In Brazil there is high number of children with Intellectual Disability (ID) who begin basic education but did not receive a diagnosis. The basic education teachers can be important agents in identifying signs of ID in the student so that they can be referred to health services.

To develop and implement a decision-making model for basic education teachers to identify students with predictive signs of ID.

The sample was composed by 51 teachers from 20 public schools and their 1758 students eligible for the study enrolled in a educational network in São Paulo state, Brazil. A standardized model was developed for the evaluation process using an open-source software named BONITA. For the screening of students with ID signs the teachers answered a checklist based on the diagnostic criteria of the DSM-5 and the students were evaluated with neuropsychological test WASI (Wechsler Abbreviated Scale of Intelligence) and neuropsychiatric assessment. A Classification Based on Association Rules (CBA) generated the predictive models of sensitivity for confirming ID from the items in the checklists.

35 children had suspected ID. The CBA showed an accuracy of 82%, identifying only 1 false-negative case and 3 false-positive cases for ID. According to the teachers, the most accurate signs were deficits in abstract thinking skills, deficits in communication and conversation and difficulties in emotional regulation in social interactions.

The decision-making model by elementary school teachers to identify students with ID showed high levels of sensitivity and can help the waiting for diagnosis.

No significant relationships.

Understanding patients' decisional control preferences (DCPs) is important to improving the quality of care and the satisfaction of patients who have advanced cancer with their care. In addition to passive decisional control (i.e., the patient prefers his/her doctor or family caregiver to make a decision on their behalf) and active decisional control (i.e., the patient decides alone), shared decisional control, where patients and caregivers decide together, could be more appropriate. The primary aim of our study was to describe the decision-making process and the DCPs of patients with advanced cancer receiving palliative care in France.

We conducted a prospective survey with advanced cancer patients referred to a palliative care team in an outpatient setting. We collected information about patients' demographic and clinical characteristics using the Decision Control Preference Scale, the Satisfaction with the Decisions and Care questionnaire, and the Understanding of Illness questionnaire.

A total of 200 patients were evaluable. The median age was 63.5 years and 53.5% female. The cancers most commonly represented were gastrointestinal and breast. A total of 72 patients (36.2%) preferred active decisional control, 52 (26.1%) preferred shared decisional control, and 75 (37.7%) preferred passive decisional control. Younger age (p = 0.003), higher education (p < 0.001), and employment status (p = 0.046) were found to be associated with active or shared DCPs. Some 82% of patients were satisfied with the decision-making process, 35% of whom expressed wishes that did not match the actual decision-making process. Only 23% of patients thought they could be cured of their illness, and 47% thought that their treatment would “get rid of ” their disease.

The decision-making processes are shared in the three models of DCPs in our cohort of French patients with advanced cancer. Further prospective studies are needed.