Meeting the Needs of Mothers During the Postpartum Period: Using Co-Creation Workshops to Find Technological Solutions
Bibliographic record
Abstract
BACKGROUND: The postnatal period is associated with many new needs for mothers. OBJECTIVE: The aim of this study was to find technological solutions that meet the needs of mothers during the year following childbirth. METHODS: Two co-creation workshops were undertaken with parents and professionals. The aim of the first workshop was to create a list of all the criteria the proposed solution would have to address to meet the needs of mothers after childbirth. The aim of the second workshop was to create solutions in response to the criteria selected during the first workshop. RESULTS: Parents and health professionals want solutions that include empathy (ie, to help fight against the feelings of abnormality and loneliness), that help mothers in daily life, that are personalized and adapted to different situations, that are educational, and that assures some continuity in their contact with health professionals. In practice, we found that parents and professionals think the solution should be accessible to everyone and available at all times. To address these criteria, technology experts proposed different solutions, such as a forum dedicated to the postpartum period that is supervised by professionals, a centralized website, a system of videoconferencing, an online exchange group, a "gift voucher" system, a virtual reality app, or a companion robot. CONCLUSIONS: The human component seems to be very important during the postnatal period. Nevertheless, technology could be a great ally in helping mothers during the postpartum period. Technology can help reliably inform parents and may also give them the right tools to find supportive people. However, these technologies should be tested in clinical trials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".