Digital
-
Diagnostic certainty during in-person and telehealth autism evaluations
Open Access paper from JCPP Advances – ‘Differences emerged in the frequency of diagnoses evaluated and made and diagnostic certainty for evaluations conducted via telehealth during the pandemic compared to in person before the pandemic, which likely impacted patients and reflect real-word challenges.’ Natasha N. Ludwig (pic) et al.
Read more -
JCPP Editorial: Volume 64, Issue 09, September 2023
Editorial: “Generative artificial intelligence and the ecology of human development” by Carlo Schuengel and Alastair van Heerden
Read more -
Communication and assessment apps for use with children and young people – recording
This free webinar was organised by ACAMH’s Adverse Childhood Experiences (ACEs) Special Interest Group, and led by Dr. David Glasgow of Child and Family Training.
Read more -
Identifying non-adult attention-deficit/hyperactivity disorder individuals using a stacked machine learning algorithm using administrative data population registers in a universal healthcare system
Open Access paper from JCPP Advances – ‘This research project aims to build a Machine Learning algorithm (ML) to predict first-time ADHD diagnosis, given that it is the most frequent mental disorder for the non-adult population.’ David Roche et al.
Read more -
Preventing Anxiety in the Children of Anxious Parents
In this Papers Podcast, Dr. Fiona Challacombe discusses her co-authored CAMH journal paper ‘Preventing anxiety in the children of anxious parents – feasibility of a brief, online, group intervention for parents of one- to three-year-olds’.
Read more -
Engaging Young People in Conversations Exploring the Impact of Their Online Use on Mental Health
Young people have better access to the internet than ever before, with those under 18 accounting for one in three internet users globally. Recently, The Royal College of the Psychiatrists in the UK advised that social media and online use should be considered in assessing risk of all young people they meet. However, it is currently unclear whether this advice has been implemented in practice.
Read more -
Technology Matters: Online, self-help single session interventions could expand current provision, improving early access to help for young people with depression symptoms, including minority groups
Open Access paper from the CAMH journal – ‘Current mental health service provision for young people was primarily designed based on an assumption of repeat attendance to enable access to interventions. This applies to in-person therapy and, in recent years, digitally provided apps and programmes. Yet, discontinuation after only one or two attendances or uses is a common problem. However, there is a different model, which is intentionally designing provision without assuming repeat attendance, that is, single session interventions.’ Maria E. Loades (pic) and Jessica L. Schleider
Read more -
Can we diagnose mental disorders in children? A large-scale assessment of machine learning on structural neuroimaging of 6916 children in the adolescent brain cognitive development study
Open Access paper from JCPP Advances – ‘Prediction of mental disorders based on neuroimaging is an emerging area of research with promising first results in adults. However, research on the unique demographic of children is underrepresented and it is doubtful whether findings obtained on adults can be transferred to children’. Richard Gaus (pic), Sebastian Pölsterl et al.
Read more -
Dr. Jennifer Martin
Dr. Jennifer Martin is Senior Programme Manager for Mental Health & Technology Research within NIHR MindTech MedTech Co-operative (MIC) at the University of Nottingham. She is an Associate Editor of CAMH, responsible for the Technology Matters section.
Read more -
The importance and challenges of improving early identification of language abilities: a commentary on Gasparini et al. (2023)
Open Access paper from the JCPP – ‘Finding early predictors of later language skills and difficulties is fraught with challenges because of the wide developmental variation in language. Gasparini et al. (Journal of Child Psychology and Psychiatry, 2023) aimed to address this issue by applying machine learning methods to parent reports taken from a large longitudinal database (Early Language in Victoria Study). This commentary highlights the advantages and challenges of identifying early predictors of language in this way, and discusses future directions that can build on this important contribution.’ Nicola Botting (pic) and Helen Spicer-Cain
Read more