A trial protocol for the effectiveness of digital interventions for preventing depression in adolescents : The Future Proofing Study

Background: Depression frequently first emerges during adolescence, and one in five young people will experience an episode of depression by the age of 18 years. Despite advances in treatment, there has been limited progress in addressing the burden at a population level. Accordingly, there has been growing interest in prevention approaches as an additional pathway to address depression. Depression can be prevented using evidence-based psychological programmes. However, barriers to implementing and accessing these programmes remain, typically reflecting a requirement for delivery by clinical experts and high associated delivery costs. Digital technologies, specifically smartphones, are now considered a key strategy to overcome the barriers inhibiting access to mental health programmes. The Future Proofing Study is a large-scale school-based trial investigating whether cognitive behaviour therapies (CBT) delivered by smartphone application can prevent depression. Methods: A randomised controlled trial targeting up to 10,000 Year 8 Australian secondary school students will be conducted. In Stage I, schools will be randomised at the cluster level either to receive the CBT intervention app (SPARX) or to a non-active control group comparator. The primary outcome will be symptoms of depression, and secondary outcomes include psychological distress, anxiety and insomnia. At the 12-month follow-up, participants in the intervention arm with elevated depressive symptoms will participate in an individual-level randomised controlled trial (Stage II) and be randomised to receive a second CBT app which targets sleep difficulties (Sleep Ninja) or a control condition. Assessments will occur post intervention (both trial stages) and at 6, 12, 24, 36, 48 and 60 months post baseline. Primary analyses will use an intention-to-treat approach and compare changes in symptoms from baseline to follow-up relative to the control group using mixed-effect models. Discussion: This is the first trial testing the effectiveness of smartphone apps delivered to school students to prevent depression at scale. Results from this trial will provide much-needed insight into the feasibility of this approach. They stand to inform policy and commission decisions concerning if and how such programmes should be deployed in school-based settings in Australia and beyond

The relationship between cognitive and affective control and adolescent mental health

Abstract Background Cognitive control problems have been implicated in the etiology and maintenance of mental health problems, including depression, in adults. Studies in adolescents have been more equivocal, with some showing changes in cognitive control in adolescents with mental health problems, whereas others fail to show an association. This study examines whether adolescent mental health is associated with affective control, the application of cognitive control in affective contexts, which shows more protracted development than cognitive control. Methods The present study investigated the association of cognitive and affective control with depressive symptomatology and self‐reported diagnostic history of mental health problems in adolescents. The study included 1929 participants (Mage = 13.89) from the Future Proofing Study (N = 6,388, 11–16 years), who completed affective (incl., affective stimuli) and/or cognitive (incl., neutral stimuli) versions of a working memory (backward digit‐span) and/or shifting (card‐sorting) task at least once within 3 weeks of assessing mental health. Results Poorer working memory was associated with greater depressive symptomatology in adolescents (β = −0.06, p = .004), similarly across cognitive and affective control conditions (β = −0.02, p = .269). Adolescents with self‐reported diagnostic history of mental health problems had significantly poorer shifting ability in affective compared to cognitive control conditions (b = 0.05, p = .010), whereas for adolescents with no self‐reported diagnoses, shifting ability did not differ between conditions (b = −0.00, p = .649). Conclusions The present analyses suggest that working memory difficulties, in particular, may be associated with the experience of current depressed mood in adolescents. Problems with affective shifting may be implicated in a range of mental health problems in adolescents. Given the ubiquitous need for efficient cognitive functioning in daily life, enhancing cognitive and affective control in adolescents may be a promising means of improving functioning across a range of domains, including affective functioning, and by extension, adolescent mental health

The relationship between cognitive and affective control and adolescent mental health

