Describe the sampling methods in your own words (paraphrase, do not quote from the article). Describe the generalizabil
Using the empirical research article that your instructor approved in the Week 5 assignment, ask yourself: “Is this a quantitative research article or a qualitative research article?” Remember, in quantitative research, the emphasis is on measuring social phenomenon because it is assumed that everything can be observed, measured, and quantified. On the other hand, in qualitative research, it is assumed that social phenomenon cannot be easily reduced and broken down into concepts that can be measured and quantified. Instead, there may be different meanings to phenomenon and experiences. Often in qualitative research, researchers use interviews, focus groups and observations to gather data and then report their findings using words and quotations.
Consider how these different methods affect the sampling design and recruitment strategy, and ask yourself how the recruitment of research participants will affect the findings.
For this Assignment, submit a 3-4 page paper. Complete the following:
- Read your selected empirical research article, and identify whether the study is a quantitative or qualitative study. Justify the reasons why you believe it is a quantitative or qualitative study. (Your instructor will indicate to you if you are correct in identifying the research design. This will point you to whether you will use the “Quantitative Article and Review Critique” or the “Qualitative Article and Review Critique” guidelines for the final assignment in week 10.)
- Using the empirical research article, focus on the sampling method in the study and begin to evaluate the sampling method by answering the following:
- Describe the sampling methods in your own words (paraphrase, do not quote from the article).
- Describe the generalizability or the transferability of the research finding based on the sampling method.
- Discuss the limitations the article identified with the sample and how those limitations affect the reliability or credibility.
- Explain one recommendation you would make to improve the sampling plan of the study that would address these limitations in future research.
Record: 1
Title:
Assessing mental health in a context of extreme poverty: Validation of the rosenberg self-esteem scale
in rural Haiti.
Authors:
Roelen, Keetie1 (AUTHOR) [email protected]
Taylor, Emily2 (AUTHOR)
Source:
PLoS ONE. 12/14/2020, Vol. 15 Issue 12, p1-14. 14p.
Document Type:
Article
Subject Terms:
*SELF-esteem
*MENTAL health
*HEALTH outcome assessment
*STANDARD model (Nuclear physics)
*RURAL poor
*POVERTY
Geographic Terms:
HAITI
NAICS/Industry Codes:
621330 Offices of Mental Health Practitioners (except Physicians)
Abstract:
A widening evidence base across low- and middle-income countries (LMICs) points towards mutually
reinforcing linkages between poverty and mental health problems. The use of validated and culturally
relevant measures of mental health outcomes is crucial to the expansion of evidence. At present, there
is a paucity of measures that have been tested and validated in contexts of extreme poverty. Using data
from adult women living in extreme poverty in rural Haiti this study assesses the cross-cultural validity of
the widely used Rosenberg Self-Esteem Scale (RSES) and its applicability in assessing linkages between
poverty and mental health outcomes. We find no evidence for a one-dimensional 10-factor structure of
the RSES within our data and agree with other authors that the standard self-esteem model does not fit
well in this cultural context. Comparisons with another widely used measure of mental health–the K6
measure–indicate that the RSES cannot be used as a proxy for mental health outcomes. We conclude
that the use of the RSES in different cultural contexts and with samples with different socioeconomic
characteristics should be undertaken with caution; and that greater consideration of the validity of
psychosocial constructs and their measurement is vital for gaining robust and replicable insights into
breaking the cycle between poverty and mental health problems. [ABSTRACT FROM AUTHOR]
Copyright of PLoS ONE is the property of Public Library of Science and its content may not be copied or
emailed to multiple sites or posted to a listserv without the copyright holder's express written permission.
However, users may print, download, or email articles for individual use. This abstract may be abridged.
No warranty is given about the accuracy of the copy. Users should refer to the original published version
of the material for the full abstract. (Copyright applies to all Abstracts.)
