compelling vision guides transformation efforts and unites support.

Effective communication is needed to spread the change vision throughout the business and ensure that all stakeholders understand the reasons, objectives, and benefits of the proposed changes. Consistent communication reduces opposition and builds support.

Empower Broad-Based Action: Kotter encourages all employees to own and implement change. By incorporating many people in decision-making and problem-solving, organizations can tap into their employees’ intelligence and creativity.

Short-Term Wins: Celebrating early triumphs and generating real results keeps momentum and builds trust in the change endeavor. Kotter suggests identifying fast wins to show vision progress and change program effectiveness.

Consolidate successes and Produce More Change: Kotter stresses the necessity of consolidating initial successes and building on them. Reinforcing new behaviors, procedures, and structures and resolving lingering change resistance is required.

To sustain change, implant new behaviors and practices within the organization’s culture. Kotter recommends leaders institutionalize change by aligning systems, structures, and processes with intended objectives and values to ensure sustainability. Applying Kotter’s theory in healthcare settings has demonstrated the validity of these principles and their current practice. A recent compilation of Change Theories developed by Harrison and colleagues found that among the 38 studies that discussed applying 12 different change management approaches in healthcare settings among ten different nations, Kotter´s Model was the most frequently used with 19 studies (Harrison et al., 2021).
A methodical strategy for enhancing depression screening procedures in primary care settings is offered by Kotter’s theory of change. Healthcare companies can improve patient outcomes and well-being by implementing Kotter’s eight-step procedure to help staff members identify depression and deliver prompt interventions. The model was used in various healthcare scenarios in these studies, including emergency services, teaching for quality improvement in hospitals, rural healthcare services in the US and UK, frontline staff in surgical units, Canadian academic teaching hospitals, nurses providing palliative care, Australia, frontline staff in maternity wards, nurses providing acute inpatient mental health units, surgical orthopedic trauma units, cancer units, and so on (Harrison et al., 2021).

