Seeking and receiving help for mental health services among pregnant women in Ghana
Bibliographic record
Abstract
OBJECTIVE: The heightened vulnerability of women to mental health issues during the period of pregnancy implies that seeking and receiving support for mental health services is a crucial factor in improving the emotional and mental well-being of pregnant women. The current study investigates the prevalence and correlates of seeking and receiving help for mental health services initiated by pregnant women and health professionals during pregnancy. DESIGN: Using a cross-sectional design and self-report questionnaires, data were collected from 702 pregnant women in the first, second and third trimesters from four health facilities in the Greater Accra region of Ghana. Data were analyzed using descriptive and inferential statistics. RESULTS: It was observed that 18.9% of pregnant women self-initiated help-seeking for mental health services whereas 64.8% reported that health professionals asked about their mental well-being, of which 67.7% were offered mental health support by health professionals. Diagnosis of medical conditions in pregnancy (i.e., hypertension and diabetes), partner abuse, low social support, sleep difficulty and suicidal ideation significantly predicted the initiation of help-seeking for mental health services by pregnant women. Fear of vaginal delivery and COVID-19 concerns predicted the provision of mental health support to pregnant women by health professionals. CONCLUSION: The low prevalence of individual-initiated help-seeking implies that health professionals have a high responsibility of supporting pregnant women achieve their mental health needs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".