Active behaviors and screen time in offspring of parents with major depressive disorder, bipolar disorder and schizophrenia

Active behaviors and screen time in offspring of parents with major depressive disorder, bipolar disorder and schizophrenia

Psychiatry Research xxx (xxxx) xxxx Contents lists available at ScienceDirect Psychiatry Research journal homepage: www.elsevier.com/locate/psychres...

555KB Sizes 0 Downloads 24 Views

Psychiatry Research xxx (xxxx) xxxx

Contents lists available at ScienceDirect

Psychiatry Research journal homepage: www.elsevier.com/locate/psychres

Active behaviors and screen time in offspring of parents with major depressive disorder, bipolar disorder and schizophrenia Pizzo A.a,b, Drobinin V.b,c, Sandstrom A.a,b, Zwicker A.b,d, Howes Vallis E.a,b, Fine A.b, Rempel S.b, Stephens M.b, Howard C.b, Villars K.b, MacKenzie L.E.b,e, Propper L.a,f, Abidi S.a,f, Lovas D.a,f, ⁎ Bagnell A.a,f, Cumby J.b, Alda M.a,b, Uher R.a,b, Pavlova B.a,b, a

Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada Nova Scotia Health Authority, Halifax, Nova Scotia, Canada c Dalhousie University, Department of Medical Neuroscience, Halifax, Nova Scotia, Canada d Dalhousie University, Department of Pathology, Halifax, Nova Scotia, Canada e Dalhousie University, Department of Psychology, Halifax, Nova Scotia, Canada f IWK Health Centre, Halifax, Nova Scotia, Canada b

ARTICLE INFO

ABSTRACT

Keywords: Mental illness Screen Physical activity Social activity Reading

Activities may be modifiable factors that moderate the risk and resilience in the development of mental health and illness. Youth who spend more time using screens are more likely to have poor mental health. Conversely, time spent engaged in active behaviors (i.e., physical activity, socializing and reading) is associated with better mental health. The choice of activities may be important in offspring of parents with mental illness, who are at increased risk for developing mental disorders. Among 357 youth of the FORBOW (Families Overcoming Risks and Building Opportunities for Well-being) cohort aged 6–21, we examined whether parental diagnosis of mental illness (i.e., major depressive disorder, schizophrenia and bipolar disorder) and current levels of depression influenced the amount of time their offspring spent using screens and engaging in active behaviors. Parental history of mental illness and higher levels of current depression in mothers were associated with less time spent engaged in active behaviors and more time spent using screens. Creating opportunities and incentives for active behaviors may redress the balance between youth with and without a familial history of mental illness.

1. Introduction Activities youth engage in may moderate the risk and resilience in the development of mental health and illness (Ahn and Fedewa, 2011; Andreassen et al., 2016; Bickham et al., 2015; Twenge et al., 2018a). While a tendency to choose certain activities is partly genetic (Lightfoot et al., 2018; Maia et al., 2002; Mustelin et al., 2012; Saudino and Zapfe, 2008), parents also influence what activities their children engage in through modeling and encouragement (Mitchell et al., 2012; Totland et al., 2013; Zecevic et al., 2010). With the increase in time that young people spend using screens (Twenge et al., 2018b), the question of the impact of screen time on mental health has become more pressing. Indeed, time spent using screens is associated with increased depressive symptoms, anxiety, attention deficit hyperactive disorder, low self-esteem, poor sleep and aggressive and anti-social behavior (Andreassen et al., 2016; Bickham et al., 2015; Chan and Rabinowitz, 2006; Gentile et al., 2012;



Lin et al., 2016; Maras et al., 2015; Pagani et al., 2016; Primack et al., 2017; Rosen et al., 2014; Shensa et al., 2017; Woods and Scott, 2016). However, many active behaviors including physical activity and mentally active sedentary behaviors (i.e., reading and socializing) are associated with better mental health. Physical activity in youth is associated with less depression and anxiety (Ahn and Fedewa, 2011; Brown et al., 2013; Camero et al., 2012; Doré et al., 2016; Nabkasorn et al., 2006). Additionally, reading and in-person social interactions are associated with lower depressive symptoms (Hallgren et al., 2019, 2018; Twenge et al., 2018a). In contrast, social isolation is related to poor psychological well-being and precedes the development of psychosis (Gayer-Anderson and Morgan, 2013; Rohde et al., 2016). Choice of activities may be especially important for offspring of parents with major depressive disorder, bipolar disorder and schizophrenia who have a one in three risk of developing a major mood or psychotic disorder themselves (Rasic et al., 2014). To date it is not known how parental diagnosis of a mood or psychotic disorder relates

Corresponding author at. Abbie J. Lane Building, 5909 Veterans' Memorial Lane, Halifax, Nova Scotia, B3H 2E2, Canada. E-mail address: [email protected] (P. B.).

https://doi.org/10.1016/j.psychres.2019.112709 Received 19 July 2019; Received in revised form 7 October 2019; Accepted 26 November 2019 0165-1781/ © 2019 Elsevier B.V. All rights reserved.

