Alexithymia among Arab mothers of disabled children and its correlation with mood disorders
Bibliographic record
Abstract
OBJECTIVE: To study alexithymia among mothers with disabled children in Saudi Arabia, and to explore if alexithymia is associated to their mood difficulties, and certain demographic variables. METHODS: We conducted a prospective study during January 2011 to April 2012, on 86 mothers (study group) caring for children with physical, mental, or sensory disabilities treated at a major tertiary rehabilitation hospital in Riyadh, Saudi Arabia. A total of 32 mothers (control group) with healthy children were also included. The Hospital Anxiety and Depression Scale (HADS) was used to measure the mood symptoms of mothers. The Toronto Alexithymia Scale (TAS-20) was administered to assess the degree of alexithymia. The demographic data of mothers and children were also collected. RESULTS: The mean age of children with a disability was 5.6.+/-3.1, and for healthy children was 6.3+/-3.7 (range 1-14) years. The mean age of mothers in the study group (n=86) was 33.9+/-6.1, and in the control group (n=32) was 35.2+/-7.3 years. Mothers of children with disabilities had a significantly higher degree of alexithymia (p=0.001) and a significantly higher mean score of HADS-anxiety (p=0.042) and HADS-depression (p=0.021). Alexithymia had a significant correlation with mother's depression (p=0.0001) and anxiety (p=0.0001). No significant correlations were found between alexithymia and child's age (p=0.303), duration of disability (p=0.0941), and mother's age (p=0.235). CONCLUSION: Mothers caring for disabled children have higher features of alexithymia, and this is correlated to their elevated mood problems. Clinical implications are discussed.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".