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Record W3020411424 · doi:10.1177/1609406920920135

Walking Interviews and Wandering Behavior: Ethical Insights and Methodological Outcomes While Exploring the Perspectives of Older Adults Living With Dementia

2020· article· en· W3020411424 on OpenAlexaff
Adebusola Adekoya, Lorna Guse

Bibliographic record

VenueInternational Journal of Qualitative Methods · 2020
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of ManitobaRed River College
Fundersnot available
KeywordsDementiaInterviewPsychologyAgency (philosophy)GerontologyVulnerability (computing)MedicineSociologyDisease

Abstract

fetched live from OpenAlex

While the use of walking interviews is not new in health care research, this method has not been used to study the wandering behavior of older adults living with dementia in long-term care (LTC) homes. The aim of this article is to describe ethical insights and consequential methodological outcomes when walking interviews were used as a means of exploring the perspectives of older adults living with mild to moderate dementia. We suggest that our use of walking interviews with older adults who presented with wandering behavior respected participants’ agency and, at times, placed the first author in the situation of “ethical vulnerability” in the roles of researcher and clinician. The first author, an experienced nurse clinician, walked with eight participants while interviewing them about why they walk and their intended destinations. Walking interviews provided the opportunity not only to interview participants but also to observe their walking behavior and interaction with others in the LTC home. Walking interviews with older adults living with dementia who are highly mobile in the LTC home acknowledge the primacy of the research participant and the researcher as learner.

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)0.007
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.187
Threshold uncertainty score0.429

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.635
GPT teacher head0.616
Teacher spread0.019 · 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 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

Citations11
Published2020
Admission routes1
Has abstractyes

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