Corrigendum/Erratum to "Teens, screens and quarantine; The relationship between adolescent media use and mental health prior to and during COVID-19" [Heliyon 8(7), July 2022 e09898].

[This corrects the article DOI: 10.1016/j.heliyon.2022.e09898.].

What is the Optimal Way to Give Thanks? Comparing the Effects of Gratitude Expressed Privately, One-to-One via Text, or Publicly on Social Media.

Numerous investigations to date have established the benefits of expressing gratitude for improved psychological well-being and interpersonal relationships. Nevertheless, the social dynamics of gratitude remain understudied. Do the effects of gratitude differ when it is expressed privately, communicated directly to the benefactor one-to-one, or shared publicly? We tested this question in a preregistered intervention study. An ethnically and economically diverse sample of undergraduate students (N = 916) was randomly assigned to 1 of 4 conditions: (1) write gratitude letters and do not share them (private gratitude), (2) share gratitude one-to-one with benefactors via text (1-to-1 gratitude), (3) share gratitude publicly on social media (public gratitude), or (4) track daily activities (control). Participants were asked to complete their assigned activity four times with different people (as applicable) over the course of about a week. Overall, participants assigned to any digital gratitude intervention experienced improvements in state gratitude, positive emotions, negative emotions, elevation, connectedness, support, and loneliness, relative to controls. Relative to all other conditions, participants assigned to text their benefactors showed the biggest boosts in social connectedness and support. Our findings show that easily scalable digital gratitude interventions can advance the well-being of young college students. Supplementary Information: The online version contains supplementary material available at 10.1007/s42761-022-00150-5.

Linear correlation is insufficient as the sole measure of associations: The case of technology use and mental health.

It is common for psychology studies to rely solely on linear correlation (r) or similar statistics and not include other measures of association (such as relative risk, which examines differences in the number of people affected). For example, the association between smoking and lung cancer (r = 0.06) could be dismissed as "small" if only linear r is examined, even though 30 times more smokers than non-smokers get lung cancer. Many studies concluding that associations between technology use and well-being as too small to be of practical importance relied solely on linear r. We show that, across five datasets, "small" correlations between technology use and mental health exist alongside practically important risk associations. As there are several valid types of association, and characterizing an association based on a single type of a measure - such as linear r or r2 - can be misleading.

Teens, screens and quarantine; the relationship between adolescent media use and mental health prior to and during COVID-19.

This study examines associations between media use and mental health for adolescents prior to and during the COVID-19 pandemic. Using two separate datasets that sampled adolescents (8th, 10th, and 12th graders) in 2018 (n = 31,825) and 2020 (n = 1,523), mental health (hopelessness and happiness), media use (time spent using a variety of media), and personal health habits (sleep) were assessed. Overall, we found that there were significant differences by year in adolescent hopelessness, with adolescents reporting less hopelessness in 2020 (during COVID-19) than in 2018 (pre COVID-19). There were not â€‹practical significant differences in adolescent happiness and loneliness. Adolescents also reported getting more sleep in our 2020 sample than the 2018 sample. Adolescents in 2020 spent significantly more time watching movies and video chatting, but less time texting and on social media than adolescents in 2018. Finally, we found that time spent video chatting and sleep had a different relationship with various aspects of mental health (happiness, hopelessness, or loneliness) in 2018 vs. 2020.

Associations between screen time and internalizing disorder diagnoses among 9- to 10-year-olds.

BACKGROUND: Children and adolescents spend an increasing amount of time with screen media. Identifying correlates of youth mental disorders has become more urgent with rates of depression, self-harm, suicide attempts, and suicide deaths rising sharply among U.S. children and adolescents after 2012. This study examined the relationship between screen time and internalizing disorders in preadolescent children between the ages of 9 and 10. METHODS: Participants were 9- and 10-year-old youth (n = 11,780) in the baseline of the multi-site Adolescent Brain and Cognitive Development Study (ABCD). Youth reported the number of hours a day they spent watching TV shows or movies, watching videos online, playing video games, texting, using social media, and video chatting. Youth responded to an abbreviated version of the Kiddie Schedule for Affective Disorders and Schizophrenia (K-SADS-5), a semi-structured clinical interview measuring current and past symptoms of internalizing disorders using DSM-5 criteria. RESULTS: Youth spending 2 or more hours (vs. less than 2) a day with screen media were more likely to fit criteria for depressive disorders, self-harm, and suicidal ideation or attempts, even after adjustment for demographic covariates. For anxiety disorders, associations with digital media use (social media, texting, gaming, and online videos) were stronger than with screen time generally. LIMITATIONS: This is a cross-sectional study utilizing retrospective screen time reports, which limits our ability to determine causality and the accuracy of the reports. CONCLUSIONS: Preadolescents who spend more time using screens, especially digital media, are more likely to fit DSM-5 criteria for internalizing disorders.

