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Lee KS, Gau SSF, Tseng WL. Autistic Symptoms, Irritability, and Executive Dysfunctions: Symptom Dynamics from Multi-Network Models. J Autism Dev Disord 2024; 54:3078-3093. [PMID: 37453959 DOI: 10.1007/s10803-023-05981-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/29/2023] [Indexed: 07/18/2023]
Abstract
Socio-cognitive difficulties in individuals with autism spectrum disorder (ASD) are heterogenuous and often co-occur with irritability symptoms, such as angry/grouchy mood and temper outbursts. However, the specific relations between individual symptoms are not well-represented in conventional methods analyzing aggregated autistic symptoms and ASD diagnosis. Moreover, the cognitive-behavioral mechanisms linking ASD to irritability are largely unknown. This study investigated the dynamics between autistic (Social Responsiveness Scale) and irritability (Affective Reactivity Index) symptoms and executive functions (Cambridge Neuropsychological Test Automated Battery) in a sample of children and adolescents with ASD, their unaffected siblings, and neurotypical peers (N = 345, aged 6-18 years, 78.6% male). Three complementary networks across the entire sample were computed: (1) Gaussian graphical network estimating the conditional correlations between symptom nodes; (2) Relative importance network computing relative influence between symptoms; (3) Bayesian directed acyclic graph estimating predictive directionality between symptoms. Networks revealed numerous partial correlations within autistic (rs = .07-.56) and irritability (rs = .01-.45) symptoms and executive functions (rs = -.83 to .67) but weak connections between clusters. This segregated pattern converged in all directed and supplementary networks. Plausible predictive paths were found between social communication difficulties to autism mannerisms and between "angry frequently" to "lose temper easily." Autistic and irritability symptoms are two relatively independent families of symptoms. It is unlikely that executive dysfunctions explain elevated irritability in ASD. Findings underscore the need for researching other mood and cognitive-behavioral bridge symptoms, which may inform individualized treatments for co-occurring irritability in ASD.
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Grants
- R00 MH110570 NIMH NIH HHS
- R00MH110570 NIMH NIH HHS
- NSC98-3112-B-002-004 Ministry of Science and Technology, Taiwan
- NSC99-2627- B-002-015 Ministry of Science and Technology, Taiwan
- NSC100-2627-B-002-014 Ministry of Science and Technology, Taiwan
- NSC101-2627-B- 002-002 Ministry of Science and Technology, Taiwan
- NSC 101-2314-B-002-136-MY3 Ministry of Science and Technology, Taiwan
- NHRI-EX104-10404PI National Health Research Institute, Taiwan
- NHRI-EX105-10404PI National Health Research Institute, Taiwan
- NHRI-EX106-10404PI National Health Research Institute, Taiwan
- NHRI-EX107-10404PI National Health Research Institute, Taiwan
- NHRI-EX108-10404PI National Health Research Institute, Taiwan
- NHRI-EX110-11002PI National Health Research Institute, Taiwan
- NHRI-EX111-11002PI National Health Research Institute, Taiwan
- 10R81918- 03101R892103 AIM for Top University Excellent Research Project
- 102R892103 AIM for Top University Excellent Research Project
- R00MH110570 NIMH NIH HHS
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Affiliation(s)
- Ka Shu Lee
- Department of Experimental Psychology, University of Oxford, Oxford, UK
- Yale Child Study Center, Yale School of Medicine, New Haven, CT, USA
| | - Susan Shur-Fen Gau
- Department of Psychiatry, National Taiwan University Hospital & College of Medicine, No. 7, Chung-Shan South Road, Taipei, 10002, Taiwan.
- Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan.
- Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan.
| | - Wan-Ling Tseng
- Yale Child Study Center, Yale School of Medicine, New Haven, CT, USA
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Watkeys OJ, O'Hare K, Dean K, Laurens KR, Harris F, Carr VJ, Green MJ. Cumulative comorbidity between neurodevelopmental, internalising, and externalising disorders in childhood: a network approach. Eur Child Adolesc Psychiatry 2024; 33:2231-2241. [PMID: 37815628 PMCID: PMC11255061 DOI: 10.1007/s00787-023-02312-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 09/25/2023] [Indexed: 10/11/2023]
Abstract
Cumulative comorbidity of mental disorders is common, but the extent and patterns of comorbid psychopathology in childhood are not well established. The current study aimed to elucidate the emergent patterns of cumulative mental disorder comorbidity in children using network analysis of diagnoses recorded between birth and age 12 years. Participants were 90,269 children (mean age 12.7 years; 51.8% male) within the New South Wales Child Development Study (NSW-CDS)-a longitudinal record-linkage cohort study of Australian children born in NSW between 2002 and 2005. Binary indicators for eight types of mental disorder were derived from administrative health records. Patterns of conditional association between mental disorders were assessed utilising network analysis. Of 90,269 children, 2268 (2.5%) had at least one mental disorder by age 12 years; of the 2268 children who had at least one mental disorder by age 12 years, 461 (20.3%) were diagnosed with two or more different disorders out of the eight disorder types included in analyses. All disorders were either directly or indirectly interconnected, with childhood affective and emotional disorders and developmental disorders being most central to the network overall. Mental disorder nodes aggregated weakly (modularity = 0.185) into two communities, representative of internalising and externalising disorders, and neurodevelopmental and sleep disorders. Considerable sex differences in the structure of the mental disorder comorbidity networks were also observed. Developmental and childhood affective and emotional disorders appear to be key to mental disorder comorbidity in childhood, potentially reflecting that these disorders share symptoms in common with many other disorders.
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Affiliation(s)
- Oliver J Watkeys
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, Faculty of Medicine and Health, University of New South Wales (UNSW), Level 1, AGSM Building, Kensington Campus, Sydney, Australia
- Neuroscience Research Australia, Sydney, Australia
| | - Kirstie O'Hare
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, Faculty of Medicine and Health, University of New South Wales (UNSW), Level 1, AGSM Building, Kensington Campus, Sydney, Australia
| | - Kimberlie Dean
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, Faculty of Medicine and Health, University of New South Wales (UNSW), Level 1, AGSM Building, Kensington Campus, Sydney, Australia
- Justice Health and Forensic Mental Network, Matraville, Australia
| | - Kristin R Laurens
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, Faculty of Medicine and Health, University of New South Wales (UNSW), Level 1, AGSM Building, Kensington Campus, Sydney, Australia
- School of Psychology and Counselling, Queensland University of Technology (QUT), Brisbane, Australia
| | - Felicity Harris
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, Faculty of Medicine and Health, University of New South Wales (UNSW), Level 1, AGSM Building, Kensington Campus, Sydney, Australia
| | - Vaughan J Carr
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, Faculty of Medicine and Health, University of New South Wales (UNSW), Level 1, AGSM Building, Kensington Campus, Sydney, Australia
- Neuroscience Research Australia, Sydney, Australia
- Department of Psychiatry, Monash University, Melbourne, Australia
| | - Melissa J Green
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, Faculty of Medicine and Health, University of New South Wales (UNSW), Level 1, AGSM Building, Kensington Campus, Sydney, Australia.
- Neuroscience Research Australia, Sydney, Australia.
