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.].

National-Level Schoolwork Pressure, Family Structure, Internet Use, and Obesity as Drivers of Time Trends in Adolescent Psychological Complaints Between 2002 and 2018

Little is known about societal processes that contribute to changes in adolescent mental health problems. This study aims to fill this gap using data from the Health Behavior in School-aged Children study between 2002 and 2018 (n_countries = 43, n_individuals = 680,269, M_age = 14.52 (SD = 1.06), 51.04% female), supplemented with other international data. National-level psychological complaints increased more strongly among girls than boys. National-level schoolwork pressure, single-parent households, time spent on internet, and obesity were generally rising. In both boys' and girls' samples, increases in national-level schoolwork pressure, obesity, and time spent on internet use were independently associated with increases national-level psychological complaints. However, national-level obesity and psychological complaints were more strongly related among girls than boys. Results highlight the potential impact of societal-level processes on adolescent mental health problems.

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.

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.

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.

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 ​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.

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.

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.

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.

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.

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.

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.

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.

Increases in Depression, Self‐Harm, and Suicide Among U.S. Adolescents After 2012 and Links to Technology Use: Possible Mechanisms

Objective

Methods

Results

Conclusions

Depression, self‐harm, suicide, and unhappiness suddenly increased among adolescents after 2012, especially among girls and young women.

Increases in depression among adolescents have been concurrent with increases in digital media use.

Increased digital media and smartphone use may influence mental health via several mechanisms, including displacement and disruption of in‐person social interactions, interference with sleep, cyberbullying, and online information about self‐harm.

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) 2020 APA, all rights reserved).

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.

Correction: Generational and Time Period Differences in American Adolescents' Religious Orientation, 1966-2014

[This corrects the article DOI: 10.1371/journal.pone.0121454.].

Why increases in adolescent depression may be linked to the technological environment

Between 2011 and 2018, rates of depression, self-harm, and suicide attempts increased substantially among U.S. adolescents. The most probable cause(s) of these trends likely 1) began or accelerated during these years, 2) affected a large number of people, 3) impacted everyday life, and 4) were associated with depression. In several large studies, heavy users of technology are twice as likely as light users to be depressed or have low well-being. Cohort declines in face-to-face social interaction may also impact even non-users of digital media. Thus, although technology use is not the cause of most depression, increased time spent on technology and the technological environment may be causes of the sudden increase in depression since 2011.