Specification curve analysis shows that social media use is linked to poor mental health, especially among girls.

An important 2019 paper applied a novel analytic technique called Specification Curve Analysis (SCA) to data from three large-scale community samples to investigate the association between adolescent technology use and mental health/well-being. The paper concluded that an association exists but is tiny, with median betas between -0.01 and -0.04. This association was reported to be smaller than links between mental health and various innocuous variables in the datasets such as eating potatoes, and therefore to be of no practical significance. The current paper re-ran SCA on the same datasets while applying alternative analytic constraints on the model specification space, including: 1) examining specific digital media activities (e.g., social media) separately rather than lumping all "screen time" including TV together; 2) examining boys and girls separately, rather than examining them together; 3) excluding potential mediators from the list of controls; and 4) treating scales equally (rather than allowing one scale with many subscales to dominate all others). We were able to reproduce the original results with the original configurations. When we used the revised constraints, we found several much larger relationships than previously reported. In particular: among girls, there is a consistent and substantial association between mental health and social media use (median betas from -0.11 to -0.24). These associations were stronger than links between mental health and binge drinking, sexual assault, obesity, and hard drug use, suggesting that these associations may have substantial practical significance as many countries are experiencing rising rates of depression, anxiety, and suicide among teenagers and young adults.

The expanding class divide in happiness in the United States, 1972-2016.

Is there a growing class divide in happiness? Among U.S. adults ages 30 and over in the nationally representative General Social Survey (N = 44,198), the positive correlation between socioeconomic status (SES; including income, education, and occupational prestige) and happiness grew steadily stronger between the 1970s and 2010s. Associations between income and happiness were linear, with no tapering off at higher levels of income. Between 1972 and 2016, the happiness of high-SES White adults was fairly stable, whereas the happiness of low-SES White adults steadily declined. Among Black adults, the happiness of low-SES adults was fairly stable, whereas the happiness of high-SES adults increased. Thus, the happiness advantage favoring high-SES adults has expanded over the decades. Age-period-cohort analyses based on hierarchical linear modeling demonstrate that this effect is primarily caused by time period rather than by birth cohort or age. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Worldwide increases in adolescent loneliness.

INTRODUCTION: Several studies have documented increases in adolescent loneliness and depression in the U.S., UK, and Canada after 2012, but it is unknown whether these trends appear worldwide or whether they are linked to factors such as economic conditions, technology use, or changes in family size. METHODS: The Programme for International Student Assessment (PISA) survey of 15- and 16-year-old students around the world included a 6-item measure of school loneliness in 2000, 2003, 2012, 2015, and 2018 (n = 1,049,784, 51% female) across 37 countries. RESULTS: School loneliness increased 2012-2018 in 36 out of 37 countries. Worldwide, nearly twice as many adolescents in 2018 (vs. 2012) had elevated levels of school loneliness. Increases in loneliness were larger among girls than among boys and in countries with full measurement invariance. In multi-level modeling analyses, school loneliness was high when smartphone access and internet use were high. In contrast, higher unemployment rates predicted lower school loneliness. Income inequality, GDP, and total fertility rate (family size) were not significantly related to school loneliness when matched by year. School loneliness was positively correlated with negative affect and negatively correlated with positive affect and life satisfaction, suggesting the measure has broad implications for adolescent well-being. CONCLUSIONS: The psychological well-being of adolescents around the world began to decline after 2012, in conjunction with the rise of smartphone access and increased internet use, though causation cannot be proven and more years of data will provide a more complete picture.

Associations Between Adolescent Depression and Self-Harm Behaviors and Screen Media Use in a Nationally Representative Time-Diary Study.

Screen media use is associated with mental health problems among adolescents. However, few studies have examined screen media use using contemporaneous time diaries (rather than retrospective reports), compared associations across specific screen media activities or by gender, or examined associations with self-harm behaviors. Participants were 13- to 15-year-old adolescents completing time diaries (n = 4,252) for one weekday and one weekend day in the 2015 administration of the Millennium Cohort Study, a nationally representative birth cohort study of UK adolescents. Participants also completed a measure of depressive symptoms and reported whether they had engaged in self-harm in the last year. Girls who spent 2 + hrs/day, compared to < 2 h/day, on digital media were more likely to self-harm (for social media use, adjusted relative risk [ARR] for self-harm = 1.46, 95% CI = 1.17, 1.82; for internet use, ARR = 1.80 [1.20, 2.70]). Girls spending more time on digital media were also more likely to be depressed (for social media, ARR = 1.29 [1.03, 1.63]; for internet use, ARR = 1.75 [1.19, 2.59]). Associations with gaming, texting/e-mailing, and TV/video watching among girls were mostly not significant. Associations for boys were mostly not significant. Girls who use digital media (especially social media and the internet) more hrs/day are more likely to have clinically significant levels of depressive symptoms and prior history of self-harm, though gaming, texting/e-mailing, and TV/video watching showed few associations. Screen media use was mostly not significantly associated with self-harm or depression among boys.