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3
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Sun HL, Chen P, Zhang Q, Si TL, Li YZ, Zhu HY, Zhang E, Chen M, Zhang J, Su Z, Cheung T, Ungvari GS, Jackson T, Xiang YT, Xiang M. Prevalence and network analysis of internet addiction, depression and their associations with sleep quality among commercial airline pilots: A national survey in China. J Affect Disord 2024; 356:597-603. [PMID: 38484881 DOI: 10.1016/j.jad.2024.03.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 02/28/2024] [Accepted: 03/09/2024] [Indexed: 05/08/2024]
Abstract
OBJECTIVE Airline pilots are members of a unique occupational group that is often confronted with sleep routine disruptions, yet relatively few studies have examined their mental health status. This study assessed the prevalence and network structure of internet addiction, depression and sleep quality problems in commercial airline pilots. METHOD A total of 7055 airline pilots were included in analyses. Internet addiction and depression were measured with the Internet Addiction Test (IAT) and 9-item Patient Health Questionnaire (PHQ-9), respectively. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI). The network model was constructed based on an Ising model and its association with sleep quality was evaluated using a flow procedure. RESULTS Internet addiction, depression and sleep quality were common among airline pilots. The prevalence of internet addiction was 8.0 % (95 % CI: 7.3-8.6 %), while the rates of depression and poor sleep quality were 23.3 % (95 % CI: 22.3-24.2 %) and 33.0 % (95 % CI: 31.9-34.1 %), respectively. In the depression and internet addiction network model, "Fatigue" (PHQ4; Expected Influence (EI): 2.04) and "Depressed/moody/nervous only while being offline" (IAT20; EI: 1.76) were most central symptoms while "Fatigue" (PHQ4; Bridge EI: 1.30) was also the most important bridge symptom. The flow network model of sleep quality with internet addiction and depression showed that "Appetite" (PHQ5) had the strongest positive association with poor sleep quality. CONCLUSION Internet addiction, depression and sleep quality were common among airline pilots and warrant regular screening and timely treatment. Strategies to improve sleep hygiene may be useful in preventing onsets or exacerbations in depression and internet addiction among airline pilots.
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Affiliation(s)
- He-Li Sun
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao, SAR; Centre for Cognitive and Brain Sciences, University of Macau, Macao, SAR.
| | - Pan Chen
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao, SAR; Centre for Cognitive and Brain Sciences, University of Macau, Macao, SAR.
| | - Qinge Zhang
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders, National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Tong Leong Si
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao, SAR.
| | - Yan-Zhang Li
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao, SAR.
| | - Han-Yu Zhu
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao, SAR.
| | - Erliang Zhang
- School of Public Health, Shanghai Jiao Tong University, Shanghai, China.
| | - Minzhi Chen
- School of Public Health, Shanghai Jiao Tong University, Shanghai, China.
| | - Jie Zhang
- School of Public Health, Shanghai Jiao Tong University, Shanghai, China.
| | - Zhaohui Su
- School of Public Health, Southeast University, Nanjing, China.
| | - Teris Cheung
- School of Nursing, Hong Kong Polytechnic University, Hong Kong, SAR.
| | - Gabor S Ungvari
- Section of Psychiatry, University of Notre Dame Australia, Fremantle, Australia; Division of Psychiatry, School of Medicine, University of Western Australia, Perth, Australia
| | - Todd Jackson
- Department of Psychology, University of Macau, Macao, SAR.
| | - Yu-Tao Xiang
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao, SAR; Centre for Cognitive and Brain Sciences, University of Macau, Macao, SAR.
| | - Mi Xiang
- School of Public Health, Shanghai Jiao Tong University, Shanghai, China; Hainan Branch, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Sanya & School of Public Health, Shanghai, China.
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4
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Chau T, Tiego J, Brown LE, Mellahn OJ, Johnson BP, Arnatkeviciute A, Fulcher BD, Matthews N, Bellgrove MA. The distribution of parent-reported attention-deficit/hyperactivity disorder and subclinical autistic traits in children with and without an ADHD diagnosis. JCPP ADVANCES 2024; 4:e12223. [PMID: 38827983 PMCID: PMC11143953 DOI: 10.1002/jcv2.12223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 11/20/2023] [Indexed: 06/05/2024] Open
Abstract
Background Autistic traits are often reported to be elevated in children diagnosed with attention-deficit/hyperactivity disorder (ADHD). However, the distribution of subclinical autistic traits in children with ADHD has not yet been established; knowing this may have important implications for diagnostic and intervention processes. The present study proposes a preliminary model of the distribution of parent-reported ADHD and subclinical autistic traits in two independent samples of Australian children with and without an ADHD diagnosis. Methods Factor mixture modelling was applied to Autism Quotient and Conners' Parent Rating Scale - Revised responses from parents of Australian children aged 6-15 years who participated in one of two independent studies. Results A 2-factor, 2-class factor mixture model with class varying factor variances and intercepts demonstrated the best fit to the data in both discovery and replication samples. The factors corresponded to the latent constructs of 'autism' and 'ADHD', respectively. Class 1 was characterised by low levels of both ADHD and autistic traits. Class 2 was characterised by high levels of ADHD traits and low-to-moderate levels of autistic traits. The classes were largely separated along diagnostic boundaries. The largest effect size for differences between classes on the Autism Quotient was on the Social Communication subscale. Conclusions Our findings support the conceptualisation of ADHD as a continuum, whilst confirming the utility of current categorical diagnostic criteria. Results suggest that subclinical autistic traits, particularly in the social communication domain, are unevenly distributed across children with clinically significant levels of ADHD traits. These traits might be profitably screened for in assessments of children with high ADHD symptoms and may also represent useful targets for intervention.
