Attention-deficit hyperactivity disorder traits are a more important predictor of internalising problems than autistic traits

The promise of precision functional mapping for neuroimaging in psychiatry

Precision functional mapping (PFM) is a neuroimaging approach to reliably estimate metrics of brain function from individual people via the collection of large amounts of fMRI data (hours per person). This method has revealed much about the inter-individual variation of functional brain networks. While standard group-level studies, in which we average brain measures across groups of people, are important in understanding the generalizable neural underpinnings of neuropsychiatric disorders, many disorders are heterogeneous in nature. This heterogeneity often complicates clinical care, leading to patient uncertainty when considering prognosis or treatment options. We posit that PFM methods may help streamline clinical care in the future, fast-tracking the choice of personalized treatment that is most compatible with the individual. In this review, we provide a history of PFM studies, foundational results highlighting the benefits of PFM methods in the pursuit of an advanced understanding of individual differences in functional network organization, and possible avenues where PFM can contribute to clinical translation of neuroimaging research results in the way of personalized treatment in psychiatry.

Recognising and responding to physical and mental health issues in neurodivergent girls and women

People experience life and interact with others in many ways. The term 'neurodivergence' refers to variations from what is considered typical. Research and education into conditions that cooccur with neurodivergence are essential in shaping clinicians' approaches to people who may present with a wide range of symptoms. Neurodivergence may influence a person's style of communication, learning, attitudes, and behaviour, and they often experience inequity and rejection. This review highlights the huge burden of cooccurring conditions carried by neurodivergent women and girls whose medical issues have largely gone under the radar. We suggest how clinicians might increase their awareness of diagnosis and management of their problems with mutual benefit.

A Female-Specific Treatment Group for ADHD-Description of the Programme and Qualitative Analysis of First Experiences

Background: The diagnostics and treatment of attention-deficit/hyperactivity disorder (ADHD) in women remain insufficient. Fluctuations of reproductive hormones during the premenstrual period, postpartum period, and (peri)menopause are neglected, even though they impact ADHD symptoms and associated mood disorders. Therefore, we created a female-specific treatment group for women with ADHD and premenstrual worsening of ADHD and/or mood symptoms. Methods: We describe the group programme and underlying rationale, offering a qualitative analysis of the participants' evaluation. Results: The seven bi-weekly sessions foreground the menstrual cycle and address several ADHD-specific topics in relation to this cyclical pattern. Concurrently, women track their menstrual cycle and (fluctuating) ADHD and mood symptoms with an adjusted premenstrual calendar. In total, 18 women (25-47 years) participated in three consecutive groups. We analysed the evaluation of the last group. Participants experienced the group as a safe and welcoming space. Recognition was valued by all. The topics discussed were deemed valuable, and the structure suited them well. Completing the premenstrual calendar augmented the awareness and recognition of individual cyclical symptoms. A lifespan approach increased self-understanding. Participants took their menstrual cycle more seriously, prioritising self-acceptance and self-care. Conclusions: Exploring a cyclical approach in a group setting seems to be a positive addition to treatment for female ADHD.

Unpacking the overlap between Autism and ADHD in adults: A multi-method approach

The overlap between Autism and Attention-Deficit Hyperactivity Disorder (ADHD) is widely observed in clinical settings, with growing interest in their co-occurrence in neurodiversity research. Until relatively recently, however, concurrent diagnoses of Autism and ADHD were not possible. This has limited the scope for large-scale research on their cross-condition associations, further stymied by a dearth of open science practices in the neurodiversity field. Additionally, almost all previous research linking Autism and ADHD has focused on children and adolescents, despite them being lifelong conditions. Tackling these limitations in previous research, 5504 adults - including a nationally representative sample of the UK (Study 1; n = 504) and a large pre-registered study (Study 2; n = 5000) - completed well-established self-report measures of Autism and ADHD traits. A series of network analyses unpacked the associations between Autism and ADHD at the individual trait level. Low inter-item connectivity was consistently found between conditions, supporting the distinction between Autism and ADHD as separable constructs. Subjective social enjoyment and hyperactivity-impulsivity traits were most condition-specific to Autism and ADHD, respectively. Traits related to attention control showed the greatest Bridge Expected Influence across conditions, revealing a potential transdiagnostic process underlying the overlap between Autism and ADHD. To investigate this further at the cognitive level, participants completed a large, well-powered, and pre-registered study measuring the relative contributions of Autism and ADHD traits to attention control (Study 3; n = 500). We detected age- and sex-related effects, however, attention control did not account for the covariance between Autism and ADHD traits. We situate our findings and discuss future directions in the cognitive science of Autism, ADHD, and neurodiversity, noting how our open datasets may be used in future research.

Social Anhedonia Accounts for Greater Variance in Internalizing Symptoms than Autism Symptoms in Autistic and Non-Autistic Youth

PURPOSE

Social anhedonia is a transdiagnostic trait that reflects reduced pleasure from social interaction. It has historically been associated with autism, however, very few studies have directly examined behavioral symptoms of social anhedonia in autistic youth. We investigated rates of social anhedonia in autistic compared to non-autistic youth and the relative contributions of autism and social anhedonia symptoms to co-occurring mental health.

METHODS

Participants were 290 youth (Mage=13.75, Nautistic=155) ranging in age from 8 to 18. Youth completed a cognitive assessment and a diagnostic interview. Their caregiver completed questionnaires regarding symptoms of autism and co-occurring psychiatric conditions.

RESULTS

Autistic youth were more likely to meet criteria for social anhedonia than non-autistic youth. There was a significant positive relationship between age and social anhedonia symptom severity, but there was no association between sex and social anhedonia. Dominance analysis revealed that social anhedonia symptom severity had the strongest association with symptoms of depression and social anxiety, while symptoms of ADHD, generalized anxiety, and separation anxiety were most strongly associated with autism symptom severity.

