SciELO - Scientific Electronic Library Online

 
vol.90 número2Síndrome de Rett: Análisis molecular del gen MECP2 en pacientes chilenasImpacto del Material Particulado aéreo (MP 2,5 ) sobre las hospitalizaciones por enfermedades respiratorias en niños: estudio caso-control alterno índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados

Revista

Articulo

Indicadores

Links relacionados

  • En proceso de indezaciónCitado por Google
  • No hay articulos similaresSimilares en SciELO
  • En proceso de indezaciónSimilares en Google

Compartir


Revista chilena de pediatría

versión impresa ISSN 0370-4106

Rev. chil. pediatr. vol.90 no.2 Santiago abr. 2019

http://dx.doi.org/10.32641/rchped.v90i2.657 

ORIGINAL ARTICLE

Dysregulation profile defined by Child Behavior Checklist in a sample of preschool children

Rodrigo Sierra Rosales1 

Paula Bedregal2 

1 Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Chile.

2 Department of Public Health, School of Medicine, Pontificia Universidad Católica de Chile, Chile.

Abstract:

Introduction:

The dysregulation profile (DP) is a relevant clinical entity in the children and ado lescent area since its association with future psychopathology. DP is defined by the Child Behavior Checklist (CBCL), combining internalizing symptoms (anxiety/depression) and externalizing ones (aggressiveness, attention problems).

Objectives:

To study the frequency of CBCL-DP in a sample of Chilean preschoolers.

Patients and Method:

A sociodemographic survey and CBCL 1.5-5 was applied to caregivers of children aged 30 to 48 months in a national representative sample of public health system users. Frequency was estimated using the Kim et al. method and an explanatory model was made using binary logistic regression of DP using the child, caregiver, and contextual variables.

Results:

The sample size was n = 1,429 preschool children and their caregivers. The frequency of DP was 11.6% (95% CI 9.9-13.5%). The variables that allow to classify DP in 88.6% of cases were: current depressive symptoms in the main caregiver (OR: 2.24; 95% CI 1.37-3.67); number of stressful events experienced by the main caregiver (p = 0.005); number of available elements for child development stimulation in the home (p = 0.001); number of chronic diseases of the child (p = 0.006).

Conclu sions:

DP has a high frequency in preschoolers, which implies a relevant mental health burden. This finding points to the need for interventions in this area and also longitudinal monitoring of this subgroup.

Keywords: Dysregulation profile; Childhood Behavior Checklist; preschoolers

Introduction

Based on the psychopathology, there has been a permanent interest in identifying children and ado lescents who present simultaneously mood, attention, and behavior alterations, as a separate clinical entity1. The application of standardized clinical evaluation instruments, such as the Achenbach Child Behavior Checklist (CBCL)2, has allowed identifying a sympto matic profile that is generically called the CBCL-dys- regulation profile (CBCL-DP)3. This profile attempted to bring together the symptomatic fields of attention problems, anxiety/depression problems, and aggressi ve behavior4,5.

Initially, this profile was associated with a higher frequency of bipolar disorder diagnosis in pediatric age according to DSM4,6; however, long-term follow-ups have had difficulties in maintaining this association, mainly by emphasizing the search for mood episodes with clear onset and end, or delusions of grandeur presence in mental examination, to differentiate from an attention-deficit hyperactivity disorder (formerly attention-deficit disorder)7,8,9.

Despite this questioning, CBCL-DP has concept reliability beyond its diagnostic association in catego rical terms, it constitutes a phenotypic homogeneity tool to compare studies in different populations10. Thus, genetic bases for the profile11,12,13 and the possi bility of longitudinal follow-up14 could even be con sidered.

In this last aspect, prospective cohorts have shown a significant evolution towards bipolar disorder4,15. However, what is most interesting to analyze is the evolution towards severe and joint alterations of affective disorders, cognition and behavior, in what has been described as the “ABC” of develop mental self-regulation (Affective, Behavioral, Cog nitive)3.

