The COVID-19 pandemic has been an historic challenge to public health and behavior change programs. In low -and middle-income countries (LMICs) such as Nigeria, there have been challenges in promoting vaccination. Vaccine hesitancy and social norms related to vaccination may be important factors in promoting or inhibiting not only COVID vaccination, but other routine vaccinations as well. The aim of this study was to conduct a national-level quasi-experimental evaluation of a social media based COVID-19 vaccination promotion campaign in Nigeria run in 2022. We followed a longitudinal cohort of Nigerians (at baseline) drawn from all 37 states in Nigeria over a 10-month period. This was done at 3 time points to evaluate psychosocial predictors of vaccination and vaccination outcomes following a theory of change based on Diffusion of Innovations, Social Norms Theory, and the Motivation, Opportunity, Ability (MOA) Framework. In a quasi-experimental design, participants in 6 Nigerian states where the social media campaign was run (treatment) were compared to participants from non-treatment states. This study highlights new social media-based data collection techniques. The study found that vaccination rates increased in treatment states compared to non-treatment states, and that these effects were strongest between baseline and first follow up (December 2021 to March 2022). We also found that more pro-vaccination social norms at one time point are associated with higher vaccination rates at a later time point. Social media campaigns are a promising approach to increasing vaccination at scale in LMICs, and social norms are an important factor in promoting vaccination, which is consistent with the Social Norms Theory. We describe implications for future vaccination campaigns and identify future research priorities in this area.

How does the internet affect young people's mental health? We study this question using administrative data on the universe of cases of mental disorders diagnosed in Italian hospitals between 2001 and 2013, which we combine with broadband internet availability at the municipal level. Broadband internet access raises the prevalence of mental disorders among younger cohorts (born between 1985 and 1995) by 0.08 standard deviation units, but it does not impact older individuals (1974 and 1984). The adverse effects are driven by individuals who were exposed early in their lives (before the age of 20). These effects persist when examining instances of self-harm and urgent or compulsory hospitalizations, indicating that the negative outcomes are not merely a result of increased awareness and detection of these conditions. The detrimental impacts span across different pathologies, including depression, anxiety, drug abuse, and personality disorders for both genders, in addition to eating disorders for females.

The coronavirus disease 2019 (COVID-19) pandemic has been the greatest public health challenge of the 21st century. By the end of 2023, there had been approximately 772 000 000 confirmed cases and 7 000 000 deaths worldwide, according to the World Health Organization (WHO) [1]. The rapid development and deployment of vaccines in late 2020 and throughout the following […]

This paper empirically examines how cheaper access to review platforms affects consumer behavior and firms’ incentives to improve product quality in markets where information is traditionally limited.

Scientists and practitioners are aggressively moving to deploy digital twins—large language model (LLM)-based models of individuals—across social science and policy research. We conducted 19 preregistered studies with 164 diverse outcomes (e.g., attitudes toward hiring algorithms and intention to share misinformation) and compared human responses with those of their digital twins (trained on each person’s previous answers to more than 500 questions). We establish an empirical benchmark for digital twin performance: Digital twins’ answers are only modestly more accurate than those from the (homogeneous) base LLM and correlate weakly with human responses (average correlation coefficient of 0.20). To guide future development, we document five ways in which digital twins distort human behavior: (i) insufficient individuation, (ii) stereotyping, (iii) representation bias, (iv) ideological biases, and (v) hyper-rationality. We make our full dataset and code public as a standardized testbed. Our results caution against premature deployment while laying the groundwork for the transparent, replicable, and iterative science necessary for responsible deployment of digital twins.