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Record W2482183501 · doi:10.14195/978-989-26-0775-7_16

Action planning fosters adoption of regular physical activity behavior among low-control individuals with high intention

2016· book-chapter· en· W2482183501 on OpenAlex
Pier-Éric Chamberland, Paule Miquelon

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.

Bibliographic record

VenueImprensa da Universidade de Coimbra eBooks · 2016
Typebook-chapter
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsAction (physics)PsychologyControl (management)Physical activitySocial psychologyComputer scienceMedicinePhysical medicine and rehabilitationArtificial intelligence

Abstract

fetched live from OpenAlex

This study aims to document how action planning (AcP) and coping planning (CP) It was hypothesized that: 1) intention and the use of planning would each have a main effect on PA behavior, 2) AcP, with or without CP, would be useful to individuals with low PBC if their intention was high. In a quasi-experimental prospective design, 122 individuals were asked to engage regularly in PA for the 5 following weeks with the help of AcP alone, AcP and CP, or no planning at all. TPB variables and past month PA behavior were measured at T1 and frequency of PA was measured at T2. Results of an ANCOVA 2 (low vs high intention) X 3 (no planning, AcP, AcP + CP) X 3 (low, average or high PBC), which controlled for the infl uence of past behavior, revealed a main effect of intention and a signifi cant interaction between intention, planning and PBC. Simple effects analysis demonstrated that AcP alone improved PA frequency among low PBC individuals with high intention. Limits of the design as well as conceptual implications are discussed.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.926
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.043
GPT teacher head0.316
Teacher spread0.274 · 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