Adolescent mental health problems are an ongoing public health concern, with approximately 10% to 20% of children and adolescents experiencing a mental health problem of some type.1 Poor mental health among adolescents has been associated with poor academic achievements, low school attendance, cognitive disturbances, lack of motivation, and suicide, many manifestations which are likely to persist into adulthood.1,2 Almost 50% of all adolescent mental health and behavioral problems start by the age of 14 years, with depression and anxiety as the most prevalent.3 Along with psychological effects, depression and anxiety are commonly associated with decreased physical health and quality of life in young people, as well as increased risks of behavioral problems (eg, aggression, misconduct) and unhealthy behaviors (eg, disturbed eating and sleeping, substance abuse).1,4
A systematic review has suggested a number of plausible mechanisms, including neurobiological, psychological, and behavioral factors, that explain how physical activity (PA) can promote mental health and well-being in young people.5 For example, participating in PA may stimulate neurochemicals (eg, brain-derived neurotrophic factor, insulin-like growth factor 1, and vascular endothelial growth factor), which facilitate the downstream effects of exercise on cognition and mental well-being.5 In addition, participation in PA may also influence physical self-perception within the appearance subdomain (eg, perceived attractiveness, body image) via a range of psychological mechanisms of well-being.5 Moreover, participation in PA can provide an opportunity for the development of self-regulation and coping skills, which may influence positive mental health outcomes.5
Recent evidence has shown that insufficient PA and prolonged screen time are both negatively associated with adolescent mental well-being.6 There is evidence to suggest that high levels of screen time and sedentary behaviors are associated with obesity, a reduction in metabolic rate, anxiety, depressive symptoms, and quality of life.7 Systematic reviews have noted positive effects of PA interventions on mental well-being in adolescents.8,9 Most interventions from these reviews identified that adolescents who were more physically active and spent less time on screen-based activities and sedentary behaviors reported better mental health outcomes.8,9
Schools are an effective setting to reach young people for the delivery of PA interventions.10 Several school-based interventions have combined PA with other components, such as health education, and shown promising effects on adolescent mental health and well-being.9 Meta-analysis has demonstrated significant positive effects of PA interventions in reducing psychosocial outcomes (eg, depression, anxiety) in adolescents with varying effect sizes from small to medium.11,12 For example, there appear to be small-to-medium effects of PA interventions on internalizing (eg, anxiety, self-esteem) and externalizing (eg, aggressive) behaviors,11 and small but significant effects on depression.12 However, the effects of PA intervention on mental health may depend on a variety of contextual factors, such as type, delivery, domain, and physical and social environments of PA.13 For example, group activities (eg, team sport) were more strongly linked to less depressive symptoms in young people than individual activities (eg, swimming). PA undertaken with others may enhance the effects of other contextual factors (eg, PA in outdoor natural environments can lead to larger improvements in mental health).13
Moreover, it has been suggested that shorter PA interventions (ie, less than 3 mo) that included health education have contributed to greater declines in mental health problems of adolescents.11,12 For example, multicomponent interventions that included PA with other features, such as nutritional education, can improve adolescents’ psychological well-being,9 while school-based interventions to promote PA are effective in improving the mental well-being of adolescents.14 Furthermore, school-based interventions that are integrated into the school curriculum may alleviate common participation barriers, such as time and cost, for the prevention of depression.15
Studies on effectiveness of school-based PA interventions are predominantly conducted in high-income countries.14 Hence, there is scarce information about the effectiveness of school-based PA interventions in low- and middle-income countries,16 including Bangladesh, which is undergoing rapid socioeconomic growth, increasing urbanization, and modernization, resulting in lifestyle changes, including increases in sedentariness. A systematic review reported the prevalence of mental disorders ranged from 13.4% to 22.9% among Bangladeshi children aged 2–16 years,17 while a cross-sectional study of urban adolescents reported that 25% experienced depressive symptoms, with a prevalence of 17% in children aged 13 years and 37% in children aged 16 years.18 Although mental disorders are prevalent among adolescents in Bangladesh,18,19 no studies have yet looked at strategies to improve mental health conditions of this pediatric population. The purpose of this study was to evaluate the effectiveness of a school-based, multicomponent PA intervention on mental health of adolescents in Bangladesh. We hypothesized that the school-based PA intervention would improve the mental health of adolescents in Bangladesh.
