The Effect of Acceptance and Commitment Therapy on Experiential Avoidance, Alexithymia and Emotion Regulation in Patients with Type One Diabetes, (Case Study)
Bibliographic record
Abstract
The aim of this study was to investigate the effect of acceptance and commitment therapy on experiential avoidance, alexithymia and emotion regulation in patients with type 1 diabetes. The statistical population was patients with type 1 diabetes that referred to Shariati hospitals from February to June 2022. Six participants were selected voluntarily according to research entry criteria. Data were collected using the Gomez Avoidance Questionnaire (1998), Toronto Alexithymia Scale, Garnowski Emotion Regulation, and Glucometer. Participants underwent eight one-hour protocol sessions after baseline, and the first follow-up was performed one month after the end of treatment and the second follow-up three months later. Data were analyzed using recovery formula, effect size, stability chamber and visual analysis. The results showed that the treatment was effective in reducing the level of avoidance, alexithymia and emotion regulation. Follow-up study showed that this treatment was also effective in lowering blood sugar. According to the findings, acceptance and commitment therapy provides the necessary conditions for adaptation and acceptance and increases the rate of self-care behaviors in individuals. This treatment regulates emotions, reduces alexithymia as well as experiential avoidance, and can be used as an effective intervention method.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 teacher head, 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".