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Record W3008872428 · doi:10.1186/s12961-020-0533-z

Is patient-centred care for women a priority for policy-makers? Content analysis of government policies

2020· article· en· W3008872428 on OpenAlexafffundabout
Anna R. Gagliardi, Sheila Dunn, Angel M. Foster, Sherry L. Grace, Nazilla Khanlou, Donna E. Stewart, Sharon E. Straus

Bibliographic record

VenueHealth Research Policy and Systems · 2020
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsSt. Michael's HospitalYork UniversityUniversity of OttawaWomen's College HospitalUniversity of TorontoToronto General HospitalUniversity Health Network
FundersOntario Ministry of Health and Long-Term Care
KeywordsGovernment (linguistics)Health careRehabilitationContent analysisHealth services researchHealth policyMedicineSocial policyHealth administrationPublic healthPublic relationsNursingPolitical scienceSociologyEconomic growthEconomicsPhysical therapy

Abstract

fetched live from OpenAlex

BACKGROUND: Considerable research shows that women experience gendered disparities in healthcare access and quality. Patient-centred care (PCC) could reduce inequities by addressing the patient's clinical and personal needs. Healthcare policies can influence service delivery to optimise patient outcomes. This study assessed whether and how government policies recognise and promote PCC for women (PCCW). METHODS: We analysed the content of English-language policies published in Canada from 2010 to 2018 on depression and cardiac rehabilitation - conditions featuring known gendered inequities - that were identified on government websites. We extracted data and used summary statistics to enumerate mentions of PCC and women's health. RESULTS: We included 30 policies (20 depression, 10 cardiac rehabilitation). Of those, 20 (66.7%) included any content related to PCC (median 1.0, range 0.0 to 5.0), most often exchanging information (14, 46.7%) and making decisions (13, 43.3%). Less frequent domains were enabling self-management (8, 26.7%), addressing emotions (6, 20.0%) and fostering the relationship (4, 13.3%). No policies included content for the domain of managing uncertainty. A higher proportion of cardiac rehabilitation guidelines included PCC content. Among the 30 policies, 7 (23.3%) included content related to at least one women's health domain (median 0.0, range 0.0 to 3.0). Most frequently included were social determinants of health (4, 13.3%). Fewer policies mentioned any issues to consider for women (2, 28.6%), issues specific to subgroups of women (2, 28.6%) or distinguished care for women from men (2, 28.6%). No policies included mention of abuse or violence, or discrimination or stigma. The policies largely pertained to depression. Despite mention of PCC or women's health, policies offered brief, vague guidance on how to achieve PCCW; for example, "Patients value being involved in decision-making" and "Women want care that is collaborative, woman- and family-centered, and culturally sensitive." CONCLUSIONS: Despite considerable evidence of need and international recommendations, most policies failed to recognise gendered disparities or promote PCC as a mitigating strategy. These identified gaps represent opportunities by which government policies could be developed or strengthened to support PCCW. Future research should investigate complementary strategies such as equipping policy-makers with the evidence and tools required to develop PCCW-informed policies.

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: yes · About a Canadian topic: yes
Qualitativehigh
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: yes
Observationalhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.001
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.639
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.723
GPT teacher head0.567
Teacher spread0.156 · 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.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designQualitative · Observational
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

Citations37
Published2020
Admission routes3
Has abstractyes

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