Publication status: PublishedFunder: Ramsay Health Philanthropic GrantFunder: University of New South Wales Scientia PhD ScholarshipAbstractBackgroundCognitive control problems have been implicated in the etiology and maintenance of mental health problems, including depression, in adults. Studies in adolescents have been more equivocal, with some showing changes in cognitive control in adolescents with mental health problems, whereas others fail to show an association. This study examines whether adolescent mental health is associated with affective control, the application of cognitive control in affective contexts, which shows more protracted development than cognitive control.MethodsThe present study investigated the association of cognitive and affective control with depressive symptomatology and self‐reported diagnostic history of mental health problems in adolescents. The study included 1929 participants (Mage = 13.89) from the Future Proofing Study (N = 6,388, 11–16 years), who completed affective (incl., affective stimuli) and/or cognitive (incl., neutral stimuli) versions of a working memory (backward digit‐span) and/or shifting (card‐sorting) task at least once within 3 weeks of assessing mental health.ResultsPoorer working memory was associated with greater depressive symptomatology in adolescents (β = −0.06, p = .004), similarly across cognitive and affective control conditions (β = −0.02, p = .269). Adolescents with self‐reported diagnostic history of mental health problems had significantly poorer shifting ability in affective compared to cognitive control conditions (b = 0.05, p = .010), whereas for adolescents with no self‐reported diagnoses, shifting ability did not differ between conditions (b = −0.00, p = .649).ConclusionsThe present analyses suggest that working memory difficulties, in particular, may be associated with the experience of current depressed mood in adolescents. Problems with affective shifting may be implicated in a range of mental health problems in adolescents. Given the ubiquitous need for efficient cognitive functioning in daily life, enhancing cognitive and affective control in adolescents may be a promising means of improving functioning across a range of domains, including affective functioning, and by extension, adolescent mental health.</jats:sec

The Relationship Between Cognitive and Affective Control and Adolescent Mental Health

Background: Cognitive control problems have been implicated in the etiology and maintenance of mental health problems, including depression, in adults. Studies in adolescents have been more equivocal, with some showing changes in cognitive control in adolescents with mental health problems, whereas others fail to show an association. This study examines whether adolescent mental health is associated with affective control, the application of cognitive control in affective contexts, which shows more protracted development than cognitive control. Methods: The present study investigated the association of cognitive and affective control with depressive symptomatology and self-reported diagnostic history of mental health problems in adolescents. The study included 1,929 participants (Mage=13.89) from the Future Proofing Study (N=6,388, 11-16 years), who completed affective (incl., affective stimuli) and/or cognitive (incl., neutral stimuli) versions of a working memory (backward digit-span) and/or shifting (card-sorting) task at least once within three weeks of assessing mental health. Results: Poorer working memory was associated with greater depressive symptomatology in adolescents (β = −0.06, p = .004), similarly across cognitive and affective control conditions (β = −0.02, p = .269). Adolescents with self-reported diagnostic history of mental health problems had significantly poorer shifting ability in affective compared to cognitive control conditions (b = 0.05, p = .010), whereas for adolescents with no self-reported diagnoses, shifting ability did not differ between conditions (b = −0.00, p = .649). Conclusions: The present analyses suggest that working memory difficulties, in particular, may be associated with the experience of current depressed mood in adolescents. Problems with affective shifting may be implicated in a range of mental health problems in adolescents. Given the ubiquitous need for efficient cognitive functioning in daily life, enhancing cognitive and affective control in adolescents may be a promising means of improving functioning across a range of domains, including affective functioning, and by extension, adolescent mental health

Associations Between Smartphone Keystroke Metadata and Mental Health Symptoms in Adolescents: Findings From the Future Proofing Study

