Recognizing pain as an early warning symptom of ischemic cardiovascular disease: A qualitative artistic representation of the journey
Bibliographic record
Abstract
: Understanding the experience of prodromal ischemic cardiac pain and associated symptoms through use of literary and visual art evokes heightened a wareness of the emotional journey. AIMS: The aim of this study was to describe the initial early prodromal pain-related symptoms and feelings associated with adjusting to this new cardiac health concern and explore the subjective experience of coming to the realization and awareness of developing heart disease. MATERIALS AND METHODS: This study is a secondary supplemental qualitative analysis, using an arts-based embodied layered exploration assisted to translate the experiences of 23 individuals' journeys through symptom recognition. The analytic process involved three iterative layers: qualitative descriptive analysis of participant pain narratives, interpretation with thematic poetry, and representation via visual art to evoke an aesthetic, heightened level of understanding of the data. RESULTS: Denial and disbelief, encroaching pain and symptoms of heart disease, and self-recrimination were three themes that emerged from the data. Pain described by participants brought forward the emotional dimensions of the experience. Participants described their process of realization as a tumultuous time, fraught with feelings of vulnerability and uncertainty, where anger and self-effacing ridicule permeated their thoughts that were tempered with profound gratitude at survival. CONCLUSION: Bridging the connection between science and art to disseminate awareness of the nature of living with cardiac-related prodromal pain and disease is novel. Providing invitation and entrance into an individual's pain experience through qualitative inquiry with use of arts-based approaches makes visible the emotional meaning of pain.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".