The Effectiveness of Acceptance and Commitment Therapy (ACT) on Self-Efficacy, Perceived Stress and Resiliency in Type II Diabetes Patients
Bibliographic record
Abstract
INTRODUCTION: The prevalence of diabetes, especially type II diabetes, is increasing in the world. It seems that psycho-cognitive factors such as perceived-stress and resiliency can play an important role in diabetes care. The aim of the present study is examining the effect of Acceptance and Commitment Therapy (ACT) on self-efficacy, perceived stress and resiliency in type II diabetes patients. METHODS: The method of this research was quasi-experimental (pre- test, post -test) with follow-up stages. The population includes women with type II diabetes that refer to Endocrine and Metabolism Research center, Isfahan university of Medical Sciences in 2014. Thirty two patients were selected by convenience sampling and they were randomly divided into two groups, namely experimental and control group (n1 =16, n2 = 16) and the follow-up stage was performed 3 months after the post test. Research tools consisted of questionnaires of self-efficacy (Sherer et al., 1982), perceived-stress (Cohen, Kamarck, & Mermelstein, 1983) and resiliency (Connor & Davidson, 2003). Term of ACT treatment was 8 sessions with one session every week in the experimental group and follow-up stage was performed three months after the post test. RESULTS: Results showed that after the treatment, the scores of self-efficacy and perceived-stress was reduced significantly compared to the control group (p<0.05) in all stages, but in resiliency they did not show any significant differences with each other in post test stage. However, in follow-up stage, the scores were reduced significantly compared to the scores in the control group (p<0.05). CONCLUSION: The results show that ACT can be useful for psycho-cognitive function in type II diabetes patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".