Subjective pain experience of people with chronic back pain
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Studies into the effect of pain experience on those who have it have largely focused on the views and interpretations of researchers gained by the use of assessment tools aimed at measuring pain. The purpose of this study was to explore and describe pain, as experienced by those with chronic back pain, and to document 'insider' accounts of how pain is perceived and understood by those who have it. METHOD: Unstructured interviews using the framework approach. Subjects were sampled for age, sex, ethnicity and occupation, from new referrals with back pain to a rheumatology outpatient clinic. Eleven subjects (5 M; 6 F) agreed to be interviewed. Interviews were unstructured, but followed a topic guide. Subjects were interviewed in English (nine) or their preferred language (two). Tape-recordings of interviews were transcribed verbatim and read in depth twice to identify the topics or concepts. Data were extracted in the form of words and phrases by use of thematic content analysis. The themes were pain description and amount of pain. An independent researcher reviewed the data and confirmed or contended the analysis. RESULTS: All subjects, except one, provided descriptors of the quality of their pain. The use of simile was common to emphasize both what the pain was, and what it was not. Five subjects expressed a loss of words in trying to describe their pain. Only 13 of 29 different pain descriptors used were commensurate with those in the McGill Pain Questionnaire (Melzack, 1983). Subjects had great difficulty quantifying their pain intensity. Several explained how the pain fluctuated, thus, quantifying pain at one point in time was problematic. Only one subject offered a numerical description of pain intensity. CONCLUSIONS: Subjects provided graphic and in-depth descriptions of their pain experience, but these bore little resemblance to commonly used assessment tools. The findings challenge the appropriateness of such formal instruments.
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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 | 0.002 | 0.000 |
| 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) | 0.011 | 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".