Chat with us, powered by LiveChat Using the attached template, critically appraise the following article (attached in the Articles section).? Chaitoff et al.?Associations Between Unhealthy Weight-Loss S - Writeedu

Using the attached template, critically appraise the following article (attached in the Articles section).? Chaitoff et al.?Associations Between Unhealthy Weight-Loss S


  1. Using the attached template, critically appraise the following article (attached in the Articles section). 
    • Chaitoff et al. Associations Between Unhealthy Weight-Loss Strategies and Depressive Symptoms.


Rubric for Article Critique Reports

Week 4 – Assignments 4a and 4b

Assignment 4 (indicate 4a or 4b)






1.Title of the article, journal name, your name


Purpose/Research problem

2a. What is the purpose of the study? Is it clearly identified? Is the research problem important?


2b. Identify the dependent variable(s)


2c. Identify the independent variable(s)


Literature review

3a. Are the cited sources relevant to the study?


3b. Does the literature review offer a balanced critical analysis of the literature?


3c. Are the cited studies recent?


Theoretical framework*

4a. Has a conceptual or theoretical framework been identified?


4b. If yes, is the framework adequately described?


Design and procedures

5a. Identify the study design used in this study? Make sure that you select the exact type of design used, i.e., one of the three discussed this week.


5b. Is the study design appropriate to answer the research question?


5c. What type of sampling design was used?


5d. Was the sample size justified on the basis of a power analysis or other rationale?


5e. Are the inclusion and exclusion criteria clearly identified? What are they?


5f. What measurement tools were used for the dependent variable(s)?


5g. What measurement tools were used for the independent variable(s)?


5h. Were validity and reliability issues discussed?


Ethical considerations

6a. Were the participants fully informed about the nature of the research?


6b. Were the participants protected from harm?


6c. Was ethical permission granted for the study?


Data analysis

7a. What type of data and statistical analysis was undertaken?


7b. Was the statistical analysis appropriate to address the research question?



8. What are the results of the study? Did the results answer the research question(s)?



9a. Were the findings linked back to the literature review?


9b. Did the authors identify study limitations? What were they?


9c. Do you think the limitations are serious enough to impact the internal and external validity** of the study?


Overall assessment

10. What is your overall assessment of the study?




Source: Coughlan M, Cronin P, Ryan F. Step-by-step guide to critiquing research. Part 1: quantitative research. Br J Nurs. 2007;16(11):658-63.

* A conceptual or theoretical framework/model is a representation of a concept and the relationships between this concept and other variables that might impact it or be affected by it. It provides structure to a study and a rationale for the different relationships between the variables. Not every study has to have a conceptual or theoretical framework clearly outlined. The better research questions are usually the ones informed by theory and a corresponding framework. For an example, check the following article:

** The validity of a study, in contrast to the validity of measurements, is the degree to which study results are accurate and well-founded, when account is taken of study methods, representativeness of study sample, and nature of the population from which it is drawn.

· Internal validity (results are attributed to hypothesized effect and not sample differences)

· External validity (generalizability)


N O N – E X P E R I M E N T A L S T U D Y D E S I G N S P A R T 2 : C O H O R T S T U D Y D E S I G N

6310-WEEK 4


• Cross-sectional study design • Cohort study design • Case-control study design



• Cohort: a group of subjects followed over time • Cohort design: A non-experimental design in which a defined

group of people (a cohort) is followed over time to study outcomes for subsets of the cohorts • Data is collected at baseline to assess exposure/characteristic • Data is collected again at later point(s) in time to examine the

development of a disease or condition • Time frame: longitudinal • Advantages:

• Allows calculation of incidence (number of new cases of a condition occurring over time)

• Establishes the time sequence of variable  strengthens the process of inferring the causal basis of an association

• Types • Prospective • Retrospective • Multiple cohort


Over time


Gather data at: Defined Population


Disease No Disease

Not Exposed

Disease No Disease


• Define selection criteria and recruit sample from the population (cohort).

• At baseline, measure predictor variables and, if appropriate, baseline level of outcome variable(s).

