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Record W4404113730 · doi:10.1007/s11065-024-09650-6

Implementation of Cognitive (Neuropsychological) Interventions for Older Adults in Clinical or Community Settings: A Scoping Review

2024· review· en· W4404113730 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNeuropsychology Review · 2024
Typereview
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of Saskatchewan
FundersGriffith UniversityLa Trobe University
KeywordsCINAHLPsycINFOPsychological interventionContext (archaeology)CognitionPsychologyMEDLINEDementiaClinical psychologyNeuropsychologySystematic reviewIntervention (counseling)Applied psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

Despite compelling evidence that cognitive interventions for older adults improve cognition, mood, and everyday function, few are implemented in clinical or community practice. This scoping review aims to understand the implementation frameworks and methods used and their contribution to implementation success of cognitive interventions for older adults. We followed the Preferred Reporting Items for Systematic Reviews and Meta-analysis extension for Scoping Reviews (PRISMA-ScR), and searched CINAHL, EMBASE, MEDLINE, and PSYCINFO databases, using terms related to cognitive interventions, implementation, and older adults. This resulted in 5002 studies, of which 29 were included following an iterative process. Most studies reported on implementation of cognitive stimulation for people with dementia. Only four studies used formal implementation frameworks, with three using RE-AIM, and one a process evaluation using complexity theory. The most frequently addressed implementation concepts were Acceptability, Feasibility, and Effectiveness, while Cost, Cost-Effectiveness, and Maintenance were rarely reported. Solutions to common barriers included the importance of good stakeholder relationships and engagement, a manualised intervention flexible enough to adapt to the context, and ensuring facilitators were well-trained, confident, and enthusiastic.

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.

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)0.020
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
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 score0.452
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0020.001

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 head0.824
GPT teacher head0.801
Teacher spread0.023 · 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