Hcs homework #7

please answer all of the question. make it easy to read and to understand. there is two document, i think u should see both.

HCS 418: Statistics for Health Professions
Homework #7
Directions: Use the following study by Hazzan et al. (2016) (attached in Brightspace) in
answering the following questions.
Hazzan, A.A., Shannon H, Ploeg J, Raina P, Gitlin LN, Oremus M. The association between caregiver
well-being and care provided to persons with Alzheimer’s disease and related disorders. BMC Res Notes.
2016; 9(344)
https://bmcresnotes.biomedcentral.com/articles/10.1186/s13104-016-2150-z
1. Who/what is the population in this study (i.e. who do the researchers want to study)?
2. What was the purpose of the study?
3. What was the research question?
4. What is/are the independent variable(s) in this study? What is/are the level of measurement of
the independent variable(s)?
5. What is/are the dependent variable(s) in this study? What is/are the level of measurement of
the dependent variables?
6. What is the level of significance () that the researchers used? How would you put this into
words?
7. Write a null hypothesis for this study
8. Write a non-directional alternative hypothesis for this study
9. Write a directional alternative hypothesis for this study
10. Describe one important finding from the study
Hazzan et al. BMC Res Notes (2016) 9:344
DOI 10.1186/s13104-016-2150-z
BMC Research Notes
RESEARCH ARTICLE
Open Access
The association between caregiver
well‑being and care provided to persons
with Alzheimer’s disease and related disorders
Afeez Abiola Hazzan1,2*, Harry Shannon2, Jenny Ploeg3, Parminder Raina2, Laura N. Gitlin4 and Mark Oremus2,5
Abstract
Background: Alzheimer’s disease and related disorders (ADRD) are some of the leading causes of morbidity in
developed nations. Unpaid family caregivers are primarily responsible for providing the care and support needed
by persons with ADRD. In the process of caring for their loved ones with ADRD, caregivers often have to deal with
multiple challenges, including their own deteriorating well-being and overall quality-of-life (QoL). A recent systematic
review showed that very little research has been undertaken to study the relationship between AD caregiver QoL and
the level or quality of care that caregivers provide to their loved ones. In this study, we investigate the relationships
between caregiver well-being and the care provided to persons with ADRD.
Methods: We used 12-month follow-up data from the Philadelphia site (n = 125) of the National Institutes of Health
(NIH) multi-site study, Resources for Enhancing Alzheimer’s Caregiver Health (REACH I) to examine the relationship
between caregiver well-being and the level or quality of care provided while adjusting for important covariates (e.g.,
age, income, and years since caregiving). Caregivers who participated in REACH I had to be at least 21 years of age
and they had to be providing at least 4 h of care per day for 6 months or more to a live-in loved one with ADRD.
Linear regression analysis was used to examine the relationships between well-being and the level or quality of care
provided to persons with ADRD.
Results: Of the 255 caregivers who participated in the REACH I study, 125 (49.0 %) remained after 12 months of follow-up. Comparisons of participants at the 12-month follow-up and participants who were lost to follow-up showed
that these two sets of participants were not statistically significantly different on any of the variables examined in this
study. Linear regression analysis showed that there was no statistically significant association between caregiver wellbeing and level or quality of care provided.
Conclusions: Further research is required to investigate the factors associated with level and quality of care provided
to persons with ADRD, and whether caregiver well-being (or QoL in general) is a contributor.
Keywords: Well-being, Quality-of-life, Quality of care, Level of care, Alzheimer’s disease and related disorders,
Dementia, Caregiving, Aging
Background
Alzheimer’s disease and related disorders (ADRD) are
incurable conditions that reduce brain function over
time. ADRD are some of the leading causes of morbidity
in North America, especially among people aged 65 years
*Correspondence: aahazzan@gmail.com
1
Department of Medicine, McMaster University, 1280 Main Street West,
Hamilton, ON L8S 4K1, Canada
Full list of author information is available at the end of the article
or older [1]. More than 5.3 million Americans are currently living with ADRD [1, 2]. Further, one in eight older
Americans currently has ADRD and up to 16 million
Americans are projected to have the disease by 2050 [3,
4].
