ABSTRACT 抽象
Many young people are exposed to risk factors that increase their risk of mental illness. Physical activity provision is an increasingly popular approach to protect against mental illness in the face of these risk factors. We examined the effectiveness of physical activity interventions for the promotion of mental health outcomes in at-risk children and adolescents. We searched health databases for randomised and non-randomised intervention studies, with no date restriction, and assessed risk of bias using the Cochrane Risk of Bias tools. We present a narrative synthesis of our results accompanied with a summary of available effect sizes. Thirty-seven reports on 36 studies were included, with multi-sport or yoga interventions the most popular intervention approaches (a combined 50% of included studies). Outcomes measured included internalising, self-evaluative, wellbeing, overall symptomatology, resilience, externalising, and trauma outcomes. We found that 63% of between-groups effects favoured the intervention arm, and 83% of within-groups effects favoured an intervention effect. While recognising high risk of bias, our findings provide evidence in support of the effectiveness of physical activity interventions for promoting mental health outcomes in at-risk young people. We encourage further work designed to better understand the intervention characteristics that may lead to positive benefits.
许多年轻人暴露于增加他们患精神疾病风险的风险因素中。面对这些风险因素，提供身体活动是一种越来越流行的预防精神疾病的方法。我们检查了体育活动干预对促进高危儿童和青少年心理健康结局的有效性。我们在健康数据库中检索了随机和非随机干预研究，没有日期限制，并使用Cochrane偏倚风险工具评估了偏倚风险。我们提出了结果的叙述性综合，并附有可用效应大小的摘要。纳入了 36 项研究的 37 份报告，其中多项运动或瑜伽干预是最受欢迎的干预方法（合计占纳入研究的 50%）。测量的结局包括内化、自我评价、幸福感、整体症状、恢复力、外化和创伤结局。我们发现 63% 的组间效应有利于干预组，83% 的组内效应有利于干预效应。虽然认识到存在高偏倚风险，但我们的研究结果提供了证据，支持体育活动干预对促进高危年轻人心理健康结果的有效性。我们鼓励进一步的工作，旨在更好地了解可能导致积极益处的干预特征。
Introduction 介绍
Mental illness is one of the leading global causes of disease burden (Vigo et al., Citation2016), with an estimated one billion people worldwide experiencing a mental illness (GBD Citation2017 Disease and Injury Incidence and Prevalence Collaborators, Citation2018). The negative impact of mental illness is evident at an individual- (e.g., lower personal income and living standards; Gibb et al., Citation2010; Kessler et al., Citation2008), relational- (e.g., feelings of isolation; Wang et al., Citation2017), and societal-level (e.g., economic cost; Doran & Kinchin, Citation2019). Subsequently, the prevention of mental illness is a key focus of contemporary health promotion research (Fusar-Poli et al., Citation2021). Childhood and adolescence have been identified as key windows of opportunity for mental illness prevention, given that a substantial proportion of lifetime cases of diagnosed mental illness begin in these periods (Kessler et al., Citation2005, Citation2007; Merikangas et al., Citation2010; Solmi et al., Citation2022). Additionally, potential intervention benefits extend beyond childhood and adolescence, across the lifespan and intergenerationally (Clark et al., Citation2020; Patton et al., Citation2016). In that vein, there is a well-established evidence base showcasing the importance of lifestyle interventions (e.g., physical activity, sleep) in preventing mental illness (see Firth et al., Citation2020, for a meta-review).
精神疾病是全球疾病负担的主要原因之一（Vigo et al.， 2016），全球估计有 10 亿人患有精神疾病（GBD 2017 疾病和伤害发生率和患病率合作者，2018 年）。精神疾病的负面影响在个人身上是显而易见的——（例如，较低的个人收入和生活水平;Gibb et al.， 2010;Kessler et al.， 2008）、关系 - （例如，孤立感;Wang et al.， 2017）和社会层面（例如，经济成本;Doran & Kinchin，2019）。随后，预防精神疾病是当代健康促进研究的重点（Fusar-Poli et al.， 2021）。儿童期和青少年期已被确定为预防精神疾病的关键机会窗口，因为一生中被诊断出的精神疾病病例中有很大一部分是从这些时期开始的（Kessler 等人，2005 年、2007 年;Merikangas et al.， 2010;Solmi et al.， 2022）。此外，潜在的干预益处超越了童年和青少年时期，贯穿了整个生命周期和代际（Clark et al.， 2020;Patton等人，2016 年）。在这方面，有一个完善的证据基础表明生活方式干预（例如，体育活动、睡眠）在预防精神疾病方面的重要性（参见 Firth 等人，2020 年，用于元审查）。
Children may be exposed to a host of individual, environmental, and/or sociocultural risk factors for mental illness (Kieling et al., Citation2011; Lund et al., Citation2018). Often, these risk factors are known collectively as adverse childhood experiences (ACEs). Examples of ACEs (see Finkelhor et al., Citation2013, for a comprehensive outline of adversities) include, but are not limited to: having a parent with a mental illness (Reupert & Maybery, Citation2016); having a sibling with a chronic health condition or disability (Vermaes et al., Citation2012); and exposure to domestic violence (Holt et al., Citation2008). Petruccelli et al. (Citation2019) provided meta-analytic evidence that, typically, the more ACEs one has, the higher the odds ratio associated with a negative outcome (e.g., psychological distress, depressed mood, panic/anxiety). In general, children and adolescents considered to be ‘at-risk’ of mental health concerns are those who have experienced adversity (including, for example, living in a family with limited socioeconomic resources), disruptive or traumatic life events, or maltreatment (Fryers & Brugha, Citation2013). Where the aetiology (and, if relevant, ACE) for mental illness is specific, known, and modifiable (e.g., bullying in schools), interventions that directly and systemically target that factor are desirable (i.e., developing an intervention to reduce bullying; Scott et al., Citation2014). In many cases, though, risk factors may not be specific, known, modifiable, or reliably measurable, and in those cases, researchers have focused more holistically on promoting protective factors that improve mental health outcomes or reduce the incidence of mental illness in at-risk populations (Wille et al., Citation2008).
