Feasibility and Acceptability of Internet-Based Interpersonal Psychotherapy for Stress, Anxiety, and Depression in Prenatal Women: Thematic Analysis (Preprint)
Bibliographic record
Abstract
BACKGROUND Prenatal mental health is a global health concern. Despite the far-reaching impact of prenatal mental health issues, many women do not receive the psychological care they require. Women in their childbearing years are frequent users of the internet and smartphone apps. Prenatal women are prime candidates for internet-based support for mental health care. OBJECTIVE This study aimed to examine the feasibility and acceptability of internet-based interpersonal psychotherapy (IPT) for prenatal women. METHODS Semistructured interviews were conducted with women who had received internet-based IPT modules with guided support as a component of a randomized controlled trial evaluating the scale-up implementation of a digital mental health platform (The Healthy Outcomes of Pregnancy and Postpartum Experiences digital platform) for pregnant women. Qualitative thematic analysis was used to explore and describe women’s experiences. Data were analyzed for emerging themes, which were identified and coded. RESULTS A total of 15 prenatal women were interviewed to examine their experiences and views on the feasibility and acceptability of internet-based IPT modules. Participants found the content informative and appreciated the ways in which the digital mental health platform made the IPT modules accessible to users. Participants voiced some differing requirements regarding the depth and the way information was presented and accessed on the digital mental health platform. The important areas for improvement that were identified were acknowledging greater depth and clarity of content, the need for sociability and relationships, and refinement of the digital mental health platform to a smartphone app. CONCLUSIONS This study provides useful evidence regarding treatment format and content preferences, which may inform future development. It also provides research data on the feasibility and acceptability of web-based applications for prenatal mental health care. CLINICALTRIAL ClinicalTrials.gov NCT01901796; https://clinicaltrials.gov/ct2/show/NCT01901796
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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 | high |
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 | 0.037 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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, 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".