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Record W2799754644 · doi:10.35680/2372-0247.1244

What are the most important dimensions of quality for addiction and mental health services from the perspective of its users?

2018· article· en· W2799754644 on OpenAlexafffund
Priscilla Liu, Shawn R. Currie, Jassandre Adamyk-Simpson

Bibliographic record

VenuePatient Experience Journal · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsAlberta Health Services
FundersCanadian Health Services Research FoundationCanadian Foundation for Healthcare Improvement
KeywordsFocus groupMental healthThematic analysisPatient experienceAddictionService (business)PsychologyPerspective (graphical)MedicineQuality (philosophy)NursingHealth careQualitative researchPsychiatryBusiness

Abstract

fetched live from OpenAlex

There is a need to better engage service users in improving their experience with the care received in Addiction and Mental Health (A&MH). Dimensions of patient experience that are most salient to A&MH service users still remain to be properly defined from the patient perspective. This research focuses on identifying key domains of service experience important to patients of Addiction and Mental Health using patient focus groups. In addition, through a patient and family advisory committee, patients were also engaged as co-partners of the research team. The patient advisors had a major role in overseeing the research project, assisting with the thematic analysis and identifying the service domains. A total of 48 individuals (60% female; mean age = 45 years) with lived experience using A&MH services participated in the focus groups. The major themes that emerged from the focus groups led to the identification of seven dimensions of service quality: 1) access, 2) humanity of care, 3) skill and quality of staff, 4) patient engagement, 5) internal and external program communication, 6) individualized treatment and 7) continuity of care. We found that these domains were similar across all service settings including addictions. Patient advisors provided a unique “insider” perspective on the data. Identifying common aspects of service is the first phase of this study. These findings will form the framework for the development of a patient experience survey for Addiction and Mental Health.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.143
Threshold uncertainty score0.511

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.203
GPT teacher head0.433
Teacher spread0.230 · 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 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

Citations12
Published2018
Admission routes2
Has abstractyes

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