儿童可能会暴露于许多个人、环境和/或社会文化风险因素中，导致精神疾病（Kieling 等人，2011 年;Lund等人，2018 年）。通常，这些风险因素统称为童年不良经历 （ACE）。ACEs的例子（参见Finkelhor等人，2013年，全面概述了逆境）包括但不限于：父母患有精神疾病（Reupert & Maybery），2016年）;有患有慢性健康状况或残疾的兄弟姐妹（Vermaes et al.， 2012）;以及暴露于家庭暴力（Holt et al.， 2008）。Petruccelli 等人（2019 年）提供了荟萃分析证据，通常，一个人拥有的 ACE 越多，与负面结果（例如，心理困扰、抑郁情绪、恐慌/焦虑）相关的比值比就越高。一般来说，被认为有心理健康问题风险的儿童和青少年是那些经历过逆境（例如，包括生活在社会经济资源有限的家庭中）、破坏性或创伤性生活事件或虐待的人（Fryers & Brugha，2013）。如果精神疾病的病因（以及 ACE，如果相关）是特异性的、已知的和可改变的（例如，校园霸凌），则直接和系统地针对该因素的干预措施是可取的（即，制定一种减少霸凌的干预措施;Scott et al.， 2014）。然而，在许多情况下，风险因素可能不是特异性的、已知的、可改变的或可靠的可衡量的，在这些情况下，研究人员更全面地专注于促进改善心理健康结果或降低高危人群精神疾病发病率的保护因素（Wille 等人，2008 年）。
Protective factors are mechanisms that may reduce the likelihood of, or protect against, experiencing undesirable outcomes (Shortt & Spence, Citation2006; Wille et al., Citation2008). In a seminal article, Rutter (Citation1987) emphasised that a defining feature of protective factors is that they are not merely the opposite of a risk factor but are catalytic in that they interact with risk variables to provide a protective (i.e., buffering) effect. For example, physical activity in and of itself is reported to have protective effects against depression and anxiety (Firth et al., Citation2020; Fusar-Poli et al., Citation2021). However, there may also be an opportunity within physical activity interventions to promote protective mechanisms (e.g., physical self-perceptions; see Lubans et al., Citation2016) to contribute positively to mental health and protect against mental ill health (in addition to the inherent benefits of physical activity).
Researchers and clinicians recognise that at-risk children and adolescents are often a challenging and resistant group (particularly in the context of ‘traditional’ therapy) and have outlined that approaching interventions of this nature in a more engaging manner may assist in fostering more positive outcomes (Kendall & Peterman, Citation2015; Sommers-Flanagan & Sommers-Flanagan, Citation2006). There is an emerging evidence base to show that alternative (i.e., outside of traditional clinical settings) intervention formats may improve mental health outcomes in at-risk children and adolescents. Such approaches include sport-based programmes (Lubans et al., Citation2012), interventions delivered through online settings (Clarke et al., Citation2015), animal-assisted programmes (Hoagwood et al., Citation2017), and art activities (Cohen-Yatziv & Regev, Citation2019), amongst others. Further investigation of these kinds of ‘alternative’ approaches is important, with the goal of generating a broader evidence base and more effective early intervention and prevention options for at-risk young people (Herati & Meyer, Citation2023; Lubans et al., Citation2012).
The psychological benefits (e.g., well-being, cognitive functioning) of physical activity and sport are well documented (see, for a brief historical account, Biddle & Vergeer, Citation2019). Additionally, physical activity is relatively (compared to other mental health treatments, e.g., pharmacotherapy) safe, inexpensive, and accessible, making it an attractive option for mental health preventative efforts (Ekkekakis, Citation2013). A number of biological, psychosocial, and behavioural mechanisms have been posited to explain the effects of physical activity and sport on mental health – these include the release of neurotransmitters (e.g., dopamine), self-perception, self-esteem, self-efficacy, affect regulation and social support (Craft, Citation2013; Di Liegro et al., Citation2019; Kandola et al., Citation2019; Lubans et al., Citation2016).
Review evidence for the effectiveness of physical activity interventions on mental health-related outcomes is well established (e.g., Singh et al., Citation2023) – however, the evidence for at-risk young people is comparatively sparse. In their review on this topic, Lubans et al. (Citation2012) identified that sport and physical activity programmes are potentially effective for improving social and emotional wellbeing in at-risk children and adolescents. However, they identified a lack of high-quality evidence and recommended more rigorous trials be conducted to determine the effectiveness of sport- and physical activity-based programmes more accurately. In other related work, Hermens et al. (Citation2017) synthesised research on sport-related life skills development programmes for vulnerable youth, providing evidence for the potential of sport programmes to have a positive impact on cognitive, emotional, and social life skills. And more recently, Rose and Soundy (Citation2020) conducted a review on physical activity for children and adolescents from low socioeconomic backgrounds (a group of children often considered at-risk due to factors such as limited access to resources or cumulative exposure to stressors; Peverill et al., Citation2021). Their review corroborated the association between moderate-to-vigorous physical activity and positive mental health and wellbeing outcomes in disadvantaged children and highlighted potential mechanisms of change.
Despite some evidence for the role of sport and physical activity on mental health-related outcomes for at-risk young people, gaps remain in our understanding of this research. In the time since Lubans et al.’s (Citation2012) review (which most closely aligns to the criteria of this review), for example, there has been no update to the review literature to scope more recent work and to identify potential improvements in evidence quality. And, although Hermens et al.'s (Citation2017) review was more recent and did include some (mental health-) relevant emotion-related outcomes (such as global self-worth), their focus was specifically on life skills – requiring studies to specifically report (in some capacity) on life skill development. This focus potentially excluded important research targeting other mental health and wellbeing indicators. Finally, despite the valuable evidence provided by Rose and Soundy’s (Citation2020) even more recent work, their review focused only on one subgroup of the broader ‘at-risk’ population (i.e., low socioeconomic status children and adolescents).
Developing a greater understanding of the effectiveness of physical activity interventions for young people at risk of mental health issues is critical for refining efforts to improve mental health outcomes in at-risk populations. This is particularly important given that ‘at-risk young people’ are often targeted as a broad population instead of specific subgroups that fall under the at-risk ‘banner’. Our systematic review focus was guided by the lack of up-to-date review evidence for the effectiveness of physical activity interventions on mental health outcomes in at-risk young people. We developed the review with one primary aim: to assess the effectiveness of physical activity interventions for mental health-related outcomes in at-risk young people, in relation to characteristics of the intervention (i.e., the target population, the intervention type, and the ‘risk factor’ for mental health concerns). With this aim in mind, two research questions guided our review: (1) are physical activity interventions effective in improving mental health outcomes in at-risk young people?; and (2) what characteristics of physical activity interventions for at-risk young people are most likely to lead to positive mental health outcomes?. In addressing these questions, this review will consolidate the literature and provide a foundation for researchers to focus on specific characteristics that may increase the likelihood of successful intervention.
