Considerations for the design of a perinatal mindfulness intervention for adolescents based on a systematic review of the literature
Bibliographic record
Abstract
Objectives: This systematic review of the literature was conducted to determine the best way to design mindfulness interventions for perinatal adolescent mothers to support mental health during the transition to parenthood and beyond. Perinatal adolescents face unique challenges compared to adults due to their developmental stage and difficulties accessing social determinants of health. Mindfulness educational interventions may be an ideal addition to perinatal supports to foster resilience and teach skills to reduce stress, anxiety, and depression. Methods: A search strategy was developed to identify articles from 6 electronic databases including PsycInfo, ProQuest, PubMed, Cochrane Library, Ovid, and CINAHL. Qualitative analysis was done to identify mindfulness interventions which significantly decrease anxiety, depression or stress and to determine the components and designs of these interventions. Participants’ satisfaction with the interventions were analyzed, when available. Best practices for designing interventions for adolescents were used to recommend adaptations to the mindfulness interventions to tailor them to the perinatal adolescent population. Results: Of the 561 studies retrieved from the search, 16 met the inclusion criteria. All included studies found at last one significant decrease in mental health outcomes (stress 9 of 13, anxiety 9 of 9; depression 9 of 14). The majority of the interventions began in the perinatal period, were delivered face-to-face, included homework, multiple sessions and by a trained professional. Conclusion: Mindfulness interventions are feasible, acceptable and effective in adult perinatal populations. Components and design of these interventions could be adapted for perinatal adolescents to increase resilience to cope with unique parenthood challenges.
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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 | 0.239 | 0.396 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.010 | 0.012 |
| Bibliometrics | 0.023 | 0.013 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".