Please cite this article as: Pizzo A., et al., Psychiatry Research, https://doi.org/10.1016/j.psychres.2019.112709

Psychiatry Research xxx (xxxx) xxxx

P. A., et al.

to the offspring engagement in different activities. As people living with mood and psychotic disorders have a harder time being active and engaging in social activities during illness episodes (Vancampfort et al., 2017), it is possible that they model these behaviors to their offspring. It is also possible that genetic factors passed down from parents living with mood and psychotic disorder to their offspring can influence the amount of time they spend being active (Lightfoot et al., 2018; Maia et al., 2002; Mustelin et al., 2012; Saudino and Zapfe, 2008). As the course of mood and psychotic disorders can vary from isolated episodes with full remission through residual symptoms outside of acute illness episodes to chronic symptoms (Heilbronner et al., 2016; Judd et al., 2003a, 2003b; Paykel, 2008; Pettit et al., 2009; Schennach et al., 2015) the environmental impact of parental mental illness on the offspring may differ depending on the current parental symptoms. Activities in offspring of parents with mood and psychotic disorders may constitute a target of preventative interventions, as activities one engages in can be modified (Fjeldose et al., 2011; Michie et al., 2009; Williams and French, 2011). In the current study, we investigated whether parental history of mood and psychotic disorders and current levels of parental depression were related to the amount of time the offspring engaged in screen activities and active behaviors. We hypothesized that youth with a parental history of mood and psychotic disorders will spend less time engaged in active behaviors (i.e., physical activity, social activity and reading) and more time using screens compared to controls. We also hypothesized that current parental depressive symptoms will be associated with more screen time and less engagement in active behaviors in offspring.

Table 1 Items used to assess active behaviors in offspring. Active Behaviors Physical Activity 1. Hours per day playing outside or outdoor activities (e.g., walking, riding bike, etc.) 2. Hours per day physical activity (i.e., organized sports and gym class) Social Activity 1. Hours per day social activity (i.e., spending time with friends outside of school) Reading 1. Hours per day reading for pleasure (i.e., being read to or reading on your own)

items and two forms (self-report and partner/spouse-report) and asks respondents how they have been feeling over the past 7 days. Some examples of items on the EFQ include “less interested in things you used to do”, “positive about the future”, “able to cope what life brings” and “tired or lacking energy”. All items are rated on a 5-point scale ranging from 1 (none of the time) to 5 (all the time). The EFQ has good internal consistency, test-retest reliability, and convergent validity with other measures of depression (Mann et al., 2013; Uher and Goodman, 2010). 2.2.2. Youth assessment Youth assessors were separate from parent assessors and blind to parent diagnoses. They asked parents and youth to identify the average amount of time during the day the youth spent engaging in active behaviors (i.e., physical activity, social activity and reading) and screen activities (i.e., playing video games, browsing the internet, using social media and watching television). Items used to assess active behaviors and screen time can be found in Table 1 and 2. Participants selected the average amount of time they spent engaged in each activity during a typical day on a 5- point scale (0 h, up to 1 h, 1–2 h, 2–3 h, 4 h or more). As reliability and validity of child self-report increases with age (Ghetti and Lee, 2011; Sallis et al., 1993), we used only parent reports for children younger than 8 years. Parent and offspring report of time the youth spent in screen and off-screen activities was aggregated and averaged, for youth aged 8 to 11 years old. Youth only report was used for offspring aged 12 years and older.

2. Methods 2.1. Participants Participants of this study were offspring of parents with major depressive disorder (MDD), bipolar disorder, schizophrenia and offspring of parents with no history of mood and psychotic disorders (i.e., controls) who participated in the Families Overcoming Risks and Building Opportunities for Well-being project (FORBOW; Uher et al., 2014). We recruited parents through their contact with mental health services in Nova Scotia, Canada. We included offspring regardless of their own psychopathology. We recruited additional offspring matched on age and socioeconomic status through local school boards and community organizations. For the current study, we included participants recruited from November 2012 to September 2018. Youths were eligible for the study if they were 6 to 21 years of age. No other inclusion or exclusion criteria were used. The Research Ethics Board of the Nova Scotia Health Authority approved all study procedures. Participants provided written informed consent. Participants who did not have the capacity to provide full consent provided an assent, and their parent or legal guardian consented on their behalf.

2.3. Data analysis We tested the effect of parental diagnosis (lifetime diagnosis of MDD, lifetime diagnosis of bipolar disorder, lifetime diagnosis of schizophrenia or no history of mood or psychotic disorder in either biological parent) on offspring time spent engaging in active behaviors and screen activities using multiple mixed effects linear regression in STATA 15 (StataCorp, 2017). In addition, we tested the effect of current parental symptoms of depression (assessed by the EFQ) on youth time spent in screen activities and in active behaviors, using multiple mixed effects linear regression. We included youth age and sex as fixed covariates in all models. We accounted for the non-independence of related individuals within families and multiple observations within individuals with hierarchical random effects of family and individual. We report the standardized regression coefficients (beta) and their 95% Table 2 Items used to assess screen time in offspring.