Methods
This review is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement (Page et al., Citation2021). The protocol for this systematic review was registered on PROSPERO (CRD42022315464) and is included in Supplementary Material S1. There were three minor deviations to the protocol. First, we modified our research questions to focus on physical activity broadly, to avoid ambiguity on what constitutes ‘sport’ or ‘physical activity’ respectively. We also refocused our research questions to be more specific. In particular, our second research question (see above) was expanded on to include not only information about ‘study characteristics’, but ‘study characteristics which led to positive outcomes’. This was the focus of the research question from the commencement of the review, but our reporting lacked clarity prior to this post-hoc modification. Second, our risk of bias assessment methodology was modified to be more suitable to the review and the interventions we were assessing (i.e., the tool we had selected initially was later deemed to be inappropriate for assessing the risk of bias for individual studies). Finally, graphical reporting of effect sizes and quantitative ‘vote counting’ procedures were included to complement the narrative synthesis. This approach is suggested by McKenzie and Brennan (Citation2022) where meta-analytic procedures are not possible.
Eligibility criteria
Two reviewers (AS and BK) independently assessed the eligibility of studies according to the inclusion criteria. Studies were included if (a) participants were children or adolescents (mean age under 18 years) at increased risk of mental health issues (for any reason identified by the authors of the original research, and which fits within the broad classification of risk factors for mental health concerns explored above), (b) sport or physical activity was the primary focus of an intervention, and (c) outcomes relating to mental health (protective factors or symptomatology) were measured and reported. We included journal articles, theses, and conference abstracts that fit the above criteria. For clarity, we defined physical activity as a bodily movement that requires energy expenditure (and therefore, interventions which provided opportunities to be physically active were included). Study designs included in this review were randomised controlled trials (RCTs), non-randomised controlled trials (nRCTs), or feasibility or pilot trials. Studies were excluded if (a) participants had an identified previous or existing diagnosis of a mental illness, (b) the intervention was designed for a population other than children or adolescents (e.g., an intervention for mothers, where child mental health was measured), (c) physical activity was not the primary focus of the intervention, or (d) the intervention was designed to improve outcomes not directly related to psychological wellbeing or mental health (e.g., a sport intervention for academic performance in at-risk children). Qualitative studies and book chapters (to maintain search strategy optimisation) were also excluded.
Search strategy
The search strategy is reported in accordance with the PRISMA-S extension for Reporting Literature Searches in Systematic Reviews (Rethlefsen et al., Citation2021). We conducted a search of six electronic databases in January 2022, namely: MEDLINE, EMBASE, PsycINFO, CINAHL, SPORTDiscus, and Psychological and Behavioural Sciences Collection. MEDLINE, EMBASE and PsycINFO were accessed through Ovid – all other databases were accessed through EBSCOHost. Online databases of grey literature (ProQuest Dissertations and Theses Global, and Web of Science Conference Proceedings Citation Index – Science and Social Science & Humanities) were also searched. The search strategy was developed in consultation with a professional librarian at the lead author’s institution – search terms comprising population (e.g., children), intervention (e.g., physical activity) and context (e.g., at-risk) were combined with Medical Subject Headings (MeSH) to form the search strategy (see Supplementary Material S2). In line with recent recommendations (Frandsen et al., Citation2020; Lefebvre et al., Citation2022), search terms of outcomes (e.g., mental health) were not included. We did not restrict our search by publication date. Only articles published in English were included. Manual searches of reference lists and article citations (i.e., articles that cited the article of interest) were also conducted. Retrieved articles were deduplicated using methods outlined by Bramer et al. (Citation2016) prior to abstract screening. An updated search was conducted in February 2023 according to the methods described above.
Study selection and data extraction
Retrieved article information (i.e., titles and abstracts) was imported into EndNote 20, deduplicated, and then transferred into Research Screener (see Chai et al., Citation2021), a validated semi-automated machine learning tool which ranks and reorders articles based on relevance to the review. Research Screener determines relevance based on ‘seed articles’ (e.g., examples of relevant studies) provided by the review team, and by machine learning processes based on the reviewers’ decisions to include and exclude studies. Sensitivity analyses conducted by Chai et al. (Citation2021) revealed that, using Research Screener, 100% of relevant articles across eleven reviews were identified after screening between 4% and 40% of all articles. Chai et al. (Citation2021) indicate that systematic reviewers can be confident that all relevant articles will have been identified after 50% (which was a conservative estimate) of articles have been screened – we adhered to this recommendation in this review. Two authors (AS and BK) independently evaluated 50% of titles and abstracts for relevance according to the inclusion and exclusion criteria. Disagreements were solved by discussion until consensus, or if necessary, a third reviewer (BJ). The search and selection process are presented in the PRISMA flow diagram in .
Figure 1. PRISMA flow diagram.
One reviewer (AS) extracted the following data from selected studies: author, year, location, study design, sample size, participant recruitment, risk factor for mental health issues, participants’ age, gender and ethnicity distribution, intervention activity and characteristics (location, duration, dose, provider, adherence, theoretical basis), outcome measures and measurement tools, and results of the study (for relevant outcomes). To ensure the accuracy and reliability of data extraction, a research assistant extracted data from 10% of studies and cross-checked with the first reviewer’s data. The agreement percentage between the two reviewers was 92% across the studies. Any queries in data extraction were resolved through discussion with a third reviewer (BK).
Risk of bias assessment
Due to the broad range of study designs included in the review, three risk of bias assessment tools were utilised – the Cochrane risk of bias tool for randomised trials (RoB 2; Sterne et al., Citation2019), RoB 2 for cluster-randomised trials (Eldridge et al., Citation2021) and the Risk of Bias in Non-randomised Studies of Interventions (ROBINS-I; Sterne et al., Citation2016) tool. One reviewer (AS) conducted all risk of bias assessments, with a second reviewer (BK) completing 11% of the assessments in addition to regular cross-checking to ensure reliability. Across all bias domains for the four assessments that the second reviewer conducted, the agreement percentage was 93%. The RoB 2 tool addresses risk of bias from randomisation, deviations from intended interventions, missing outcome data, measurement of the outcome, and selection of the reported result, on a three-point scale from low to high (Sterne et al., Citation2019). An additional domain is considered in the cluster-randomised trial variant – risk of bias from the timing of identification or recruitment of participants (Eldridge et al., Citation2021). The ROBINS-I tool assesses the risk of bias due to confounding, selection of participants, classification of interventions, deviations from intended interventions, measurement of outcomes, and selection of reported result, on a four-point scale from low to critical (Sterne et al., Citation2016).
