Research on children and parents’ experiences of ADHD has grown in recent years, attracting attention to their subjective perception of ADHD as a disorder. Theoretical accounts of illness perception ...suggest that it is multi-dimensional, consisting of at least five core constructs (see the common-sense model of illness representations or CSM: Leventhal et al., in: Rachman (ed) Medical psychology, Pergamon, New York, vol 2, pp 7–30,
1980
, in: Baum, Taylor, Singer (eds) Handbook of psychology and health: social psychological aspects of health, Earlbaum, Hillsdale, vol 4, pp 219–252,
1984
). We suggest that the application of CSM in children/adolescents with ADHD and their parents may play an important role in understanding their coping behavior, treatment adherence, and emotional well-being. A systematic search identified 101 eligible studies that investigated the perception of ADHD among diagnosed children/adolescents and their parents. In general, these studies support the existence of the multiple facets of illness representations proposed by the CSM in both diagnosed youngsters and parents indicating substantial variability among both parents and youngsters on each of these facets. The comprehensive assessment of the representations of ADHD indicates imbalance attention to the different representations of ADHD in the literature; disproportional research attention has been paid to the perceived effectiveness of treatment (i.e.,
treatment control
dimension) compared to other illness representations (e.g.,
timeline
,
consequence,
and
coherence
), despite research showing their relevance to treatment adherence among other implications. The review identifies the limitation of existing relevant research, needed foci for future studies, specific testable hypotheses, and potential clinical implications of the multifaceted representations of ADHD among youngsters and carers alike.
Abstract
Despite decades of research on suicide risk factors in young people, there has been no significant improvement in our understanding of this phenomenon. This study adopts a positive deviance ...approach to identify individuals with suicide resilience and to describe their associated psychological and sociodemographic profiles. Australian young adults aged 18–25 years with suicidal thoughts (N = 557) completed an online survey covering sociodemographic, mental health status, emotion regulatory and suicide-related domains. Latent class analysis was used to identify the individuals with suicide resilience. The predictors of suicide resilience were assessed using logistic regression models. The results suggested that one in ten (n = 55) met the criteria for suicide resilience. Factors that had a significant association with suicide resilience included greater cognitive flexibility, greater self-efficacy in expressing positive affect, reduced use of digital technology and less self-harm and substance use as a response to emotional distress. This study identified the factors that may protect young adults with suicidal thoughts from progressing to suicide attempts. Suicide prevention programs might be optimised by shifting from a deficit-based to a strength-based approach through promoting cognitive flexibility, self-efficacy and reducing maladaptive coping.
Digital interventions that deliver psychological self-help provide the opportunity to reach individuals at risk of suicide who do not access traditional health services. Our primary objective was to ...test whether direct (targeting suicidality) and indirect (targeting depression) digital interventions are effective in reducing suicidal ideation and behaviours, and our secondary analyses assessed whether direct interventions were more effective than indirect interventions.
In this systematic review and meta-analysis, we searched online databases MEDLINE, PubMed, PsycINFO, and Cochrane CENTRAL for randomised controlled trials published between database inception to May 21, 2019. Superiority randomised controlled trials of self-guided digital interventions (app or web based, which delivered theory-based therapeutic content) were included if they reported suicidal ideation, suicidal plans, or suicide attempts as an outcome. Non-inferiority randomised controlled trials were excluded to ensure comparability of the effect. Data were extracted from published reports, and intention-to-treat data were used if available. The primary outcome was the difference in mean scores of validated suicidal ideation measures (Hedges'g) with the associated 95% CI for the analysis of digital intervention effectiveness on suicidal ideation. We also present funnel plots of the primary outcome measure (suicidal ideation) for direct and indirect interventions to assess for publication bias. We calculated I2 (with I2 CI) values to test heterogeneity. We used random-effects modelling for the meta-analyses to assess the primary and secondary outcomes. This study is registered with PROSPERO, CRD42018102084.
The literature search yielded 739 articles (including manual searching) for suicidality and 8842 articles for depression. After screening, 14 papers reporting on 16 studies were included in the narrative review and meta-analysis. The 16 studies (ten on direct interventions and six on indirect interventions) provided baseline data for 4398 participants. The primary outcome of overall post-intervention effect for suicidal ideation was small but significant immediately following the active intervention phase (Hedges'g −0·18, 95% CI −0·27 to −0·10, p<0·0001; I2=0%, I2 CI 0·0–47·9). The secondary objective, comparing direct and indirect interventions, showed that direct interventions (targeting suicidality) significantly reduced suicidal ideation at post-intervention (g −0·23, 95% CI −0·35 to −0·11, p<0·0001; I2=17·6%, I2 CI 0·0–58·6), but indirect interventions (targeting depression) failed to reach significance (g −0·12, 95% CI −0·25 to 0·01, p=0·071; I2=0%, I2 CI 0·0–30·7).
