Mamma Mia: A Feasibility Study of a Web-Based Intervention to Reduce the Risk of Postpartum Depression and Enhance Subjective Well-Being
Bibliographic record
Abstract
BACKGROUND: Currently, 10-15% of women giving birth suffer from symptoms of postpartum depression. Due to a lack of knowledge of this condition and the stigma associated with it, as well as few treatment options, a large proportion of postpartum women with depression remain untreated. Internet-based interventions have been found effective in treating depression, anxiety, phobias, and addictions. Hence, we developed such program ("Mamma Mia") with the aim of reducing the risk for postpartum depression and enhance subjective well-being. Mamma Mia is based on positive psychology, metacognitive therapy, and couples therapy. It starts in gestational week 22, and lasts until 6 months after birth. During pregnancy, Mamma Mia is delivered weekly (every Monday). After birth, Mamma Mia is delivered three times per week for six weeks. The remaining weeks, the program is delivered more sporadically. In total, Mamma Mia consists of 44 sessions. The program is individualized, interactive, and tunneled (ie, the user is guided through the program in a pre-determined manner). OBJECTIVE: The purpose of the present study was to pilot test the intervention in order to assess the feasibility and acceptance among program users. METHODS: The present paper reports a feasibility study that combined quantitative survey data with semi-structured interviews. Participants (N=103) were recruited via hospitals, well-baby clinics, and Facebook. Due to time constraint in completing the current study, our results were based on participation in one of the two phases: pregnancy or maternity. Participants in the pregnancy phase were surveyed 4 and 8 weeks after intervention enrollment, and participants in the postnatal phase were surveyed 2 and 4 weeks after intervention enrollment. The survey assessed perceived usefulness, ease-of-use, credibility, and unobtrusiveness. All measures were filled in by participants at both measurement occasions. Data were analyzed by running descriptives and frequencies with corresponding percentages. Binomial tests were carried out to investigate whether demographics differed significantly from a 50/50 distribution. Paired sample t tests were used to examine differences between time 1 and 2. Four participants were interviewed in the qualitative follow-up study, where they were given the opportunity to address and elaborate on similar aspects as assessed in the survey. RESULTS: More than two-thirds of users found Mamma Mia to be of high quality and would recommend Mamma Mia to others. By far, most also found the amount of information and frequency of the intervention schedule to be appropriate. Mamma Mia was perceived as a user-friendly and credible intervention. CONCLUSIONS: Overall, the user acceptance of Mamma Mia was good and our findings add to the feasibility of the program. The effect of Mamma Mia on depression and subjective well-being will be evaluated in a large randomized controlled trial, and if found to be effective, Mamma Mia could serve as a low-threshold prevention program.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".