Analysis and synthesis
Due to vast differences in interventions, populations, and outcomes, in addition to a lack of compatible data, we deemed it unsuitable to conduct a meta-analysis. Instead, we present our findings according to procedures outlined in the Cochrane Handbook for Systematic Reviews of Interventions (chapter 12; McKenzie & Brennan, Citation2022). First, we provide descriptive information regarding the included studies. Second (and in line with recommendations to explore data synthesis alternatives beyond a narrative synthesis when meta-analysis is not possible; McKenzie & Brennan, Citation2022), where appropriate data were available to calculate effect sizes (i.e., means and standard deviations, or other relevant data for use according to Wilson, Citationn.d.), we present a graphical summary of effect estimates. We also present the proportion of effects ‘favouring the intervention’ (i.e., where the intervention arm had a more favourable score than the control arm for a specific outcome) compared to not favouring an intervention effect (i.e., where the control arm had a more favourable or equal score compared to the intervention arm). The above process, where effects are categorised as favouring the intervention or not, is known as vote counting (McKenzie & Brennan, Citation2022) – it is important to note that this analysis does not consider statistical significance, but instead the direction of effect. Additionally, each effect was included in this process – for example, if a three-armed study included a comparison of an outcome between the intervention arm and each comparator arm, we extracted and reported on both of those comparisons separately. Finally, we present a narrative synthesis of studies according to the type of intervention.
Results
Study characteristics
Our search yielded 37 reports on 36 studies (i.e., two journal articles on the same study were published: Tesler et al., Citation2018, Citation2022). For a full summary of study characteristics, see below. Half of all studies included in the review were conducted in the USA, and 56% of studies included a control arm (70% of which had an element of randomisation). Of the studies with a control arm, 40% had an active control (and therefore 22% of all studies included in the review had an active control arm). Participant age varied across studies, ranging from 6 to 21-years old (Hilgendorf, Citation2015; Szoko et al., Citation2022) – the median number of participants per study included in analyses was 72.5, and across the 36 studies, there were 5,098 participants. The most prevalent risk factor among included studies was low socioeconomic status. For a visual depiction of participant risk factors, see .
Figure 2. Participant risk factors in included studies.
Note. This figure shows the number of included studies that were targeted at each risk factor (i.e., the ‘reasons’ that young people participating in each study were deemed to be ‘at-risk’). ‘Alternative Schooling’ = exclusion from mainstream schooling; ‘Immigrants’ = recent immigrants and refugees; ‘Health’ = health condition; ‘Justice’ = involved in the juvenile justice system; ‘ASD’ = Autism Spectrum Disorder from a low socioeconomic background.
Table 1. Summary of studies.
Across the 36 studies, 85 outcomes were measured and reported – we categorised these outcomes into seven distinct categories following consultation with an expert in the mental health field, and the literature: (1) Internalising outcomes (measured 36 times; e.g., anxiety symptoms, depressive symptoms, mood), (2) self-evaluative outcomes (22; e.g., self-esteem, self-concept, self-worth), (3) wellbeing outcomes (8; e.g., emotional wellbeing, life satisfaction), (4) overall symptomatology (7; e.g., psychological difficulties, emotional dysregulation), (5) externalising outcomes (5; e.g., externalising symptoms, aggression), (6) resilience/coping outcomes (4; e.g., resilience, coping strategies), and (7) trauma outcomes (3; e.g., validity of cognition, trauma-related symptoms). For a graphical representation of outcome measures, see .
Figure 3. Outcomes measured in included studies.
For intervention factors, the median intervention dose was 29.5 h. Intervention dose was calculated as the duration of an individual intervention session multiplied by the number of sessions, and included all intervention components (i.e., if an intervention had multiple components, we did not extract only physical activity). Six studies did not report session duration or frequency and were therefore not included in the calculation of the median intervention dose. For studies that reported a range for number of sessions or session duration, the lowest value was used for calculation of intervention dose. All interventions were delivered in a group setting. There were a range of physical activities used to promote mental health outcomes – the most common of which were multi-sport (25%) and yoga (25%) interventions, but physical activities also included aerobic and resistance exercise, surfing, martial arts, basketball, and soccer (see narrative synthesis below). For the interested reader, brief descriptions of each intervention included in this review are presented in Supplementary Material S3.
Risk of bias assessment
Twenty-two studies (twenty-three reports, when including the two articles from the same study) were assessed for risk of bias via the ROBINS-I tool, eight studies via the RoB 2.0 tool, and five studies via the RoB 2.0 Cluster tool. One study was not assessed for risk of bias as it was a conference abstract and would therefore not be expected to provide sufficient information to make judgement on risk of bias domains. The risk of bias tools used in this review are designed to assess risk of bias at an outcome level (e.g., if four outcomes were measured in one study, all four outcomes had their own risk of bias assessment, instead of one per study). below provide information regarding the risk of bias within each bias domain. Overall, there was a high (‘serious’ for ROBINS-I) risk of bias across outcomes, and across bias domains. All studies assessed using the ROBINS-I tool were deemed to have a serious risk of bias, primarily due to the outcome measurement domain, which typically considers self-report psychological measures as having a high risk of bias. To account for this, we also provide an overall adjusted domain (see ), which removes the outcome measurement domain from consideration. Although this procedure improved (i.e., reduced) the risk of bias assessment for some outcomes (from serious to moderate), more than 60% of outcomes remained in the serious risk category. A moderate-to-high risk of bias was present across all study characteristics (e.g., intervention type, outcome, risk factor) irrespective of the risk of bias assessment tool used, and there were no patterns in regard to specific characteristics among included studies in the review.
Figure 4. ROBINS-I assessments.
Figure 5. Rob 2.0 assessments.
Figure 6. ROB cluster assessments.
Study findings
There was evidence indicating an effect of physical activity interventions on mental health-related outcomes (i.e., on the ‘categories’ of outcomes listed above; see ): of the between-groups (i.e., intervention against comparator / control arm) effects where the direction of effect could be ascertained, 39 favoured the intervention arm (62.9%), 10 favoured the control arm (16.1%), and three favoured neither arm (i.e., outcome scores were identical between-groups). For 10 effects, there was insufficient information to confidently identify the direction of effect (and therefore, the proportion of effects favouring the intervention from studies with available information was 75%, and 19% for effects favouring the control). A graphical presentation of the range of between-group effect sizes for characteristics with sufficient available data (i.e., a minimum of five effect sizes) is provided in (with shape indicating risk of bias for each effect). The median effect size (of 20 effects from eight studies) for internalising symptoms was d = 0.38, and the median effect size (of ten effects from seven studies) for self-evaluative outcomes was d = 0.25. Additionally, 29 (out of 35; 82.9%) within-groups effects (i.e., findings derived from pre-to-post change in single-group, uncontrolled studies) displayed evidence of a potential intervention effect, where scores on the outcome were more favourable at follow-up compared to baseline. It is important to exercise caution, however, when considering these within-group effects due to the absence of control measures.