Self-guided digital interventions directly targeting suicidal ideation are effective immediately post-intervention. Indirect interventions were not significant for reducing suicidal ideation. Our findings suggest that digital interventions should be promoted and disseminated widely, especially where there is a lack of, or minimal access to, health services.
Australian National Health and Medical Research Council.
ObjectivesAcross 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.DesignSearches 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.ResultsAfter 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).ConclusionsMost 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.
Research into the causes and outcomes of attention deficit hyperactivity disorder (ADHD) has been extensive, yet little is known about the perception of ADHD as a disorder and its related outcomes ...among diagnosed youth. The present study applied the Common-Sense Model of Illness Representations (CSM) to examine the perception of ADHD and its association with quality of life (QoL), coping strategies, and treatment adherence among 63 diagnosed adolescents (10–18 years). Adolescents recruited from clinics, parent support groups, and an educational service completed self-report measures of the key constructs. Results indicated that adolescents generally perceive their ADHD as mildly threatening; four illness beliefs (perceived impact, personal control, timeline, and coherence) are significant predictors of coping and four (perceived impact, causes, personal control, and treatment control) are that of QoL. Adolescents who perceived minimal impact, expected longer duration, had strong sense of coherence, and believed in personal control of ADHD coped with the disorder more actively. Those who made weaker attribution to psychological and environmental causes, believed in personal control and the effectiveness of behavioral treatment enjoyed better QoL. In addition, female adolescents seem to experience more difficulties in the management of ADHD than male counterparts. These findings have potentially important clinical implications, suggesting that perceptions of ADHD related to the disorder's impact, duration, coherence, and personal control, may be important for clinicians to address when caring for adolescents with the disorder.
Psychology; Common-sense model; Quality of life; Adolescents; Coping; Perception of ADHD; Illness representations; ADHD
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.
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.
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.
Australian and New Zealand Clinical Trial Registry, ACTRN12619000855123. Registered on 31 May 2019. Clinical Trial Notification Scheme (CTN), CT-2019-CTN-02110-1-v1. Registered on 30 June 2019.
Objective:
Prior research suggests there are observable behaviours preceding suicide attempts in public places. However, there are currently no ways to continually monitor such sites, limiting the ...potential to intervene. In this mixed-methods study, we examined the acceptability and feasibility of using an automated computer system to identify crisis behaviours.
Methods:
First, we conducted a large-scale acceptability survey to assess public perceptions on research using closed-circuit television and artificial intelligence for suicide prevention. Second, we identified crisis behaviours at a frequently used cliff location by manual structured analysis of closed-circuit television footage. Third, we configured a computer vision algorithm to identify crisis behaviours and evaluated its sensitivity and specificity using test footage.
Results:
Overall, attitudes were positive towards research using closed-circuit television and artificial intelligence for suicide prevention, including among those with lived experience. The second study revealed that there are identifiable behaviours, including repetitive pacing and an extended stay. Finally, the automated behaviour recognition algorithm was able to correctly identify 80% of acted crisis clips and correctly reject 90% of acted non-crisis clips.
Conclusion:
The results suggest that using computer vision to detect behaviours preceding suicide is feasible and well accepted by the community and may be a feasible method of initiating human contact during a crisis.
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.
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.
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.
The trial recruitment started in May 2020. Data collection is currently ongoing.
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.
Australian New Zealand Clinical Trials Registry ACTRN12619001671156; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=378366.
PRR1-10.2196/23655.
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•The date hub proteins tend to occur within the intersection of real overlapping protein complexes.•We demonstrated that degree and transitivity can be used to predict a reliable list ...of date hub proteins.•A complex discovery algorithm after removing date hubs from PPI networks recalls more overlapping complexes that were missed earlier.•We proposed the “double-barrel strategy” to combine the complexes predicted before and after we remove date hubs.
Proteins physically interact with each other and form protein complexes to perform their biological functions. The prediction of protein complexes from protein–protein interaction (PPI) network is usually difficult when the complexes are overlapping with each other in a dense region of the network. To address the problem of predicting overlapping complexes, a previously proposed network–decomposition approach is promising. It decomposes a PPI network by e.g. removing proteins with high degree (hubs) which may participate in different complexes. This motivates us to examine a list of proteins, which bind their different partners at different time or at different location (viz. date hubs), manually collected from literature, for network decomposition. Results show that the CMC complex discovery algorithm after removing date hubs recalls more overlapping complexes that were missed earlier. Further improvement in performance is achieved when we predict date hub proteins based on simple network features and remove them from PPI networks.
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