2.2. Procedure

Screen Time Video Games 1. Hours per day playing video games on the computer (e.g., Minecraft, gaming website) 2. Hours per day playing console video games (e.g., X-box, PlayStation, Nintendo) Internet Browsing 1. Hours per day on the computer browsing (e.g., website browsing, email) Social Media Use 1. Hours per day using social media (e.g., Facebook, Twitter, Instagram) Television Watching 1. Hours per day watching television/videos (e.g., Netflix, streaming videos, YouTube)

2.2.1. Parent assessment We assessed parental lifetime diagnoses of mood and psychotic disorders using the Schedule for Affective Disorders and Schizophrenia (SADS-IV) (Endicott and Spitzer, 1979) and the Structured Clinical Interview for DSM 5 Disorders (SCID-5) (First et al., 2015). We confirmed parent diagnoses in consensus meetings with psychiatrists blind to offspring psychopathology. We assessed current depressive symptoms in parents annually with the self-report and partner-report version of the Everyday Feelings Questionnaire (EFQ; Uher and Goodman, 2010). The EFQ consists of 10 2

Psychiatry Research xxx (xxxx) xxxx

P. A., et al.

Table 3 Sample characteristics at the last recorded assessment. Parental Diagnosis

Mean Age of Offspring in Years (SD)

Number of Offspring

Percentage of Female Offspring

Control Depression Bipolar Disorder Schizophrenia

11.19 12.16 13.56 10.46

105 153 74 25

46.67 52.94 51.35 56.00

(3.19) (3.72) (4.07) (3.97)

Table 5 Daily mean time spent engaged in screen activities and active behaviors in offspring of parents with and without mood and psychotic disorders.

Notes. SD = Standard Deviation.

3.1. Sample characteristics We obtained 895 reports of screen time and time spent engaged in active behaviors of 357 (males 175 and 182 females) participants from 206 families. A total of 377 participants were eligible for the current study however, no data was obtained regarding time spent for 20 of them. Sample characteristics for participants with no data on screen time and time spent in active behaviors was collected can be found in supplementary material. Participants were on average 10.71 years old (SD = 3.76) on their initial assessment and 12.05 years old (SD = 3.77) on their last recorded assessment. Of the youth participants, 153 had a biological parent with major depressive disorder (MDD), 74 had a biological parent with bipolar disorder, 25 had a biological parent with schizophrenia and 105 had parents with no history of mood or psychotic disorders. Sample characteristics are shown in Table 3.

Table 4 The estimate of differences in time spent in active behaviors and screen activities in offspring at familial high risk compared to offspring of parents without mood or psychotic disorders.

p-value 0.017

Beta 0.23

Bipolar

−0.34

0.013

0.26

Schizophrenia

−0.27

0.164

0.10

95% C.I. −0.50 to −0.05 −0.60 to −0.07 −0.65 to 0.11

95% C.I. 0.004 to 0.45 0.005 to 0.52 −0.28 to 0.47

4.29 5.22 5.55 4.02

7.49 6.78 6.71 7.00

(2.39) (2.87) (2.84) (2.21)

(2.60) (2.73) (2.70) (2.38)

Youth with a parental history of MDD and bipolar disorder spend less time engaged in active behaviors, i.e. physical activity, social interactions, and reading compared to controls. They also spend more time engaged in screen activities than controls. We found no statistically significant difference between offspring of parents with schizophrenia and controls in time spent engaged in active behaviors and screen activities. This is probably because our sample of offspring of parents with schizophrenia was too small to detect a statistically significant difference between the two groups. The mean amount of time that offspring of parents with schizophrenia spent in active behaviors was similar to that reported by offspring of parents with depression. Higher levels of current maternal symptoms of depression were associated with offspring spending less time engaged in active behaviors and more time in screen activities. We did not find an association between paternal symptoms of depression and offspring time spent engaged in active behaviors or using screens. To our knowledge, this is the first study that found that offspring of people with mood disorders spend less time in health-promoting behaviors (i.e. physical activity, social interactions, and reading) and more time using screens than offspring of people without mood or psychotic disorders. These differences may be partly due to the fact that engagement in certain activities, especially physical activity, has a genetic component (Lightfoot et al., 2018; Maia et al., 2002; Mustelin et al., 2012; Saudino and Zapfe, 2008). Environmental

Offspring of parents with MDD (beta = −0.28, 95% CI −0.50 to −0.05, p = 0.017) and bipolar disorder (beta = −0.34, 95% CI −0.60 to −0.07, p = 0.013) spent less time engaged in active behaviors compared to controls. Offspring of parents with schizophrenia reported spending less time in active behaviors but did not significantly differ from the controls (beta = −0.27, 95% CI −0.65 to 0.11, p = 0.164). Offspring of parents with MDD (beta= 0.23, 95% CI 0.004 to 0.45, p = 0.046) and bipolar disorder (beta = 0.26, 95% CI 0.005 to 0.52, p = 0.046) spent more time using screens compared to controls. Offspring of parents with schizophrenia reported spending more time engaged in screen activities than controls however, this did not reach statistical significance (beta= 0.10, 95% CI −0.28 to 0.47, p = 0.613; Table 4). Daily mean time spent engaged in screen and active behaviors can be found in Table 5.

