The Canadian Healthy Life Trajectories Initiative (HeLTI) Trial: a study protocol for monitoring fidelity of a preconception-lifestyle behaviour intervention
Bibliographic record
Abstract
BACKGROUND: In evaluating technology-based behaviour change interventions, it is increasingly important to have a monitoring plan for intervention fidelity. It is important to maintain intervention fidelity to ensure that the theory-based intervention that is being tested is what causes the observed changes, particularly for eHealth behaviour change interventions. In this protocol, we outline the intervention fidelity and monitoring protocol for Healthy Life Trajectory Initiative (HeLTI) Canada, a randomized controlled trial evaluating the effect of a preconception-early childhood technology-based intervention delivered by public health nurses among pregnancy-planning women and their partners to optimize child growth and development. METHODS: The HeLTI Canada fidelity protocol is based on the National Institutes of Health Behaviour Change Consortium (NIH BCC) Treatment Fidelity Framework, outlining the following components of intervention fidelity: study design, provider training, intervention delivery, intervention receipt, and intervention enactment. The intervention fidelity components and associated monitoring strategies were developed to align with the HeLTI Canada approach. Strategies for intervention fidelity monitoring include a pre-post written evaluation of training, standardization of provider training, use and monitoring of activity logs, and intervention session checklists. Possible challenges to intervention fidelity include provider turnover due to the length of the trial and lack of ability to directly monitor participant behaviour change in real-life settings. Details about intervention fidelity monitoring are provided in detail. The study launched in January 2021 and is currently recruiting. DISCUSSION: Using the NIH BCC Treatment Fidelity Framework, HeLTI Canada has a robust framework for monitoring and reporting intervention fidelity to improve intervention validity, ability to assess intervention effectiveness, and transparency. TRIAL REGISTRATION: ISRCN ISRCTN13308752 . Registered on February 29, 2019.
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How this classification was reachedexpand
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 | 0.091 | 0.060 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.042 | 0.006 |
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 source (direct Gemma or distilled Codex), 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".