Dataset Information

The Center for Epidemiologic Studies-Depression (CES-D) scale measures a continuum from well-being to depression: Testing two key predictions of positive clinical psychology.

ABSTRACT:

Background

Two core but untested predictions of Positive Clinical Psychology (PCP) are that (1) Many psychiatric problems can be understood as one end of bipolar continua with well-being, and (2) that reducing psychiatric symptoms will provide an equal (near linear) decrease in risk for several other psychiatric variables, irrespective of position on continua.

Aims

We test these predictions in relation to a purported well-being/depression continuum, as measured by the Center for Epidemiologic Studies-Depression (CES-D), a popular measure of depressive experiences in research and clinical practice.

Method

A large (N=4138), diverse sample completed the CES-D, which contains a mixture of negatively worded and positively worded items (e.g., "I felt sad," "I enjoyed life"). The latter are conventionally reverse scored to compute a total score. We first examined whether purportedly separate well-being and depression CES-D factors can be reconceptualised as a bipolar well-being/depression continuum. We then characterised the (linear or nonlinear) form of the relationship between this continuum and other psychiatric variables.

Results

Both predictions were supported. When controlling for shared method bias amongst positively worded items, a single factor well-being/depression continuum underlies the CES-D. Baseline levels on this continuum are found to have near linear relationships with changes in anxiety symptoms, aggression, and substance misuse over time, demonstrating that moving from depression to well-being on the CES-D provides an equal decrease in risk for several other psychological problems irrespective of position on the continuum.

Limitations

The CES-D does not measure well-being as comprehensively as established scales of well-being.

Conclusions

Results support calls for mental health services to jointly focus on increasing well-being and reducing distress, and point to the value of early intervention and instilling resilience in order to prevent people moving away from high levels of well-being.

SUBMITTER: Siddaway AP

PROVIDER: S-EPMC6191531 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Publications

The Center for Epidemiologic Studies-Depression (CES-D) scale measures a continuum from well-being to depression: Testing two key predictions of positive clinical psychology.

Siddaway Andy P AP Wood Alex M AM Taylor Peter J PJ

Journal of affective disorders 20170220

<h4>Background</h4>Two core but untested predictions of Positive Clinical Psychology (PCP) are that (1) Many psychiatric problems can be understood as one end of bipolar continua with well-being, and (2) that reducing psychiatric symptoms will provide an equal (near linear) decrease in risk for several other psychiatric variables, irrespective of position on continua.<h4>Aims</h4>We test these predictions in relation to a purported well-being/depression continuum, as measured by the Center for E ...[more]

PMID: 28254608

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Project description:BackgroundDepression is among the top mental health problems with a major contribution to the global burden of disease. This study aimed at identifying the latent factor structure and construct validity of the Center for Epidemiologic Studies Depression (CES-D) Scale.Participants and settingA cross-sectional survey of 562 adults aged 18 years and above who were randomly selected from the Eritrean refugee community living in the Mai-Aini refugee camp, Ethiopia.MeasuresThe CES-D Scale, Primary Care PTSD (PC-PTSD) screener, premigration and postmigration living difficulties checklist, Oslo Social Support Scale (OSS-3), Sense of Coherence Scale (SoC-13), Coping Style Scale and fast alcohol screening test (FAST) were administered concurrently. Confirmatory factor analysis was employed to test prespecified factor structures of CES-D.ResultFirst-order two factors with second-order common factor structure of CES-D (correlated error terms) yielded the best fit to the data (Comparative Fit Index =0.975; root mean square error of approximation=0.040 [90% CI 0.032 to 0.047]). The 16 items defining depressive affect were internally consistent (Cronbach's α=0.932) and internal consistency of the 4 items defining positive affect was relatively weak (Cronbach's α=0.703). These two latent factors have a weaker standardised covariance estimate of 33% (24% for women and 40% for men), demonstrating evidence of discriminant validity. CES-D is significantly associated with measures of adversities, specifically, premigration living difficulties (r=0.545, p<0.001) and postmigration living difficulties (r=0.47, p<0.001), PC-PTSD (r=0.538, p<0.001), FAST (r=0.197, p<0.001) and emotion-oriented coping (r=0.096, p˂0.05) providing evidence of its convergent validity. It also demonstrated inverse association with measures of resilience factors, specifically, SoC-13 (r=-0.597, p<0.001) and OSS-3 (r=-0.319, p<0.001). The two correlated factors model of CES-D demonstrated configural, metric, scalar, error variance and structural covariance invariances (p>0.05) for both men and women.ConclusionsUnlike previous findings among Eritreans living in USA, second-order two factors structure of CES-D best fitted the data for Eritrean refugees living in Ethiopia; this implies that it is important to address culture for the assessment and intervention of depression.