BackgroundMental disorders are prevalent during adolescence. Among the digital phenotypes currently being developed to monitor mental health symptoms, typing behavior is one promising candidate. However, few studies have directly assessed associations between typing behavior and mental health symptom severity, and whether these relationships differs between genders. ObjectiveIn a cross-sectional analysis of a large cohort, we tested whether various features of typing behavior derived from keystroke metadata were associated with mental health symptoms and whether these relationships differed between genders. MethodsA total of 934 adolescents from the Future Proofing study undertook 2 typing tasks on their smartphones through the Future Proofing app. Common keystroke timing and frequency features were extracted across tasks. Mental health symptoms were assessed using the Patient Health Questionnaire-Adolescent version, the Children’s Anxiety Scale-Short Form, the Distress Questionnaire 5, and the Insomnia Severity Index. Bivariate correlations were used to test whether keystroke features were associated with mental health symptoms. The false discovery rates of P values were adjusted to q values. Machine learning models were trained and tested using independent samples (ie, 80% train 20% test) to identify whether keystroke features could be combined to predict mental health symptoms. ResultsKeystroke timing features showed a weak negative association with mental health symptoms across participants. When split by gender, females showed weak negative relationships between keystroke timing features and mental health symptoms, and weak positive relationships between keystroke frequency features and mental health symptoms. The opposite relationships were found for males (except for dwell). Machine learning models using keystroke features alone did not predict mental health symptoms. ConclusionsIncreased mental health symptoms are weakly associated with faster typing, with important gender differences. Keystroke metadata should be collected longitudinally and combined with other digital phenotypes to enhance their clinical relevance. Trial RegistrationAustralian and New Zealand Clinical Trial Registry, ACTRN12619000855123; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=377664&isReview=tru

A trial protocol for the effectiveness of digital interventions for preventing depression in adolescents: The Future Proofing Study

BACKGROUND: Depression frequently first emerges during adolescence, and one in five young people will experience an episode of depression by the age of 18 years. Despite advances in treatment, there has been limited progress in addressing the burden at a population level. Accordingly, there has been growing interest in prevention approaches as an additional pathway to address depression. Depression can be prevented using evidence-based psychological programmes. However, barriers to implementing and accessing these programmes remain, typically reflecting a requirement for delivery by clinical experts and high associated delivery costs. Digital technologies, specifically smartphones, are now considered a key strategy to overcome the barriers inhibiting access to mental health programmes. The Future Proofing Study is a large-scale school-based trial investigating whether cognitive behaviour therapies (CBT) delivered by smartphone application can prevent depression. METHODS: A randomised controlled trial targeting up to 10,000 Year 8 Australian secondary school students will be conducted. In Stage I, schools will be randomised at the cluster level either to receive the CBT intervention app (SPARX) or to a non-active control group comparator. The primary outcome will be symptoms of depression, and secondary outcomes include psychological distress, anxiety and insomnia. At the 12-month follow-up, participants in the intervention arm with elevated depressive symptoms will participate in an individual-level randomised controlled trial (Stage II) and be randomised to receive a second CBT app which targets sleep difficulties (Sleep Ninja) or a control condition. Assessments will occur post intervention (both trial stages) and at 6, 12, 24, 36, 48 and 60 months post baseline. Primary analyses will use an intention-to-treat approach and compare changes in symptoms from baseline to follow-up relative to the control group using mixed-effect models. DISCUSSION: This is the first trial testing the effectiveness of smartphone apps delivered to school students to prevent depression at scale. Results from this trial will provide much-needed insight into the feasibility of this approach. They stand to inform policy and commission decisions concerning if and how such programmes should be deployed in school-based settings in Australia and beyond.Funding for this project came from a NHMRC Project Grant Awarded to HC (APP1120646), an Early-Mid Career Fellowship awarded to AW-S, an NHMRC Fellowship awarded to PJB (APP1158707) and a Sir Henry Wellcome fellowship awarded to S

Risk factors for mild cognitive impairment, dementia and mortality: The Sydney Memory and Ageing Study

