A systematic review of the intervention characteristics, and behavior change theory and techniques used in mother-daughter interventions targeting physical activity
Bibliographic record
Abstract
Growing gender disparities in levels of physical inactivity put women and female youths at a greater risk of associated health problems. Mother-daughter interventions have been proposed as means to promote physical activity in this at-risk cohort. However, there is a lack of clarity as to if and why these types of interventions might be effective. This systematic review examined the intervention characteristics, and behavior change theory and techniques used in these interventions to promote physical activity for mothers and daughters. PubMed, EMBASE, PsycINfO, CINAHL and Cochrane Library (Wiley) databases were searched for English language studies from inception to 13th May 2020. Interventions of any design that targeted daughters and mothers' physical activity were included. Data was extracted using the Template for Intervention Description and Replication (TIDieR) checklist, and the Behavior Change Technique (BCT) Taxonomy v1. 4962 articles were screened and 11 unique studies met the inclusion criteria. The risk of bias in studies was generally high. Narrative summary highlighted that many studies used social cognitive theory as a theoretical foundation, were based in the community and less than three months in duration with multiple sessions per week. Thirty-seven behavior change techniques were identified across studies. Some techniques were deemed potentially effective including credible source, information on the health consequences of the behavior and the self-regulatory techniques of goal-setting, self-monitoring and problem-solving. Future research should consider the use of the TIDieR guidelines and BCT Taxonomy v1 to improve the quality of information for intervention development, implementation, and reporting phases.
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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 | 0.019 | 0.081 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.015 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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, 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".