A comparison of perception of ADHD among diagnosed children and their parents

Although research on youngsters’ and parents’ experience of ADHD has grown in recent years, little is known about their subjective perception of ADHD as a disorder. Previous studies on subjective perceptions of individuals with ADHD have examined only one or two facets of such perceptions simultaneously. However, theories of illness perception suggest that such perception consists of at least five constructs (see the Common-Sense Model of Illness Representations or CSM; Leventhal et al., 1997, 1984). The present thesis sought to address this research gap by applying CSM in the context of ADHD. The thesis aimed to 1)obtain a comprehensive understanding of perception of ADHD among diagnosed youngsters and their parents, 2)examine the predictive ability of the perceptions on their coping and emotional well-being, 3)compare parents- and offspring perceptions, and 4)examine the predictive ability of discrepant perception on their coping and emotional well-being. The systematic review of literature shows that disproportional research attention has been paid to the perceived effectiveness of treatment compared to other illness beliefs. The empirical study utilizing cross-sectional design included 61 dyads of adolescents with ADHD (10 to 18 years) and their parents, who were recruited from clinic, support groups and educational consultancy. Findings show that several illness beliefs (e.g., coherence, timeline), which have been under-researched, are predictors of adolescents’ coping. Adolescents see ADHD as less threatening and less biologically based than parents. Several discrepant illness beliefs (e.g., timeline, cause) seem to predict adolescents’ coping and quality of life. Different perceptions of impact were related to parents’ elevated stress. Overall, the present study provided initial evidence for the utility of CSM in youngsters of ADHD and their parents that may have significant implications for psycho-education, clinical practice and ongoing research

A mobile health intervention (LifeBuoy App) to help young people manage suicidal thoughts : protocol for a mixed-methods randomized controlled trial

Background: Self-help smartphone apps offer a new opportunity to address youth suicide prevention by improving access to support and by providing potentially high fidelity and cost-effective treatment. However, there have been very few smartphone apps providing evidence-based support for suicide prevention in this population. To address this gap, we developed the LifeBuoy app, a self-help smartphone app informed by dialectical behavior therapy (DBT), to help young people manage suicidal thoughts in their daily life. Objective: This study describes the protocol for a randomized controlled trial to evaluate the efficacy of the LifeBuoy app for reducing suicidal thoughts and behaviors, depression, anxiety, and psychological distress, and improving general mental well-being in young adults aged 18 to 25 years. Methods: This is a randomized controlled trial recruiting 378 young adults aged between 18 and 25 years and comparing the LifeBuoy app with a matched attention control (a placebo app with the same display but no DBT components). The primary outcome is suicidal thoughts measured by the Suicidal Ideation Attributes Scale (SIDAS). The secondary outcomes are suicidal behavior, depression, anxiety, psychological distress, and general mental well-being. The changes in the levels of insomnia, rumination, suicide cognitions, distress tolerance, loneliness, and help seeking before and after using the app are evaluated in this study. The study also addresses risk factors and responses to the intervention. A series of items assessing COVID-19 experiences is included in the trial to capture the potential impact of the pandemic on this study. Assessments will occur on the following three occasions: baseline, postintervention, and follow-up at 3 months postintervention. A qualitative interview about user experience with the LifeBuoy app will take place within 4 weeks of the final assessment. Using linear mixed models, the primary analysis will compare the changes in suicidal thoughts in the intervention condition relative to the control condition. To minimize risks, participants will receive a call from the team clinical psychologist by clicking a help button in the app or responding to an automated email sent by the system when they are assessed with elevated suicide risks at the baseline, postintervention, and 3-month follow-up surveys. Results: The trial recruitment started in May 2020. Data collection is currently ongoing. Conclusions: This is the first trial examining the efficacy of a DBT-informed smartphone app delivered to community-living young adults reporting suicidal thoughts. This trial will extend knowledge about the efficacy and acceptability of app-based support for suicidal thoughts in young people

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

A comparison of perception of ADHD among diagnosed children and their parents

This study extends the application of the Common-Sense Model of Illness Representations (Leventhal, Meyer, & Nerenz, 1980; Leventhal, Nerenz, & Steele, 1984) from people with physical and mental illnesses to people with developmental disorders. The study aimed to 1) obtain a comprehensive understanding of the perception of ADHD among the diagnosed youngsters and their parents, 2) to examine the predictive ability of their perceptions of ADHD in their coping and emotional well-being, 3) to compare parents- and offspring perceptions of ADHD, and 4) to examine the predictive ability of potential discrepant perceptions of ADHD on their coping and emotional well-being

Here’s something I prepared earlier: a review of the time to publication of cross-sectional reviews of smartphone health apps

