Volume 28, Issue 1 (Spring 2022)                   IJPCP 2022, 28(1): 106-121 | Back to browse issues page


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Ghahremani S, Ahmadian Vargahan F, Khanjani S, Farahani H, Fathali Lavasani F. Psychometric Properties of the Mental Health and Social Inadaptation Assessment in Iranian Adolescents. IJPCP 2022; 28 (1) :106-121
URL: http://ijpcp.iums.ac.ir/article-1-3292-en.html
1- Department of Clinical Psychology, Faculty of Behavioral Sciences and Mental Health (Tehran Institute of Psychiatry), Iran University of Medical Sciences, Tehran, Iran.
2- Research Center Cognitive Sciences and Behavioral in Police, Directorate of Health, Rescue & Treatment, Police Headquarter, Tehran, Iran.
3- Department of Psychology, Faculty of Humanities Sciences, Tarbiat Modares University, Tehran, Iran.
4- Department of Clinical Psychology, Faculty of Behavioral Sciences and Mental Health (Tehran Institute of Psychiatry), Iran University of Medical Sciences, Tehran, Iran. , lavasani.f@gmail.com
Full-Text [PDF 6832 kb]   (1901 Downloads)     |   Abstract (HTML)  (4537 Views)
Full-Text:   (1575 Views)
Introduction
Recent studies show that adolescent mental health problems are growing [3, 4, 5, 6]. However, in many cases, their problems remain undetected. If mental health problems in adolescents are not identified on time, they may hinder the emergence of their potential abilities and affect the quality of their personal and social life [7, 12, 13]. One way to diagnose and manage adolescent mental health problems quickly is to use screening instruments [1516]. However, the majority of the existing instruments suffer from a few limitations: they do not meet the diagnostic criteria for the latest classification of mental disorders (DSM-V), most of them evaluate only one or more disorders [17], and they mainly consider problems that are common among children and adolescents and do not take into account disorders that emerge or intensify exclusively during adolescence [2021], and in most of them, screening is based on a categorical approach, and the severity of adolescent problems is ignored [202122]. Considering the abovementioned limitations, Cote et al. [24] designed a self-report questionnaire for mental health assessment and social maladaptation in adolescents (MIA). Although they examined some of the psychometric properties of the MIA questionnaire, such as the internal consistency, construct validity, and other psychometric properties, including that test-retest reliability and concurrent validity, are still unexplored. Therefore, this study aimed to investigate the construct and concurrent validity and reliability of the instrument. 
Methods
This study was conducted in two phases. The study population of the first phase included all students aged 11-17 years living in Islamshahr City, Iran, in the 2019- 2020 academic year. Accordingly, 604 adolescents were selected using the cluster sampling method. The average age of the sample was 15.70 ±1.10 years. A total of 530 students (87.7%) lived with both parents, 16 (2.6%) with their father, 46 (7.6) with their mother, and 12 (2%) with others. Also, 124 students (20.5%) had a history of receiving mental health services, while 480 (79.5%) had no history of receiving health services. The sample of the study’s second phase was selected conveniently from adolescents referred to the medical center of Tehran Institute of Psychiatry (from October 2019 to March 2020). In this phase, 44 adolescents (age range=14-17, Mean±SD=16.14±1.09 years) were participants from whom 29 (65.9%) were boys and 15 (34.1%) were girls. Thirty-nine people (88.7%) lived with both parents, 2 (4.5%) with a father, 1 (2.3) with a mother, and 2 (4.5%) with others. Twenty-five students (56.8%) had a history of receiving mental health services, while 19 (43.2%) had no history of receiving mental health services. Confirmatory factor analysis (CFA) was used to investigate the structural validity of the questionnaire. Moreover, The concurrent validity of the questionnaire was checked with the strength and difficulties questionnaire (SDQ). Finally, the obtained data were analyzed considering descriptive statistics, correlation coefficients, and CFA using SPSS V. 22 and LISERL 8.8.
Results
To investigate the CFA model, 1-factor and 2-factor structural models were hypothesized for the psychopathology scale, and the scales related to dysfunction were analyzed using a separate factor structure. The hypothesized models were analyzed using LISREL 8.8. Table 1 summarizes the results of the CFA models.

