Estudo de atitudes relacionadas ao câncer em pacientes com esquizofrenia
Bibliographic record
Abstract
Patients with schizophrenia have higher morbidity / mortality from physical illness compared to the general population. That result, in many cases, the attitude of patients towards disease prevention. In schizophrenia, several factors such as negative symptoms, cognitive impairment and stigma, can adversely affect the motivation and access to information, among other requirements proper attitude towards disease prevention. Furthermore, no studies in Brazil related to attitude towards cancer and its determinants in people with schizophrenia. The objective was to translate, adapt and validate to the Portuguese of Brazil the Questionnaire of Attitudes in Cancer (QAC) in patients with schizophrenia and evaluate the attitude related to cancer in patients with schizophrenia and controls. The study was developed from a cross-sectional design. The sample consisted of 71 patients with stabilized schizophrenia diagnosis, 32 controls. Participants were evaluated through the Brazilian version of the QAC, the scale of the Positive and Negative Syndrome (PANSS), the Cognitive Assessment Scale (SCoRS) and Calgary scale of depressive symptoms. The results showed that the three dimensions of QAC (cognitive, affective and behavioral) showed good reliability, both with regard to internal consistency ( = 0.70; = 0.77, = 0.81, respectively) as Temporal stability evaluated by the correlation between the test and the retest (r = 0.483, p <0.01, r = 0.798, p <0.01, r = 0.668, p <0.01, respectively). There was a correlation between the cognitive dimension and the behavioral dimension of attitude among patients (r = 0.267; p <0.05). The responses of patients and controls in the behavioral dimension of attitude were different (r = 3.860; p <0.01). Positive symptoms of schizophrenia negatively correlated with the answers of behavioral dimension (r = - 0.272, p <0.05). The participants were able to correctly identify some risk factors for cancer. However, patients had significantly lower performance than the controls on identifying some proven carcinogenic factors. Based on the results presented we can conclude that the process of translation and cultural adaptation of QAC did not affect the essence of the original instrument. The QAC presented satisfactory psychometric properties, reliable and valid in assessing the attitude related to cancer. Symptoms, yet residual, seem to have negative impact on proactive intention to prevent cancer
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".