ArticleAging & mental health
Distinct latent symptom profiles in late-onset depressive symptoms in community-dwelling older adults.
Article in Aging & mental health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 1 citations in OpenAlex.
- Late-Onset Depression in an Aging World: A Multidimensional Perspective on Risks, Mechanisms, and Treatment.Geriatrics (Basel, Switzerland) · 2026Review
- Latent profile analysis of depressive symptoms among Chinese older adults with disabilities and associated factors.Frontiers in psychiatry · 2026Article
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Authors and funding
5 authors at 3 institutions in 1 country.
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Abstract
objectivesTo examine the symptom profiles of late-onset depressive symptoms in a sample of older adults.
methodThe sample included 1,192 participants from the National Alzheimer's Coordinating Center Data Set. Participants were ≥65 years old, community-dwelling, and without cognitive impairment or a prior history of depression. Depressive symptoms were assessed using the Geriatric Depression Scale, 15-item (GDS-15). Latent class analysis (LCA) was used to identify and group participants based on profiles of depressive symptoms.
resultsLCA revealed three distinct symptom profiles: (1) an Anhedonia/Amotivation profile with a higher probability of endorsing a combination of low positive emotion and amotivation (6%), (2) an Amotivation/Withdrawal profile with a high probability of endorsing only amotivational depressive symptoms (35%), and (3) an asymptomatic profile with no probability of endorsing any depressive symptoms (59%). Amotivational depressive symptoms were observed across both symptomatic profiles, while depressed mood (e.g. sadness) did not predominantly characterize any profile in this sample. There were also significant differences among symptom profiles in terms of demographic and clinical characteristics.
conclusionsFindings highlight the importance of understanding depression at the symptom pattern level. A profile-based diagnostic approach may help improve the recognition of depressive symptoms in older adults.
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