Adolescent-Centered Pain Management in School When Adolescents Have Chronic Pain-A Qualitative Study
Bibliographic record
Abstract
Chronic pain is common among Swedish adolescents, and stress is an independent factor in the onset and persistence of chronic pain. When Swedish school nurses conduct their health dialogs they have a unique opportunity to find adolescents with chronic pain. The aim of this study was to explore school nurses’ and adolescents’ experiences of factors that influence adolescent-centered pain management in school health care, when adolescents have chronic pain. The study context is schools in Sweden where primary health care is available through school nurses. A total of 15 school nurses and 15 adolescents participated in individual interviews, which were transcribed and analyzed by qualitative conventional content analysis. Bronfenbrenner’s bioecological model was used to explain how these factors are directed at the individual or society. The results demonstrated eight different categories of factors that influenced the pain management. The categories focused mainly on the adolescents’ micro- and mesosystems; few strategies were conducted on an exo- and macrosystem level. On the micro- and mesosystem levels, it was necessary to build trust to be able to influence the adolescents’ behavior in the pain management. Pharmacological strategies were paracetamol and non-steroidal anti-inflammatory drugs; non-pharmacological strategies were physical activities and stress-reducing activities. Research and practice involving a more holistic perspective, studying the possibilities of both change at the organizational level and individual support for adolescents, are essential.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".