The Data Lab

Abstract We study judicial in-group bias in Indian criminal courts using newly collected data on over 5 million criminal case records from 2010–2018. After classifying gender and religious identity with a neural network, we exploit quasi-random assignment of cases to judges to determine whether judges favor defendants with similar identities to themselves. In the aggregate, we estimate tight zero effects of in-group bias based on shared gender or religion, including in settings where identity may be especially salient, such as when the victim and defendant have discordant identities. Proxying caste similarity with shared last names, we find a degree of in-group bias, but only among people with rare names; its aggregate impact remains small.

BackgroundAntidepressants are commonly prescribed. There are clear national guidelines in relation to treatment sequencing. This study examines trends and variation in antidepressant prescribing across English primary care.AimTo examine trends and variation in antidepressant prescribing in England, with a focus on: monoamine oxidase inhibitors (MAOIs); paroxetine; and dosulepin and trimipramine.Design & settingRetrospective longitudinal study using national and practice-level data on antidepressant items prescribed per year (1998–2018) and per month (2010–2019).MethodClass- and drug-specific proportions were calculated at national and practice levels. Descriptive statistics were generated, percentile charts and maps were plotted, and logistic regression analysis was conducted.ResultsAntidepressant prescriptions more than tripled between 1998 and 2018, from 377 items per 1000 population to 1266 per 1000. MAOI prescribing fell substantially, from 0.7% of all antidepressant items in 1998 to 0.1% in 2018. There was marked variation between practices in past year prescribing of paroxetine (median practice proportion [MPP] = 1.7%, interdecile range [IDR] = 2.6%) and dosulepin (MPP = 0.7%, IDR = 1.8%), but less for trimipramine (MPP = 0%, IDR = 0.2%).ConclusionRapid growth and substantial variation in antidepressant prescribing behaviour was found between practices. The causes could be explored using mixed-methods research. Interventions to reduce prescribing of specific antidepressants, such as dosulepin, could include review prompts, alerts at the time of prescribing, and clinician feedback through tools like OpenPrescribing.net.