The Effect of Time Management Training on Occupational Performance, Depression, Quality of Life and Stress Management in Mothers Having Disabled Child: A Pilot Study
Bibliographic record
Abstract
Purpose: The aim of the study is to evaluate the effects of time management trainings on occupational performance, depression, life quality and coping stress of mothers of disabled children. Materials and Method: 20 mothers of disabled children were included. A group of 10 mothers were given 2-hours time management training while test group of 10 mother were observed without interference. Canadian Occupational Performance Measure was used to evaluate the pre-training and post-training activity performance, Beck Depression Inventory to measure depression level, The Short Form Health Survey to evaluate quality of life, The Ways of Coping Questionnaire for ways of handling stress, and Time Management Inventory were used to measure time management. Results: Significant changes were observed in the study group in time planning, saving and spending areas, meaningful differences were seen in physical functions, pain, vitality, mental health, optimistic approach and submissive approach parameters of coping with stress, occupational performance and satisfaction points (p<0.05). On the other hand, no significant difference were found in the analyzed parameters (p>0.05). conclusion: Time management affects daily life activities, depression, quality of life and coping with stress of mothers of disabled children. Further researches must be planned
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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) | 0.002 | 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".