Project description:Aims: Depression is prevalent among university students worldwide, and the prevalence appears to be increasing. As an intermediate stage between being healthy and having depression, students with subthreshold depression could develop worsening depression or recover with intervention to prevent depression. The Center for Epidemiologic Studies Depression Scale (CES-D) is a useful tool to assess subthreshold depression. The primary purpose of the current study was to evaluate the psychometric characteristics of CES-D in Chinese university students. Secondly, we aimed to describe the prevalence of subthreshold depression among the student sample and examine its demographic correlates. Methods: A total of 2,068 university students participated in the study, and they were asked to respond to the Chinese CES-D, Beck Depression Inventory-II (BDI-II), and Positive and Negative Affect Schedule (PANAS). The factor structure was evaluated by conducting exploratory (EFA) and confirmatory factor analysis (CFA) using a structural equation modeling approach. The reliability was assessed by calculating Cronbach's alpha, inter-item correlation, and item-total correlation coefficients. The prevalence of subthreshold depression was calculated and demographic correlates of gender, grade, and major were examined by multiple regression. Results: The final sample included 1,920 participants. The EFA results suggested extraction of three factors (somatic symptoms, negative affect, and anhedonia) that account for 52.68% of total variance. The CFA results suggested that the newly derived model with 14 items was the best fit for our data. Six items were removed from the original scale (item 9, 10, 13, 15, 17, and 19). The Cronbach's alpha of the 14-item CES-D was 0.87. The prevalence of subthreshold depression among university students reached 32.7% for the 20-item CES-D and 31% for the 14-item CES-D, although there was no significant difference of prevalence in gender, grade, and major. Conclusions: The CES-D has good reliability and validity for assessing subthreshold depression in Chinese university students.

Project description:OBJECTIVE:We aimed to collect and meta-analyse the existing evidence regarding the performance of the Center for Epidemiologic Studies Depression (CES-D) for detecting depression in general population and primary care settings. METHOD:Systematic literature search in PubMed and PsychINFO. Eligible studies were: a) validation studies of screening questionnaires with information on the accuracy of the CES-D; b) samples from general populations or primary care settings; c) standardized diagnostic interviews following standard classification systems used as gold standard; and d) English or Spanish language of publication. Pooled sensitivity, specificity, likelihood ratios and diagnostic odds ratio were estimated for several cut-off points using bivariate mixed effects models for each threshold. The summary receiver operating characteristic curve was estimated with Rutter and Gatsonis mixed effects models; area under the curve was calculated. Quality of the studies was assessed with the QUADAS tool. Causes of heterogeneity were evaluated with the Rutter and Gatsonis mixed effects model including each covariate at a time. RESULTS:28 studies (10,617 participants) met eligibility criteria. The median prevalence of Major Depression was 8.8% (IQ range from 3.8% to 12.6%). The overall area under the curve was 0.87. At the cut-off 16, sensitivity was 0.87 (95% CI: 0.82-0.92), specificity 0.70 (95% CI: 0.65-0.75), and DOR 16.2 (95% CI: 10.49-25.10). Better trade-offs between sensitivity and specificity were observed (Sensitivity = 0.83, Specificity = 0.78, diagnostic odds ratio = 16.64) for cut-off 20. None of the variables assessed as possible sources of heterogeneity was found to be statistically significant. CONCLUSION:The CES-D has acceptable screening accuracy in the general population or primary care settings, but it should not be used as an isolated diagnostic measure of depression. Depending on the test objectives, the cut-off 20 may be more adequate than the value of 16, which is typically recommended.

Project description:BACKGROUND:Depression is a prevalent and serious mood disorder and a major source of disability adjusted life years (DALY) in Uganda. Furthermore, evidence from Uganda and other countries throughout sub-Saharan Africa suggests that nearly a third of persons living with human immunodeficiency virus (HIV) suffer from depression and it adversely affects healthcare seeking behavior. The high burden of disease attributable to depression makes data on the prevalence of depression in Uganda, a country with a generalized HIV epidemic, a public health priority. This paper describes the psychometric properties of the Center for Epidemiologic Studies-Depression (CES-D) measure when administered to men and women residing in three fishing communities along the shore of Lake Victoria. METHODS:We applied methods based on item response theory and classical test theory approaches to assess individual item characteristics, conducted exploratory factor analysis and assessed internal reliability, and construct and content validity of the measure. All analyses were performed in R Studio. RESULTS:The study sample consisted of 300 residents of fishing communities in Wakiso District, Uganda. Fifty-six percent of the sample was female and 19.7% reported being HIV positive. Seven items of the measure that did not perform well, either because they could not differentiate between levels of the latent trait or because they did not map onto the primary factor, were removed from the scale. A single factor structure best fit our final set of 13-items and we found an overall coefficient alpha of 0.89, indicating high internal consistency in this population. CONCLUSIONS:Based on our findings, we recommend that future use of the CES-D in this population utilize our revised scale with the final set of 13-items. The addition of other measures that can improve the rigor of CES-D validation efforts, such as inclusion of a clinical depression measure and administration in both a clinical and a general population sample in this setting are needed.

Dataset Information

The Center for Epidemiologic Studies-Depression (CES-D) scale measures a continuum from well-being to depression: Testing two key predictions of positive clinical psychology.

Background

Aims

Method

Results

Limitations

Conclusions

Publications

The Center for Epidemiologic Studies-Depression (CES-D) scale measures a continuum from well-being to depression: Testing two key predictions of positive clinical psychology.

Similar Datasets

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