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Record W2802981747 · doi:10.2196/resprot.9902

Characteristics of Cognitive Behavioral Therapy for Older Adults Living in Residential Care: Protocol for a Systematic Review

2018· review· en· W2802981747 on OpenAlexvenueno aff
Phoebe Chan, Sunil Bhar, Tanya E. Davison, Colleen Doyle, Bob G. Knight, Deborah Koder, Ken Laidlaw, Nancy A. Pachana, Yvonne Wells, Viviana M. Wuthrich

Bibliographic record

VenueJMIR Research Protocols · 2018
Typereview
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsProtocol (science)GerontologyCognitionMedicineResidential careDementiaPsychologyClinical psychologyAlternative medicinePsychiatryDisease

Abstract

fetched live from OpenAlex

BACKGROUND: The prevalence rates of depressive and anxiety disorders are high in residential aged care settings. Older adults in such settings might be prone to these disorders because of losses associated with transitioning to residential care, uncertainty about the future, as well as a decline in personal autonomy, health, and cognition. Cognitive behavioral therapy (CBT) is efficacious in treating late-life depression and anxiety. However, there remains a dearth of studies examining CBT in residential settings compared with community settings. Typically, older adults living in residential settings have higher care needs than those living in the community. To date, no systematic reviews have been conducted on the content and the delivery characteristics of CBT for older adults living in residential aged care settings. OBJECTIVE: The objective of this paper is to describe the systematic review protocol on the characteristics of CBT for depression and/or anxiety for older adults living in residential aged care settings. METHODS: This protocol was developed in compliance with the recommendations of the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P). Studies that fulfill the inclusion criteria will be identified by systematically searching relevant electronic databases, reference lists, and citation indexes. In addition, the PRISMA flowchart will be used to record the selection process. A pilot-tested data collection form will be used to extract and record data from the included studies. Two reviewers will be involved in screening the titles and abstracts of retrieved records, screening the full text of potentially relevant reports, and extracting data. Then, the delivery and content characteristics of different CBT programs of the included studies, where available, will be summarized in a table. Furthermore, the Downs and Black checklist will be used to assess the methodological quality of the included studies. RESULTS: Systematic searches will commence in May 2018, and data extraction is expected to commence in July 2018. Data analyses and writing will happen in October 2018. CONCLUSIONS: In this section, the limitations of the systematic review will be outlined. Clinical implications for treating late-life depression and/or anxiety, and implications for residential care facilities will be discussed. TRIAL REGISTRATION: PROSPERO 42017080113; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=80113 (Archived by WebCite at http://www.webcitation.org/70dV4Qf54). REGISTERED REPORT IDENTIFIER: RR1-10.2196/9902.

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)0.075
metaresearch head score (Gemma)0.101
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.078
Threshold uncertainty score0.399

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0750.101
Meta-epidemiology (narrow)0.0060.006
Meta-epidemiology (broad)0.0180.020
Bibliometrics0.0130.013
Science and technology studies0.0050.004
Scholarly communication0.0080.008
Open science0.0050.005
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0780.010

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 head0.435
GPT teacher head0.683
Teacher spread0.247 · 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
GenreProtocol

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

Citations16
Published2018
Admission routes1
Has abstractyes

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