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Record W3010703366 · doi:10.1186/s13690-020-0397-2

Evaluating sustainability in the Childhood Obesity Research Demonstration project: the model and process

2020· article· en· W3010703366 on OpenAlexaff
Rebecca E. Lee, Dennis Kao, Nathan H. Parker, Allen M. Hallett, Camila Kochi, Maria Modelska, Hanadi S. Rifai, Daniel P. O’Connor

Bibliographic record

VenueArchives of Public Health · 2020
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsCarleton University
FundersNational Center for Chronic Disease Prevention and Health PromotionCenters for Disease Control and Prevention
KeywordsHealth services researchPublic healthProcess (computing)SustainabilityChildhood obesityHealth informaticsMedicineHealth administrationProcess managementEnvironmental healthObesityComputer scienceBusinessNursing

Abstract

fetched live from OpenAlex

BACKGROUND: In the context of health-related interventions, sustainability is the capacity to maintain the changes resulting from the intervention. These can be improved policies, practices or trends intended to improve population health. The Childhood Obesity Research Demonstration (CORD) project was a multi-site, multi-intervention collaboration testing the Obesity Chronic Care Model with interventions for childhood obesity prevention and management. We present the model, definitions and methodology used for the cross-site sustainability evaluation of CORD. METHODS: We applied the Ecologic Model of Obesity to childhood obesity interventions to operationalize four sustainability constructs: replicability, continuation of benefits, institutionalization, and community capacity. We used a triangulation approach and employed mixed methods to assess sustainability constructs at each level of the Ecologic Model of Obesity: Micro, Meso, Exo and Macro. We constructed checklists to count and code intervention activities, use of evidence-based practices among providers, and environmental factors and policies hypothesized to influence intervention sustainability. We developed in-depth interviews for principal investigators and project leads. We applied the Wilder Collaboration Factors Inventory with key stakeholders. RESULTS: Lessons learned suggested that sustainability constructs should be clearly identified and operationalized a priori. Constructs must be flexible to account for differences between intervention plans and implementation to obtain robust and informative data. CONCLUSION: Strong links are needed among researchers, program implementers and communities to accomplish consistent, robust and valuable data collection efforts to assure sustainable and healthy 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)0.035
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.621
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0350.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.834
GPT teacher head0.727
Teacher spread0.107 · 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; both teacher heads agree on what is shown here.

Study designQualitative
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

Citations4
Published2020
Admission routes1
Has abstractyes

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