Disease - caused transformations: Phenomenological study of illness experience in people with cardiovascular diseases
Bibliographic record
Abstract
Background: The experience of cardiovascular diseases affects various physical, psychological, social and existential aspects of the patient. But, after studying the research background, it was found that Each of the conducted studies have studied only one of these dimensions. Therefore, the absence of a research that examines all the mentioned components in relation to each other is a sign of the existence of a scientific gap in this field. Aims: The present research was conducted with the aim of studying the "disease experience" in people suffering from cardiovascular diseases. Methods: In this qualitative research, interpretive phenomenological method was used. Sampling was done using the purposeful sampling method and in order to collect data, a semi-structured interview based on the axes proposed by Spradley (2016) was conducted individually with 16 cardiovascular patients. The data were analyzed based on the 6-step strategy of Smith, Larkin and Flowers (2021) and using MAXQDA-2020 software. Results: From the analysis of the findings, the central category of "Disease-caused Transformations" was identified, which includes five main categories of phenomenal body, agency barrier, communication interference, difficult emotional experiences, and existential challenges. Conclusion: According to the obtained results, it can be said that cardiovascular diseases cause profound changes in various aspects of the patients' personal and social life. Using the categories identified in the current research can be a guide for specialists to evaluate that In which of the categories of "pathological changes" does the cardiovascular patient have more serious problems and as a result, it can help specialists in designing and implementing interventions according to the same category.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".