PROOF Questionnaire

A Prognosis Prediction Model of First Episode Using the Psychosis Risk: Onset and Outcome Factors (PROOF) Questionnaire

Project description

This project aims to explore a new questionnaire designed to estimate prognosis following a first episode of psychosis. The Psychosis Risk: Onset and Outcome Factors (PROOF) Questionnaire is a brief, manualised, semi-structured interview designed to measure the presence of premorbid and postmorbid risk factors for psychosis in order to inform on prognosis. PROOF was developed with the knowledge that there is no such questionnaire currently available.

An initial investigation will examine existing files from approximately 80 patients who are part of the early psychosis service at Monash Health (previously Southern Health) and were administered the PROOF upon referral to the service for good clinical practice. Data will be extracted from these files, in order to perform a descriptive and cluster analysis on the presence/absence of risk factors both within the cohort as a whole and by diagnosis as determined by the consultant psychiatrist to the patients.

A method for scoring the PROOF will be developed concurrently. It may be that each risk factor is assigned a score based on odds ratios/relative risk reported in the literature. Due to the fluid nature of the area, it is likely that scores will be grouped into low, low-medium, medium, high and very high.

Other risk assessment scales have used such broad groupings in addition to imputing intuitive rating through clinical assessment. A consultant statistician will be asked to provide assistance in the development of a scoring system for the PROOF.

This scoring system will be used to give each of the 80 or so patients a total score. Consent will then be sought to follow-up the 80 or so patients to gather information on outcome at 12 months. Statistical analysis will be performed to assess whether scores on the PROOF can predict outcome. In particular, a decision about how much weight should be based in clinical judgment and how this is to be quantified should be implemented in the manual.