Figure 7. Summary of effect sizes in controlled studies by outcome.
Note: An effect size above zero indicates a positive intervention effect. Due to the variance in outcomes measured within included studies, and the differences in measurement approach within an outcome category, we converted all ‘desirable’ effects to a positive effect size, and ‘undesirable’ effects to a negative effect size. For example, some outcomes or measures within the internalising category ‘improve’ when one’s score increases (e.g., affect), whereas other outcomes are measured such that a decrease in one’s score is indicative of an improvement (e.g., depressive symptoms). Subsequently, across all outcomes, all effect sizes are in the same direction (and therefore a negative effect size is a negative, or ‘undesirable’ finding). The number in parentheses of the legend indicates the number of studies effect size data were extracted from for that outcome. The shape of the data point indicates the risk of bias – triangular data points indicate a high risk of bias, and circular data points indicate a moderate risk of bias. For effects assessed for risk of bias using the ROBINS-I tool, the ‘overall adjusted’ risk of bias assessment was used.
In addition to overall effectiveness of physical activity interventions on mental health-related outcomes in at-risk young people, we explored the direction of effects organised by intervention type, risk factor, and outcome classification. A summary of these findings is available in . Only one study (out of nine) involving a multi-sport intervention reported an effect which did not favour the intervention – 23 effects (from seven studies) favoured the intervention, and one study had insufficient data. For yoga interventions, evidence was mixed – of 17 between-groups effects (from five studies), only six effects favoured the intervention. In regard to risk factor, 11 out of 18 effects for interventions for people deemed to be of a ‘high-risk’ race and socioeconomic status favoured the intervention. Notably, half of the between-groups effects for interventions for children in out-of-home care favoured the control. Analysis of direction of effect by outcome revealed that the majority (32 out of 41) of effects for internalising outcomes favoured the intervention (from 18 studies, of which three reported an effect favouring the control). A slightly lower proportion of effects for self-evaluative outcomes favoured the intervention (14 out of 22 effects, from 18 studies). Additionally, all six studies investigating wellbeing outcomes revealed positive intervention effects.
Table 2. Direction of effects grouped by intervention type, risk factor, and outcome.
Narrative synthesis
The findings summary above is an amalgamation of results according to the direction of effect. The following narrative synthesis, however, provides an overview of findings from included studies according to how they are reported in the study (i.e., generally, with reference to statistical significance), categorised by the ‘type’ of intervention. The purpose of this synthesis is to provide an overall depiction of the landscape of the literature – for specific details about each study (and characteristics of each intervention), we refer the reader to and Supplementary Material S3.
Multi-sport interventions
The most common approach (alongside yoga; 25% of included studies) to intervention was categorised as a ‘multi-sport’ intervention. These studies all used multiple sports or physical activities within their intervention or provided a choice of activity for participants. Five studies involved interventions for children or adolescents in low socioeconomic situations (Bonhauser et al., Citation2005; Dandan, Citation2019; Kishton & Dixon, Citation1995; Laberge et al., Citation2012; Ullrich-French et al., Citation2012). Across these five studies, evidence is mixed in regard to the effectiveness of multi-sport interventions for at-risk young people – three studies reported a positive intervention effect for at least one of their outcomes, and two studies found no intervention effect. Within these studies, positive intervention effects were found for two internalising outcomes: Bonhauser et al. (Citation2005) reported that, following a multi-sport intervention for adolescents in Chile, those who participated in the intervention demonstrated significantly lower anxiety symptoms, and Dandan (Citation2019) reported substantial improvements in internalising features following a team-work based multi-sport intervention. Additionally, two significant positive findings were reported for self-evaluative outcomes: in Ullrich-French et al.’s (Citation2012) study, children’s global and physical self-worth improved following a summer camp intervention, and Bonhauser et al. (Citation2005) found that intervention participants presented with higher self-esteem scores compared to controls following their intervention.
However, the above studies also reported some findings which did not support the effectiveness of multi-sport interventions for mental health outcomes in young people with low socioeconomic status – namely, no significant intervention effect was found for depressive symptoms (Bonhauser et al., Citation2005) or hope (Ullrich-French et al., Citation2012). Similarly, Laberge et al. (Citation2012) found no significant interaction effect (group-by-time) on self-esteem following an in-school, lunch-time intervention. Of particular note is the work by Kishton and Dixon (Citation1995) – following a summer sports camp, boys’ pre – and post-intervention global self-worth scores were not significantly different, however, girls’ self-worth significantly decreased, representing a negative finding for the effect of the multi-sport intervention.
Four other multi-sport interventions were included in the review targeting different populations (Hilgendorf, Citation2015; Tesler et al., Citation2018, Citation2022; Welfare & Mitchell, Citation2005; Xu et al., Citation2021). Positive findings were reported by Welfare and Mitchell (Citation2005), who demonstrated improvements in self-esteem and reductions in feelings of hopelessness (although statistical significance was not reported) following a multi-sport intervention for adolescents in juvenile detention. In addition, Tesler et al. (Citation2018, Citation2022) reported substantially higher self-efficacy and life satisfaction in at-risk youth following a multi-sport intervention, and Xu et al. (Citation2021) found significant between-groups effects favouring the intervention for well-being, psychological distress, positive emotions, and positive psychological functioning. Hilgendorf (Citation2015), however, found no significant differences in psychological difficulties between baseline and follow-up in children with a history of chronic maltreatment. Many multi-sport interventions incorporated a classroom learning / discussion element to complement the physical activity component (Dandan, Citation2019; Kishton & Dixon, Citation1995; Tesler et al., Citation2018, Citation2022; Ullrich-French et al., Citation2012; Welfare & Mitchell, Citation2005; Xu et al., Citation2021).
Yoga interventions
There were nine interventions (25%) designed to provide at-risk young people with exposure to yoga. We recognise that there are different ‘styles’ or ‘traditions’ of yoga; however, it is beyond the scope of this review to individually categorise and explore these variants. For this reason, the following yoga interventions are referred to collectively as ‘yoga interventions’. Overall, there were few findings to suggest that yoga interventions are effective for improving mental health outcomes in at-risk young people.
