Effects of digital chatbot on gender attitudes and exposure to intimate partner violence among young women in South Africa

Background South Africa has among the highest rates of intimate partner violence (IPV) globally, with young women at heightened risk due to inequitable gender roles, limited relationship skills, and inadequate social support. Despite an urgent need for violence prevention in low- and middle-income settings, most efficacious approaches are time-intensive and costly to deliver. Digital, interactive chatbots may help young women navigate safer relationships and develop healthier gender beliefs and skills Methods Young women (18–24 years old) across South Africa were recruited via Facebook for participation in an individually randomised controlled trial (n = 19,643) during the period of June 2021-September 2021. Users were randomly allocated, using a pipeline algorithm, to one of four trial arms: Pure Control (PC) had no user engagement outside of study measures; Attention Treatment (T0) provided didactic information about sexual health through a text-based chatbot; Gamified Treatment (T1) was a behaviourally-informed gamified text-based chatbot; Narrative Treatment (T2) was a behaviourally-informed drama delivered through pre-recorded voice notes. All chatbots were delivered in WhatsApp, through which users were invited to complete brief “quizzes” comprising adapted versions of validated scales. Primary outcomes were short-form adaptations of scales for gender attitudes (Gender Relations Scale) and past-month IPV (WHO Multi-country Study Instrument). Secondary outcomes were identification of unhealthy relationship behaviours (Intimate Partner Violence Attitudes Scale) and brief screener for depressive symptoms (Patient Health Questionnaire). A direct chat link to a trained counsellor was a safety measure (accessed by 4.5% of the sample). We estimated treatment effects using ordinary least squares and heteroskedasticity robust standard errors Findings The trial retained 11,630 (59.2%) to the primary endpoint of gender attitudes. Compared to control, all treatments led to moderate and significant changes in attitudes towards greater gender equity (Cohen’s D = 0.10, 0.29, 0.20 for T0, T1, and T2, respectively). The gamified chatbot (T1) had modest but significant effects on IPV: 56% of young women reported past-month IPV, compared to 62% among those without treatment (marginal effects = -0.07, 95%CI = -0.09to-0.05). The narrative treatment (T2) had no effect on IPV exposure. T1 increased identification of unhealthy relationship behaviours at a moderate and significant level (Cohen’s D = 0.25). Neither T1 nor T2 had a measurable effect on depressive symptoms as measured by the brief screener. Interpretation: A behaviourally-informed, gamified chatbot increased gender equitable attitudes and was protective for IPV exposure among young women in South Africa. These effects, while modest in magnitude, could represent a meaningful impact given potential to scale the low-cost intervention

Effects of digital chatbot on gender attitudes and exposure to intimate partner violence among young women in South Africa.

BackgroundSouth Africa has among the highest rates of intimate partner violence (IPV) globally, with young women at heightened risk due to inequitable gender roles, limited relationship skills, and inadequate social support. Despite an urgent need for violence prevention in low- and middle-income settings, most efficacious approaches are time-intensive and costly to deliver. Digital, interactive chatbots may help young women navigate safer relationships and develop healthier gender beliefs and skills.MethodsYoung women (18-24 years old) across South Africa were recruited via Facebook for participation in an individually randomised controlled trial (n = 19,643) during the period of June 2021-September 2021. Users were randomly allocated, using a pipeline algorithm, to one of four trial arms: Pure Control (PC) had no user engagement outside of study measures; Attention Treatment (T0) provided didactic information about sexual health through a text-based chatbot; Gamified Treatment (T1) was a behaviourally-informed gamified text-based chatbot; Narrative Treatment (T2) was a behaviourally-informed drama delivered through pre-recorded voice notes. All chatbots were delivered in WhatsApp, through which users were invited to complete brief "quizzes" comprising adapted versions of validated scales. Primary outcomes were short-form adaptations of scales for gender attitudes (Gender Relations Scale) and past-month IPV (WHO Multi-country Study Instrument). Secondary outcomes were identification of unhealthy relationship behaviours (Intimate Partner Violence Attitudes Scale) and brief screener for depressive symptoms (Patient Health Questionnaire). A direct chat link to a trained counsellor was a safety measure (accessed by 4.5% of the sample). We estimated treatment effects using ordinary least squares and heteroskedasticity robust standard errors.FindingsThe trial retained 11,630 (59.2%) to the primary endpoint of gender attitudes. Compared to control, all treatments led to moderate and significant changes in attitudes towards greater gender equity (Cohen's D = 0.10, 0.29, 0.20 for T0, T1, and T2, respectively). The gamified chatbot (T1) had modest but significant effects on IPV: 56% of young women reported past-month IPV, compared to 62% among those without treatment (marginal effects = -0.07, 95%CI = -0.09to-0.05). The narrative treatment (T2) had no effect on IPV exposure. T1 increased identification of unhealthy relationship behaviours at a moderate and significant level (Cohen's D = 0.25). Neither T1 nor T2 had a measurable effect on depressive symptoms as measured by the brief screener. Interpretation: A behaviourally-informed, gamified chatbot increased gender equitable attitudes and was protective for IPV exposure among young women in South Africa. These effects, while modest in magnitude, could represent a meaningful impact given potential to scale the low-cost intervention

Whole RNA-Sequencing and Transcriptome Assembly of Candida albicans and Candida africana under Chlamydospore-Inducing Conditions

Candida albicans is the most common cause of life-threatening fungal infections in humans, especially in immunocompromised individuals. Crucial to its success as an opportunistic pathogen is the considerable dynamism of its genome, which readily undergoes genetic changes generating new phenotypes and shaping the evolution of new strains. Candida africana is an intriguing C. albicans biovariant strain that exhibits remarkable genetic and phenotypic differences when compared with standard C. albicans isolates. Candida africana is well-known for its low degree of virulence compared with C. albicans and for its inability to produce chlamydospores that C. albicans, characteristically, produces under certain environmental conditions. Chlamydospores are large, spherical structures, whose biological function is still unknown. For this reason, we have sequenced, assembled, and annotated the whole transcriptomes obtained from an efficient C. albicans chlamydospore-producing clinical strain (GE1), compared with the natural chlamydospore-negative C. africana clinical strain (CBS 11016). The transcriptomes of both C. albicans (GE1) and C. africana (CBS 11016) clinical strains, grown under chlamydospore-inducing conditions, were sequenced and assembled into 7,442 (GE1 strain) and 8,370 (CBS 11016 strain) high quality transcripts, respectively. The release of the first assembly of the C. africana transcriptome will allow future comparative studies to better understand the biology and evolution of this important human fungal pathogen