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Effects of social support interventions on depressive symptoms and quality of life among older adults: a systematic review and meta-analysis

2025· other· en· W6959391336 on OpenAlexaff

Bibliographic record

VenueFigshare · 2025
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvances in Cucurbitaceae Research
Canadian institutionsMcGill UniversityDalhousie UniversityUniversity of Manitoba
Fundersnot available
KeywordsSocial supportPsychological interventionQuality of life (healthcare)Depression (economics)Depressive symptomsRandomized controlled trialSystematic review

Abstract

fetched live from OpenAlex

Abstract Background Interventions that include participation in social or group connections as measures to prevent or reduce depression have received little attention. This systematic review and meta-analysis aimed to determine the effects of social support interventions on depressive symptoms and Quality of life (QoL) among older adults. Methods A detailed search of six databases comprising Medline, CINAHL, PubMed, Cochrane Library, African Journals Online and Web of Science Core Collections was conducted until January 2025. A review protocol was developed and registered with the PROSPERO database (ID-CRD42021283342). A meta-analysis was used to synthesize the findings of the included studies based on subgroups of social support interventions. Of the 1524 articles found from the six databases, only 16 randomised controlled trials (14 parallel and 2 cluster) were eligible for inclusion. Conclusion Social support interventions included emotional support, social engagement, instrumental, instrumental and appraisal, and social engagement and appraisal support. Meta-analysis findings indicated that social support interventions had non-significant effects on depression and QoL among older adults. Social support interventions have the potential to reduce depressive symptoms and improve QoL. However, current evidence is insufficient to determine the impact of social support interventions on depression and QoL in older adults.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.654
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0140.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.041
GPT teacher head0.384
Teacher spread0.344 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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