The results showed a good fit of the hypothesized 1-factor and 2-factor models to the data. However, the model fit of the dysfunction scale is moderate (Table 1).
Furthermore, the internal consistency and test-retest reliability indices support the instrument’s reliability. The Cronbach α coefficients for the overall score of psychopathological, externalizing, and internalizing behavior scales were good (0.86<α<0.94). In addition,  except for the two scales of eating disorder and psychopathy, which had the lowest value (α=0.57), the α coefficients of the other scales of psychopathology and dysfunction were good (0.73<α<0.89). The test-retest reliability showed good intra-class correlation coefficient (ICC) indices for the overall score of psychopathology (ICC=0.78) and intrinsic behaviors (ICC=0.81). However, the correlation coefficient of median internalizing behaviors was moderate (0.67). Moreover, except for the three scales of psychopathy, eating disorder, and an eating disorder, with low correlation coefficients (0.42, 0.48, and 0.38, respectively), the correlation coefficient of other scales of psychopathology was moderate to good (0.54 to 0.90). Results of the concurrent validity support a significant positive relationship (P<0.05) between the overall score of  MIA psychopathology scales and those of SDQ psychopathology. In addition, the correlation coefficient among the internalizing and externalizing factors and their subscales, as well as the subscales of SDQ psychopathology, were significantly positive (P<0.05). Moreover, the significantly negative relationship between the MIA scores and its related subscales, such as prosocial behavior in SDQ, supported the concurrent validity of the questionnaire.
Discussion  
This study aimed to investigate the validity and reliability of MIA by assessing the concurrent and construct validity as well as the internal consistency and test-retest reliability of the questionnaire. In line with the original study’s findings [24], our findings support the 2-factor structural model for the questionnaire. In addition, 1-factor structural model for psychopathology was confirmed. The results of the analysis show a good α coefficient for the overall score of psychopathology, externalizing and internalizing, and factors (0.86<α<0.94). The Cronbach α coefficient for other scales other than eating disorders and psychopathy is acceptable, though lower than the original study [24]. Moreover, the correlation coefficient of the total scores of psychopathology and externalizing behavior was good (the questionnaires were tested at a time interval of two weeks). However, the correlation coefficient of the scores of the internalizing behaviors was mediocre. Results of the concurrent validity showed a positive correlation (P<0.05) between the scales of the MIA questionnaire and the scales of SDQ with similar concepts. MIA scales also negatively correlated (P<0.05) with the prosocial behavior scale, which was a different concept. Overall, CFA, internal consistency, and correlation coefficient indices of all the scales (except for psychopathy and eating disorder) support the validity and reliability of the questionnaire to be used as a screening tool in adolescents.

Ethical Considerations
Compliance with ethical guidelines

This research was conducted with the code of ethics IR.IUMS.1398.1192 and informed consent of the participants. All participants were aware of the confidentiality of the information and their willingness to cooperate in the research or withdraw from it.

Funding
This research was conducted with the financial support of the Iran University of Medical Sciences.

Authors contributions
Conceptualization and writing of the draft: Fahima Fethali Lavasani, Sosan Garhami; Data collection: Fahima Ahmadian Varghan and Sosan Garhami; Writing and editing the text of the article: Sosan Ghahrani and Fahima Fathali Lavasani; Data analysis: Sajjad Khanjani and Hojatullah Farahani.

Conflicts of interest
The authors declared no conflict of interest.

Acknowledgements
The authors of this article thank and appreciate all the participants in the research and the people who provided the necessary background for conducting this research.