Methods
Data for this study were from a cluster-randomized controlled trial, conducted in high school settings in Dhaka, the capital of Bangladesh, with schools as clusters. Design and reporting were guided by CONSORT reporting guidelines for nonpharmacological cluster-randomized controlled trials,20 TIDieR,21 and the GUIDED checklist.22 A number of schools were approached based on personal relationship with the research team, location or accessibility where the number of students at each school varied from 150 to 200 in grades 8 and 9. Schools were selected as per the inclusion criteria: (1) public or private high schools, (2) located in the urban area of Dhaka City, and (3) had (≥40) students in years 8 and 9. For this trial, sample size calculation was based on a previous study that demonstrated the effectiveness of an intervention with an increase of 10 minutes per day of moderate PA.23 A minimum of 36 students per cluster (ie, school) was required to achieve 80% power to detect a difference of 10 minutes per day of moderate PA between the group means at a 5% level of significance; the SD was 31.98 minutes per day and the intracluster correlation was assumed as .03. Considering an attrition of 10%, we would require a minimum of 40 students per cluster or school from grades 8 and 9. Of the 13 schools purposively invited to take part in the trial, 11 accepted the invitation, and 8 were randomly allocated to either intervention or control (4 schools per group). The intervention was offered to all 8th and 9th grade students at the intervention schools. For a school with more than 40 students in grades 8 and 9, there were 40 students randomly selected for the assessments; hence, a total of 320 students (160 per group) were included in the data analysis (see Supplementary Figure S1 [available online]). To improve students’ engagement, a variety of strategies were implemented, including: using physical education (PE) classes to create a supportive environment to deliver the intervention; making the circuit activities fun, such as having interactive health education discussions to facilitate collaborative learning; offering group activities to identify unhealthy behaviors relevant to them; and providing opportunities to participate in sports activities of their choice during lunchtime.
A 12-week, multicomponent PA intervention was developed based on the World Health Organization’s Health-Promoting Schools framework.24 Prior to the intervention, formative research (preintervention) was conducted using 4 focus-group discussions (FGDs) with 32 students (2 FGDs with 16 boys, 2 FGDs with 16 girls) from the participating intervention schools, to understand their perceptions and preferences of PA and sports to inform the intervention components.25 The intervention included 3 voluntary components offered by the research team once a week for 12 weeks. The first component consisted of a health education lesson for 10 minutes, followed by a 30-minute supervised circuit session delivered in the PE classes. The PE classes were chosen with the aim that, if effective, the intervention can be embedded in the existing national curriculum without any additional adjustment. Participants in the intervention group took part in different sets of circuit activities, changed every fortnight (see Supplementary Table S1 [available online]); however, the intervention was not designed to increase the difficulty level of PA over time. The second component was 20 minutes of monitored lunchtime outdoor activities of their choice using sports equipment, supplied through an activity bin (ie, a large container with playing materials including soccer balls, cricket bat and balls, skipping ropes, badminton). The study used observational data on sports participation, collected by the lead author during the intervention period. All students in the intervention group took part in outdoor sports activities of their choice; however, there were gender differences in their participation. Boys participated in playing football and cricket, while girls took part in skipping and running. The third component was health promotion materials (eg, infographics) distributed to the students to take home for their parents and other family members to promote an active lifestyle. The infographics included information on benefits of PA, recommended PA levels, healthy eating, and the health effects of screen-based behaviors, including their consequences. At the end of the intervention, data were collected to conduct a process evaluation with an aim to assess acceptability of the intervention among the participants. A manuscript on the process evaluation is currently in progress.
Assessments were conducted at baseline and postintervention (after completing the 12-wk intervention) on school sites during school days. Ethical approval was obtained from the human research ethics committee of The University of Queensland, Australia (2018000885), and the Bangladesh University of Health Sciences (BUHS/BIO/EA/18/12). Written informed parental consent and student’s assent were obtained from all those who participated in this trial. Details of the trial, including delivery of the intervention, can be found elsewhere.26
Outcome Measures
Depressive symptoms were measured using the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10).18 The CESD-10 has been shown to be an acceptable self-reporting tool to screen depression in adolescents in the community and nonclinical settings.27 Items ask how often respondents have experienced each of 10 symptoms during the past week (eg, felt depressed, felt lonely, felt fearful, felt that everything was an effort, etc), using a 4-point Likert scale for responses with 0 indicating “rarely or none of the time” and 3 indicating “most or all the time.” The internal consistency, measured by Cronbach alpha coefficient, for CESD-10 in this study was .84. A total score for each adolescent was obtained by summing the scores across 10 graded items with an admissible range of 0 to 30, a higher score indicating more depressive symptoms.28 Life satisfaction was assessed using a single item, the Cantril Ladder, which has demonstrated reliability and convergent validity in adolescents.29 Participants responded on a visual analogous scale ranging from the worst possible life (0 point) to the best possible life (10 points).