Author Affiliations:
1Institute of Development Studies, Brighton, United Kingdom 2The University of Edinburgh, Edinburgh, United Kingdom
Full Text Word Count:
6522
ISSN:
1932-6203
DOI:
10.1371/journal.pone.0243457
Accession Number:
147599301
Persistent link to this record (Permalink):
https://ezp.waldenulibrary.org/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=a9h
&AN=147599301&site=eds-live&scope=site
Cut and Paste:
<A
href="https://ezp.waldenulibrary.org/login?url=https://search.ebscohost.com/login.aspx?direct=true&d
b=a9h&AN=147599301&site=eds-live&scope=site">Assessing mental health in a context of extreme
poverty: Validation of the rosenberg self-esteem scale in rural Haiti.</A>
Database:
Academic Search Complete
Assessing mental health in a context of extreme poverty: Validation of the rosenberg self-esteem
scale in rural Haiti
Introduction
A widening evidence base across low- and middle-income countries (LMICs) points towards mutually
reinforcing linkages between poverty and mental health problems. The use of validated and culturally
relevant measures of mental health outcomes is crucial to the expansion of evidence. At present, there
is a paucity of measures that have been tested and validated in contexts of extreme poverty. Using data
from adult women living in extreme poverty in rural Haiti this study assesses the cross-cultural validity of
the widely used Rosenberg Self-Esteem Scale (RSES) and its applicability in assessing linkages between
poverty and mental health outcomes. We find no evidence for a one-dimensional 10-factor structure of
the RSES within our data and agree with other authors that the standard self-esteem model does not fit
well in this cultural context. Comparisons with another widely used measure of mental health–the K6
measure–indicate that the RSES cannot be used as a proxy for mental health outcomes. We conclude
that the use of the RSES in different cultural contexts and with samples with different socioeconomic
characteristics should be undertaken with caution; and that greater consideration of the validity of
psychosocial constructs and their measurement is vital for gaining robust and replicable insights into
breaking the cycle between poverty and mental health problems.
Despite widespread poverty and high levels of mental health disorders, research on the relationship
between poverty and mental health in low and middle-income countries (LMICs) has only started
emerging in the last two decades [[ 1]]. Evidence from across LMICs finds an association between
indicators of poverty such as low socioeconomic status and food insecurity, and common mental health
disorders [[ 2]]. While some studies suggest that poor mental health is not strongly associated with
poverty [[ 3]], others have dispelled this by attributing lack of association to narrow or inadequate use of
poverty measures [[ 5]]. More recent research in countries including India and Indonesia points towards
a causal relationship between low income and poor mental health [[ 7]]. Nevertheless, research on
linkages between poverty and mental health, and particularly the role of poverty alleviation
interventions in improving mental health, in low-resource settings is scarce [[ 1]].
The use of validated, comparable and culturally relevant measures of mental health outcomes is central
to the expansion of research. Efficiency and generalisability are key requirements of such measures,
particularly when mental health is not the primary focus of enquiry but one of a broad set of socio-
economic outcomes, as is common in relation to anti-poverty interventions [[ 9]]. Despite a widening of
the evidence base, there is a paucity of measures that have been validated within the context of LMICs
and that ensures their relevance in different resource and cultural contexts [[11]]. Against the backdrop
of this paucity, we assess the validity of a widely used measure of self-esteem in a context of low
resources and high levels of extreme poverty in rural Haiti.
Self-esteem describes an individual's positive or negative evaluation of their self-worth, self-confidence
and self-respect [[13]]. Self-esteem is positively associated with goal-directed behaviour [[14]],
negatively associated with depression [[15]] and a wide range of other psychiatric disorders [[16]].
Evidence leans towards self-esteem being an etiological factor in the development of depression (the
vulnerability model) rather than a side-effect (the scar model) of depression [[17]]. Therefore, self-
esteem is not only an indicator of psychological wellbeing [[18]] but may also serve as an early indicator
of vulnerability to depression or other psychological distress. The Rosenberg Self Esteem Scale (RSES)
[[19]] is regarded as the gold-standard measure of self-esteem, with established reliability and validity,
and is used across different contexts, languages and cultures [[20]].
