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.

Predicting bee community responses to land-use changes: Effects of geographic and taxonomic biases

Land-use change and intensification threaten bee populations worldwide, imperilling pollination services. Global models are needed to better characterise, project, and mitigate bees' responses to these human impacts. The available data are, however, geographically and taxonomically unrepresentative; most data are from North America and Western Europe, overrepresenting bumblebees and raising concerns that model results may not be generalizable to other regions and taxa. To assess whether the geographic and taxonomic biases of data could undermine effectiveness of models for conservation policy, we have collated from the published literature a global dataset of bee diversity at sites facing land-use change and intensification, and assess whether bee responses to these pressures vary across 11 regions (Western, Northern, Eastern and Southern Europe; North, Central and South America; Australia and New Zealand; South East Asia; Middle and Southern Africa) and between bumblebees and other bees. Our analyses highlight strong regionally-based responses of total abundance, species richness and Simpson's diversity to land use, caused by variation in the sensitivity of species and potentially in the nature of threats. These results suggest that global extrapolation of models based on geographically and taxonomically restricted data may underestimate the true uncertainty, increasing the risk of ecological surprises.