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Record W4308261765 · doi:10.1002/bin.1918

The effects of a self‐management treatment package on daily step count in university students with depressive symptoms

2022· article· en· W4308261765 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.

Bibliographic record

VenueBehavioral Interventions · 2022
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsBrock University
Fundersnot available
KeywordsDepression (economics)PsychologyIntervention (counseling)Clinical psychologyDepressive symptomsConsistency (knowledge bases)Scale (ratio)Clinical Global ImpressionPhysical therapyPsychiatryMedicineAlternative medicineAnxiety

Abstract

fetched live from OpenAlex

Abstract Research demonstrates that exercise can decrease depressive symptoms, yet it is infrequently prescribed as an intervention. Self‐management techniques offer an effective and cost‐efficient approach to increase engagement in physical activity. The purpose of this study was to evaluate the efficacy of goal setting, self‐monitoring, and feedback for increasing daily step count in university students ( N = 4) reporting depressive symptoms. The treatment was efficacious for increasing steps for three participants with varying levels of consistency. All participants showed a decrease in some depression symptoms on the University Student Depression Inventory. Expert ratings on the Clinical Global Impression Scale indicated improvement in global functioning for three participants. Additional research is needed to determine the efficacy of this intervention package for increasing daily steps and the relation to depression symptoms.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score0.252

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.034
GPT teacher head0.356
Teacher spread0.321 · 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