Feasibility, user experiences, and preliminary effect of Conversation Cards for Adolescents© on collaborative goal-setting and behavior change: protocol for a pilot randomized controlled trial
Bibliographic record
Abstract
Abstract Background Adolescents and providers can benefit from practical tools targeting lifestyle modification for obesity prevention and management. We created Conversation Cards for Adolescents© (CCAs), a patient-centered communication and behavior change tool for adolescents and providers to use in clinical practice. The purpose of our study is to (i) assess the feasibility of CCAs in a real-world, practice setting to inform full-scale trial procedures, (ii) assess user experiences of CCAs, and (iii) determine the preliminary effect of CCAs on changing behavioral and affective-cognitive outcomes among adolescents. Methods Starting in early 2019, this prospective study is a nested mixed-methods, theory-driven, and pragmatic pilot randomized controlled trial with a goal to enroll 50 adolescents (13–17 years old) and 9 physicians practicing at the Northeast Community Health Centre in Edmonton, Alberta, Canada. Adolescents will collaboratively set one S.M.A.R.T. (specific, measurable, attainable, realistic, timely) goal with their physician to implement over a 3-week period; however, only those randomized to the experimental group will use CCAs to inform their goal. Outcome assessments at baseline and follow-up (3 weeks post-baseline) will include behavioral, affective-cognitive, and process-related outcomes. Discussion In examining the feasibility, user experiences, and preliminary effect of CCAs, our study will add contributions to the obesity literature on lifestyle modifications among adolescents in a real-world, practice setting as well as inform the scalability of our approach for a full-scale effectiveness randomized controlled trial on behavior change. Trial registration ClinicalTrials.gov Identifier: NCT03821896.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | high |
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.064 | 0.061 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.043 | 0.007 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".