Цифрова турбота та міжсесійна підтримка психоемоційного благополуччя: кейс дослідження прототипу мобільного застосунку для жінок репродуктивного віку
Bibliographic record
Abstract
The psychoemotional health of women of reproductive age requires special attention during periods of chronic stress, social displacement, and reduced access to regular psychological care. Mobile mental health technologies offer new opportunities for maintaining psychological well-being between psychotherapy sessions.The objective: to analyze the innovative international experience of using the mobile application for psychoemotional support as a tool for intersessional psychological support of psychoemotional health among women of reproductive age.Materials and methods. The study involved 827 women aged 22–45 years from 14 countries, including Ukraine, Spain, Germany, Montenegro, Hungary, Poland, the Netherlands, Portugal, Israel, the United Kingdom, Switzerland, Croatia, the USA, and Canada. The majority of participants were Ukrainians (87%), while 13% represented other nationalities. Among the total sample, 46% of women were Ukrainian residents, whereas 54% or persons were living abroad. The methodo-logy included pre- and post-intervention assessments using the GAD-7 (Generalized Anxiety Disorder scale), and Qualitative Feedback Analysis. Quantitative data were processed using IBM SPSS Statistics v.27 and Microsoft Excel 2016. Statistical indicators such as means (M), standard deviations (SD), and significance levels (p) were calculated using Student’s t-test. Additionally, qualitative feedback from anonymized user responses and semi-structured interviews was analyzed.Results. A statistically significant decrease in generalized anxiety (GAD-7) was observed in women who used mobile application for psychoemotional support, compared to those who received standard psychological support without digital tools (p ≤ 0.05). Thematic analysis of user reports revealed positive changes in mood regulation, stress resilience, and perceived safety. Participants emphasized the personalized format of the content, the emotional tone of the voice recordings, and the daily structure of the mobile application for psychoemotional support as factors that enhanced their psychological stability.Conclusions. The mobile application for psychoemotional support demonstrates strong potential as an intersessional support tool for the psychoemotional well-being of women of reproductive age. It may serve as an accessible supplement to traditional psychotherapy, especially in cross-cultural, remote, or crisis contexts. Future versions of the application could integrate biometric feedback and artificial intelligence driven personalization.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".