Prevalence and Characteristics of Upper or Mid-Back Pain in Finnish Men
Bibliographic record
Abstract
In Brief Study Design. Descriptive epidemiologic study. Objectives. To examine the 1-year prevalence, severity, and frequency of mid-back pain in a general population sample of men, with comparisons to neck and low back pain. Summary of Background Data. No previous studies reporting the characteristics of mid-back pain in a general population were found. Methods. A total of 600 Finnish men 35 to 70 years of age were drawn from a population-based twin sample and interviewed with standardized pain questions. Results. The 1-year prevalence of mid-back pain was 17.0% (95% confidence interval, 14.3–19.7) compared to 64.0% (95% confidence interval, 60.6–67.5) for neck and 66.8% (95% confidence interval, 63.4–70.3) for low back pain. The frequency of pain over the previous year among those with mid- and low back pain was less than for neck pain. The mean severity of the worst pain episode was highest for low back pain followed by mid-back and neck pain, which were similar. Associated disability tended to be less frequent from mid-back pain (23.5% vs. 30.3%–41.1%). Odds ratios for neck and low back pain when mid-back pain was reported were 2.32 and 2.86, respectively. Conclusion. The prevalence of mid-back pain was approximately one fourth that of neck and low back pain and was somewhat less likely to be disabling. In cases of mid-back pain, spinal comorbidity was nearly always reported. The 1-year prevalence of mid-back pain (17%) was approximately one fourth that of neck and low back pain in Finnish men. The worst episodes of pain were most severe for low back pain and similarly severe for neck and mid-back pain; and mid-back pain was somewhat less likely to be disabling.
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 | 0.001 | 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 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".