A Neuro-Influence Experiment to Evaluate the Persuasiveness of Pre-Exposure Prophylaxis Promotion Messages Among Men Who Have Sex With Men: Protocol for a Randomized Controlled Trial.

BACKGROUND: Pre-exposure prophylaxis (PrEP) is recommended by the US Centers for Disease Control and Prevention, but behavioral factors limit uptake, especially among men who have sex with men. A better understanding of how humans cognitively process information may inform health message development to promote PrEP uptake. OBJECTIVE: This paper is informed by the neuroscience of persuasion and influence and describes the protocol of a neuro-influence experiment using functional near-infrared spectroscopy (fNIRS) to evaluate the persuasiveness of PrEP promotion messages among men who have sex with men in Baltimore, Maryland. METHODS: We will conduct a randomized controlled trial using fNIRS to measure brain activation among 60 participants viewing PrEP promotion messages either developed through a crowdsourcing open contest implemented by the study team or developed with a traditional social marketing approach. We will evaluate the effectiveness of PrEP promotion messages by assessing brain activation in the regions associated with persuasion and changes in PrEP willingness, behavioral intention, initiation, and action between the 2 groups. RESULTS: This study is funded by the National Institutes of Health (National Institute of Mental Health: R34MH116725). Participant recruitment and data collection were completed in October 2023. The first results are expected to be submitted for publication in 2024. CONCLUSIONS: In addition to providing insight into the effectiveness of PrEP promotion messages, this study will examine the feasibility, acceptability, and utility of neuroimaging techniques to evaluate PrEP promotion messages for high-risk men who have sex with men. The findings can also demonstrate the utility of fNIRS as a tool for preproduct testing of health campaigns and enable the public health community to deliver more effective messages to improve health outcomes. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/52546.

An experiment on the impact of predictive analytics on kidney offers acceptance decisions.

Because of the breadth of factors that might affect kidney transplant decisions to accept an organ or wait for another, presumably "better" offer, a high degree of heterogeneity in decision making exists among transplant surgeons and hospitals. These decisions do not typically include objective predictions regarding the future availability of equivalent or better-quality organs or the likelihood of patient death while waiting for another organ. To investigate the impact of displaying such predictions on organ donation decision making, we conducted a statistically designed experiment involving 53 kidney transplant professionals, in which kidney offers were presented via an online application and systematically altered to observe the effects on decision making. We found that providing predictive analytics for time-to-better offers and patient mortality improved decision consensus and decision-maker confidence in their decisions. Providing a visual display of the patient's mortality slope under accept/reject conditions shortened the time-to-decide but did not have an impact on the decision itself. Presenting the risk of death in a loss frame as opposed to a gain frame improved decision consensus and decision confidence. Patient-specific predictions surrounding future organ offers and mortality may improve decision quality, confidence, and expediency while improving organ utilization and patient outcomes.

Neural reference groups: a synchrony-based classification approach for predicting attitudes using fNIRS.

Social neuroscience research has demonstrated that those who are like-minded are also 'like-brained.' Studies have shown that people who share similar viewpoints have greater neural synchrony with one another, and less synchrony with people who 'see things differently.' Although these effects have been demonstrated at the 'group level,' little work has been done to predict the viewpoints of specific 'individuals' using neural synchrony measures. Furthermore, the studies that have made predictions using synchrony-based classification at the individual level used expensive and immobile neuroimaging equipment (e.g. functional magnetic resonance imaging) in highly controlled laboratory settings, which may not generalize to real-world contexts. Thus, this study uses a simple synchrony-based classification method, which we refer to as the 'neural reference groups' approach, to predict individuals' dispositional attitudes from data collected in a mobile 'pop-up neuroscience' lab. Using functional near-infrared spectroscopy data, we predicted individuals' partisan stances on a sociopolitical issue by comparing their neural timecourses to data from two partisan neural reference groups. We found that partisan stance could be identified at above-chance levels using data from dorsomedial prefrontal cortex. These results indicate that the neural reference groups approach can be used to investigate naturally occurring, dispositional differences anywhere in the world.

Inferring True COVID19 Infection Rates From Deaths.

The novel coronavirus, SARS-CoV-2, commonly known as COVID19 has become a global pandemic in early 2020. The world has mounted a global social distancing intervention on a scale thought unimaginable prior to this outbreak; however, the economic impact and sustainability limits of this policy create significant challenges for government leaders around the world. Understanding the future spread and growth of COVID19 is further complicated by data quality issues due to high numbers of asymptomatic patients who may transmit the disease yet show no symptoms; lack of testing resources; failure of recovered patients to be counted; delays in reporting hospitalizations and deaths; and the co-morbidity of other life-threatening illnesses. We propose a Monte Carlo method for inferring true case counts from observed deaths using clinical estimates of Infection Fatality Ratios and Time to Death. Findings indicate that current COVID19 confirmed positive counts represent a small fraction of actual cases, and that even relatively effective surveillance regimes fail to identify all infectious individuals. We further demonstrate that the miscount also distorts officials' ability to discern the peak of an epidemic, confounding efforts to assess the efficacy of various interventions.

Making social neuroscience less WEIRD: Using fNIRS to measure neural signatures of persuasive influence in a Middle East participant sample.

The large majority of social neuroscience research uses WEIRD populations-participants from Western, educated, industrialized, rich, and democratic locations. This makes it difficult to claim whether neuropsychological functions are universal or culture specific. In this study, we demonstrate one approach to addressing the imbalance by using portable neuroscience equipment in a study of persuasion conducted in Jordan with an Arabic-speaking sample. Participants were shown persuasive videos on various health and safety topics while their brain activity was measured using functional near infrared spectroscopy (fNIRS). Self-reported persuasiveness ratings for each video were then recorded. Consistent with previous research conducted with American subjects, this work found that activity in the dorsomedial and ventromedial prefrontal cortex predicted how persuasive participants found the videos and how much they intended to engage in the messages' endorsed behaviors. Further, activity in the left ventrolateral prefrontal cortex was associated with persuasiveness ratings, but only in participants for whom the message was personally relevant. Implications for these results on the understanding of the brain basis of persuasion and on future directions for neuroimaging in diverse populations are discussed. (PsycINFO Database Record (c) 2019 APA, all rights reserved).