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A Randomised Controlled Trial to Evaluate the Administration of the Health Improvement Card as a Health Promotion Tool: A Physiotherapist-led Community-based Initiative v1

2020· preprint· en· W4243952990 on OpenAlexaff
Yi-Wen Bai, Xubo Wu, Raymond S. W. Tsang, Ruisheng Yun, Yan Lü, Elizabeth Dean, Alice Jones

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHealth promotionMedicineIntervention (counseling)Physical therapyHealth educationRandomized controlled trialPromotion (chess)Report cardBiometricsNursingFamily medicinePsychologyGerontologyPublic health

Abstract

fetched live from OpenAlex

This study describes a physiotherapy-led health promotion project in Shanghai. A randominsed controlled trial was conducted to evaluate the administration of the Health Improvement Card (HIC) on lifestyle practices and biometric variables in community-dwelling Chinese participants. Adults living in Shanghai were randomly assigned to either the HIC-intervention or control group. Measurements / assessments were conducted at baseline and three-month follow-up. Supervised physiotherapy students administered the HIC and four standardised questionnaires related to health and wellbeing. Both groups received a health promotion education pamphlet. Based on participants’ HIC biometric and lifestyle scores, students prescribed lifestyle and exercise advice to the HIC-intervention group. This is the first study to demonstrate that HIC-informed health promotion education can improve people’s lifestyle practices, thereby, objective biometric variables.

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)0.017
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.497
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.005
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 head0.185
GPT teacher head0.484
Teacher spread0.299 · 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.

Study designRandomized 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

Citations0
Published2020
Admission routes1
Has abstractyes

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