Synthesis of the Literature

A study published in 2022 by Blackstone et al. described a quality improvement program that was applied in five Family Medicine clinics to increase the rates of depression screening, which was especially pertinent during the COVID-19 pandemic. The Journal of Community Health released an article titled “Improving Depression Screening in Primary Care: A Quality Improvement Initiative,” which summarized the initiative’s findings. The program included distributing instructional materials, working with health information technology, standardizing workflows, and offering staff and clinicians follow-up training.
23,745 clinic encounters between September 2020 and April 2021 were analyzed, and the results showed that the percentage of patients who were up to date on depression screening had significantly increased, going from 61.03% to 82.33%. According to a multi-level logistic regression model, patients who were attending in-person appointments, had comorbidities, and were 65 years of age or older were more likely to be up to date on screening. Telemedicine visits, on the other hand, were linked to decreased probabilities. In addition to offering suggestions for future interventions, the study sheds light on a successful intervention that improved depression screening in a primary care context (Blackstone et al., 2022).
The Journal of the American Psychiatric Nurses Association published an article by Brown et al. (2020) titled “Enhancing PHQ-9 Utilization Rates in a Primary Care–Mental Health Integration Setting,” which summarizes the research findings. In order to enhance the use of the Patient Health Questionnaire-9 (PHQ-9) in a primary care-mental health integration (PC-MHI) environment, the study focuses on a quality improvement (QI) procedure. Baseline and follow-up PHQ-9 administration rates were 76% and 35%, respectively, prior to the intervention. In 2017, the QI program was put into action, involving motivational improvement sessions and educational initiatives. Provider utilization rates for PHQ-9 increased dramatically after the intervention, reaching 88% at follow-up and 98% at baseline.
The study highlights the potential for better patient care through systematic monitoring by showing that a brief educational intervention effectively boosts clinician utilization of Measurement-Based Care (MBC) within a PC-MHI scenario. The paper also emphasizes how critical it is to conduct additional research on the meaningful application of MBC to inform treatment choices (Brown et al., 2020).
“Barriers to Healthcare Access among U.S. Adults with Mental Health Challenges: A Population-based Study” was the title of the Coombs study. The purpose of this cross-sectional study was to measure the prevalence of barriers to healthcare access among individuals in the United States, with a particular focus on mental health problems (MHC). The study used data from the 2017–2018 National Health Interview Survey. 50,103 adults participated in the study by Coombs and colleagues, who divided the participants into three categories of psychological distress: none, moderate, and severe.
Even though most participants said they had faced at least one obstacle to receiving healthcare, the study found no significant correlation between severe psychological distress and not having a regular source of care (NUSC). Rather, NUSC was linked to variables like Hispanic ethnicity, male gender, and worries about the cost of healthcare. The study found that having dependents, a current partner, and access to paid sick leave were protective variables. The findings support more research into how social and environmental factors affect the degree of obstacles faced by people with mental health issues and emphasize the significance of addressing financial concerns to improve healthcare access (Coombs et al., 2021).
A systematic evaluation was carried out by Costantini and associates to assess the efficacy of the Patient Health Questionnaire 9 (PHQ-9) as a depression screening instrument in primary care settings. In 2021, their research was presented in a paper titled “Screening for depression in primary care with Patient Health Questionnaire-9 (PHQ-9): a systematic review.” 42 research publications from 1995 to 2018 were retrieved from different databases and examined for this review. Most of the research was cross-sectional (95%), concentrated on adult populations (90%), and was carried out in high-income nations (71%).
The PHQ-9’s accuracy was evaluated in 74% of the studies through a two-stage screening process that frequently including organized interviews with mental health and primary care providers. In most investigations, a cut-off score of 10 was recommended. PHQ-9 overall showed a range of values for specificity (0.42 to 0.99), positive predictive value (0.09 to 0.92), negative predictive value (0.8 to 1), and sensitivity (0.37 to 0.98). The review emphasizes the need for longitudinal research to determine the long-term efficacy of depression screening in primary care, even if it also emphasizes the PHQ-9’s widespread validation and recommendation in a two-stage screening approach (Costantini et al., 2021).
By utilizing the American Academy of Pediatrics (AAP) Guidelines for Adolescent Depression in Primary Care (GLAD-PC), Costello and colleagues conducted a descriptive and exploratory study with the goal of improving the identification and treatment of adolescent depression in a pediatric primary care setting. The Journal of Clinical Psychology in Medical Settings published their findings under the heading “Addressing Adolescent Depression in Primary Care: Building Capacity Through Psychologist and Pediatrician Partnership.” Between January 2017 and August 2018, 2,107 adolescents, ages 11 to 18, received depression screenings using the PHQ-9A, thanks to the collaboration of integrated psychologists, clinicians, and clinic personnel.
Results were published in 2019 and showed that 7% of adolescents tested positive for suicidal thoughts and 11% of adolescents had heightened screening (scoring ≥ 10). Increased use of integrated behavioral health services by psychologists, psychiatrists, and psychology trainees was brought about by the identification of depressed symptoms. The implementation’s success demonstrated the value of psychologists in helping primary care practitioners follow GLAD-PC principles and get past implementation roadblocks in practical situations. The importance of universal screening and response strategies for teenage depression in pediatric primary care is highlighted by this study (Costello et al., 2019).
A study titled “Psychological Treatment of Depression in Primary Care,” carried out in 2019 by Cuijpers and colleagues, provides information on the most recent developments in psychological therapies for depression in basic care settings. The study presents a number of important findings, such as the efficiency of using e-health applications to deliver psychotherapies, the successful use of lay health counselors in low- and middle-income nations, and the similar effectiveness of behavioral activation and cognitive behavior therapy.
In addition, managing subthreshold depression not only mitigates symptoms but also acts as a deterrent to the development of major depression. Psychological therapy are effective for a wide range of populations, such as the elderly, those with general medical issues, and pregnant women who are depressed. All things considered, psychological therapies used in primary care are more patient-preferred, have longer-lasting effects than pharmaceutical interventions, and may be applied in a variety of ways to different target groups and formats. The study’s findings were released in 2019 by Cuijpers et al. in the Journal Current Psychiatry Reports.
According to a report in The Lancet Psychiatry, the same researcher oversaw a study titled “Treatment Outcomes for Depression: Challenges and Opportunities.” The wide-ranging effects of depressive disorders on quality of life are highlighted by this study, underscoring the urgent need for efficient treatments. Even though antidepressant drugs and psychotherapies are examples of current interventions that have proven effective, there are still areas that might use better and some noticeable limits. The paper outlines ten important data that shed light on these limitations, one of which is the noteworthy finding that a considerable number of patients—especially children and adolescents—show improvement in the absence of official treatment.
The effectiveness of treatments is still unknown despite a large number of randomized trials because of biases, low statistical power, and a variety of outcome measures. The results of the study highlight knowledge gaps on the fundamental causes of depression, the limits of its diagnosis, and the intrinsic variability of the illness. In order to address these issues and encourage the creation of novel methods and treatments for depression in the upcoming ten years, the paper presents the Wellcome Trust’s innovative mental health program strategy as a possible solution (Cuijpers et al., 2020).
In 2020, Davis and associates carried out research with the goal of using depression screening to determine the risk of teenage suicide. The results of this study, titled “Identifying Adolescent Suicide Risk via Depression Screening in Pediatric Primary Care: An Electronic Health Record Review,” were published in the Journal Psychiatric Services. Retrospective data from electronic health records was used in this study. The researchers looked at the suicide risk rates found using a depression screener that was used in a sizable pediatric primary care system. They also examined the one-year follow-up care that was given to teenagers who expressed a risk of suicide.
To determine suicide risk rates based on items affirmed on the Patient Health Questionnaire-Modified for Teens (PHQ-9-M), retrospective electronic health record data were collected. The evaluation covered teenagers between the ages of 12 and 18 between September 1, 2014, and August 31, 2016. After a manual review of the charts, the charts were coded to record different follow-up care actions in the year that followed the suicidality endorsement. These actions included referrals to mental health practitioners and the distribution of information about crisis lines.
In a sample of 12,690 teenagers, 5.1% admitted to having thoughts of suicide or self-harm, 3.6% said they had attempted suicide at least once in their lives, and 2.4% said they had had significant suicidal thoughts in the previous month. A manual record review was conducted on a stratified random subsample of 150 out of the 643 teenagers who reported having had a lifetime attempt at suicide, current serious thoughts, or both, in order to evaluate the sorts of follow-up care they had received. High fidelity was shown by the PCPs (primary care physicians) in following the suicide evaluation questions provided by the system. Nonetheless, there was greater variation in the follow-up care provided by PCPs and other healthcare professionals in the year that followed the suicide risk recommendation.
These results highlight how easily suicide assessment processes can be included into pediatric primary care depression screening processes. Additionally, they stress how crucial it is to give adolescents who have been recognized as having an elevated risk of suicide as many options for preventive care as possible (Davis et al., 2020).
In a study published in 2021, Davis and colleagues investigated sociodemographic differences in the frequency of increased depression and suicide risk, as well as adolescent depression screening rates, in a sizable pediatric primary care network in the United States. The study’s conclusions, titled “Adolescent Depression Screening in Primary Care: Who is Screened and who is at Risk?” were published in the Journal of Affective Disorders. The network expanded its standard methodology for universal depression screening to include well-visits for all adolescents 12 years of age and older.
The data showed an 81.48% screening rate, with higher screening probabilities seen in female teenagers, those who were 12–14 years old on their first well-visit, White people, Hispanic/Latino people, and people with public insurance. A significant proportion of teenagers (5.92%) met the criteria for depression symptoms, and 7.19% said they had considered suicide. Risk differences were seen for a number of sociodemographic characteristics, highlighting the need for more equal screening procedures to address these differences (Davis et al., 2021).
In order to examine patterns of stability and change in the risk of adolescent depression and suicide identified through universal depression screening in pediatric primary care, Davis and colleagues conducted a study titled “Emerging Risk of Adolescent Depression and Suicide Detected Through Pediatric Primary Care Screening.” They also sought to identify factors associated with emerging risk.
Retrospective data from electronic health records was gathered, comprising sociodemographic information and depression screening results at two intervals, for adolescents aged 12 to 17 who received well-visits in a large pediatric primary care network between November 15, 2017, and February 1, 2020. The study included 27,335 teenagers in total who completed depression screening twice.
Some adolescents experienced emerging risk (i.e., low risk initially but elevated risk later), decreasing risk (i.e., high risk initially but low risk later), or consistently high risk for depression or suicide, even though the majority of adolescents maintained low-risk levels for depression and suicide throughout both time points. Adolescents with Medicaid insurance had a higher chance of suffering developing depression and a higher risk of suicide than adolescents with private insurance, as well as a higher likelihood of experiencing these conditions among Black adolescents compared to White adolescents. Furthermore, compared to their younger and non-Hispanic/Latino counterparts, older adolescents and those who identified as Hispanic/Latino were more likely to exhibit emerging depression risk. These results shed light on how to keep an eye on symptoms and spot possibilities for prevention in primary care settings (Davis et al., 2024).
At an academic medical center, Ayvaci and colleagues compared the treatment of teenage depression in pediatric and psychiatric settings. The results, titled “Treatment of Adolescent Depression: Comparison of Psychiatric and Pediatric Settings at an Academic Medical Center Using the VitalSign6 Application,” were published in the Journal of Child and Adolescent in 2024. The purpose of the study was to close the knowledge gap regarding the management of pediatric depression in various healthcare settings.
Little is known regarding the management of pediatric depression in primary and psychiatric care settings, despite the fact that treatment outcomes and remission rates for depression in adults have been thoroughly investigated in both settings. Thus, the purpose of this study was to compare pediatric and psychiatric depression treatment modalities. It was hypothesized that patients with milder depression would receive more frequent treatment in pediatric settings and use medication less frequently.
Between May 2017 and May 2022, 3498 patients at a children’s hospital were screened for depression using the VitalSign6 initiative, a web-based tool for managing depression. The two-item Patient Health Questionnaire (PHQ) was used for screening, and patients who scored ≥10 on the baseline nine-item PHQ (PHQ-9) were included in the analysis. Measures reported by patients as well as diagnosis and treatment decisions made by providers were included in the data for each clinic visit.
Of the 1323 patients who tested positive for depression, PHQ-9 ratings were considerably higher in psychiatric settings (15.9 ± 5.0 vs. 12.1 ± 5.5; p < 0.0001) than in pediatric settings. In comparison to pediatric settings, patients with PHQ-9 scores ≥10 in psychiatric facilities had a higher likelihood of receiving medication (54.8% vs. 6.6%) and receiving a major depressive disorder diagnosis (60.6% vs. 24.7%, p < 0.0001). On the other hand, patients in pediatric settings were more likely to obtain an outside referral (27.7% vs. 5.7%) or nonpharmacological treatment alone (36.3% vs. 4.3%). There was no discernible difference in remission rates between the two environments. According to the study's findings, children and adolescents in psychiatric facilities are more likely than those in pediatric settings to screen positive for depression and to have a more severe form of the illness. Treatment suggestions for moderate-to-severe depression are provided in both settings, however the specific forms of care differ significantly. However, remission rates don't change much. To completely comprehend the subtleties of therapy variations and their ramifications, more investigation is required (Ayvaci, et al., 2024). Adolescent depression screening and early management are advised, however they can be difficult to execute. at order to increase the number of adolescents who are screened for depression during preventive care visits at twelve primary care clinics, Beck and colleagues carried out a project. The objective was to continue these gains for a full year by raising screening rates from 65.4% to 80% and increasing the percentage of documented initial care for positive screens from 69.5% to 85%. The study, "Improving Primary Care Adolescent Depression Screening and Initial Management: A Quality Improvement Study," which was published in "Pediatric Quality & Safety," focused on adolescents aged 12 to 17 and involved 12 urban primary care clinics that served over 120,000 patients, the majority of whom were enrolled in Medicaid. Standardized depression screening with tablets that were integrated with automated scoring and electronic health record (EHR) recording were among the interventions. Other strategies included provider education, performance evaluation for individual clinicians and clinics, and the integration of screening results and first management actions into the EHR. The average rate of depression screening increased to 91.9% after the screening methodology was standardized. However, the percentage of properly documented initial management plans dropped from 89.7% to 67.6% once tablets were introduced into the clinic workflow. In response to this unanticipated variation, the EHR flow was redesigned with regard to result presentation and action prompts after a positive screen, in addition to enhanced provider feedback and education. As a result, by the time the project was finished, 87.3% of the initial management had been properly recorded. The use of EHR scoring capture during screening resulted in a considerable increase in the number of depression screenings; however, it also required extra work to improve post-positive screening treatment. Meaningful and long-lasting gains in comprehensive adolescent depression screening required a comprehensive system strategy that included EHR upgrades, clinical education, and performance evaluation (Beck et al., 2022). Global disability-adjusted life years (DALYs) are greatly impacted by major depression, especially in resource-constrained areas where illness often coexists with socioeconomic problems. Therefore, developing depression screening tools for primary healthcare settings is absolutely necessary. Verifying the PHQ-9 in Tanzania was the main goal of the research done in 2019 by Fawzi et al. The validation study involved persons accessing primary healthcare services at public clinics in Dar es Salaam between August and October of 2014. identifying current major depressive episodes by applying the Mini-International Neuropsychiatric Interview (MINI) as the reference standard. Results from the examination of 174 individuals (six of whom were excluded) showed that the PHQ-9 had acceptable reliability in this situation (α=0.83). Associations with female gender (r=0.16, p=0.04) and food insecurity (r=0.30, p<0.0001) confirmed the construct validity. The most relevant findings from this study were published in 2019 under the heading "Validating the Patient Health Questionnaire-9 (PHQ-9) for Screening of Depression in Tanzania" in the Journal of Neurology, Psychiatry, and Brain Research. The PHQ-9's overall accuracy was shown to be commendable by the Receiver Operating Characteristic analysis (AUC=0.87, 95% CI: 0.77, 0.96). It was shown that 9 was the ideal cut-off score for this population, with a sensitivity of 78% and a specificity of 87%. It is imperative to recognize the limits of this study, especially with respect to the study sample that was drawn from a primary healthcare environment, since this could potentially limit the study's applicability to a larger community. In conclusion, among people in Dar es Salaam seeking basic healthcare, the PHQ-9 showed validity and reliability. These results point to its effectiveness as a useful tool for diagnosing depression in Tanzanian primary care clinics and comparable settings (Fawzi, et al., 2019). Depression is a prevalent and complex illness that frequently presents as a recurrent and chronic condition in primary care settings. Primary care physicians have a crucial role in managing depression in conjunction with medical comorbidities; yet, they encounter challenges in the areas of diagnosis and therapy. Our goal is to assist primary care clinicians in properly diagnosing and treating depression in a two-part series. The focus of this review, "Depression in Primary Care: Part 1—screening and Diagnosis," is on how depression is identified and treated in basic care settings. This means evaluating currently available evidence-based guidelines and applying their suggestions to clinical practice. The review that follows explores an evidence-based approach to primary care depression treatment that includes suggested lifestyle changes, medication interventions, and individual psychological therapies. Moreover, Ferenchick et al. (2019) emphasize the importance of organizational-level interventions in enhancing the effective management of depression in primary care settings. In 2020, Ford and his research team published their findings in the journal Qualitative Health Research regarding the use of the Patient Health Questionnaire (PHQ-9) in clinical practice. The nine-item PHQ-9 is a widely used measure for diagnosing and grading depression severity. The study, "Use of the Patient Health Questionnaire (PHQ-9) in Practice: Interactions between patients and physicians," looked at how healthcare professionals use it. The authors used conversation analysis to show how a doctor uses the PHQ-9 in response to a patient who is unsure about whether they are depressed. The doctor goes off script and gives a few response alternatives that emphasize how serious the patient's symptoms are, rather than delivering the PHQ-9 questions straight. This tactical deviance validates a diagnosis that is positive and supports a recommended course of treatment that the patient had previously refused. This is different from other cases in the dataset where a diagnosis was made without using the PHQ-9 or no diagnosis was made because of persistent problems. According to the study, the manner in which doctors administer the PHQ-9 items may have an impact on the results, possibly resulting in an overestimation or underestimation of the severity of depression (Ford et al., 2020). Depression, a debilitating medical condition often overlooked in certain demographic groups such as men, racial and ethnic minorities, older adults, and those with language barriers, poses significant health risks. Disparities in depression screening may contribute to inadequate treatment. Garcia and colleagues conducted a cohort study from September 1, 2017, to December 31, 2019, analyzing electronic health records of 52,944 adult patients across six University of California, San Francisco, primary care facilities to evaluate depression screening rates after implementing a universal screening policy. Their findings were published in JAMA Network Open under the title “Equitability of depression screening after implementation of general adult screening in primary care.” The study excluded patients with pre-existing diagnoses of depression, bipolar disorder, schizophrenia, schizoaffective disorder, or dementia. Depression screening, conducted by medical assistants using the Patient Health Questionnaire-2, was assessed across different screening years: the rollout period (September 1, 2017, to December 31, 2017), and subsequent calendar years (January 1 to December 31, 2018, and January 1 to December 31, 2019). Results indicated a notable increase in depression screening from 40.5% at rollout in 2017 to 88.8% in 2019. In 2018, screening rates decreased with age, and patients with limited English proficiency were less likely to be screened compared to English-speaking White patients. However, by 2019, depression screening rates had significantly improved for all at-risk groups, with most disparities eliminated. Nevertheless, men continued to have significantly lower screening odds than women. Conclusively, the study suggests that the comprehensive implementation of depression screening in a large academic health system led to a significant rise in screening rates among demographic groups at risk for depression undertreatment. Furthermore, over time, depression screening disparities diminished, indicating that routine screening in primary care settings may reduce disparities and improve the identification and treatment of depression across diverse patient populations (Garcia, et al., 2022). The cross-cultural measurement invariance (MI) of the PHQ-9, the self-reported tool for depression screening in measurement-based care (MBC), has been explored in a regional cohort of American Indian/Alaska Native (AI/AN) and non-Hispanic White adults. However, for comprehensive health equity, it is imperative to investigate the cross-cultural MI of the PHQ-9 across various AI/AN groups and diverse populations. In this investigation, titled “Assessing the differential item functioning of PHQ-9 items for diverse racial and ethnic adults with mental health and/or substance use disorder diagnoses: A retrospective cohort study,” the MI of both the one-factor PHQ-9 model and five previously identified two-factor models was evaluated among non-Hispanic AI/AN adults (ages 18-64) from healthcare systems A (n=1,759) and B (n=2,701) using secondary data and robust maximum likelihood estimation. Subsequently, fully or partially invariant models for MI were tested between combined or separate AI/AN groups and Hispanic (n=7,974), White (n=7,974), Asian (n=6,988), Black (n=6,213), and Native Hawaiian/Pacific Islander (n=1,370) adults from healthcare system B. All individuals had diagnoses of mental health or substance use disorders and received care in behavioral health or primary care settings from 1/1/2009 to 9/30/2017. Findings revealed that the one-factor PHQ-9 model exhibited partial invariance, with two-factor models displaying partial or full invariance among AI/AN groups. Furthermore, the one-factor model and three two-factor models demonstrated partial invariance between all seven groups. In contrast, one two-factor model was fully invariant, and another was partially invariant between a combined AI/AN group and other racial and ethnic groups. In conclusion, achieving health equity in MBC necessitates ensuring the cross-cultural validity of measurement tools. Before comparing mean scores, it is crucial to assess the fit of PHQ-9 models for individual racial and ethnic groups among adults with mental health or substance use disorders. (Harry, et al., 2021). The same researcher, Harry, undertook another study aiming to address health equity in depression care and suicide screening, highlighting the importance of uniform measurement tools such as the Patient Health Questionnaire 9 (PHQ-9) across diverse racial and ethnic groups. A retrospective cohort study utilized secondary electronic health record (EHR) data from eight healthcare systems to assess PHQ-9 differential item functioning (DIF) among various racial/ethnic groups. This study was entitled “Assessing the differential item functioning of PHQ-9 items for diverse racial and ethnic adults with mental health and/or substance use disorder diagnoses: A retrospective cohort study” and published in the Journal of Affective Disorders. The study population, as conducted by Harry et al. in 2023, included 755,156 patients aged 18–64 with diagnoses of mental health and/or substance use disorders (SUD), who had a complete PHQ-9 during primary care or mental health visits from 1/1/2009 to 9/30/2017. Two random samples of 1000 individuals were selected from recorded racial/ethnic groups, such as Hispanic, non-Hispanic White, Black, Asian, American Indian/Alaska Native, Native Hawaiian/Other Pacific Islander, and multiracial. DIF was assessed using iterative hybrid ordinal logistic regression and item response theory, with a significance level of p < 0.01 and 1000 Monte Carlo simulations, where a change in model R2 > 0.01 indicated clinically meaningful DIF.
Results showed statistically significant but clinically negligible DIF for all PHQ-9 items across compared groups. Although the negligible DIF varied across random samples, six items consistently displayed negligible DIF between the same comparison groups in both samples. Limitations include potential issues with generalizability to disaggregated racial/ethnic groups or individuals without mental health and/or SUD diagnoses. In conclusion, the study revealed that the PHQ-9 demonstrated clinically negligible cross-cultural DIF among adult patients with mental health and/or SUD diagnoses. Further research is recommended to disaggregate race/ethnicity and investigate whether within-group identification influences PHQ-9 DIF. (Harry, et al., 2023).
An essential article by Jha and colleagues provides insights into the ongoing quality improvement initiative, the VitalSign6 project, conducted by this research team in a large metropolitan area in the United States. The project aims to improve the identification, treatment, and outcomes of patients with depression across 16 primary care clinics, including 6 charity clinics, 6 federally qualified health centers, and four private clinics catering to low-income populations or patients with Medicare or private insurance.
The most significant findings from this project were published in an article titled “A Structured Approach to Detecting and Treating Depression in Primary Care: The VitalSign6 Project” in 2019. This retrospective analysis focuses on the initial 25,000 patients aged 12 years and above who underwent screening with the 2-item Patient Health Questionnaire (PHQ-2) as part of the VitalSign6 project. Patients with positive screens (PHQ-2 > 2) underwent further evaluations, including self-reports and clinician assessments. Data spanning from August 2014 to November 2016 were analyzed at three levels: initial PHQ-2 screening (n = 25,000), positive screens (n = 4,325), and clinician-diagnosed depressive disorder with 18 or more weeks of enrollment (n = 2,160).
The results revealed that 17.3% (4,325/25,000) of patients screened positive for depression. Among those with positive screens, 56.1% (2,426/4,325) received a clinician-diagnosed depressive disorder. For patients enrolled for 18 or more weeks, 64.8% initiated measurement-based pharmacotherapy, and 8.9% were referred externally. Among the 1,400 patients starting pharmacotherapy, the distribution of follow-up visits was as follows: 45.5%, 30.2%, 12.6%, and 11.6% for 0, 1, 2, and 3 or more follow-up visits, respectively. Remission rates were 20.3%, 31.6%, and 41.7% for those with 1, 2, and 3 or more follow-up visits, respectively. Higher attrition was associated with non-white ethnicity, positive drug-abuse screen, lower depression/anxiety symptom severity, and younger age.
Despite the notably high remission rates observed with three or more follow-up visits after routine screening and depression treatment, attrition from care remains a significant challenge affecting overall outcomes (Jha, et al., 2019).
In 2019, Levis and colleagues conducted a study to evaluate the effectiveness of the Patient Health Questionnaire-9 (PHQ-9) as a screening tool for detecting major depression. The findings of this meta-analysis were published in BMJ under the title “Accuracy of Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression: individual participant data meta-analysis.”
This study aimed to examine the accuracy of the PHQ-9 in identifying major depression. An individual participant data meta-analysis was conducted, utilizing data from various sources including Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, and Web of Science, spanning from January 2000 to February 2015. Eligible studies were those that compared PHQ-9 scores with major depression diagnoses obtained from validated diagnostic interviews. Both primary study data and study-level data were synthesized, and a bivariate random-effects meta-analysis was utilized for PHQ-9 cut-off scores ranging from 5 to 15.
