Designing Positive Psychology Interventions for Social Media: Cross-Sectional Web-Based Experiment With Young Adults With Cancer.

Background: Young adults (ages 18-39 years) with cancer face unique risks for negative psychosocial outcomes. These risks could be lessened with positive psychology interventions adapted for social media if intervention messages encourage intentions to do the activities and positive message reactions and if young adults with cancer perceive few downsides.

Objective: This study aimed to assess whether social media messages from evidence-based positive psychology interventions encouraged intentions to do the intervention activities and intended positive message reactions, overall and among sociodemographic or cancer characteristic subgroups.

Can an Algorithm Tell How Spiritual You Are? Using Generative Pretrained Transformers for Sophisticated Forms of Text Analysis.

Objective: Text analysis is a form of psychological assessment that involves converting qualitative information (text) into quantitative data. We tested whether automated text analysis using Generative Pre-trained Transformers (GPTs) can match the "gold standard" of manual text analysis, even when assessing a highly nuanced construct like spirituality.

Method: In Study 1, N = 2199 US undergraduates wrote about their goals (N = 6597 texts) and completed self-reports of spirituality and theoretically related constructs (religiousness and mental health).

Predicting psychosocial intervention response from baseline gene expression.

To address the challenge of predicting psychological response to a psychosocial intervention we tested the possibility that baseline gene expression profiles might provide information above and beyond baseline psychometric measures. The genomics strategy utilized individual level inferences of transcription factor activity to predict changes in loneliness and affect in response to two well-established meditation interventions. Initial algorithm development analyses focused on three a-priori defined stress-related gene regulation pathways (CREB, GR, and NF-ĸB) as inferred from TELiS promoter-based bioinformatic analysis of basal (pre-intervention) blood samples from a randomized-controlled trial comparing a compassion-based meditation (CM, n = 45) with mindfulness meditation (MM, n = 44).

Positive emotions co-experienced with strangers and acquaintances predict COVID-19 vaccination intentions through prosocial tendencies.

Background: The efficacy of vaccination depends on its widespread adoption, making vaccine uptake not just a personal health behavior but also a prosocial one. Previous research has shown that everyday moments of co-experienced positive emotions (positivity resonance) are associated with higher prosocial tendencies, and these moments, in turn, prospectively predict people's pandemic hygiene behaviors. Yet, limited research has explored how moments of positivity resonance may have predicted greater COVID-19 vaccine intentions during the early months of the pandemic.

Interparental Positivity Spillover Theory: How Parents' Positive Relational Interactions Influence Children.

Interparental interactions have an important influence on child well-being and development. Yet prior theory and research have primarily focused on interparental conflict as contributing to child maladjustment, which leaves out the critical question of how interparental positive interactions-such as expressed gratitude, capitalization, and shared laughter-may benefit child growth and development. In this article, we integrate theory and research in family, relationship, and affective science to propose a new framework for understanding how the heretofore underexamined positive interparental interactions influence children: interparental positivity spillover theory (IPST).