ArticleBMC psychiatry2025
Agreement between CES-D and CIDI-SF scales of depression among older adults: a cross-sectional comparative study based on the longitudinal aging study in India, 2017-19.
Article in BMC psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- The Longitudinal Associations of Denture Use and Subjective Chewing Difficulty with Depressive Symptoms Among Middle-Aged and Older Adults: A Sex-Stratified Analysis of the Korean Longitudinal Study of Aging (2006-2022).Healthcare (Basel, Switzerland) · 2026Article
- Social engagement, formal education, and cognitive outcomes among older adults in India: A longitudinal population-based study.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Compensatory Effects of Long-Term Care Insurance on Mental Health Among Rural Older Women: Evidence from China.Healthcare (Basel, Switzerland) · 2026Article
- Latent profiles and network dynamics of psychological frailty in older adults: a computational simulation study.BMC geriatrics · 2026Article
- Association Between Extreme Climate Exposures and Bodily Pain: Evidence from the Chinese Health and Retirement Longitudinal Study.Journal of epidemiology and global health · 2026Article
- How migration and its types affect mental health in later life: a cross-sectional study among the older adults in India.BMC psychiatry · 2025Article
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Abstract
backgroundUnderstanding the differences between various instruments for assessing depression will help researchers and health practitioners to choose a more appropriate tool and develop a framework to enhance resilience to mental health problems in the older population. The current study aimed to compare the 10-item Center for Epidemiological Studies-Depression (CES-D) scale with the Composite International Diagnostic Interview-Short Form (CIDI-SF) for measuring depressive symptoms in older Indians.
methodsData came from the first wave of the Longitudinal Aging Study in India (LASI) which was conducted during 2017-19. The final sample included 30,368 older individuals aged 60 years and above (15,824 women and 14,544 men). The level of agreement between the CES-D and CIIDI-SF instruments for depression classification was assessed using Kappa coefficients at various cut-off values. Multivariable logistic regression models were used to examine the associations between background characteristics and depressive symptoms assessed by both instruments.
resultsThe prevalence of depressive symptoms based on the CES-D instrument was higher than that of CIDI-SF (30.2% vs. 8.3%). The level of agreement between the CES-D and CIDI-SF for depression classification was 'none' to 'minimal' (κ = 0.04-0.24). Assuming the CIDI-SF scale as the "gold standard", with rising threshold values, sensitivity of the CES-D scale decreased while specificity increased. The CES-D scale yielded a sensitivity of 29-82% and specificity of 39-92% across cut-off values of 3 to 6. The Pearson correlation between the CIDI-SF and CES-D total scores was significant but weak (r =.20). Multivariable analysis showed that depressive symptoms were more prevalent among women, those with higher education, individuals living alone, those with diagnosed psychiatric disorders, and individuals with two or more chronic conditions, compared to men, those who were uneducated, those not living alone and healthier peers, when assessed using both CES-D and CIDI-SF scales. The associations of marital status, religion and wealth quintiles were significant only for depressive symptoms assessed using the CES-D scale.
conclusionsDepression cases identified by the CES-D showed poor agreement with those identified by the CIDI-SF. Therefore, the prevalence of depressive symptoms measured by the CESD is not interchangeable with that measured by the CIDI-SF. These findings suggest the importance of using both the CES-D and CIDI-SF in large population-based cohorts and surveillance surveys to obtain more accurate and nuanced understanding of depressive disorders across various subgroups of the older population.
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