scholarly journals Corrigendum to “Mental health apps for adolescents and young adults: A systematic review of randomised controlled trials” [Child. Youth Serv. Rev. 127 (2021) 106073]

Author(s):  
Teghan Leech ◽  
Diana Dorstyn ◽  
Amanda Taylor ◽  
Wenjing Li
2017 ◽  
Vol 48 (7) ◽  
pp. 1068-1083 ◽  
Author(s):  
A. P. Bailey ◽  
S. E. Hetrick ◽  
S. Rosenbaum ◽  
R. Purcell ◽  
A. G. Parker

AbstractWe aimed to establish the treatment effect of physical activity for depression in young people through meta-analysis. Four databases were searched to September 2016 for randomised controlled trials of physical activity interventions for adolescents and young adults, 12–25 years, experiencing a diagnosis or threshold symptoms of depression. Random-effects meta-analysis was used to estimate the standardised mean difference (SMD) between physical activity and control conditions. Subgroup analysis and meta-regression investigated potential treatment effect modifiers. Acceptability was estimated using dropout. Trials were assessed against risk of bias domains and overall quality of evidence was assessed using GRADE criteria. Seventeen trials were eligible and 16 provided data from 771 participants showing a large effect of physical activity on depression symptoms compared to controls (SMD = −0.82, 95% CI = −1.02 to −0.61, p < 0.05, I2 = 38%). The effect remained robust in trials with clinical samples (k = 5, SMD = −0.72, 95% CI = −1.15 to −0.30), and in trials using attention/activity placebo controls (k = 7, SMD = −0.82, 95% CI = −1.05 to −0.59). Dropout was 11% across physical activity arms and equivalent in controls (k = 12, RD = −0.01, 95% CI = −0.04 to 0.03, p = 0.70). However, the quality of RCT-level evidence contributing to the primary analysis was downgraded two levels to LOW (trial-level risk of bias, suspected publication bias), suggesting uncertainty in the size of effect and caution in its interpretation. While physical activity appears to be a promising and acceptable intervention for adolescents and young adults experiencing depression, robust clinical effectiveness trials that minimise risk of bias are required to increase confidence in the current finding. The specific intervention characteristics required to improve depression remain unclear, however best candidates given current evidence may include, but are not limited to, supervised, aerobic-based activity of moderate-to-vigorous intensity, engaged in multiple times per week over eight or more weeks. Further research is needed. (Registration: PROSPERO-CRD 42015024388).


Author(s):  
Charlotte Parbery-Clark ◽  
Marvellas Lubamba ◽  
Louise Tanner ◽  
Elaine McColl

Background: The aim of this systematic review was to evaluate the effectiveness of Animal-Assisted Interventions (AAIs), particularly Animal-Assisted Therapy (AAT) and Animal-Assisted Activity (AAA), in improving mental health outcomes for students in higher education. The number of students in higher education reporting mental health problems and seeking support from universities’ student support services has risen over recent years. Therefore, providing engaging interventions, such as AAIs, that are accessible to large groups of students are attractive. Methods: MEDLINE, PsycINFO, Embase and Cochrane Library were searched from relative inception to end of April 2020. Additionally, a grey literature search was undertaken. Independent screening, data extraction and risk of bias assessment were completed, with varying percentages, by two reviewers. Results: After de-duplication, 6248 articles were identified of which 11 studies were included in the narrative synthesis. The evidence from randomised controlled trials suggests that AAIs could provide short-term beneficial results for anxiety in students attending higher education but with limited evidence for stress, and inconclusive evidence for depression, well-being and mood. For the non-statistically significant results, the studies either did not include a power calculation or were under-powered. Conclusions: Potential emerging evidence for the short-term benefits of AAI for anxiety, and possibly stress, for students in higher education was found.


2015 ◽  
Vol 18 (11) ◽  
pp. 2074-2093 ◽  
Author(s):  
Rachelle S Opie ◽  
Adrienne O’Neil ◽  
Catherine Itsiopoulos ◽  
Felice N Jacka

AbstractObjectiveNon-pharmacological approaches to the treatment of depression and anxiety are of increasing importance, with emerging evidence supporting a role for lifestyle factors in the development of these disorders. Observational evidence supports a relationship between habitual diet quality and depression. Less is known about the causative effects of diet on mental health outcomes. Therefore a systematic review was undertaken of randomised controlled trials of dietary interventions that used depression and/or anxiety outcomes and sought to identify characteristics of programme success.DesignA systematic search of the Cochrane, MEDLINE, EMBASE, CINAHL, PubMed and PyscInfo databases was conducted for articles published between April 1971 and May 2014.ResultsOf the 1274 articles identified, seventeen met eligibility criteria and were included. All reported depression outcomes and ten reported anxiety or total mood disturbance. Compared with a control condition, almost half (47 %) of the studies observed significant effects on depression scores in favour of the treatment group. The remaining studies reported a null effect. Effective dietary interventions were based on a single delivery mode, employed a dietitian and were less likely to recommend reducing red meat intake, select leaner meat products or follow a low-cholesterol diet.ConclusionsAlthough there was a high level of heterogeneity, we found some evidence for dietary interventions improving depression outcomes. However, as only one trial specifically investigated the impact of a dietary intervention in individuals with clinical depression, appropriately powered trials that examine the effects of dietary improvement on mental health outcomes in those with clinical disorders are required.


2021 ◽  
Author(s):  
Madison Milne-Ives ◽  
Emma Selby ◽  
Becky Inkster ◽  
Edward Meinert

BACKGROUND Mental health conditions can have significant negative impacts on wellbeing and healthcare systems. Despite their high prevalence worldwide, there is still insufficient recognition and accessible treatments. Many mobile apps are available to the general population that aim to support mental health needs; however, there is limited evidence of their effectiveness. Mobile apps for mental health are beginning to incorporate artificial intelligence and there is a need for an overview of the state of the literature on these apps. OBJECTIVE The purpose of this scoping review is to provide an overview of the current research landscape and knowledge gaps regarding the use of artificial intelligence in mobile health apps for mental health. METHODS The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) and Population, Intervention, Comparator, Outcome, and Study (PICOS) frameworks were used to structure the review and the search. PubMed was systematically searched for randomised controlled trials and cohort studies published in English since 2014 that evaluate artificial intelligence-enabled mobile apps for mental health support. Two reviewers collaboratively screened references, selected studies for inclusion based on the eligibility criteria, and extracted the data, which were synthesised in a descriptive analysis. RESULTS 1,022 studies were identified in the initial search and 6 were included in the final review. The mobile apps investigated incorporated artificial intelligence for a variety of purposes (risk prediction, classification, and personalisation) and aimed to address a wide range of mental health needs (including developmental disabilities, depression, stress, and suicide risk). The studies’ characteristics also varied in terms of methods, sample size, and study duration. CONCLUSIONS Overall, the studies demonstrated the feasibility of using artificial intelligence to support mental health apps, but the early stages of the research and weaknesses in the study designs highlight the need for more research into artificial intelligence-enabled mental health apps and stronger evidence of their effectiveness. This research is essential and urgent, considering the easy availability of these artificial intelligence-enabled mental health apps to a large population.


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