The Effectiveness of Acceptance and Mindfulness-Based Therapy on Physical Activity Increment and Obesity Decrement in the Patients Suffering from Heart Disease in Bandar Abbas
Bibliographic record
Abstract
This research is aimed at determining the role of acceptance and mindfulness therapy on physical activity increment and obesity decrement in in the patients suffering from heart disease in Bandar Abbas. In terms of type, the research is applied one and in terms of research method, it is a quasi-experimental study along with a pretest-posttest with a control group. The statistical population of the research involves all the patients suffering from heart disease being overweight who had visited Bandar Abbas’ hospitals during 2016-2017 and according to angiographic reports, eclipse was more than 50% and BMI >= 30. Available sampling method was used in the study. The population size was 20 that 10 were assigned to experimental group and 10 to control group. The data were collected though making use of physical activity level, body mass index (BMI) questionnaire. The obtained data were analyzed using covariance analysis and SPSS software. The results showed that acceptance therapy had been effective on physical activity increment and body mass decrement of the patients suffering from heart disease. Based on the obtained results, it can be concluded that mindfulness-based therapy can be considered as a non-invasive treatment.
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 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 | 0.001 |
| 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) | 0.001 | 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".