For some studies there appeared to be mixed evidence. For example, Frank et al. (Citation2014) measured positive and negative affect, depression, anxiety, somatisation, emotional distress, and stress symptomatology in a group of students not succeeding in a traditional schooling environment, and found significant pre–post improvements in depression, anxiety, emotional distress, and stress symptomatology (and therefore found no significant within-group effect for affect or somatisation). The trend of mixed findings was also apparent in Mendelson et al.’s (Citation2010), Sarkissian et al.’s (Citation2018), and Velásquez et al.’s (Citation2015) work (which were all for young people living in low socioeconomic or ‘urban’ environments), with all three studies reporting positive findings in regard to some outcomes, and no significant intervention effects in others. Mendelson et al. (Citation2010) found no between-groups differences in depressive symptoms or positive or negative affect, but did report higher involuntary engagement (i.e., stress responses) for intervention participants at follow-up compared to controls. This was congruent, in part, with Sarkissian et al. (Citation2018)’s findings – they reported significant pre–post improvements in stress, and no significant differences in negative affect. However, they also found a significant improvement in positive affect and resilience. Finally, in regard to studies with mixed findings, Velásquez et al. (Citation2015) reported a significant group-by-time interaction effect for anxiety and depression (favouring the intervention), but found no significant interaction effect for aggression.
Five studies found no significant beneficial effects of yoga interventions. In uncontrolled studies, Kwasky and Serowoky (Citation2018) found no improvements in emotional self-efficacy, and Szoko et al. (Citation2022) found no significant differences in resilience or psychological distress, following their respective interventions. In a non-randomised controlled study, Berger et al. (Citation2009) reported no significant differences at follow-up between intervention and control participants on global self-worth and self-perception. Their study, however, included a control group which participated in physical activity. Fishbein et al. (Citation2016), in a randomised controlled trial, reported no group-by-time interactions for emotional dysregulation, mood, coping, or externalising and social competency behaviours, although their control group was passive (in that, control arm participants had standard-practice lunch time at school). One other yoga intervention study (for youth living in an orphanage in Haiti; Culver et al., Citation2015) incorporated a control arm that participated in other physical activities (in this case, dance; as well as a wait-list control). Compared to the wait-list control, change in trauma-related symptoms was significantly higher (i.e., intervention participants’ post-intervention trauma symptomatology scores significantly decreased to a greater degree than controls) in the yoga intervention group, although the intervention group started with a higher baseline score. Despite trends in the data, no differences for trauma-related symptoms and psychological difficulties were reported for any between-groups comparison at follow-up.
Aerobic or resistance exercise
Interventions which involved group sessions of activities primarily designed to improve cardiovascular fitness (e.g., running, cycling) or muscular strength / endurance (e.g., free-weight resistance exercises such as deadlifts) were placed in this category.
Three studies reported findings from interventions that only included ‘aerobic’ activities (Crews et al., Citation2004; Draper et al., Citation2020; Lemstra & Rogers, Citation2022). Participant risk factors differed across the three studies, although all studies reported some positive intervention effects. Crews et al. (Citation2004) reported a main effect for group allocation on self-esteem following their intervention for low socioeconomic status children, and they found that intervention participants had improved depression scores at post-test compared to controls. Lemstra and Rogers (Citation2022) also found improvements in depression – in their large non-randomised, uncontrolled study of children with obesity, the percentage of participants with depressed mood decreased by 18.4% following programme participation. Draper et al.’s (Citation2020) work was trauma-focused – they reported significant improvements in two trauma outcomes (validity of cognition and subjective units of disturbance) following unaccompanied asylum seekers’ participation in at least running drill session. In addition to the positive findings highlighted above, Crews et al. (Citation2004) found no between-group differences (compared to an ‘other physical activities’ control group) in trait anxiety, and no group-by-time interaction effect for self-esteem, exemplifying the ‘mixed’ nature of findings highlighted in this review.
Other interventions involved a combination of aerobic and resistance-based activities, with mixed findings. There were some positive intervention effects for self-evaluative outcomes – Eather et al. (Citation2016) reported a large significant group-by-time interaction effect for improvements in self-esteem, and Annesi et al. (Citation2008) reported significantly greater improvements among intervention participants (compared to an unstructured physical activity control group) in general and physical self-description, and physical self-concept. Annesi et al. (Citation2008) also reported substantial improvements in mood, while Eather et al. (Citation2016) found a medium-sized (d = 0.7) non-significant group-by-time interaction effect for improvements in total psychological difficulties. Finally, in a study by Gehricke et al. (Citation2022), children of low socioeconomic status with autism spectrum disorder reported within-group improvements in anxiety following a physical activity intervention – however, there was no evidence of a treatment effect when compared with a LEGO® comparator group.
Surfing interventions
There were four surfing interventions included in the review – two in Portugal (de Matos et al., Citation2017; Pereira et al., Citation2020), and two in the UK (Godfrey et al., Citation2015; Hignett et al., Citation2018). Both interventions in Portugal were for young people living in residential care, and the interventions themselves were similar – Pereira et al.’s (Citation2020) study, however, was a randomised controlled trial (whereas de Matos et al., Citation2017, was not) and was over a longer intervention period. Findings from both studies indicated a substantial intervention effect on carer-rated psychological difficulties, but no effect for self-reported psychological difficulties. Additionally, Pereira et al. (Citation2020) reported no significant group-by-time interaction effects for anxiety symptoms, depressive symptoms, or self-esteem. In the UK, both Godfrey et al. (Citation2015) and Hignett et al. (Citation2018) used single-group pre–post designs, and both examined their respective interventions’ effects on wellbeing – Hignett et al. (Citation2018) reported no significant differences between baseline and follow-up on their measure of wellbeing (satisfaction with life overall), whereas Godfrey et al. (Citation2015) found substantial improvements in emotional wellbeing. In addition, Godfrey et al. reported substantial improvements in vulnerable young peoples’ positive functioning/outlook and self-esteem following their surfing intervention.
Martial arts interventions
Martial arts interventions were grouped together, despite some differences in the specific martial art that they included. Three of the four studies investigating martial arts interventions examined self-evaluative outcomes. Blowers (Citation2007) measured self-esteem at three timepoints, and revealed that intervention participants’ self-esteem at timepoint three was higher than at timepoint two and baseline – however, p-values were not reported. Harwood-Gross et al. (Citation2021) also measured self-esteem, as well as aggression, and found no differences in either outcome between intervention and control participants following a mixed martial art intervention for at-risk young people in Israel. In a small single-group study (n = 9), Conant et al. (Citation2008) reported slight pre–post differences (although statistically non-significant) in self-concept and quality of life following their karate intervention for young people with epilepsy. Finally, in an Australian study examining the effects of Capoeira Angola (a non-contact martial art involving dance, music, and singing), Momartin et al. (Citation2019) reported reductions in resettled refugees’ psychological difficulties following the intervention period.
