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Record W2991499223 · doi:10.1016/j.jneb.2019.10.010

Survey of Barriers and Facilitators to Engagement in a Multidisciplinary Healthy Lifestyles Program for Children

2019· article· en· W2991499223 on OpenAlexvenueno aff
C. Wild, Niamh O’Sullivan, Arier Lee, Tami L. Cave, Esther Willing, Donna Cormack, Paul L. Hofman, Yvonne C. Anderson

Bibliographic record

VenueJournal of Nutrition Education and Behavior · 2019
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
FundersCure Kids
KeywordsAttendanceMultidisciplinary approachIndigenousIntervention (counseling)ConfidentialityPsychologyNursingFamily medicineMedicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To understand facilitators and barriers to engagement in a multidisciplinary assessment and intervention program for children and adolescents with obesity, particularly for Māori, the Indigenous people of New Zealand. METHODS: Whānau Pakari participants and caregivers (n = 71, 21% response rate) referred to the family-based healthy lifestyles program in Taranaki, New Zealand, were asked to participate in a confidential survey, which collected self-reported attendance levels and agreement with statements around service accessibility and appropriateness and open-text comments identifying barriers and facilitators to attendance. RESULTS: Self-reported attendance levels were higher when respondents reported sessions to be conveniently located (P = .03) and lower when respondents considered other priorities as more important for their family (P = .02). Māori more frequently reported that past experiences of health care influenced their decision to attend (P = .03). Facilitators included perceived convenience of the program, parental motivation to improve child health, and ongoing support from the program. CONCLUSIONS AND IMPLICATIONS: Program convenience and parental and/or self-motivation to improve health were facilitators of attendance. Further research is required to understand the relationship between past experiences with health care and subsequent engagement with services.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.051
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.002
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 head0.025
GPT teacher head0.366
Teacher spread0.341 · 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 source (direct Gemma or distilled Codex), 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

Citations14
Published2019
Admission routes1
Has abstractno

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