In this paper, we use data from adult women living in extreme poverty in rural Haiti to assess the cross-
cultural validity of the RSES, and its applicability in studies on linkages between poverty and on mental
health outcomes. For this purpose, we investigate two specific questions in reference to our data and
context: (i) Does a Creole-language version of the RSES have a coherent factor structure when applied in
Haiti? and (ii) Can the RSES serve as a proxy for mental health? We do so by investigating the factor
structure of the RSES and by comparing results for the RSES with another measure of mental health in
order to establish construct validity, namely the K6 [[21]].
RSES in LMICs
We provide a short review of applications of the RSES in LMICs.
The RSES was originally designed as a single-dimension construct [[22]] measuring self-esteem via 10
items and a four-point scale. Items cover what are understood to be universal indicators of self-esteem
such as self-worth, self-respect and self-like using both positively and negatively worded items (more
detail is provided in the section Measures below). A comparative study of the RSES in 53 nations,
including 10 LMICs, found broad statistical support with a one-factor model [[20]]. Other country-
focused studies, such as in Brazil, also find high internal consistency [[23]]. However, the amount of
variance accounted for by the single factor was low in some countries, especially in Botswana, the
Democratic Republic of Congo (DRC) and Ethiopia, where it fell below 30 percent. This was reflected in
poor internal consistency as measured by Cronbach's alpha in the DRC, Ethiopia, and Tanzania [[20]].
Confirmatory factor analyses (CFA) provide a more thorough validation of a scale's internal structure.
We found five studies using CFA with samples from LMICs, describing six samples (see Table 1). Only
Fromont et al [[24]] found support for a one-factor model, in Burundi, with weak internal consistency (α
=.63). All other studies found that a two-factor model achieved the best fit across multiple indices. Two
studies excluded item 8 to achieve the best fit, resulting in a 9-item scale [[22], [25]]. Both these samples
were Chinese, but another study with a Chinese sample preferred a 10-item model [[26]].
Graph
Table 1 Published confirmatory factor analyses in LMIC-derived samples.
1st author LMIC & Language Sample details
N
items
N
Factors CFI1 RMSEA2
Cronbach's
α3
Fromont
(2017)
Burundi—French
version translated into
Kirundi
Burundi health workers
and general population N
= 906 10 1 0.966 0.045 .63
Makhubela
(2017) South Africa–NR4
Black South African
students n = 579 10 2 0.988 0.032 .73
Wu (2017) China—Chinese
Migrant and urban
children in China N = 982 10 2 0.995 .036 .73
Li (2015)
China—Chinese, Adolescents n = 350 9 2 0.988 .072 .84
Costa Rica–Spanish Adolescents n = 343 10 2 0.989 .046 .76
1st author LMIC & Language Sample details
N
items
N
Factors CFI1 RMSEA2
Cronbach's
α3
Farruggia
(2004) China–Chinese Adolescents N = 502 9 2 0.966 .065 .83
1 1Comparative Fit Index.
• 2 2Root Mean Squared Error of Approximation.
• 3 3Internal consistency of scale prior to CFA.
• 4 4Not reported.
Two features recurred across these studies. Firstly, method effects were common across samples with
items splitting into two factors depending on whether they were negatively or positively worded.
Secondly, item 8 "I wish I could have more respect for myself" seems to have been variously interpreted
by different cultures, with the consequence of it not reliably loading onto the one-factor model or onto
the negatively worded factor in the two-factor version. This does not appear to be a language
translation issue, as the phenomenon has been noted in English-speaking LMICs such as Botswana and
Zimbabwe [[20]]. These features suggest a cultural effect. The differential understanding of item 8 has
contributed to an argument that the effect is in some way caused by collectivist culture, although this
argument has been applied to countries that would not fit the typically understood collectivist
paradigm. Wu, Zuo [[26]] argued that item 8 should be treated as a positively worded item. However, in
other studies item 8 does not appear to be a useful part of the scale construct, and may be measuring
something different altogether.