Covariates
The modified version of the International Physical Activity Questionnaire for Adolescents, which has been validated in Asian adolescents,30 was used to assess habitual levels of PA in 4 domains: (1) school-related PA including activity during PE classes and breaks, (2) transportation, (3) housework and gardening, and (4) leisure-time activity.31 PA data were converted into average metabolic equivalent tasks (METs, in MET-minutes per week), as per the International Physical Activity Questionnaire guidelines with the MET score of 3.3 for walking, 4.0 for moderate activity, and 8.0 for vigorous activity.31 To calculate daily PA levels, the number of minutes reported in each activity was multiplied by the specific MET score for that activity. The total amount of PA was quantified by summing all MET values for each domain of PA.
The Adolescent Sedentary Activity Questionnaire, which has satisfactory test–retest reliability,32 was used to assess recreational screen time. Participants were asked to report time (hours and minutes) spent on (1) a usual school day and (2) a usual weekend day for each of the following activities: (1) watching television, (2) watching DVDs/videos, (3) using the computer for fun, and (4) using social media (eg, Facebook, Twitter). Recreational screen time (ST) for a usual school day and a usual weekend day were computed by summing the time spent across the 4 screen-based activities.
Weight and height were measured to the nearest 0.1 kg and 0.1 cm on a portable digital scale and a portable stadiometer, respectively (Seca Instruments Ltd). We calculated body mass index (BMI), derived age- and sex-specific height and BMI z scores, using Centers for Disease Control and Prevention growth charts as underweight (BMI < 5th percentile), ideal weight (BMI ≥5th to <85th percentile), overweight (BMI ≥85th to <95th percentile), or obese (BMI ≥ 95th percentile).33
The students completed a self-administered questionnaire with items to assess their age, sex, grade, school, and family-level data (eg, parental education, family income data provided by parents). Participants were also asked to report time spent sleeping on (1) a usual school day and (2) a usual weekend day, to determine their sleep duration.
Statistical Analysis
Given the nested structure of the outcome data, we used multilevel, mixed-effects modeling to evaluate the effectiveness of the intervention in enhancing mental health indicators. Interaction effects (group × timepoint) were examined to determine whether the intervention group compared with the control group had differential effects on the changes in the outcome variables over time. Analyses were conducted under the intention-to-treat approach. Before employing mixed-effects modeling, collinearity of the explanatory variables was examined. Fathers’ education was excluded from any further analyses due to their considerable association with mothers’ education. All models were adjusted for age, sex, BMI z score, mothers’ education, income, sleep duration, PA, and screen time measured at baseline. Outliers and other assumptions of the models were checked, and the model fit was assessed before finalizing the models. Given the baseline differences in the outcome measures, sensitivity analyses were conducted using baseline outcome as a covariate to examine whether the baseline differences could affect the results. The association estimates are presented in the form of regression coefficients and their 95% confidence intervals (CIs). All analyses are conducted using Stata/SE (version 17).
