ABSTRACT
OBJECTIVE: Patients with schizophrenia often become non-adherent following negative treatment experiences as antipsychotics'side-effects. The objective of this study was to propose an alternative measure of patients'perception of atypical antipsychotics'side-effects on weight, as weight is a major concern reported by patients. METHOD: We used a computer-assisted method called Alceste, which is a pragmatic analysis of speech. We selected three groups of ten patients respectively treated by three different atypical antipsychotics: aripiprazole, olanzapine and risperidone. Participants were administered an interview. All speeches were retranscribed and structured in a set of texts, called a corpus. Regarding antipsychotic treatment, we constituted three corpuses of ten speeches. We analyzed separately the three corpuses with the software Alceste. RESULTS: Our findings revealed the presence of a specific class dealing with treatment and illness in the speech of patients, regardless of their treatment. We found weight-related words in all three-treatment groups. The examination of the context of use showed this notion was differently employed in each treatment group: if weight was statistically associated with the notion of loss in the aripiprazole group, the reverse was found (notion of gain) in the two other treatment groups. CONCLUSION: Our findings are valuable because they contribute to validate this speech analysis method. Actually our results, which are mathematically obtained through speech analysis, are convergent with those objectively observed by clinicians. Thus we hypothesize the Alceste-software is a relevant tool to evaluate the perceptions of antipsychotic side-effects.
