The association between early childhood onset epilepsy and attention-deficit hyperactivity disorder (ADHD) in 3237 children and adolescents with Autism Spectrum Disorder (ASD): a historical longitudinal cohort data linkage study.

Children and young people with Autism Spectrum Disorder (ASD) have an increased risk of comorbidities, such as epilepsy and Attention-Deficit/Hyperactivity Disorder (ADHD). However, little is known about the relationship between early childhood epilepsy (below age 7) and later ADHD diagnosis (at age 7 or above) in ASD. In this historical cohort study, we examined this relationship using an innovative data source, which included linked data from routinely collected acute hospital paediatric records and childhood community and inpatient psychiatric records. In a large sample of children and young people with ASD (N = 3237), we conducted a longitudinal analysis to examine early childhood epilepsy as a risk factor for ADHD diagnosis while adjusting for potential confounders, including socio-demographic characteristics, intellectual disability, family history of epilepsy and associated physical conditions. We found that ASD children and young people diagnosed with early childhood epilepsy had nearly a twofold increase in risk of developing ADHD later in life, an association which persisted after adjusting for potential confounders (adjusted OR = 1.72, CI95% = 1.13-2.62). This study suggests that sensitive monitoring of ADHD symptoms in children with ASD who have a history of childhood epilepsy may be important to promote early detection and treatment. It also highlights how linked electronic health records can be used to examine potential risk factors over time for multimorbidity in neurodevelopmental conditions.

Reciprocal developmental pathways between future-related thinking and symptoms of adolescent depression and anxiety: A systematic review and meta-analysis of longitudinal studies.

Adolescence is a time when important decisions about the future are made and vulnerability to mental health problems increases. We reviewed longitudinal studies examining the reciprocal pathways between future-related thinking (hopelessness, hope, optimism/positive future expectations) and adolescent depression and anxiety symptoms. Evidence from 22 studies (N = 10,682) found that negative future-related thinking predicted subsequent depression (r = 0.27, p < .001), an effect still significant after controlling for baseline depression (r = 0.23, p < .001). Higher hopelessness (r = 0.34, p < .001), lower hope (r = 0.16, p < .001), and reduced optimism/positive future expectations (r = 0.18, p < .001) were associated with subsequently increased depressive symptoms. Negative future-related thinking also predicted later increased anxiety symptoms (r = 0.15, p = .021). Concerning the reciprocal pathway, depressive symptoms were associated with later negative future-related thinking (r = 0.32, p < .001), which remained after baseline levels of future-related thinking were controlled (r = 0.07, p = .02). There were insufficient studies to infer reciprocal links between anxiety and future-related thinking. Our analyses provided evidence of a reciprocal developmental relationship between depressive symptoms and future-related thinking, implying a negative cycle. Identifying precursors of this cycle could provide the basis for depression prevention in adolescents and promote better decision-making about the future.

Young people's future thinking and mental health: The development and validation of the Adolescent Future Thinking Rating Scale.

OBJECTIVES: We aimed to develop and validate a new scale of future thinking and adolescent mental health-the Adolescent Future Thinking Rating Scale (AFTRS). METHODS: A provisional AFTRS was developed from interviews with 19 adolescents. It was completed by three samples: exploratory (n = 161) aged 16-21 years, who also completed established measures of future thinking, cognitive risk factors, depression and anxiety; replication (n = 209) aged 16-25 years; and test-retest (n = 102) aged 17-23 years. The reliability, convergent, predictive, and discriminant validity were examined. RESULTS: Exploratory factor analyses identified the AFTRS-18 and AFTRS-12. Both had three sub-scales: (i) Concerns about Maladaptive Future Thinking, (ii) Future Positivity, and (iii) Ability to Visualise the Future. Established future thinking measures were combined into two factors: Negative Future Emotions (Cognitive Triad Inventory-View of Future and Beck's Hopelessness Scale) and Immediacy Preference (Consideration of Future Consequences and Quick Delay Questionnaire). The AFTRS-18 and AFTRS-12 were similarly associated with both factors and with depression/anxiety. Internal consistency and test-retest reliability were high. CONCLUSIONS: The AFTRS-12 and AFTRS-18 are reliable and valid measures of the three key dimensions of adolescent future thinking and mental health. The first subscale remained significant in predicting depression and anxiety after controlling for general cognitive risks.

Links between mental health problems and future thinking from the perspective of adolescents with experience of depression and anxiety: a qualitative study.