Beta −0.28

Control Depression Bipolar Disorder Schizophrenia

4. Discussion

3.2. Parent diagnosis and time offspring spent engaged in active behaviors and screen activities

Parental History Depression

Hours per Day Spent in Active Behaviors (SD)

Increased levels of maternal depressive symptoms were associated with the offspring spending less time engaged in active behaviors (beta = −0.12, 95% CI −0.23 to −0.01, p = 0.036). No association was found between paternal levels of depression and amount of time the offspring spent engaged in active behaviors (beta = −0.09, 95% CI −0.27 to 0.08, p = 0.289). Maternal symptoms of depression were associated with more time spent using screens in the offspring (beta=0.16, 0.06 to 0.27, p = 0.002). This association remained significant after controlling for multiple testing. Paternal symptoms of depression were not significantly associated with the amount of time the offspring spent using screens (beta = 0.10, 95% CI −0.05 to 0.26, p = 0.196) (Table 6).

3. Results

Time Spent Using Screens

Hours per Day Spent Using Screens (SD)

3.3. Current parental symptoms of depression and time offspring engaged in active behaviors and screen activities

confidence interval (95% C.I.). We report results with p < 0.05 as nominally statistically significant. We also report significance corrected for the number of tests (ten tests, corrected p-value < 0.005).

Time Spent in Active Behaviors

Parental Diagnosis

Table 6 Relationship between the parental levels of depression and the time their offspring spends in active behaviors and screen activities.

p-value 0.046

Maternal EFQ Total Paternal EFQ Total

0.046 0.613

Time Spent in Active Behaviors Beta 95% C.I. p-value

Time Spent Using Screens Beta 95% C.I. p-value

−0.12

0.036

0.16

0.289

0.10

−0.09

−0.23 to −0.01 −0.27 to 0.08

0.06 to 0.27 −0.05 to 0.26

0.002 0.196

Notes. 95% C.I. = 95% Confidence Interval; EFQ = Everyday Feelings Questionnaire.

Notes. 95% C.I. = 95% Confidence Interval. 3

Psychiatry Research xxx (xxxx) xxxx

P. A., et al.

influences have also been found to play a role in the level of youth activity and screen time (Mitchell et al., 2012; Totland et al., 2013; Zecevic et al., 2010). As depression makes it hard for individuals to spend time actively, it is possible that offspring of people with mood disorders learn to spend less time reading or in physical or social activities and more time using screens by observing their parents when they are ill (Totland et al., 2013; Lee et al., 2018; Xu et al., 2015). This is in line with our finding that mothers' higher current levels of depressive symptoms are associated with less time spent engaged in active behaviors and more screen time in their offspring. It is also possible that parents who are not experiencing a mood episode may be able to provide more persistent encouragement for their children to engage in physical and social activity as well as reading (Zecevic et al., 2010). The association between increased parental depressive symptoms and offspring spending less time in active behaviors and more time using screens was limited to mother's symptoms. Mothers on average spend more time with their children compared to fathers (Craig and Bittman, 2008; Craig and Mullan, 2011) and may thus have more opportunities to model their behaviors to their child. The lack of significant effect of parental diagnosis of schizophrenia on offspring time spent in screen activities and on engagement in active behaviors needs to be interpreted with caution, as our sample of offspring of parents with schizophrenia was small. While it is possible that the effect on offspring time spent in active behaviors and screen time is specific to families with a parent with a mood disorder or that parents with schizophrenia may exert less influence on the types of activities their offspring participate in as they are more likely to be absent in their child's life (Simolia et al., 2019; Seeman, 2012), we are mindful of not over-interpreting this finding, that is likely to be due to insufficient power. Lack of engagement in physical activity, social activity and reading and more time using screens by youth with a familial history of mental illness could contribute to the heightened risk of future psychopathology. Poor mental health outcomes are related to the use of screens (Andreassen et al., 2016; Bickham et al., 2015; Chan and Rabinowitz, 2006; Gentile et al., 2012; Lin et al., 2016; Maras et al., 2015; Pagani et al., 2016; Primack et al., 2017; Rosen et al., 2014; Shensa et al., 2017; Woods and Scott, 2016) and active behaviors are associated with favourable mental health outcomes (Ahn and Fedewa, 2011; Doré et al., 2016; Twenge et al., 2018a). Therefore, reductions in screen time and increasing time spent in active behaviors may help reduce the likelihood of developing mental illness. Promotion of physical activity, social interactions, and reading in youth at familial high risk for mental illness may be an effective way to reduce screen time and increase active behaviors. Preventive interventions for youth with parents with mental illness which promote participation in active behaviors may help protect against future psychiatric disorders. Efficacious interventions aimed at changing behavior and activities individuals partake in have been developed (Fjeldose et al., 2011; Michie et al., 2009; Williams and French, 2011). Therefore, youth with a parental history of mental illness should be targeted for these interventions. Interventions which promote behavioral changes at multiple settings (i.e., school, home and community) have been shown to be most effective in children and adolescents (Kreimler et al., 2011; van Sluijs et al., 2007). Interventions with younger children are likely to require parent involvement. Programs which promote physical activity, social activity and reading (e.g., organized sports, scouts, community organizations, book clubs, music programs and afterschool clubs) may be especially important for these young people. Economical support for parents living with a mental illness may help the financial burden of enrolling their child in organized sports or afterschool programs. In addition, treating maternal symptoms of depression may contribute to increased offspring engagement in active behaviors and reductions in screen time and therefore to decreasing their risk of developing mental illness.

