Network Analysis of Teachers Views of ADHD Symptoms and Their Associations with Global Functioning among Adolescents-Journal of Psychiatry and Brain Science-CSCIED科技核心评价数据库-手机版

Network Analysis of Teachers Views of ADHD Symptoms and Their Associations with Global Functioning among Adolescents

Network Analysis of Teachers Views of ADHD Symptoms and Their Associations with Global Functioning among Adolescents

ES评分 0 浏览量：158 下载量：0

全文阅读下载引用收藏

DOI	10.20900/jpbs.20250005
刊名	Journal of Psychiatry and Brain Science JPBS
年，卷(期)	2025, 10(4)
作者	Rapson Gomez*,Stephen Houghton,Andre Gomez,
作者单位	School of Health and Biomedical Sciences, Federation University Australia, Ballarat, VIC 3353, Australia ; Graduate School of Education, University of Western Australia, Crawley, WA 6009, Australia ; Wings Wellness Psychology Clinic, Melbourne, VIC 3029, Australia ;
摘要	Based on teacher ratings of Attention Deficit Hyperactivity Disorder (ADHD) symptoms, this study utilized network analyses to examine how teachers view ADHD symptoms and their associations with global functioning in a group of adolescents. Teachers (N = 934) rated the ADHD symptoms and global functioning of children (6 to 12 years; males = 46.68%), from the Malaysian general community. The network findings showed that for the inattention symptom group teachers viewed “making careless mistakes” and “difficulty following instructions” as most central; and for the hyperactive/impulsive symptom group, they viewed “on the go/driven by a motor” and “difficulty waiting for turn” as most central. Also, their ratings indicated that “trouble paying attention”, “difficulty following instructions”, “trouble getting organized”, “am often forgetful”, “runs/climbs when not expected” and “difficult waiting for turn” demonstrated the theoretically expected associations with global functioning. Overall, these findings should be prioritized when interpreting and using teachers’ reports of adolescents’ ADHD when used for assessment, diagnosis and treatment of adolescent ADHD. As this study is the first to use network analysis to examine teacher ratings of ADHD symptoms, the findings provide new contributions to the ADHD literature, in particular how teachers view ADHD in adolescents. However, in view of a number of study limitations, we offer our findings as preliminary.
Abstract	Based on teacher ratings of Attention Deficit Hyperactivity Disorder (ADHD) symptoms, this study utilized network analyses to examine how teachers view ADHD symptoms and their associations with global functioning in a group of adolescents. Teachers (N = 934) rated the ADHD symptoms and global functioning of children (6 to 12 years; males = 46.68%), from the Malaysian general community. The network findings showed that for the inattention symptom group teachers viewed “making careless mistakes” and “difficulty following instructions” as most central; and for the hyperactive/impulsive symptom group, they viewed “on the go/driven by a motor” and “difficulty waiting for turn” as most central. Also, their ratings indicated that “trouble paying attention”, “difficulty following instructions”, “trouble getting organized”, “am often forgetful”, “runs/climbs when not expected” and “difficult waiting for turn” demonstrated the theoretically expected associations with global functioning. Overall, these findings should be prioritized when interpreting and using teachers’ reports of adolescents’ ADHD when used for assessment, diagnosis and treatment of adolescent ADHD. As this study is the first to use network analysis to examine teacher ratings of ADHD symptoms, the findings provide new contributions to the ADHD literature, in particular how teachers view ADHD in adolescents. However, in view of a number of study limitations, we offer our findings as preliminary.
关键词	teachers views of ADHD symptoms; global functioning; network analysis; teacher ratings; centrality; edge weights
KeyWord	teachers views of ADHD symptoms; global functioning; network analysis; teacher ratings; centrality; edge weights
基金项目
页码	-

参考文献
相关文献

1.American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 5th ed. Washington (DC, US): American Psychiatric Association; 2013.

2.American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Washington (DC, US): American Psychiatric Association; 1994.

3.American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 4th ed. TR. Washington (DC, US): American Psychiatric Association; 2000.

4.Borsboom D. A network theory of mental disorders. World Psychiatry. 2017;16:5-13.

5.Borsboom D, Cramer AO. Network analysis: An integrative approach to the structure of psychopathology. Annu Rev Clin Psychol. 2013;9:91-121. doi: 10.1146/annurev-clinpsy-050212-185608.

6.Boschloo L, van Borkulo CD, Rhemtulla M, Keyes KM, Borsboom D, Schoevers RA. The network structure of symptoms of the diagnostic and statistical manual of mental disorders. PLoS ONE. 2015;10(9):e0137621. doi: 10.1371/journal.pone.0137621.

7.Epskamp S, Fried EI. A tutorial on regularized partial correlation networks. Psychol Methods. 2018;23:617-63. doi: 10.1037/met0000167.