Arguments about the cultural specificity of self-esteem more generally tend to be polarised. Hewitt
[[27]] argued that self-esteem is essentially socially constructed and therefore culturally situated. Du,
King [[28]] point out that individualistic cultures may place more emphasis on personal self-esteem
while relational aspects of self-esteem may be more salient in collectivist cultures. At the other end is
the position of self-esteem as a trait characteristic of humans and therefore universal [[29]]. The
possible cultural specificity of self-esteem, and therefore the RSES, aligns with a wider literature
cautioning against comparing mental health outcomes across interventions and contexts without
ensuring that construct and measurement of it are applicable to that culture [[30]]. The picture is further
complicated by the assertion that self-esteem is gendered, with large-scale cross-cultural evidence
showing that men consistently have higher self-esteem than women [[31]]. Researchers should
therefore approach self-esteem measurement in specific populations with caution, with routine
validation within samples preliminary to other analyses. However, evaluations of anti-poverty
interventions in different LMICs, having employed the RSES as a measure of psychological wellbeing,
tend not to report steps to establish sample-level validation such as confirmatory factor analysis [[10],
[32]].
This study therefore set out to validate the RSES in a sample of Haitian women, testing construct validity
using confirmatory factor analysis and discriminant validity through comparison with a measure of
mental health, namely K6. Secondly, we aim to test whether self-esteem, as measured by the RSES, can
be used as a proxy measure for mental health, hypothesising that self-esteem will predict mental health.
Methods
Design, sample and procedure
The data is drawn from the baseline study of a quasi-experimental impact evaluation of the Chemen Lavi
Miyò (CLM)—"the pathway to a better life"–programme in rural Haiti, which is implemented by local
NGO Fonkoze. The CLM programme targets adult women who are extremely poor [[34]] and supports
them with a package of cash and asset transfers, skills development, coaching and service provision over
a period of 18 months in a bid to move them out of poverty [[35]].
The data includes 1,381 women from across treatment and control groups in the Central Plateau region
in Haiti. The sample for the treatment group (n = 631) was pre-determined by programming
considerations, with all women in the programme sites who were eligible having been selected into the
programme. Inclusion criteria include living in extreme poverty (based on a wide set of indicators such
as having little income, being unable to send their child(ren) to school and having limited assets), having
dependants and being able to work. Women from similar communities in the same region were selected
into the control group (n = 750) using participatory wealth rankings (PWRs) within selected
communities. PWRs are widely used participatory and community-based exercises that ask a small
group of community members to rank those living in the community according to their wealth, serving
as a proxy for poverty status and helping to establish programme eligibility.
The two sub-samples are described in Table 2 for illustrative purposes. Women had an average age of
33.49 years with median household size of 5 members, including median of 3 children under 18 years
and 1 child under 5 years. More than three out of four women were traditionally or legally married.
Participants' literacy was ranked on a 4-point scale from completely illiterate to able to read and write;
67 percent were unable to read or write. Although differences between groups in household size,
numbers of children and marital status reached significance, effect sizes were negligible (Cohen's d<0.2,
r<0.2).
Graph
Table 2 Overview of sample.