Results
A total of 160 students from each of the 2 groups participated in the trial (n = 320) with the average age being 14.4 (SD 1.15) years (64% boys) in the intervention group and 14.2 (SD 0.89) years (52% boys) in the control group (see Supplementary Tables S2 and S3 [available online] for details). All participants completed the trial with no loss to follow-up. Figure 1 presents the average score of depressive symptoms and life satisfaction across 2 groups at baseline and postintervention (endline). Averages of depressive symptoms in the intervention groups decreased about 41% at postintervention, while remained stable in the control group. At postintervention, there was a 24% increase in average life satisfaction in the intervention group, while there was a 3.3% decrease in the control group. None of the group × timepoint interactions were significant, which supported the across-group comparison over time. Mixed-effects modeling, adjusted for the set of covariates, showed that the intervention was effective in significantly decreasing the depressive symptoms (adjusted β = −4.60; 95% CI, −5.76 to −3.46) in the intervention group compared with the control group (Table 1). The modeling also showed that total PA was not associated with depressive symptoms, while total ST was positively associated with depressive symptoms. The intervention was also effective in significantly increasing life satisfaction (adjusted β = 1.43; 95% CI, 0.77 to 2.10) when total PA was positively and total ST was inversely associated with life satisfaction. Considering the baseline outcome data as a covariate, sensitivity analyses showed that the intervention demonstrated a significant decrease in depressive symptoms (adjusted β = −6.46; 95% CI, −9.12 to −3.80) and a significant increase in life satisfaction (adjusted β = 2.30; 95% CI, 1.71 to 2.89) in the intervention group at the postintervention.
—Average of depressive symptoms (CESD total) and life satisfaction across intervention and control groups over a period of 12 weeks. CESD indicates Center for Epidemiologic Studies Depression Scale.
Citation: Journal of Physical Activity and Health 20, 12; 10.1123/jpah.2023-0062
—Average of depressive symptoms (CESD total) and life satisfaction across intervention and control groups over a period of 12 weeks. CESD indicates Center for Epidemiologic Studies Depression Scale.
Citation: Journal of Physical Activity and Health 20, 12; 10.1123/jpah.2023-0062
—Average of depressive symptoms (CESD total) and life satisfaction across intervention and control groups over a period of 12 weeks. CESD indicates Center for Epidemiologic Studies Depression Scale.
Citation: Journal of Physical Activity and Health 20, 12; 10.1123/jpah.2023-0062
Evaluation of Effectiveness of a School-Based Physical Activity Intervention on Mental Health Indicators, Using Mixed-Effects Modelinga
| Model | Intervention vs control | β (95% CI) | P |
|---|---|---|---|
| Depressive symptoms (range 0–30) as outcome | |||
| Model 1a (main analysis) | Intervention group (control as reference) | −4.61 (−5.76 to −3.46) | <.001 |
| Model 2a (sensitivity analysis) | Intervention group (control as reference) | −6.27 (−9.25 to −3.30) | <.001 |
| Life satisfaction (range 0–10) as outcome | |||
| Model 1b (main analysis) | Intervention group (control as reference) | 1.43 (0.77 to 2.10) | <.001 |
| Model 2b (sensitivity analysis) | Intervention group (control as reference) | 2.30 (1.62 to 2.99) | <.001 |
Abbreviations: BMI, body mass index; CI, confidence interval; MET, metabolic equivalent task. Note: Model 1—main analysis considering both baseline and endline measures as outcomes. Model 2—sensitivity analysis considering postintervention as outcome and baseline as a covariate.
aAdjusted for age, gender, mother’s education, family income, BMI z scores, physical activity (MET per minute), screen time, and sleep duration.
Discussion
This is the first study of its kind in Bangladesh to assess the effectiveness of a school-based, multicomponent PA intervention to promote adolescent mental health. Our findings showed that there was a 41% decrease in depressive symptoms and 24% increase in life satisfaction in the intervention group, while both outcomes remained stable in the control group. Mixed-effects modeling showed that students in the intervention group had significantly lower levels of depressive symptoms and higher levels of life satisfaction compared with their counterparts in the control group. Our modeling also showed that high ST was detrimentally associated with both mental health outcomes, while PA was positively associated with life satisfaction. Moreover, the sensitivity analyses supported the positive effects of the intervention on both mental health outcomes in adolescents.