CONCLUSION

This was the first study to tease out the relative importance of social anhedonia and autism symptoms in understanding psychiatric symptoms in autistic youth. Findings revealed higher rates of social anhedonia in autistic youth. Our results indicate that social anhedonia is an important transdiagnostic trait that plays a unique role in understanding co-occurring depression and social anxiety in autistic youth. Future research should utilize longitudinal data to test the transactional relationships between social anhedonia and internalizing symptoms over time.

Effectiveness of Cognitive Behavioral Therapy (CBT) on Psychological Distress among Mothers of Children with Autism Spectrum Disorder: The Role of Problem-Solving Appraisal

Mothers of children with autism spectrum disorder (ASD) face considerable psychological distress. Cognitive behavioral therapy (CBT) has shown promise in reducing caregiver burden, but evidence in the Arab world is lacking. Problem-solving appraisal training may optimize CBT's benefits. This study evaluated a tailored CBT program emphasizing the role of problem-solving appraisal in managing distress through the process of CBT. Sixty mothers were randomly allocated in a 1:1 ratio to either the CBT intervention group or the control group. The CBT group received 3-month sessions incorporating problem-solving appraisal training within a CBT curriculum from October 2022 to April 2023. Problem-solving techniques are focused on equipping individuals with the skills to identify, approach, and effectively resolve problems, leading to a reduction in stress levels and an improved capacity to cope with difficult situations. All mothers completed assessments of socio-demographics such as age, level of education, marital status, occupation, and adequacy of family income, the Depression Anxiety Stress Scale (DASS-21) and the Problem-Solving Inventory (PSI) before and after the program. The CBT group showed significant pre-to-post reductions in depression, anxiety, stress, and general psychological distress compared to controls (all p < 0.05). They also exhibited significant improvements in problem-solving confidence, approach-avoidance style and personal control (all p < 0.05). The customized CBT program markedly improved psychological well-being for mothers of children with ASD in Egypt. Incorporating problem-solving techniques may optimize CBT's benefits cross-culturally. These findings have implications for the implementation of evidence-based support programs for families impacted by ASD worldwide.

Mechanisms of cognitive disinhibition explain individual differences in adult attention deficit hyperactivity disorder traits

BACKGROUND

Attention deficit hyperactivity disorder (ADHD) in adults is strongly associated with psychiatric comorbidity and functional impairment. Here, we aimed to use a newly developed online cognitive battery with strong psychometric properties for measuring individual differences in three cognitive mechanisms proposed to underlie ADHD traits in adults: 1) attentional control - the ability to mobilize cognitive resources to stop a prepotent motor response; 2) information sampling/gathering - adequate sampling of information in a stimulus detection task prior to making a decision; and 3) shifting - the ability to adapt behavior in response to positive and negative contingencies.

METHODS

This cross-sectional and correlational study recruited 650 adults (330 males) aged 18-69 years (M = 33.06; MD = 31.00; SD = 10.50), with previously diagnosed ADHD (n = 329) and those from the general community without a history of ADHD (n = 321). Self-report measures of ADHD traits (i.e., inattention/disorganization, impulsivity, hyperactivity) and the cognitive battery were completed online.

RESULTS

Latent class analysis, exploratory structural equation modeling and factor mixture modeling revealed self-reported ADHD traits formed a unidimensional and approximately normally distributed phenotype. Bayesian structural equation modeling demonstrated that all three mechanisms measured by the cognitive battery, explained unique, incremental variance in ADHD traits, with a total of 15.9% explained in the ADHD trait factor.

CONCLUSIONS

Attentional control and shifting, as well as the less researched cognitive process of information gathering, explain individual difference variance in self-reported ADHD traits with potential to yield genetic and neurobiological insights into adult ADHD.

Training and specialisation of psychiatrists in ADHD

OBJECTIVE

To identify the level of training of Australian psychiatrists in Attention Deficit Hyperactivity Disorder (ADHD), and to compare the number of psychiatrists specialising in ADHD versus other psychiatric conditions on the basis of the prevalence of conditions, by interrogating the RANZCP 'Find a Psychiatrist' database.

CONCLUSION

Fewer psychiatrists listed in the RANZCP database specialise in ADHD than in many other psychiatric conditions. Given that 5% of the Australian population suffers from ADHD, the condition can have significant adverse outcomes and is a common comorbidity with other psychiatric conditions, the RANZCP Training Program would be improved by requiring an in-depth knowledge of ADHD. Further training in ADHD would assist many practising psychiatrists.

Assessing Autistic Traits in Toddlers Using a Data-Driven Approach with DSM-5 Mapping

Autistic spectrum disorder (ASD) is a neurodevelopmental condition that characterises a range of people, from individuals who are not able to speak to others who have good verbal communications. The disorder affects the way people see, think, and behave, including their communications and social interactions. Identifying autistic traits, preferably in the early stages, is fundamental for clinicians in expediting referrals, and hence enabling patients to access to required healthcare services. This article investigates various ASD behavioral features in toddlers and proposes a data process using machine-learning techniques. The aims of this study were to identify early behavioral features that can help detect ASD in toddlers and to map these features to the neurodevelopment behavioral areas of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). To achieve these aims, the proposed data process assesses several behavioral features using feature selection techniques, then constructs a classification model based on the chosen features. The empirical results show that during the screening process of toddlers, cognitive features related to communications, social interactions, and repetitive behaviors were most relevant to ASD. For the machine-learning algorithms, the predictive accuracy of Bayesian network (Bayes Net) and logistic regression (LR) models derived from ASD behavioral data subsets were consistent pinpointing to the suitability of ML techniques in predicting ASD.