Background The nature and commonality of late-life risk factors for mild cognitive impairment (MCI), dementia, and mortality remain unclear. Our aim was to investigate potential risk factors, simultaneously in a single cohort including many individuals initially with normal cognition and followed for 6 years. Methods We classified 873 community-dwelling individuals (70–90 years old and without dementia at baseline) from the Sydney Memory and Ageing Study as cognitively normal (CN), having MCI or dementia, or deceased 6 years after baseline. Associations with baseline demographic, lifestyle, health, and medical factors were investigated, including apolipoprotein (APOE) genotype, MCI at baseline, and reversion from MCI to CN within 2 years of baseline. Results Eighty-three (9.5%) participants developed dementia and 114 (13%) died within 6 years; nearly 33% had MCI at baseline, of whom 28% reverted to CN within 2 years. A core set of baseline factors was associated with MCI and dementia at 6 years, including older age (per year: odds ratios and 95% confidence intervals = 1.08, 1.01–1.14 for MCI; 1.19, 1.09–1.31 for dementia), MCI at baseline (5.75, 3.49–9.49; 8.23, 3.93–17.22), poorer smelling ability (per extra test point: 0.89, 0.79–1.02; 0.80, 0.68–0.94), slower walking speed (per second: 1.12, 1.00–1.25; 1.21, 1.05–1.39), and being an APOE ε4 carrier (1.84, 1.07–3.14; 3.63, 1.68–7.82). All except APOE genotype were also associated with mortality (age: 1.11, 1.03–1.20; MCI: 3.87, 1.97–7.59; smelling ability: 0.83, 0.70–0.97; walking speed: 1.18, 1.03–1.34). Compared with stable CN participants, individuals reverting from MCI to CN after 2 years were at greater risk of future MCI (3.06, 1.63–5.72). Those who reverted exhibited some different associations between baseline risk factors and 6-year outcomes than individuals with stable MCI. Conclusion A core group of late-life risk factors indicative of physical and mental frailty are associated with each of dementia, MCI, and mortality after 6 years. Tests for slower walking speed and poorer smelling ability may help screen for cognitive decline. Individuals with normal cognition are at greater risk of future cognitive impairment if they have a history of MCI

Risk Factors for Mild Cognitive Impairment, Dementia and Mortality: The Sydney Memory and Ageing Study

© 2016 AMDA - The Society for Post-Acute and Long-Term Care Medicine.Background: The nature and commonality of late-life risk factors for mild cognitive impairment (MCI), dementia, and mortality remain unclear. Our aim was to investigate potential risk factors, simultaneously in a single cohort including many individuals initially with normal cognition and followed for 6 years. Methods: We classified 873 community-dwelling individuals (70-90 years old and without dementia at baseline) from the Sydney Memory and Ageing Study as cognitively normal (CN), having MCI or dementia, or deceased 6 years after baseline. Associations with baseline demographic, lifestyle, health, and medical factors were investigated, including apolipoprotein (APOE) genotype, MCI at baseline, and reversion from MCI to CN within 2 years of baseline. Results: Eighty-three (9.5%) participants developed dementia and 114 (13%) died within 6 years; nearly 33% had MCI at baseline, of whom 28% reverted to CN within 2 years. A core set of baseline factors was associated with MCI and dementia at 6 years, including older age (per year: odds ratios and 95% confidence intervals = 1.08, 1.01-1.14 for MCI; 1.19, 1.09-1.31 for dementia), MCI at baseline (5.75, 3.49-9.49; 8.23, 3.93-17.22), poorer smelling ability (per extra test point: 0.89, 0.79-1.02; 0.80, 0.68-0.94), slower walking speed (per second: 1.12, 1.00-1.25; 1.21, 1.05-1.39), and being an . APOE ε4 carrier (1.84, 1.07-3.14; 3.63, 1.68-7.82). All except . APOE genotype were also associated with mortality (age: 1.11, 1.03-1.20; MCI: 3.87, 1.97-7.59; smelling ability: 0.83, 0.70-0.97; walking speed: 1.18, 1.03-1.34). Compared with stable CN participants, individuals reverting from MCI to CN after 2 years were at greater risk of future MCI (3.06, 1.63-5.72). Those who reverted exhibited some different associations between baseline risk factors and 6-year outcomes than individuals with stable MCI. Conclusion: A core group of late-life risk factors indicative of physical and mental frailty are associated with each of dementia, MCI, and mortality after 6 years. Tests for slower walking speed and poorer smelling ability may help screen for cognitive decline. Individuals with normal cognition are at greater risk of future cognitive impairment if they have a history of MCI