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.
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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
