The mediating effect of positive expectations in the relationship between social support and post-traumatic stress disorder symptoms among parents of children with acute lymphoblastic leukemia
Bibliographic record
Abstract
PURPOSE: Parents of children with cancer are exposed to risks of developing post-traumatic stress disorder (PTSD) symptoms, but few studies have explored PTSD symptoms of Chinese parents of children with acute lymphoblastic leukemia (ALL). Our study aimed to examine the association between social support and PTSD symptoms and to examine the mediating effect of positive expectations in this relationship among parents of children with ALL. METHODS: A cross-sectional study was conducted of consecutive parents of children with ALL in the Shengjing Hospital of China Medical University. A total of 177 parents eligible for this study completed questionnaires on PTSD symptoms, perceived social support, optimism and general self-efficacy anonymously. Asymptotic and resampling strategies were used to examine how positive expectations mediated the association between perceived social support and PTSD symptoms. RESULTS: Mean score of PTSD symptoms was 37.64 ± 14.44; 29.4% of the sample scored 44 and above, 19.8% scored 50 and above. After adjusting for covariates, perceived social support was negatively associated with the total score of PTSD symptoms (β = -0.209, p < 0.01). Positive expectations were found to mediate the relationship between perceived social support and PTSD symptoms, especially for the symptoms of avoidance and hyperarousal. CONCLUSIONS: Optimism and general self-efficacy fully mediated the association between perceived social support and PTSD symptoms. Therefore, social support and positive expectations should be included in PTSD preventions and treatments targeting Chinese parents of children with ALL.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".