Towards Improved Measurement of Individual Diet Behaviors and Food Environment Exposures: Resources from the National Collaborative on Childhood Obesity Research (P16-026-19)
Bibliographic record
Abstract
Selection of appropriate and robust measures for capturing individual-level diet behaviors and the environmental factors that influence these behaviors is critical to advancing the knowledge base on effective approaches to promote health and well-being among children. However, selecting appropriate measures for a given research or evaluation purpose from the wide-ranging options available can be challenging. To provide guidance to researchers and practitioners working with child and adolescent populations, the National Collaborative on Childhood Obesity Research (NCCOR) has developed a suite of resources, including the Measures Registry, User Guides, and eLearning Modules. The Measures Registry is a free searchable database of nearly 1400 diet and physical activity measures relevant to childhood obesity research. The User Guides, introduced in 2017 to complement the Measures Registry, discuss critical issues in measurement and walk users through the process of selecting and implementing appropriate measures for their research and evaluation. In 2018, the Registry was viewed almost 13,000 times, and the User Guides were viewed over 25,000 times. More recently, eLearning modules were introduced to summarize critical considerations from the User Guides in an engaging, interactive manner. Use of this suite of resources can support selection of the most appropriate measures of diet behaviors and food environment exposures for a given study or evaluation and foster greater standardization of measures across studies. In addition to highlighting the resources, in this session, we will provide an overview of key challenges and considerations in selecting measures of diet behaviors and food environments and demonstrate the use of the resources, the Registry, User Guides and eLearning Modules, to show how to identify appropriate measures for a given research purpose. In the long-term, robust measurement of diet behaviors and food environments can strengthen the evidence base for intervening to improve children’s health and well-being. NCCOR is funded by NIH, CDC, USDA, and RWJF. Additional funding to support the development of the NCCOR measurement resources has been provided by The JPB Foundation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".