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Record W2902860759 · doi:10.1016/j.invent.2018.11.003

Development of a self-guided web-based intervention to promote physical activity using the multi-process action control framework

2018· article· en· W2902860759 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternet Interventions · 2018
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversity of Victoria
FundersUniversity of VictoriaSocial Sciences and Humanities Research Council of CanadaHeart and Stroke Foundation of Canada
KeywordsProcess (computing)Intervention (counseling)Action (physics)Web applicationComputer scienceControl (management)Self-controlPsychologyHuman–computer interactionArtificial intelligenceWorld Wide WebPsychotherapistPhysics

Abstract

fetched live from OpenAlex

PURPOSE: Physical activity promotion has mostly focused on theories of intention-formation, with the assumption that positive intentions will lead to behaviour. Though necessary, exercise intentions alone are often not sufficient to improve physical activity behaviour. The Multi-Process Action Control (M-PAC) framework builds on previous intention-based theories by including both determinants of intention formation and its translation into behaviour. The purpose of this study was to describe the process of developing a self-guided web-based intervention to promote physical activity among adults using the M-PAC model. PROCEDURES: The development process consisted of the following three phases: 1) Intervention planning: determine intervention needs and requirements; 2) Intervention development: use an iterative process to design a web-based physical activity intervention based on the M-PAC framework; 3) Pilot testing: conduct usability and acceptability assessment on the web-based intervention to further enhance user experience. PRINCIPAL RESULTS: The intervention planning phase suggested that there is a need for web-based physical activity interventions and there is currently no web-based intervention designed using the M-PAC model. In phase two, we adopted an iterative process to develop a 10-week self-guided web-based intervention to help adults (>18 years of age) to meet 150 min of moderate to vigorous physical activity per week. The pilot testing phase yielded valuable feedback on usability, content, and design of the web-based intervention. MAJOR CONCLUSIONS: The development of a web-based physical activity intervention using the M-PAC model could further enhance the effectiveness of web-based interventions and have a significant impact on extending the reach of existing physical activity promotion programs. This study has reinforced the importance of an iterative development process that involves a multi-disciplinary team to design a web-based intervention to promote physical activity. The process enabled the team to clarify the needs for an intervention for our target users, and provided valuable feedback on the design and content of the web-based intervention. Future studies are now needed to evaluate the effectiveness of our web-based intervention.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.707
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.204
GPT teacher head0.510
Teacher spread0.306 · 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