Findings in longitudinal follow-up of patients have included diverse forms of psychopathology, in addi tion to the persistence over time of a consistent symp tomatic pattern4,14,15, where an increased suicidality has been observed in adolescence, higher substance use rate, impaired functionality, higher rate of Clus ter B personality disorders in adulthood, higher rate of anxiety disorders diagnosis, major depressive disorder, and behavioral disorders16,17,18,19.

Interest has also emerged in the early identifica tion of children with such characteristics20. A study in preschoolers found several associations that involve important environmental factors21, such as the rate of psychopathology in parents and the presence of mala daptive parenting techniques, in addition to significant psychiatric symptoms in the state of mind and beha vior already at that age.

It is important to point out that, in the psycho pathological discussion, a new diagnosis for child and adolescent age has appeared, listed in the DSM-5 manual, called “Disruptive Mood Dysregulation Disorder”22. There is still some discussion about the im plications of this diagnosis. However, the diagnostic criteria have not been tested for their association with the CBCL scale, in addition to considering specific age and temporal criteria, which do not make it compa rable with the dysregulation profile described in the previous paragraphs.

Having identified this powerful marker of cu rrent and future psychopathology, and the lack of descriptions made in the Chilean population, even less so in the preschool population, this research is proposed with the objective to study the CBCL-DP frequency from a sample of Chilean preschoolers and subsequently to explore associations that help to understand its distribution in the studied popu lation.

Patients and Method

Sample size and selection

Secondary data analysis was carried out with the collected information based on the results evaluation of the Program to Support Biopsychosocial Develop ment, from the Social Protection Subsystem Chile Cre ce Contigo (“Chile grows with you”)23.

The program is carried out in the public health care network and its objective is to monitor the children de velopment since the gestation to the age of six. In this evaluation, data were collected from a representative sample of the Program users23. The sample framework corresponded to children between 30 and 48 months of age (in 2013) who received their benefits from ges tation, in public primary health centers in Chile. The public health sector serves 85% of the population aged 1-524. In order to obtain a representative national sam ple, a cluster sampling was carried out stratified in three stages. The first sampling unit was stratified by public communal networks of organized primary care services. The second sampling unit corresponded to the random selection of a facility to comply with the foreseen quota; if this was not sufficient, another fa cility of the same commune was selected. Finally, the study units correspond to the children treated in these facilities.

The estimated sample size was 1,400 of children aged 30-48 months at the time of the evaluation. This size allows obtaining national frequencies with at least 95% reliability, with a power close to 90% based on European prevalence of developmental problems of approximately 10%.

Construction of the variable “Dysregulation Profile”

For the CBCL-DP measurement, data from the CBCL application in its version for preschoolers aged 18 to 60 months were used25. This instrument has high validity and reliability levels26 and has been validated in this version for Chilean preschoolers27. This ins trument consists of 99 items that represent behaviors which are answered as 0 = not present in the child, 1 = the behavior is sometimes presented in the child, and 2 = it is always presented. A total gross score is esta blished with the sum of each item, which is then stan dardized, using the proposed criteria by the manual25.

The CBCL-DP variable was constructed following the recommendations of Kim et al.21: under this moda lity, each item mentioned above (attention problems, anxiety/depression, aggressiveness) was standardized independently. A new variable was then generated ba sed on the standardized scores sum of each one and was studied with cut-off points from the standardized scores sum in T > 180. This method allows a compari son between both report samples in preschools of di fferent nationalities.

Other used instruments

Child development was assessed with the Batte- lle Developmental Inventory 1 (BDI)28, which is used for the development diagnosis between 0-8 years of age considering the personal-social, social adaptation, motor skills, communication, and cognition aspects. Battelle is considered altered if the instrument shows a significant age lag with respect to the expected ac complishments for the test reference. In the studied sample, the internal reliability of the instrument BDI (Cronbach’s Alpha) was 0.96.

