Evidence map›Paper›PMID 42839307›Full record

SynthesisBrain and behavior2026

Prevalence and Predictors of Depressive Symptom Trajectories in Older Adults: A Systematic Review.

Yuying Li, Qiuyan Liu, Xue Dong

Abstract readSystematic Review
In one paragraph

Synthesis in Brain and behavior, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yuying LiDepartment of Nursing, Changchun University of Chinese Medicine, Changchun, Jilin, China.ORCID https://orcid.org/0009-0008-5708-3165
Qiuyan LiuDepartment of Nursing, Changchun University of Chinese Medicine, Changchun, Jilin, China.
Xue DongDepartment of Nursing, Changchun University of Chinese Medicine, Changchun, Jilin, China.ORCID https://orcid.org/0000-0002-5874-3451

Funding

Scientific Research Program of Education Department of Jilin ProvinceThe Education Department of Jilin Provincial No. JJKH20250671KJ
6 · The paper itself

Abstract

purposeTo describe the distribution patterns and cross-study heterogeneity of depressive symptom trajectories in older adults and to identify consistent predictors of high-symptom trajectories for targeted intervention strategies.

methodsFollowing PRISMA 2020 guidelines, six databases were searched from April 2010 to January 2026 for longitudinal studies using latent variable mixture models in adults aged ≥ 60 years. Study quality was assessed using the Newcastle-Ottawa Scale. Descriptive synthesis was employed due to methodological heterogeneity.

resultsTwenty-one studies (median N = 3428; 26 observations after accounting for within-study stratification by sex, poverty status, and country) met inclusion criteria. High-symptom trajectories were identified in 18 of 21 studies (0%-42.2%). Low-symptom trajectories predominated (12.4%-84.5%). Consistent risk factors included female sex, functional limitations, and multimorbidity. Higher educational attainment was the most consistent protective factor.

conclusionsOlder adults exhibit heterogeneous depressive symptom trajectories, with clinically significant high-symptom subgroups universally present but context-dependent. Modifiable predictors provide evidence for precision prevention strategies. Because estimates are descriptive and derived from heterogeneous instruments, they should be interpreted as heuristic indicative ranges rather than precise global benchmarks. Standardized assessment protocols are needed to enable quantitative synthesis.

Indexed as

DepressionAgedFemaleHumansMiddle AgedPrevalenceRisk Factorsgeriatric depressionrisk factorssystematic reviewtrajectory analysis

Identifiers

PMID42839307
PMCPMC13642571

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.