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Record W2428350211 · doi:10.1037/hea0000259

A tale of two models: Changes in psychological need satisfaction and physical activity over 3 years.

2015· article· en· W2428350211 on OpenAlexafffund
Katie E. Gunnell, Mathieu Bélanger, Jennifer Brunet

Bibliographic record

VenueHealth Psychology · 2015
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsUniversity of OttawaUniversité de SherbrookeChildren's Hospital of Eastern Ontario
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health ResearchFondation de la recherche en santé du Nouveau-Brunswick
KeywordsPsychologyClinical psychologySocial psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: (a) Examine longitudinal measurement invariance of scores from psychological need satisfaction (PNS) scales, and (b) examine if changes in PNS were associated with change in moderate-to-vigorous physical activity (MVPA). METHOD: Adolescents (N = 842, Mage = 10.8, SD = .6) enrolled in the Monitoring Activities of Teenagers to Comprehend their Habits (MATCH) study completed measures of PNS and MVPA every 4 months over a 3-year period (2011-14) for a total of 9 times. RESULTS: PNS scores demonstrated strong longitudinal measurement invariance (i.e., invariant factor loadings and intercepts). Latent growth curve modeling indicated that a factor representing perceptions of all 3 PNS variables was positively associated with MVPA at Time 1 (β = .562, p < .05), and that increases in the common PNS factor were associated with increases in MVPA (β = .545, p < .05) with a large effect size (Rinitial MVPA2 = .316; Rchange in MVPA2 = .301). In an alternative model, MVPA at Time 1 was associated with perceived common PNS at Time 1 (β = .602, p < .001), and increases in MVPA were associated with increases in common PNS (β = .667, p < .001) with a large effect size (Rinitial PNS2 = .363 of the Rchange in PNS2 = .426). CONCLUSIONS: Longitudinal measurement invariance was supported, and therefore PNS scores could be used to study change over time. Further, 2 equally well fitting models were found suggesting that change in PNS can be both an antecedent and an outcome of MVPA. As such, both PNS and MVPA could be targeted in interventions aimed at increasing need satisfaction or MVPA.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.396
Threshold uncertainty score0.631

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.135
GPT teacher head0.457
Teacher spread0.322 · 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

Citations35
Published2015
Admission routes2
Has abstractyes

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