Satisfaction with medication in coronary disease treatment: psychometrics of the Treatment Satisfaction Questionnaire for Medication
Bibliographic record
Abstract
OBJECTIVE: to psychometrically test the Brazilian version of the Treatment Satisfaction Questionnaire for Medication - TSQM (version 1.4), regarding ceiling and floor effect, practicability, acceptability, reliability and validity. METHODS: participants with coronary heart disease (n=190) were recruited from an outpatient cardiology clinic at a university hospital in Southeastern Brazil and interviewed to evaluate their satisfaction with medication using the TSQM (version 1.4) and adherence using the Morisky Self-Reported Measure of Medication Adherence Scale and proportion of adherence. The Ceiling and Floor effect were analyzed considering the 15% worst and best possible TSQM scores; Practicability was assessed by time spent during TSQM interviews; Acceptability by proportion of unanswered items and participants who answered all items; Reliability through the Cronbach's alpha coefficient and Validity through the convergent construct validity between the TSQM and the adherence measures. RESULTS: TSQM was easily applied. Ceiling effect was found in the side effects domain and floor effect in the side effects and global satisfaction domains. Evidence of reliability was close to satisfied in all domains. The convergent construct validity was partially supported. CONCLUSIONS: the Brazilian TSQM presents evidence of acceptability and practicability, although its validity was weakly supported and adequate internal consistency was observed for one domain.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".