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Affiliation(s)
- Tracey Chau
- Turner Institute for Brain and Mental HealthSchool of Psychological SciencesMonash UniversityClaytonVictoriaAustralia
| | - Jeggan Tiego
- Turner Institute for Brain and Mental HealthSchool of Psychological SciencesMonash UniversityClaytonVictoriaAustralia
| | - Louise E. Brown
- School of Nursing, Midwifery & ParamedicineCurtin UniversityBentleyWestern AustraliaAustralia
| | - Olivia J. Mellahn
- Turner Institute for Brain and Mental HealthSchool of Psychological SciencesMonash UniversityClaytonVictoriaAustralia
| | - Beth P. Johnson
- Turner Institute for Brain and Mental HealthSchool of Psychological SciencesMonash UniversityClaytonVictoriaAustralia
| | - Aurina Arnatkeviciute
- Turner Institute for Brain and Mental HealthSchool of Psychological SciencesMonash UniversityClaytonVictoriaAustralia
| | - Ben D. Fulcher
- School of PhysicsThe University of SydneyCamperdownWestern AustraliaAustralia
| | - Natasha Matthews
- School of PsychologyThe University of QueenslandSaint LuciaQueenslandAustralia
| | - Mark A. Bellgrove
- Turner Institute for Brain and Mental HealthSchool of Psychological SciencesMonash UniversityClaytonVictoriaAustralia
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5
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Sun HL, Chen P, Bai W, Zhang L, Feng Y, Su Z, Cheung T, Ungvari GS, Cui XL, Ng CH, An FR, Xiang YT. Prevalence and network structure of depression, insomnia and suicidality among mental health professionals who recovered from COVID-19: a national survey in China. Transl Psychiatry 2024; 14:227. [PMID: 38816419 PMCID: PMC11139988 DOI: 10.1038/s41398-024-02918-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 02/16/2024] [Accepted: 05/07/2024] [Indexed: 06/01/2024] Open
Abstract
Psychiatric syndromes are common following recovery from Coronavirus Disease 2019 (COVID-19) infection. This study investigated the prevalence and the network structure of depression, insomnia, and suicidality among mental health professionals (MHPs) who recovered from COVID-19. Depression and insomnia were assessed with the Patient Health Questionnaire (PHQ-9) and Insomnia Severity Index questionnaire (ISI7) respectively. Suicidality items comprising suicidal ideation, suicidal plan and suicidal attempt were evaluated with binary response (no/yes) items. Network analyses with Ising model were conducted to identify the central symptoms of the network and their links to suicidality. A total of 9858 COVID-19 survivors were enrolled in a survey of MHPs. The prevalence of depression and insomnia were 47.10% (95% confidence interval (CI) = 46.09-48.06%) and 36.2% (95%CI = 35.35-37.21%), respectively, while the overall prevalence of suicidality was 7.8% (95%CI = 7.31-8.37%). The key central nodes included "Distress caused by the sleep difficulties" (ISI7) (EI = 1.34), "Interference with daytime functioning" (ISI5) (EI = 1.08), and "Sleep dissatisfaction" (ISI4) (EI = 0.74). "Fatigue" (PHQ4) (Bridge EI = 1.98), "Distress caused by sleep difficulties" (ISI7) (Bridge EI = 1.71), and "Motor Disturbances" (PHQ8) (Bridge EI = 1.67) were important bridge symptoms. The flow network indicated that the edge between the nodes of "Suicidality" (SU) and "Guilt" (PHQ6) showed the strongest connection (Edge Weight= 1.17, followed by "Suicidality" (SU) - "Sad mood" (PHQ2) (Edge Weight = 0.68)). The network analysis results suggest that insomnia symptoms play a critical role in the activation of the insomnia-depression-suicidality network model of COVID-19 survivors, while suicidality is more susceptible to the influence of depressive symptoms. These findings may have implications for developing prevention and intervention strategies for mental health conditions following recovery from COVID-19.