8.Epskamp S, Borsboom D, Fried EI. Estimating psychological networks and their accuracy: A tutorial paper. Behav Res Methods. 2018;50:195-212. doi: 10.3758/s13428-017-0862-1.

9.von Klipstein L, Borsboom D, Arntz A. The exploratory value of cross-sectional partial correlation networks: Predicting relationships between change trajectories in borderline personality disorder. PLoS ONE. 2021;16(7):e0254496. doi: 10.1371/journal.pone.0254496.

10.Epskamp S, Rhemtulla M, Borsboom D. Generalized network psychometrics: Combining network and latent variable models. Psychometrika. 2017;82:904-27. doi: 10.1007/s11336-017-9557-x.

11.Bringmann LF, Eronen MI. Don’t blame the model: Reconsidering the network approach to psychopathology. Psychol Rev. 2018;125(4):606-15. doi: 10.1037/rev0000108.

12.Hevey D. Network analysis: A brief overview and tutorial. Health Psychol Behav Med. 2018;6:301-28. doi: 10.1080/21642850.2018.1521283.

13.Robinaugh DJ, Millner AJ, McNally RJ. Identifying highly influential nodes in the complicated grief network. J Abnorm Psychol. 2016;125(6):747-57. doi: 10.1037/abn0000181.

14.Spiller TR, Levi O, Neria Y, Suarez-Jimenez B, Bar-Haim Y, Lazarov A. On the validity of the centrality hypothesis in cross-sectional between-subject networks of psychopathology. BMC Med. 2020; 18(1):297.

15.McNally RJ, Robinaugh DJ, Wu GW, Wang L, Deserno MK, Borsboom D. Mental disorders as causal systems: A network approach to posttraumatic stress disorder. Clin Psychol Sci. 2015;3(6):836-49.

16.Rodebaugh T L, Tonge NA, Piccirillo ML, Fried E, Horenstein A, Morrison AS, et al. Does centrality in a cross-sectional network suggest intervention targets for social anxiety disorder? J Cons Clin Psychol. 2018;86(10):831.

17.Ruzzano L, Borsboom D, Geurts HM. Repetitive behaviors in autism and obsessive–compulsive disorder: New perspectives from a network analysis. J Autism Dev Dis. 2015;45(1):192-202.

18.Liu L, Wang Y, Chen W, Gao Y, Li H, Wang Y, et al. Network analysis of 18 attention-deficit/hyperactivity disorder symptoms suggests the importance of “Distracted” and “Fidget” as central symptoms: Invariance across age, gender, and subtype presentations. Front Psychiatry. 2022;13:974283. doi: 10.3389/fpsyt.2022.974283.

19.Martel MM, Levinson CA, Langer JK, Nigg JT. A network analysis of developmental change in ADHD symptom structure from preschool to adulthood. Clin Psychol Sci. 2016;4(6):988-1001. doi: 10.1177/2167702615618664.

20.Preszler J, Burns GL, Becker SP, Servera M. Multisource longitudinal network and latent variable model analyses of ADHD symptoms in children. J Clin Child Adolesc Psychol. 2022;51(2):211-8. doi: 10.1080/15374416.2020.1756297.

21.Silk TJ, Malpas CB, Beare R, Efron D, Anderson V, Hazell P, et al. A network analysis approach to ADHD symptoms: More than the sum of its parts. PLoS ONE. 2019;14(1):1-17. doi: 10.1371/journal.pone.0211053.

22.Preszler J, Burns GL. Network analysis of ADHD and ODD symptoms: Novel insights or redundant findings with the latent variable model? J Abnorm Child Psychol. 2019;47:1599-610. doi: 10.1007/s10802-019-00549-y.

23.Lee CA, Goh PK, Shelton CR, Hartung CM. Networks of ADHD and SCT symptoms in emerging adulthood. J Atten Disord. 2022;26(7):991-1000. doi: 10.1177/10870547211045743.

24.Goh PK, Martel MM, Barkley RA. Clarifying ADHD and sluggish cognitive tempo item relations with impairment: A network analysis. J Abnorm Child Psychol. 2020;48:1047-61. doi: 10.1007/s10802-020-00655-2

25.van Borkulo C, Boschloo L, Borsboom D, Penninx BW, Waldorp LJ, Schoevers RA. Association of symptom network structure with the course of depression. JAMA Psych. 2015;72(12):1219-26.

26.American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorder. 5th ed. TR. Washington (DC, US): American Psychiatric Association; 2022.

27.Burns GL, Walsh JA, Gomez R, de Moura MA. Understanding source effects in ADHD rating scales: Reply to DuPaul. Psychol Assess. 2003;15:118–9. doi: 10.1037/1040-3590.15.1.118.

28.Gomez R, Burns GL, Walsh JA, Hafetz N. A. Multitrait-multisource confirmatory factor analytic approach to the construct validity of ADHD and ODD rating scales with Malaysian children. J Abnorm Child Psychol. 2005;33:241-54.