• Follow cohort over time, minimizing loss to follow-up. • Measure outcome variable(s) at follow-up.


• Identify an existing cohort that has some predictor information already recorded

• Assess loss to follow-up that has occurred • Measure outcome variable(s) that have already



• Two or more separate samples: one with exposure to a potential risk factor (predictor) and one or more with no exposure.

• Next steps: measure other predictors; follow up; assess outcomes

• Note that a double-cohort design is different from the use of two samples in a case-control design • Double-cohort: two groups chosen based on level of predictor • Case-control: two groups chosen based on presence or

absence of an outcome • Strengths: Feasible approach to study rare exposures to

environmental and occupational hazards • Weaknesses: Confounding since the cohorts are

assembled from separate populations.


• Cohort study results are usually reported in measures that reflect the concept of being at risk.* • Risk • Odds • Rate

*See the example in Hulley’s textbook and Table 7.2 on page 93 for a good example on the calculation of these measures.


• In the context of cohort studies, risk refers to the number of new cases who develop the health outcome among those at risk, over a specified time period.

• It refers to the probability that a health outcome will occur.

• It is usually expressed as a percentage (ranging from 0% to 100%).


• Define the population at risk • Determine the number of new cases (those who

develop the outcome/disease) • Specify the time period

Risk = Number of new cases In specified time period

Population at risk


• 15,000 children, ages 2 to 8, who live in an area around high-voltage power lines were followed for 10 years or until the development of a childhood leukemia. Fifty cases were identified over the 10- year period.

• Risk = 50/15,000 = .0033 or .33% or 3.3 people per 1000 over 10 years

*This is a hypothetical example and does not reflect the actual risk of childhood leukemia. There is also no consistent body of evidence on an association between living near high-voltage power lines and childhood leukemia.


• Odds refers to the probability (p) of an event occurring to the probability that it will not occur (1-p).

• Odds of an event = p/(1-p) • Odds ratios (OR) are used to compare the relative odds of the

occurrence of the outcome of interest (e.g. disease or disorder), given exposure to the variable of interest (e.g. health characteristic, aspect of medical history). The odds ratio can also be used to determine whether a particular exposure is a risk factor for a particular outcome, and to compare the magnitude of various risk factors for that outcome. • OR=1 Exposure does not affect odds of outcome • OR>1 Exposure associated with higher odds of outcome • OR<1 Exposure associated with lower odds of outcome

Sources: Polit DF, Beck CT. 2012. Nursing Research: Generating and Assessing Evidence for Nursing

Practice. Szumilas M. Explaining Odds Ratios. Journal of the Canadian Academy of Child and

Adolescent Psychiatry. 2010;19(3):227-229.


• Rate refers to the number of subjects who develop an outcome (new cases) divided by the person-time at risk

• Rate accounts for the reality of a changing population through the person-time concept

• Person-time is an estimate of the actual time each person remains at risk for the health outcome (in years, months, or days). It is the sum of each participant’s time at risk before developing the outcome, leaving the study, being lost to follow-up, or dying.

Rate = Number of new cases Person-time at risk


• For more information on prevalence, incidence, risk and rate, click here.

• For more information on the concept of person- year, watch the following video, available here (6:09 minutes).


• Subjects are: • appropriate to research question, • available for follow-up, and • representative of the population to which findings will be

generalized. • Number of subjects provides adequate power. • Measurements of predictor and outcome variables

are precise and accurate. • Potential confounders are measured. • Loss to follow-up is minimized.


• Bias specific to cohort study designs • Attrition bias resulting from losing people to follow-up

• To assess the extent of attrition bias, compare baseline characteristics of those who were available and not available for follow-up

• To minimize attrition bias, • Use incentives • Collect multiple contact information items • Incorporate additional contact attempts • Include follow-ups between data collection points



• Objective: To identify risk factors for cardiovascular disease (CVD) by following its development over a long period of time in a large group of participants who had not yet developed overt symptoms of CVD or suffered a heart attack or stroke.

• Sample: 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts.

