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Record W2806010681

A Method for Evaluation of the Management of Chronic Non-cancer Pain in Global Cities

2016· dissertation· en· W2806010681 on OpenAlexaboutno aff
S. Fatima Lakha

Bibliographic record

VenueTSpace · 2016
Typedissertation
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsChronic painCancerMedicinePhysical therapyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.933
Threshold uncertainty score0.273

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.426
Teacher spread0.406 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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