The situation in Canada is similar. Out of a population
of approximately 36 million people, more than 750,000
Canadians are currently living with ADRD [5]. More than
40,000 Canadians develop these diseases annually and
© 2016 The Author(s). This article is distributed under the terms of the Creative Commons Attribution 4.0 International License
(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium,
provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license,
and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/
publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Hazzan et al. BMC Res Notes (2016) 9:344
projections suggest that the total number of Canadians
with ADRD could double to 1.4 million people by 2030
[5].
The impact of ADRD is global. A recent systematic
review and meta-analysis estimated the age-standardized
prevalence of ADRD in persons aged ≥60 to be 5–7 %
in most world regions [2]. The authors found the highest prevalence in Latin America (8.5 %) and the lowest
in sub-Saharan Africa (2–4 %) [2]. The authors also estimated that about 40 million people worldwide are currently living with ADRD, with these numbers expected to
double every 20 years [2].
The majority of persons diagnosed with ADRD receive
their care in the community instead of in long-term care
or other assisted living facilities [6]. Among communitydwelling persons with ADRD, 80 % of their care is delivered by family caregivers [3, 5], who bear the burden of
this care without receiving financial compensation [5, 7,
8]. These caregivers are usually the spouses or children of
the person with ADRD.
As ADRD progresses, caregivers often have to manage
increasing complexity of multiple care challenges, including changes to their own well-being [9]. Well-being is an
important component of quality-of-life (QoL) and studies
have shown that the QoL experienced by family caregivers of persons with ADRD is generally lower than that of
caregivers who are caring for people with other chronic
diseases such as cancer or acquired immune deficiency
syndrome [10]. The link between caregiver well-being
and the level or quality of care is important to investigate
because caregivers are the primary carers for persons
with ADRD. Indeed, caregivers have been called “hidden victims” because of the high social, emotional, and
financial costs associated with caring for someone with
ADRD [11]. However, it is not clear how the decline in
ADRD caregiver well-being is related to the level or quality of care that these caregivers provide. No conceptual
framework exists to specifically explain the link between
caregiver QoL and the level or quality of care provided in
AD. However, research evidence does link lower QoL to
greater absences from work and reduced job productivity [12]. A nationally representative survey in the United
States showed that lower QoL among working adults
increased absences from work and reduced job productivity [12]. In the domain of care provision, these workplace productivity issues might translate into declining
‘caregiver productivity,’ which is conceived as the level
and quality of care that caregivers provide to persons
with AD. The study of factors that affect whether caregivers deliver optimal care is necessary to promote favorable
outcomes among care recipients and also to design effective interventions that support both the quality of life of
caregivers and persons with dementia.
Page 2 of 8
A recent systematic review found very little published
information about the relationship between AD caregiver
QoL and the level or quality of care provided [13]. The
systematic review included only one study, by Gitlin et al.
[14], that recruited ADRD caregivers from the Philadelphia site of the Resources for Enhancing Alzheimer’s
Caregiver Health (REACH I) research project. Although
Gitlin et al. collected data on caregiver well-being (an
important component of QoL [13]), level of care provided, mastery, and skill enhancement, the purpose of
their research was to examine the six-month effects of
a Home Environmental Skill-Building Program (ESP)
on caregiver well-being and care recipient functioning.
Consequently, Gitlin et al.’s study was not focused on the
association between caregiver well-being and the level or
quality of care. The strength of evidence using GRADE
was “moderate,” thereby indicating that further research
would be necessary to examine whether caregiver wellbeing and the level or quality of care are related [15, 16].