Anxiety and depressive symptoms in U.S. Census Bureau assessments of adults: Trends from 2019 to fall 2020 across demographic groups.

BACKGROUND: Events from spring to fall 2020, including the COVID-19 pandemic, hate crimes, and social unrest, may have impacted mental health, particularly mood and anxiety disorders. This study compares rates of positive screens for anxiety and depressive disorders in separate U.S. national samples from 2019 and April to September 2020. The analysis includes trends within demographic groups, which have received scant attention. METHODS: Nationally representative probability samples of U.S. adults administered by the U.S. Census Bureau (n = 1.3 million) completed the PHQ-2 screening for depressive disorder and the GAD-2 screening for anxiety disorder. RESULTS: U.S. adults in 2020 were four times more likely to screen positive for depressive and anxiety disorders than in 2019, with the largest increases among males, 18- to 29-year-olds (for depression), Asian Americans, and parents with children in the home. Anxiety and depression rose and fell in tandem with the number of COVID-19 cases in the U.S., as well as increasing during the early June weeks of racial justice protests. CONCLUSIONS: Screens for mood and anxiety disorders remained at elevated levels in spring, summer, and fall 2020, especially among certain groups.

Sleep characteristics of U.S. adults before and during the COVID-19 pandemic.

RATIONALE: Understanding how health has changed in response to the COVID-19 pandemic is critical to recovering from the pandemic. OBJECTIVE: This study focused on how sleep characteristics in the United States may be different from before to during the COVID-19 pandemic. METHODS: To this end, the sleep characteristics of a nationally representative sample of U.S. adults collected before the COVID-19 outbreak (i.e., 2018 National Health Interview Survey, n = 19,433) were compared to the sleep characteristics of a nationally representative sample of U.S. adults recruited via Luc.id, an online survey sampling company, during the COVID-19 outbreak (i.e., 2020 Luc.id, n = 2059). RESULTS: While average sleep duration did not change between 2018 and 2020, the prevalence of both shorter and longer than recommended sleep duration were greater in 2020. Moreover, the number of days with difficulty falling asleep, difficulty staying asleep, and not feeling rested was greater in 2020 than 2018. Adults younger than 60 had larger differences than those 60 or older. CONCLUSIONS: Sleep health in U.S. adults was worse in 2020 than in 2018, particularly in adults younger than 60. Findings highlight sleep as target in future research and interventions seeking to understand and reduce the effects of the COVID-19 pandemic.

Increased Support for Same-sex Marriage in the US: Disentangling Age, Period, and Cohort Effects.

Previous research established a substantial increase in support for same-sex marriage in the US, but it is unclear if this increase is due to cohort (a change that affects only the younger generation) or time period (a change that affects those of all ages). In a nationally representative sample of American adults (n = 13,483) in 1988 and 2004-2018, increased support for same-sex marriage was primarily due to time period (from 11.1% in 1988 to 66.7% in 2018). There was a smaller cohort effect, with a fairly linear increase between cohorts born in the 1960s and those born in the 1990s. Time period increases in support for same-sex marriage appeared among across gender, race, education levels, regions, and levels of religious service attendance, though differences in support still remain. The results suggest Americans of all ages modified their beliefs about same-sex marriage over time.

Not all screen time is created equal: associations with mental health vary by activity and gender.

PURPOSE: Previous research on associations between screen media use and mental health produced mixed findings, possibly because studies have not examined screen activities separately or accounted for gender differences. We sought to examine associations between different types of screen activities (social media, internet, gaming, and TV) and mental health indicators separately for boys and girls. METHODS: We drew from a nationally representative sample of 13-15-year-old adolescents in the UK (n = 11,427) asking about hours per day spent on specific screen media activities and four mental health indicators: self-harm behavior, depressive symptoms, life satisfaction, and self-esteem. RESULTS: Hours spent on social media and Internet use were more strongly associated with self-harm behaviors, depressive symptoms, low life satisfaction, and low self-esteem than hours spent on electronic gaming and TV watching. Girls generally demonstrated stronger associations between screen media time and mental health indicators than boys (e.g., heavy Internet users were 166% more likely to have clinically relevant levels of depressive symptoms than low users among girls, compared to 75% more likely among boys). CONCLUSION: Thus, not all screen time is created equal; social media and Internet use among adolescent girls are the most strongly associated with compromised mental health. Future research should examine different screen media activities and boys and girls separately where possible. Practitioners should be aware that some types of screen time are more likely to be linked to mental health issues than others.