BACKGROUND: Depression and anxiety are common during adolescence and could have detrimental impacts on young people's ability to make and implement plans for their future. However, to the best of our knowledge, no other study has adopted a qualitative approach in investigating these effects from the perspective of adolescents with lived experiences of depression and anxiety. We sought to understand how young people perceive and interpret the impact of mental health conditions on their thinking about the future. METHODS: We conducted semi-structured interviews with 19 adolescents aged 16-19 years in the UK (median age = 19, IQR = 1.5), who had a history of protracted periods of clinical or subclinical depression and/or anxiety. They were asked to reflect on how their ability to think about the future and the content of the future-related thinking was impacted during periods of poor mental health, compared with periods of feeling well. Interviews were transcribed verbatim and subjected to thematic content analysis. RESULTS: Five domains were identified. First, the impact of mood on future thinking capability focuses on reduced ability and motivation to engage in future thinking. Second, the impact of mood on images, thoughts, and feelings about the future includes the emotional valence of future-related thoughts, their vividness, structure, and the extent to which they intimated subjective feelings of control (i.e., agency). Third, social influences focuses on social factors that might ameliorate or exacerbate future thinking. Fourth, reflections on personal worries and expectations about the future captures personal interpretations of past worries and hopes and how future thinking affected mood. Finally, personal coping refers to how young people cope with the negative emotions that come with future thinking. CONCLUSIONS: This study provided a nuanced and granular account of how depression and anxiety impacted young people's future thinking based on their lived experiences. By highlighting the different ways that variations in future thinking were experienced as a function of depression and anxiety, our analysis highlighted new factors that should be considered in studies of adolescent mental health risk, which could inform the development of new therapeutic approaches.

Evaluation of Psychometric Properties and Factorial Structure of ADHD Module of K-SADS-PL in Children From Rural Kenya.

Objective: We determined the reliability of The Kiddie-Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime (K-SADS-PL) for screening and diagnosing ADHD in children. Method: K-SADS-PL was administered to 2,074 children in the community. Psychometric properties, factorial structure, and clinical validity of K-SADS-PL in screening or diagnosis of ADHD were examined. Results: Internal consistency was excellent for items in the screening interview (Macdonald's Omega [ω] = 0.89; 95% confidence interval [CI] [0.87, 0.94]) and diagnostic supplement (ω = 0.95; 95% CI [0.92, 0.99]). The standardized coefficients for items in the screening interview were acceptable (0.59-0.85), while fit indices for single factorial structure reached acceptable levels. Screening items were associated with high sensitivity (97.8%; 95% CI [97.2, 98.5%]) and specificity (94.0%; 95% CI [93.0, 95.0%]) for diagnosis of ADHD in the supplement. The test-retest and interinformant reliability as measured by intraclass correlation coefficient was good for most of the items. Conclusion: This large study shows that K-SADS-PL can be reliably used to screen and diagnose ADHD in children in Kenya.

Validating Screening Tool in Malayalam for Mental Disorders.

OBJECTIVES: Valid screening tools are needed to identify Indian children and adolescents with mental health problems, both for clinical or research purposes. The present study validated the Strengths and Difficulties Questionnaire (SDQ) in Malayalam across different informants and sub-scales. METHODS: A sample of 150 children and adolescents seen in a psychiatric clinic for children in Kerala, India was compared to a community sample of 1984 children from six surrounding urban and rural districts. Children in clinic and community samples were screened with the parent-report SDQ; those over 11 y completed the self-report SDQ. The community sample was also screened with the teacher-report SDQ and the clinical sample received formal diagnoses from a child psychiatrist blind to SDQ scores. The discriminative validity of the SDQ was investigated using Receiver Operator Characteristic (ROC) curves and by assessing Area Under the Curve (AUC). RESULTS: The SDQ discriminated reliably between clinical and community samples for the SDQ total score and its subscales. Within the clinic sample, 49 % of patients qualified for more than one broad diagnostic grouping. The SDQ discriminated between diagnostic categories in the clinic sample, but did so most effectively for conduct disorders. Based on the cut-offs that generated the highest combined value of sensitivity and specificity, the estimated rate of psychiatric disorder in the community sample was 13.6 % (parent-report) and 7.3 % (self-report). CONCLUSIONS: The SDQ is a useful screening tool for child and adolescent mental disorders for Malayalam speakers in Kerala, India.