In their site-specific study as part of the National Institutes of Health (NIH) REACH I initiative [14], caregiver
overall well-being was measured with a 13-item scale
[the perceived change index (PCI)]. The relevant level
of care measure was caregiver time (the amount of time
devoted to providing care and total hours of instrumental activities of daily living or IADL help). The quality
of care measures included caregiver mastery and skill
enhancement. Caregiver mastery was measured with
the caregiving mastery index (CMI). The CMI is a sixitem scale evaluating the caregiver’s appraisal of his or
her ability to provide care to the care recipient (CR) (e.g.,
“How often do you feel you should be doing more for
care recipient?). Skill enhancement was measured with
the task management strategy index (TMSI), which is a
19-item scale that measures the extent to which positive
caregiving strategies were used to manage activities of
daily living (ADL) dependence and problem behaviours
in care recipients.
Since the REACH I data used in the Gitlin et al. study
[14] contained information that could help to directly
assess the relation between well-being and level or quality of care, we obtained the Philadelphia REACH I dataset and posed the following research questions:
What is the relationship between caregiver well-being
(PCI) and the level of care that these caregivers provide
to persons with ADRD?
Can caregiver well-being (PCI) predict quality (CMI
and TMSI) of care at 12 months?
If the results of the analyses show that caregiver wellbeing is related to the level or quality of care provided,
then additional resources could be targeted toward
improving caregiver well-being (for example, counseling,
educational programs, skills enhancement opportunities,
Hazzan et al. BMC Res Notes (2016) 9:344
etc.) as a means of enhancing the level or quality of care
provided to persons with ADRD.
Methods
Reach I
The REACH I research project (1996–2001) [17] involved
six sites in the United States. The project was designed
to investigate promising and innovative interventions for
family caregivers of persons with ADRD or other dementias. The Philadelphia site examined the effects of the
Environmental Skill-Building Program (ESP) (currently
renamed and referred to as Skills2CareR) on caregiver
well-being and care recipient functioning.
Caregivers who participated in REACH I had to be
at least 21 years of age and they had to be providing at
least 4 h of care per day for 6 months or more to a livein loved one with ADRD. In Philadelphia, caregivers were
recruited from the local area agency on aging (Philadelphia Corporation for Aging) and from media announcements. Follow-up lasted a maximum of 12 months.
Detailed information about REACH I’s Philadelphia site,
including participant eligibility criteria and selection
methods, as well as the delivery characteristics of the
intervention, have been reported elsewhere [14].
For the present analysis, we used demographic, caregiver well-being (PCI), and level of care variables
from baseline. In addition, quality of care data from the
12-month follow-up were used.
Variables
Main effect variable: perceived change index (PCI)
Gitlin et al. measured caregiver well-being in the form
of the perceived change index (PCI). The PCI is a selfreport tool to measure caregivers’ own appraisal of the
levels of improvement or deterioration in their well-being
[18]. Well-being is an important component of overall
QoL that is closely related to health-related quality-oflife (HRQOL), a term used to distinguish aspects of QoL
that are health-related from those that are not [19, 20].
HRQOL has also been described as a measure of perceived well-being [20].
The PCI was specifically developed to measure caregiver appraisals of self-improvement or decline in
well-being and has since been used in other caregiver
intervention trials [18]. The PCI is a 13-item instrument
that uses a 5-point scale to rate whether a caregiver’s life
situation has become worse (1) or improved (5) over the
past month. Examples of scale items include caregivers’
ability to sleep through the night, ability to manage dayto-day caregiving, and feelings of being overwhelmed
[18]. In support of its construct validity as a measure of
caregiver well-being, higher PCI scores were found to
be associated with fewer depressive symptoms, more
Page 3 of 8
activity engagement, and greater perceived benefits from
caregiving [18]. Psychometric analyses suggest the PCI is
valid and internally consistent (Cronbach’s alpha = 0.90)
[18].
Outcome variables: level and quality of care provided
by caregivers in ADRD
Based on the variables available in the REACH I dataset,
we defined ‘level of care’ as the total number of hours
per week that caregivers spent providing care for their
loved ones with ADRD [13, 14]. This included the total
amount of time spent helping with ADLs and IADLs.
Since REACH I contained data on level of care at baseline
only, we conducted a cross-sectional analysis of the association between PCI and level of care.
