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Record W2175095300 · doi:10.2196/resprot.4623

Changes in Physical Activity and Psychological Variables Following a Web-Based Motivational Interviewing Intervention: Pilot Study

2015· article· en· W2175095300 on OpenAlexvenueno aff
Sasha Karnes, Barbara B. Meyer, Lisa Berger, Michael J. Brondino

Bibliographic record

VenueJMIR Research Protocols · 2015
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsnot available
Fundersnot available
KeywordsMotivational interviewingPsychologyApplied psychologyIntervention (counseling)Physical activityClinical psychologyPsychological interventionMedicinePhysical therapyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Web-based interventions for enhancing physical activity participation are in demand for application in health care settings. Recent research suggests Web-based interventions that are based on motivational interviewing are effective to increase physical activity. It is unclear whether motivational interviewing can influence targeted psychological variables such as perceived readiness, willingness, and ability to participate in physical activity. OBJECTIVE: The aims of this study were to determine whether there were changes in physical activity and psychological variables associated with readiness, willingness, and perceived ability to participate in physical activity following completion of a novel Web-based intervention. The goal of the motivational interviewing-based intervention was to increase physical activity. METHODS: Twenty-three underactive or inactive urban dwelling adults were recruited at a medical office for participation in a 4-session Web-based intervention lasting approximately 15 minutes per week. Sessions were based on principles of motivational interviewing. Assessment of physical activity was conducted using pedometers immediately prior to intervention participation (pre) and immediately post intervention (post1). Self-report assessments of physical activity and psychological variables were conducted using online surveys at pre, post1, and again at one month following intervention participation (post2). RESULTS: Comparisons of pre and post1 pedometer recordings revealed significant increases in steps per day (t22=2.09, P=.049). There were also significant changes in total physical activity energy expenditure per week (χ(2) 2=8.4, P=.02) and in moderate intensity physical activity energy expenditure per week (χ(2) 2=13.9, P<.001) over time following participation in the Web-based intervention. Significant changes in psychological variables following participation in the Web-based intervention included: (1) change in stage classification over time (χ(2) 2=21.5, P<.001), where the percentage of participants classified in the action or maintenance stages of change in physical activity increased over time (pre=25% [6/24], post1=71% [17/24], post2=68% [15/22]); (2) decreases in self-reported decisional balance cons (F2,42=12.76, P<.001); (3) increases in self-reported decisional balance pros (F2,42=16.19, P<.001); (4) increases in physical activity enjoyment (F2,20=3.85, P=.04); and (5) increases in self-efficacy (F2,42=3.30, P=.047). CONCLUSIONS: The Web-based intervention piloted in this study shows preliminary promise as a tool to promote physical activity in health care settings. Additional research is needed to test the effectiveness of motivational interviewing compared to a control condition and to refine content by considering mediation by psychological variables in a larger sample.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.671
GPT teacher head0.619
Teacher spread0.052 · 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 designNon-randomized trial
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
Published2015
Admission routes1
Has abstractyes

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