Patterns of Homotypic and Heterotypic Continuity Between ADHD Symptoms, Externalising and Internalising Problems from Age 7 to 15

Abstract: ADHD presents a serious community-health problem through its links to a wide range of negative outcomes. These outcomes are exacerbated when ADHD symptoms co-occur with other mental health problems. Research evidence suggests high rates of co-comorbidity with a range of problems. However, there is a paucity of longitudinal research that examines the predictive links between ADHD symptoms and symptoms of other mental health problems. We examined a cross-lagged autoregressive model in order to assess homotypic and heterotypic continuity between ADHD symptoms, aggressive behavior, non-aggressive behavior problems and anxiety/depression in a community-based sample of 1571 youth (761 female, 810 male) assessed annually from age 7 to 13 and again at age 15. Consistently significant correlations between each pair of problem behaviors provided support for concurrent comorbidity. Furthermore, significant autoregressive pathways provided support for homotypic continuity. Support for heterotypic continuity was limited to ADHD symptoms predicting both aggressive behavior and non-aggressive behavior problems, but not vice versa. Our study highlights the importance of focusing on ADHD symptoms to identify children at risk not only for continued ADHD symptomatology but also a range of externalizing behavior problems including different types of aggression and non-aggressive behavior problems, such as rule-breaking. Identifying these patterns in a community-based sample provides support for the possibility of early identification of risk for a range of problem behaviors

Skin to skin interactions. Does the infant massage improve the couple functioning?

Transition to parenthood is a critical stage of life due to several changes the couple has to handle. A large body of studies described how transition to parenthood can be linked to the onset of depressive symptoms, as well as the perception of a low social support, and an increased stress, representing a risk for the early mother—baby relationship. Infant Massage (IM) emerged as an helpful tool to improve maternal skills in interacting with the baby, and leading toward a decreasing of post partum symptoms. However, a growing body of literature highlights that men also may experience post-partum diseases, representing an additional risk for the development of the baby. To date, no study observed the impact of the infant massage on both partners. The aim of the current qualitative research is to observe the impact of the IM on a single couple of parents at childbirth. Pre (Time 1) and post-intervention (Time 3) procedure has been established to observe the changes occurring over the time in the couple. In particular, each member of the couple filled out the EPDS, the BDI-II, the MSPSS and the PSI-SF both at Time 1 and at Time 3. The treatment (Time 2) was represented by the IM training, and lasted 4 weeks. Findings revealed a decrease in depressive symptoms in both partners, as well as an improvement of their perception of stress related to parental role. No changes has been detected with respect to the perception of social support. The IM seems to be a helpful approach to prevent the establishment of pathological conditions in new parents. Although no direct measures on the child were used, the current qualitative data seem to suggest that the IM may represent a valuable tool to prevent the onset of early negative outcomes of the baby. Further investigations and empirical data are needed to improve the knowledge in this field

The School Attachment Monitor—A novel computational tool for assessment of attachment in middle childhood

© 2021 Rooksby et al. This is an open access article distributed under the terms of the Creative Commons Attribution License.Background Attachment research has been limited by the lack of quick and easy measures. We report development and validation of the School Attachment Monitor (SAM), a novel measure for largescale assessment of attachment in children aged 5–9, in the general population. SAM offers automatic presentation, on computer, of story-stems based on the Manchester Child Attachment Story Task (MCAST), without the need for trained administrators. SAM is delivered by novel software which interacts with child participants, starting with warm-up activities to familiarise them with the task. Children’s story completion is video recorded and augmented by ‘smart dolls’ that the child can hold and manipulate, with movement sensors for data collection. The design of SAM was informed by children of users’ age range to establish their task understanding and incorporate their innovative ideas for improving SAM software. Methods 130 5–9 year old children were recruited from mainstream primary schools. In Phase 1, sixty-one children completed both SAM and MCAST. Inter-rater reliability and rating concordance was compared between SAM and MCAST. In Phase 2, a further 44 children completed SAM complete and, including those children completing SAM in Phase 1 (total n = 105), a machine learning algorithm was developed using a “majority vote” procedure where, for each child, 500 non-overlapping video frames contribute to the decision. Results Using manual rating, SAM-MCAST concordance was excellent (89% secure versus insecure; 97% organised versus disorganised; 86% four-way). Comparison of human ratings of SAM versus the machine learning algorithm showed over 80% concordance. Conclusions We have developed a new tool for measuring attachment at the population level, which has good reliability compared to a validated attachment measure and has the potential for automatic rating–opening the door to measurement of attachment in large populations.Peer reviewedFinal Published versio

Automating the Administration and Analysis of Psychiatric Tests: the Case of Attachment in School Age Children

This article presents the School Attachment Monitor, a novel interactive system that can reliably administer the Manch- ester Child Attachment Story Task (a standard psychiatric test for the assessment of attachment in children) without the supervision of trained professionals. Attachment prob- lems in children cause significant mental health issues and costs to society which technology has the potential to re- duce. SAM collects, through instrumented doll-play games, enough information to allow a human assessor to manually identify the attachment status of children. Experiments show that the system successfully does this in 87.5% of cases. In addition, the experiments show that an automatic approach based on deep neural networks can map the information collected into the attachment condition of the children. The outcome SAM matches the judgment of expert human asses- sors in 82.8% of cases. This is the first time an automated tool has been successful in measuring attachment. This work has significant implications for psychiatry as it allows profes- sionals to assess many more children cost effectively and to direct healthcare resources more accurately and efficiently to improve mental health