We used two measures from REACH I to operationalize quality of care: caregiver mastery (or “proficiency”)
and task management. Caregiver mastery was measured
with the Caregiving Mastery Index (CMI) from Lawton
et al. [21]. The CMI is a six-item scale that uses a 5-point
Likert format ranging from 1 (never) to 5 (always). A
higher score means greater mastery of the caregiving
role. Items on the CMI include questions such as “How
often do you feel you should be doing more for the care
recipient?” Regarding the psychometric properties of the
CMI, the coefficient of internal consistency (a measure
of the correlations between different items on the test)
was found to be 0.66 in the REACH I study and 0.71 in
another study of 74 caregivers that was designed to investigate caregiver appraisal of the caregiving process (e.g.,
caregiving satisfaction and caregiving impact) [14, 21].
Task management was measured with the task management strategy index (TMSI), a scale shown to have adequate psychometric properties. The TMSI is a 19-item
scale that measures the extent to which positive caregiving strategies were used to manage ADL dependence
and problem behaviours in care recipients. The TMSI
also uses a 5-point Likert format from 1 (never) to 5
(always). Higher scores on the TMSI indicate greater use
of such strategies. Examples of items include the extent
to which caregivers employed visual and tactile cueing or
short instructions to communicate with their loved ones.
Regarding the psychometric properties of the CMI, the
coefficient of internal consistency in REACH I was found
to be 0.77 [22].
Since data on quality of care (CMI and TMSI) were
available at baseline and 12-month follow-up periods, we
conducted a longitudinal analysis to see if caregiver wellbeing can predict quality of care at 12-months.
Socio‑demographic variables (covariates)
We examined the impact of several socio-demographic
variables as covariates in all analyses. These variables
Hazzan et al. BMC Res Notes (2016) 9:344
included age, gender, income, education, and employment status. Research has shown that age and gender are
inversely associated with well-being because women and
older participants are more likely to report higher rates of
disability [23, 24]. Regarding level or quality of care, older
caregivers may be less able to provide the same level or
quality of care as younger caregivers because of factors
such as decreased mobility or increased health challenges
[24]. Traditional, gender-prescribed roles might differentiate the type of care provided by male and female caregivers in certain areas such as assistance with activities
of daily living.
Higher income and education are positively associated with well-being because both could generate the
resources needed to provide higher levels and better
quality of care than what would be the case if caregivers had lower income and education [25]. For example,
caregivers with higher income could hire a substitute
carer for their loved one to provide round-the-clock care,
thereby leading to higher levels of care. High-income
caregivers could also purchase better quality of care by
hiring caregivers with specialized skills in ADRD care
provision. Better-educated caregivers may be more aware
of, and therefore more likely to seize, opportunities that
could lead to higher levels and better quality of care for
their loved ones. For example, these caregivers may be
more likely to conduct research into support services
such as respite care to provide better care [25].
Employment may be negatively associated with
well-being because caregivers who work may experience job-related stresses (burnout, tiredness, etc.) that
impact well-being [26]. Conversely, these stresses might
entail less impact for caregivers who do not work. Also,
employment may be negatively associated with level and
quality of care because caregivers who work may be unable to devote as much time or effort to caring as would
caregivers who do not work.
Statistical analyses
We computed descriptive statistics for all variables to
assess the variability of the data. We used the independent t test (continuous measures) and the Chi square test
(categorical measures) to compare participants who
completed 12 months of follow-up with participants who
provided baseline data yet were lost to follow-up. For the
outcome variables that were measured longitudinally
(i.e., well-being, mastery, task management), we conducted paired samples t-tests to compare the mean values measured at baseline with the mean values measured
at the 12-month follow-up time [27, 28].
Linear regression analysis was used to examine the
relationships between PCI and the level or quality of
care provided to persons with ADRD [29, 30]. Separate
Page 4 of 8
analyses were performed for level and quality as outcomes. We adjusted all regression analyses for the covariates discussed above. We also controlled for whether
caregivers were in treatment (ESP intervention) or control groups. We coded categorical variables (income,
employment status, and sex) into dummy variables.