The analysis was stratified based on the type of diagnostic interviews used, including semi-structured interviews for clinicians, fully structured interviews for lay administration, and the Mini International Neuropsychiatric (MINI) diagnostic interviews. Sensitivity and specificity were examined across different cut-off scores and participant subgroups.
Data from 58 out of 72 eligible studies (total participants n=17,357; major depression cases n=2312) were included in the analysis.
The optimal cut-off score for maximizing combined sensitivity and specificity was determined to be 10 or above, particularly among studies using semi-structured interviews. Sensitivity was found to be higher with semi-structured interviews compared to fully structured interviews and the MINI across cut-off scores ranging from 5 to 15. However, specificity remained consistent across different types of diagnostic interviews. Additionally, the study suggested that the PHQ-9 may be more sensitive but potentially less specific for younger patients compared to older patients.
All things considered, the PHQ-9 proved to be more sensitive than earlier traditional meta-analyses, particularly when semi-structured diagnostic interviews were employed as benchmarks. According to Levis et al. (2019), a cut-off score of 10 or above was found to be the best for maximizing combined sensitivity and specificity, demonstrating its dependability for major depression screening across a range of subgroups.
Quality improvement (QI) in healthcare refers to continuous efforts made by staff members and organizations to improve patient outcomes, care quality, and operational procedures. In the summer of 2017, the clinical director and head of nursing of a health board in Wales gave their approval and support to a quality improvement (QI) effort.
The QI program is being implemented in one of the three community mental health services run by the health board, according to 2020 research by Davies. A QI champion was recruited to foster QI skills and competencies among staff members throughout the clinical teams of the local mental health service, and a QI board was formed to oversee and support the process. Among the noteworthy advancements made by the QI champions throughout the first twelve months of the program were improved readmission rates, more accurate electronic transfers of care, cooperative construction of ward-based staff engagement guides, and the production of digital staff stories.
The authors also discuss the difficulties that arose when the QI program was first introduced and provide suggestions for organizations and senior nurses who want to successfully implement these kinds of programs (Davies, et al., 2020).
Determining research gaps in particular health domains is the goal of research priority setting. Given the widespread effects of mental disease and the paucity of financing for research on mental health compared to other health-related areas, knowledge of scientific techniques might improve the quality of prioritization in order to identify relevant and influential studies. Priority setting methodologies utilized in specifically mental health research focused initiatives have not yet been thoroughly reviewed, despite being essential knowledge for filling research gaps. To help guide future prioritization initiatives, this article offers an overview of approaches, plans, and current frameworks that might be used for determining the priority of mental health research.
Using a critical interpretative synthesis, Deering and his team of collaborators performed a systematic search of electronic databases to find prioritization-related literature. Based on the good practice checklist for priority setting developed by Viergever and colleagues, this synthesis incorporated the evaluation of methodological approaches into the findings.
The checklist covered topics like (1) Comprehensive Approach—frameworks/designs that direct the entire process of setting priorities; (2) Inclusiveness—participation techniques that guarantee equal stakeholder contribution; (3) Information Gathering—data collection techniques to identify research gaps; and (4) Deciding Priorities—prioritization procedures.
After 903 papers were found, 889 of them were disregarded for being duplicates or failing to meet the inclusion/exclusion requirements. There were fourteen articles with thirteen different priority setting projects described. The most common technique was to involve participants, however the prioritizing frameworks that were already in place were frequently altered with little to no justification for the changes, adaptation procedures, or theoretical underpinnings.
Patients were involved in some processes, although researchers led them most of the time. Information was typically gathered using surveys and consensus-building techniques, and priorities were determined using thematic analysis and ranking systems. However, there was little evidence to support the translation of priorities into real research projects, and there were few implementation strategies offered to help translate research into user-informed design.
Prioritization initiatives could benefit from elucidating the rationale behind certain methodologies, defending methodological choices for finding mental health research, and providing justification for framework adaptations. Finalized priorities should also be expressed in a form that makes it easy for research projects to include them. [Deering and others, 2023].
Ferris-Day carried out a comprehensive investigation into the obstacles and enablers related to obtaining mental health services in a remote area. The {International Journal of Mental Health Nursing¨ published the results in 2021.
The investigation was centered on the challenges and variables that impact mental health assessment and engagement in a rural setting. The aim of this study was to compile and summarize the literature pertaining to adult experiences of seeking or attempting to seek mental health treatment in rural locations.
Using CINAHL, PsycINFO, Web of Science Core Collection, PubMed, Psychology and Behavioral Sciences Collection, Google Scholar, and Scopus, a comprehensive search covering the years 2010 to 2020 was conducted. From the initial selection of 573 papers, 32 relevant papers were found using PRISMA methods.
After applying Braun and Clarke’s (Qualitative Research in Psychology, 3:77–101, 2006) thematic analysis methodology to the data, two themes emerged: the first theme focused on help-seeking and included subthemes related to stigma and the availability of health services. The second topic, which encompassed subthemes including personal identity and support networks, was connectivity.
The review brought attention to gender-related viewpoints on mental health support access, highlighting the need for more investigation into the diverse social networks and support systems found in rural areas. The results emphasize how crucial it is to investigate the barriers that lower the possibility of receiving mental health services in rural locations. Ferris-Day and associates, 2021).
The routine use of symptom rating scales to guide treatment decisions is known as measurement-based care (MBC), although it is still a little-used tactic to improve patient care. A major barrier to the generalization of MBC is the absence of comprehensive foundational training. Freedman et al.’s scoping study from 2023 aims to review the research on MBC-focused educational programs for mental health professionals.
Up until June 2021, researchers searched Ovid Medline, PsycINFO, Embase, Cochrane Central, and Ebsco CINAHL for records that described studies pertaining to MBC educational programs for learners at the undergraduate, graduate, or postgraduate levels in mental health.
1263 of the 1270 unique items were disqualified after full-text and abstract/title screening. Seven articles in all, the majority of which were empirical case studies done in the United States, were included in this scoping review.
The identified curriculum covered a range of delivery modes, such as lectures and on-the-job training. Both learner-focused (such as learner reaction or attitudinal/behavioral change) and organizational-focused (such as greater clinical use of MBC) components were included in the measured learner outcomes. Improved stakeholder support and continuous curriculum improvement are two of the suggested approaches that provide favorable results.
MBC courses can be offered in a variety of ways to accommodate a broad spectrum of mental health education students. By encouraging stakeholder support and ongoing program improvement, contextual factors like committed resources, MBC champions, supervisor training, online measurement feedback systems, the use of simple measures, and the gathering and sharing of feedback can support the success of curricula.
Future studies on MBC education should investigate the use of quality improvement techniques in the implementation of MBC education, as well as the integration of educational frameworks in curriculum design, in order to fill in the gaps in the literature. Freedman and colleagues (2023).
Measurement-based care (MBC) is a mental health treatment technique that uses symptom rating scales on a regular basis to inform decisions. It has demonstrated efficacy, viability, and widespread acceptance, resulting in enhanced treatment outcomes in various fields including psychology, social work, medicine, and psychotherapy. Clinicians frequently underuse MBC despite its possible advantages; this could be because they haven’t had enough training in this field. To better understand the features of MBC-focused teaching programs for clinical trainees at the undergraduate, graduate, and postgraduate levels of mental healthcare, Freedman and colleagues have conducted a scoping review.
We will find pertinent research by using specific search tactics for databases such as Medline, PsycINFO, Embase, CINAHL, and Cochrane Central. The information about the delivery of educational programs, the clinical and educational results connected to these programs, and the possible facilitators and barriers to MBC education will then be extracted from the chosen studies through analysis. The procedure for carrying out this scoping review is described in this document (Freedman et al., 2021).
Garcia studied the equity of screening for depression following the introduction of adult screening for general conditions in primary care. The introduction of routine primary care depression screening was the topic of discussion, as it was linked to higher screening rates for populations at risk of receiving insufficient depression therapy.
A general screening policy was implemented, and as a result, depression screening rates increased significantly from 40.5% in 2017 to 88.8% in 2019 in this cohort study of 52,944 adult patients in primary care practices within a California health system. Notably, by 2019 screening discrepancies for men continued, but not for older patients, Black/African American and other English-speaking patients, or those with language problems.
The findings indicate that the introduction of depression screening could potentially improve the detection and effective management of depression in all patient populations while also potentially reducing screening inequities.
The debilitating disorder known as depression, which is typically left untreated, is more common in older adults, men, members of racial and ethnic minorities, and people who are dyslexic. Differences in screening could be a factor in undertreatment.
This cohort study examined depression screening rates in a California health system following the implementation of a general screening strategy. It ran from September 1, 2017, to December 31, 2019. Indicating that routine depression screening in primary care could potentially mitigate screening disparities and improve the recognition and appropriate treatment of depression for all patients, the study found a significant increase in screening rates among at-risk groups, with disparities narrowing over time. Garcia and colleagues (2022).
Jackson et al. reported the findings of their study, “The Importance of Screening for Depression in Primary Care,” in the Journal of General Internal Medicine.
In 2016, the USPSTF updated its guidelines for depression screening in primary care, encouraging universal screening instead of screening only when a systematic depression management approach was available.
Depression is common in primary care, affecting up to 10% of patients with significant depression and about 25% of patients with moderate (subclinical) depression. Before this suggestion, only around half of patients with serious depression were identified as such by their primary care providers throughout a 5-year follow-up period, despite the movement toward universal screening.
Only 3% of patients at initial primary care visits completed depression screening, according to a study by Samples and colleagues, which is consistent with rates seen in other studies, despite expectations of improvement following the universal screening suggestion. The authors additionally noted that throughout their visits, approximately twice as many diagnoses of depression were made by clinicians with greater screening rates.
Given the substantial effects of depression on patients and their families, and the fact that primary care is the main source for diagnosis and treatment, the low screening rate is depressing. There are a number of barriers to depression screening, such as discomfort on the part of the provider, a lack of structured approaches to management, and, most significantly, the way that depressed patients arrive in primary care. Patients frequently have somatic symptoms in place of overt depressed symptoms, which obscures the sad state.
During their first visit, patients with depression frequently describe a variety of physical symptoms. While it is important to rule out other medical issues, depression should be taken into consideration if no other diagnosis is made.
Clinical signs that may indicate depression at the first visit include stress, a greater frequency of severe physical symptoms, and a notable functional impairment. When all four of these signs are present in a patient, approximately 60% of the time depression is the underlying cause of the symptoms. Although the authors rely on these clinical cues and diagnostic suspicions, they support annual universal screening in primary care offices and suggest the PHQ2 as a useful screening instrument.
The VA has implemented this two-question test, which is well-known for its validity and reliability. In comparison to standard treatment, the rate of depression diagnoses increased by more than double when universal screening was implemented. Utilized in positive PHQ-2 screens, the PHQ-9 provides an objective assessment of the intensity of depression symptoms, supporting the evaluation of treatment options.
In summary, existing primary care approaches of detecting depression mainly rely on individual provider clinical judgment, despite the recognized incidence and effect of the condition. To enhance care for the millions of patients who live with depression, the authors argue for a reevaluation of primary care screening methods for depression and a move toward comprehensive screening tools like the PHQ2. [Jackson and others, 2019].
Most adults in the US who suffer from Major Depressive Disorder (MDD) are treated by primary care physicians (PCPs). Thus, in order to support the rehabilitation of patients with MDD, PCPs must be adept at implementing patient-centered care strategies. In particular, persistent MDD symptoms and unwanted antidepressant side effects are two common obstacles to recovery that PCPs must be able to identify and manage.
Two knowledgeable faculty members go into detail in these articles about how time-constrained PCPs can improve MDD care by implementing measurement-based care, shared decision-making, identifying and managing residual MDD symptoms, managing the side effects of antidepressants, and carefully moving patients to new antidepressants when needed. Two patient cases that provide insights into evidence-based strategies for typical clinical circumstances are discussed. Jackson (2021).
Finding the best depression screening instruments could improve the health of mothers and babies in maternal health clinics. In terms of epidemiologic connections and diagnostic performance, we performed a comparative analysis of four instruments. This research was a component of a cluster-randomized trial conducted in Kenya with women from 20 maternal health clinics who were assessed using the Center for Epidemiologic Studies six weeks after giving birth. Depression Measures for moderate-to-severe depressive symptoms (MSD) include the Edinburgh Postnatal Depression Scale (EPDS), the Patient Health Questionnaire-9 and -2 (PHQ-9, PHQ-2) [CESD-10 > 10, EPDS ≥ 13, PHQ-9 ≥ 10, or PHQ-2 ≥ 3]. Using the PHQ-9 scoring system, the authors calculated the area under the curve (AUC) for each scale (CESD-10, EPDS) in relation to probable major depressive disorder (MDD). We compared the relationships between MSD and intimate partner violence (IPV) on different scales.
The prevalence of MSD symptoms varied by tool among 3605 women, with a median age of 24 and 10% reporting IPV: 13% CESD-10, 9% EPDS, 5% PHQ-2, and 3% PHQ-9. When compared to probable MDD, the AUC of the CESD-10 was greater (0.82) than that of the EPDS (0.75). Using all of the following scales, IPV was linked to MSD: CESD-10 (RR: 1.9, 95%CI: 1.2–2.9), PHQ-2 (RR: 2.3, 95%CI: 1.6–3.4), EPDS (RR: 2.5, 95%CI: 1.7–3.7), and PHQ-9 (RR: 1.8, 95%CI: 0.8–3.8).
A preliminary diagnosis of likely MDD categorized by the PHQ-9 algorithm was utilized as a reference standard for diagnostic performance evaluations in the study, rather than a clinical diagnosis of MDD by a trained physician. The ability of depression screening instruments to identify postpartum mood disorders varied. The PHQ-2 showed a substantial epidemiologic connection with a cofactor, but it also resulted in fewer referrals. (Et al., Larsen, 2023).
The findings of a study titled “Accuracy of the PHQ-2 Alone and in Combination With the PHQ-9 for Screening to Detect Major Depression: Systematic Review and Meta-analysis” were released by Levis et al. in 2020. What is the accuracy of screening for depression with the Patient Health Questionnaire (PHQ)-2 alone and in conjunction with the PHQ-9? was the study’s main goal.
In a meta-analysis that used semi-structured diagnostic interviews and individual participant data from 44 studies (a total of 10,627 participants), the combination of PHQ-2 (cutoff ≥2) and PHQ-9 (cutoff ≥10) showed an area under the receiver operating characteristic curve of 0.90, a specificity of 0.87, and a sensitivity of 0.82. Employing PHQ-2 and then PHQ-9 could provide reasonable precision in diagnosing depression.
The depression module of the Patient Health Questionnaire (PHQ-9) is frequently used to identify and grade the degree of depression. The initial step in identifying people for a thorough evaluation using the entire PHQ-9 is to administer the Patient Health Questionnaire–2 (PHQ–2), which consists of the first two items of the PHQ-9. The purpose of this study was to evaluate the efficacy of PHQ-2 both by itself and in conjunction with PHQ-9 for the detection of serious depression.
From January 2000 to May 2018, information was gathered from MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, PsycINFO, and Web of Science. PHQ-2 scores and major depression diagnoses obtained through verified diagnostic interviews were compared in eligible datasets.
A total of 44,318 participants were in 100 of the 136 studies that qualified, and their individual participant data was included. Comparing PHQ-9 cutoff scores of 10 or higher alone to PHQ-2 (cutoff ≥2) and PHQ-9 (cutoff ≥10) together showed similar sensitivity but higher specificity. It was projected that by using this combination strategy, 57% fewer participants would need to complete the entire PHQ-9.
This individual participant data meta-analysis suggests that the combination of PHQ-2 followed by PHQ-9 could enhance specificity while maintaining sensitivity in comparison to using PHQ-9 alone. Further research is warranted to ascertain the clinical and research significance of this combined screening approach (Levis et al., 2020).
A screening program was put into place with the aim of determining the frequency of depressed characteristics and identifying potential risk factors in adult patients receiving primary healthcare (PHC).
A thorough cross-sectional investigation was conducted at a South African clinic in Pretoria. A self-administered questionnaire containing the Patient Health Questionnaire-9 (PHQ-9) screening instrument was completed by clinic patients. A positive test for depressed characteristics was indicated by a PHQ-9 score of five or higher, whereas a score below five indicated a negative screen. A multivariate logistic regression model was utilized to identify the characteristics linked to a positive screen for depressed symptoms.
Using the PHQ-9 instrument, 46.23% (n = 92) of the 199 patients who took part screened positive for depressed characteristics. The odds of screening positive were significantly lower for participants who were employed (odds ratio [OR] = 0.48; 95% confidence interval [CI]: 0.25 – 0.94) compared to those who had co-morbidities (OR = 2.12; 95% CI: 1.08 – 4.17) and a history of stressful life events (OR = 3.21; 95% CI: 1.64 – 6.28), who showed significantly higher odds.
According to the study, depression is quite common in PHC settings in South Africa. Primary level targeted screening that concentrates on people with known risk factors, recent exposure to stressful life events, and chronic medical illnesses may increase detection rates, allowing for an earlier diagnosis and ultimately better health outcomes. (Et al., Mashaba, 2021).
Pediatric rheumatologists frequently neglect to regularly evaluate patients with childhood-onset systemic lupus erythematosus (c-SLE) for depressive symptoms, despite the increased risk of depression among this population. In an academic pediatric rheumatology clinic, Mulvihill’s study sought to systematically increase the rates of formal depression screening for patients with c-SLE.
Using the Patient Health Questionnaire-9 (PHQ-9), a multidisciplinary quality improvement (QI) team retrospectively evaluated baseline rates of documented depression screening using electronic health record (EHR) documentation. A clinical workflow for formal depression screening was developed with input from key stakeholders, and practitioners were trained on mental health issues in patients with chronic sickle cell disease (c-SLE), with a focus on screening techniques, prevalence, and positive screen management. The Plan-Do-Study Act (PDSA) approach to quality improvement was used to continually evaluate and make real-time process adjustments. The percentage of c-SLE patients examined each month who had a recorded PHQ-9 screening during the previous year was the primary outcome.
The initial proportions of kids with verified PHQ-9 scores varied from 0% to 4.5%. This number rose to 91.0% within a year of the project’s start, with monthly screening rates consistently above 80% for ten months. Twenty-seven patients (48.2%) showed signs of depression as a result of these efforts, and seven patients (12.5%) who had thoughts of self-harm were appropriately directed to mental health facilities.
The viability of routine formal depression screening in a busy specialist clinic is demonstrated by this study. Formal depression screening rates for children with c-SLE increased from an average of 3.3% per month to a sustained monthly rate of 80% with the application of QI approaches. By being proactive, it was easier to identify those who had suicidal thoughts and/or depression symptoms, which allowed for prompt referral to the right mental health services. Mulvihill and colleagues, 2021).
¨Accuracy of the Patient Health Questionnaire-9 for screening to detect major depression: revised systematic review and individual participant data meta-analysis¨ was the title of a study that Negeri et al. continued. A meta-analysis of individual participant data and a systematic review were carried out.
The purpose of this study was to evaluate the efficacy of the Patient Health Questionnaire-9 (PHQ-9), a commonly used depression screening instrument in general practice, for identifying major depression across different study and participant subgroups, and to update a previous meta-analysis of individual participant data.
Up until May 9, 2018, Medline, Medline In-Process, and Other Non-Indexed Citations were searched for using Ovid, PsycINFO, and Web of Science.
The Mini International Neuropsychiatric Interview (MINI), a brief lay-administered interview, or a validated semistructured diagnostic interview (for clinician administration) or fully structured interview (for lay administration) were the methods used to determine current major depression status in eligible studies that employed the PHQ-9.
Point and interval estimates of the pooled PHQ-9 sensitivity and specificity at cut-off values between 5 and 15 were obtained using a bivariate random effects meta-analytic model. Meta-regression was used to investigate relationships between participant characteristics, reference standard categories, and PHQ-9 accuracy.
Data were collected from 100 out of 127 eligible studies (42 extra studies; 79% eligible studies; 86% eligible participants) for a total of 44,503 participants (27,146 additional from the update). The pooled PHQ-9 sensitivity and specificity (95% confidence interval) at the usual cut-off value of ≥10 were 0.85 (0.79 to 0.89) and 0.85 (0.82 to 0.87), respectively, in studies using a semi-structured interview reference standard.
Semi-structured interview studies showed increased sensitivity when compared to fully structured reference standards and the MINI, but the specificity of the results was the same for all reference standards. Specificity varied with reference standards and cut-off values, with men (median 3%) and those 60 years of age or older (median 5%) having higher specificity.
Using the knowledge translation tool at www.depressionscreening100.com/phq, researchers and clinicians can use the findings to evaluate outcomes, such as the total number of positive screens and false positive screens, at different PHQ-9 cut-off values in a variety of clinical settings (Negeri, et al., 2021).
Efficient care structures, when combined with efficient resource allocation, have the ability to reduce inefficiencies in mental health services. We commence our investigation by examining the complexities related to mental health and clarifying their influence on the provision of services. The authors then carried out a thorough scoping assessment of the literature, concentrating on research that use optimization techniques to address service delivery issues in the mental healthcare field.
These studies are divided into groups according to factors including the care environment, the goal of the study, and the planning decisions that are addressed. Analysis includes the modeling approaches used, the goals sought, the obstacles faced, and the solutions these models provide. Compared to other healthcare fields, the implementation of optimization in mental healthcare is still in its infancy.
The authors’ discussion of similarities between the provision of mental healthcare services and other services illuminated possible directions for further investigation. Our results imply that optimization techniques that have been successful in particular healthcare contexts can be modified for application in mental health care. Furthermore, we pinpoint chances to tackle particular issues encountered by mental health services (Noorain et al., 2022).
2023 saw the completion of a study by O’Connor and associates titled “Screening for Depression, Anxiety, and Suicide Risk in Adults.” The purpose of this research was to evaluate the benefits and limitations of diagnosing and treating depression, anxiety, and suicide risk in primary care patients, as well as the precision of the tools employed in this process.
Up until September 9, 2022, researchers searched the Cochrane Database of Systematic Reviews, PsychINFO, MEDLINE, and the Cochrane Central Register of Controlled Trials (CENTRAL). From earlier USPSTF evaluations or other pertinent reviews, the search was expanded. furthermore kept an eye on published works until November 25, 2022, to incorporate pertinent research from the upgrade.
Following the assessment of 23,497 abstracts, 1,237 full-text papers were evaluated in accordance with preset inclusion criteria. Studies that addressed screening, therapy (in comparison to control conditions), or the test accuracy of particular screening instruments were eligible as long as they were written in English.
Primary care populations were the only focus of primary care populations’ primary research on screening and test accuracy, as well as primary care populations’ primary care studies on anxiety therapy. Studies involving suicide prevention treatment recruited participants from non-acute outpatient settings.
Using primary trials and test accuracy studies for smaller evidence bases and existing systematic reviews (ESR) for well-established bodies of literature, the study design differed depending on the condition and central topic. When evaluating the risks of medication, observational studies and their ESRs were taken into account.
For primary research, critical evaluation was carried out separately by two investigators, whereas ESRs were evaluated by one reviewer and verified by another if minimal quality requirements were not fulfilled. One reviewer extracted the data, while another double-checked it.
Random effects meta-analysis was carried out using the DerSimonian & Laird or restricted maximum likelihood technique with the Knapp-Hartung correction for a small number of studies when sufficient primary research evidence permitted pooling. When it was feasible, subgroup analysis and meta-regression were used to investigate effect modification.
Eleven hundred and ninety-nine primary studies and eighty-six ESRs totaling an estimated 13 million participants were included, covering all major issues and conditions. After six to twelve months, depression screening interventions—which frequently included extra elements—were linked to a lower prevalence of depression or clinically severe depressed symptoms. Test accuracy was satisfactory for a number of the instruments, and a large body of research confirmed the advantages of both pharmacological and psychological treatment for depression.
Studies on treatments for suicide prevention revealed that second-generation antidepressants only slightly raised the absolute probability of a suicide attempt. Studies on anxiety screening, however, did not reveal any advantages, although those on anxiety treatment did indicate some advantages. There was insufficient data to support the accuracy of certain anxiety screening tools. Evidence gaps for suicide risk screening in primary care settings were identified.
Typically, control groups in suicide prevention treatment studies were provided with standard or optimal specialty mental health care. It’s possible that pertinent studies were left out of the predetermined a priori selection of anxiety screening tools. The analysis of impacts in certain patient populations may have been limited by the dependence on ESRs.
The usefulness of depression screening in primary care settings, including during pregnancy and the postpartum period, is supported by both direct and indirect data. Nevertheless, there is not enough data to make judgments regarding the advantages or disadvantages of anxiety screening programs. There is substantial evidence to support the efficacy of anxiety treatments, yet there is insufficient evidence to support the acceptable accuracy of some anxiety screening tools. The data supporting suicide risk screening in primary care settings is noticeably lacking in certain areas. (O’Connor and others, 2023).
In a 2019 study by Packness et al. titled “Are perceived barriers to accessing mental healthcare associated with socioeconomic position among individuals with depression symptoms?”, researchers seek to determine whether perceived barriers to mental healthcare access (MHC) in depressed individuals are related to socioeconomic position (SEP).
A questionnaire-based population survey from the Lolland-Falster Health Study (LOFUS) 2016–17, with 5076 participants, was used to conduct a cross-sectional survey.
372 participants in LOFUS who scored positively on the Major Depression Inventory (MDI) were included in the research.
Five questions about perceived obstacles to seeking professional care for mental health issues were given to those who had symptoms of depression (MDI score > 20).
We examined the relationship between SEP (as determined by financial hardship, work status, and educational attainment) and five categories of barriers to MHC access using independent multivariable logistic regression models that controlled for age and gender.
314 (84%) of the 372 people who answered the survey questions mentioned obstacles to obtaining MHC access. Of the five types of hurdles, concern over costs associated with seeking or maintaining MHC was the most common, accounting for 30% of the barriers that respondents reported.