Other studied variables of interest come from the Chile Crece Contigo Survey23. It includes family socio demographic variables such as socioeconomic level measured by ESOMAR method29, and family functio ning, using a translation of the subscale of McMas- ter Family Assessment Device which evaluates family functioning30,31,32,33 and main caregiver variables, such as history of consumption of alcohol, drugs, and smo king. The internal reliability (Cronbach’s Alpha) of the family functioning scale in this sample was 0.842.

In addition, the history of depression in pregnan cy and depression diagnosis made by a physician at some point in life were included, and current depres sive symptoms were evaluated through the Composite International Diagnostic Interview Short Form (CIDI-SF) for major depression34, in the Spanish version used in three National Health Surveys of Chile35. On the other hand, it was analyzed the caregiver perception of stressful events in the last twelve months, and percep tion of general health and domestic violence (psycho logical, financial, physical, and sexual abuse towards the caregiver, and violence in general at home). Among the variables of the child was considered the presence of childhood chronic diseases according to the Survey. In addition, aspects relating to parenting available in the Survey were considered, such as the number of available elements at home to stimulate (which pro poses a list of 12) and the parents’ participation in stimulation areas (reading, singing, playing, visiting relatives, walking).

Statistical analysis

Based on an integrated database construction, the analysis was performed using the statistical software SPSS 17.0 and STATA. The frequency was studied according to the described methods with 95% confidence intervals. Secondly, an association was pursued between the several available exhibitions through the used instruments and the dysregulation profile emer gence. Candidate variables were evaluated with biva riate analysis using chi-squared or T-student tests as appropriate. Statistically significant results were con sidered with p-value < 0.05. Additionally, an explana tory model was created using binary logistic regression with the conditional method, starting with those varia bles that were significantly associated in the bivariate analysis.

Ethical considerations

The study was approved by the research ethics committee of the Eastern Metropolitan Health Service (at the request of the Ministry of Health) and required informed consent from the caregivers participating in the study. No additional funding was required to con duct this secondary analysis.

Results

The resulting sample consisted of 1,429 preschoo lers users of the public health system. The average age of the preschoolers sample was 41.2 ± 4.8 months; 51.2% were male. The educational level of the main ca regiver in years was 9.5±3.6. Table 1 describes the main characteristics of the studied population (Table 1).

Table 1 Sociodemographic characteristics of studied sample. 

The CBCL-DP frequency was 11.6% (95% CI 9.9 13.5%), which in males was somewhat higher than in females. The CBCL-DP was significantly associated with impairment in the Battelle cognitive aspect, fa mily functioning, and the presence of depressive symp toms in the main caregiver. A trend towards a higher frequency was observed in the case of maternal depres sion history during pregnancy (Table 2).

Table 2 Frequencies of dysregulation profile and association* with categorical variables. 

(Table 3) shows how the averages of some continuous variables differ in the case CBCL-DP. In a statistically significant way, there is a higher average of chronic diseases in those with CBCL-DP, a higher number of stressful vital events experienced by the main caregiver in the last twelve months, and a higher number of su ffered types of violence. By contrast, a higher number of areas of the main caregiver involvement in children’s activities is observed in those children without CBCL- DP.

Table 3 Frequencies of dysregulation profile and association* with continuous variables. 

Finally, (Table 4) shows the CBCL-DP explanatory model using binary logistic regression. By entering all statistically significant variables in the bivariate analy sis and observing behavior step-by-step, only four va riables remain in the model: current depressive symp toms of the main caregiver, number of stressful events experienced in the last 12 months by the main caregi ver, number of stimulation elements available at home (as protector), and the number of chronic diseases of the evaluated children, explaining 88.6% of the classi fication coincidences.

Table 4 Explanation model for the dysregulation profile in preschoolers from 36 to 48 months of age. 

Discussion

This study is the first report on the national fre quency of dysregulation profile according to CBCL in Chilean preschoolers between 36 and 48 months of age, users of the public health system. In addition, it is the first frequency report close to the prevalence esti mate of the country. It points out that the frequency tends to be higher in males than in females, and that there are factors of the main caregiver that importantly explain the presence CBCL-DP. In our study, the edu cational level of the caregiver and the socioeconomic level by ESOMAR method did not show significant associations, possibly given the homogeneity in this aspect due to the type of population under study (Chi lean public health sector).