Characteristic
measure of central
tendency/%
Total sample
(n = 1381)
Treatment
group (n = 631)
Control
group (n =
750)
p-
value
effect
size
Age Mean (SD) 33.5 (11.7) 33.6 (11.8) 33.4 (11.6) .647 0.03
N children Median (IQR)
aged 0–5
1 (0–2) 1 (0–2) 1 (0–1) <.001 0.10
aged 0–18
3 (2–4) 3 (2–4) 2 (1–4) <.001 0.11
Household size Median (IQR) 5 (4–6) 5 (4–6) 5 (3–6) <.001 0.10
Marital status N (%)
<.001 0.17
Never married
104 (7.5) 19 (3.0) 85 (11.3)
Characteristic
measure of central
tendency/%
Total sample
(n = 1381)
Treatment
group (n = 631)
Control
group (n =
750)
p-
value
effect
size
Traditionally or legally
married
1069 (77.4) 515 (81.6) 554 (73.8)
Divorced/separated
129 (9.3) 51 (8.1) 78 (10.4)
Widowed
69 (5.3) 39 (6.2) 30 (4.0)
Literacy Median (IQR) 0 (0–1) 0 (0–1) 0 (0–1) .006 0.12
RSES total Mean (SD) 15.6 (2.8) 15.9 (2.5) 15.3 (3.1) <.001 0.20
5 Notes: p-values for age and RSES total score are based on two-sample t-tests on the equality of mean;
Cohen's d is reported for effect size; p-values for literacy, numbers of children and household size are
based on Mann-Whitney's U test on the equality of mean ranks, r is reported for effect size; Marital
status difference is based on Cramer's V Association.
Data was collected over an extended period from June to December 2017. The length of this period was
in part due to the remoteness of fieldwork sites and the time-consuming process of selecting women for
the control group through participatory wealth ranking exercises. Data collection was undertaken by the
Social Impact team, which is a semi-autonomous monitoring and evaluation branch within Fonkoze.
Research adhered to ethical protocol, including informed consent, anonymity in data analysis and
dissemination and respectful conduct in the field. All research respondents provided informed consent
before participating in the study. They received verbal information (in Haitian Creole) about the
research objectives and the requested input. Respondents were allowed to offer consent in the most
culturally appropriate way, which in all cases proved to be verbal consent (due to high levels of illiteracy
among research participants). Ethical clearance for this study was provided by the Research Ethics
Committee of the Institute of Development Studies in March 2017.
Measures
Rosenberg Self-Esteem Scale
The RSES is a 10-item measure of self-esteem [[19]], with a scoring range of 0–30, that includes half
positively and half negatively worded statements such as "On the whole, I am satisfied with myself" and
"I certainly feel useless at times". It is the most widely used measure of self-esteem employed with
adults and youth globally. It has been extensively validated with evidence for cultural variations in its
constructs (the focus of this study). In this sample, internal consistency for the full 10-item scale was α =
0.52. This low alpha is consistent with several studies using the RSES as a single-factor structure in LMICs
including Fromont, Haddad [[24]] in Burundi; Oladipo and Kalule-Sabiti [[36]] in Nigeria; and Schmitt and
Allik [[20]] in the Democratic Republic of Congo, Ethiopia and Tanzania. It contrasts with better internal
consistency found in a Costa Rica sample Li, Delvecchio [[25]] (see Table 1).
K6
The K6 is a 6-item self-report measure with a five-point response scale designed to screen for serious
mental illness [[21]], and has been validated for use in multiple cultural contexts with very good
specificity and sensitivity for psychological distress [[37]]. Items cover typical symptoms of psychological
distress including feelings of hopelessness, nervousness, depression, and worthlessness. It has been
adopted
Who We Are
We are a professional custom writing website. If you have searched a question and bumped into our website just know you are in the right place to get help in your coursework.
Do you handle any type of coursework?
Yes. We have posted over our previous orders to display our experience. Since we have done this question before, we can also do it for you. To make sure we do it perfectly, please fill our Order Form. Filling the order form correctly will assist our team in referencing, specifications and future communication.
Is it hard to Place an Order?
1. Click on the “Place order tab at the top menu or “Order Now” icon at the bottom and a new page will appear with an order form to be filled.
2. Fill in your paper’s requirements in the "PAPER INFORMATION" section and click “PRICE CALCULATION” at the bottom to calculate your order price.
3. Fill in your paper’s academic level, deadline and the required number of pages from the drop-down menus.
4. Click “FINAL STEP” to enter your registration details and get an account with us for record keeping and then, click on “PROCEED TO CHECKOUT” at the bottom of the page.
5. From there, the payment sections will show, follow the guided payment process and your order will be available for our writing team to work on it.
Need help with this assignment?
Order it here claim 25% discount
Discount Code: SAVE25