Our findings suggest that the school-based, multicomponent intervention that included PA components (eg, circuit exercises, sports), health education lessons (eg, healthy eating, consequences of sedentariness), and health promotion materials reduced the level of depression in adolescents in the intervention group, which remained stable in the control group. This is consistent with the findings of a review that multicomponent, school-based interventions are effective in the reduction of depressive symptoms in the intervention group compared with the control group among adolescents in India.34 The results are also in line with a longitudinal study suggesting that increased involvement in PA was a significant predicator of lower depression levels among adolescents.35 Furthermore, a meta-analysis noted supervised light- or moderate-intensity exercise activities as a useful treatment strategy for depression in adolescents aged 13–17 years.36 However, a more recent meta-analysis and systematic review reported that PA components (eg, type and intensity of PA) of school-based interventions slightly improved mental health outcomes in adolescents, although the overall effect was not significant.37 Our intervention consisted of multiple components, including in-class activities (eg, circuit exercises) and outdoor lunchtime activities (eg, sports of their choice), that might have provided adolescents in the intervention group with opportunities to interact with others, engaging with fellow students and school staff that could influence their positive well-being. Available evidence suggests that adolescents who regularly participate in PA (eg, indoor or outdoor activities) are more likely to form good interpersonal relationships with others, and to enhance their social adaptability, self-esteem, mood states, eating disorder symptoms, and good psychological regulation.38,39 Available evidence also suggests several potential mechanisms that have been postulated to explain how PA benefits mental health.5,40 According to Lubans et al,5 PA can offer opportunities for improvement in a variety of cognitive and mental health indicators, including mastery in the physical domain (eg, self-efficacy and perceived competence), improvements in appearance self-perceptions (eg, body image), and independence (eg, autonomy), all of which can result in improved mental well-being.5,40 In addition, PA can lead to improved quality and duration of sleep as well as enhanced coping and self-regulation skills that are crucial for mental health and well-being.5,40 Our current study demonstrated significant decreases in depressive symptoms in the intervention group compared with the control group when the level of PA increased marginally in the intervention group and remained steady in the control group. We also found a sharp decrease in ST in the intervention group compared with the control. Hence, our findings suggest that reducing ST can have positive effects on depressive symptoms, irrespective of PA levels.
The present study also showed a significant positive effect of the intervention on life satisfaction. The findings showed that adolescents in the intervention group were more satisfied with their life experience when they participated in the intervention compared with their counterparts in the control group. Several reviews also demonstrated that PA has beneficial effects for the improvement of positive mental well-being, including life satisfaction of adolescents.41–43 Available evidence also suggests that the more PA that a student engaged in, the higher level of life satisfaction they obtained,44 suggesting that participation in PA may be considered a good way to develop adolescents’ life satisfaction. Earlier studies also found that adolescents who engaged in more PA were likely to feel more energetic throughout the day, and in turn, felt more satisfied with their life.45,46 Moreover, a systematic review reported that adolescents may feel more socially connected and be exposed to more green space when they are more physically active than usual, which may promote positive perceptions of satisfaction with their life.47 As the level of PA has positive effects and the level of ST has negative effects on life satisfaction, targeting both the behaviors has the potential to increase life satisfaction of young people. This is particularly important given that only one in 5 adolescents in Bangladesh are meeting the current PA (20%) or ST (21%) guidelines.27
Strengths of the current study include the use of a cluster-randomized controlled trial design with a multicomponent approach, based on the World Health Organization’s Health-Promoting Schools framework. Another strength was the development of the intervention program that was informed by a systematic review on successful components of PA promotion in the Asian context48 and formative preintervention FGDs on preferred sports activities.26 Our intervention was implemented in the PE classes within the school curriculum, which could be a key factor for scaling up the intervention at the national level. However, this study has some limitations. While it would have been ideal to combine all the secondary outcomes of the trial into a single paper, we chose to present them separately to provide specific insights that would engage relevant stakeholders. This could be a limitation of the current paper; however, presenting the secondary outcomes separately was deemed crucial given the limited intervention research of this area within the developing world context. PA, screen time, depressive symptoms, and life-satisfaction data were subjectively measured using self-report instruments, which may involve biases including recall bias. Furthermore, all participants were from public and semipublic schools in urban settings, which may not represent other schools in semiurban or rural settings in Bangladesh. PE classes are offered once or twice a week for each grade, depending on school curriculum in Bangladesh. Thus, running the intervention in PE classes may affect the other activities designed for those PE classes; as such, instead of embedding the intervention in the existing PE classes, the intervention can be offered through supplementary PE classes to optimize mental health benefits of school children.
Conclusion
Our study provides compelling evidence of the effectiveness of school-based, multicomponent PA intervention in reducing depressive symptoms and increasing life satisfaction among adolescents in urban settings in Bangladesh. These results highlight the potential of such an intervention in school settings to promote mental well-being among adolescents. Future trials should be scaled up to include schools in rural and semiurban settings using robust measures of mental well-being and activity behaviors, before progressing to a large-scale effectiveness trial.
