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Record W4302303994 · doi:10.1108/qaoa-12-2021-0092

Optimizing older adult co-researchers’ involvement in PAR: proposed evaluation tool

2022· article· en· W4302303994 on OpenAlexaff
Émilie Raymond, Christophe Tremblay, Jean-Guy Lebel

Bibliographic record

VenueQuality in Ageing and Older Adults · 2022
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsCentre Jeunesse de QuebecUniversité Laval
Fundersnot available
KeywordsOriginalityOlder peopleParticipatory action researchParticipatory evaluationValue (mathematics)DignityPsychologyAction (physics)Citizen journalismAction researchPopulationSociologyGerontologyComputer scienceMedicinePedagogySocial psychologyPolitical scienceSocial science

Abstract

fetched live from OpenAlex

Purpose This paper aims to share a practical evaluation tool intended to guide and support the participation of older people in PAR projects. Participatory action research (PAR) studies with older adults have been increasing over the past ten years. Scientific evidence provides key principles for PAR projects to achieve meaningful participation by older people; however, respecting the ideals of PAR is not always straightforward. Design/methodology/approach This paper presents a case study that evaluated the involvement of nonacademic researchers in a PAR project using an evaluation tool derived from a literature review of PAR undertaken with this population (Corrado et al. , 2020). The study goals were first to assess the assets and limits of the older co-researchers’ participation within the PAR project, and second to provide a revised version of the evaluation tool to support future PAR with older people. First, the authors designed an evaluation tool for nonacademic participation in PAR studies by older people that covers three main themes: older people positioned as prominent research partners; symmetrical power relations between academic and nonacademic researchers; and commitment regarding inclusiveness and long-term collaboration. Second, the authors performed an evaluation using this tool within the Active Aging with Dignity PAR Project. Findings Third, the authors used the results of this experiment to suggest improvements for an enhanced version of the evaluation tool aiming at supporting fuller involvement of older nonacademic researchers in PAR studies. Originality/value To the authors’ knowledge, this evaluative tool is a methodological innovation in gerontology.

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)0.010
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.277
GPT teacher head0.489
Teacher spread0.212 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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
Published2022
Admission routes1
Has abstractyes

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