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Record W2444066881 · doi:10.1177/1054773816654137

Psychometric Properties of the Treatment Perception and Preferences Measure

2016· article· en· W2444066881 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueClinical Nursing Research · 2016
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsYork UniversityToronto Metropolitan University
FundersCanadian Institutes of Health Research
KeywordsPerceptionPreferenceClinical psychologyPsychologyMeasure (data warehouse)PsychometricsMedicineStatistics

Abstract

fetched live from OpenAlex

Patient-centered care involves the provision of treatments that are responsive to patients' preferences. This study aimed to examine the psychometric properties of the Treatment Perception and Preferences measure. Participants ( n = 128) completed the measure relative to pharmacological, educational, and behavioral treatments for the management of insomnia. For each treatment, the measure presents a description of its goal, activities, mode and dose of delivery, and nine items to rate its perceived acceptability. All items measuring perception of treatment were internally consistent (α > .85) and loaded on one factor, except the item assessing severity of side effects. Differences in the measure's scores between groups of participants provided evidence of validity: participants with a preference for a particular treatment rated it more favorably than alternative treatments. The measure provides a systematic and efficient method for eliciting well-informed treatment preferences. Its use in practice should be investigated.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.786
Threshold uncertainty score0.502

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.327
GPT teacher head0.493
Teacher spread0.166 · 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