Twenty-two percent of respondents said stigma was a barrier, and there was no correlation between perceived stigma and SEP. Transportation showed the most constant socio-economic gap (OR 2.99, 95% CI 1.19 to 7.52) between the lowest and highest educational groups, despite being the least problematic obstacle overall. Concerns over costs (OR 2.77, 95% CI 1.34 to 5.76) also showed a difference in socioeconomic status for the same categories.
Compared to people with high SEP, those with low SEP more frequently saw problems with costs and transportation as obstacles to receiving MHC. There was no correlation between perceived stigma and SEP. Written informed permission was obtained for the study, and the Danish Data Protection Agency (REG-24–2015) and Region Zealand’s Ethical Committee on Health Research (SJ-421) approved it ethically. The Creative Commons Attribution Non-Commercial (CC BY-NC 4.0) license governs how the article is distributed. Packness and colleagues, 2019).
The predictive validity of the Edinburgh Postnatal Depression Scale (EPDS) was compared with other depression screening instruments for expectant and postpartum mothers through a systematic review and meta-analysis.
The search was conducted using keywords linked to depression, perinatal terminology, and EPDS, and it covered electronic databases such as MEDLINE, EMBASE, CINAHL, and PsycArticles. The possibility of bias in diagnostic studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2.
Of the 823 papers found, 17 studies were deemed eligible for inclusion. The EPDS showed a summary receiver operating characteristic (sROC) curve of 0.90, a pooled sensitivity of 0.81, and a specificity of 0.87 in 1,831 pregnant women from nine investigations.
The EPDS showed a pooled sensitivity of 0.79, specificity of 0.92, and a sROC curve of 0.90 for 515 postpartum women from six trials. The sROC curve of the Patient Health Questionnaire-9 was found to be 0.74, lower than that of the EPDS (0.86), after comparative comparisons with other tools utilizing three or more studies were conducted.
The ten-item Kessler Psychological Distress Scale and the Beck Depression Inventory both had sROC curves of 0.91, which was similar to the EPDS’s 0.90 and 0.87. However, the EPDS showed a lower sROC curve of 0.54 compared to the Postpartum Depression Screening Scale (0.98).
The EPDS worked very well as a specialist tool for screening depression in expectant and new mothers. Consequently, in primary care settings or midwifery clinics, the EPDS is preferred over alternative instruments for the screening of depression in postpartum women. Park and others (2023).
Identifying depression in diabetes patients in an Indian primary care context: Is depression associated with a lower sense of perceived quality of life? In a primary care environment in India, Patra sought to screen for depression in people with type 2 diabetes and determine the factors that may be involved. Furthermore, an assessment was conducted on the correlation between depression and the perceived quality of life.
In this one-year cross-sectional study, convenience sampling was used to enroll 388 consecutive patients with type 2 diabetes mellitus. 50.3% of patients who completed the Patient Health Questionnaire (PHQ-9) screened positive, with 21.4% indicating moderate to severe depression.
Poor glycemic control, middle age, and male gender were factors linked to depression. The depression category was included as an independent variable in a stepwise linear regression analysis. Other independent variables were age, gender, education, income, lifestyle, glycosylated hemoglobin, and body mass index. The dependent variables of the World Health Organization Quality of Life questionnaire were the transformed domains.
According to the study, patients with type 2 diabetes in primary care in India had a high prevalence of depression. There was a strong correlation found between depression and all four quality of life areas. The domain of physical activity showed the strongest correlation with depression (β -0.385, p = 0.000), with the social domain following closely behind (β -0.372, p = 0.000).
The increased frequency of depression and its association with a lower quality of life highlight how crucial it is to better identify depression in order to improve the outcomes for diabetes patients at this medical facility (Patra et al., 2020).
In order to enhance health outcomes, a task-sharing approach to managing chronic diseases that includes treatment for co-existing CMDs is required. This is due to the growth in multimorbid chronic ailments in South Africa, the significant treatment gap for common mental disorders (CMDs), and the scarcity of mental health professionals. Evaluating a task-shared integrated collaborative care package of care for chronic patients with co-existing depressive and alcohol use disorder (AUD) symptoms was the goal of the ongoing study, “Evaluation of a collaborative care model for integrated primary care of common mental disorders comorbid with chronic conditions in South Africa.”
The intricate intervention improved primary care nurse practitioners’ ability to recognize, assess, and diagnose CMD symptoms in patients receiving long-term care. It also established a more robust referral system that involved mental health professionals, doctors, and clinic-based psychosocial lay counselors.
A non-randomly assigned comparison group cohort study consisting of 373 screen positive patients with depressive symptoms using the Patient Health Questionnaire-9 (PHQ9) at baseline, evaluated responses of patients correctly identified and referred for treatment (intervention arm) or not identified and referred (control arm) at three and twelve months. These studies were conducted under real-world conditions in four PHC facilities, using a repeat cross-sectional Facility Detection Survey (FDS) to assess changes in nurses’ capacity to correctly detect CMDs in 1310 patients prior to implementation and 1246 patients after the intervention at 12 months.
The findings of the FDS indicate a noteworthy rise in the detection of AUD and depression between the pre-implementation and 12-month post-implementation periods. AUD: (0 to 13.8%) 95% CI [0.6–24.9]; depression: (5.8 to 16.4%) 95% CI [2.9, 19.1]. During the 3-month and 12-month follow-up periods (intervention: n = 57, 47.9%; comparison: n = 60, 30.8%; RR = 1.52, p = 0.006), patients with depressive symptoms who had more than a 50% reduction in PHQ-9 scores were more numerous in the treatment group (n = 69, 55.2%) than in the comparison group (n = 49, 23.4%). At 12 months, the intervention group (n = 32, 26.9%) had a higher rate of remission (PHQ-9≉≤ 5) than the comparison group (n = 33, 16.9%) (RR = 1.72, p = 0.016).
In real-world settings, a task-shared collaborative stepped care model can decrease depressive symptoms and increase the diagnosis of CMDs in patients with chronic diseases. Petersen and colleagues, 2019).
Quality measures based on screening are unlikely to improve results unless the systematic application of depression screening is linked to early treatment.
to assess how clinical decision support and systematic depression screening affect the diagnosis and management of depression. pre-post retrospective research.
Included were adults who visited a primary care physician in a sizable integrated health system in 2016. Excluded were adults who received a diagnosis of depression in 2015 or before to their first primary care appointment in 2016.
In the middle of 2016, the Patient Health Questionnaire (PHQ) was used to start a systematic screening process.
ICD codes were used in the diagnosis of depression. The three options for treatment were: (1) prescription antidepressants; (2) referrals; or (3) assessment by a behavioral health professional. To find out if the percentage of visits with a diagnosis of depression varied before and after the introduction of systematic screening, we used an adjusted linear regression model. The relationship between screening and treatment odds was evaluated using an adjusted multilevel regression model.
There were 259,411 patients in the research population. Following implementation, 59% of patients were screened, and 3% of those individuals were found to have moderate to severe depression. Immediately following systematic screening, the rate of depression diagnoses rose by 1.2% (from 1.7% to 2.9%). After implementation, the adjusted chances of therapy increased by 20% (AOR 1.20, 95% CI 1.12–1.28, p < 0.01), and the percentage of patients with diagnosed depression who received treatment within 90 days improved from 64% before to 69% after (p < 0.01). High screening rates and higher rates of depression diagnosis and treatment were the outcomes of implementing systematic depression screening inside a big health care system. (Pfoh and others, 2020). Boland claims that the use of quality improvement (QI) techniques has grown in importance in the provision of mental healthcare globally. The idea of methodically improving processes was first created in the manufacturing industry and has now spread to many other areas, most notably the healthcare sector. QI techniques, which were first introduced in the United States by organizations such as the Institute for Healthcare Improvement and Virginia Mason, have been deeply ingrained in mental health services offered by the National Health Service (NHS) in the United Kingdom. Boland has suggested two main models that have acquired popularity: "lean thinking" and the "Model for Improvement." Virginia Mason gave rise to lean thinking, which emphasizes process simplification and waste reduction. The Institute of Healthcare Improvement is the source of the Model for Improvement, which emphasizes the iterative testing and improvement of change concepts. The philosophical foundations of these theories and their suitability for mental health treatment are the main points of contention. Some contend that lean thinking may ignore the complexity and individuality inherent in mental health therapy, even as it stresses efficiency and waste reduction. In contrast, the Model for Improvement's focus on iterative testing fits in well with the dynamic nature of mental health care, albeit it might need to be modified to handle the particular difficulties and results in this area. A strong foundation for data collecting, evidence-based practice, and metrics is necessary for the effective application of QI techniques in mental healthcare. This means obtaining pertinent data and analyzing it in light of patient experiences and outcomes. Metrics should also be chosen with care to account for the complex relationship between mental health outcomes and society impact, patient satisfaction, and clinical efficacy. Actually, even while the Model for Improvement and lean thinking are useful frameworks for improving the delivery of mental healthcare, their use necessitates careful evaluation of the particularities of this subject. Mental health services may provide patient-centered care and systematically enhance quality by utilizing data, evidence, and relevant indicators (Boland, 2020). Among healthcare professionals (HPs), the frequency of mental problems, particularly addictions, has increased significantly during the COVID-19 pandemic. It is anticipated that this pattern will continue long after the pandemic passes. HPs have traditionally been conditioned to put the needs of others before their own self-care, which makes it difficult for them to ask for assistance when they do. Starting early in undergraduate education and continuing throughout professionals' careers are the best times to address this issue. Globally, HPs have had access to a multitude of specialized mental health programs and wellbeing services in recent decades. More measures to promote the mental health of HPs have been sparked by the pandemic, however many of these might only last temporarily. But mental illnesses among HPs only make up a small portion of the larger problem of HPs' welfare. It necessitates a multifaceted viewpoint that takes into account both contextual impacts and individual factors. In their study, Braquehais and associates demonstrated that although offering suitable treatment plans to individuals suffering from psychological and psychiatric disorders is vital, the COVID-19 pandemic offers a chance to acknowledge caregiver care as a professional duty as well as a moral obligation. According to Shanafelt's concept, doctors should move from a distressing period marked by high expectations and a disregard for self-care to a wellbeing 1.0 paradigm that places an emphasis on resilience, relationships with coworkers, and work-life balance. On the other hand, the pandemic might spur adoption of the new wellness 2.0 paradigm. This paradigm emphasizes the human traits and self-compassion of HPs, makes work seem worthwhile, and fosters collaborative teamwork. It will take the participation of leaders, institutions, professional associations, HPs themselves, and society at large to implement this new paradigm. Healthcare systems can better support HPs' well-being by adopting this move, which will ultimately improve patient care results (Braquehais et al., 2023). Depression is a common, multifaceted illness that has a long-term, recurrent course and is commonly seen in basic care settings. Primary care physicians play a crucial role in the management of depression as well as the treatment of coexisting medical conditions. They do, however, have significant difficulties in correctly detecting and treating this illness. Our goal in offering evidence-based insights to primary care practitioners and practices in this two-part series is to help them identify and treat depression more effectively. Ramanuj, et al. have concentrated on describing a method for identifying and diagnosing depression in the primary care context in our first review. Researchers provide useful ideas for clinical implementation and condense recommendations based on existing evidence-based guidelines. The goal is to equip primary care clinicians with the knowledge and skills needed to properly diagnose and evaluate depression by compiling the best available evidence. The review that follows will examine an evidence-based strategy for treating depression in primary care. It will cover all advised lifestyle adjustments, medication therapy, and psychiatric counseling on an individual basis. It will also provide insight into organizational tactics meant to improve the efficiency of managing depression in primary care settings. When taken as a whole, these evaluations seek to close the gap that exists between clinical practice and evidence-based recommendations, thereby improving the standard of care given to depressed patients in primary care settings. We hope to enhance outcomes for patients with depression and contribute to more efficient depression management within primary care by arming primary care practitioners and practices with evidence-based insights and useful interventions (Ramanuj, et al., 2019). The goal of the study by Ravaldi and associates was to evaluate the attitudes, clinical background, and knowledge of Italian midwives about prenatal depression (PND) and how it affects the standard of care given. A cross-sectional online survey was administered to 152 midwives working in Italian public hospitals. Key findings showed that, according to recent scientific research, 76.3% of midwives showed insufficient knowledge of PND. Compared to their less informed counterparts, midwives who had a deeper understanding of the subject matter showed greater confidence in their work, less anxiety while speaking with moms, and less worry for the mothers' long-term welfare. The study emphasized midwives' requests for official training in PND management and specific recommendations. It also emphasized how crucial family involvement, continuity of treatment, and effective communication are to helping impacted women. In summary, this study offers insightful information about the attitudes and knowledge that Italian midwives currently hold about PND. It highlights areas for practice and educational development, indicating that more midwives with experience in PND might greatly raise the bar for care and make early identification and treatment easier (Ravaldi, et al., 2024). Previous studies have shown that examining how first-person singular pronouns are used can provide information about people's mental health, especially how severe their depressive symptoms are. Traditional methods, however, count the frequency of certain pronouns, which may miss subtleties in their usage. Contextualized language representation models, which provide a more sophisticated knowledge of language usage, have been introduced by recent developments in neural language modeling. In order to capture the subtleties of first-person pronoun usage and examine their association with mental health state, researchers in this work sought to leverage embeddings of first-person pronouns derived from contextualized language representation models. We used de-identified text messages that were exchanged during weekly assessments of depression severity that were part of online psychotherapy sessions. According to research findings, when it comes to predicting the severity of depressive symptoms, contextualized embeddings of first-person pronouns perform better than frequency-based pronoun analysis and standard categorization token embeddings. This implies that first-person pronoun contextual representations can greatly improve the prediction power of language used by people who are depressed. Overall, this study emphasizes how critical it is to take into account the contextual subtleties of language usage in addition to its existence when assessing mental health, especially in those who are depressed. We can learn more about the linguistic indicators of mental health and possibly enhance diagnosis and treatment strategies in psychotherapy by utilizing cutting-edge neural language modeling tools (Ren, et al., 2024). In primary care settings across the United States, depression screening is widely recommended for adolescents; yet, little is known regarding its effect on later diagnosis and mental health care access. Riehm et al. used insurance claims data from teenagers who had well-visits between 2014 and 2017 for their longitudinal cohort study. Adolescents with and without screening were compared using propensity score matching. Over the course of a six-month follow-up, diagnoses and treatment adherence were assessed. This included psychotherapy, antidepressants, any mental health medications, and diagnoses linked to depression and mood disorders. Sex-based heterogeneity was investigated. There were 57,732 teenagers in the sample (mean age: 14.26 years; 48.9% female). Compared to their counterparts who were not screened, adolescents who underwent screening had a 30% higher chance of receiving a diagnosis of depression (RR=1.30, 95% CI=1.11-1.52) and a 17% higher chance of receiving a diagnosis linked to mood (RR=1.17, 95% CI=1.08-1.27). The usage of antidepressants (RR=1.11, 95% CI=0.82-1.51), any type of mental health treatment (RR=1.15, 95% CI=0.87-1.53), and psychotherapy (RR=1.13, 95% CI=0.98-1.31) did not differ significantly from one another, though. Adolescent females had stronger associations overall. A future diagnosis of depression or a mood disorder was more likely to be given to adolescents who had undergone depression screening during well-child visits. On the other hand, there were no appreciable variations in treatment uptake. Subsequent studies ought to investigate methods for improving treatment uptake after screening (Riehm, et al., 2021). An evidence-based strategy called mindfulness-based cognitive therapy (MBCT) is designed to help people who are at risk of relapsing into depression achieve long-term recovery. Although it is recommended in the standards, there is a noticeable "implementation cliff". The objective of this research was to comprehend the elements that promote the thorough application of MBCT. In 2019, Rycroft-Malone et al. conducted a study that covered primary and secondary care mental health services across the United Kingdom. A two-phase, nationwide qualitative study utilizing many methods was carried out, with the Promoting Action on Research Implementation in Health Services framework serving as a guide. In Phase I, stakeholders from 40 service providers were interviewed to learn more about the existing state of MBCT provision. Ten purposefully picked case studies comprised Phase II, which looked more closely at the application of MBCT. A modified framework analysis was used for data analysis, and it was improved through stakeholder input. MBCT access differed throughout UK services, which were frequently customized to meet regional needs. Pilots, audits, reviews, clinical guidelines, and experience sessions were among the many types of evidence that were crucial in assisting with implementation. The pivotal function of MBCT implementers became evident as essential, frequently self-appointed persons supporting grassroots implementation. A theoretical construct was created that provided an explanation of a typical implementation process that combined top-down and bottom-up effects and had turning points that offered chances or obstacles. Even though more people in the UK have access to MBCT, disparities still exist. The study's explanatory framework serves as a helpful heuristic for guiding implementation techniques and resources, offering insightful information about the MBCT implementation process. This study highlights the significance of taking into account a variety of factors impacting implementation success and is one of the most systematic investigations into the implementation of a psychological therapy (Rycroft-Malone et al., 2019). 232 professionals were chosen by stratified sampling from all health professional departments of Delta State University Teaching Hospital in order to participate in Obiebi's analytical cross-sectional design study, which aimed to evaluate health professionals' perceptions, determinants of their health, and practices of preventive self-care. The sampling frame includes medical personnel who had been employed by the hospital for a minimum of six months. Professionals who were supernumerary and pregnant were not allowed. A self-administered questionnaire was employed, and SPSS was used for data analysis. The degree to which preventive self-care was practiced and the degree to which self-health was perceived were the primary outcome measures. Good health perception was reported by 64.8% of nurses and more than four-fifths of doctors, with a substantial correlation found between perception and service area. Physician screening rates were lowest, with the exception of HIV/HBV screening. Only 36.2% of participants truly had a normal BMI, despite the fact that 63.4% of participants thought their BMI was normal. This disparity was noteworthy. The similar percentage of physicians and nurses reported never checking their FBS, and over 20% of physicians had not checked their blood pressure in a year or more. Among healthcare professionals, nurses (76.1%) and doctors (58.3%) had the highest percentage of individuals who had never evaluated their serum lipid profile. The respondents started managing after the disease started, despite having high perception but poor preventive activity. This could be concerning for the industry. To protect productivity, immediate health promotion measures are required. A fuller understanding of the problem will be possible with comprehensive data from a multi-center study (Obiebi, et al., 2020). Economic prosperity, social harmony, and general well-being all depend on the mental health of the populace. In order to prevent, treat, maintain, or restore mental health, mental health services are essential. The findings of a study conducted by Samartzis and associates were released in 2019. The goal of the study is to provide a framework for the qualitative and quantitative assessment and enhancement of mental health care systems. The goal of this narrative review is to find methods, markers, and standards for evaluating and improving the caliber of mental health care by searching the literature. Prominent databases, including PubMed, Google Scholar, and CINAHL, were searched using different combinations of keywords, including "mental," "health," "quality," and "indicators." Significant quality indicators for mental health services are compiled in this study, with required revisions made. Every indication is described, including how it is calculated and how important it is. Eight dimensions are used to classify these indicators in order to assess quality: • Appropriateness of services; • Patient acceptance of services; • Availability of services; • Capacity of medical personnel to provide services. • The effectiveness of medical personnel and providers • Service continuity across time (maintaining therapeutic continuity) • The effectiveness of medical personnel and services • Security (for both medical personnel and patients) For services to be appealing and used by the public, indicators of their acceptability and accessibility are essential. The sustainability and viability of services, which are now crucial components in health policy considerations, depend on economic profitability metrics. Each of the aforementioned variables has an effect on public health, either directly or indirectly affecting life expectancy, morbidity, mortality, and quality of life. Evidence-based health policy aimed at improving the quality of mental health care is based on the systematic measurement, tracking, and quantification of these variables (Samartzis, et al., 2019). In the UK, access to mental health care during pregnancy is a critical public health issue. Access barriers can appear at different stages of the treatment pathway; however, multilevel system barriers and their linkages that impede women's access to services have not been examined in previous assessments. In 2019, Sambrook Smith and colleagues conducted a literature review that explores the viewpoints of women, their families, and healthcare providers concerning the obstacles faced by women suffering from perinatal mental illness in the United Kingdom while trying to seek mental health services. A meta-synthesis and systematic review of qualitative research were carried out. Electronic searches in databases like MEDLINE, PsycINFO, EMBASE, and CINAHL were used to find qualitative research published between January 2007 and September 2018. Hand searches of reference lists and citation tracking were also used to find relevant studies. The studies that were included examined perinatal mental health disorders using qualitative approaches and focused on women, family members, or healthcare providers in the United Kingdom. The Critical Appraisal Skills Programme for Qualitative Studies was used to assess quality. 35 research out of the 9882 papers found satisfied the inclusion requirements. Using an already-existing multilevel conceptual model, emerging themes were examined. Four levels of barriers were found to prevent women with prenatal mental illness from receiving mental health services: Social (e.g., language/cultural hurdles) • Organizational (e.g., resource shortages, service fragmentation) • Individual (e.g., stigma, low awareness) • Structural levels, such as ambiguous policies. Women with prenatal mental disorder face complex, interconnected, multilayered barriers that impede their access to mental health services. Multilevel solutions that address organizational, sociocultural, individual, and structural barriers at various phases of the care pathway are advised in order to improve access (Sambrook Smith, et al., 2019). Primary care physicians see patients with depression on a regular basis, yet a significant number go misdiagnosed and untreated. In order to better understand how depression is screened and how it affects depression diagnosis and treatment in outpatient primary care settings, Samples and colleagues developed this study. Nationally representative survey data from the National Ambulatory Medical Care Surveys conducted between 2005 and 2015 were subjected to a cross-sectional analysis. Patients who were 12 years of age or older (N=16,887) who had recently had their first primary care visit were included in the sample. The relationships between visit features and depression screening, as well as between depression screening and on-site diagnosis and treatment, were investigated using logistic regression. The probability of diagnosing and treating depression under the counterfactual scenario, in which patients attended providers with lower screening rates but instead visited providers with higher screening rates, were evaluated using logistic regression with propensity score weighting. All models were modified to account for the features of the patient and visit. The percentage of visits that involved screening for depression was a meager 3.0%. Patients who complained of depressed symptoms during their visits were more likely to get screened. Visits to providers with greater screening rates were linked to higher probabilities of depression diagnosis (OR=1.99, p<0.001) and treatment (OR=1.61, p=0.001) compared to visits to providers with lower screening rates, after visits were weighted to have equivalent demographic and clinical characteristics. It seems that doctors selectively use depression screening based on patients' presenting symptoms. Greater chances of depression diagnosis and treatment were linked to higher screening rates, indicating that even small improvements in screening rates could have a major positive impact on the population's rates of depression identification and treatment in primary care. In order to enhance services and patient outcomes, future research should concentrate on identifying obstacles to depression treatment and putting systematic interventions into place (Samples, et al., 2020). Although evaluating depressive symptoms in multiracial/ethnic communities using instruments like the Patient Health Questionnaire-9 (PHQ-9) presents difficulties, depression and suicide are serious public health concerns. The purpose of this study, which was carried out in the US, was to assess the psychometric qualities of the PHQ-9 among a multiracial/ethnic sample. 1,012 English-speaking multiracial and ethnic people from the US participated in the study. The PHQ-9's factor structure and internal consistency were evaluated. It was also looked at how the White/Non-White and Non-White Multiracial/Ethnic categories differed in measurement. Furthermore, the effectiveness of the PHQ-2, a condensed form of the PHQ-9, was assessed. Strong internal consistency (α=0.93) and support for a one-factor structure were demonstrated by the PHQ-9. There was no discernible measurement variance among various racial/ethnic categories. With a threshold of ≥3, the PHQ-2 detected fewer cases of depression (32% vs. 40%) than the PHQ-9, with sensitivities ranging from 75% to 99% and specificities from 74% to 96%. Less instances were missed with a threshold of ≥2. The PHQ-9's ninth question, which deals with thoughts of suicide or self-harm, showed notable generational differences in item performance. Younger generations were shown to be more likely to support such thoughts, irrespective of the severity of their symptoms. This shows that the ninth item, especially when it comes to older Multiracial/Ethnic adults, may not be able to sufficiently identify people who are at risk for suicidal thoughts or behaviors. The PHQ-9 showed sufficient dependability in an adult population of mixed racial and ethnic backgrounds in the United States. However, especially in older persons, the PHQ-9's ninth question might not be enough to identify people who are at risk of having suicidal thoughts or actions. According to Shaf et al. (2024), it could be better to use a cutoff of ≥2 for the PHQ-2 in order to overlook fewer cases of depression in this cohort. A primary care clinic's patient records were reviewed, and it was discovered that none of the patients were undergoing a validated and trustworthy depression screening. It is well known that depression has a significant negative influence on the mental and physical health of a significant number of primary care patients. The U.S. Preventive Services Task Force's recommendations were used to develop a depression screening and management strategy, which was used to address the issue. The procedures were advised by the Institute for Clinical Systems Improvement and the American College of Preventive Medicine. At the primary care clinic, a plan was established for the screening, management, and treatment of patients with depression. Metrics such as the number of patients evaluated for depression, newly diagnosed cases, those provided antidepressants, referrals, and follow-up management were compared before and after adoption in the analysis. The number of depression tests performed, the proportion of patients receiving a new diagnosis, and the number of patients receiving treatment all increased dramatically after the depression screening and management protocol was put into place. The primary care clinic's depression screening, diagnosis, and treatment were all improved as a result of this quality improvement effort. Subsequent initiatives must to concentrate on creating metrics to monitor the progress of depression patients receiving care at the clinic (Sharp, et al., 2023). In line with the US Preventive Services Task Force's recommendations, this quality improvement initiative sought to improve depression screening and treatment for adults receiving primary care at an academic medical center. Even though depression is among the most common mental health conditions among adults in the US, there is still a big demand for screening and treatment for depression that has to be made universally available. In order to enhance depression screening and treatment, the initiative put into practice VitalSign6, a measurement-based care program. To assess changes in screening rates, results, and patient satisfaction, a pre-post design was used. 95.4% of the 1200 distinct adult patients underwent a preliminary test for depression. 