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Record W4224276803 · doi:10.21853/jhd.2022.165

‘My Wellbeing Journal’: Using experience-based co-design to improve caring for older adults with multimorbidity

2022· article· en· W4224276803 on OpenAlexaff
Michael Lawless, Matthew Wright-Simon, Maria Alejandra Pinero de Plaza, Rachel C. Ambagtsheer, Tim Schultz, Rachel Milte, Lucy K. Lewis, Lyn Whiteway, Marilyn von Thien, Mandy M. Archibald, Alison Kitson

Bibliographic record

VenueThe Journal of Health Design · 2022
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsUniversity of Manitoba
FundersAustralian Association of Gerontology
KeywordsStakeholderProcess (computing)MultimorbidityCo-designStakeholder engagementPsychologyProcess managementComputer scienceKnowledge managementEngineeringPublic relationsComorbidity

Abstract

fetched live from OpenAlex

In this study, we investigated whether using an accelerated experience-based co-design (EBCD) approach is an effective way to involve multiple stakeholder perspectives in the development of a creative tool to support goal setting in care planning for older adults with multimorbidity. We describe the iterative multi-stage approach of developing “My Wellbeing Journal”, an innovative tool that incorporates consumer experiences and priorities and research evidence on goal-based shared decision-making. The EBCD process ensured stakeholders were involved in every stage of the design and development of the journal. We also discuss procedural and methodological considerations for others conducting similar co-design research.

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)0.016
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.527
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0060.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.313
GPT teacher head0.452
Teacher spread0.138 · 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.

Study designQualitative
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

Citations3
Published2022
Admission routes1
Has abstractyes

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