Prevalence of Psychiatric Disorder in Lone Fathers and Mothers: Examining the Intersection of Gender and Family Structure on Mental Health
Bibliographic record
Abstract
OBJECTIVE: While mothers head the majority of single-parent households, the percentage of father-headed, lone-parent households has increased in recent years. However, current mental health research on single parents focuses almost exclusively on single mothers. In this analysis, we disaggregate the unique and combined effects of gender and family structure on the mental health of fathers and mothers. METHODS: We used the Canadian Community Health Survey: Mental Health and Well-Being, a nationally representative population health survey. In this survey, 769 and 1964 lone fathers and mothers, respectively, and 5340 and 5505 married or cohabitating fathers and mothers, respectively, with at least 1 child aged 25 years or younger living at home, were identified. We also used the World Mental Health Composite International Diagnostic Interview (WMH-CIDI) to provide diagnoses for various anxiety and mood disorders and a revised version of the WHM-CIDI to identify substance use disorders (SUDs). RESULTS: Lone fathers and lone mothers have higher rates of mood disorders and SUDs than their married counterparts. Comparing lone parents, mothers had higher rates of anxiety disorders (10.7%, compared with 4.9%) and mood or anxiety disorders (19.9%, compared with 11.1%) than fathers but were not significantly different across total disorders when SUD was included. Social support significantly moderated effects for single-parent status and gender. Social support appears to be more of a protective factor for lone fathers than among lone mothers. CONCLUSIONS: Similar to lone mothers, lone fathers are at greater risk of psychiatric disorders than their married counterparts, indicating that this disadvantaged family structure has negative consequences for all parents.
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 | 0.001 | 0.000 |
| 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) | 0.002 | 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, 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".