The CBCL-DP presentation frequency in the sam ple is close to the only frequency reported in indivi duals of the same age, in the study of Kim et al.21, who report a frequency in a sample of similar size (n=955), separated by the report of the mother (11.1% frequency with n=549), and of the father (6.4% fre quency with n=406). The reported frequency in the total sample was 9.1%.

Given the results, a first theoretical model is propo sed that interrelates the found associations (Figure 1).

Figure 1 Theorical model. From the found results and in relation to other studies, we propose a schematic representation of hypothetical relationships between study variables and presentation of the dysregulation profile in chilean preschoolers. 

In general, the variables are grouped into intrinsic elements of the child, the elements of the main caregi ver, and the relational elements between them, which occur together in the environment, where factors are also identified. First of all, among the child’s elements, the proposed model shows the number of chronic di seases in the child. It is hypothesized that the physical symptoms presence predisposes to discomfort that can be associated with the greater presence of behavioral symptoms and indicators of internalizing discomfort, as has been observed in bronchial asthma36, which has even had physiopathological mechanisms proposed from neuroendocrine systems37.

Prenatal risk factors associated with this profile have also been reported, such as the educational level of the mother, passive smoking, and identification of mycoplasma in placental samples38, which would fall within the category of intrinsic factors of the child, but which were not included in the studied factors in this sample.

Secondly, among the analyzed elements of the caregiver appear the current depressive symptoms, which have been suggested as modulating of their ability to perceive the needs of the child and also predisposes to irritability of mood and in parenting, which has been widely studied in different populations39. This may be related to the findings of Kim et al. study, where an association between more punitive and controlling parental behaviors and emotional dysregulation was reported21.

In this model, no elements have been found that can be classified entirely in the category of interacting elements. A proxy variable that is related in this aspect is the stimulation elements of the child since these ele ments can act as interaction modulators. In this sense, the stimulation quality has demonstrated significant effects on neurobiological development, both in ani mal and human models40.

From external factors in this model, appears the number of stressful life events. Stressful environments have been suggested as modulators of neuroendocri ne responses that are also related to long-term general health outcomes in individuals who experience it41. Stressful events are related to the onset of depressive symptoms and link the factors mentioned earlier in this model.

Thus, a factors confluence of the child, the caregi ver, the interaction and the environment can be consi dered, which determine the risk of presenting this poor capacity for self-regulation described in this symptomatic profile. However, we must remember that, in the development, these aspects also modify psychological and neurophysiological factors41, which maintain a cycle where the child with dysregulation causes res ponses from the environment (caregivers), since they become part of the dynamics, and can lead to a factor of self-perpetuation in time.

While these results are important in relation to re porting frequencies and associations, they also have extrapolation limitations, since they do not include children users of the private health system. On the other hand, the explanatory model includes proxy va riables to elements difficult to quantify in the dyadic interaction. It is also important to note that the Chi lean population is undergoing significant changes in relation to migration, which are not represented in this database42.

As a projection, it is proposed to identify the model based on the suggested theory, in addition to carrying out a symptomatic re-evaluation of this population in later years, in order to check the evolution reported in the literature of other countries and possibly to study factors susceptible of intervention for the improvement of the mental health standards of this population. It is worth mentioning that to date there are no published studies that test interventions to modify the evolution of this symptomatology profile, which is proposed to encourage research in this area.

In conclusion, the CBCL-Dysregulation Profile, proposed as a construct that combines indicators of psychopathology in cognitive, emotional and beha vioral areas, has a high presentation frequency in this representative sample of Chilean preschoolers, users of the public health system. This implies an important mental health burden in the long term, given the inter national observations that show a high psychopatholo gy incidence of varied nature. The need for interven tions in this area to test their effectiveness, in addition to longitudinal monitoring of this subpopulation, may provide technical guidelines for the development of public policies in child and adolescent mental health.