We used IBM Statistics (SPSS) version 22 (IBM Corporation, Armonk, NY) and SAS version 9.2 (The SAS Institute, Cary, NC) to conduct the statistical analyses. The
level of statistical significance was set at p < 0.05. This study adheres to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement [16]. Ethics, consent and permissions The Philadelphia REACH data collection site obtained ethics clearance from the Thomas Jefferson University Institutional Review Board (Control number: 95.9074). All participants gave informed consent to participate. Results Caregiver sample The Philadelphia site of REACH I initially contacted 413 caregivers, of whom 290 met the eligibility criteria for participation. Of that number, 255 caregivers agreed to participate in the study [14] and 125 (49.0 %) remained after 12 months of follow-up [31]. Reasons for drop-out included the death of the care recipient (n = 40), placing the care recipient in a long-term care facility (n = 39), missing the follow-up interview (n = 26), or withdrawing from the study (n = 25). Table 1 presents the demographic profile of the 255 caregivers at baseline, as well as the 125 eligible participants remaining at the 12-month follow-up. At baseline, caregivers had a median age of 60 years, most (75 %) were female, and the majority (76 %) obtained at least a high school education. Most (67 %) of the caregivers were unemployed and 76 % had an annual income of less than $40,000. Although the majority of caregivers were married (58 %), most (61.2 %) were not the spouses of care recipients. Comparisons of participants at the 12-month followup (n = 125) and participants who were lost to followup between baseline and 12 months (n = 130) showed that these two sets of participants were not statistically significantly different on any of the variables examined in this study (all p values for comparisons were greater than 0.05). Change in PCI scores and quality of care over time The mean PCI score increased by 0.12 (95 % confidence interval [CI] −0.23 to −0.01) between baseline and follow-up, meaning that caregiver well-being increased Hazzan et al. BMC Res Notes (2016) 9:344 Page 5 of 8 Table 1 Caregiver demographics providing care for their loved ones (level of care). The table also shows the results of the longitudinal analysis between caregiver well-being and caregiver mastery, as well as the longitudinal analysis between caregiver wellbeing and task management. An inverse yet statistically non-significant relationship was found between caregiver well-being and the amount of time that caregivers spent providing care for their loved ones. For every 1-unit increase in PCI score, caregivers spent an average of 4 min less per week providing care for their loved ones (95 % CI −77 to 69 min). Also, for every one-unit increase in caregiver wellbeing, the CMI score increased by an average of 0.10 points, although the association was not statistically significant (95 % CI −0.1 to 0.3). For the relationship between the PCI and TSMI, a one-unit increase in wellbeing led to an average 0.20 increase in the TMSI, which was also not statistically significant (95 % CI −0.1 to 0.5). Variable Age in years, median (25th, 75th percentile) T0 (n = 255) T1 (n = 125) 60 (50, 73) 59.0 (50, 70) Gender, n (%) Male 65 (25) 26 (21) Female 190 (75) 99 (79) Educational achievement (ISCED classification), n (%) High school 110 (43) 53 (42) Employment status, n (%) Full-time 60 (24) 34 (27) Part-time 24 (9) 11 (9) Unemployed 171 (67) 80 (64) Income category (LICO), n (%) Low income 115 (46) 55 (45) Moderate income 79 (32) 38 (31) Middle class income 37 (15) 22 (18) High income 16 (7) 7 (6) Marital status, n (%) Never married 44 (17) 16 (13) Married or living as married 148 (58) 70 (56) Widowed/divorced/separated 63 (25) 39 (31) Relation to care recipient, n (%) Spouse 99 (39) 43 (34) Child 121 (47) 65 (52) Other family 35 (14) 17 (14) 4 (4) 4 (4) Years of caregiving, mean (SD) Caregiving time/week in minutes, median (25th, 75th percentile) 300 (180, 480) NA ISCED Educational achievement classified based on the International Standard Classification of Education; LICO low income is based on the Federal Low-Income Cut-Offs of