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Record W4364352292 · doi:10.2196/46093

Understanding Intersectional Ageism and Stigma of Dementia: Protocol for a Scoping Review

2023· review· en· W4364352292 on OpenAlexafffundvenue
Juanita-Dawne Bacsu, August Kortzman, Sarah Fraser, Alison L. Chasteen, Jennifer MacDonald, Megan E. O’Connell

Bibliographic record

VenueJMIR Research Protocols · 2023
Typereview
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsUniversity of TorontoUniversity of OttawaUniversity of SaskatchewanThompson Rivers University
FundersConsortium canadien en neurodégénérescence associée au vieillissementCanada Research ChairsCanadian Institutes of Health ResearchAlzheimer SocietySaskatchewan Health Research FoundationThompson Rivers University
KeywordsPsycINFOCINAHLDementiaStigma (botany)MEDLINEChecklistPsychologySystematic reviewScopusGerontologySocial stigmaMedicineApplied psychologyPsychological interventionPsychiatryFamily medicineDiseasePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Ageism and stigma reduce the quality of life of older adults living with dementia. However, there is a paucity of literature addressing the intersection and combined effects of ageism and stigma of dementia. This intersectionality, rooted in the social determinants of health (ie, social support and access to health care), compounds health disparities and is, therefore, an important area of inquiry. OBJECTIVE: This scoping review protocol outlines a methodology that will be used to examine ageism and stigma confronting older adults living with dementia. The aim of this scoping review will be to identify the definitional components, indicators, and measures used to track and evaluate the impact of ageism and stigma of dementia. More specifically, this review will focus on examining the commonalities and differences in definitions and measures to develop a better understanding of intersectional ageism and stigma of dementia as well as the current state of the literature. METHODS: Guided by Arksey and O'Malley's 5-stage framework, our scoping review will be conducted by searching 6 electronic databases (PsycINFO, MEDLINE, Web of Science, CINAHL, Scopus, and Embase) and a web-based search engine (ie, Google Scholar). Reference lists of relevant journal articles will be hand-searched to identify additional articles. The results from our scoping review will be presented using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews) checklist. RESULTS: This scoping review protocol was registered with the Open Science Framework on January 17, 2023. Data collection and analysis and manuscript writing will occur from March to September 2023. The target date for manuscript submission will be October 2023. Findings from our scoping review will be disseminated through various means, such as journal articles, webinars, national networks, and conference presentations. CONCLUSIONS: Our scoping review will summarize and compare the core definitions and measures used to understand ageism and stigma toward older adults with dementia. This is significant because there is limited research addressing the intersectionality of ageism and stigma of dementia. Accordingly, findings from our study may provide critical knowledge and insight to help inform future research, programs, and policies to address intersectional ageism and stigma of dementia. TRIAL REGISTRATION: Open Science Framework; https://osf.io/yt49k. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/46093.

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)0.120
metaresearch head score (Gemma)0.118
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.120
Threshold uncertainty score0.634

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1200.118
Meta-epidemiology (narrow)0.0060.007
Meta-epidemiology (broad)0.0110.017
Bibliometrics0.0170.014
Science and technology studies0.0070.006
Scholarly communication0.0080.011
Open science0.0060.010
Research integrity0.0100.010
Insufficient payload (model declined to judge)0.0940.018

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 head0.914
GPT teacher head0.744
Teacher spread0.169 · 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 designNot applicable
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

Citations7
Published2023
Admission routes3
Has abstractyes

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