236 patients were diagnosed by providers, who also provided measurement-based care. 27.5% of patients came back for at least one follow-up appointment after a 14-week period. From baseline to follow-up, there was a statistically significant drop in self-reported depression scores. The successful use of VitalSign6 resulted in improved primary care depression diagnosis and treatment. The study successfully improved patient outcomes, facilitated diagnosis, and raised screening rates. (Et al., Siniscalchi, 2020). Even though depression is common in older persons, primary care settings still don't always screen for it. Other professional disciplines have the ability to screen for depression, even though doctors are frequently the first to see depressed older persons. The purpose of this study was to investigate the obstacles to screening for depression in older individuals and the variations in screening propensities among clinical trainees from different fields. An online, cross-sectional survey was carried out using vignette manipulation experiments. The impact of clinical discipline (between subjects) and variables like as time constraints, patient difficulties, and symptom severity (among subjects) on trainees' likelihood of screening were investigated using a four-way mixed analysis of variance. 229 trainees in social work, nursing, psychology, and medicine participated in the study. The chance of screening was enhanced by higher symptom severity and less time constraint. Discipline, patient difficulty, and symptom level all showed a significant three-way interaction. Social work trainees were more likely to screen for depression when more symptoms were present, but this propensity was lessened if the patient was thought to be difficult. Furthermore, there was a two-way interaction between the severity of the symptoms and the patient's difficulty; the more symptoms, the higher the likelihood of screening; however, the effect decreased as the patient's perceived difficulty increased. This study emphasizes how important it is to close knowledge gaps in depression screening in several therapeutic fields. Interventions could concentrate on increasing awareness of depression in the elderly, offering opportunities for practice-based screening, boosting behavior control skills, and strengthening time management abilities. These kinds of initiatives may reduce obstacles to depression screening and enhance the quality of mental health services provided to senior citizens in a range of clinical contexts (Smith et al., 2019). Initiatives focused on quality improvement (QI) have shown to have a number of important advantages, including better financial results, operational effectiveness, organizational performance, and patient outcomes. Businesses with an exceptional rating from the Care Quality Commission (CQC) frequently have a QI culture ingrained in their operations. This study investigated how trusts used Quality Improvement (QI) as a methodical way to improve service quality, productivity, and morale. The goal was to disseminate these organizations' findings in order to raise the standard of care even higher. Through the CQC's inspection programme, nineteen trusts were selected, and their QI journeys were thoroughly reviewed. The study looked at how frontline employees and leaders work together to drive change, as well as the importance of leadership and the methodical approach to quality improvement. The study underlined how crucial senior leadership and the board's commitment are to the success of the QI journey. The key to establishing the intended culture of improvement is effectively modeling effective leadership behaviors. Organizations displayed a methodical approach to quality improvement (QI), frequently based on a systems approach and applied throughout the health system. The improvement model promoted cooperation between managers and frontline employees, dismantling obstacles and creating a common goal of providing patients with improved care. Although QI is not a magic bullet, it is essential to an organization's transition from traditional "command and control" management to more productive methods of planning and overseeing work. In order to promote continuous improvement in healthcare organizations, the study emphasizes the significance of leadership commitment, methodical methods to quality improvement, and cooperative efforts between leaders and frontline workers (Thorne I, et al., 2019). Important professionals in the healthcare and non-healthcare industries suffered possible psychological suffering in the early stages of the COVID-19 epidemic. The purpose of this study was to evaluate acute stress, health-related concerns, and functional impairment among key workers during this time, as well as to find factors that were predictive of these psychological effects. Using probability-based approaches, a sample of 1,821 self-identified vital workers in the United States was polled across three consecutive 10-day cohorts from March 18, 2020, to April 18, 2020. Assessments were conducted on acute stress, health-related concerns, and functional impairment. The following variables were looked at as potential predictors of psychological outcomes: pre-COVID-19 mental and physical health, secondary stresses (such lack of childcare or healthcare, lost pay), and demographics. Acute stress, health-related concerns, and functional impairment all rose during the first few weeks of the pandemic. Compared to non-health care essential workers, health care essential workers reported less acute stress and functional impairment. Acute stress, concerns about health, and functional impairment were linked to past mental and physical health problems, lack of access to healthcare, lost income, female gender, and Hispanic ethnicity. Acute stress was positively correlated with not having daycare. During the COVID-19 pandemic, non-healthcare critical workers may be more susceptible to detrimental psychosocial consequences. The results point to the necessity of providing key workers with specialized training and assistance to help them deal with the difficulties of working in-person during the ongoing pandemic. As society adjusts to live with COVID-19 and its variations, these insights can guide intervention efforts (Waheed, et al., 2024). Using the PCP-FIRST model, a VitalSign6 project report breaks down treatment choices, follow-up rates, and remission outcomes by initial depression severity. 32,106 patients who were 12 years of age or older and who were tested using the Patient Health Questionnaire 2-item (PHQ-2) at 37 primary care clinics between November 2016 and July 2019 were included in this retrospective analysis. PHQ-2 positive-screen patients (PHQ-2 ≥ 3) were evaluated for medication management using measurement-based care (MBC), and they were given access to 9-item PHQ (PHQ-9) and 7-item Generalized Anxiety Disorder scales, as well as clinical assessments. 18.7% (5994/32,106) of PHQ-2 screening patients tested positive and were assigned a PHQ-9. Out of the 5994 PHQ-9 patients, 2571 were diagnosed with depression. Of these, 333 had non-mild depression (PHQ-9 < 10) and 2238 had moderate-severe depression (PHQ-9 ≥ 10). There were 266 and 1929 patients with at least 18 weeks of data available out of the 333 patients with none-mild depression and the 2238 patients with moderate-severe depression. Among those, 69.1% (1332/1929) with moderate-severe depression and 54.9% (146/266) with none-mild depression began taking medication. Of the 1478 patients with a clinical diagnosis of depression who were started on medication, 1046 came back for at least one follow-up and 616 for at least three follow-ups spread over an 18-week period. Remission rates for patients with mild depression, moderate-severe depression, and overall were found to be 55.6% (66/99), 30% (282/941), and 32.4% (338/1040) of the 1046 patients who had at least one follow-up visit within an 18-week period. Remission results above real-world expectations for remission rates in primary care, which are set at 6%, even if this is a sample of typical treatment (Wang, et al., 2021). In order to treat depression in a hospice setting, Williams' study attempted to create and execute a strategy that included verified screening instruments within the electronic medical record. Depression has the potential to worsen outcomes for people with life-limiting illnesses by exacerbating their psychological and physical pain. There is evidence to support the creation of protocols that use referral procedures and validated screening instruments to manage depression in hospice settings. Social workers conducted initial psychosocial assessments on newly admitted patients who met the inclusion criteria after developing the procedure and integrating screening tools into the electronic medical record. Patients were then referred for both pharmaceutical and nonpharmacological therapy, depending on the protocol's description of the severity of depression. Using the Patient Health Questionnaire-2, all eligible patients were screened, and 52% of them had depression to some degree. Of those found, 26 percent were suitably referred for treatment, with 26 percent receiving nonpharmacological treatment and 50 percent receiving pharmacological approaches. Assessments conducted before and after the intervention revealed a statistically significant difference in the intensity of depression. When a structured process for managing depression was put into place in a hospice setting, more people with symptoms of depression were identified and assessments using validated screening instruments could be conducted consistently. According to Williams et al. (2023), this strategy makes it easier to implement timely interventions to enhance hospice patients' mental health and general well-being. Clinically significant depression is one of the most prevalent illnesses that appear in primary care, according to Zimmerman. Patients with a range of medical conditions frequently have it as a comorbid condition. Depression is prevalent, with an annual frequency of 8% and a lifetime prevalence of 19%. It is linked to deficits in main role function and premature mortality. Depression is among the most incapacitating medical conditions due to its high frequency and related psychosocial morbidity. They failed to consider the possible influence of differing severity scores on treatment choices, though. There are important clinical ramifications for the severity score categories' width and narrowness. It is not ideal to define severity groups based only on recall ease. Rather, they ought to consider the clinical importance of depression symptoms and direct treatment strategies accordingly. The PHQ-9 tends to overstate depression severity when compared to other self-report scales and clinician-rated measures, according to several research including primary care patients. This propensity causes moderate depression to be underdiagnosed and severe depression to be overdiagnosed. As a result, depending only on the PHQ-9 could lead to a decrease in psychotherapy referrals and a rise in the use of medicine as the main form of treatment. In summary, the PHQ-9 is a reliable self-administered measure for assessing depression; nevertheless, when depression is suspected, a clinical interview should be conducted to confirm the diagnosis of major depressive disorder based on the scale's scores. Regular PHQ-9 administration helps quantify therapy response for people receiving depression treatment. However, because the PHQ-9 tends to overclassify depression severity, a clinician should make the decision on the type of depression treatment rather than relying only on it (Zimmerman et al., 2019). Practice Recommendations Quality of the Strength The body of evidence consists of high-quality, well-planned studies, including observational studies, systematic reviews, meta-analyses, randomized controlled trials (RCTs), and quality improvement initiatives. These studies use solid protocols, well-established technologies, and careful data analysis to produce results that are trustworthy and widely applicable. Quantity: The effectiveness of primary care clinics in managing depression screening and therapies is the subject of numerous studies. Numerous research on the PHQ-9's use, attempts to raise screening rates by improving quality, and the impact of various medications on depression management are all included in the body of evidence. This extensive investigation results in a comprehensive understanding of the subject. Consistency: Many studies have demonstrated the effectiveness of systematic depression screening programs in primary care settings, particularly when the PHQ-9 is used. The information demonstrates how much these initiatives improve patient outcomes, treatment start rates, and depression identification rates. The positive benefits regularly seen across a range of demographics, situations, and intervention types lend more credence to the reliability of the evidence. In summary, the data that is now accessible offers compelling proof of the effectiveness of organized depression screening programs in primary care settings, including the PHQ-9. Initiatives for quality improvement and educational interventions that consistently demonstrate significant improvements in depression screening rates, timely detection, and management of depression lead to better patient outcomes. When utilizing the PHQ-9, a reliable and validated tool for depression screening, a cut-off score of 10 is recommended to enhance sensitivity and specificity. The findings emphasize how important it is to regularly screen for depression and provide follow-up care in primary care in order to enhance mental health outcomes. Recommendations for Practice Change The extensive and reliable amount of scientific evidence supports the recommendation that primary care settings use an organized and methodical approach to depression screening. This strategy ought to consist of: 1. Usage of PHQ-9 in Routine: Use the PHQ-9 as a standard instrument for screening patients for depression at all primary care appointments, especially for those with established depression risk factors and during routine check-ups. 2. Standardized Workflows for Screening: Create and put into place standardized processes for screening for depression to guarantee that every patient is evaluated in a methodical manner. For automated prompts and scoring, this involves integrating screening procedures into electronic health records (EHRs). 3. Training and Education: Regularly educate and train licensed healthcare on follow-up treatment protocols, the PHQ-9, and the significance of depression screening. This will improve their understanding, proficiency, and self-assurance in handling depression. 4. Follow-up and Management Procedures: Clearly define the procedures for managing patients who test positive for depression and for follow-up care. This includes alternatives for medication, continuing patient progress monitoring, and referral paths to behavioral health care. 5. Overcoming Telemedicine Challenges: Create plans to get around the decreased likelihood of screening for depression during telemedicine encounters. This could entail giving telemedicine providers specialized training, introducing digital tools for remote screening, and ensuring patients have access to the needed materials. 6. Equitable Screening Procedures: Make certain that screening procedures for depression are fair to all racial and ethnic groups. Resolve obstacles to screening in marginalized communities, such as language hurdles, and offer care sensitive to cultural differences. Primary care facilities can greatly improve the identification and treatment of depression by using these evidence-based practices, which will benefit patients' mental health and general well-being. Proposed algorithm for the development of the Project Although ideally and methodologically, this intervention should include a control group, it has not yet been decided to be performed this way. The absence of a control group in a before-after interventional study provides a fortress to the conclusions, mainly due to the and is scientifically recommended, but sometimes practical issues such as human resources availability could be restrictive. The next flow diagram represents the main activities in the Change Project: Setting Description of the DNP Scholarly Project Type of Setting A huge healthcare system will host several Family Medicine clinics where the project will be implemented. These clinics offer complete primary care services to a wide range of patients. To provide comprehensive patient treatment, the environment is typified by a multidisciplinary team approach that unites doctors, nurses, mental health specialists, and administrative personnel. Typical Client Profile The demographics of patients at family medicine clinics differ greatly, encompassing factors such as age, gender, socioeconomic level, and medical issues. An adult or teenager with a variety of health challenges, such as acute or chronic illnesses, mental health disorders like depression, and acute conditions, could be the usual client. Comorbidities are another common occurrence in patients, necessitating coordinated care from a number of healthcare professionals. Goals and Objectives Vision: To be a premier supplier of all-inclusive, patient-focused primary care that enhances community well-being and general health. Our mission is to improve the quality of life for our patients by providing them with high-quality, compassionate healthcare services via a team-based approach that prioritizes chronic illness management, mental health assistance, and preventive care. Culture and Organizational Structure The clinics are organized hierarchically, with department heads handling specialized services, including mental health, chronic illness management, and preventative care, and clinic managers in charge of day-to-day operations. The culture is patient-centered and collaborative, with a focus on interdisciplinary teamwork, evidence-based methods, and ongoing development. Determining the Need for the Organization A thorough requirements evaluation that identified deficiencies in the present depression screening procedures and inconsistent PHQ-9 instrument utilization indicated the necessity for this study. Stakeholders, including administrators and licensed healthcare were aware of the need to improve depression screening to improve patient outcomes and support the institution's mission of providing high-quality patient care. Stakeholders Key stakeholders include: · Healthcare Providers: Licensed healthcare providers such as registered nurses, advanced nurse practitioners, physician assistants, and primary care physicians who will directly use the PHQ-9 tool. · Clinic Managers and Administrators: Responsible for operational support and resource allocation. · Patients: Indirect beneficiaries of improved depression screening and care. · Educational and Training Staff: Responsible for delivering the educational program. · IT Department: Ensuring the integration of the PHQ-9 tool into the electronic health record (EHR) system. Confirming Organizational Support and Sustainability Plans Organizational support was confirmed through meetings with senior leadership, who endorsed the project due to its alignment with the institution's mission and its potential to improve patient care. Sustainability plans include: · Ongoing Training Programs: Regular updates and refresher courses for new and existing staff. · Integration into EHR: Ensuring the PHQ-9 tool is embedded in the EHR for ease of use. · Continuous Monitoring and Feedback: Regular audits and feedback sessions to assess the effectiveness and adherence to the screening protocol. · Resource Allocation: Committing necessary resources such as educational materials, trainers, and technical support for sustained implementation. SWOT Analysis Strengths: · High-Quality Training: Comprehensive educational program on the PHQ-9 tool. · Stakeholder Buy-In: Strong support from healthcare providers and administrators. · Resource Availability: Access to necessary tools and materials for implementation. Weaknesses: · Time Constraints: Limited time frame for initial implementation and evaluation. · Resistance to Change: Potential reluctance among some providers to adopt new practices. Opportunities: · Enhanced Patient Care: Helping to improve early detection and management of depression. · Professional Development: Helping to increase knowledge and skills among licensed healthcare providers · Accreditation Support: Alignment with accreditation standards and quality improvement initiatives. Threats: · Sustainability Challenges: Ensuring long-term adherence and integration into daily practice. · External Factors: Changes in healthcare policies or funding that could impact resources. SWOT MATRIX The proposed project helps to enhance licensed healthcare providers’ role in assessing, helping, and monitoring depression levels through the systematic use of the PHQ-9 tool is feasible and valuable. It aligns with institutional goals, has strong stakeholder support, and is designed to be sustainable beyond the initial implementation phase. By focusing on education and systematic application, this project help to aims significantly improve depression screening and patient outcomes in primary care settings. Project Vision, Mission, and Objectives Vision To create a primary care net in which licensed healthcare providers can accurately diagnose and monitor patients' levels of depression by utilizing the PHQ-9 depression screening instrument. This will ultimately result in better mental health outcomes for patients. Mission Our goal is to help make the PHQ-9 depression screening tool more useful to licensed healthcare providers working in primary care settings. Our goal is to help to enhance the early detection and treatment of depression by providing focused guidance and assistance, guaranteeing that patients have prompt and suitable medical attention. Objectives Short-Term Objectives: 1. Create and implement a thorough training curriculum on the PHQ-9 depression screening test for licensed healthcare providers. 2. Raise licensed healthcare providers ‘knowledge and comprehension of depression and how it affects general health. 3. Give licensed healthcare providers’ the knowledge and abilities to administer, decipher, and act upon PHQ-9 test results. 4. Evaluate the training program’s immediate effects by evaluating the knowledge and confidence of licensed healthcare providers before and after the training. Long-Term Objectives: 1. Pursue a consistent improvement in the PHQ-9 tool's routine application in primary care settings. 2. Encourage licensed healthcare providers to adopt a culture of ongoing education and understanding of mental health and depression. 3. Enhance patient outcomes by identifying and treating depression early on. 4. Create a scalable methodology that other healthcare facilities can use to incorporate mental health screening into their primary care procedures. Setting The project will be carried out in a primary care context, like a primary care clinic connected to a bigger healthcare organization or a community health center. Because there are many patient encounters in this context and there is a chance to incorporate mental health care into routine medical visits, depression screening instruments can be used here. Congruence with Organizational Mission and Vision Organization’s Mission and Vision: · Mission: To help provide comprehensive, patient-centered primary care services that promote the health and well-being of the community. · Vision: To be a leading provider of integrated healthcare services, known for our commitment to excellence in patient care, education, and community health. Project’s Mission and Vision Congruence: The primary care organization's goal of providing comprehensive, patient-centered care aligns with the project's goal of improving the roles of licensed healthcare providers in diagnosing and tracking depression. Helping to improve patient outcomes via education and integrated healthcare services is emphasized in both goals. The organization's mission of excellence in patient care and dedication to community health is supported by the project's goal of enhancing mental health outcomes using the PHQ-9 test. Risks and Unintended Consequences Risks: 1. Overcoming potential resistance to additional training and managing licensed healthcare providers' hectic schedules to ensure consistent engagement and participation. 2. Resource allocation can influence the scope and caliber of the training program due to constraints on time and financial resources. 3. Obstacles in Implementation: Diverse approaches among providers in utilizing the PHQ-9 instrument, resulting in inconsistent methodologies. Unintended Consequences: 1. Provider Overburden: The additional obligation of depression screening may induce feelings of being overburdened among licensed healthcare providers which could potentially culminate in burnout. 2. Data Management: Managing and safeguarding confidential patient information obtained via PHQ-9 assessments may pose difficulties about privacy and confidentiality. The project seeks to effectively achieve its objectives and improve licensed healthcare providers overall capacity to assess their patients' mental health by clearly defining its vision and mission, objectives and feasibility to develop the activities in a defined setting. Proactively addressing risks and unintended consequences through careful planning, continuous support, and evaluation, this project execution will positively contribute to the impact of the general population's mental health. Project Plan Change Model selection To advance the development of depression screening procedures in this project, a coalition of administrators, mental health specialists, healthcare professionals, and community leaders can offer guidance, resources, and support. In this sense, Kotter´s theory underscores the importance of assembling a steering group of interested parties dedicated to the transformation project. It's crucial to create a compelling vision for enhancing primary care depression screening. Kotter's approach accentuates the organization's envisioned future state. A compelling vision can ignite a passion in healthcare professionals to further their understanding of depression detection and appropriate intervention techniques, fostering personal and professional growth (Blackstone et al., 2022). Implementing Kotter's theory of change in healthcare settings can yield significant practical benefits. By following the eight-step procedure, healthcare companies can enhance patient outcomes and well-being. This is achieved by empowering staff members to identify depression and deliver prompt interventions. In the context of our Practice Change Project, the application of Kotter's change management theory can effectively address our research questions and objectives. It can guide the education program on PHQ9 and facilitate sustainable improvements in knowledge and practices related to depression screening among healthcare providers, leading to better patient outcomes (Brown et al., 2020). Kotter´s change model encompasses the following steps: John Kotter's Theory of Change management provides a framework for understanding how organizations can effectively implement and sustain change. (Graves et al., 2023). The theory consists of eight steps that guide organizations through initiating and managing change. These steps are: 1. Establishing a sense of urgency 2. Creating a guiding coalition 3. Developing a vision and strategy 4. Communicating the change vision 5. Empowering broad-based action 6. Generating short-term wins 7. Consolidating gains and producing more change 8. Anchoring new approaches in the culture Application of the Kotter´s Change Theory in a primary care setting. Step 1: Create a Sense of Urgency: Highlight the rising incidence of depression and its impact on patient outcomes. Present data on the benefits of early detection and treatment of depression through screening tools like the PHQ-9. Emphasize primary care providers' critical role in identifying and managing mental health issues, thereby improving overall patient care and outcomes. Step 2: Form a Powerful Coalition: Assemble a team of influential leaders, including primary care physicians, nurses, mental health specialists, and administrative staff, committed to improving depression screening and management. This coalition will guide the change process, providing direction and resources to ensure successful implementation. Step 3: Create a Vision for Change: Develop a clear vision that outlines the goal of integrating regular depression screening using the PHQ-9 into routine primary care practices. The vision should emphasize improved patient outcomes, enhanced care quality, and the importance of mental health in overall health management. Step 4: Communicate the Vision: Use multiple communication channels, such as meetings, newsletters, and training sessions, to share the vision with all healthcare staff. Ensure that everyone understands the rationale, objectives, and benefits of using the PHQ-9 tool for depression screening. Address concerns and encourage open dialogue to build support and mitigate resistance. Step 5: Empower Broad-Based Action: Provide training and resources to empower healthcare professionals at all levels to effectively use the PHQ-9 tool. Create an environment that encourages collaboration and innovation, allowing staff to take ownership of the change process. Remove any barriers, such as lack of time or resources, that might hinder implementation. Step 6: Generate Short-Term Wins: Identify and celebrate early successes in the implementation of the PHQ-9 tool. Share stories of patients who benefited from early depression detection and treatment, demonstrating the positive impact on patient care. Recognize and reward staff who actively contribute to the change process. Step 7: Consolidate Gains and Produce More Change: Build on the momentum of early successes by integrating the PHQ-9 tool into standard operating procedures and workflows. Continue to provide training and support to ensure consistent use. Address any remaining challenges and refine processes to enhance effectiveness. Expand the tool's use to other areas of practice where appropriate. Step 8: Anchor New Approaches in the Culture: Institutionalize the use of the PHQ-9 tool by embedding it into the organizational culture. Align policies, procedures, and incentives with the goal of routine depression screening. Reinforce the importance of mental health in patient care through ongoing education and training. Ensure the changes are sustained over time by continuously monitoring and evaluating the impact on patient outcomes. Timetable & Duration Week 1-2: Introduction and Initial Assessments • Introduce the program, its objectives, and the importance of prompt identification and treatment of depression. • Conduct an initial assessment to gauge the current knowledge level and identify specific areas of learning needs. During weeks 3-4, students will engage in independent study and participate in introductory group discussions. • Distribute educational materials and online courses. • Facilitate group discussions to share first views and experiences related to the topic . During weeks 5-6, the workshops will concentrate on experiential learning and problem-solving. • Conduct a thorough examination of case studies and participate in authentic role-playing scenarios. • Organize workshops focused on addressing prevalent difficulties, such as lack of knowledge on depression screening. Week 7 focuses on the process of getting feedback and offering peer support. • Schedule sessions to gather feedback on the learning process and the level of progress achieved. • Establish peer support groups to promote continuous learning and the sharing of best practices. Week 8 will consist of final evaluations and program evaluations. • Conduct a post-assessment to examine the knowledge that has been obtained. Evaluate the program's effectiveness and gather input to improve it in the future. Timetable for the activities Activity Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 Meet with faculty & preceptor. X X X X X X X X Introduction and Initial Assessment X X Introductory group discussions X X Experiential learning and problem-solving X X Feedback and peer support X Final assessments and program evaluation. X Project Process The project will take place in a primary care setting, chosen as a preventive approach, which is vital for