Objectives Across a range of health conditions, apps are increasingly valued as tools for supporting the delivery and coordination of healthcare. Research-led cross-sectional reviews of apps are a potential resource to inform app selection in face of uncertainties around content quality, safety and privacy. However, these peer-reviewed publications only capture a snapshot of highly dynamic app stores and marketplaces. To determine the extent to which marketplace dynamics might impact the interpretation of app reviews, the current study sought to quantify the lag between the reported time of app assessment and publication of the results of these studies.Design Searches were conducted on MEDLINE, Embase and PsycINFO to identify published cross-sectional reviews of health, fitness or wellness apps. Publication timeline metadata were extracted, allowing the primary outcome measure, the delay between app store search and manuscript publication, to be calculated. A secondary measure, the time between search and manuscript submission, was also calculated where possible.Results After screening, 136 relevant cross-sectional app review studies were analysed. The median time to publication was 431 days (approximately 14 months, range: 42–1054 days). The median time to submission was 269 days (approximately 9 months, range: 5–874 days). Studies which downloaded apps typically took longer to publish (p=0.010), however the number of apps reviewed did not impact the time to publication (p=0.964). Studies which recommended specific apps were not published more rapidly (p=0.998).Conclusions Most health app reviews present data that are at least a year out-of-date at the time of publication. Given the high rate of turnover of health apps in public marketplaces, it may not be appropriate, therefore, for these reviews to be presented as a resource concerning specific products for commissioners, clinicians and the public. Alternative sources of information may be better calibrated to the dynamics of the app marketplace

Here's something I prepared earlier : a review of the time to publication of cross-sectional reviews of smartphone health apps

Objectives: Across a range of health conditions, apps are increasingly valued as tools for supporting the delivery and coordination of healthcare. Research-led cross-sectional reviews of apps are a potential resource to inform app selection in face of uncertainties around content quality, safety and privacy. However, these peer-reviewed publications only capture a snapshot of highly dynamic app stores and marketplaces. To determine the extent to which marketplace dynamics might impact the interpretation of app reviews, the current study sought to quantify the lag between the reported time of app assessment and publication of the results of these studies. Design: Searches were conducted on MEDLINE, Embase and PsycINFO to identify published cross-sectional reviews of health, fitness or wellness apps. Publication timeline metadata were extracted, allowing the primary outcome measure, the delay between app store search and manuscript publication, to be calculated. A secondary measure, the time between search and manuscript submission, was also calculated where possible. Results: After screening, 136 relevant cross-sectional app review studies were analysed. The median time to publication was 431 days (approximately 14 months, range: 42-1054 days). The median time to submission was 269 days (approximately 9 months, range: 5-874 days). Studies which downloaded apps typically took longer to publish (p=0.010), however the number of apps reviewed did not impact the time to publication (p=0.964). Studies which recommended specific apps were not published more rapidly (p=0.998). Conclusions: Most health app reviews present data that are at least a year out-of-date at the time of publication. Given the high rate of turnover of health apps in public marketplaces, it may not be appropriate, therefore, for these reviews to be presented as a resource concerning specific products for commissioners, clinicians and the public. Alternative sources of information may be better calibrated to the dynamics of the app marketplace

Here’s something I prepared earlier: A review of the time to publication of cross-sectional reviews of smartphone health apps

Objectives: Across a range of health conditions, apps are increasingly valued as tools for supporting the delivery and coordination of healthcare. Research-led cross-sectional reviews of apps are a potential resource to inform app selection in face of uncertainties around content quality, safety and privacy. However, these peer-reviewed publications only capture a snapshot of highly dynamic app stores and marketplaces. To determine the extent to which marketplace dynamics might impact the interpretation of app reviews, the current study sought to quantify the lag between the reported time of app assessment and publication of the results of these studies. Design: Searches were conducted on MEDLINE, Embase and PsycINFO to identify published cross-sectional reviews of health, fitness or wellness apps. Publication timeline metadata were extracted, allowing the primary outcome measure, the delay between app store search and manuscript publication, to be calculated. A secondary measure, the time between search and manuscript submission, was also calculated where possible. Results: After screening, 136 relevant cross-sectional app review studies were analysed. The median time to publication was 431 days (approximately 14 months, range: 42-1054 days). The median time to submission was 269 days (approximately 9 months, range: 5-874 days). Studies which downloaded apps typically took longer to publish (p=0.010), however the number of apps reviewed did not impact the time to publication (p=0.964). Studies which recommended specific apps were not published more rapidly (p=0.998). Conclusions: Most health app reviews present data that are at least a year out-of-date at the time of publication. Given the high rate of turnover of health apps in public marketplaces, it may not be appropriate, therefore, for these reviews to be presented as a resource concerning specific products for commissioners, clinicians and the public. Alternative sources of information may be better calibrated to the dynamics of the app marketplace