Strengths and limitations To our knowledge, this is the first study to assess how offspring of parents with mood and psychotic disorders spend their time. Our study benefits from a longitudinal design which allowed for multiple reports to be gathered on each participant. However, our study is not without limitations. The sample of offspring of parents with schizophrenia is small and it is possible that the negative findings are due to the small sample size. Also, we did not collect information on parents’ activities and thus can only speculate that parents and offspring are similar in the way they spend their time. Reports of time spent in various activities depended on the participants’ recall and willingness to share this information. While it is possible that we overestimated, or underestimated the amount of time the offspring spent engaging in certain activities, it is unlikely that this would have systematically differed between the groups. Measures of depressive symptoms are not independent of personality (Bagby et al., 2008; Hakulinen et al., 2015), hence we cannot exclude the possibility that the EFQ score may have been affected by personality as well as psychopathology. However, this does not bias our conclusions. The effect of having two parents with a mood or psychotic disorder was not analyzed and therefore its influence on offspring engagement in various activities is unknown. Offspring symptoms of psychopathology were not accounted for and may have influenced our results. Finally, we did not assess every activity participants engaged in, thus, can only make conclusions on activities that were assessed. Future directions Future research will benefit from enrolling a larger number of parents with schizophrenia and their offspring and concurrently collecting information on offspring and parental time spent in various activities. Using activity logs may improve participants’ recall and help assess a wider range of activities and using actigraphy may help estimate time spent in physical activity more precisely and without reporter bias. Finally, assessing a wider range of activities will give a more complete picture of the ways youth with and without family history of mental illness spend their time. Conclusions In conclusion, youth with a parental history of mood disorders spend less time engaged in active behaviors such as, physical activity, reading and social interactions and more time using screens, compared to controls. Higher current levels of depression in mothers are associated with less time spent engaged in active behaviors and more time spent using screens among their offspring. Youth with parental history of mood disorders may benefit from programs which promote active behaviors such as organized sports, scouts, and afterschool clubs. This may be especially important for young people whose mothers are experiencing symptoms of depression. Treating parents’, especially mothers’, depression may increase the amount of time their offspring spend reading, exercising and socializing and reduce screen time and hence may help increase the offspring resilience to mental illness. Funding This work was supported by the Canada Research Chairs Program (award number 231397), the Canadian Institutes of Health Research (grant reference numbers 124976, 142738 and 148394), the Brain & Behavior Research Foundation (NARSAD) Independent Investigator Grant 24684, Nova Scotia Health Research Foundation (grants 275319, 1716 and 353892) and the Dalhousie Medical Research Foundation and the CIHR Doctoral Award (award number 157975). The funders had no role in the study design, data collection, data analysis, data interpretation, preparation of the manuscript or the decision to submit the manuscript for publication. 4

