Psychological Stress and Perceived Self-Efficacy in Mothers of Autistic Children
Bibliographic record
Abstract
Background: Literature has indicated that parents of autistic children face higher stress levels than parents of allistic children (non-autistic children), leading them to experience depressive symptoms that impact their daily lives, reducing their quality of life. This study aims to investigate the relationship between psychological stress and perceived self-efficacy in mothers and fathers of autistic children. Methods: This study is descriptive and cross-sectional. A total of 125 mothers and fathers consented to participate in the current study. 15 parents only partially completed the survey, so their data was not included. The remaining 110 cases were included. This left a final sample of 110 parents of autistic children, 100 mothers (90.9 %), and 10 fathers (9.1%). All were biological parents. Results: As indicated by the results, all statements in the Parental distress (PD) subscale had a score ranging between high (the majority of items, 10) to medium (two items). All statements in the Parent-Child Dysfunctional interaction (P-CDI) subscale had a score ranging between high (the majority of items, 10) to low (two items). All statements in the Difficult Child (DC) subscale scored high. The whole subscale had a mean score of 4.04 (SD=3.17) with a high score. For correlations, psychological stress was negatively correlated with perceived self-efficacy (r = -0. 34, p < 0.001). Conclusion: The stress experienced during the nurturing of children with disabilities is a factor that threatens the psychological well-being of mothers of autistic children.
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 | 0.000 | 0.003 |
| 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) | 0.002 | 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".