References
  1. Ogden T, Hagen KA. Adolescent mental health: Prevention and intervention. London: Routledge; 2018. [DOI:10.4324/9781315295374]
  2. Das JK, Salam RA, Lassi ZS, Khan MN, Mahmood W, Patel V, et al. Interventions for adolescent mental health: An overview of systematic reviews. Journal of Adolescent Health. 2016;  59(4):S49-60. [DOI:10.1016/j.jadohealth.2016.06.020] [PMID] [PMCID]
  3. Canino G, Shrout PE, Rubio-Stipec M, Bird HR, Bravo M, Ramirez R, et al. The dsm-iv rates of child and adolescent disordersin puerto rico: Prevalence, correlates, service use, and the effects of impairment. Archives of General Psychiatry. 2004; 61(1):85-93. [DOI:10.1001/archpsyc.61.1.85] [PMID]
  4. Merikangas KR, He J-p, Burstein M, Swanson SA, Avenevoli S, Cui L, et al. Lifetime prevalence of mental disorders in US adolescents: Results from the national comorbidity survey replication-adolescent supplement (NCS-A). Journal of the American Academy of Child & Adolescent Psychiatry. 2010; 49(10):980-9. [DOI:10.1016/j.jaac.2010.05.017] [PMID] [PMCID]
  5. Polanczyk GV, Salum GA, Sugaya LS, Caye A, Rohde LA. Annual research review: A meta-analysis of the worldwide prevalence of mental disorders in children and adolescents. Journal of Child Psychology & Psychiatry. 2015 ; 56(3):345-65 [DOI:10.1111/jcpp.12381] [PMID]
  6. Bor W, Dean AJ, Najman J, Hayatbakhsh R. Are child and adolescent mental health problems increasing in the 21st century? A systematic review. Australian & New Zealand journal of Psychiatry. 2014; 48(7):606-16. [DOI:10.1177/0004867414533834] [PMID]
  7. World Health Organization. Adolescent health: Geneva: World Health Organization; 2017. [Link]
  8. Dalsgaard S, Thorsteinsson E, Trabjerg BB, Schullehner J, Plana-Ripoll O, Brikell I, et al. Incidence rates and cumulative incidences of the full spectrum of diagnosed mental disorders in childhood and adolescence. JAMA Psychiatry. 2020; 77(2):155-64. [DOI:10.1001/jamapsychiatry.2019.3523] [PMID] [PMCID]
  9. Bronsard G, Alessandrini M, Fond G, Loundou A, Auquier P, Tordjman S, et al. The prevalence of mental disorders among children and adolescents in the child welfare system: A systematic review and meta-analysis. Medicine. 2016; 95(7):e2622. [DOI:10.1097/MD.0000000000002622] [PMID] [PMCID]
  10. Morris J, Belfer M, Daniels A, Flisher A, Villé L, Lora A, et al. Treated prevalence of and mental health services received by children and adolescents in 42 low-and-middle-income countries. Journal of Child Psychology and Psychiatry. 2011; 52(12):1239-46. [DOI:10.1111/j.1469-7610.2011.02409.x] [PMID]
  11. Merten EC, Cwik JC, Margraf J, Schneider S. Overdiagnosis of mental disorders in children and adolescents (in developed countries). Child and Adolescent Psychiatry and Mental Health. 2017; 11(1):5. [DOI:10.1186/s13034-016-0140-5] [PMID] [PMCID]
  12. Humphrey N, Wigelsworth M. Making the case for universal school-based mental health screening. Emotional and Behavioural Difficulties. 2016; 21(1):22-42. [DOI:10.1080/13632752.2015.1120051]
  13. Fergusson DM, Horwood LJ, Ridder EM, Beautrais AL. Subthreshold depression in adolescence and mental health outcomes in adulthood. Archives of General Psychiatry. 2005; 62(1):66-72. [DOI:10.1001/archpsyc.62.1.66] [PMID]
  14. Kieling C, Baker-Henningham H, Belfer M, Conti G, Ertem I, Omigbodun O, et al. Child and adolescent mental health worldwide: Evidence for action. The Lancet. 2011; 378(9801):1515-25. [DOI:10.1016/S0140-6736(11)60827-1] [PMID]
  15. Prochaska JD, Le VD, Baillargeon J, Temple JR. Utilization of professional mental health services related to population-level screening for anxiety, depression, and post-traumatic stress disorder among public high school students. Community Mental Health Journal. 2016; 52(6):691-700. [DOI:10.1007/s10597-015-9968-z] [PMID] [PMCID]