Psychiatry Research xxx (xxxx) xxxx

P. A., et al.

Declaration of Competing Interest

Keller, M.B., 2003b. The comparative clinical phenotype and long term longitudinal episode course of bipolar I and II: a clinical spectrum or distinct disorders? J. Affect. Disord. 73, 19–32. https://doi.org/10.1016/S0165-0327(02)00324-5. Kriemler, S., Meyer, U., Martin, E., van Sluijs, E.M.F., Andersen, L.B., Martin, B.W., 2011. Effect of school-based interventions on physical activity and fitness in children and adolescents: a review of reviews and systematic update. Br. J. Sports Med. 45, 923–930. https://doi.org/10.1136/bjsports-2011-090186. Lee, E.-Y., Hesketh, K.D., Rhodes, R.E., Rinaldi, C.M., Spence, J.C., Carson, V., 2018. Role of parental and environmental characteristics in toddlers’ physical activity and screen time: bayesian analysis of structural equation models. Int. J. Behav. Nutr. Phys. Activ. 15. https://doi.org/10.1186/s12966-018-0649-5. Lightfoot, J.T., De Geus, E.J.C., Booth, F.W., Bray, M.S., Den Hoed, M., Kaprio, J., Kelly, S.A., Pomp, D., Saul, M.C., Thomis, M.A., Garland, T., Bouchard, C., 2018. Biological/ Genetic regulation of physical activity level: consensus from genbiopac. Med. Sci. Sport. Exerc. 50, 863–873. https://doi.org/10.1249/MSS.0000000000001499. Lin, L., Sidani, J.E., Shensa, A., Radovic, A., Miller, E., Colditz, J.B., Hoffman, B.L., Giles, L.M., Primack, B.A., 2016. Association between social media use and depression among U.S. young adults research article: social media and depression. Depress Anxiety 33, 323–331. https://doi.org/10.1002/da.22466. Maia, J.A.R., Thomis, M., Beunen, G., 2002. Genetic factors in physical activity levels. Am. J. Prev. Med. 23, 87–91. https://doi.org/10.1016/S0749-3797(02)00478-6. Mann, J., Henley, W., O’Mahen, H., Ford, T., 2013. The reliability and validity of the everyday feelings questionnaire in a clinical population. J. Affect. Disord. 148, 406–410. https://doi.org/10.1016/j.jad.2012.03.045. Maras, D., Flament, M.F., Murray, M., Buchholz, A., Henderson, K.A., Obeid, N., Goldfield, G.S., 2015. Screen time is associated with depression and anxiety in Canadian youth. Prev. Med. 73, 133–138. https://doi.org/10.1016/j.ypmed.2015.01. 029. Michie, S., Abraham, C., Whittington, C., McAteer, J., Gupta, S., 2009. Effective techniques in healthy eating and physical activity interventions: a meta-regression. Health Psychol. 28, 690–701. https://doi.org/10.1037/a0016136. Mitchell, J., Skouteris, H., McCabe, M., Ricciardelli, L.A., Milgrom, J., Baur, L.A., FullerTyszkiewicz, M., Dwyer, G., 2012. Physical activity in young children: a systematic review of parental influences. Early Child. Dev. Care 182, 1411–1437. https://doi. org/10.1080/03004430.2011.619658. Mustelin, L., Joutsi, J., Latvala, A., Pietiläinen, K.H., Rissanen, A., Kaprio, J., 2012. Genetic influences on physical activity in young adults: a twin study. Med. Sci. Sport. Exerc. 44, 1293–1301. https://doi.org/10.1249/MSS.0b013e3182479747. Nabkasorn, C., Miyai, N., Sootmongkol, A., Junprasert, S., Yamamoto, H., Arita, M., Miyashita, K., 2006. Effects of physical exercise on depression, neuroendocrine stress hormones and physiological fitness in adolescent females with depressive symptoms. Eur. J. Public Health 16, 179–184. https://doi.org/10.1093/eurpub/cki159. Pagani, L.S., Lévesque-Seck, F., Fitzpatrick, C., 2016. Prospective associations between televiewing at toddlerhood and later self-reported social impairment at middle school in a Canadian longitudinal cohort born in 1997/1998. Psychol. Med. 46, 3329–3337. https://doi.org/10.1017/S0033291716001689. Paykel, E.S., 2008. Partial remission, residual symptoms, and relapse in depression. Dialog. Clin. Neurosci. 10, 431–437. Pettit, J.W., Lewinsohn, P.M., Roberts, R.E., Seeley, J.R., Monteith, L., 2009. The longterm course of depression: development of an empirical index and identification of early adult outcomes. Psychol. Med. 39, 403. https://doi.org/10.1017/ S0033291708003851. Primack, B.A., Shensa, A., Escobar-Viera, C.G., Barrett, E.L., Sidani, J.E., Colditz, J.B., James, A.E., 2017. Use of multiple social media platforms and symptoms of depression and anxiety: a nationally-representative study among U.S. young adults. Comput. Human Behav. 69, 1–9. https://doi.org/10.1016/j.chb.2016.11.013. Rasic, D., Hajek, T., Alda, M., Uher, R., 2014. Risk of mental illness in offspring of parents with schizophrenia, bipolar disorder, and major depressive disorder: a meta-analysis of family high-risk studies. Schizophr. Bull. 40, 28–38. https://doi.org/10.1093/ schbul/sbt114. Rohde, N., D’Ambrosio, C., Tang, K.K., Rao, P., 2016. Estimating the mental health effects of social isolation. Appl. Res. Qual. Life 11, 853–869. https://doi.org/10.1007/ s11482-015-9401-3. Rosen, L.D., Lim, A.F., Felt, J., Carrier, L.M., Cheever, N.A., Lara-Ruiz, J.M., Mendoza, J.S., Rokkum, J., 2014. Media and technology use predicts ill-being among children, preteens and teenagers independent of the negative health impacts of exercise and eating habits. Comput. Human Behav. 35, 364–375. https://doi.org/10.1016/j.chb. 2014.01.036. Sallis, J.F., Buono, M.J., Roby, J.J., Micale, F.G., Nelson, J.A., 1993. Seven-day recall and other physical activity self-reports in children and adolescents. Med. Sci. Sports Exerc. 25, 99–108. Saudino, K.J., Zapfe, J.A., 2008. Genetic influences on activity level in early childhood: do situations matter? Child Dev. 79, 930–943. https://doi.org/10.1111/j.1467-8624. 2008.01168.x. Schennach, R., Riedel, M., Obermeier, M., Spellmann, I., Musil, R., Jäger, M., Schmauss, M., Laux, G., Pfeiffer, H., Naber, D., Schmidt, L.G., Gaebel, W., Klosterkötter, J., Heuser, I., Maier, W., Lemke, M.R., Rüther, E., Klingberg, S., Gastpar, M., Möller, H.J., 2015. What are residual symptoms in schizophrenia spectrum disorder? Clinical description and 1-year persistence within a naturalistic trial. Eur. Arch. Psychiatry Clin. Neurosci. 265, 107–116. https://doi.org/10.1007/s00406-014-0528-2. Seeman, M.V., 2012. Intervention to prevent child custody loss in mothers with schizophrenia. Schizophr. Res. Treatment 2012, 1–6. https://doi.org/10.1155/2012/ 796763. Shensa, A., Escobar-Viera, C.G., Sidani, J.E., Bowman, N.D., Marshal, M.P., Primack, B.A., 2017. Problematic social media use and depressive symptoms among U.S. young adults: a nationally-representative study. Soc. Sci. Med. 182, 150–157. https://doi.