Soccer interventions
There was little evidence to support the effectiveness of soccer interventions for mental health outcomes among the included studies in this review. In fact, two of the studies (Richards et al., Citation2014; Tilzey, Citation2020) revealed negative findings (i.e., evidence of worsening of mental health symptomatology). In Uganda, Richards et al. (Citation2014) conducted a randomised controlled trial nested within an observational study of Ugandan adolescents in a post-conflict setting. They measured two outcomes, which were derived from scores on four mental health syndromes local to the Gulu, Uganda area: ‘Depression-like syndrome’, and ‘anxiety-like syndrome’. Male participants’ scores on these two measures both worsened (i.e., they exhibit more depression-like and anxiety-like symptoms) following the intervention compared to a wait-list control and observational group, and there were no between-groups findings for girls. Tilzey (Citation2020), however, reported a worsening of internalising and externalising symptoms for girls (underserved newcomer immigrant youth) following participation in the soccer intervention, compared to matched sample means of underserved newcomer immigrant girls who did not participate in the programme. Conversely, Carter et al. (Citation2017) did not report any negative findings, however their findings were mixed. Carter et al. found that participants in their intervention group showed fewer internalising symptoms at follow-up compared to controls – however, there was no intervention effect for externalising symptoms.
Basketball interventions
One study (Tester et al., Citation1999) included in the review examined the effectiveness of a basketball intervention. Tester et al. reported that there was a 44% increase (pre-to-post-programme) in overall self-esteem for at-risk primary school students, and an 18% increase in overall self-esteem for at-risk secondary school students, although p-values were not reported.
Negative findings
In trying to understand the characteristics of effective physical activity interventions for children and adolescents at risk of mental health concerns, it is important to also consider the characteristics of studies where negative or iatrogenic findings were reported. There were few similarities across these studies included in the review. Two studies where soccer was the intervention activity reported negative findings, however both assessed different outcomes, were for different populations, and had different intervention doses, making it difficult to gain insight into why negative findings were observed (Richards et al., Citation2014; Tilzey, Citation2020). Tilzey (Citation2020) suggested that methodological issues may potentially explain their findings. Richards et al. (Citation2014), however, proposed that the iatrogenic effects they discovered may have been a result of the introduction of new stressors associated with competition. The notion that an unintended shift towards competitiveness among participants occurred is also posited by Kishton and Dixon (Citation1995), who reported a decrease in girls’ global self-worth following a multi-sport summer camp intervention.
Discussion
Our primary aim in this systematic review was to assess the effectiveness of physical activity interventions for mental health-related outcomes in at-risk young people, in relation to characteristics of the intervention. Major differences in intervention, population, and outcomes meant that a meta-analysis was not suitable. However, our findings from 36 included studies provide evidence for the effectiveness of physical activity interventions for beneficial effects on more than 60% of outcomes reported in controlled studies, and more than 80% of outcomes reported in uncontrolled studies. These findings generally corroborated those made by similar previous reviews (e.g., Hermens et al., Citation2017; Lubans et al., Citation2012; Rose & Soundy, Citation2020), and reiterate the need for more high-quality research in this field given the high risk of bias observed in this review and in previous reviews. In addition to examining whether physical activity interventions were effective for improving mental health-related outcomes, we aimed to gain insight into which characteristics of physical activity interventions (e.g., target population, intervention type, and ‘risk factor’ for mental health concerns) were more likely to lead to positive outcomes. In this regard, there was evidence to suggest that multi-sport interventions are effective, as well as interventions targeting internalising, self-evaluative, or wellbeing outcomes. There was mixed evidence regarding yoga interventions or interventions for young people in out-of-home care in particular, and other characteristics had too few studies to make significant conclusions either way. Additionally, all findings should be considered with caution due to the moderate-to-high risk of bias present. Where sufficient data were available, we provided summaries of effect size – small-to-moderate median effect sizes for internalising and self-evaluative outcomes support the notion that physical activity interventions are effective for eliciting mental health improvements in at-risk young people. We provide additional comment on intervention characteristics (and their association with effectiveness) throughout the discussion.
There is an extensive (and continually developing) evidence base supporting the effectiveness of physical activity (e.g., Biddle et al., Citation2019) and sport specifically (e.g., Boelens et al., Citation2022) for improving mental health outcomes in children and adolescents. In comparison, the evidence for ‘vulnerable’, ‘at-risk’, or ‘underserved’ children and adolescents is much less developed. This is a noteworthy gap given the elevated potential for mental health concerns in these at-risk populations (Kieling et al., Citation2011). It has also been documented previously that as well as a lack of work and evidence on this population in general, there is also a lack of high-quality evidence, particularly randomised controlled trials and/or longitudinal insight (Lubans et al., Citation2012; Rose & Soundy, Citation2020). Our review provides an updated (and largest-to-date) scope of the literature and reinforces that physical activity interventions can be effective for improving mental health outcomes in at-risk young people (although, the effectiveness of an intervention may depend upon the population, intervention, and the targeted outcomes).
It is important to recognise patterns within the ‘effective’ interventions to inform (a) the design of randomised controlled trials, and (b) meta-analyses which may explore potential moderating pathways of some of the following characteristics. One notable pattern amongst the effective controlled studies in the review was the implementation of multi-sport interventions. Despite twelve of the eighteen positive effects coming from Xu et al. (Citation2021), this observation indicates that a multi-sport approach may be worth considering as a strategy for physical activity interventions for at-risk young people. Overall, four controlled studies and three single-group studies reported positive effects following a ‘multi-sport’ physical activity intervention, which is promising evidence for the effectiveness of such interventions.
The popularity of multi-sport interventions (and preliminary evidence for effectiveness) in the field may stem from the notion that not all individuals who participate in physical activity are interested in the same activities. Although providing one activity may be associated with fewer logistical issues, evidence from our review suggests that providing young people at risk of mental health issues with a variety or choice of activity may foster more positive outcomes. This principle has been applied in similar contexts, such as school physical education (e.g., Pesce et al., Citation2013), and may also link to self-determination theory literature (for a recent review, see Vasconcellos et al., Citation2020). Within this theory, it is posited that satisfying one’s autonomy, relatedness, and competence in a physical activity context can lead to increased intrinsic motivation for participating in physical activity (and, importantly, outcomes such as improved wellbeing; Ryan & Deci, Citation2002; Teixeira et al., Citation2012). Within their review of physical activity interventions for underprivileged youth, Rose and Soundy (Citation2020) identified autonomy support as a potential mechanism for change in mental health outcomes. The prevalence of multi-sport interventions (where, often, participants could choose an activity) in our review suggests that researchers may be making considerations based on psychological theory (although, we cannot be certain of this until more specific review work is conducted). The authors of some studies included in our review did make specific reference to theory having influenced the design of the intervention, and others included theoretical concepts as part of their introductions (see Supplementary Material S3 for further information). One example of a popular theory which features prominently in the field is positive youth development (Bruner et al., Citation2023; Holt et al., Citation2017). Hermens et al. (Citation2017) examined life-skills development interventions, which closely aligns with positive youth development – 12 of the 18 programmes in their review were grounded in positive youth development theory. Thorough exploration of the theoretical foundations of included studies (and, by extension, the interventions reported within them) was beyond the scope of our review, however, we implore researchers to align their work with psychological theory whenever possible. Additionally, application of theory (and perhaps specific theories) may be a factor in the effectiveness of an intervention, although we cannot determine this within our extant review and encourage further pursuit of this line of enquiry.