Ethical Responsibilities

Human Beings and animals protection: Disclosure the authors state that the procedures were followed ac cording to the Declaration of Helsinki and the World Medical Association regarding human experimenta tion developed for the medical community.

Data confidentiality: The authors state that they have followed the protocols of their Center and Local regu lations on the publication of patient data.

Rights to privacy and informed consent: The authors have obtained the informed consent of the patients and/or subjects referred to in the article. This docu ment is in the possession of the correspondence author.

Financial Disclosure: This study was based on information available from the original study of data mining and analysis of child development data and their main social and economic determinants of children who participated in the sup port program to the bio-psycho-social development [“Levantamiento y análisis de información sobre desa rrollo infantil y sus principales determinantes sociales y económicos de niños y niñas que participaron del Programa de Apoyo al Desarrollo Biopsicosocial del Programa Chile Crece Contigo”] of 2013, which was financed by the Social Development Ministry of Chi le. There was no influence from this financing to this secondary study design, the data mining, analysis or interpretation of results, nor in the redaction, revision or approval of this manuscript.

Conflicts of Interest: Authors declare no conflict of interest regarding the present study.

Referencias:

1. Carlson GA. Early onset bipolar disorder: clinical and research considerations. J Clin Child Adolesc Psychol 2005; 34(2):333-43. [ Links ]

2. Achenbach TM, Edelbrock CS. The classification of child psychopathology: A review and analysis of empirical efforts. Psychol Bull 1978;85(6):1275-301. [ Links ]

3. Althoff R. Dysregulated Children Reconsidered. J Am Acad Child Adolesc Psychiatry 2010;49(4):302-5. [ Links ]

4. Biederman J, Wozniak J, Kiely K, et al. CBCL clinical scales discriminate prepubertal children with structured interview-derived diagnosis of mania from those with ADHD. J Am Acad Child Adolesc Psychiatry 1995; 34(4):464-471. [ Links ]

5. Galanter CA, Carlson GA, Jensen PS, et al. Response to methylphenidate in children with attention deficit hyperactivity disorder and manic symptoms in the multimodal treatment study of children with attention deficit hyperactivity disorder titration trial. J Child Adolesc Psychopharmacol 2003;13(2):123-36. [ Links ]

6. Faraone SV, Althoff RR, Hudziak JJ, Monuteaux M, Biederman J. The CBCL predicts DSM bipolar disorder in children: a receiver operating characteristic curve analysis. Bipolar Disord 2005;7(6):518-24. [ Links ]

7. Diler RS, Birmaher B, Axelson D, et al. The Child Behavior Checklist (CBCL) and the CBCL-bipolar phenotype are not useful in diagnosing pediatric bipolar disorder. J Child Adolesc Psychopharmacol 2009;19(1):23-30. [ Links ]

8. Hazell PL, Lewin TJ, Carr VJ. Confirmation that Child Behavior Checklist clinical scales discriminate juvenile mania from attention deficit hyperactivity disorder. J Paediatr Child Health 1999;35(2):199-203. [ Links ]

9. Volk HE, Todd RD. Does the Child Behavior Checklist juvenile bipolar disorder phenotype identify bipolar disorder?. Biol Psychiatry 2007;62(2):115-20. [ Links ]

10. Althoff R, Ayer L, Rettew D, Hudziak J. Assessment of Dysregulated Children using the Child Behavior Checklist: A receiver operating Characteristic curve analysis. Psychol Assess 2010;22(3):609-17. [ Links ]

11. Boomsma DI, Rebollo I, Derks EM, et al. Longitudinal stability of the CBCL- juvenile bipolar disorder phenotype: a study in Dutch twins. Biol Psychiatry 2006;60(9):912-20.14. [ Links ]

12. Hudziak JJ, Althoff RR, Derks EM, Faraone SV, Boomsma DI. Prevalence and genetic architecture of Child Behavior Checklist-juvenile bipolar disorder. Biol Psychiatry 2005;58(7):562-8. [ Links ]