None Supplementary materials Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.psychres.2019.112709. References Ahn, S., Fedewa, A.L., 2011. A meta-analysis of the relationship between children’s physical activity and mental health. J. Pediatr. Psychol. 36, 385–397. https://doi. org/10.1093/jpepsy/jsq107. Andreassen, C.S., Billieux, J., Griffiths, M.D., Kuss, D.J., Demetrovics, Z., Mazzoni, E., Pallesen, S., 2016. The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: a large-scale cross-sectional study. Psychol. Addict. Behav. 30, 252–262. https://doi.org/10.1037/adb0000160. Bagby, R.M., Quilty, L.C., Ryder, A.C., 2008. Personality and depression. Can. J. Psychiatry 53, 14–25. https://doi.org/10.1177/070674370805300104. Bickham, D.S., Hswen, Y., Rich, M., 2015. Media use and depression: exposure, household rules, and symptoms among young adolescents in the USA. Int. J. Public Health 60, 147–155. https://doi.org/10.1007/s00038-014-0647-6. Brown, H.E., Pearson, N., Braithwaite, R.E., Brown, W.J., Biddle, S.J.H., 2013. Physical activity interventions and depression in children and adolescents: a systematic review and meta-analysis. Sports Med. 43, 195–206. https://doi.org/10.1007/s40279-0120015-8. Camero, M., Hobbs, C., Stringer, M., Branscum, P., Taylor, E.L., 2012. A review of physical activity interventions on determinants of mental health in children and adolescents. Int. J. Ment. Health Promot. 14, 196–206. https://doi.org/10.1080/ 14623730.2012.752901. Chan, P.A., Rabinowitz, T., 2006. A cross-sectional analysis of video games and attention deficit hyperactivity disorder symptoms in adolescents. Ann. Gen. Psychiatry 5. https://doi.org/10.1186/1744-859X-5-16. Craig, L., Bittman, M., 2008. The incremental time costs of children: an analysis of children’s impact on adult time use in Australia. Fem. Econ. 14, 59–88. https://doi. org/10.1080/13545700701880999. Craig, L., Mullan, K., 2011. How mothers and fathers share childcare: a cross-national time-use comparison. Am. Sociol. Rev. 76, 834–861. https://doi.org/10.1177/ 0003122411427673. Doré, I., O’Loughlin, J.L., Beauchamp, G., Martineau, M., Fournier, L., 2016. Volume and social context of physical activity in association with mental health, anxiety and depression among youth. Prev. Med. 91, 344–350. https://doi.org/10.1016/j.ypmed. 2016.09.006. Endicott, J., Spitzer, R., 1979. Use of the research diagnostic criteria and the schedule for affective disorders and schizophrenia to study affective disorders. Am. J. Psychiatry 136, 52–56. https://doi.org/10.1176/ajp.136.1.52. First, M., Williams, J., Karg, R., Spitzer, R., 2015. Structured Clinical Interview For DSM5— Research Version (SCID-5 For DSM-5, Research Version; SCID-5-RV). American Psychiatric Association, Arlington. Fjeldsoe, B., Neuhaus, M., Winkler, E., Eakin, E., 2011. Systematic review of maintenance of behavior change following physical activity and dietary interventions. Health Psychol. 30, 99–109. https://doi.org/10.1037/a0021974. Gayer-Anderson, C., Morgan, C., 2013. Social networks, support and early psychosis: a systematic review. Epidemiol. Psychiatr. Sci. 22, 131–146. https://doi.org/10.1017/ S2045796012000406. Gentile, D.A., Swing, E.L., Lim, C.G., Khoo, A., 2012. Video game playing, attention problems, and impulsiveness: evidence of bidirectional causality. Psychol. Pop. Media Cult. 1, 62–70. https://doi.org/10.1037/a0026969. Ghetti, S., Lee, J., 2011. Children’s episodic memory: children’s episodic memory. Wiley Interdiscip. Rev. Cogn. Sci. 2, 365–373. https://doi.org/10.1002/wcs.114. Hakulinen, C., Elovainio, M., Pulkki-Råback, L., Virtanen, M., Kivimäki, M., Jokela, M., 2015. Personality and depressive symptoms: individual participant meta-analysis of 10 cohort studies: research article: personality and depression. Depress Anxiety 32, 461–470. https://doi.org/10.1002/da.22376. Hallgren, M., Nguyen, T.-T., Owen, N., Stubbs, B., Vancampfort, D., Lundin, A., Dunstan, D., Bellocco, R., Lagerros, Y.T., 2019. Cross-sectional and prospective relationships of passive and mentally active sedentary behaviours and physical activity with depression. Br. J. Psychiatry 1–7. https://doi.org/10.1192/bjp.2019.60. Hallgren, M., Owen, N., Stubbs, B., Zeebari, Z., Vancampfort, D., Schuch, F., Bellocco, R., Dunstan, D., Trolle Lagerros, Y., 2018. Passive and mentally-active sedentary behaviors and incident major depressive disorder: a 13-year cohort study. J. Affect. Disord. 241, 579–585. https://doi.org/10.1016/j.jad.2018.08.020. Heilbronner, U., Samara, M., Leucht, S., Falkai, P., Schulze, T.G., 2016. The longitudinal course of schizophrenia across the lifespan: clinical, cognitive, and neurobiological aspects. Harv. Rev. Psychiatry 24, 118–128. https://doi.org/10.1097/HRP. 0000000000000092. Judd, L.L., Akiskal, H.S., Schettler, P.J., Coryell, W., Endicott, J., Maser, J.D., Solomon, D.A., Leon, A.C., Keller, M.B., 2003a. A prospective investigation of the natural history of the long-term weekly symptomatic status of bipolar II disorder. Arch. Gen. Psychiatry 60, 261. https://doi.org/10.1001/archpsyc.60.3.261. Judd, L.L., Akiskal, H.S., Schettler, P.J., Coryell, W., Maser, J., Rice, J.A., Solomon, D.A.,

