Background: Research increasingly supports a transdiagnostic conceptualization of emotional disorders (ie applying the same underlying treatment principles across mental disorders, without tailoring the protocol to specific diagnoses), and many international researchers are currently investigating this issue. Objective: The aim of this study was to evaluate the efficacy and acceptability of a Web-based transdiagnostic program using a sample of Romanian adults diagnosed with anxiety and/or depression. Methods: Volunteer participants registered for the study and completed a series of online self-report measures. Participants who fulfilled basic inclusion criteria on these measures were contacted for a telephone diagnostic interview using the Structural Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, 4th Edition Axis I Disorders (SCID-I). Enrolled participants were randomized to either the active treatment group (N=69) or the wait-list control group (N=36) using a 2:1 ratio. The transdiagnostic treatment was based on the Unified Protocol for Transdiagnostic Treatment of Emotional Disorders (UP; Barlow et al, 2011) that addresses common underlying mechanisms of anxiety and depression. Participants randomized to the active treatment condition received 10 weeks of Web-based treatment based on the UP. Throughout treatment, graduate students in clinical psychology provided guidance that consisted of asynchronous written communication on a secure Web platform. After the intervention, participants in both study conditions were invited to complete a set of self-report measures and a postintervention SCID-I interview conducted by a different team of graduate students blinded to participants’ group and diagnostic status. Six months later, participants in the active treatment group were invited to complete an online follow-up assessment. Results: During the intervention, active treatment participants completed on average 19 homework assignments (SD 12.10), and we collected data from 79.0% (83/105) at postintervention and 51% (35/69) at follow-up for self-report measures. Postintervention SCID-I interviews were collected from 77.1% (81/105) participants. Relative to the wait-list control group, the transdiagnostic intervention yielded overall medium to large effect sizes for the primary outcome measures (within-group Hedges g=0.52-1.34 and between-group g=0.39-0.86), and also for anxiety sensitivity (g=0.80), symptom interference (g=0.48), and quality of life (g=0.38). Significant within-groups effects only were reported for the active treatment group on Panic Disorder Severity Scale-Self Report (PDSS-SR, g=0.58-0.65) and Yale-Brown Obsessive Compulsive Scale (Y-BOCS, g=0.52-0.58). Conclusions: Insignificant between-group differences for the Y-BOCS and PDSS-SR could be explained by the small number of participants with the associated primary diagnostic (eg, only 3 participants with obsessive compulsive disorder) by the choice of outcome measure (PDSS-SR was not rated among the evidence-based measures) and by the fact that these disorders may be more difficult to treat. However, the overall results suggest that the transdiagnostic intervention tested in this study represents an effective treatment option that may prove easier to disseminate through the use of Web-based delivery systems. Trial Registration: ClinicalTrials.gov CT02739607; https://clinicaltrials.gov/ct2/show/study/NCT02739607 (Archived by WebCite at http://www.webcitation.org/6yY1VeYIZ)

The COVID-19 pandemic, and the social distancing practices that followed, have been associated with increased prevalence of emotional disorders. However, not all individuals affected by COVID-19-related social distancing experienced elevations in emotional disorder symptoms. Understanding this phenomenon is of crucial public health significance given the burden of emotional disorders on individuals and systems. In this narrative review, we consider the differential impact of COVID-19-related social distancing on mental health outcomes from a transdiagnostic perspective. We argue that individuals high in negative affect and aversive reactivity to emotion, that is, neuroticism, and who respond to such emotional experiences with emotion-motivated avoidant coping, are most likely to experience emotional disorders in the context of COVID-19 social distancing. We acknowledge the pro-social and adaptive function of some types of avoidance during the pandemic, which may have initially buffered against negative mental health outcomes. Implications of this conceptualization for treatment of emotional disorders in the present sociocultural context are discussed.

Background: Digital well-being encourages balanced mobile use. The Perceived Digital Well-Being in Adolescence Scale measures this in adolescents but has been validated only in Slovenia, raising questions about its relevance for other age groups and cultural contexts. Objective: This study had three primary objectives: (1) confirm the 3-factor structure of an English version of the Perceived Digital Well-Being in Adolescence Scale, renamed the Perceived Digital Well-Being Scale (PDWS), in samples of young adults from the United States and the United Kingdom; (2) examine the associations between PDWS dimensions and participants’ sociodemographic characteristics; and (3) explore the relationships between PDWS scores and patterns of smartphone use. Methods: A total of 1854 young adults from the United States and the United Kingdom (ages 18‐25 years; mean 22.4, SD 2.1; 892, 48.1% female, 872, 47.0% male, 90, 4.9% nonbinary) participated in an online survey including the PDWS, digital flourishing, and digital stress measures. Data were analyzed using descriptive statistics, confirmatory factor analysis, correlations, t tests, chi-squared tests, and moderation-mediation analysis. Results: Smartphone screen time and smartphone time for nonessential activities were statistically higher in the US sample than in the UK sample (mean 6.95 vs mean 6.13; t ₁₈₅₂ =4.97; P <.001; d =0.27 and mean 3.62 vs mean 3.29; t ₁₈₅₂ =5.57; P <.001; d =0.25, respectively). The digital well-being total score was statistically higher among US participants when compared with the UK counterparts (mean 3.49 vs mean 3.38; t ₁₈₅₂ =3.33; P <.001; d =0.15). Male participants were significantly more represented among the group with higher PDWB scores ( χ ² ₁₃₆ =478.45; P <.001). Confirmatory factor analysis supported the adequacy of the 3-factor model (emotional, social, and cognitive), indicating strong model fit (critical indices ≥0.90). Evidence of convergent validity was established through significant associations between PDWS scores and measures of digital flourishing and digital stress (most correlation coefficients being significant at P <.001). Measurement invariance testing confirmed the scale’s equivalence across US and UK samples ( χ ² ₂₄₆ change=17.90; P =.21); however, strict invariance across gender (male vs female) was not supported ( χ ² ₂₄₆ change=200.91; P <.001). Gender, sexual orientation, relationship status, ethnicity, socioeconomic status, and education level significantly influenced PDWS scores. Gender and socioeconomic status also moderated the relationship between smartphone use or screen time and PDWS scores ( b =0.048; P =.03 and b =0.020; P =.03, respectively), indicating that these factors affect how smartphone usage relates to psychological distress or well-being in different demographic groups. Conclusions: The PDWS showed good psychometric properties in the US and UK samples. The scale offers a promising tool for identifying individuals at risk of adverse outcomes associated with digital connectivity.