addressing challenges like increased vulnerability to mental health issues and the need for effective screening tools. Licensed healthcare providers such as registered nurses, advanced registered nurse practitioners, physician assistants, and primary care physicians are often the first contact point with patients, making it crucial to enhance their knowledge and skills in managing and interpreting the PHQ-9 questionnaire for depression screening. Flyers (Annexed G) will be distributed at strategic points in the interior and exterior of the practice, as well as visible points such as the entrance of the offices and social spaces, to inform staff about the project. Participation in the study will be declared voluntary. This way, the interested staff members will attend a personal instructive activity in a conference room of the clinic to receive a more detailed description of the project´s activities. Once the potential participants are contacted, the project will be presented in the conference room of the clinic, allowing participants to ask questions and express their voluntary desire to participate. Thus, this project will be sampled through recruiting strategies. After receiving approval of the research protocol from AGMU-IRB, the principal investigator will meet with the clinic administrator on the first week to select the date on which the project will be announced in the clinic. Flyers will be placed in the main lobby to notify and advertise those interested in participating in the study. The principal investigator will personally meet with the participants who met the inclusion criteria and have expressed willingness to participate. The principal investigator will also invite the participants to attend the orientation session, wherein a discussion of the project including its objectives, confidentiality, and consent will be discussed with them. The preliminary orientation will be conducted in the private conference room of the clinic. Doors will be kept closed to maintain confidentiality. Eligible healthcare providers meeting the criteria will be invited to join, and informed consent will be obtained before participation. A pre-survey test will be conducted to assess baseline knowledge. The principal investigator (PI) will use strategies to preserve personal information confidentiality effectively. By using this first instrument (Annexed A), the PI will employ strategies to protect the confidentiality of personal information such as assigning code numbers to pair the same individual across two different application points (before and after). These numeric codes will be securely stored in a locked box in the PI’s office. Information about the participant will never be disclosed to outside parties. The PI and his mentor will keep all obtained information confidential for five years after the project's completion, with accessibility only to them. This information will be stored in sealed envelopes in a locked cabinet at the PI's office. After five years, it will be shredded and discarded. Further, the PI will destroy all information stored in external hard drive or electronic devices by smashing it with a blunt object. This project aims to help improve licensed healthcare providers’ understanding and use of the PHQ-9 questionnaire, ultimately enhancing patient care and reducing errors associated with poor mental health screening practices. The project is programmed to include 15 - 20 participants. After the interview to determine final eligibility. The inclusion criteria for the project participants includes licensed healthcare providers such as registered nurses, advanced registered nurse practitioners, physician assistants, and primary care practitioners who are currently practicing in the primary care setting, and who work full-time. The exclusion criteria included unlicensed healthcare providers, who are not currently practicing in the primary care setting, and who work part-time. The prinicpal investigator will personally meet with the participants who met the inclusion criteria and have expressed willingness to participate. The principal investigator will also invite the participants to attend the orientation session, wherein a discussion of the project including its objectives, confidentiality, and consent will be discussed with them. The preliminary orientation will be conducted in the private conference room of the clinic. Doors will be kept closed to maintain confidentiality. The informed consent form will contain relevant information on the project activities, what these activities will mean in the future screening of patients' depression, and what they mean for the prevention or timing of early diagnosis in the population. The informed consent will also include that the providers participation in this study is totally voluntary. Eligible participants have the right to decide whether to participate or not. If eligible providers decide to participate in this study, they have the right to withdraw at any time without penalty or retaliation. All these activities will take place in an assigned private office at the clinic, which is designed specifically for the project setting. The interview and acquiring informed consent signatures will take place in the clinic conference room, which will take all necessary precautions to maintain confidentiality. All information regarding the participant's identity will be kept private, secret, and permanently secured. Any document collected will be stored in the PI’s office in a locked drawer for five (5) years. Any data stored in the researcher’s encrypted USB will be kept in a locked drawer in the same PI’s office. They will be under the tutelage of the PI. Data collected during the project will be stored and preserved for five years in the PI’s office in a locked drawer and under the tutelage of the PI. Only the principal investigator and his mentor will have access to the information obtained. After five (5) years, the PI will destroy all related documentation using a paper shredder. All electronic storage devices will be destroyed using a blunt object. This project does not consider applying material incentives for the participants. The instruments for the pre- and post-evaluation are presented in the corresponding annexes. The collected data will be stored in EXCEL databases after a process of codification. The pre-intervention data will be analyzed to determine and orient the intervention's design, which will consider the gaps and principal lack of knowledge on PHQ-9 questionnaire management and interpretation. This first analytical step will consider descriptive statistics, highlighting the following topics: · What is known and what is unknown about PHQ-9 management and interpretation? · Who are the staff participants most in need of instruction, according to their designations, work positions, and responsibilities? After applying the tailored educative intervention, a post-test will be applied (Annexed) with a similar structure to the pretest. The pre and post questionnaire uses an ordinal Likert-like scale. The appropriate statistical test often depends on whether your data meets certain assumptions. The Wilcoxon signed-rank test, which is a non-parametric rank test will be used to examine the differences' distribution and determine the median differences between pre- and post-intervention scores. Respecting the stratification, it means that it is also important to know how and who were more benefit by the educative intervention among the different licensed healthcare providers that participated as declared in the project. The PI and his mentor will protect all the gathered information during the project's development and until five years after concluding these activities. Only the PI and his mentor have permission to access this information. Project Evaluation Plan Participants The inclusion criteria for the participants will be licensed healthcare providers such as registered nurses, advanced registered nurse practitioners, physician assistants, and primary care physicians; who are currently practicing in the primary care setting; who work full-time. Whereas the exclusion criteria will be unlicensed healthcare providers; who are not currently practicing in the primary care setting; who work part-time. Analysis Structure This work will be conducted using a quasi-experimental approach, pre and posttest design. Baseline knowledge regarding depression and PHQ9 depression screening tool will be obtained using a pre-test questionnaire. After providing an educational training intervention, a posttest will be administered. Both formative evaluation—which will be a final assessment at the conclusion of the eight-week intervention to assess the program's overall effectiveness—and summative evaluation—which will be a final assessment at the conclusion of the intervention to monitor progress and make some adjustments—will be part of the study. Evaluations will take place at the pre-intervention baseline, four weeks later, and eight weeks later. The PHQ-9 depression screening tool is a reliable and validated instrument that is extensively used in clinical practice; the knowledge assessment tool will be standardized and verified as well. Planned Evaluation Data Analysis The demographics and starting levels of expertise of the participants will be summed up using descriptive statistics. Application of inferential statistics will be made, namely independent t-tests to compare post-intervention scores between the intervention and comparison groups and paired t-tests to compare pre- and post-intervention knowledge scores within the intervention group. Given the small volume of participants, alternative non-parametric statistic tests such as the Willcoxon signed rank test could be applied. We shall compute effect sizes to ascertain the program's effect. To control extraneous factors, attempts will be made to match the intervention and comparison groups according to comparable traits, such as years of experience and position in the practice. Standardized training materials and techniques will guarantee uniformity, and attendance will be tracked to ensure that every member of the intervention group shows up for every session. Getting informed permission, guaranteeing secrecy, getting ethics clearance, and adhering to HIPAA rules will all be part of safeguarding human rights and health information privacy. Barriers and Facilitators Barriers: Implementing a PHQ-9 education program for licensed healthcare such as registered nurses, advanced registered nurse practitioners, physician assistants, and primary care physicians in a primary care context may face reluctance to change due to practitioners' commitment to current depression screening approaches and concerns about increased workload. Scheduling issues may emerge due to licensed healthcare providers such as registered nurses, advanced registered nurse practitioners’, physician assistants’, and primary care physicians’ busy schedules, making completing training sessions difficult. Furthermore, there may be a lack of understanding or awareness of the PHQ-9 tool's benefits, resulting in a reluctance to adopt the new strategy. Facilitators: To improve the project's performance, capitalizing on the growing acknowledgment of the importance of mental health in overall patient care can assist build support for better depression screening procedures. Leadership endorsement and active participation can increase employee engagement. Clear, evidence-based statistics confirming the usefulness of the PHQ-9 instrument might help to demonstrate actual advantages and overcome reluctance. Integrating training into regular professional development and providing continuing education credits might encourage participation. Creating an interactive, practical training program, as well as encouraging open communication and feedback, can help to accelerate the shift. Additionally, having mental health specialists or advocates within the practice to provide continuing support might help to maintain the shift over time. Supplementary materials Appendix A: Test of Knowledge Assessment (Pre-test) • A selection of inquiries encompassing subjects outlined in the PHQ-9 criteria. Appendix B: Test of Knowledge Assessment (Post-Test) Appendix C: Test on the technical aspects of the PHQ-9. Interpreting the results. Appendix D: The Observation Checklist is a tool for monitoring and recording participants' involvement and active participation levels. Appendix E: Informed Consent Form • A comprehensive consent form that provides detailed information on the study, including the potential risks, benefits, and measures taken to ensure confidentiality. Appendix F: Site Consent Appendix G: Flyer Implementing the education program on the PHQ-9 in a primary care context requires a systematic approach to identifying the problem, evaluating the willingness to make a change, facilitating the change process, and guaranteeing long-term effectiveness. By following these instructions, healthcare professionals can enhance their understanding and utilization of the PHQ-9 for depression screening, leading to better patient results. The evaluation plan for this project aims to thoroughly analyze the educational intervention's effect on licensed healthcare providers’ understanding of depression screening using the PHQ-9. By implementing a thorough assessment design and maintaining strong data protection and ethical standards, the project intends to provide significant insights and improvements in clinical practice. Plans for Dissemination The practice change project's findings will be disseminated to ensure that those who can use them do so to maximize the project's advantages. The results dissemination process considers the target audiences and the contexts in which the findings must be interpreted and put into practice (Ashcraft et al., 2020). To share these results and promote the extension and sustainability of the experience, the results will be disseminated in attractive spaces according to the participants' interests. In this way, the project will be initially defended and shared through a PowerPoint presentation on the premises of the Ana G Mendez University that formed us. Still, spaces will be sought to show the findings at relevant conferences, workshops, and seminars to engage with healthcare providers and stakeholders. Additionally, it is considering publishing the results in peer-reviewed journals and creating accessible content such as webinars, infographics, and blog posts to reach a broader audience. These spaces will emphasize practical recommendations for integrating the PHQ-9 tool into routine clinical practice, highlighting its benefits for patient care and mental health outcomes. The principal researcher will be attentive to the conferences launched shortly, such as the NCHS Webinar: A Look at Suicide Rates in Puerto Rico, providing a convenient space to share the results (Dockter et al., 2021). This activity will improve publicity and increase the possibility of uptake and evidence translation into policies. Other forms of dissemination will be through flyers, manuals, summary sheets, posters, and pamphlets (Ross-Hellauer et al., 2020). Additionally, the institution will be asked to highlight the practice change effort in its newsletters and online content. Participants will also get a letter of appreciation explaining the project's findings (Hu et al., 2022). A roundtable presentation initiative will start discussions on the practice change initiative. There will be roundtable talks with the clinic staff and management about where the project will be carried out. The conclusions of the practice change that can be implemented in the organization are highlighted in this presentation (Phillips & Klein, 2023). Newsletters will be used as another medium to share results. PowerPoint presentations, posters, hard copies for the library, and magazine publishing are other methods for sharing the results among academics. The findings will be presented to classmates, university lecturers, and project site practitioners through PowerPoint presentations, and a synthesis will be exhibited and e-poster in the University Gallery. A hard copy of the Change Project report will be available at the University library. Also, the principal researcher will seek to publish these results in peer-reviewed Journals such as the Journal of Mental Health, an international forum for the latest research in the mental health field. To this end, the journal's specific guidelines will be observed. Peer-reviewed, original articles on clinical and translational research into Mental Health and particularly on Depression are the primary publication strategy for this magazine. The papers in this journal are primarily about identifying, classifying, and managing depressive symptoms and choosing the corresponding treatment or if required, derivation to a specialist treating Mood Disorders accordingly (Constantini et al., 2021). The principal researcher will seek other appropriate Journals that fit the characteristics of the research already done. In this sense, Journals dedicated to continuing education in health and journals dedicated to primary care issues are highly recommended. To timely detect mood disorders, particularly depression diagnosis and proper management of patients with depressive disorders among this demographic, this research seeks to ascertain whether pairing an educational meeting with the principal aspect and how important it is to implement the routine assessment of depression using PHQ-9 tool. This change project pursues overcoming the knowledge barriers that impede the early diagnosis of “hidden depression” in the population in primary care settings. The literature review already finished advises about the importance of screening for depression and demonstrates that the use of PHQ-9 as part of the normal encounter with patients is useful to detect and treat depression accordingly, even if it is not severe. Enhancing the mood in the patients always will be helpful for reaching better responses to the affections they are treated with. Implementation The central point of this Change Project is to improve healthcare practitioners' comprehension and application of the Patient Health Questionnaire (PHQ-9) for clinical practice depression screening. Using the Kotter Model of Change to guide the actions of this project, it was hypothesized that through targeted education and training, licensed healthcare providers will demonstrate increased awareness, proficiency, and utilization of the PHQ-9 for screening depression in clinical practice (Portela dos Santos et al., 2022). This change project focused on carrying out an educational intervention to improve the knowledge and performance of primary care staff regarding the application and interpretation of the PHQ-9, an instrument to detect depression in the general population. The project justified this need based on the previous knowledge, recognized in the reviewed literature, of the importance of detecting the presence and novelty of depression in patients who come to primary care even for reasons other than those associated with disorders of their mental state (mood). It is widely recognized that the presence of existing depression or depression resulting from a specific condition, whether transient or chronic, is an important element in the prognosis of patient improvement (Remes et al., 2021). Furthermore, it is hypothesized that early detection and treatment of depression will lead to improved patient outcomes, reduced risk of complications, and ultimately enhanced quality of life. The vision of the project involved familiarizing primary care workers with the use and interpretation of the PHQ-9, for which a before-after type of research was designed, where an instrument was applied to analyze the state of knowledge at baseline (before the intervention), apply an educational intervention reinforcing the most deficient aspects identified in the pre-test and re-evaluate the level of confidence that this learning reported to the participants (post-test) for the practical application after receiving this educational intervention. To achieve this goal an interventional educational activity was designed. After the participants were selected through proper interviews to meet eligibility and after the informed consent was signed, the implementation process of the project started. The step-by-step activities in this implementation stage are as follows: Week 1-2: Introduction and Initial Assessments • Introduce the program, its objectives, and the importance of prompt identification and treatment of depression. • Conduct an initial assessment to gauge the current knowledge level and identify specific areas of learning needs. Weeks 3-4: Participants will engage in independent study and participate in introductory group discussions. • Distribute educational materials and online courses. • Facilitate group discussions to share first views and experiences related to the topic . Weeks 5-6: The workshops will concentrate on experiential learning and problem-solving. • Conduct a thorough examination of case studies and participate in authentic role-playing scenarios. • Organize workshops focused on addressing prevalent difficulties, such as lack of knowledge on depression screening. Week 7: focuses on the process of getting feedback and offering peer support. • Schedule sessions to gather feedback on the learning process and the level of progress achieved. • Establish peer support groups to promote continuous learning and the sharing of best practices. Week 8: Final evaluations and program evaluations. • Conduct a post-assessment to examine the knowledge that has been obtained. · Evaluate the program's effectiveness and gather input to improve it in the future. Current stage of the project implementation. As stated in the methodology section, this project followed a pre-post design centered on Kotter's theory of change, highly recommended for didactic approach in medical subjects (Haas et al. 2019). At the time of submitting the implementation report, the following steps were taken: 1- Selection of participants: workers from a primary care setting who met the inclusion criteria (20). 2- Application for the pre-test in week 2. 3- Coding of variables and creation of the EXCEL database with the initial information. 4- Descriptive analysis of the pre-test. Setting up the educational intervention (adjustments according to pre-test results). 5- Development of the educational sessions (3 weeks) 6- Feedback and consolidation 7- Application for the post-test. Introduction of the coded results in the EXCEL database. Pending activities 1- Development of the descriptive analysis of the post-test. 2- Inferential analysis. 3- Discussion of the results. To guarantee the confidentiality of the information, the PI used numerical codes that only he had access to and that allowed the individual pairing of the pre-post instruments in order to obtain contrasts of the group against itself but also to obtain them individually, that is, the person against themselves before and after the educational intervention. Once the pre- and post-test stages were completed, all the data were stored in a file in SPSS for preparation for the inferential analysis phase. At this stage, the measurement levels of the variables and the coding of the variables that required it were recorded. In this stage of implementation, the primary information has been completed and the data is ready for inferential statistic analysis and the discussion of the results. Conclusion This practice change project aims to help enhance the knowledge and abilities of licensed healthcare providers such as registered nurses, advanced registered nurse practitioners, physician assistants, and primary care physicians in assessing depression levels in the general population by applying the PHQ-9 questionnaire. Because it offers patients a uniform way to be assessed and monitored for depression, the PHQ-9 depression screening tool is crucial in primary care settings. Often the first point of contact for patients with mental health problems, licensed healthcare providers should be able to handle and interpret PHQ-9 results properly. With the PHQ-9 used correctly, depression can be identified early, treatments can be started quickly, and patient outcomes can be better. Improving the knowledge and abilities of licensed healthcare providers to use this tool guarantees evidence-based, high-quality treatment, lowers healthcare expenses by averting complications, and resolves inequalities in mental health. Teaching licensed healthcare providers, the PHQ-9 will improve patient well-being generally and mental health management. Participants in this initiative were licensed healthcare providers who work full-time in a primary care context and are directly engaged in patient care. Once a brochure outlining the goal of the inquiry was distributed, potential participants were chosen from those who met the inclusion criteria and consented to participate. Currently all stages of implementation were completed and the primary data collected is ready for the application of the inferential statistical analysis and the discussion of the results. Statistical Analysis Objectives Objective 1: Assess the baseline knowledge level of licensed healthcare providers regarding depression screening using the Patient Health Questionnaire 9 (PHQ9) before implementing the education program. Objective 2: Implement an educational program for licensed healthcare on the Patient Health Questionnaire 9 (PHQ9), focusing on understanding the tool's administration, interpretation, and implications for depression screening. Objective 3: Evaluate the effectiveness of the educational program by comparing the post-intervention knowledge level of licensed healthcare providers regarding depression screening using the PHQ9 with their baseline knowledge level, measured at the end of an 8-week period. PICOT Question For healthcare providers (P), does an education program on the Patient Health Questionnaire 9 (PHQ9) (I), compared with no education program (C), increase knowledge on screening depression (O) over a period of 8 weeks (T)? Hypothesis: It is hypothesized that through targeted education and training, licensed healthcare providers will demonstrate increased awareness, proficiency, and utilization of the PHQ-9 for screening depression in clinical practice. Furthermore, it is hypothesized that early detection and treatment of depression will lead to improved patient outcomes, reduced risk of complications, and ultimately enhanced quality of life. Analysis of the Frequency Table This data represents a pre- and post-intervention comparison regarding familiarity, confidence, likelihood, and agreement with using the PHQ-9 Depression Screening Tool. Below is an analysis of the trends and insights: General Observations: 1. Familiarity with PHQ-9 Depression Screening Tool (PRE-Q1 vs. POS-Q1) · Pre-Intervention: · Most participants (40%) rated themselves at a moderate level of familiarity (scores 2 and 3 combined). · Only 5% rated their familiarity as very high (score 5). · Cumulative higher familiarity (scores 4 and 5) was 30%. · Post-Intervention: · Familiarity significantly increased, with 40% rating themselves as very familiar (score 5). · Cumulative familiarity at higher levels (scores 4 and 5) jumped to 60%, indicating improved familiarity post-intervention. Insight: The intervention appears to have had a positive impact, as participants showed increased self-reported familiarity with the PHQ-9 tool. 2. Confidence in Assessing and Managing Depression (PRE-Q2 vs. POS-Q2) · Pre-Intervention: · Most participants reported moderate confidence (40% rated themselves as 3). · Only 15% reported high confidence (score 4). · Post-Intervention: · Confidence levels shifted upwards. The percentage of participants with high confidence (scores 4 and 5 combined) rose from 15% to 35%. · Moderate confidence ratings (score 3) decreased slightly, indicating a movement toward higher confidence levels. Insight: Confidence in managing depression improved after the intervention, suggesting increased capability or comfort with using the PHQ-9 tool. 3. Likelihood of Assisting Patients with PHQ-9 (PRE-Q3 vs. POS-Q3) · Pre-Intervention: · Moderate likelihood (score 3) was the most common response (35%). · High likelihood (scores 4 and 5 combined) reached 50%. · Post-Intervention: · High likelihood responses (scores 4 and 5 combined) increased to 55%. · Moderate likelihood ratings (score 3) remained at 30%, indicating an upward trend but less pronounced improvement compared to familiarity and confidence. Insight: While there was some increase in participants' willingness to assist patients with the PHQ-9 tool, this area did not show as strong a change as familiarity or confidence. 4. Agreement on the Usefulness of the PHQ-9 Tool (PRE-Q4 vs. POS-Q4) · Pre-Intervention: · Agreement was moderate, with 25% at score 3 and 20% at score 4. · Only 15% strongly agreed (score 5). · Post-Intervention: · Agreement shifted upwards. The majority (42.1%) rated agreement at score 3, and 31.6% rated it at score 4. · However, strong agreement (score 5) decreased slightly to 5.3%. Insight: While the intervention improved moderate levels of agreement, it did not significantly increase the proportion of participants who strongly agreed with the usefulness of the PHQ-9 tool. This could indicate lingering uncertainty about its application. Conclusion: 1. Positive Trends: · Significant improvements were seen in familiarity (Q1) and confidence (Q2), indicating that the intervention effectively addressed these aspects. · Participants were more likely to assist patients (Q3) after the intervention, though the improvement was less pronounced than in Q1 and Q2. 2. Challenges: · Agreement on the usefulness of the PHQ-9 tool (Q4) improved only moderately, and strong agreement declined slightly post-intervention. This suggests that while participants recognize its value, they may not be fully convinced of its effectiveness in practice. 3. Participation Rates: · A consistent 75.3% of the data is missing, which could affect the reliability of these findings. Efforts to engage more participants might yield more robust conclusions. Crosstab Analyses Crosstab 1: Familiarity with PHQ9 Depression Screening Tool · PRE vs. POST Familiarity: · There is a noticeable increase in familiarity levels post-intervention, as evidenced by a shift toward higher familiarity ratings (4 and 5). For instance: · PRE-Q1 familiarity rating of 3 (50% within PRE-Q1) largely corresponds to POST-Q1 ratings of 4 or 5. · Participants who initially had low familiarity (PRE-Q1 ratings of 1 or 2) generally show improvement post-intervention, with many moving to higher ratings. · Chi-Square Test: · The Chi-Square value (17.867, df=16, p=0.332) suggests no statistically significant association between pre- and post-intervention familiarity levels. This may result from the small sample size and the uneven distribution of data across the cells. Crosstab 2: Confidence in Managing Patients with Depression · PRE vs. POST Confidence: · Participants' confidence ratings show a general improvement: · PRE-Q2 confidence levels of 1 or 2 shift to higher POST-Q2 levels (e.g., 4 or 5). · A notable increase in the percentage of participants at confidence level 3 post-intervention (40% of the total). · The distribution of PRE-Q2 levels indicates that participants were initially more diverse in their confidence, but post-intervention confidence seems to converge toward higher ratings. · Chi-Square Test: · The Pearson Chi-Square value (14.486, df=12, p=0.271) indicates no statistically significant relationship between pre- and post-confidence ratings. However, the trend toward higher confidence levels post-intervention is worth noting. Crosstab 3: Likelihood of Assisting Patients with PHQ9 Screening · PRE vs. POST Likelihood: · Most participants shifted toward higher likelihood ratings (e.g., 3, 4, or 5 post-intervention). · For instance, PRE-Q3 ratings of 1 and 2 (15% of total) moved to ratings of 4 or 5 (45% of total) post-intervention. · Chi-Square Test: · The Chi-Square value (13.690, df=12, p=0.321) again suggests no statistically significant relationship. The small sample size and low counts in some cells may contribute to this finding. Crosstab 4: Agreement on Incorporating PHQ9 Screening · PRE vs. POST Agreement: · Agreement levels are more evenly distributed pre-intervention but shift toward higher agreement post-intervention (ratings of 4 or 5). · PRE-Q4 ratings of 1 or 2 (37%) show a strong trend of shifting to higher ratings post-intervention. · Chi-Square Test: · The Chi-Square value (p=0.321) suggests no statistically significant association between pre- and post-agreement levels. However, the trend toward increased agreement supports the intervention's positive influence. General Observations 1. Positive Trends: · Across all measures, there are clear trends toward higher ratings post-intervention, indicating improvements in familiarity, confidence, likelihood of using the tool, and agreement with its usefulness. 2. Statistical Significance: · While the trends are evident, the lack of statistical significance (p > 0.05) in all Chi-Square tests highlights limitations due to:
· Small sample size (N=20).
· Uneven distribution of responses across categories, leading to low expected counts in cells.
3.
Future Considerations:

· Increase sample size to improve the robustness of statistical tests.
· Consider collapsing response categories (e.g., combine ratings 4 and 5) to address low expected counts and improve test validity.
4.
Impact of Intervention:

· Despite the lack of statistical significance, the observed trends suggest the intervention effectively increased familiarity, confidence, likelihood of use, and agreement with the PHQ9 tool. These trends can be further explored with larger samples and complementary qualitative analyses.

APPENDIX A

Frequency Table

PRE-Q1-To what extent are you familiar with the PHQ9 Depression Screening tool?

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

1

2

2,5

10,0

10,0

2

6

7,4

30,0

40,0

3

6

7,4

30,0

70,0

4

5

6,2

25,0

95,0

5

1

1,2

5,0

100,0

Total

20

24,7

100,0

Missing

System

61

75,3

Total

81

100,0

POS-Q1-To what extent are you familiar with the PHQ9 Depression Screening tool?

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

1

1

1,2

5,0

5,0

2

2

2,5

10,0

15,0

3

5

6,2

25,0

40,0

4

4

4,9

20,0

60,0

5

8

9,9

40,0

100,0

Total

20

24,7

100,0

Missing

System

61

75,3

Total

81

100,0

PRE-Q2-How confident are you in assessing and managing patients with depression?

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

1

5

6,2

25,0

25,0

2

4

4,9

20,0

45,0

3

8

9,9

40,0

85,0

4

3

3,7

15,0

100,0

Total

20

24,7

100,0

Missing

System

61

75,3

Total

81

100,0

POS-Q2-How confident are you in assessing and managing patients with depression?

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

1

3

3,7

15,0

15,0

2

4

4,9

20,0

35,0

3

6

7,4

30,0

65,0

4

3

3,7

15,0

80,0

5

4

4,9

20,0

100,0

Total

20

24,7

100,0

Missing

System

61

75,3

Total

81

100,0

PRE-Q3-How likely are you to assist your patients in recognizing the signs and symptoms of depression using the PHQ-9 screening tool?

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

1

1

1,2

5,0

5,0

2

2

2,5

10,0

15,0

3

7

8,6

35,0

50,0

4

6

7,4

30,0

80,0

5

4

4,9

20,0

100,0

Total

20

24,7

100,0

Missing

System

61

75,3

Total

81

100,0

POS-Q3-How likely are you to assist your patients in recognizing the signs and symptoms of depression using the PHQ-9 screening tool?

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

2

3

3,7

15,0

15,0

3

6

7,4

30,0

45,0

4

8

9,9

40,0

85,0

5

3

3,7

15,0

100,0

Total

20

24,7

100,0

Missing

System

61

75,3

Total

81

100,0

PRE-Q4-Do you agree that incorporating PHQ(9 depression screening tool will assist you in managing patients with depression?

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

1

2

2,5

10,0

10,0

2

6

7,4

30,0

40,0

3

5

6,2

25,0

65,0

4

4

4,9

20,0

85,0

5

3

3,7

15,0

100,0

Total

20

24,7

100,0

Missing

System

61

75,3

Total

81

100,0

POS-Q4-Do you agree that incorporating PHQ(9 depression screening tool will assist you in managing patients with depression?

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

2

4

4,9

21,1

21,1

3

8

9,9

42,1

63,2

4

6

7,4

31,6

94,7

5

1

1,2

5,3

100,0

Total

19

23,5

100,0

Missing

System

62

76,5

Total

81

100,0

Crosstabs Gender vs Knowledge

Crosstabs

Crosstabs

PRE-Q1-To what extent are you familiar with the PHQ9 Depression Screening tool? * POS-Q1-To what extent are you familiar with the PHQ9 Depression Screening tool? Crosstabulation

POS-Q1-To what extent are you familiar with the PHQ9 Depression Screening tool?

Total

1

2

3

4

5

PRE-Q1-To what extent are you familiar with the PHQ9 Depression Screening tool?

1

Count

0

1

0

0

1

2

% within PRE-Q1-To what extent are you familiar with the PHQ9 Depression Screening tool?

0,0%

50,0%

0,0%

0,0%

50,0%

100,0%

% within POS-Q1-To what extent are you familiar with the PHQ9 Depression Screening tool?

0,0%

50,0%

0,0%

0,0%

12,5%

10,0%

% of Total

0,0%

5,0%

0,0%

0,0%

5,0%

10,0%

2

Count

1

1

3

0

1

6

% within PRE-Q1-To what extent are you familiar with the PHQ9 Depression Screening tool?

16,7%

16,7%

50,0%

0,0%

16,7%

100,0%

% within POS-Q1-To what extent are you familiar with the PHQ9 Depression Screening tool?

100,0%

50,0%

60,0%

0,0%

12,5%

30,0%

% of Total

5,0%

5,0%

15,0%

0,0%

5,0%

30,0%

3

Count

0

0

0

2

4

6

% within PRE-Q1-To what extent are you familiar with the PHQ9 Depression Screening tool?

0,0%

0,0%

0,0%

33,3%

66,7%

100,0%

% within POS-Q1-To what extent are you familiar with the PHQ9 Depression Screening tool?

0,0%

0,0%

0,0%

50,0%

50,0%

30,0%

% of Total

0,0%

0,0%

0,0%

10,0%

20,0%

30,0%

4

Count

0

0

2

2

1

5

% within PRE-Q1-To what extent are you familiar with the PHQ9 Depression Screening tool?

0,0%

0,0%

40,0%

40,0%

20,0%

100,0%

% within POS-Q1-To what extent are you familiar with the PHQ9 Depression Screening tool?

0,0%

0,0%

40,0%

50,0%

12,5%

25,0%

% of Total

0,0%

0,0%

10,0%

10,0%

5,0%

25,0%

5

Count

0

0

0

0

1

1

% within PRE-Q1-To what extent are you familiar with the PHQ9 Depression Screening tool?

0,0%

0,0%

0,0%

0,0%

100,0%

100,0%

% within POS-Q1-To what extent are you familiar with the PHQ9 Depression Screening tool?

0,0%

0,0%

0,0%

0,0%

12,5%

5,0%

% of Total

0,0%

0,0%

0,0%

0,0%

5,0%

5,0%

Total

Count

1

2

5

4

8

20

% within PRE-Q1-To what extent are you familiar with the PHQ9 Depression Screening tool?

5,0%

10,0%

25,0%

20,0%

40,0%

100,0%

% within POS-Q1-To what extent are you familiar with the PHQ9 Depression Screening tool?

100,0%

100,0%

100,0%

100,0%

100,0%

100,0%

% of Total

5,0%

10,0%

25,0%

20,0%

40,0%

100,0%

Chi-Square Tests

Value

df

Asymptotic Significance (2-sided)

Pearson Chi-Square

17,867a

16

,332

Likelihood Ratio

20,732

16

,189

Linear-by-Linear Association

2,550

1

,110

N of Valid Cases

20

a. 25 cells (100,0%) have expected count less than 5. The minimum expected count is ,05.

Crosstabs

PRE-Q2-How confident are you in assessing and managing patients with depression? * POS-Q2-How confident are you in assessing and managing patients with depression? Crosstabulation

POS-Q2-How confident are you in assessing and managing patients with depression?

Total

1

2

3

4

5

PRE-Q2-How confident are you in assessing and managing patients with depression?

1

Count

1

0

1

1

2

5

% within PRE-Q2-How confident are you in assessing and managing patients with depression?

20,0%

0,0%

20,0%

20,0%

40,0%

100,0%

% within POS-Q2-How confident are you in assessing and managing patients with depression?

33,3%

0,0%

16,7%

33,3%

50,0%

25,0%

% of Total

5,0%

0,0%

5,0%

5,0%

10,0%

25,0%

2

Count

1

0

2

1

0

4

% within PRE-Q2-How confident are you in assessing and managing patients with depression?

25,0%

0,0%

50,0%

25,0%

0,0%

100,0%

% within POS-Q2-How confident are you in assessing and managing patients with depression?

33,3%

0,0%

33,3%

33,3%

0,0%

20,0%

% of Total

5,0%

0,0%

10,0%

5,0%

0,0%

20,0%

3

Count

0

4

3

0

1

8

% within PRE-Q2-How confident are you in assessing and managing patients with depression?

0,0%

50,0%

37,5%

0,0%

12,5%

100,0%

% within POS-Q2-How confident are you in assessing and managing patients with depression?

0,0%

100,0%

50,0%

0,0%

25,0%

40,0%

% of Total

0,0%

20,0%

15,0%

0,0%

5,0%

40,0%

4

Count

1

0

0

1

1

3

% within PRE-Q2-How confident are you in assessing and managing patients with depression?

33,3%

0,0%

0,0%

33,3%

33,3%

100,0%

% within POS-Q2-How confident are you in assessing and managing patients with depression?

33,3%

0,0%

0,0%

33,3%

25,0%

15,0%

% of Total

5,0%

0,0%

0,0%

5,0%

5,0%

15,0%

Total

Count

3

4

6

3

4

20

% within PRE-Q2-How confident are you in assessing and managing patients with depression?

15,0%

20,0%

30,0%

15,0%

20,0%

100,0%

% within POS-Q2-How confident are you in assessing and managing patients with depression?

100,0%

100,0%

100,0%

100,0%

100,0%

100,0%

% of Total

15,0%

20,0%

30,0%

15,0%

20,0%

100,0%

Chi-Square Tests

Value

df

Asymptotic Significance (2-sided)

Pearson Chi-Square

14,486a

12

,271

Likelihood Ratio

19,144

12

,085

Linear-by-Linear Association

,309

1

,578

N of Valid Cases

20

a. 20 cells (100,0%) have expected count less than 5. The minimum expected count is ,45.

Crosstabs

PRE-Q3-How likely are you to assist your patients in recognizing the signs and symptoms of depression using the PHQ-9 screening tool? * POS-Q3-How likely are you to assist your patients in recognizing the signs and symptoms of depression using the PHQ-9 screening tool? Crosstabulation

POS-Q3-How likely are you to assist your patients in recognizing the signs and symptoms of depression using the PHQ-9 screening tool?

Total

2

3

4

5

PRE-Q3-How likely are you to assist your patients in recognizing the signs and symptoms of depression using the PHQ-9 screening tool?

1

Count

0

0

1

0

1

% within PRE-Q3-How likely are you to assist your patients in recognizing the signs and symptoms of depression using the PHQ-9 screening tool?

0,0%

0,0%

100,0%

0,0%

100,0%

% within POS-Q3-How likely are you to assist your patients in recognizing the signs and symptoms of depression using the PHQ-9 screening tool?

0,0%

0,0%

12,5%

0,0%

5,0%

% of Total

0,0%

0,0%

5,0%

0,0%

5,0%

2

Count

0

0

1

1

2

% within PRE-Q3-How likely are you to assist your patients in recognizing the signs and symptoms of depression using the PHQ-9 screening tool?

0,0%

0,0%

50,0%

50,0%

100,0%

% within POS-Q3-How likely are you to assist your patients in recognizing the signs and symptoms of depression using the PHQ-9 screening tool?

0,0%

0,0%

12,5%

33,3%

10,0%

% of Total

0,0%

0,0%

5,0%

5,0%

10,0%

3

Count

1

2

3

1

7

% within PRE-Q3-How likely are you to assist your patients in recognizing the signs and symptoms of depression using the PHQ-9 screening tool?

14,3%

28,6%

42,9%

14,3%

100,0%

% within POS-Q3-How likely are you to assist your patients in recognizing the signs and symptoms of depression using the PHQ-9 screening tool?

33,3%

33,3%

37,5%

33,3%

35,0%

% of Total

5,0%

10,0%

15,0%

5,0%

35,0%

4

Count

0

4

1

1

6

% within PRE-Q3-How likely are you to assist your patients in recognizing the signs and symptoms of depression using the PHQ-9 screening tool?

0,0%

66,7%

16,7%

16,7%

100,0%

% within POS-Q3-How likely are you to assist your patients in recognizing the signs and symptoms of depression using the PHQ-9 screening tool?

0,0%

66,7%

12,5%

33,3%

30,0%

% of Total

0,0%

20,0%

5,0%

5,0%

30,0%

5

Count

2

0

2

0

4

% within PRE-Q3-How likely are you to assist your patients in recognizing the signs and symptoms of depression using the PHQ-9 screening tool?

50,0%

0,0%

50,0%

0,0%

100,0%

% within POS-Q3-How likely are you to assist your patients in recognizing the signs and symptoms of depression using the PHQ-9 screening tool?

66,7%

0,0%

25,0%

0,0%

20,0%

% of Total

10,0%

0,0%

10,0%

0,0%

20,0%

Total

Count

3

6

8

3

20

% within PRE-Q3-How likely are you to assist your patients in recognizing the signs and symptoms of depression using the PHQ-9 screening tool?

15,0%

30,0%

40,0%

15,0%

100,0%

% within POS-Q3-How likely are you to assist your patients in recognizing the signs and symptoms of depression using the PHQ-9 screening tool?

100,0%

100,0%

100,0%

100,0%

100,0%

% of Total

15,0%

30,0%

40,0%

15,0%

100,0%

Chi-Square Tests

Value

df

Asymptotic Significance (2-sided)

Pearson Chi-Square

13,690a

12

,321

Likelihood Ratio

15,267

12

,227

Linear-by-Linear Association

2,741

1

,098

N of Valid Cases

20

a. 20 cells (100,0%) have expected count less than 5. The minimum expected count is ,15.

Crosstabs

PRE-Q4-Do you agree that incorporating PHQ(9 depression screening tool will assist you in managing patients with depression? * POS-Q4-Do you agree that incorporating PHQ(9 depression screening tool will assist you in managing patients with depression? Crosstabulation

POS-Q4-Do you agree that incorporating PHQ(9 depression screening tool will assist you in managing patients with depression?

Total

2

3

4

5

PRE-Q4-Do you agree that incorporating PHQ(9 depression screening tool will assist you in managing patients with depression?

1

Count

0

1

1

0

2

% within PRE-Q4-Do you agree that incorporating PHQ(9 depression screening tool will assist you in managing patients with depression?

0,0%

50,0%

50,0%

0,0%

100,0%

% within POS-Q4-Do you agree that incorporating PHQ(9 depression screening tool will assist you in managing patients with depression?

0,0%

12,5%

16,7%

0,0%

10,5%

% of Total

0,0%

5,3%

5,3%

0,0%

10,5%

2

Count

2

2

0

1

5

% within PRE-Q4-Do you agree that incorporating PHQ(9 depression screening tool will assist you in managing patients with depression?

40,0%

40,0%

0,0%

20,0%

100,0%

% within POS-Q4-Do you agree that incorporating PHQ(9 depression screening tool will assist you in managing patients with depression?

50,0%

25,0%

0,0%

100,0%

26,3%

% of Total

10,5%

10,5%

0,0%

5,3%

26,3%

3

Count

1

2

2

0

5

% within PRE-Q4-Do you agree that incorporating PHQ(9 depression screening tool will assist you in managing patients with depression?

20,0%

40,0%

40,0%

0,0%

100,0%

% within POS-Q4-Do you agree that incorporating PHQ(9 depression screening tool will assist you in managing patients with depression?

25,0%

25,0%

33,3%

0,0%

26,3%

% of Total

5,3%

10,5%

10,5%

0,0%

26,3%

4

Count

1

2

1

0

4

% within PRE-Q4-Do you agree that incorporating PHQ(9 depression screening tool will assist you in managing patients with depression?

25,0%

50,0%

25,0%

0,0%

100,0%

% within POS-Q4-Do you agree that incorporating PHQ(9 depression screening tool will assist you in managing patients with depression?

25,0%

25,0%

16,7%

0,0%

21,1%

% of Total

5,3%

10,5%

5,3%

0,0%

21,1%

5

Count

0

1

2

0

3

% within PRE-Q4-Do you agree that incorporating PHQ(9 depression screening tool will assist you in managing patients with depression?

0,0%

33,3%

66,7%

0,0%

100,0%

% within POS-Q4-Do you agree that incorporating PHQ(9 depression screening tool will assist you in managing patients with depression?

0,0%

12,5%

33,3%

0,0%

15,8%

% of Total

0,0%

5,3%

10,5%

0,0%

15,8%

Total

Count

4

8

6

1

19

% within PRE-Q4-Do you agree that incorporating PHQ(9 depression screening tool will assist you in managing patients with depression?

21,1%

42,1%

31,6%

5,3%

100,0%

% within POS-Q4-Do you agree that incorporating PHQ(9 depression screening tool will assist you in managing patients with depression?

100,0%

100,0%

100,0%

100,0%

100,0%

% of Total

21,1%

42,1%

31,6%

5,3%

100,0%

Chi-Square Tests

Value

df

Asymptotic Significance (2-sided)

Pearson Chi-Square

8,022a

12

,783

Likelihood Ratio

10,018

12

,614

Linear-by-Linear Association

,151

1

,697

N of Valid Cases

19

a. 20 cells (100,0%) have expected count less than 5. The minimum expected count is ,11.

GRAPHICS:

Interpret Results

Levels Using PHQ-9 Depression Screening Tool

Depression continues to be a prominent health issue in the world today, meaning that it is vital to have accurate methods for screening and knowledgeable practitioners (Blackstone et al., 2022). The Patient Health Questionnaire-9 (PHQ-9) has been widely used in the real world and has been identified as suitable for depression screening (Ford et al., 2020). This manuscript seeks to explain the findings of an educational intervention to increase the knowledge and self-efficiency of healthcare professionals in using PHQ-9 through the use of statistics and graphical data display.

Statistical Tools Used

Self-administered questionnaires, descriptive statistics, frequency tables and Chi-square cross-tabulation summarizing healthcare practitioners’ familiarity, confidence, likelihood to assist patients and level of agreement on the usefulness of the PHQ-9 (Levis et al., 2019). Crosstab analysis helped identify the changes in the responses, and the Chi-Square test helped determine the statistical significance of the changes observed in the responses.

INTERPRETATION OF FINDINGS

Familiarity with PHQ-9 (PRE-Q1 vs. POS-Q1)

· The degree of familiarity before the intervention was relatively low: 40% of participants scored 2 or 3, and only 5% scored 5.
· After the intervention, 40% responded with a rating of very familiar (rating 5), and 60% were highly familiar (rating 4 and 5) with the newly acquired knowledge.
· Insight: The awareness of the educational program and the PHQ-9 tool improved greatly.

Confidence in Managing Depression (PRE-Q2 vs. POS-Q2)

· The respondents’ confidence level before the intervention was moderate (score 3), and the majority had a score of 40. More respondents with a score of 15 had high confidence (score 4).
· High confidence (ratings 4 and 5) increased to 35%, signifying an improvement in the ability to manage depression after the intervention.
· Insight: This is evident since the confidence level is higher, which indicates that the program was good in enhancing healthcare providers’ competence.

Likelihood of Assisting Patients (PRE-Q3 vs. POS-Q3)

· Pre-Intervention: 35% expressed a moderate risk score of 3; risk scores of 4 and 5 (high risk) were 50%.
· Out of the first responses, high likelihood responses increased to 55 per cent after the intervention.
· Findings: Familiarity, confidence, and participants’ inclination to help patients all increased post-intervention but to a lower extent than the other two factors.

Agreement on PHQ-9 Usefulness (PRE-Q4 vs. POS-Q4)

· Before the intervention, the respondents were moderately agreed with the statements (25%: score 3, 20%: score 4, 15%: score 5).
· Post-Intervention: There was also a slight de-adoption of strong agreement from the original survey, which had it at 5.3%.
· The information refinements improved the overall consensus, but concerns regarding tool implementation continued to be voiced.

