OptimalMe Intervention for Healthy Preconception, Pregnancy, and Postpartum Lifestyles: Protocol for a Randomized Controlled Implementation Effectiveness Feasibility Trial
Bibliographic record
Abstract
BACKGROUND: Reproductive-aged women are a high-risk population group for accelerated weight gain and obesity development, with pregnancy recognized as a critical contributory life-phase. Healthy lifestyle interventions during the antenatal period improve maternal and infant health outcomes, yet translation and implementation of such interventions into real-world health care settings remains limited. OBJECTIVE: We aim to generate key implementation learnings to inform the feasibility of future scale up and determine the effectiveness of intervention delivery methods on engagement, experience, acceptability, knowledge, risk perception, health literacy, and modifiable weight-related health behaviors in women during preconception, pregnancy, and postpartum periods. METHODS: This randomized hybrid implementation effectiveness study will evaluate the penetration, reach, feasibility, acceptability, adoption, and fidelity of a healthy lifestyle intervention (OptimalMe) implemented into, and in partnership with, private health care. Individual health outcomes associated with implementation delivery mode, including knowledge, risk perception, health literacy, self-management, and health behaviors, are secondary outcomes. A total of 300 women aged 18 to 44 years, who are not pregnant but wish to conceive within the next 12 months, and with access to the internet will be recruited. All participants will receive the same digital lifestyle intervention, OptimalMe, which is supported by health coaching and text messages during preconception, pregnancy, and postpartum periods. We will use a parallel 2-arm design to compare telephone with videoconference remote delivery methods for health coaching. Methods are theoretically underpinned by the Consolidated Framework for Implementation Research and outcomes based on the Reach, Engagement, Adaptation, Implementation and Maintenance framework. RESULTS: The study was approved on August 16, 2019 and has been registered. Recruitment commenced in July 2020, and data collection is ongoing. Results are expected to be published in 2022. CONCLUSIONS: The study's design aligns with best practice implementation research. Results will inform translation of evidence from randomized controlled trials on healthy lifestyle interventions into practice targeting women across preconception, pregnancy, and postpartum periods. Learnings will target consumers, program facilitators, health professionals, services, and policy makers to inform future scale up to ultimately benefit the health of women across these life-phases. TRIAL REGISTRATION: Australian and New Zealand Clinical Trial Registry ACTRN12620001053910; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=378243&isReview=true. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/33625.
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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 | 0.042 | 0.033 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.011 | 0.005 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.083 | 0.013 |
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".