Acknowledgments
The authors would like to thank the schools that participated in the study, as well as students and parents for their involvement. We also acknowledge the contribution of student volunteers in this study. Special thanks go to Dr Tracy Kolbe-Alexander of the University of Southern Queensland for her input in designing the study. The trial was registered with the Australian New Zealand Clinical Trials Registry (ACTRN12619000091101). This study did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
References
- 1.↑
Schulte-Körne G. Mental health problems in a school setting in children and adolescents. Dtsch Arztebl Int. 2016;(*)(11):183–190. doi:10.3238/arztebl.2016.0183
- 2.↑
Wickersham A, Sugg HVR, Epstein S, Stewart R, Ford T, Downs J. Systematic review and meta-analysis: the association between child and adolescent depression and later educational attainment. J Am Acad Child Adolesc Psychiatry. 2021;(*)(1):105–118. doi:10.1016/j.jaac.2020.10.008
- 3.↑
Klasen H, Crombag A-C. What works where? A systematic review of child and adolescent mental health interventions for low and middle income countries. Soc Psychiatry Psychiatr Epidemiol. 2013;(*)(4):595–611. doi:10.1007/s00127-012-0566-x
- 4.↑
Thapar A, Collishaw S, Pine DS, Thapar AK. Depression in adolescence. Lancet. 2012;(*)(9820):1056–1067. doi:10.1016/S0140-6736(11)60871-4
- 5.↑
Lubans D, Richards J, Hillman C, et al. Physical activity for cognitive and mental health in youth: a systematic review of mechanisms. Pediatrics. 2016;(*)(3):1642. doi:10.1542/peds.2016-1642
- 6.↑
Khan A, Lee EY, Rosenbaum S, Khan SR, Tremblay MS. Dose-dependent and joint associations between screen time, physical activity, and mental wellbeing in adolescents: an international observational study. Lancet Child Adolesc Health. 2021;(*)(10):729–738. doi:10.1016/S2352-4642(21)00200-5
- 7.↑
Stiglic N, Viner RM. Effects of screentime on the health and well-being of children and adolescents: a systematic review of reviews. BMJ Open. 2019;(*)(1):e023191. doi:10.1136/bmjopen-2018-023191
- 8.↑
Andermo S, Hallgren M, Nguyen TTD, et al. School-related physical activity interventions and mental health among children: a systematic review and meta-analysis. Sports Med—Open. 2020;(*)(1):25. doi:10.1186/s40798-020-00254-x
- 9.↑
Hale GE, Colquhoun L, Lancastle D, Lewis N, Tyson PJ. Review: physical activity interventions for the mental health and well-being of adolescents—a systematic review. Child Adolesc Ment Health. 2021;(*)(4):357–368. doi:10.1111/camh.12485
- 10.↑
Hills AP, Dengel DR, Lubans DR. Supporting public health priorities: recommendations for physical education and physical activity promotion in schools. Prog Cardiovasc Dis. 2015;(*)(4):368–374. doi:10.1016/j.pcad.2014.09.010
- 11.↑
Spruit A, Assink M, van Vugt E, van der Put C, Stams GJ. The effects of physical activity interventions on psychosocial outcomes in adolescents: a meta-analytic review. Clin Psychol Rev. 2016;45:56–71. doi:10.1016/j.cpr.2016.03.006
- 12.↑
Brown HE, Pearson N, Braithwaite RE, Brown WJ, Biddle SJ. Physical activity interventions and depression in children and adolescents. Sports Med. 2013;(*)(3):195–206. doi:10.1007/s40279-012-0015-8
- 13.↑
Vella SA, Aidman E, Teychenne M, et al. Optimising the effects of physical activity on mental health and wellbeing: a joint consensus statement from Sports Medicine Australia and the Australian Psychological Society. J Sci Med Sport. 2023;(*)(2):132–139. doi:10.1016/j.jsams.2023.01.001
- 14.↑
Amudhan S, Jangam K, Mani K, et al. Project SUMS (scaling up of mental health in schools): design and methods for a pragmatic, cluster randomised waitlist-controlled trial on integrated school mental health intervention for adolescents. BMC Public Health. 2021;(*)(1):2034. doi:10.1186/s12889-021-12086-9
- 15.↑
Werner-Seidler A, Perry Y, Calear AL, Newby JM, Christensen H. School-based depression and anxiety prevention programs for young people: a systematic review and meta-analysis. Clin Psychol Rev. 2017;51:30–47. doi:10.1016/j.cpr.2016.10.005
- 16.↑
van Sluijs EMF, Ekelund U, Crochemore-Silva I, et al. Physical activity behaviours in adolescence: current evidence and opportunities for intervention. Lancet. 2021;(*)(10298):429–442. doi:10.1016/S0140-6736(21)01259-9
- 17.↑
Hossain MD, Ahmed HU, Chowdhury WA, Niessen LW, Alam DS. Mental disorders in Bangladesh: a systematic review. BMC Psychiatry. 2014;(*)(1):216. doi:10.1186/s12888-014-0216-9.