  16. Essex MJ, Kraemer HC, Slattery MJ, Burk LR, Thomas Boyce W, Woodward HR, et al. Screening for childhood mental health problems: Outcomes and early identification. Journal of Child Psychology and Psychiatry. 2009; 50(5):562-70. [DOI:10.1111/j.1469-7610.2008.02015.x] [PMID] [PMCID]
  17. Tarren-Sweeney M. The Brief Assessment Checklists (BAC-C, BAC-A): Mental health screening measures for school-aged children and adolescents in foster, kinship, residential and adoptive care. Children and Youth Services Review. 2013; 35(5):771-9. [DOI:10.1016/j.childyouth.2013.01.025]
  18. Goodman R. The strengths and difficulties questionnaire: A research note. Journal of Child Psychology and Psychiatry. 1997; 38(5):581-6. [DOI:10.1111/j.1469-7610.1997.tb01545.x] [PMID]
  19. Achenbach TM. Manual for the youth self-report and 1991 profile. Burlington: University of Vermont Department of Psychiatry;  1991. [Link]
  20. Collishaw S. Annual research review: Secular trends in child and adolescent mental health. Journal of Child Psychology and Psychiatry. 2015; 56(3):370-93. [DOI:10.1111/jcpp.12372] [PMID]
  21. Stattin H, Skoog T. Pubertal timing and its developmental significance for mental health and adjustment. Encyclopedia of Mental Health (Second Edition). 2016; 386-97. [DOI:10.1016/B978-0-12-397045-9.00073-2]
  22. Hawton K, Saunders KE, O’Connor RC. Self-harm and suicide in adolescents. The Lancet. 2012; 379(9834):2373-82. [DOI:10.1016/S0140-6736(12)60322-5]
  23. Martel MM, Markon K, Smith GT. Research Review: Multi‐informant integration in child and adolescent psychopathology diagnosis. Journal of Child Psychology and Psychiatry. 2017; 58(2):116-28. [DOI:10.1111/jcpp.12611] [PMID] [PMCID]
  24. Côté SM, Orri M, Brendgen M, Vitaro F, Boivin M, Japel C, et al. Psychometric properties of the mental health and social inadaptation assessment for adolescents (MIA) in a population-based sample. International Journal of Methods in Psychiatric Research. 2017; 26(4):e1566. [DOI:10.1002/mpr.1566] [PMID] [PMCID]
  25. Augenstein TM, Thomas SA, Ehrlich KB, Daruwala S, Reyes SM, Chrabaszcz JS, et al. Comparing multi-informant assessment measures of parental monitoring and their links with adolescent delinquent behavior. Parenting. 2016; 16(3):164-86. [DOI:10.1080/15295192.2016.1158600] [PMID] [PMCID]
  26. Klaus NM, Mobilio A, King CA. Parent-adolescent agreement concerning adolescents’ suicidal thoughts and behaviors. Journal of Clinical Child & Adolescent Psychology. 2009; 38(2):245-55. [DOI:10.1080/15374410802698412] [PMID] [PMCID]
  27. American Psychiatric Association. Diagnostic and statistical manual of mental disorders (DSM-5®). Washington: American Psychiatric Publisher; 2013. [Link]
  28. American academy of pediatrics. Supplemental Appendix S12: Mental health screening and assessment tools for primary care. Pediatrics. 2010; 125(Supplement_3):S173-92. [DOI10.1542/peds.2010-0788R]
  29. Bird HR, Canino GJ, Davies M, Ramírez R, Chávez L, Duarte C, et al. The brief impairment scale (BIS): A multidimensional scale of functional impairment for children and adolescents. Journal of the American Academy of Child & Adolescent Psychiatry. 2005; 44(7):699-707. [DOI:10.1097/01.chi.0000163281.41383.94] [PMID]
  30. Bird HR, Shaffer D, Fisher P, Gould MS. The Columbia Impairment Scale (CIS): Pilot findings on a measure of global impairment for children and adolescents. International Journal of Methods in Psychiatric Research. 1993. [Link]
  31. Guillemin F, Bombardier C, Beaton D. Cross-cultural adaptation of health-related quality of life measures: Literature review and proposed guidelines. Journal of Clinical Epidemiology. 1993; 46(12):1417-32. [DOI:10.1016/0895-4356(93)90142-N]