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Affiliation(s)
- He-Li Sun
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, & Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao SAR, China
- Centre for Cognitive and Brain Sciences, University of Macau, Macao SAR, China
| | - Pan Chen
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, & Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao SAR, China
- Centre for Cognitive and Brain Sciences, University of Macau, Macao SAR, China
| | - Wei Bai
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Ling Zhang
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Yuan Feng
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Zhaohui Su
- School of Public Health, Southeast University, Nanjing, China
| | - Teris Cheung
- School of Nursing, Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Gabor S Ungvari
- Section of Psychiatry, University of Notre Dame Australia, Fremantle, WA, Australia
- Division of Psychiatry, School of Medicine, University of Western Australia, Perth, WA, Australia
| | - Xi-Ling Cui
- Department of Business Administration, Hong Kong Shue Yan University, Hong Kong, Hong Kong SAR, China
| | - Chee H Ng
- Department of Psychiatry, The Melbourne Clinic and St Vincent's Hospital, University of Melbourne, Richmond, VIC, Australia.
| | - Feng-Rong An
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.
| | - Yu-Tao Xiang
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, & Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao SAR, China.
- Centre for Cognitive and Brain Sciences, University of Macau, Macao SAR, China.
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Waldren LH, Leung FYN, Hargitai LD, Burgoyne AP, Liceralde VRT, Livingston LA, Shah P. Unpacking the overlap between Autism and ADHD in adults: A multi-method approach. Cortex 2024; 173:120-137. [PMID: 38387375 DOI: 10.1016/j.cortex.2023.12.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 12/11/2023] [Accepted: 12/18/2023] [Indexed: 02/24/2024]
Abstract
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.
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Affiliation(s)
| | | | | | | | - Van Rynald T Liceralde
- Department of Psychology and Human Development, Vanderbilt University, Nashville, TN, USA
| | - Lucy A Livingston
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Punit Shah
- Department of Psychology, University of Bath, Bath, UK.
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Harkness K, Bray S, Murias K. The role of stimulant washout status in functional connectivity of default mode and fronto-parietal networks in children with neurodevelopmental conditions. RESEARCH IN DEVELOPMENTAL DISABILITIES 2024; 146:104691. [PMID: 38340416 DOI: 10.1016/j.ridd.2024.104691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 01/22/2024] [Accepted: 01/24/2024] [Indexed: 02/12/2024]
Abstract
BACKGROUND Stimulant medication is the primary pharmacological treatment for attention dysregulation and is commonly prescribed for children with Attention-Deficit/Hyperactivity Disorder (ADHD) and Autism. Neuroimaging studies of these groups commonly use a 24-48-hour washout period to mediate the effects of stimulant medication on functional connectivity (FC) metrics. However, the impact of washout on functional connectivity has received limited study. METHODS We used fMRI data from participants with diagnosis of Autism and ADHD (and an off stimulant control) from the Adolescent Brain and Cognitive Development (ABCD) and Autism Brain Imaging Data Exchange (ABIDE) databases to explore the effect of simulant washout on FC. Connectivity within and between the default mode (DMN) and fronto-parietal networks (FPN) was examined, as these networks have previously been implicated in attention dysregulation and associated with stimulant medication usage. For each diagnostic group, we assessed effects in interconnectivity between DMN and FPN, intraconnectivity within DMN, and intraconnectivity within FPN. RESULTS We found no significant effect of medication status in intra- and inter-connectivity of the DMN and the FPN in either diagnostic group. IMPLICATIONS Our findings suggest that more information is needed about the effect of stimulant medication, and washout, on the FC of attention networks in clinical populations.