13. Althoff RR, Rettew DC, Faraone SV, Boomsma DI, Hudziak JJ. Latent class analysis shows strong heritability of the Child Behavior Checklist-Juvenile Bipolar Phenotype. Biol Psychiatry 2006;60(9):903-11. [ Links ]

14. Deutz M, Vossen H, De Haan A, Dekovic M, Van Baar A, Prinzie P. Normative development of the Child Behavior Checklist Dysregulation Profile from early childhood to adolescence: Associations with personality pathology. Dev Psychopathol 2018;30(2):437-47. [ Links ]

15. Meyer SE, Carlson GA, Youngstrom, E, et al. Long-term outcomes of youth who manifested the CBCL-Pediatric Bipolar Disorder phenotype during childhood and/or adolescence. J Affect Disord 2009; 113(3):227-35. [ Links ]

16. Holtmann M, Buchmann AF, Esser G, Schmidt MH, Banaschewski T, Laucht M. The Child Behavior Checklist- Dysregulation Profile predicts substance use. suicidality. and functional impairment: a longitudinal analysis. J Child Psychol Psychiatry 2011;52(2):139-47. [ Links ]

17. Holtmann M, Bolte S, Goth K, et al. Prevalence of the Child Behavior Checklist-pediatric bipolar disorder phenotype in a German general population sample. Bipolar Disord 2007;9(8):895-900. [ Links ]

18. Masi G, Pisano S, Milone A, Muratori P. Child Behavior checklist dysregulation profile in children with disruptive behavior disorders: A longitudinal study. J Affect Disord 2015;186:249-53. [ Links ]

19. Mick E, Biederman J, Pandina G, Faraone SV. A preliminary meta-analysis of the child behavior checklist in pediatric bipolar disorder. Biol Psychiatry 2003;53(11):1021-7. [ Links ]

20. Liu J, Cheng H, Leung PWL. The Application of the Preschool Child Behavior Checklist and the Caregiver- Teacher Report Form to Mainland Chinese Children: Syndrome Structure, Gender Differences, Country Effects, and Inter-Informant Agreement. J Abnorm Child Psychol 2011;39(2):251-64. [ Links ]

21. Kim J, Carlson GA, Meyer SE, et al. Correlates of the CBCL-dysregulation profile in preschool-aged children. J Child Psychol Psychiatry 2012;53(9):918-26. [ Links ]

22. Copeland WE, Angold A, Costello EJ, Egger H. Prevalence, Comorbidity, and Correlates of DSM-5 Proposed Disruptive Mood Dysregulation Disorder. Am J Psychiatry 2013;170:173-9. [ Links ]

23. Ministerio de Desarrollo Social, Departamento de Salud Pública, Escuela de Medicina PUC. (2013) Levantamiento y análisis de información sobre desarrollo infantil y sus principales determinantes sociales y económicas, del grupo de niños/as pertenecientes al PADB, en el contexto del Subsistema de Protección a la Infancia Chile Crece Contigo. Disponible en: Disponible en: http://www.crececontigo.gob.cl/material-de-apoyo/material-para-equipos-chile-crece-contigo/estudios/?filtroetapa=gestacion-y-nacimiento&filtrobeneficio . [Última visita: 1 de septiembre de 2018]. [ Links ]

24. Ministerio de Desarrollo Social (2015). Informe de Política Social 2015. Disponible en Disponible en http://www.ministeriodesarrollosocial.gob.cl/storage/docs/Libro_IDS_2015_final.pdf [Última visita: 1 de septiembre de 2018]. [ Links ]

25. Achenbach TM, Rescorla LA. Manual for the ASEBA Preschool Forms & Profiles. Burlington, VT: University of Vermont, Research Center for Children, Youth, & Families. 2001. [ Links ]

26. Rey JM, Schrader E, Morris-Yates A. Parent-child agreement on children’s behaviours reported by the child behaviour checklist (CBCL). J Adolesc 1992;15:219-30. [ Links ]