Chi-Square Test Results

Chi-Square tests applied were used to determine the Outcome Analysis results’ statistical significance:
Familiarity: χ2(16, N=20) = 17.867, p = 0.332
Confidence: χ2(12, N=20) = 14.486, p = 0.271
Likelihood to Assist: χ2(12, N=20) = 13.690, p = 0.321
Agreement: χ2(12, N=19) = 8.022, p = 0.783
Interpretation: As displayed in the table, none of the changes were statistically significant (p > 0.05), which could be attributed to the small sample size and data distribution. Nevertheless, all these variables have shown positive trends, which indicates that the system is on the right path to enhancing its performance.

Graphical Representations

1. Familiarity

Observation: As seen by the blue bars, there is an overall trend of improvement towards higher scores post-intervention, the difference being much more pronounced at score five suggesting gaining more familiarization with the PHQ-9.
Thus, the intervention promoted increased participant familiarity, as seen by the increased concentration of scores on the higher part of the scale after the intervention.

2. Confidence

As depicted in Table 2, more post-intervention scores are distributed in the higher score bracket (scores 4 and 5) than the pre-intervention scores, which showed more of the lower scores.
The intervention was effective in enhancing the confidence of healthcare professionals when it comes to handling depression, especially when it comes to utilizing the PHQ-9 tool.

3. Likelihood of Assisting Patients

Observation: When comparing post-intervention scores, a positive trend is observed, which reveals that a greater number of participants feel highly likely to assist patients after the training, as indicated by score 4.
Insight: Although not as high as familiarity and confidence, there is still an increase in the readiness of individuals to participate in depression management.

4. Agreement on PHQ-9 Usefulness

Observation: The distribution of post-intervention scores moves upwards in the higher levels of the scale, rating slightly better than the rest of the other categories.
Emphasis: Even with the small change observed, there is still some concern about the PHQ-9’s practical utility, so the concept needs to be reinforced in subsequent sessions.

Overall Trends

Positive changes: In all categories, post-intervention scores showed positive changes, proving the efficiency of the educational program.
Top Gains: Both for the category of Familiarity and Confidence, the gains were recorded at their highest
Opportunities: Perhaps the most important issue concerning the effectiveness of PHQ-9 is the lack of input regarding practitioners’ acceptance of the measure.

Figure 1:
Intervention Scores

In sum, the educational intervention on PHQ-9 made the healthcare practitioners more familiar and confident while moderately increasing their probability of helping the patients, which had a negligible impact on their agreement about the tool’s usefulness. However, even in this regard, the above findings suggest that the project has a positive influence in the following manner: Future research with the current study should include larger sample sizes to increase the statistical ability to detect and confirm the results.

Project Results

Educational Intervention and Study Design

The study assessed baseline knowledge, delivered an educational intervention, and quantified post-intervention knowledge through surveys and statistical analysis. Over eight weeks, the intervention covered PHQ-9 administration, interpretation, and clinical implications.

Data Analysis and Findings

Descriptive statistics, crosstabulations, and Chi-square tests were used to examine trends and ascertain statistical significance.
Familiarity with PHQ-9 (PRE-Q1 vs. POS-Q1)
Before the intervention, 40% of the participants positioned themselves at moderate familiarity (combined scores 2 and 3), with only 5% reporting high familiarity (score 5). The cumulative percentage of high familiarity (scores 4 and 5) was 30%, indicating comparatively low previous exposure to the PHQ-9.
Post-intervention scores showed significant improvement. The percentage of participants who rated themselves as very familiar (score 5) increased to 40%, and the cumulative percentage of high familiarity (scores 4 and 5) increased to 60%. It shows that the educational program effectively enhanced healthcare practitioners’ knowledge regarding the administration and clinical utility of the PHQ-9.
Insight: The intervention greatly improved knowledge of the PHQ-9, indicating that targeted education can eliminate knowledge deficits in depression screening (Levis & Benedetti, 2021).

Confidence in Assessing and Managing Depression (PRE-Q2 vs. POS-Q2)

40% of participants were moderately confident (score 3), and only 15% were highly confident (score 4) as per the pre-intervention scores. It shows a lack of certainty in being able to evaluate and manage depression efficiently.
After the intervention, the confidence level increased significantly. The percentage of the participants who were very confident (combined scores 4 and 5) increased from 15% to 35%. Additionally, the percentage of the participants who scored the highest in confidence (score 5) increased from 0% to 20%.
Insight: The intervention increased providers’ confidence in using the PHQ-9, which is crucial for effective depression screening and early intervention.

Likelihood of Helping Patients with PHQ-9 (PRE-Q3 vs. POS-Q3)

Before the intervention, 35% of the participants rated their likelihood of assisting patients with depression screening as moderate (score 3), while 50% reported high likelihood (scores 4 and 5 combined).
Following intervention, high likelihood responses increased slightly to 55%, and moderate likelihood ratings remained stable at 30%. It represents a modest change in providers’ willingness to actively assist patients with PHQ-9.
Insight: While the potential for assisting patients grew, the shift was less pronounced than familiarity and confidence.

Agreement on the Usefulness of PHQ-9 (PRE-Q4 vs. POS-Q4)

Before the intervention, 25% of respondents reported moderate agreement with PHQ-9 usefulness (score 3), and 15% strongly agreed (score 5).
Following the intervention, moderate agreement increased to 42.1%, and strong agreement decreased slightly to 5.3%. This shows that while agreement overall increased, some participants became more critical of the tool’s utility in practice after learning more about it.
Insight: Intervention enhanced levels of agreement, yet uncertainty about the PHQ-9’s effectiveness in real-world settings remained (Ford et al., 2020).

Statistical Analysis and Limitations

Crosstab analyses and Chi-square tests showed positive trends across all measures but no findings of statistical significance (p > 0.05). It is most likely due to:
· Small sample size (N = 20).
· Skewed distribution of answers, which affected statistical power.
People are generally undiagnosed because health care practitioners perform inadequate screening procedures. This study was designed to assess the impact of an educational session on increasing knowledge, self-efficacy, and practice behaviors regarding the use of the Patient Health Questionnaire-9 (PHQ-9) for depression screening.

Practice Recommendations

Enhance Education: Extend the PHQ-9’s educational program to different healthcare facilities to ensure the populace’s familiarity with and efficiency in using it (GBD 2019 Mental Disorders Collaborators, 2022).
Training: Intensive training during professional development for the participants to refresh their knowledge and introduce them to new practices in mental health screening.
Into Routine Practice: Promoting the use of PHQ-9 as part of routine assessments recommended by clinical guidelines and through the implementation of EHR prompts (Levis & Benedetti, 2021).
Remove Practical Issues: Practical issues often act as barriers, and these include lack of time, availability of resources, and stigmatization when it comes to mental health assessments.
More general research questions: Extend the research to check the consistency of the results obtained and investigate the effects on the patients’ outcomes in the long run.

Final Conclusions

The educational intervention improved the healthcare providers’ knowledge and self-confidence in utilizing PHQ-9 in screening depression. While the statistical significance test was not attained, the trends displayed positive results for the intervention. Therefore, future work should aim to increase the size of such campaigns, tackle implementation issues, and conduct large-scale research to support these conclusions. Hence, the training of PHQ-9 in standard patient care delivery systems provides ways through which primary care providers can quickly identify, treat, or refer patients with a probable case of depression, thus increasing patient satisfaction and good mental health.

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ANNEXED

Appendix A

Project Title: “Enhancing Healthcare Professional’s Role in Assessing and Monitoring Depression Levels Using
PHQ 9 Depression Screening Tool
This practice change project study intends to assess the baseline knowledge on PHQ 9 Depression Screening Tool, implement an educational program using PHQ 9 Depression Screening Tool and evaluate its effectiveness in enhancing the healthcare professional’s role. Participation in the study will be voluntary.

Pre-Test

Instructions:
Please answer the question by writing a checkmark next to the question. Do not write your name or any other information on the test. Thank you for your participation.

Question 1.

(1)
Very Unfamiliar

(2)
Unfamiliar

(3)
Somewhat Familiar

(4)
Familiar

(5)
Very Familiar

To what extent are you familiar with the PHQ9 Depression Screening tool?

Question 2.

(1)
Not Confident at all

(2)
Slightly Confident

(3)
Somewhat Confident

(4)
Fairly Confident

(5)
Completely Confident

How confident are you in assessing and managing patients with depression?

Question 3.

(1)
Not Likely at all

(2)
Slightly Likely

(3)
Not Sure

(4)
Very Likely

(5)
Extremely Likely

How likely are you to assist your patients in recognizing the signs and symptoms of depression using the PHQ-9 screening tool?

Question 4.

(1)
Strongly Disagree

(2)
Disagree

(3)
Neutral

(4)
Agree

(5)
Strongly Agree

Do you agree that incorporating PHQ-9 depression screening tool will assist you in managing patients with depression?

Adopted from Stroh, A. M. (2020). Implementing a depression protocol in a primary care practice.

https://dl.acm.org/doi/10.5555/AAI27830956

Appendix B

Project Title: “Enhancing Healthcare Professional’s Role in Assessing and Monitoring Depression Levels Using
PHQ 9 Depression Screening Tool
This practice change project study intends to assess the baseline knowledge on PHQ 9 Depression Screening Tool, implement an educational program using PHQ 9 Depression Screening Tool and evaluate its effectiveness in enhancing the healthcare professional’s role. Participation in the study will be voluntary.

Post-Test

Instructions: Please answer the question by writing a checkmark next to the question. Do not write your name or any other information on the test. Thank you for your participation.

Question 1.

(1)
Very Unfamiliar

(2)
Unfamiliar

(3)
Somewhat Familiar

(4)
Familiar

(5)
Very Familiar

To what extent are you familiar with the PHQ9 Depression Screening tool?

Question 2.

(1)
Not Confident at all

(2)
Slightly Confident

(3)
Somewhat Confident

(4)
Fairly Confident

(5)
Completely Confident

How confident are you in assessing and managing patients with depression?

Question 3.

(1)
Not Likely at all

(2)
Slightly Likely

(3)
Not Sure

(4)
Very Likely

(5)
Extremely Likely

How likely are you to assist your patients in recognizing the signs and symptoms of depression using the PHQ-9 screening tool?

Question 4.

(1)
Strongly Disagree

(2)
Disagree

(3)
Neutral

(4)
Agree

(5)
Strongly Agree

Do you agree that incorporating PHQ(9 depression screening tool will assist you in managing patients with depression?

Adopted from Stroh, A. M. (2020). Implementing depression protocol in primary care practice. https://dl.acm.org/doi/10.5555/AAI2783095

Appendix C

SURVEY

Managing and Interpreting the PHQ-9 Depression Screening Tool.

Section 1: Demographics

1. What is your role in the primary care setting?
· Physician (PCP)
· Registered Nurse (RN)
· Physician Assistant (PA)
· Advanced Practice Registered Nurse (APRN)
2. How many years of experience do you have in primary care?
· Less than 1 year
· 1-3 years
· 3-5 years
· More than 5 years
3. Have you received any formal training on the use of the PHQ-9 Depression Screening Tool?
· Yes
· No
4. If yes, when was your last training session?
· Less than 6 months ago
· 6-12 months ago
· More than a year ago

Section 2: Knowledge on PHQ-9 Management

1. What is the primary purpose of the PHQ-9 Depression Screening Tool?
· a) To diagnose depression
· b) To screen for depression severity
· c) To evaluate treatment response
· d) All of the above
2. How frequently should the PHQ-9 be administered to patients diagnosed with depression?
· a) At every visit
· b) Every two weeks
· c) Monthly
· d) Every six months
3. What score range on the PHQ-9 indicates moderate depression?
· a) 0-4
· b) 5-9
· c) 10-14
· d) 15-19
4. Which of the following actions is appropriate when a patient scores 20 or higher on the PHQ-9?
· a) Monitor and re-evaluate at the next visit
· b) Consider initiating or adjusting treatment
· c) Refer to a mental health specialist immediately
· d) Both b and c

Section 3: Interpretation Skills

1. A patient scores 12 on the PHQ-9. What is the recommended management step?
· a) No action needed
· b) Provide psychoeducation and follow-up
· c) Consider starting antidepressant treatment
· d) Immediate referral to psychiatric services
2. What should a healthcare provider do if a patient endorses item 9 (thoughts of self-harm) on the PHQ-9?
· a) Document and monitor the patient
· b) Provide immediate intervention and safety planning
· c) Refer to emergency mental health services
· d) Both b and c
3. How can the PHQ-9 scores be used to track treatment progress in patients with depression?
· a) By comparing scores over time to assess symptom improvement or worsening
· b) By using scores to determine medication adjustments
· c) By integrating scores into comprehensive treatment planning
· d) All of the above

Appendix D

CHECKLIST

Note: All documents submitted for IRB Review must be uploaded using web-based system provided by AGMU. Applications without all required information/documents will not be accepted for IRB review.

Principal Investigator :
Manuel Rivero Jr

Proposal Title :
Enhancing Healthcare Professional’s Role in Assessing and Monitoring Depression Levels Using PHQ 9 Depression Screening Tool    

Official Stamped Program: |_| Yes |_| No

Type of Application: Include the appropriate form. Documents will be submitted using Web-Based IRBNet Platform

|_| F01
-New Protocol |_| F02-Continuing Review |_| F03-Amendment |_| F04-Closure |_| F05-Adverse/Non-Unanticipated Event

|_| F08
Exempt Study/Research Submission

Research Materials: Select from the following and include documents that may apply even if you have them in your email or you have downloaded from online (documents must have a bottom page margin of 2 inches and pages must be numbered “format 1 of 1”).

|_| Questionnaire |_| Interview |_| Survey |_| Test |_| Focal Group |_| Advertisement/Recruitment tool

|_| Recording: Audio/Video |_| Photos |_| Secondary Data |_| Other, specify
     

Select type of proposal to be submitted for review:

|_|
Federal Proposal – include the assessment or research activities sections and must include (refer to list below):

|_| Proposal (Thesis/Independent Research)- must include the following:

|_| Table of Contents

|_| Provisions for subject and data confidentiality

|_| Introduction

|_| Statement of potential research risks to subjects

|_| Specific Aims

|_| Statement of potential research benefits to subjects

|_| Methods of Data Collection and Analysis
(Qualitative and Quantitative)

|_| Description of the subject population, research setting, subject recruitment procedures

|_| References/Bibliography

|_| Copyright, if applicable

|_| Informed consent procedure

|_| Other      

Additional documents required by the IRB Board when applicable: (Consent Form or Written Statement, Assent Form, Research Materials, and Letter of Recruitment should be submitted with
a bottom page margin of 2 inches. (Documents will not be accepted without these indications).

|_| Consent Form

|_| Assent Form

|_| Support Letter: |_| internal |_| external

|_| Amendment Letter

|_| Advertisement/Recruitment material (Flyer)

|_| Evidence/Receipt of questionnaire

|_| Form FDA 1572 (Clinical Studies)

|_| Package Insert (product description)

|_| Investigator Brochure (Clinical Studies)

|_| Other:      

All staff involved and responsible for submitting an IRB Review must complete and include the reports below. For Clinical Trials, when necessary, the “Good Clinical Practice” (GCP) certifications must be submitted.

Staff

Resume/ CV

HIPS

IRB

RCR

GCP*

Principal Investigator

|_|

03/14/2024/
Mo Day Yr

05/16/2024/
Mo Day Yr

02/04/2024/
Mo Day Yr

05/16/2024/
Mo Day Yr

Co-Investigator

|_|

     /     /     /
Mo Day Yr

     /     /     /
Mo Day Yr

     /     /     /
Mo Day Yr

     /     /     /
Mo Day Yr

Mentor

|_|

01/28/2023/
Mo Day Yr

01/28/2023/
Mo Day Yr

01/28/2023/
Mo Day Yr

01/30/2023/
Mo Day Yr

Important: If you have questions or need any additional information, please contact
Amílcar Jiménez-Gómez, IRB Coordinator at (407) 563-6501 Ext. 5520 or at

amjimenez@agmu.edu
.

Appendix E

Dean of Academic Affairs

Board for the Protection of Human Subjects in Research

AGM University

South Florida Campus
US Center
Nursing Department

Informed consent for a study with minimum risk

Enhancing Healthcare Professional’s Role in Assessing and Monitoring Depression Levels Using PHQ 9 Depression Screening Tool

Description of the study and the role of your participation

Manuel Rivero Jr. is inviting you to participate in a research study. Manuel Rivero Jr., the Principal Investigator, is a student, and Dr. Luzviminda V. Boyonas is a professor at the AGM University, South Florida Campus. The purpose of this research is to help improve Licensed Healthcare Providers comprehension and application of the Patient Health Questionnaire (PHQ-9) for clinical practice depression screening, thoroughly highlighting the significance of prompt identification and treatment of depression; the initiative seeks to help enhancing patient outcomes.

Your participation in this research will consist of 4 questions before and after (pre- and post-tool), an education meeting related to depression, and a survey with 11 questions about managing and interpreting the PHQ-9 Depression Screening Tool.
To participate in this investigation, it will take a total of 45 minutes to complete all the process, first you must attend the educational meeting for 30 minutes, and then you will complete the Managing and Interpreting the PHQ-9 Depression Screening Tool survey for another 15 minutes.

Risks and Discomforts

We do not know of possible risks or discomforts you may suffer during the process other than
those experienced in everyday life. These could be tiredness when completing the questionnaire. However, it would be best if you did not worry because we have an action plan to meet your needs in case of an unexpected event. These include taking a brief break from the questionnaire or, at
some point during the investigation process, if you do not feel comfortable with the questions and decide not to continue being part of the study, you can leave the project at any time without any retaliation or penalty.

AGMU IRB Consent Form
Rev.: #3: 08/24/2023

Potential benefits

The potential benefit of this project for participants includes help to increase the knowledge of depression, aiming to give licensed healthcare providers the necessary understanding, abilities, and self-assurance to evaluate, treat, and track depression levels in various healthcare environments. Moreover, the information provided to the participants is valuable for developing culturally responsive interventions to help early detection and adequate management of this condition. Potential societal benefits might include helping address the identified problem of poor depression guideline adherence in high-risk populations. Improvements in adherence to the guidelines are expected after implementing this project.

Incentives

There are no incentives for participation in this study.

Protection of Privacy, Confidentiality, and Decommission Process

All information about your identity will be handled privately and confidentially and permanently protected. Under no circumstances will the participant’s information be shared with third parties. The collected data will be stored in a private, secure, and locked place. Any document collected will be stored in the principal investigator’s office in a locked drawer for five (5) years. Any data stored in the researcher’s encrypted USB will be kept in a locked drawer in the same principal investigator’s office. They will be under the tutelage of the Principal Investigator, Manuel Rivero Jr. Data collected during the project will be stored and preserved for five years in the principal investigator’s office in a locked drawer and under the tutelage of the Principal Investigator. Only the principal investigator and his mentor will have access to the information obtained. After five (5) years, Manuel Rivero Jr. will destroy all related documentation using a paper shredder. All electronic storage devices will be destroyed using a blunt object.

Decision about your participation in this study

Your participation in this study is totally voluntary. You have the right to decide whether to participate or not. If you decide to participate in this study, you can withdraw at any time without penalty or retaliation.

Contact information

If you have any questions or concerns regarding this research study or if any situation arises during the study period, please contact Manuel Rivero Jr., at mrivero2@student.agmu.edu. If you have questions about your rights as a research subject or need any additional information or have questions, you can contact
Amílcar Jiménez-Gómez, IRB Coordinator at (407) 563-6501 Ext. 5520 or at
amjimenez@agmu.edu.

You should contact (407) 563- 6502 Ext. 5575 or write to the address below to report a case of non-compliance in the investigation.
AGMU IRB Consent Form
Rev.: #3: 08/24/2023

AGM University

Dean of Academic Affairs

5575 S Semoran Blvd. Suite 502
Orlando, FL 32822
Tel. (407) 563-6501 Ext. 5575; Fax (407) 277-8706

Consent

Participant’s Name

Signature

MM/DD/YYYY

Principal Investigator Name

Signature

MM/DD/YYYY

I have read this document and I have been given the opportunity to clarify all the doubts related to it. For this reason, I agree to participate in this investigation.

NOTE:

It is our responsibility to provide you with a copy of this document. Please select the option of your preference.

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Appendix F

Appendix G

Classified as Confidential

Classified as Confidential

Classified as Confidential

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“Enhancing Healthcare Professional’s Role in Assessing and Monitoring Depression Levels Using PHQ 9 Depression Screening Tool”

Helping to improve Licensed Healthcare Providers RN’s, APRN’s, PA’s, and PCP’s knowledge on the Patient Health Questionnaire 9 (PHQ9), focusing on understanding the tool’s administration, interpretation, and implications for depression screening. Through highlighting the significance of prompt identification and treatment of depression, the initiative seeks to help enhancing patient outcomes.

Qualified participants will receive an informed consent, a Pre & Post questionnaire, and a survey about managing and interpreting the PHQ-9 Screening Tool.

Requirements:

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Licensed Healthcare Providers: (RN’s, APRN’s, PA’s, and PCP’s)

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Who are currently practicing in the primary care setting.

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Who works Full-time

For more information, Contact me at:

MRivero2@ student.agmU.edu

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