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Table 2 Longitudinal and intervention findings

From: The associations between sedentary behaviour and mental health among adolescents: a systematic review

Author, Year, Country of study

Sample characteristics

Study design

Mental health measure

Sedentary behaviour measure

Findings

Quality of evidencea

Longitudinal

Bickham et al. (2015) [14]

United States

Total: 126 young Americans

Mean age at baseline:14.0y (SD: not reported) 46.8 % female

1 year follow-up

Baseline: 2009

Depressive symptoms: Beck Depression Inventory

Electronic media use: participants were asked to report the typical amount of time on school days and weekends that they used electronic media including TV, video games, computers, mobile phones and music. Calculated a daily average.

Also calculated using time use diaries.

Significant positive association between mobile phone use and depression.

Longitudinal analyses found that more TV use (b:0.205, p < 0.05)and phone use (b:0.177, p < 0.10) reported at baseline the higher participants’ depression score was at the 1-year follow-up.

Moderate

Hume et al. (2011) [55]

Australia

Total: 155 Australian adolescents

Mean age: females 14.4y (SD: 0.64y), males 14.4y (SD: 0.57y) 60 % female

2 year follow-up

Baseline: 2004

Depressive symptoms: Centres for Epidemiological Studies Depression Scale for Children

Cut point with depressive symptoms: ≥15

Times spent sedentary: accelerometer worn during waking hours for 1 week at the same time of year in 2004 and in 2006

Screen time: self-reported usual TV/video/DVD viewing during a typical week on weekends and weekend days, total was summed to indicate total TV viewing time (min/week)

Females with depressive symptoms in 2004 watched approximately 168 mins/week more TV in 2006 than did those without depressive symptoms.

No other relationships were significant.

Models accounted for school participants attended.

Strong

Nelson & Gordon-Larsen (2006) [15]

United States

Total: 11,957 American adolescents in grades 7–12

Mean age: 15.8y (SD:11.6y) 50 % female

1 year follow-up

Baseline: 1994–1995

Self-esteem: Rosenberg Self-esteem Scale

Screen time: adolescents reported watching/playing TV/videos, video or computer games in hours/week.

Adolescents group into clusters and compared to those watching most screen time (sedentary compared to active young people). Active teens were less likely to have low self-esteem.

Moderate

Primack et al. (2009) [16]

United States

4142 adolescents in grade 7 through 12

Mean age at follow-up: 21.8y (1.8y) 52.5 % female

7 year follow-up

Baseline: 1994

Depressive symptoms: Centres for Epidemiologic Studies-Depression Scale

Scores (0–27) summed and used as continuous where higher scores indicated greater severity of symptoms.

Screen time: participants asked to report hours of exposure during the last week to each of 4 types of electronic media: TV, videocassettes, computer games, and radio.

Each media type treated as continuous hours per day. Also summed to create overall hours per day.

Those reporting more TV use had significantly greater odds of developing depression (OR:1.08 95 % CI: 1.01-1.16, p < 0.05) for each additional hour of daily TV use.

Those reporting more total media exposure had greater odds of developing depression (OR:1.05 95 % CI: 1.0004–1.10, p < 0.05) for each additional hour of daily use.

Females were less likely than males to develop depression given the same total media exposure (OR for interaction term: 0.93 95 % CI: 0.88–0.99, p < 0.05)

Moderate

Romer et al. (2013) [17]

United States

Total: 719 American youth aged 14–24 years

Mean age and gender % not reported.

1 year follow-up

Baseline: 2008

Depressive symptoms: one item taken from the Youth Risk Behaviour Survey. Participants asked to indicate the number of times one had experienced ‘≥2 weeks of ‘sadness or hopelessness that interfered with daily activities in the past 12 months’ (once, twice, three times or more)

Screen time: time spent using internet and TV with items that asked for approximate number of hours spent on a typical weekday and weekend using each medium (<1 h, 1–2 h, 3–5 h, 6–8 h, or > 8 h). Converted to a single estimate of weekly use.

Video game use assessed with single item asking for time spent on a typical day.

Internet and video game use were associated with increased reports of depression,

Controlling for past symptoms and media use, recent depression was associated with greater Internet use, (B:0.119 SE:0.058, p < 0.05) and video game playing (B:0.144 SE:0.044, p = 0.001).

Moderate

Sund et al. (2011) [53]

Norway

Total: 2,464 Norwegian adolescents 12–15 years

Mean age at baseline: 13.7y (0.58y) 50.5 % female

1 year follow-up

Baseline: 1998

Depressive symptoms: Mood and Feelings Questionnaire total summed score used 0 to 68 where higher scores represent greater severity of symptoms.

Sedentary behaviour: time spent on sedentary activities everyday outside school (e.g., homework, reading, watching TV, games) were assessed in four response categories ranging from ‘less than three hours’ to ‘more than six hours’.

High levels of sedentary activities predicted high depressive symptoms (≥25 score) at follow-up (OR:1.22 95 % CI: 1.02–1.47, p < 0.05).

A significant sex by sedentary activities interaction effect was found in that sedentary activities was significant only for boys in predicting high scorers (OR:1.53 95 % CI: 1.15–2.03, p < 0.05).

Strong

Witt et al. (2011) [18]

United States

Total: 592 young Americans

Mean age at baseline: 12.2y (SD not reported) 53.6 % female

3-year follow-up.

Baseline: 2005

Self-esteem: Rosenberg Self-Esteem scale

Technology frequency of use: participants asked to report their frequency of technology use for a number of items (never, sometimes, often, very often) for video games, general computer use, and communication.

Self-esteem was negatively associated with mean levels of videogame playing and positively associated with computer use.

Moderate

Intervention

Lubans et al. (2015) [54]

Australia

Total: 361 adolescent boys who reported failing to meet international guidelines regarding physical activity or recreational screen time.

Mean age: 12.7y (SD:0.5y)

Intervention: 181

Control (wait list for ATLAS program): 180

8 month follow-up

Baseline: 2012

Intervention design: 20-week school based obesity prevention intervention targeting health behaviours of low-income adolescent boys considered at risk of obesity.

Six intervention components, including; parental newsletter focused on limiting recreational screen time and interactive seminars addressing key behavioural messages.

Psychological well-being: measured by 8-item Flourishing Scale. Composite scores of flourishing represent a summary measure of a person’s self-perceived success in areas such as engagement, relationships, self-esteem, meaning, purpose, and optimism.

Screen-time: measured using a modified version of the Adolescent Sedentary Activity Questionnaire asking participants to report total time spent using screens (of any kind) for the purpose of entertainment, on each day of the week.

After adjusting for school and baseline values, the intervention effect on well-being was small but statistically significant (β: 0.10 SE:0.05, p = 0.023).

The intervention had a positive effect on screen time (β:-0.21 SE:0.06, p < 0.001).

In the multiple mediator model (including autonomy choice, screen time, muscular fitness, and RT skills competency) changes in screen time was significantly associated to changes in well-being (product of coefficients estimate: 0.038 95 % CI:0.007–0.080, p < 0.05.)

Strong

  1. β standardised beta coefficient; B unstandardized beta coefficient; CI confidence interval; F analysis of variance; OR odds ratio; SD standard deviation; SE standard error; y years
  2. a Quality of evidence based on assessment tool for quantitative studies [26] including selection bias, study design, confounders, blinding, data collection methods, withdrawals and drop outs, intervention integrity, and analysis. Strong quality of evidence = if three or more components scored strong. Moderate quality of evidence = if less than three components were strong with no more than one weak score. Weak quality of evidence = if two or more components scored weak