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Affiliation(s)
- Kelsey Harkness
- Department of Graduate Studies, University of Calgary, Canada; Hotchkiss Brain Institute, Cumming School of Medicine, Canada; Alberta Children's Hospital Research Institute, Canada.
| | - Signe Bray
- Hotchkiss Brain Institute, Cumming School of Medicine, Canada; Alberta Children's Hospital Research Institute, Canada; Cumming School of Medicine, University of Calgary, Canada
| | - Kara Murias
- Hotchkiss Brain Institute, Cumming School of Medicine, Canada; Alberta Children's Hospital Research Institute, Canada; Cumming School of Medicine, University of Calgary, Canada
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8
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Suen YN, Chau APY, Wong SMY, Hui CLM, Chan SKW, Lee EHM, Wong MTH, Chen EYH. Comorbidity of autism spectrum and attention deficit/hyperactivity disorder symptoms and their associations with 1-year mental health outcomes in adolescents and young adults. Psychiatry Res 2024; 331:115657. [PMID: 38056129 DOI: 10.1016/j.psychres.2023.115657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 11/27/2023] [Accepted: 12/01/2023] [Indexed: 12/08/2023]
Abstract
Autism spectrum (ASD) and attention deficit/hyperactivity disorders (ADHD) share genetic, neurological, and behavioural features. However, related research in Asia is limited. We collected self-reported ASD and ADHD symptoms from 2186 Hong Kong adolescents and young adults aged 15-24 years, among whom, 1200 provided 1-year data on mental health-related outcomes. Comparative and network analyses were performed. Rating scale cutoff scores were used to divide participants into ASD, ADHD, comorbid, and control groups. The prevalence rates of ASD, ADHD, and comorbidities in Hong Kong were 13.3 %, 10.6 %, and 2.7 %, respectively. Compared with the control group, the comorbid group experienced more psychotic-like experiences (PLEs), the ASD group had poorer functioning, and the ADHD group had higher depression and anxiety symptoms and a lower quality of life after 1 year. The ability to switch attention, preference for routines and difficulty with change, and problems with organisation and planning were positively associated with depressive symptoms, forgetfulness and working memory issues with anxiety symptoms, and heightened sensory input and difficulties in sustaining attention and task completion with PLEs after 1 year. Our findings provide insight into support strategies to address the needs of young Asians to improving their well-being and long-term outcomes.
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Affiliation(s)
- Yi Nam Suen
- School of Nursing, the University of Hong Kong, 5/F, Academic Building, 3 Sassoon Road, Pokfulam Road, Hong Kong, Hong Kong SAR, China.
