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Record W4306934468 · doi:10.2196/42484

Experiences of Health Care Access Challenges for Back Pain Care Across the Rural-Urban Continuum in Canada: Protocol for Cross-sectional Research

2022· article· en· W4306934468 on OpenAlexafffundvenueabout
Katie Crockett, Stacey Lovo, Alison Irvine, Catherine Trask, Sarah Oosman, Veronica McKinney, Terrence McDonald, Nazmi Sari, Bertha Carnegie, Marie Custer, Stacey McIntosh, Brenna Bath

Bibliographic record

VenueJMIR Research Protocols · 2022
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of CalgaryUniversity of Saskatchewan
FundersCanadian Institutes of Health ResearchGovernment of Canada
KeywordsIndigenousHealth careNursingRural areaPopulationMedicineRural healthEnvironmental healthEconomic growth

Abstract

fetched live from OpenAlex

BACKGROUND: Back pain is common and costly, with negative impacts on both individuals and the health care system. Rural, remote, and Indigenous populations are at greater risk of experiencing back pain compared to urban and non-Indigenous populations. Potential barriers to health care access among Canadians with chronic back pain (CBP) have been identified; however, no study has used lived experiences of people with CBP to drive the selection, analysis, and interpretation of variables most meaningful to patients. OBJECTIVE: The aims of this study are to (1) engage with rural, remote, and urban Indigenous and non-Indigenous patients, health care providers, and health system decision makers to explore lived experiences among people with CBP in Saskatchewan, Canada; (2) cocreate meaningful indicators of CBP care access and effectiveness; and (3) identify program and policy recommendations to overcome access barriers to CBP care. METHODS: In phase 1, one-on-one interviews with 30 people with current or past CBP and 10 health care providers residing or practicing in rural, remote, or urban Saskatchewan communities will be conducted. We will recruit Indigenous (n=10) and non-Indigenous (n=20) rural, remote, and urban people. In phase 2, findings from the interviews will inform development of a population-based telephone survey focused on access to health care barriers and facilitators among rural, remote, and urban people; this survey will be administered to 383 residents with CBP across Saskatchewan. In phase 3, phase 1 and 2 findings will be presented to provincial and national policy makers; health system decision makers; health care providers; rural, remote, and urban people with CBP and their communities; and other knowledge users at an interactive end-of-project knowledge translation event. A World Café method will facilitate interactive dialogue designed to catalyze future patient-oriented research and pathways to improve access to CBP care. Patient engagement will be conducted, wherein people with lived experience of CBP, including Indigenous and non-Indigenous people from rural, remote, and urban communities (ie, patient partners), are equal members of the research team. Patient partners are engaged throughout the research process, providing unique knowledge to ensure more comprehensive collection of data while shaping culturally appropriate messages and methods of sharing findings to knowledge users. RESULTS: Participant recruitment began in January 2021. Phase 1 interviews occurred between January 2021 and September 2022. Phase 2 phone survey was administered in May 2022. Final results are anticipated in late 2022. CONCLUSIONS: This study will privilege patient experiences to better understand current health care use and potential access challenges and facilitators among rural, remote, and urban people with CBP in Saskatchewan. We aim to inform the development of comprehensive measures that will be sensitive to geographical location and relevant to culturally diverse people with CBP, ultimately leading to enhanced access to more patient-centered care for CBP. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/42484.

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 imitation

Not 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.

metaresearch head score (Codex)0.025
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.361
Threshold uncertainty score0.726

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.016
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0040.006
Science and technology studies0.0150.003
Scholarly communication0.0050.002
Open science0.0050.004
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0310.004

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 head0.324
GPT teacher head0.616
Teacher spread0.291 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreProtocol

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

Citations5
Published2022
Admission routes4
Has abstractyes

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