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Record W2074699596 · doi:10.1038/oby.2007.71

Constructs of Health and Environment Inform Child Obesity Prevention in American Indian Communities

2008· article· en· W2074699596 on OpenAlexaff
Alexandra Adams, Heather Harvey, David Brown

Bibliographic record

VenueObesity · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsChild and Family Research InstituteProvincial Health Services Authority
Fundersnot available
KeywordsObesityEnvironmental healthMedicineGerontologyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Obesity prevention efforts have had limited success in American Indian (AI) populations. More effective prevention programs might be designed using insights into linkages between parental health beliefs, environmental constraints and healthy lifestyle choices. METHODS AND PROCEDURES: Focus group sessions (n = 42 participants) were conducted to explore parental perspectives on children's health, diet and physical activity in three Wisconsin Tribal communities. Focus group questions were derived from preliminary interviews and observations on environmental barriers surrounding nutrition and physical activity. RESULTS: Two broad thematic areas emerged from the focus groups: child health themes and environmental themes. Health themes included views of child health (emphasizing emotional health), views on parenting, and assessment of risks to child safety. Environmental (social and physical) themes included assessments of personal support networks, assessments of local facilities and programs, and values regarding household relationships. A provisional model of family behaviors related to child nutrition and physical activity was developed to better understand these themes and the potential tensions among them. DISCUSSION: Understanding the unique cultural constructs of health and environment of AI communities can inform decision making in community-level prevention research. The proposed model served as a useful starting point for designing healthy lifestyle interventions in these AI communities. This model may also be applicable to other minority communities.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.430
Threshold uncertainty score0.998

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 studies0.0030.001
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 head0.017
GPT teacher head0.272
Teacher spread0.256 · 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 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

Citations49
Published2008
Admission routes1
Has abstractyes

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