| | | | - Stephanie Ming Yin Wong
- Department of Social Work and Social Administration, the University of Hong Kong, Hong Kong SAR, China
| | | | - Sherry Kit Wa Chan
- Department of Psychiatry, the University of Hong Kong, Hong Kong SAR, China; State Key Laboratory of Brain and Cognitive Sciences, the University of Hong Kong, Hong Kong SAR, China
| | - Edwin Ho Ming Lee
- Department of Psychiatry, the University of Hong Kong, Hong Kong SAR, China
| | | | - Eric Yu Hai Chen
- Department of Psychiatry, the University of Hong Kong, Hong Kong SAR, China
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9
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Sun HL, Chen P, Feng Y, Si TL, Lam MI, Lok KI, Chow IHI, Su Z, Cheung T, Tang YL, Jackson T, Sha S, Xiang YT. Depression and anxiety among Macau residents during the COVID-19 outbreak: A network analysis perspective. Front Psychiatry 2023; 14:1159542. [PMID: 37181879 PMCID: PMC10169684 DOI: 10.3389/fpsyt.2023.1159542] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 03/29/2023] [Indexed: 05/16/2023] Open
Abstract
Background The 2019 novel coronavirus disease (COVID-19) outbreak affected people's lifestyles and increased their risk for depressive and anxiety symptoms (depression and anxiety, respectively hereafter). We assessed depression and anxiety in residents of Macau during "the 6.18 COVID-19 outbreak" period and explored inter-connections of different symptoms from the perspective of network analysis. Methods In this cross-sectional study, 1,008 Macau residents completed an online survey comprising the nine-item Patient Health Questionnaire (PHQ-9) and seven-item Generalized Anxiety Disorder Scale (GAD-7) to measure depression and anxiety, respectively. Central and bridge symptoms of the depression-anxiety network model were evaluated based on Expected Influence (EI) statistics, while a bootstrap procedure was used to test the stability and accuracy of the network model. Results Descriptive analyses indicated the prevalence of depression was 62.5% [95% confidence interval (CI) = 59.47-65.44%], the prevalence of anxiety was 50.2% [95%CI = 47.12-53.28%], and 45.1% [95%CI = 42.09-48.22%] of participants experienced comorbid depression and anxiety. "Nervousness-Uncontrollable worry" (GADC) (EI = 1.15), "Irritability" (GAD6) (EI = 1.03), and "Excessive worry" (GAD3) (EI = 1.02) were the most central symptoms, while "Irritability" (GAD6) (bridge EI = 0.43), "restlessness" (GAD5) (bridge EI = 0.35), and "Sad Mood" (PHQ2) (bridge EI = 0.30) were key bridge symptoms that emerged in the network model. Conclusion Nearly half of residents in Macau experienced comorbid depression and anxiety during the 6.18 COVID-19 outbreak. Central and bridge symptoms identified in this network analysis are plausible, specific targets for treatment and prevention of comorbid depression and anxiety related to this outbreak.
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Affiliation(s)
- He-Li Sun
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Taipa, Macau SAR,, China
- Centre for Cognitive and Brain Sciences, University of Macau, Taipa, Macau SAR, China
| | - Pen Chen
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Taipa, Macau SAR,, China
- Centre for Cognitive and Brain Sciences, University of Macau, Taipa, Macau SAR, China
| | - Yuan Feng
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital and the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Tong Leong Si
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Taipa, Macau SAR,, China
- Centre for Cognitive and Brain Sciences, University of Macau, Taipa, Macau SAR, China
| | - Mei Ieng Lam
- Kiang Wu Nursing College of Macau, Macau, Macau SAR, China
| | - Ka-In Lok
- Faculty of Health Sciences and Sports, Macao Polytechnic University, Macau, Macau SAR, China
| | - Ines Hang Iao Chow
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Taipa, Macau SAR,, China
- Centre for Cognitive and Brain Sciences, University of Macau, Taipa, Macau SAR, China
| | - Zhaohui Su
- School of Public Health, Southeast University, Nanjing, China
| | - Teris Cheung
- School of Nursing, Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Yi-Lang Tang
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States
- Atlanta VA Medical Center, Atlanta, GA, United States
| | - Todd Jackson
- Department of Psychology, University of Macau, Macau, Macau SAR, China
| | - Sha Sha
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital and the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Yu-Tao Xiang
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Taipa, Macau SAR,, China
- Centre for Cognitive and Brain Sciences, University of Macau, Taipa, Macau SAR, China
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Xu XP, Wang W, Wan S, Xiao CF. Convergence mechanism of mindfulness intervention in treating attention deficit hyperactivity disorder: Clues from current evidence. World J Clin Cases 2022; 10:9219-9227. [PMID: 36159418 PMCID: PMC9477656 DOI: 10.12998/wjcc.v10.i26.9219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 06/26/2022] [Accepted: 07/29/2022] [Indexed: 02/05/2023] Open
Abstract
This paper reviews the underlying evidence for various aspects of the convergence mechanism of mindfulness intervention in attention deficit hyperactivity disorder (ADHD). There may be compatibility among various ADHD remission models and the therapeutic mechanism of mindfulness intervention in ADHD may be mainly via the convergence mechanism. However, neuroimaging-based analysis of the mechanisms of mindfulness intervention in treating ADHD is lacking. Differences in the efficacy of various subtypes of mindfulness intervention, and corresponding specific imaging changes need further investigation. Future research may focus on the neuroimaging features of specific mindfulness intervention subtypes.
