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Record W4409625842 · doi:10.1177/13591053251331279

Experiences of disempowerment amongst endometriosis patients: Toward comprehensive care to address the psychosocial impact of chronic illness

2025· article· en· W4409625842 on OpenAlexafffundabout
Hannah Paige Valihora

Bibliographic record

VenueJournal of Health Psychology · 2025
Typearticle
Languageen
FieldMedicine
TopicEndometriosis Research and Treatment
Canadian institutionsThompson Rivers University
FundersThompson Rivers University
KeywordsEndometriosisPsychosocialReflexivityThematic analysisNarrativeHealth careParticipant observationMedicineQualitative researchDiseasePsychologyPsychiatryFamily medicineGynecologySociologyPolitical science

Abstract

fetched live from OpenAlex

Endometriosis is a devastating chronic condition with significant physical and social implications. This research focused on two questions: 1) how do endometriosis patients experience healthcare in Canada, and 2) how can the healthcare encounter effectively address the psychosocial burden of disease that patients bear? This study examines the psychosocial implications of endometriosis diagnosis and treatment. Data was obtained through semi-structured interviews with nine people diagnosed with endometriosis. Interview questions centering patient perceptions of care were thematically analyzed utilizing reflexive thematic analysis. Analyzing participant narratives and drawing upon Kleinman’s concepts of illness experiences and slow medicine , this article underlines the urgency of moving toward a deeper ethics of care for endometriosis patients, wherein the patient is understood and advocated for within the Canadian healthcare system. Drawing upon participant experiences, the present research calls for the widespread availability of a comprehensive healthcare model for the treatment of endometriosis.

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)0.004
metaresearch head score (Gemma)0.009
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 score0.087
Threshold uncertainty score0.172

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.012
Scholarly communication0.0050.002
Open science0.0010.007
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.458
Teacher spread0.422 · 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 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

Citations0
Published2025
Admission routes3
Has abstractyes

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