29.Gomez R. Australian parent and teacher ratings of the DSM-IV ADHD symptoms: Differential symptom functioning and parent-teacher agreement and differences. J Atten Disord. 2007;11:17-27.

30.Wolraich ML, Lambert EW, Bickman L, Simmons T, Doffing MA, Worley KA. Assessing the impact of parent and teacher agreement on diagnosing attention-deficit hyperactivity disorder. J Dev Behav Pediatrics. 2004;25(1):41-7.

31.Antrop I, Roeyers H, Oosterlaan J, Van Oost P. Agreement between parent and teacher ratings of disruptive behavior disorders in children with clinically diagnosed ADHD. J Psychopathol Behav Assess. 2002;24:67-73.

32.Gomez R, Harvey J, Quick C, Scharer I, Harris G. DSM-IV AD/HD: Confirmatory factor models, prevalence, and gender and age differences based on parent and teacher ratings of Australian primary school children. J Child Psychol Psychiatry.1999;40:265-274

33.Barkley RA, Murphy KR. Attention-Deficit Hyperactivity Disorder: A Clinical Workbook. 2nd ed. New York (NY, US): Guilford; 1998.

34.Setterberg S, Bird H, Gould M, Shaffer D, Fisher P. Parent and interviewer version of the Children’s Global Assessment Scale. New York (NY, US): Columbia University; 1992.

35.Bird HR, Andrews H, SchwabStone M, Goodman S, Dulcan M, Richters J, et al. Global measures of impairment for epidemiologic and clinical use with children and adolescents. Int J Methods Psychiatr Res. 1996;6:295-307.

36.Gomez R, Vance A. Parent ratings of ADHD symptoms: Differential symptom functioning across Malaysian Malay and Chinese children. J Abnorm Child Psychol. 2008;36:955-67.

37.Muthen LK, Muthen BO. Mplus User’s Guide. 7th ed. Los Angeles (CA, US): Muthen & Muthen; 2012.

38.Hu LT, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct Equ Modeling. 1999;6:1-55. doi: 10.1080/10705519909540118.

39.Tavakol M, Wetzel A. Factor analysis: A means for theory and instrument development in support of construct validity. Int J Med Educ. 2020;6:245-7. doi: 10.5116/ijme.5f96.0f4a.

40.Constantin MA, Schuurman NK, Vermunt JK. A general Monte Carlo method for sample size analysis in the context of network models. Psychol Methods. 2023. doi: 10.1037/met0000555.

41.Leme DEDC, Alves EVDC, Lemos VDCO, Fattori A. Network analysis: A multivariate statistical approach for health science research. Geriatr Gerontol Aging. 2020;14(1):43-51. doi: 10.5327/Z2447-212320201900073.

42.JASP Team. JASP (Version 0.14.1.0)
[Computer software]. 2018. Available from: https://jasp-stats.org/previous-versions/. Accessed on 15 Jul 2025.

43.Epskamp S, Cramer AO, Waldorp LJ, Schmittmann VD, Borsboom D. qgraph: Network visualizations of relationships in psychometric data. J Stat Softw. 2012;48:1-18. doi: 10.18637/jss.v048.i04.

44.Foygel R, Drton M. Extended Bayesian information criteria for Gaussian graphical models. Adv Neural Inf Process Syst. 2010;23. doi: 10.48550/arXiv.1011.6640.

45.Fruchterman TM, Reingold EM. Graph drawing by force-directed placement. Softw Pract Exp. 1991;21(11):1129-64.

46.Christensen AP, Golino H. Estimating the stability of psychological dimensions via bootstrap exploratory graph analysis: A Monte Carlo simulation and tutorial. Psych. 2021;3(3):479-500. doi: 10.3390/psych3030032.

47.Barkley RA, Murphy KR. Attention-Deficit Hyperactivity Disorder: A Clinical Workbook. New York (NY, US): Guilford; 2006.

48.World Health Organisation. International Classification of Diseases-ICD-11. Geneva (Switzerland): World Health Organisation; 2019.

49.World Health Organization. International Statistical Classification of Diseases and Related Health Problems. 10th ed. Geneva (Switzerland): World Health Organization; 1993.

50.Robinaugh DJ, Hoekstra RH, Toner ER, Borsboom D. The network approach to psychopathology: A review of the literature 2008–2018 and an agenda for future research. Psychol Med. 2020;50(3):353-66.

引用本文

Rapson Gomez*,Stephen Houghton,Andre Gomez. Network Analysis of Teachers Views of ADHD Symptoms and Their Associations with Global Functioning among Adolescents [J]. Journal of Psychiatry and Brain Science. 2025; 10; (4). - .

文献评论

相关学者

相关机构