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      E-Health interventions for anxiety and depression in children and adolescents with long-term physical conditions

      1 , 1 , 1 , 2 , 1 , 3 , 1
      Cochrane Common Mental Disorders Group
      Cochrane Database of Systematic Reviews
      Wiley

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          Abstract

          Long‐term physical conditions affect 10% to 12% of children and adolescents worldwide; these individuals are at greater risk of developing psychological problems, particularly anxiety and depression. Access to face‐to‐face treatment for such problems is often limited, and available interventions usually have not been tested with this population. As technology improves, e‐health interventions (delivered via digital means, such as computers and smart phones and ranging from simple text‐based programmes through to multimedia and interactive programmes, serious games, virtual reality and biofeedback programmes) offer a potential solution to address the psychological needs of this group of young people. To assess the effectiveness of e‐health interventions in comparison with attention placebos, psychological placebos, treatment as usual, waiting‐list controls, or non‐psychological treatments for treating anxiety and depression in children and adolescents with long‐term physical conditions. We searched the Cochrane Common Mental Disorders Group's Controlled Trials Register (CCMDTR to May 2016), the Cochrane Central Register of Controlled Trials (CENTRAL) (Issue 8, 2017), Web of Science (1900 ‐ 18 August 2016, updated 31 August 2017) and Ovid MEDLINE, Embase, PsycINFO (cross‐search 2016 to 18 Aug 2017). We hand‐searched relevant conference proceedings, reference lists of included articles, and the grey literature to May 2016. We also searched international trial registries to identify unpublished or ongoing trials. We included randomised controlled trials (RCTs), cluster‐randomised trials, and cross‐over trials of e‐health interventions for treating any type of long‐term physical condition in children and adolescents (aged 0 to 18 years), and that measured changes in symptoms or diagnoses of anxiety, depression, or subthreshold depression. We defined long‐term physical conditions as those that were more than three‐months' duration. We assessed symptoms of anxiety and depression using patient‐ or clinician‐administered validated rating scales based on DSM III, IV or 5 ( American Psychological Association 2013 ), or ICD 9 or 10 criteria ( World Health Organization 1992 ). Formal depressive and anxiety disorders were diagnosed using structured clinical interviews. Attention placebo, treatment as usual, waiting list, psychological placebo, and other non‐psychological therapies were eligible comparators. Two review authors independently reviewed titles, abstracts, and full‐text articles; discrepancies were resolved through discussion or addressed by a third author. When available, we used odds ratio (OR) to compare dichotomous data and standardised mean differences (SMD) to analyse continuous data, both with 95% confidence intervals (CI). We undertook meta‐analysis when treatments, participants, and the underlying clinical question were adequately similar. Otherwise, we undertook a narrative analysis. We included five trials of three interventions (Breathe Easier Online, Web‐MAP, and multimodal cognitive behavioural therapy (CBT)), which included 463 participants aged 10 to 18 years. Each trial contributed to at least one meta‐analysis. Trials involved children and adolescents with long‐term physical conditions, such as chronic headache (migraine, tension headache, and others), chronic pain conditions (abdominal, musculoskeletal, and others), chronic respiratory illness (asthma, cystic fibrosis, and others), and symptoms of anxiety or depression. Participants were recruited from community settings and hospital clinics in high income countries. For the primary outcome of change in depression symptoms versus any control, there was very low‐quality evidence meaning that it could not be determined whether e‐health interventions were clearly better than any comparator (SMD ‐0.06, 95% CI ‐0.35 to 0.23; five RCTs, 441 participants). For the primary outcome of change in anxiety symptoms versus any comparator, there was very low‐quality evidence meaning that it could not be determined whether e‐health interventions were clearly better than any comparator (SMD ‐0.07, 95% CI ‐0.29 to 0.14; two RCTs, 324 participants). For the primary outcome of treatment acceptability, there was very low‐quality evidence that e‐health interventions were less acceptable than any comparator (SMD 0.46, 95% CI 0.23 to 0.69; two RCTs, 304 participants). For the secondary outcome of quality of life, there was very low‐quality evidence meaning that it could not be determined whether e‐health interventions were clearly better than any comparator (SMD ‐0.83, 95% CI ‐1.53 to ‐0.12; one RCT, 34 participants). For the secondary outcome of functioning, there was very low‐quality evidence meaning that it could not be determined whether e‐health interventions were clearly better than any comparator (SMD ‐0.08, 95% CI ‐0.33 to 0.18; three RCTs, 368 participants). For the secondary outcome of status of long‐term physical condition, there was very low‐quality evidence meaning that it could not be determined whether e‐health interventions were clearly better than any comparator (SMD 0.06, 95% CI ‐0.12 to 0.24; five RCTs, 463 participants). The risk of selection bias was considered low in most trials. However, the risk of bias due to inadequate blinding of participants or outcome assessors was considered unclear or high in all trials. Only one study had a published protocol; two trials had incomplete outcome data. All trials were conducted by the intervention developers, introducing another possible bias. No adverse effects were reported by any authors. At present, the field of e‐health interventions for the treatment of anxiety or depression in children and adolescents with long‐term physical conditions is limited to five low quality trials. The very low‐quality of the evidence means the effects of e‐health interventions are uncertain at this time, especially in children aged under 10 years. Although it is too early to recommend e‐health interventions for this clinical population, given their growing number, and the global improvement in access to technology, there appears to be room for the development and evaluation of acceptable and effective technologically‐based treatments to suit children and adolescents with long‐term physical conditions. E‐health interventions for anxiety and depression in children and adolescents with long‐term physical conditions Why is this review important? More than one in ten children and adolescents worldwide have long‐term physical conditions, such as asthma, diabetes, and cancer. They are more likely to develop psychological problems, which include anxiety or depression. Treating such problems early can prevent difficulties with friendships, family life, school, and future mental health problems. Accessing traditionally delivered face‐to‐face therapy can be difficult, due to the limited number of services. As technology improves, and therapies become available on computers and mobile telephones, e‐health interventions (delivered by digital means and ranging from simple text‐based programmes through to multimedia and interactive programmes, serious games, virtual reality and biofeedback programmes) may be useful to treat anxiety and depression in these children and adolescents. Who will be interested in this review? This review will be of interest to parents, children and adolescents, mental healthcare providers, service commissioners, and professionals caring for children with long‐term physical conditions. What questions does this review aim to answer? This review aimed to answer the following questions: 1) Are e‐health interventions better than a selected range of other therapies or waiting list in reducing symptoms of anxiety and depression in children and adolescents with long‐term physical conditions? and 2) Are e‐health interventions acceptable to these children and adolescents? Which studies were included in the review? We searched reference databases to find all randomised controlled trials, cluster‐randomised trials, and cross‐over trials of e‐health interventions for treating anxiety or depression in children and adolescents with long‐term physical conditions that were published between 1970 and August 2017. Trials had to be randomised controlled trials that included children and young people with either symptoms or formal diagnoses of anxiety or depression. We included five trials, with a total of 463 young people, in the review. What does the evidence from the review tell us? We included five trials of three e‐health interventions (Breathe Easier Online, Web‐MAP, and multimodal cognitive behavioural therapy (CBT)), undertaken with children aged 10 to 18 years old. Although some of these interventions were acceptable to users, none of them were clearly any better than a selected range of other therapies or waiting list at reducing symptoms of anxiety or depression.The very low quality of the evidence means the effects of e‐health interventions are uncertain at this time, especially in children aged under 10 years. The review authors rated the overall risk of bias in the trials as high or uncertain. What should happen next? Further research should be undertaken to develop more effective e‐health interventions to treat anxiety and depression in children and adolescents with long‐term physical conditions.

