Review: Attachment and attachment-related outcomes in preschool children – a review of recent evidence

Background Secure attachment is associated with optimal outcomes across all domains in childhood, and both insecure and disorganised attachment are associated with a range of later psychopathologies. Insecure and disorganised attachment are common, particularly in disadvantaged populations, pointing to the need to identify effective methods of addressing such problems. Aims This paper presents the findings of a review of secondary and primary studies evaluating the effectiveness of interventions aimed at improving attachment and attachment-related outcomes on a universal, targeted or indicated basis, which was undertaken as part of an update of the evidence base for a UK-based national programme targeting children aged 0–5 years (Healthy Child Programme). Method A systematic search of key electronic databases was undertaken to identify secondary and primary sources of data that addressed the research question and that had been published between 2008 and 2014; search sources included Cochrane Collaboration, NICE, EPPI Centre, Campbell Collaboration and PubMed, PsychInfo, CINAHL databases. Findings Six systematic reviews and 11 randomised controlled trials were identified that had evaluated the effectiveness of universal, selective or indicated interventions aimed at improving attachment and attachment-related outcomes in children aged 0–5 years. Potentially effective methods of improving infant attachment include parent–infant psychotherapy, video feedback and mentalisation-based programmes. Methods that appear to be effective in improving attachment-related outcomes include home visiting and parenting programmes. Conclusions A number of methods of working to promote attachment and attachment-related outcomes in preschool children are now being recommended as part of the Healthy Child Programme. The implications in terms of the role and contribution of practitioners working in child and adolescent mental health service are discusse

A comparison of the effectiveness of cognitive behavioural interventions based on delivery features for elevated symptoms of depression in adolescents: A systematic review

This is the final version. Available on open access from Wiley via the DOI in this record. Data availability statement: The data that support the findings of this study are available from the corresponding author upon reasonable request.Background Depression is a public health problem and common amongst adolescents. Cognitive behavioural therapy (CBT) is widely used to treat adolescent depression but existing research does not provide clear conclusions regarding the relative effectiveness of different delivery modalities. Objectives The primary aim is to estimate the relative efficacy of different modes of CBT delivery compared with each other and control conditions for reducing depressive symptoms in adolescents. The secondary aim is to compare the different modes of delivery with regard to intervention completion/attrition (a proxy for intervention acceptability). Search Methods The Cochrane Depression, Anxiety and Neurosis Clinical Trials Register was searched in April 2020. MEDLINE, PsycInfo, EMBASE, four other electronic databases, the CENTRAL trial registry, Google Scholar and Google were searched in November 2020, together with reference checking, citation searching and hand-searching of two databases. Selection Criteria Randomised controlled trials (RCTs) of CBT interventions (irrespective of delivery mode) to reduce symptoms of depression in young people aged 10–19 years with clinically relevant symptoms or diagnosis of depression were included. Data Collection and Analysis Screening and data extraction were completed by two authors independently, with discrepancies addressed by a third author. CBT interventions were categorised as follows: group CBT, individual CBT, remote CBT, guided self-help, and unguided self-help. Effect on depressive symptom score was estimated across validated self-report measures using Hedges' g standardised mean difference. Acceptability was estimated based on loss to follow-up as an odds ratio. Treatment rankings were developed using the surface under the cumulative ranking curve (SUCRA). Pairwise meta-analyses were conducted using random effects models where there were two or more head-to-head trials. Network analyses were conducted using random effects models. Main Results Sixty-eight studies were included in the review. The mean age of participants ranged from 10 to 19.5 years, and on average 60% of participants were female. The majority of studies were conducted in schools (28) or universities (6); other settings included primary care, clinical settings and the home. The number of CBT sessions ranged from 1 to 16, the frequency of delivery from once every 2 weeks to twice a week and the duration of each session from 20 min to 2 h. The risk of bias was low across all domains for 23 studies, 24 studies had some concerns and the remaining 21 were assessed to be at high risk of bias. Sixty-two RCTs (representing 6435 participants) were included in the pairwise and network meta-analyses for post-intervention depressive symptom score at post-intervention. All pre-specified treatment and control categories were represented by at least one RCT. Although most CBT approaches, except remote CBT, demonstrated superiority over no intervention, no approaches performed clearly better than or equivalent to another. The highest and lowest ranking interventions were guided self-help (SUCRA 83%) and unguided self-help (SUCRA 51%), respectively (very low certainty in treatment ranking). Nineteen RCTs (3260 participants) were included in the pairwise and network meta-analyses for 6 to 12 month follow-up depressive symptom score. Neither guided self-help nor remote CBT were evaluated in the RCTs for this time point. Effects were generally attenuated for 6- to 12-month outcomes compared to posttest. No interventions demonstrated superiority to no intervention, although unguided self-help and group CBT both demonstrated superiority compared to TAU. No CBT approach demonstrated clear superiority over another. The highest and lowest ranking approaches were unguided self-help and individual CBT, respectively. Sixty-two RCTs (7347 participants) were included in the pairwise and network meta-analyses for intervention acceptability. All pre-specified treatment and control categories were represented by at least one RCT. Although point estimates tended to favour no intervention, no active treatments were clearly inferior. No CBT approach demonstrated clear superiority over another. The highest and lowest ranking active interventions were individual CBT and group CBT respectively. Pairwise meta-analytic findings were similar to those of the network meta-analysis for all analyses. There may be age-based subgroup effects on post-intervention depressive symptoms. Using the no intervention control group as the reference, the magnitudes of effects appear to be larger for the oldest age categories compared to the other subgroups for each given comparison. However, they were generally less precise and formal testing only indicated a significant difference for group CBT. Findings were robust to pre-specified sensitivity analyses separating out the type of placebo and excluding cluster-RCTs, as well as an additional analysis excluding studies where we had imputed standard deviations. Authors' Conclusions At posttreatment, all active treatments (group CBT, individual CBT, guided self-help, and unguided self-help) except for remote CBT were more effective than no treatment. Guided self-help was the most highly ranked intervention but only evaluated in trials with the oldest adolescents (16–19 years). Moreover, the studies of guided self-help vary in the type and amount of therapist support provided and longer-term results are needed to determine whether effects persist. The magnitude of effects was generally attenuated for 6- to 12-month outcomes. Although unguided self-help was the lowest-ranked active intervention at post-intervention, it was the highest ranked at follow-up. This suggests the need for further research into whether interventions with self-directed elements enable young people to maintain effects by continuing or revisiting the intervention independently, and whether therapist support would improve long-term outcomes. There was no clear evidence that any active treatments were more acceptable to participants than any others. The relative effectiveness of intervention delivery modes must be taken into account in the context of the needs and preferences of individual young people, particularly as the differences between effect sizes were relatively small. Further research into the type and amount of therapist support that is most acceptable to young people and most cost-effective would be particularly useful.Jacobs FoundationNational Institute for Health and Care Research (NIHR

Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network

A tool that could suggest new personalized research directions and ideas by taking insights from the scientific literature could significantly accelerate the progress of science. A field that might benefit from such an approach is artificial intelligence (AI) research, where the number of scientific publications has been growing exponentially over the last years, making it challenging for human researchers to keep track of the progress. Here, we use AI techniques to predict the future research directions of AI itself. We develop a new graph-based benchmark based on real-world data -- the Science4Cast benchmark, which aims to predict the future state of an evolving semantic network of AI. For that, we use more than 100,000 research papers and build up a knowledge network with more than 64,000 concept nodes. We then present ten diverse methods to tackle this task, ranging from pure statistical to pure learning methods. Surprisingly, the most powerful methods use a carefully curated set of network features, rather than an end-to-end AI approach. It indicates a great potential that can be unleashed for purely ML approaches without human knowledge. Ultimately, better predictions of new future research directions will be a crucial component of more advanced research suggestion tools

Diagnosis and management of miliary tuberculosis: current state and future perspectives [Retraction]

Ray S, Talukdar A, Kundu S, Khanra D, Sonthalia N. Ther Clin Risk Mngmt. 2013;9:9–26.The editor of the Indian Journal of Medical Research has brought to our attention the unacknowledged re-use of significant portions of text in the above article. The source of much of the text appears to be from:Sharma SK, Mohan A, Sharma A. Challenges in the diagnosis and treatment of miliary tuberculosis. Indian J Med Res. 135, May 2012, pp 703–730.Dr Ray comments thus: “Regarding the similarities found we want to clarify that this apparent plagiarism is not an intentional act and likely to be factual error. In any way, we do not want to undermine scientific pursuit or vitiate the investigational spirit of hard work and creativity. Please be informed that the different portions of the review were written by different co-authors and most of them were postgraduate students at that time. It seems that they have taken materials/ideas from previously published source unaware of the issues of plagiarism.” This retraction relates to this pape