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Abstract Research shows that skills for improving Psychological Well‐Being (PWB) may belearnedthrough PWB interventions; however, the dynamic mechanisms underlying this learning process are not well understood. Using an Ecological Momentary Intervention (EMI) design, we conducted an 8‐week Randomized Controlled Trial (N = 160; aged 18–22 years), implemented in a mobile Health (mHealth) platform to characterize these dynamical mechanisms. College‐attending early adults were randomized to three groups: an active control group (N = 55); an intervention group (N = 51) with positive practices intervention; and a second intervention group (N = 54) with positive practices and meditation intervention. The mHealth implementation allowed us to introduce the interventions in participants' daily lives while also assessing their PWB (in terms of positive emotions and relationship quality) several times a day. We used a Bayesian process model to analyze changes in PWB in terms of the underlying dynamical characteristics of change. Findings suggested that the mobile assessment tool itself may have longitudinally improved college‐attending early adults' PWB, as evidenced by instances of directional changes in dynamic characteristics (increased within‐person mean levels, decreased intra‐individual variability, and increased regulation) of PWB measures. Moderation analysis also revealed that people who were low on negative affect improved the most in terms of their mean levels of positive emotions and relationship quality.more » « lessFree, publicly-accessible full text available May 29, 2026
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Benetreau, Yann (Ed.)To advance understanding of doctoral student experiences and the high attrition rates among Science, Technology, Engineering, and Mathematics (STEM) doctoral students, we developed and examined the psychological profiles of different types of doctoral students. We used latent class analysis on self-reported psychological data relevant to psychological threat from 1,081 incoming doctoral students across three universities and found that the best-fitting model delineated four threat classes: Lowest Threat , Nonchalant , Engaged/Worried , and Highest Threat . These classes were associated with characteristics measured at the beginning of students’ first semester of graduate school that may influence attrition risk, including differences in academic preparation (e.g., amount of research experience), self-evaluations and perceived fit (e.g., sense of belonging), attitudes towards graduate school and academia (e.g., strength of motivation), and interpersonal relations (e.g., perceived social support). Lowest Threat students tended to report the most positive characteristics and Highest Threat students the most negative characteristics, whereas the results for Nonchalant and Engaged/Worried students were more mixed. Ultimately, we suggest that Engaged/Worried and Highest Threat students are at relatively high risk of attrition. Moreover, the demographic distributions of profiles differed, with members of groups more likely to face social identity threat (e.g., women) being overrepresented in a higher threat profile (i.e., Engaged/Worried students) and underrepresented in lower threat profiles (i.e., Lowest Threat and Nonchalant students). We conclude that doctoral students meaningfully vary in their psychological threat at the beginning of graduate study and suggest that these differences may portend divergent outcomes.more » « less
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