Examining Perceived Social Support and Levels of Happiness in Mothers of Children with Autism Spectrum Disorder
Bibliographic record
Abstract
The aim of this study is to examine perceived social support and levels of happiness in mothers of children with autism spectrum disorder. The study group of the research consists of 30 mothers providing primary care to 30 subjects (5 girls and 25 boys) aged 7-25 attending the Armağan Dönertaş Handicapped Children Education and Rehabilitation Application and Research Centre of Trakya University, and who were in the autism spectrum disorder group according to the DSM-5 criteria. In line with the purpose of the study, the participants were asked to respond to the Multidimensional Scale of Perceived Social Support, whose Turkish validity and reliability study was conducted by Doğan and Akıncı-Çötok (2011), and the Oxford Happiness Questionnaire, whose Turkish validity and reliability study was carried out by Arkar and Yaldız (2001). Based on the findings of the study, it was determined that the highest perception of social support was for Family Support. Furthermore, when evaluated in terms of standard deviations, it was determined that there was a more homogeneous distribution in this dimension compared to the others. It was seen that the distributions in the other dimensions were slightly above the mean. Considering the distribution of the happiness questionnaire, it was determined that the distribution was close to the mean. Moreover, it was determined that the minimum score was 77 and that the maximum score that could be obtained from the scale was 139, not 174. It was seen that the distribution was in the range of 62 points and remained within a limited structure. The findings of the study show that there was no significant relationship between the items of Happiness and Perceived Social Support. It is predicted that mothers’ levels of happiness will increase by benefitting from professional social support resources and services provided by social care experts.
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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 | 0.002 |
| 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 | 0.001 |
| 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".