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Record W2144686207 · doi:10.1177/070674370404900210

Patient Factors Associated with Missed Appointments in Persons with Schizophrenia

2004· article· en· W2144686207 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2004
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Operations and Scheduling Optimization
Canadian institutionsResearch ManitobaSt. Boniface HospitalUniversity of ManitobaWinnipeg Regional Health Authority
Fundersnot available
KeywordsSchizoaffective disorderMedicinePsychiatrySchizophrenia (object-oriented programming)PopulationDelusional disorderOutreachSubstance abusePsychosis

Abstract

fetched live from OpenAlex

OBJECTIVE: There is limited research on factors that may predict missed appointments. This study examined correlates to missed appointments in a sample of persons attending an outpatient schizophrenia program. METHOD: We measured the rate of missed appointments for 342 outpatients with severe and persistent mental illness (that is, with diagnoses of schizophrenia, schizoaffective disorder, and delusional disorder) attending a psychiatric outpatient clinic over a period of 2 years and 3 months. We collected and analyzed demographic and clinical variables to ascertain differences between patients with high and low rates of nonattendance. RESULTS: Patients who missed 20% or more of their appointments were significantly younger, were more likely to abuse drugs and alcohol, and manifested lower levels of community functioning. CONCLUSIONS: This profile may be useful in helping clinicians to schedule appointments for this clinical population, to identify those who may need community outreach services, and to improve their treatment prospects.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.832
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.045
GPT teacher head0.318
Teacher spread0.273 · 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