Factors influencing engagement and dietary behaviour change of mothers and their children in a blog-delivered healthy eating intervention: a process evaluation of a randomised controlled trial
Bibliographic record
Abstract
OBJECTIVE: A randomised controlled trial found no evidence of an impact of a blog written by a registered dietitian (RD) on vegetables and fruit and milk and alternatives (e.g. soya-based beverages, yogurt and cheese) consumption - two food groups included in the 2007 version of the Canadian Food Guide - in mothers and their children compared with a control condition. To investigate these null findings, the current study explored participants' perceptions of engagement with the blog and its influence on their dietary behaviours. DESIGN: Mixed methods process evaluation using a post-intervention satisfaction questionnaire and a content analysis of mothers' comments on the blog (n 213 comments). SETTING: French-speaking adult mothers living in Quebec City, Quebec, Canada (n 26; response rate = 61·9 % of the total sample randomised to exposure to the blog). RESULTS: Most mothers (n 20/26; 76·9 %) perceived the blog useful to improve their dietary habits - with the most appreciated blog features being nutritional information and healthy recipes and interactions with fellow participants and the RD. Mothers reported several facilitators (e.g. meal planning and involving children in household food activities) and few barriers (e.g. lack of time and children's food preferences) to maternal and child consumption of vegetables and fruit and milk and alternatives. Lack of time was the principal reported barrier affecting blog engagement. CONCLUSIONS: The findings from the current study suggest that blogs written by an RD may be an acceptable format of intervention delivery among mothers, but may not alleviate all the barriers to healthy eating and engagement in a dietary intervention.
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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: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
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 | 0.014 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".