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Record W4360620561 · doi:10.1136/bmjopen-2022-066674

‘It’s so simple’ Lessons from the margins: a qualitative study of patient experiences of a mobile health clinic in Hamilton, Ontario, Canada

2023· article· en· W4360620561 on OpenAlexaffabout
Lisa Nussey, Larkin Lamarche, Tim O’Shea

Bibliographic record

VenueBMJ Open · 2023
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsYork UniversityMcMaster University
Fundersnot available
KeywordsMedicineQualitative researchPublic healthSimple (philosophy)Family medicineHealth services researchEpidemiologyGerontologyNursingPathologySocial science

Abstract

fetched live from OpenAlex

OBJECTIVE: Our study explored the experiences of clients of HAMSMaRT (Hamilton Social Medicine Response Team), a mobile health service, in the context of their experiences of the overall healthcare system. DESIGN: We conducted a qualitative study with reflexive thematic analysis. SETTING: HAMSMaRT is a mobile health service in Hamilton, Ontario Canada providing primary care, internal and addiction medicine and infectious diseases services. PARTICIPANTS: Eligible participants were clients of HAMSMaRT who could understand English to do the interview and at least 16 years of age. Fourteen clients of HAMSMaRT were interviewed. RESULTS: Our findings represented five themes. When the themes of people deserve care, from the margins to the centre, and improved and different access to the system are enacted, the model of care works, represented by the theme it works!. The way in which participants compared their experiences of HAMSMaRT to the mainstream healthcare system insinuated how simple it is, represented by the theme it's so simple. CONCLUSIONS: Our findings offer guidance to the broader healthcare system for walking from the rhetoric to practice of person-centred care.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: yes
Qualitativelow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: yes
Qualitativehigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.007
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.270
Threshold uncertainty score0.543

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0210.019
Scholarly communication0.0060.003
Open science0.0030.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.198
GPT teacher head0.539
Teacher spread0.341 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations4
Published2023
Admission routes2
Has abstractyes

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