• Extensive physical examinations and lifestyle interviews to analyze common patterns related to CVD development. • Since 1948, subjects return to the study every two years. • In 1971, the Study enrolled a second generation: 5,124 of the original participants'

adult children and their spouses. • In 1994, a different cohort was enrolled to reflect a more diverse community of

Framingham (Omni cohort of the Framingham Heart Study). • In April 2002 the Study enrolled a third generation of participants (grandchildren of

Original Cohort). In 2003, a second group of Omni participants was enrolled. • Results: identification of major CVD risk factors – high blood pressure, high

blood cholesterol, smoking, obesity, diabetes, and physical inactivity. • Click here if you are interested in more information on the Framingham

Heart Study.


• Objective: To investigate factors that influence women’s health with a primary focus on cancer prevention.

• 1976 baseline sample: 122,000 registered nurses ages 30 to 55 years.

• Results: diet, physical activity and other lifestyle factors can promote better health.

• Click here if you are interested in more information on the Nurses Health Study.


• Hispanic Established Populations for the Epidemiologic Study of the Elderly

• Objectives • Estimate the prevalence of key physical and mental health conditions and

functional impairments in older Mexican Americans. • Investigate predictors of physical and mental health conditions and

functional status at baseline. • Study changes in health and functioning among survivors • Examine changes in health behaviors and key social mediators of health

status (social networks and support, various key transitions such as changes in living arrangements, widowhood, etc.).

• Sample: 1993-94 representative sample of community-dwelling Mexican-American elderly, aged 65 years and older, residing in the five southwestern states of Arizona, California, Colorado, New Mexico, and Texas. • Five follow-ups. • N = 3,050 participants with an additional 902 added at 4th follow-up.

• Note that analysis of baseline data serves as a cross-sectional study.

• Click here if you interested in more information on the H-EPESE.

  • 6310-Week 4
  • Main Non-Experimental Study Designs
  • Cohort Study Design
  • Cohort Study Design
  • Cohort Study Design
  • Steps in a Prospective �Cohort Study
  • Steps in a Retrospective �Cohort Study
  • Multiple-Cohort Design
  • Statistical Measures �in Cohort Designs
  • Risk
  • Calculating Risk
  • Example*: Risk Calculation
  • Odds
  • Rate
  • Additional Resources
  • Issues to Consider when Evaluating Cohort Studies
  • Bias Specific to �Cohort study designs
  • Examples
  • Framingham Heart Study
  • Nurses Health Study
  • Hispanic EPESE


© 2018 American Journal of Preventive Medicine. Pu reserved.


From the 1Cleve Reserve Univers Research, Medici ter for Behavior Cleveland Clinic,

Address corr Clinic Main Cam 44195. E-mail: ch


blished by Elsevier Inc. All

Associations Between Unhealthy Weight-Loss

Strategies and Depressive Symptoms

D1X XAlexander Chaitoff, D2X XMPH,1 D3X XCarol Swetlik, D4X XBA,1 D5X XCatherine Ituarte, D6X XBS,1 D7X XElizabeth Pfoh, D8X XPhD, MPH,2

D9X XLing-Ling Lee, D10X XBS,1 D11X XLeslie J. Heinberg, D12X XPhD,3 D13X XMichael B. Rothberg, D14X XMD, MPH2

Introduction: There appears to be a link between weight loss and improved mental health, but less is known about how using unhealthy weight-loss strategies impacts the odds of reporting depression.

Methods: This study includes respondents from the National Health and Nutrition Examination Survey from 2005 to 2014 who attempted to lose weight over the past year. Analysis occurred in 2017. Multivariable logistic regression was used to describe associations between all weight-loss strategies, including those grouped as unhealthy (smoking, vomiting, laxatives, skipping meals, and using diet pills), and the adjusted odds of depression (Patient Health Questionnaire−9 score ≥10). The model was then stratified by BMI, sex, race, and antidepressant use to compare the effect of using at least one unhealthy weight-loss strategy and depression within certain populations.

Results: The sample included 6,765 respondents (weighted n=59.2 million, 95% CI=55.5, 62.9 mil- lion). Of these respondents, 18.0%

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