Mental distress among U.S. adults during the COVID-19 pandemic.

OBJECTIVE: This study aims to document the impact of the COVID-19 pandemic on mental health. METHOD: We compared a nationally representative online sample of 2,032 U.S. adults in late April 2020 to 19,330 U.S. adult internet users who participated in the 2018 National Health Interview Survey (NHIS) using the Kessler-6 scale of mental distress in the last 30 days. RESULTS: Compared to the 2018 NHIS sample, U.S. adults in April 2020 were eight times more likely to fit criteria for serious mental distress (27.7% vs. 3.4%) and three times more likely to fit criteria for moderate or serious mental distress (70.4% vs. 22.0%). Differences between the 2018 and 2020 samples appeared across all demographic groups, with larger differences among younger adults and those with children in the household. CONCLUSIONS: These considerable levels of mental distress may portend substantial increases in diagnosed mental disorders and in their associated morbidity and mortality.

Screen media use and sleep disturbance symptom severity in children.

OBJECTIVES: Few studies have sought to evaluate how screen media use relates to symptoms of sleep-wake disturbances. To extend these prior studies in a large sample of children, this study examined associations of different types of screen media with symptom severity of different classes of sleep-wake disturbances. This study was preregistered here. DESIGN: This study utilized the baseline cross-sectional survey administered within the Adolescent Brain Cognitive Development Study (ABCD; Release 2.0). PARTICIPANTS: ABCD recruited over 11,000 U.S. children age 9-10 across 21 study sites using an epidemiologically-informed school-based recruitment strategy. MEASUREMENTS: Children reported typical weekend and weekday use of TV, video, video game, social media, texting, and video chat, and parents completed reports of the child's symptom severity of sleep-wake disturbances via the Sleep Disturbance Scale for Children. RESULTS: Greater screen media use, TV, video, and video game use, was associated with decreased sleep duration, increased sleep onset latency as well as greater excessive sleepiness, insomnia, and overall sleep disturbance symptom severity. Use of these screen medias were also associated with clinically relevant sleep problems. Ethnoracial differences emerged in screen use and sleep, but did not moderate the association between screen use and sleep. CONCLUSIONS: Greater use of screen medias was not just associated with longer sleep onset latency and shorter sleep duration, but also increased severity of multiple types of sleep-wake disturbances. Future research should use longitudinal designs to determine the direction of these associations in adolescent populations.

U.S. Census Bureau-assessed prevalence of anxiety and depressive symptoms in 2019 and during the 2020 COVID-19 pandemic.

BACKGROUND: The disruptions to daily life caused by the coronavirus disease 2019 (COVID-19) pandemic may have impacted mental health, particularly mood disorders. This study aimed to compare prevalence rates of anxiety disorder and depressive disorder in national samples in the U.S. before and during the pandemic. METHODS: Participants (n = 336,525) were from U.S. Census Bureau-administered nationally representative probability samples, one from the first half of 2019 and four during the pandemic in April and May 2020. All participants completed the Patient Health Questionnaire-2 screening for depressive disorder and the Generalized Anxiety Disorder-2 screening for anxiety disorders. RESULTS: Compared to U.S. adults in 2019, U.S. adults in April and May 2020 were more than three times as likely to screen positive for depressive disorders, anxiety disorders, or one or both, with more than one out of three screening positive for one or both. The prevalence of anxiety decreased slightly between the April 23-May 4, 2020 and the May 21-26, 2020 administrations, while the prevalence of depression increased slightly. CONCLUSIONS: U.S. adults in 2020 are considerably more likely to screen positive for mood disorders than in 2019, with anxiety declining and depression increasing from April to May.

Gender differences in associations between digital media use and psychological well-being: Evidence from three large datasets.

INTRODUCTION: Adolescents spend an increasing amount of time using digital media, but gender differences in their use and in associations with psychological well-being are unclear. METHOD: We drew from three large, representative surveys of 13- to 18-year-old adolescents in the U.S. and UK (total N = 221,096) examining digital media use in hours per day and several measures of psychological well-being separately in each of the three datasets. RESULTS: Adolescent girls spent more time on smartphones, social media, texting, general computer use, and online, and boys spent more time gaming and on electronic devices in general. Associations between moderate or heavy digital media use and low psychological well-being/mental health issues were generally larger for girls than for boys. Light users of digital media were slightly higher in well-being than non-users, with larger differences among boys. Among both genders, heavy users of digital media were often twice as likely as low users to be low in well-being or have mental health issues, including risk factors for suicide. CONCLUSIONS: Associations between heavy digital media use and low psychological well-being are larger for adolescent girls than boys.