- 18.↑
Khan A, Ahmed R, Burton NW. Prevalence and correlates of depressive symptoms in secondary school children in Dhaka city, Bangladesh. Ethn Health. 2020;(*)(1):34–46. doi:10.1080/13557858.2017.1398313
- 19.↑
Anjum A, Hossain S, Hasan MT, Uddin ME, Sikder MT. Anxiety among urban, semi-urban and rural school adolescents in Dhaka, Bangladesh: investigating prevalence and associated factors. PLoS One. 2022;(*)(1):e0262716. doi:10.1371/journal.pone.0262716.
- 20.↑
Moher D, Hopewell S, Schulz KF, et al. CONSORT 2010 explanation and elaboration: updated guidelines for reporting parallel group randomised trials. BMJ. 2010;340:c869. doi:10.1136/bmj.c869
- 21.↑
Hoffmann TC, Glasziou PP, Boutron I, et al. Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide. BMJ. 2014;348:g1687. doi:10.1136/bmj.g1687
- 22.↑
Duncan E, O’Cathain A, Rousseau N, et al. Guidance for reporting intervention development studies in health research (GUIDED): an evidence-based consensus study. BMJ Open. 2020;(*)(4):e033516. doi:10.1136/bmjopen-2019-033516
- 23.↑
Harrington DM, Davies MJ, Bodicoat DH, et al. Effectiveness of the ‘Girls Active’ school-based physical activity programme: a cluster randomised controlled trial. Int J Behav Nutr Phys Act. 2018;(*)(1):40. doi:10.1186/s12966-018-0664-6
- 24.↑
Langford R, Bonell C, Jones H, et al. The World Health Organization’s health promoting schools framework: a Cochrane systematic review and meta-analysis. BMC Public Health. 2015;(*)(1):1360. doi:10.1186/s12889-015-1360-y
- 25.↑
Khan A, Ahmed KR, Hidajat T, Edwards EJ. Examining the association between sports participation and mental health of adolescents. Int J Environ Res Public Health. 2022;(*)(24):17078. doi:10.3390/ijerph192417078
- 26.↑
Ahmed KR, Kolbe-Alexander T, Khan A. Effectiveness of a school-based intervention on physical activity and screen time among adolescents. J Sci Med Sport. 2022;25(3):242–248. doi:10.1016/j.jsams.2021.10.007
- 27.↑
Bradley KL, Bagnell AL, Brannen CL. Factorial validity of the center for epidemiological studies depression 10 in adolescents. Issues Ment Health Nurs. 2010;(*)(6):408–412. doi:10.3109/01612840903484105
- 28.↑
Radloff LS. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas. 1977;(*)(3):385–401. doi:10.1177/014662167700100306
- 29.↑
Levin K, Currie C. Reliability and validity of an adapted version of the Cantril ladder for use with adolescent samples. Soc Indic Res. 2014;(*)(2):1047–1063. doi:10.1007/s11205-013-0507-4
- 30.↑
Choi SM, Sum RKW, Leung EFL, Ng RSK. Relationship between perceived physical literacy and physical activity levels among Hong Kong adolescents. PLoS One. 2018;(*)(8):e0203105. doi:10.1371/journal.pone.0203105
- 31.↑
Hagströmer M, Bergman P, De Bourdeaudhuij I, et al. Concurrent validity of a modified version of the International Physical Activity Questionnaire (IPAQ-A) in European adolescents: The HELENA Study. Int J Obes. 2008;(*)(S5):S42–S8. doi:10.1038/ijo.2008.182
- 32.↑
Hardy LL, Booth ML, Okely AD. The reliability of the adolescent sedentary activity questionnaire (ASAQ). Prev Med. 2007;(*)(1):71–74. doi:10.1016/j.ypmed.2007.03.014
- 33.↑
Ogden CL, Flegal KM. Changes in terminology for childhood overweight and obesity. Age. 2010;25;1–5. PubMed ID: 20939253
- 34.↑
