A Method for Evaluation of the Management of Chronic Non-cancer Pain in Global Cities
Bibliographic record
Abstract
This dissertation explores the outputs of structures and processes influencing clinical services for chronic non-cancer pain (CNCP) management globally. It focuses on facilities and services available in three global cities: Kuwait, Karachi, and Toronto. It develops and demonstrates qualitative and descriptive survey tools capable of assessing CNCP services and management, and associated barriers from the perspective of academic pain specialist involved in the delivery of CNCP services in those cities. Those tools are based on an original conceptual framework for guiding evaluation of CNCP services and management globally. In addition to a general introduction and discussion sections, the dissertation is made up of three sections. The first section integrates and reviews the literature on chronic diseases, CNCP management, and existing health care systems with respect to CNCP services generally and with a focus on the target global cities in particular. The second section consists of an analysis of methodological research options and development of a Structure Process Output evaluation frameworks based on a hybridization of Donabedian and Logistic evaluation frameworks (DL-Hybrid). Mixed methodology survey and interview instruments were designed to evaluate perspectives of pain clinic leader using that DL-Hybrid framework and organized to characterize three output domains: 1) infrastructure utilization, 2) clinical service delivery and 3) education and research activities. The third section reports on semi-structured interviews with academic pain specialists using those instruments. Four participants were recruited from each of the three global cities (8 men and 4 women). Data was analyzed both quantitatively and qualitatively. Krippendorffâ s thematic clustering was used to reveal themes within qualitative data. The three cities showed important differences in how the health system operated but pain specialist shared common training and professional goals and barriers. This qualitative survey provided insights into those goals and barriers. Similarities were observed across the three cities reflecting perhaps the fact that by definition global cities resemble each other economically. The biggest shared obstacle was a lack of resources for coordinating services and evaluating outputs as well as the lack of recognition of the significance of CNCP. The study highlights similarities and variation in perception of barriers. It demonstrates how a global cities lens and a systematic evaluation framework can reveal structural and process issues related to pain clinic outputs aimed at reducing the burden of chronic diseases such as chronic pain both locally and globally.
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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 | 0.041 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".