A pilot study assessing art therapy as a mental health intervention for subfertile women
Bibliographic record
Abstract
BACKGROUND Subfertility is a common but hidden source of anxiety, depressive symptoms and hopelessness. Counselling reduces this emotional burden and may even enhance the likelihood of pregnancy. Art therapy may be a useful intervention, because it facilitates the expression of feelings, both visually and verbally, and may ease emotional distress. METHODS Weekly 2-h art therapy group courses were held for a total of 21 subfertile women. The impact of subfertile women's support systems and barriers to coping were all explored. The effectiveness of art therapy was assessed using Beck Hopelessness, Depression and Anxiety Inventories, administered before and after participation, as well as a qualitative exit questionnaire. RESULTS The mean age of participants was 35.7 (SD 2.1) years and duration of infertility was 64 (12.0) months. Mean Beck Hopelessness Scale fell from 6.1 (3.8) to 3.5 (3.1, P = 0.01) after therapy. Beck Depression Inventory-II Score fell from 19.8 (11.0) to 12.5 (10.2, P = 0.01) and Beck Anxiety Inventory Score changed from 12.4 (8.4) to 8.4 (5.2, P = 0.3). Based on the exit questionnaire, women felt the course was insightful, powerful and enjoyable. CONCLUSIONS Art therapy is an inexpensive, non-pharmacological intervention, which was associated with decreased levels of hopelessness and depressed mood in subfertile women. It also provides insight into the meaning and emotional implications of subfertility for patients and caregivers. This pilot study highlights the need for further research in this field.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.005 | 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".