The Social Media Use Scale: Development and Validation.

Social media (SM) use has been primarily operationalized as frequency of use or as passive versus active use. We hypothesize that these constructs have shown mixed associations with psychological constructs because the factor structure underlying social media use (SMU) has not been fully identified. We conducted three studies with college students. In Study 1 (N = 176), we collected data about participants' SMU, informing item generation. In Study 2 (N = 311), we tested two factor structures: (a) passive, active social, and active non-social and (b) a hypothesized four-factor structure. Neither confirmatory model produced acceptable fits, but an exploratory factor analysis suggested a four-factor model: belief-based, consumption-based, image-based, and comparison-based SMU. This four-factor structure was supported in Study 3 (N = 397), which was preregistered, via a confirmatory factor analysis. The subscale items showed good internal consistencies, and evidence is presented for convergent validity. These factors represent a novel classification of people's SMU that can be measured with the Social Media Use Scale.

Social media's influence on momentary emotion based on people's initial mood: an experimental design.

Can you think of a meme that made you laugh or a political post that made you angry? These examples illustrate how social media use (SMU) impacts how people feel. Similarly, how people feel when they initiate SMU may impact the emotional effects of SMU. Someone feeling happy may feel more positively during SMU, whereas someone feeling sad may feel more negatively. Using an experimental design, we examined whether following SMU, those in a happy mood would experience increases in positive affect (PA) and those in a sad mood would experience increases in negative affect (NA). A large sample of college students (N = 703) were randomly assigned to a happy, sad, or neutral mood induction before SMU. PA and NA were assessed at baseline, post-mood induction, and after SMU. Contrary to hypotheses, after SMU, people in happy moods experienced decreases in PA, and those in sad moods experienced decreases in NA, reflecting SMU having a dampening effect on emotions. PA and NA were significantly lower after SMU compared to baseline and did not vary by condition. How young adults feel when they log onto SMU matters in understanding how SMU impacts PA and NA, but on average, emotional experiences are dampened.

Everyday emotion regulation goals, motives, and strategies in current and remitted major depressive disorder: An experience sampling study.

People with major depressive disorder (MDD) report difficulties with emotion regulation (ER), particularly in habitual strategy use. We examined ER strategy use and other aspects of ER-desired emotional states (emotion goals) and reasons for ER (ER motives)-in current and remitted MDD. In a 2-week experience sampling study, adults with current MDD (n = 48), remitted MDD (n = 80), and healthy controls (n = 87) reported their negative affect (NA) and positive affect (PA), emotion goals (frequency, direction), ER motives (hedonic, instrumental), and ER strategy use (social sharing, acceptance, savoring, reappraisal, suppression, distraction). Multilevel modeling and Bayes factors were used to assess differences and similarities across groups. Compared to the remitted MDD and control groups, the current MDD group regulated emotion more frequently in general but showed weakened associations between initiating regulation and momentary affect and reported different emotion goal directions. Although all groups mostly reported emotion goals to regulate prohedonically (decrease NA, increase or maintain PA), the current MDD group was the most likely to try to amplify NA and PA simultaneously. Current MDD and remitted MDD groups endorsed hedonic motives more than controls, but the three groups did not differ in instrumental motives. The only group difference in ER strategy use was that the current MDD group used distraction more than controls. Most group differences in ER were between the current MDD group and controls, with the remitted MDD group and controls being quite similar. ER in current MDD is characterized by frequent regulation, weakened association between initiating regulation and momentary affect, increased hedonic-focused ER motives, and a greater use of distraction. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Can integrating the Memory Support Intervention into cognitive therapy improve depression outcome? A randomized controlled trial.

We investigated if improving a patient's memory for the content of their treatment, via the Memory Support Intervention, improves illness course and functional outcomes. The platform for investigating this question was major depressive disorder (MDD) and cognitive therapy (CT). Adults diagnosed with MDD (N = 178) were randomly allocated to CT + Memory Support (n = 91) or CT-as-usual (n = 87). Both treatments were comprised of 20-26, 50-min sessions over 16 weeks. Blind assessments were conducted before and immediately following treatment (post-treatment) and 6 months later (6FU). Patient memory for treatment, assessed with a free recall task, was higher in CT + Memory Support for past session recall at post-treatment. Both treatment arms were associated with reductions in depressive symptoms and functional impairment except: CT + Memory Support exhibited lower depression severity at 6FU (b = -3.09, p = 0.050, d = -0.27), and greater reduction in unhealthy days from baseline to 6FU (b = -4.21, p = 0.010, d = -1.07), compared to CT-as-usual. While differences in illness course and functional outcomes between the two treatment arms were limited, it is possible that future analyses of the type of memory supports and longer follow-up may yield more encouraging outcomes. TRIAL REGISTRATION: ClinicalTrials.gov NCT01790919. Registered October 6, 2016.

