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Record W4404473992 · doi:10.1002/ijop.13269

Virtual motivational interviewing for physical activity among older adults: A non‐randomised, mixed‐methods feasibility study

2024· article· en· W4404473992 on OpenAlexaff
Olayinka Akinrolie, Jacquie Ripat, Shaelyn M. Strachan, Sandra C. Webber, Allister McNabb, Jennifer Peters, Sasha M. Kullman, Ruth Barclay

Bibliographic record

VenueInternational Journal of Psychology · 2024
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMotivational interviewingAttritionPsychologyInterviewClinical psychologyPhysical activityIntervention (counseling)Physical therapyMedicinePsychiatry

Abstract

fetched live from OpenAlex

The objective of this study was to evaluate the feasibility of Virtual Motivational Interviewing (VIMINT) for improving physical activity among community-dwelling older adults. A feasibility study using a mixed-method single-group pre- and post-design. Each participant received five sessions of motivational interviewing (MI) through the Zoom platform. Feasibility and acceptability were assessed through recruitment, attrition and retention rates; adherence; satisfaction; counsellors' competency; and interviews with participants and counsellors. Other outcomes including physical activity were assessed at baseline, post- and 2-month follow-up. Eight participants were recruited; the mean age was 68.9 ± 3.9 years. The retention rate was 88%, 92.5% of the sessions were attended, and the participants' satisfaction score was 24.14 ± 7.3/32. The counsellors were rated as "good" and "fair" in relational and technical components, respectively. The categories derived from qualitative analysis were session composition, acceptability of outcome measures, positive impact of the VIMINT study and suggestions to improve future studies. The findings showed that VIMINT intervention should be feasible and acceptable for older adults. Evidence from this study provides relevant information that will guide the planning of future studies investigating the effectiveness of virtual MI on physical activity among community-dwelling older adults.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.914
Threshold uncertainty score0.544

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.083
GPT teacher head0.506
Teacher spread0.423 · 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
Published2024
Admission routes1
Has abstractyes

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