More than 80% of internalising outcomes measured across all controlled studies included in the review were positively affected by a physical activity intervention, indicating the potential for physical activity interventions to foster benefits for outcomes such as depression or anxiety symptomatology, affect, and psychological distress or difficulties in young, at-risk populations. Outside of self-esteem, there were few ‘positive’ psychological outcomes in general (e.g., ‘protective factors’, such as self-evaluations, resilience, and wellbeing), which is particularly noteworthy given the potential mechanistic role that these outcomes (e.g., self-perception; Lubans et al., Citation2016) play on mental health, and child and adolescent development more broadly (Patton et al., Citation2016). Additionally, all six studies investigating the effect of physical activity interventions on wellbeing included in our review reported positive directions of effect, highlighting the potential salience of promoting protective factors (although, the risk of bias was high). We recommend that researchers advance this line of investigation by further exploring mechanisms (such as self-esteem, coping, or self-perception) of mental health improvements within at-risk populations.
The variation in outcomes, populations, and interventions in our review makes it difficult to confidently assert as to why some (i.e., 63% of between-groups effects in our review, and 75% of those with available data) physical activity interventions are effective, and some are ineffective. Some authors of included studies, however, suggested that a sense of competitiveness amongst participants may have led to iatrogenic effects – although this was not specifically measured and therefore remains speculative. Additionally, although not explored in the studies included in our review, at-risk young people (and specific risk factors under that ‘banner’) have unique barriers to participation which may ultimately impact the effectiveness of an intervention. For example, physical activity participation among at-risk young people may be impacted by situational and socioenvironmental factors (e.g., violence, crime; Ries et al., Citation2010). The effectiveness of an intervention may have been influenced by variations in the presence or severity of such factors across different populations. In light of the difficulties pinpointing effective (or ineffective) intervention characteristics, we encourage more work in this field (particularly high-quality RCTs) to advance the evidence base and provide a more concrete foundation for meta-analyses. However, as noted above, the characteristics with the largest body of evidence for effectiveness (e.g., multi-sport interventions) may offer a starting point for such work.
We also recognise that a large proportion of the studies included in our review were single-sport (activity) interventions – we were unable to identify any specific physical activity which had greater (more conclusive or higher quality) evidence of intervention effectiveness. Primarily, this was due to the dearth of available evidence for each activity. Subsequently, we encourage researchers to review the literature for specific physical activities (perhaps with a broader population focus) to advance our understanding of effective physical activity-based intervention for at-risk young people.
A strength of the current review is that it provides a summation and description of evidence pertaining to physical activity interventions for the mental health of at-risk young people. Nonetheless, these findings should be interpreted with consideration of its limitations. First, in regard to limitations of the evidence, and given extant evidence of the effectiveness of physical activity interventions, we reiterate the need for more adequately powered, high-quality randomised controlled trials. Although there appears to have been some improvements in the field more broadly (see Biddle et al., Citation2019), for at-risk populations these methodological challenges appear to persist (Hermens et al., Citation2017; Lubans et al., Citation2012; Rose & Soundy, Citation2020). Additionally, when authors reported on multi-component interventions (e.g., physical activity with an educational component), we were not able to infer whether the effects in these studies were derived from the physical activity, the other component(s) of the intervention, or both. Our inclusion criteria dictated that the interventions were primarily physical activity-focused, but further research design should include methods of isolating intervention components.
In regard to limitations of the review process, we note that it was difficult to capture all relevant articles that would likely fit our criteria, despite our rigorous systematic process. Our non-specific approach (i.e., not restricting our search to specific risk factors, or specific outcomes) meant that some articles would likely have fit our criteria, but may have been missed due to authors not mentioning the risk of mental ill health associated with their population. However, we believe that not including outcomes in our search strategy provided the best opportunity for the review team to include all relevant articles (and, was in line with recent recommendations; see Frandsen et al., Citation2020; Lefebvre et al., Citation2022). Additionally, only one reviewer conducted risk of bias assessments, and therefore our reporting of risk of bias was subject to the interpretation of that reviewer. However, we did include a cross-checking reliability process with a second reviewer for a portion of the studies (with a very high agreement percentage) to alleviate any potential errors or biases this may introduce. Additionally, the risk of bias tools we used are well-established and are designed to minimise the risk of subjective interpretation where possible. We also included a cross-checking process for our data extraction, in that 10% of our data were double-extracted (with a very high agreement percentage), instead of entirely double-extracted. The decision to conduct data extraction and risk of bias assessment with one reviewer (cross-checked by a second reviewer) was made based on utilising available resources (e.g., time) while maintaining methodological rigour and reducing the risk of error. Similar processes are common in systematic review literature (e.g., Kenny et al., Citation2024; Rogers et al., Citation2020), and any errors that may have occurred are very unlikely to have impacted the conclusions of the study (particularly, given that no meta-analysis was conducted) (Jones et al., Citation2005). Our review consolidates the notion that physical activity interventions can be effective for mental health outcomes in at-risk young people as a ‘general’ population, although we recommend review authors narrow their focus onto specific risk factors and populations. In doing so, the opportunity for meta-analysis may arise to provide higher level evidence for the effectiveness of physical activity interventions for at-risk young people.
In this systematic review, we provide updated and comprehensive evidence for the effectiveness of physical activity interventions for mental health-related outcomes in at-risk young people. Additionally, we present insight into the characteristics of physical activity interventions which may lead to more positive outcomes, which may assist those designing interventions in the future. We offer recommendations for future research at the individual study level (higher quality, powered randomised controlled trials) and the review level (focus on specific risk factors, which opens the potential for meta-analyses or a review of reviews). Our findings provide additional evidence that physical activity may be a valuable avenue for the prevention of mental ill health for at-risk young people, in addition to its other well-evidenced health benefits.
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