Sun et al., (2021) note that autism is associated with a wide range of health-related risky behaviours (HRBs). They emphasize that research done so far focused on single behaviours and not a comprehensive study of it as a phenomenon exploring various risk factors. Thus they establish a need to comprehensively study various HRBs in adolescents with autism. They also discuss the drawbacks of available instruments to study HRBs, to navigate through which, they use Adolescents Health-Risky Behavior Inventory (AHRBI) developed by Wang et al. (2012).
Authors evaluate 150 adolescents with autism (12-19 years) and 150 neurotypical adolescents (age- and gender-matched controls enrolled from a public school). Two psychiatrists interview all the subjects using Schedule for Affective Disorders and Schizophrenia for School-Age Child-Present and Lifetime Version (K-SADS-PL) and evaluate subjects from autism group using Childhood Autism Rating Scale (CARS). All the participants complete AHRBI. While individuals with autism complete Zung Self-rating Anxiety Scale (SAS), Zung Self-rating Depression Scale (SDS), Self-Esteem Scale (SES), Wechsler Intelligence Scale and Theory of Mind (ToM) test, their parents fill in ASSQ (Autism Spectrum Screening Questionnaire). The team uses chi-square test to analyse differences among count data, Kolmogorov–Smirnov test to check normality of the sample, and Mann–Whitney U test and Spearman’s rank correlation analysis for making comparisons. They conduct multivariate regression analysis to explore factors associated with HRBs in the autism group.
Authors identify that the total AHRBI scores and scores on “aggression and violence (AV)”, “suicide or self-injury (SS)”, “health-compromising behavior (HCB)”, and “unprotected sex (US)” subscales in the autism group are significantly higher than those in the control group (Z value = − 4.58 ~ − 2.26, all P < 0.05). Different HRBs have different risk factors. Overall, they enumerate anxiety, depression, low self-esteem, low IQ score, low ToM test score, increasing age, and communication disorder as risk factors for HRBs in adolescents with autism. The team concludes that adolescents with autism are more likely to have HRBs. They recommend that comprehensive intervention should be done with more attention to HRBs. In view, of relatively small sample size, possible bias due to most subjects with autism being male and all enrolled from a single medical centre, and limited number of independent variables used in the multivariate regression analysis, they suggest future studies addressing these drawbacks to confirm their findings.
Daniunaite et al., (2021) discuss the negative impact of COVID-19 pandemic on adolescent mental health and wellbeing by referring to recent studies. They highlight that majority of the studies are cross-sectional in nature and further research is needed to understand the stability and patterns of change. Thus, they set a context for their current longitudinal study to assess the impact of the COVID-19 pandemic and accompanying countermeasures on adolescent mental health and patterns of change.
Authors analyse a subsample of 331 adolescents (12-16 years) from the first two waves of the longitudinal study Stress and Resilience in Adolescent (STAR-A). They obtain data at two timepoints: baseline/pre-test (T1, wave 1, March-May 2019) and 18 months later at six months since the first national lockdown in Lithuania (T2, wave 2, 24 September to 21 October 2020). The participants are from seven general schools from across Lithuania. The team assesses psychosocial functioning at T1 and T2 using the Strengths and Difficulties Questionnaire (SDQ). In addition, they measure psychological resilience and lifetime abuse exposure at T1 using The Resilience Scale (RS-14) and questionnaire developed by the Norwegian Center for Violence and Traumatic Stress Studies (NKVTS) respectively. They analyse data using multivariate latent change modelling and latent class change approaches (by controlling for child abuse experience and resilience) to identify patterns of change.
Overall, authors record a small but significant increase in hyperactivity/inattention, emotional symptoms, and prosocial behavior. Baseline rates of emotional problems and prosocial behavior are higher in girls than boys. They identify three change profiles: strained – most subjects (70.7%) report a significant but small increase in hyperactivity/inattention, emotional symptoms and conduct problems; peer-problems – almost one in five adolescents (19.6%) experiences an increase in peer-problems; and social adaptation – almost one in ten participants (9.7%) reports a significant decrease in peer relationship problems and increase in prosocial behaviour. They attribute these changes to prevailing circumstances such as – school closures, restrictions on after-school activities, and changes in interpersonal relationships.