  32. Comrey A, Lee H. Interpretation and application of factor analytic results. In: Comrey AL, Lee HB, editors. A first course in factor analysis. New York: Psychology Press; 1992. [DOI: 10.4324/9781315827506]
  33. Hobart JC, Cano SJ, Warner TT, Thompson AJ. What sample sizes for reliability and validity studies in neurology? Journal of Neurology. 2012; 259(12):2681-94. [DOI:10.1007/s00415-012-6570-y] [PMID]
  34. Aguilar-Vafaie M, Gharehbaghy F. [Psychometric Properties of Persian Parent and Teacher Versions of the Strengths and Difficulties questionnaire in a sample of Iranian children (Persian)]. Iranian Journal of Psychiatry and Clinical Psychology. 2009; 15(3):231-41. [Link]
  35. Goodman R. Psychometric properties of the strengths and difficulties questionnaire. Journal of the American Academy of Child & Adolescent Psychiatry. 2001; 40(11):1337-45. [DOI:10.1097/00004583-200111000-00015] [PMID]
  36. Ghanizadeh A, Izadpanah A. [Scale validation of the strengths and difficulties questionnaire in Iranian children (Persian)]. Iranian Journal of Psychiatry. 2007; 2(2): 65-71. [link]
  37. Brown TA. Confirmatory factor analysis for applied research.New York: Guilford publications; 2015. [link]
  38. Schermelleh-Engel K, Moosbrugger H, Müller H. Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of Psychological Research Online. 2003; 8(2):23-74. [Link]
  39. Tabachnick BG, Fidell LS. Using multivariate statistics. London : Pearson; 2007. [Link]
  40. Tabachnick BG, Fidell LS. Using multivariate statistics: International edition. New York: Pearson; 2012. [Link]
  41. Hu LT, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal. 1999 ; 6(1):1-55. [DOI:10.1080/10705519909540118]
  42. Portney LG. Foundations of clinical research: Applications to evidence-based practice. Philadelphia: FA Davis; 2020. [Link]
  43. Verschuere B, van Ghesel Grothe S, Waldorp L, Watts AL, Lilienfeld SO, Edens JF, et al. What features of psychopathy might be central? A network analysis of the psychopathy checklist-revised (PCL-R) in three large samples. Journal of Abnormal Psychology. 2018; 127(1):51-5. [DOI:10.1037/abn0000315] [PMID]
  44. Frick PJ, Marsee MA. Psychopathy and developmental pathways to antisocial behavior in youth. In: C J Patrick, editor. Handbook of Psychopathy. New York: Guilford Press; 2018. [Link]
  45. Bartels M, van de Aa N, van Beijsterveldt CE, Middeldorp CM, Boomsma DI. Adolescent self-report of emotional and behavioral problems: Interactions of genetic factors with sex and age. Journal of the Canadian Academy of Child and Adolescent Psychiatry. 2011; 20(1):35-52. [PMCID]
  46. Marsee MA, Silverthorn P, Frick PJ. The association of psychopathic traits with aggression and delinquency in non-referred boys and girls. Behavioral Sciences & the Law. 2005; 23(6):803-17. [DOI:10.1002/bsl.662] [PMID]
  47. Varner M. Internalizing disorders among Mississippi public school students and the need for intervention [Dissertation]. Oxford: University of Mississippi; 2019. [Link]
  48. Goodman R, Meltzer H, Bailey V. The Strengths and Difficulties questionnaire: A pilot study on the validity of the self-report version. International Review of Psychiatry. 2003; 15(1-2):173-7. [DOI:10.1080/0954026021000046137] [PMID]

 
Type of Study: Original Research | Subject: Psychiatry and Psychology
Received: 2020/07/3 | Accepted: 2021/01/31 | Published: 2022/04/1

Add your comments about this article : Your username or Email:
CAPTCHA

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2025 CC BY-NC 4.0 | Iranian Journal of Psychiatry and Clinical Psychology

Designed & Developed by : Yektaweb