Social Networking Site Use During the COVID-19 Pandemic and Its Associations With Social and Emotional Well-being in College Students: Survey Study.

BACKGROUND: Social distancing during the COVID-19 pandemic has reduced the frequency of in-person social interactions. College students were highly impacted, since many universities transferred curriculum from in-person to entirely online formats, physically separating students with little notice. With social distancing, their use of social networking sites (SNSs) likely changed during the COVID-19 pandemic, possibly holding implications for well-being. OBJECTIVE: This study aimed to determine (1) how components of SNS use (ie, weekly frequency, time per day, habitual use, engagement, enjoyment, addiction, and emotional impact) changed from before to during COVID-19, (2) how these changes in SNS use were associated with pandemic-related social and emotional well-being, and (3) how SNS use and changes in use during the pandemic were associated with loneliness. METHODS: College students (N=176) were surveyed during the time when their university campus in the United States was operating online. Participants completed the same SNS use questionnaires twice, once with regard to the month preceding the onset of COVID-19 and again with regard to the month since this time. They also reported the extent to which they experienced perceived change in social support resulting from the pandemic, pandemic-related stress, and general loneliness. RESULTS: After the onset of COVID-19, participants showed an increase in daily time spent on SNSs (t169=5.53, d=0.42, P<.001), habitual use (t173=3.60, d=0.27, P<.001), and addiction (t173=4.96, d=0.38, P<.001); further, enjoyment on SNSs decreased (t173=-2.10, d=-0.16, P=.04) and the emotional impact of SNS activities became more negative (t172=-3.76, d=-0.29, P<.001). Increased perceived social support during COVID-19 was associated with changes in frequency of SNS use, time per day, addiction, and engagement (r>0.18 for all). Pandemic-related stress was associated with changes in SNS addiction and the extent to which one's SNS content was related to the pandemic (r>0.20 for all). Loneliness was positively associated with SNS addiction (r=0.26) and negatively associated with SNS engagement (r=-0.19) during the pandemic. Loneliness was also negatively associated with changes in habit and engagement (r<-0.15 for all). CONCLUSIONS: Findings suggest that components of SNS use are associated with both positive and negative pandemic-related social outcomes, but largely negative pandemic-related emotional outcomes. Further, some components of SNS use are positively associated with loneliness (eg, addiction) while others show a negative association (eg, engagement). These findings provide a more nuanced picture of how SNS use is associated with social and emotional well-being during the time of a global health crisis when in-person interactions are scarce.

Systematic review to examine the methods used to adapt evidence-based psychological treatments for adults diagnosed with a mental illness.

QUESTION: The context for the implementation of evidence-based psychological treatments (EBPTs) often differs from the context in which the treatment was developed, which necessitates adaptations. In this systematic review we build on, and add to, prior approaches by examining the method used to guide such adaptations. In particular, we sought to elucidate the extent to which an empirical process is used. STUDY SELECTION AND ANALYSIS: We focused on publications describing adaptations made to EBPTs for adults diagnosed with a mental illness. We searched PubMed, PsycINFO, Embase and Web of Science from database inception to July 2018. Two raters independently coded the articles for the method used to conduct the adaptation, the reason for and nature of the adaptation, and who made the adaptation. FINDINGS: The search produced 20 194 citations, which yielded 152 articles after screening. The most commonly used methods for planned adaptations were literature review (57.7%), clinical intuition (47.0%) and theory (38.9%). The use of data from stakeholder interviews ranked fourth (21.5%) and the use of other types of data (eg, pilot study, experiment, survey, interview) ranked last at fifth (12.1%). Few publications reporting ad hoc adaptations were identified (n=3). CONCLUSIONS: This review highlights a need to (a) educate providers and researchers to carefully consider the methods used for the treatment adaptation process, and to use empirical methods where possible and where appropriate, (b) improve the quality of reporting of stakeholder interviews and (c) develop reporting standards that articulate optimal methods for conducting treatment adaptations.