Authors highlight the importance of supporting adolescents to deal with pandemic-related challenges. They mention the strengths of their study viz. longitudinal design, high response rates and inclusion of pre-pandemic measures; and also its limitations – data based on self-report measures and not multi-informant, and the fact that results cannot be attributed exclusively to the pandemic as many life events could occur in the long interval period of 18 months between the two timepoints. They recommend studies that negate these limitations and longitudinal research in the post-pandemic period to study adolescents’ functioning trajectories. They underscore the value of such research in societal preparedness for future pandemics.
Egbegi et al., (2021) draw attention to high prevalence and adverse effects of sleep difficulties in adolescents and the treatment gap especially in Low and Middle Income Countries (LMICs) like Nigeria. They note that the evidence-base for psychological interventions for adolescent insomnia is good in High Income Countries (HICs). However, despite sufficient evidence for Cognitive Behavioural Therapy for Insomnia (CBT-I), it needs adaption to be accessible and effective due to socio-ecological differences between HICs and LMICs. They conduct a pilot study to evaluate a locally adapted manualized intervention that derives its components from CBT-I.
The team manualizes the intervention by making adaptations to improve feasibility, cost-effectiveness, and accessibility such as shortening the course to 5-sessions, delivering it in groups and in schools, delivery by a professional with no prior specialist certification in CBT-I, emphasis on certain components such as psychoeducation and other contextual adaptations to suit general living arrangements. They carry out a parallel two-group intervention study (January-March 2020) with a sample of 50 in-school adolescents (13-17 years) from four secondary schools (two government and two private schools) of Southern Nigeria. They use balloting to assign one government school and one private school as “intervention sites” and the other two schools as waiting-list controls. Twenty-five subjects with highest ranked scores on the Insomnia Severity Index (ISI) in the two intervention schools are selected and dyadically matched on gender, ISI scores, and type of school with 25 participants from the control schools.
The intervention consists of weekly group-based sessions of 45 min each delivered in their schools (during school-breaks) over 5 weeks. Twenty-one subjects in the intervention group and 16 controls complete the post-intervention outcome measures [ISI, Short Mood and Feelings Questionnaire (SMFQ), Sleep Hygiene Questionnaire (SHQ), Knowledge of Sleep Questionnaire (KSQ)]. The primary outcome is ISI score at sixth week. The secondary outcomes are sleep onset latency (SOL), total sleep duration (TSD), depressive symptoms, sleep hygiene, and knowledge about sleep. Authors use Kolmogorov–Smirnov and Shapiro-Wilk tests to assess normality of all continuous measures, t-test for continuous variables and Chi-square or Fisher’s Exact tests for categorical variables and Analysis of covariance (ANCOVA) to evaluate treatment effect. They prefer Per Protocol analysis over intent-to-treat analysis to negate disproportionate Covid-19-related loss of post-intervention data in the control group.
Authors report a significant reduction of insomnia, shorter SOL, longer TSD, lower depressive symptoms and higher knowledge of sleep in the intervention group as compared to the control group. They point out that psychoeducation constituted a significant proportion of their manualized intervention and was the component that adolescents liked most. They state that this study is the first from an African setting to support effectiveness of CBT-based intervention for adolescents with insomnia. In view of the methodological limitations such as small sample size, data based on self-report measures, lack of objective measurements, and single post-intervention data point, they recommend larger controlled trials with actigraphy measured outcomes, and extended follow-up.
Daniunaite, I., Truskauskaite-Kuneviciene, I., Thoresen, S. et al. Adolescents amid the COVID-19 pandemic: a prospective study of psychological functioning. Child Adolesc Psychiatry Ment Health 15, 45 (2021). https://doi.org/10.1186/s13034-021-00397-z.
Egbegi, D.R., Bella-Awusah, T., Omigbodun, O. et al. A controlled trial of Cognitive Behavioural Therapy-based strategies for insomnia among in-school adolescents in southern Nigeria. Child Adolesc Psychiatry Ment Health 15, 52 (2021). https://doi.org/10.1186/s13034-021-00406-1.
Sun, Y., Li, X., Xu, L. et al. Health-related risky behaviors in Chinese adolescents with autism: a cross-sectional study. Child Adolesc Psychiatry Ment Health 15, 39 (2021). https://doi.org/10.1186/s13034-021-00390-6.
Wang M, Yi J, Cai L, et al. Development and psychometric properties of the health-risk behavior inventory for Chinese adolescents. BMC Med Res Methodol. 2012. https:// doi. org/ 10. 1186/ 1471- 2288- 12- 94.