27. Lecannelier F, Pérez JC, Groissman S, et al. Validación del Inventario de Conductas Infantiles para niños de entre 1/2-5 años (CBCL 1/2-5) en la Ciudad de Santiago de Chile. Univ Psychol 2014;13(2):491-500. [ Links ]

28. Newborg, J. Battelle Developmental Inventory, 2nd edition. Rolling Meadows, IL: Riverside Publishing. 2005. [ Links ]

29. Grupo Adimark. El Nivel Socioeconómico ESOMAR. 2000. Disponible en: Disponible en: http://www.microweb.cl/idm/documentos/ESOMAR.pdf . [Última visita 1 de septiembre de 2018]. [ Links ]

30. Epstein NB, Baldwin LM, Bishop DS. The McMaster family assessment device. J Marital Fam Ther 1983;9(2):171-80. [ Links ]

31. Byles J, Byrne C, Boyle MH, Offord DR. Ontario Child Health Study: reliability and validity of the general functioning subscale of the McMaster Family Assessment Device. Family process 1988;27(1):97-104. [ Links ]

32. Barroilhet S, Cano-Prous A, Cervera-Enguix S, Forjaz MJ, Guillén-Grima F. A Spanish version of the family assessment device. Soc Psychiatry Psychiatr Epidemiol 2009;44(12):1051-65. [ Links ]

33. Walrath CM, Franco E, Liao Q, Holden EW. Measures of child emotional and behavioral strengths and family functioning: A preliminary report on the reliability and validity of their Spanish translations. J Psychoeduc Assess 2004;22(3):209-19. [ Links ]

34. Kessler RC, Andrews G, Mroczek D, Ustun TB, Wittchen HU. The World Health Organization Composite International Diagnostic Interview Short- Form (CIDI-SF). Int J Methods Psychiatr Res 1998;7:171-85. [ Links ]

35. Ministerio de Salud de Chile. Encuestas Nacionales de Salud. 2017. Disponible en: Disponible en: http://epi.minsal.cl/encuesta-ens/ [Última visita: 1 de septiembre de 2018]. [ Links ]

36. Klinnert MD, McQuaid EL, McCormick D, Adinoff AD, Bryant NE. A Multimethod Assessment of Behavioral and Emotional Adjustment in Children with Asthma. J Pediatr Psychol 2000;25(1):35-46. [ Links ]

37. Wood BL, Lim JH, Miller BD, et al. Family Emotional Climate, Depression, Emotional Triggering of Asthma, and Disease Severity in Pediatric Asthma: Examination of Pathways of Effect. J Pediatr Psychol 2007;32(5):542-51. [ Links ]

38. Frazier JA, Wood ME, Ware J, et al. Antecedents of the Child Behavior Checklist-Dysregulation Profile in Children Born Extremely Preterm. J Am Acad Child Adolesc Psychiatry 2015;54(10):816-23. [ Links ]

39. Lovejoy MC, Graczyk PA, O’Hare E, Neuman G. Maternal Depression and Parenting Behavior: A Meta-Analytic Review. Clin Psychol Rev 2000;20(5):561-92. [ Links ]

40. Farah MJ, Betancourt L, Shera DM, et al. Environmental stimulation, parental nurturance and cognitive development in humans. Dev Sci 2008;11(5):793-801. [ Links ]

41. Taylor SE, Lerner JS, Sage RM, Lehman BJ, Seeman TE. Early Environment, Emotions, Responses to Stress, and Health. J Pers 2004;72(6):1365-94. [ Links ]

42. Vasquez-De Kartzow, R. Impacto de las migraciones en Chile: Nuevos retos para el pediatra. ¿Estamos preparados?. Rev Chil Pediatr. 2009;80(2):161-7. [ Links ]

Received: March 12, 2018; Accepted: November 15, 2018

Correspondence: Paula Bedregal. E-mail: pbedrega@gmail.com.

Creative Commons License Este es un artículo publicado en acceso abierto bajo una licencia Creative Commons