Assessing and Reporting the Adverse Effects of Antipsychotic Medication: A Systematic Review of Clinical Studies, and Prospective, Retrospective, and Cross-Sectional Research

Objective: Adverse effects (AEs) of antipsychotic medication have important implications for patients and prescribers in terms of wellbeing, treatment adherence and quality of life. This review summarises strategies for collecting and reporting AE data across a representative literature sample to ascertain their rigour and comprehensiveness. Methods: A PsycINFO search, following PRISMA Statement guidelines, was conducted in English-language journals (1980–July 2014) using the following search string: (antipsychotic* OR neuroleptic*) AND (subjective effect OR subjective experience OR subjective response OR subjective mental alterations OR subjective tolerability OR subjective wellbeing OR patient perspective OR self-rated effects OR adverse effects OR side-effects). Of 7,825 articles, 384 were retained that reported quantified results for AEs of typical or atypical antipsychotics amongst transdiagnostic adult, adolescent, and child populations. Information extracted included: types of AEs reported; how AEs were assessed; assessment duration; assessment of the global impact of antipsychotic consumption on wellbeing; and conflict of interest due to industry sponsorship. Results: Neurological, metabolic, and sedation-related cognitive effects were reported most systematically relative to affective, anticholinergic, autonomic, cutaneous, hormonal, miscellaneous, and non-sedative cognitive effects. The impact of AEs on patient wellbeing was poorly assessed. Cross-sectional and prospective research designs yielded more comprehensive data about AE severity and prevalence than clinical or observational retrospective studies. 3 Conclusions: AE detection and classification can be improved through the use of standardised assessment instruments and consideration of subjective patient impact. Observational research can supplement information from clinical trials to improve the ecological validity of AE data.

Investigating the effects of caffeine on executive functions using traditional Stroop and a new ecologically-valid virtual reality task, the Jansari assessment of Executive Functions (JEF©)

Objective: Caffeine has been shown to have effects on certain areas of cognition, but in executive functioning the research is limited and also inconsistent. One reason could be the need for a more sensitive measure to detect the effects of caffeine on executive function. This study used a new non-immersive virtual reality assessment of executive functions known as JEF© (the Jansari Assessment of Executive Function) alongside the ‘classic’ Stroop Colour- Word task to assess the effects of a normal dose of caffeinated coffee on executive function. Method: Using a double-blind, counterbalanced within participants procedure 43 participants were administered either a caffeinated or decaffeinated coffee and completed the ‘JEF©’ and Stroop tasks, as well as a subjective mood scale and blood pressure pre- and post condition on two separate occasions a week apart. JEF© yields measures for eight separate aspects of executive functions, in addition to a total average score. Results: Findings indicate that performance was significantly improved on the planning, creative thinking, event-, time- and action-based prospective memory, as well as total JEF© score following caffeinated coffee relative to the decaffeinated coffee. The caffeinated beverage significantly decreased reaction times on the Stroop task, but there was no effect on Stroop interference. Conclusion: The results provide further support for the effects of a caffeinated beverage on cognitive functioning. In particular, it has demonstrated the ability of JEF© to detect the effects of caffeine across a number of executive functioning constructs, which weren’t shown in the Stroop task, suggesting executive functioning improvements as a result of a ‘typical’ dose of caffeine may only be detected by the use of more real-world, ecologically valid tasks.