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Affiliation(s)
- Xin-Peng Xu
- Universal Scientific Education and Research Network, Beijing 100088, China
| | - Wei Wang
- Beijing Anding Hospital, Capital Medical University, Beijing 100088, China
| | - Song Wan
- Universal Scientific Education and Research Network, Beijing 100088, China
| | - Chun-Feng Xiao
- Universal Scientific Education and Research Network, Beijing 100088, China
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11
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Tang S, Liu X, Nie L, Chen Z, Ran Q, He L. Diagnosis of children with attention-deficit/hyperactivity disorder (ADHD) comorbid autistic traits (ATs) by applying quantitative magnetic resonance imaging techniques. Front Psychiatry 2022; 13:1038471. [PMID: 36465303 PMCID: PMC9712964 DOI: 10.3389/fpsyt.2022.1038471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Accepted: 11/03/2022] [Indexed: 11/18/2022] Open
Abstract
OBJECTIVE To explore the feasibility of applying quantitative magnetic resonance imaging techniques for the diagnosis of children with attention-deficit/hyperactivity disorder (ADHD) comorbid autistic traits (ATs). METHODS A prospective study was performed by selecting 56 children aged 4-5 years with ADHD-ATs as the study group and 53 sex- and age-matched children with ADHD without ATs as the control group. All children underwent magnetic resonance scans with enhanced T2*- weighted magnetic resonance angiography (ESWAN), 3D-PCASL, and 3D-T1 sequences. Iron content and cerebral blood flow parameters were obtained via subsequent software processing, and the parameter values in particular brain regions in both groups were compared and analyzed to determine the characteristics of these parameters in children with ADHD-ATs. RESULTS Iron content and cerebral blood flow in the frontal lobe, temporal lobe, hippocampus, and caudate nucleus of children with ADHD-ATs were lower than those of children with ADHD without ATs (p < 0.05). Iron content and CBF values in the frontal lobe, temporal lobe and caudate nucleus could distinguish children with ADHD-ATs from those without ATs (AUC > 0.5, p < 0.05). CONCLUSIONS Quantitative magnetic resonance techniques could distinguish children with ADHD-ATs. TRIAL REGISTRATION This study protocol was registered at the Chinese clinical trial registry (ChiCTR2100046616).
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Affiliation(s)
- Shilong Tang
- Department of Radiology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing, China
| | - Xianfan Liu
- Department of Radiology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing, China
| | - Lisha Nie
- GE Healthcare, MR Research China, Beijing, China
| | - Zhuo Chen
- Department of Radiology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing, China
| | - Qiying Ran
- Department of Radiology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing, China
| | - Ling He
- Department of Radiology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing, China
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12
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Using network analysis to improve understanding and utility of the 10-item Autism-Spectrum Quotient. EXPERIMENTAL RESULTS 2022. [DOI: 10.1017/exp.2022.7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Abstract
The 10-item Autism-Spectrum Quotient (AQ10) is a measure of autistic traits used in research and clinical practice. Recently, the AQ10 has garnered critical attention, with research questioning its psychometric properties and clinical cutoff value. To help inform the utility of the measure, we conducted the first network analysis of the AQ10, with a view to gain a better understanding of its individual items. Using a large dataset of 6,595 participants who had completed the AQ10, we found strongest inter-subscale connections between communication, imagination, and socially relevant items. The nodes with greatest centrality concerned theory of mind differences. Together, these findings align with cognitive explanations of autism and provide clues about which AQ10 items show greatest utility for informing autism-related clinical practice.
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