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Record W4386271580 · doi:10.3928/02793695-20230821-03

Group Reminiscence Programs for Older Adults Without Cognitive Impairment: A Scoping Review

2023· review· en· W4386271580 on OpenAlexafffund
Maude Dessureault, Gabrièle Dubuc, Marie‐Éve Leblanc, Lyson Marcoux

Bibliographic record

VenueJournal of Psychosocial Nursing and Mental Health Services · 2023
Typereview
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersMinistère de la SantéMinistère de la Santé et des Services sociaux
KeywordsReminiscencePsychosocialPsychological interventionPsychologyCognitionClinical psychologyPsychotherapistSession (web analytics)Cognitive impairmentGerontologyMedicinePsychiatryCognitive psychologyWorld Wide Web

Abstract

fetched live from OpenAlex

Reminiscence interventions have been tested with people with and without cognitive impairment. However, the literature on reminiscence interventions for the latter is less extensive. The purpose of the current scoping review was to list and describe group session reminiscence protocols used with older adults without cognitive impairment and not involving psychotherapy. Arksey and O'Malley's five stages scoping framework was used for this review. Seven databases were searched, and nine articles were included. Results show the heterogeneity of reminiscence programs available for older adults without cognitive impairment and highlight that key elements for replication are often lacking. Well-defined reminiscence programs should be selected for replication and evaluation studies. However, few well-defined reminiscence programs not involving psychotherapy are available for older adults without cognitive impairment. [ Journal of Psychosocial Nursing and Mental Health Services, 62 (3), 15–21.]

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.054
GPT teacher head0.480
Teacher spread0.427 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2023
Admission routes2
Has abstractyes

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Same venueJournal of Psychosocial Nursing and Mental Health ServicesSame topicIdentity, Memory, and TherapyFrench-language works237,207