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          Most cited references115

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            To qualitatively review the literature of the past decade covering the epidemiology, clinical characteristics, natural course, biology, and other correlates of early-onset major depressive disorder (MDD) and dysthymic disorder (DD). A computerized search for articles published during the past 10 years was made and selected studies are presented. Early-onset MDD and DD are frequent, recurrent, and familial disorders that tend to continue into adulthood, and they are frequently accompanied by other psychiatric disorders. These disorders are usually associated with poor psychosocial and academic outcome and increased risk for substance abuse, bipolar disorder, and suicide. In addition, DD increases the risk for MDD. There is a secular increase in the prevalence of MDD, and it appears that MDD is occurring at an earlier age in successive cohorts. Several genetic, familial, demographic, psychosocial, cognitive, and biological correlates of onset and course of early-onset depression have been identified. Few studies, however, have examined the combined effects of these correlates. Considerable advances have been made in our knowledge of early-onset depression. Nevertheless, further research is needed in understanding the pathogenesis of childhood mood disorders. Toward this end, studies aimed at elucidating mechanisms and interrelationships among the different domains of risk factors are needed.
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              Major depressive disorder in older adolescentsPrevalence, risk factors, and clinical implications

              In this article we summarize our current understanding of depression in older (14-18 years old) adolescents based on our program of research (the Oregon Adolescent Depression Project). Specifically, we address the following factors regarding adolescent depression: (a) phenomenology (e.g., occurrence of specific symptoms, gender and age effects, community versus clinic samples); (b) epidemiology (e.g., prevalence, incidence, duration, onset age); (c) comorbidity with other mental and physical disorders; (d) psychosocial characteristics associated with being, becoming, and having been depressed; (e) recommended methods of assessment and screening; and (f) the efficacy of a treatment intervention developed for adolescent depression, the Adolescent Coping With Depression course. We conclude by providing a set of summary statements and recommendations for clinicians.
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                Author and article information

                Journal
                Cochrane Database of Systematic Reviews
                Wiley
                14651858
                August 15 2018
                Affiliations
                [1 ]University of Auckland; Department of Psychological Medicine; Level 12 Support Building Auckland Hospital, Park Road, Grafton Auckland New Zealand
                [2 ]University of Melbourne; The Centre of Youth Mental Health; Melbourne Victoria Australia
                [3 ]University of Kassel; Department of Psychology; Kassel Germany
                Article
                10.1002/14651858.CD012489.pub2
                0cc6b040-717a-4a38-bf08-3a4eea9d9332
                © 2018
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