5

Psychiatry Research xxx (xxxx) xxxx

P. A., et al. org/10.1016/j.socscimed.2017.03.061. Simoila, L., Isometsä, E., Gissler, M., Suvisaari, J., Sailas, E., Halmesmäki, E., Lindberg, N., 2019. Maternal schizophrenia and out-of-home placements of offspring: a national follow-up study among Finnish women born 1965-1980 and their children. Psychiatry Res. https://doi.org/10.1016/j.psychres.2019.01.011. Statacorp, 2017. Stata Statistical Software: Release 15. StataCorp LLC, College Station, TX. Totland, T.H., Bjelland, M., Lien, N., Bergh, I.H., Gebremariam, M.K., Grydeland, M., Ommundsen, Y., Andersen, L.F., 2013. Adolescents’ prospective screen time by gender and parental education, the mediation of parental influences. Int. J. Behav. Nutr. Phys. Activ. 10, 89. https://doi.org/10.1186/1479-5868-10-89. Twenge, J.M., Joiner, T.E., Rogers, M.L., Martin, G.N., 2018a. Increases in depressive symptoms, suicide-related outcomes, and suicide rates among U.S. adolescents after 2010 and links to increased new media screen time. Clin. Psychol. Sci. 6, 3–17. https://doi.org/10.1177/2167702617723376. Twenge, J.M., Martin, G.N., Spitzberg, B.H., 2018b. Trends in U.S. adolescents’ media use, 1976–2016: the rise of digital media, the decline of TV, and the (near) demise of print. Psychol. Pop. Media Cult. https://doi.org/10.1037/ppm0000203. Uher, R., Cumby, J., MacKenzie, L.E., Morash-Conway, J., Glover, J.M., Aylott, A., Propper, L., Abidi, S., Bagnell, A., Pavlova, B., Hajek, T., Lovas, D., Pajer, K., Gardner, W., Levy, A., Alda, M., 2014. A familial risk enriched cohort as a platform for testing early interventions to prevent severe mental illness. BMC Psychiatry 14. https://doi. org/10.1186/s12888-014-0344-2.

Uher, R., Goodman, R., 2010. The everyday feeling questionnaire: the structure and validation of a measure of general psychological well-being and distress. Soc. Psychiatry Psychiatr. Epidemiol. 45, 413–423. https://doi.org/10.1007/s00127-009-0074-9. van Sluijs, E.M.F., McMinn, A.M., Griffin, S.J., 2007. Effectiveness of interventions to promote physical activity in children and adolescents: systematic review of controlled trials. BMJ 335, 703. https://doi.org/10.1136/bmj.39320.843947.BE. Vancampfort, D., Firth, J., Schuch, F.B., Rosenbaum, S., Mugisha, J., Hallgren, M., Probst, M., Ward, P.B., Gaughran, F., De Hert, M., Carvalho, A.F., Stubbs, B., 2017. Sedentary behavior and physical activity levels in people with schizophrenia, bipolar disorder and major depressive disorder: a global systematic review and meta-analysis. World Psychiatry 16, 308–315. https://doi.org/10.1002/wps.20458. Williams, S.L., French, D.P., 2011. What are the most effective intervention techniques for changing physical activity self-efficacy and physical activity behaviour–and are they the same? Health Educ. Res. 26, 308–322. https://doi.org/10.1093/her/cyr005. Woods, H.C., Scott, H., 2016. #Sleepyteens: social media use in adolescence is associated with poor sleep quality, anxiety, depression and low self-esteem. J. Adolesc. 51, 41–49. https://doi.org/10.1016/j.adolescence.2016.05.008. Xu, H., Wen, L.M., Rissel, C., 2015. Associations of parental influences with physical activity and screen time among young children: a systematic review. J. Obes. 2015, 1–23. https://doi.org/10.1155/2015/546925. Zecevic, C.A., Tremblay, L., Lovsin, T., Michel, L., 2010. Parental influence on young children’s physical activity. Int. J. Pediatr 2010, 1–9. https://doi.org/10.1155/2010/ 468526.

6