Mehra D, Lakiang T, Kathuria N, Kumar M, Mehra S, Sharma S. Mental health interventions among adolescents in India: a scoping review. Healthcare. 2022;(*)(2):337. doi:10.3390/healthcare10020337
- 35.↑
Jewett R, Sabiston CM, Brunet J, O’Loughlin EK, Scarapicchia T, O’Loughlin J. School sport participation during adolescence and mental health in early adulthood. J Adolesc Health. 2014;(*)(5):640–644. doi:10.1016/j.jadohealth.2014.04.018
- 36.↑
Carter T, Morres ID, Meade O, Callaghan P. The effect of exercise on depressive symptoms in adolescents: a systematic review and meta-analysis. J Am Acad Child Adolesc Psychiatry. 2016;(*)(7):580–590. doi:10.1016/j.jaac.2016.04.016
- 37.↑
Neill RD, Lloyd K, Best P, Tully MA. The effects of interventions with physical activity components on adolescent mental health: systematic review and meta-analysis. Ment Health Phys Act. 2020;19;359. doi:10.1016/j.mhpa.2020.100359
- 38.↑
Gu J. Physical activity and depression in adolescents: evidence from china family panel studies. Behav Sci. 2022;(*)(3):71. doi:10.3390/bs12030071
- 39.↑
Carney R, Firth J. Exercise interventions in child and adolescent mental health care: an overview of the evidence and recommendations for implementation. JCPP Adv. 2021;(*)(4):e12031. doi:10.1002/jcv2.12031
- 40.↑
Khan A, Burton NW. 10 Physical activity as recovery resource for mental health in young people. In: Kellmann M, Jakowski S, Beckmann J, eds. The Importance of Recovery for Physical and Mental Health: Negotiating the Effects of Underrecovery. Routledge; 2023:154–171.
- 41.↑
Janssen I, LeBlanc AG. Systematic review of the health benefits of physical activity and fitness in school-aged children and youth. Int J Behav Nutr Phys Act. 2010;(*)(1):40. doi:10.1186/1479-5868-7-40
- 42.
Biddle SJH, Asare M. Physical activity and mental health in children and adolescents: a review of reviews. Br J Sports Med. 2011;(*)(11):886–895. doi:10.1136/bjsports-2011-090185
- 43.↑
Lachytova M, Katreniakova Z, Mikula P, Jendrichovsky M, Nagyova I. Associations between self-rated health, mental health problems and physical inactivity among urban adolescents. Eur J Public Health. 2017;(*)(6):984–989. doi:10.1093/eurpub/ckx051
- 44.↑
Chen S, HO WKY, Ahmed MD. Physical activity and its relationship with life satisfaction among middle school students: a cross-culture study. Sustainability. 2020;(*)(17):6932. doi:10.3390/su12176932
- 45.↑
Pierannunzio D, Spinelli A, Berchialla P, et al. Physical activity among italian adolescents: association with life satisfaction, self-rated health and peer relationships. Int J Environ Res Public Health. 2022;(*)(8):4799. doi:10.3390/ijerph19084799
- 46.↑
Urchaga JD, Guevara RM, Cabaco AS, Moral-García JE. Life satisfaction, physical activity and quality of life associated with the health of school-age adolescents. Sustainability. 2020;(*)(22):9486. doi:10.3390/su12229486
- 47.↑
Vanaken GJ, Danckaerts M. Impact of green space exposure on children’s and adolescents’ mental health: a systematic review. Int J Environ Res Public Health. 2018;(*)(12):668. doi:10.3390/ijerph15122668
- 48.↑
Ahmed KR, Uddin R, Kolbe-Alexander TL, Khan A. The effectiveness of physical activity interventions in Asian children and adolescents: a systematic review. Public Health. 2021;194:48–59. doi:10.1016/j.puhe.2021.02.011
