Emotion dysregulation as cross-disorder trait in child psychiatry predicting quality of life and required treatment duration

doi:10.21203/rs.3.rs-2009062/v1

Download PDF

Research Article

Emotion dysregulation as cross-disorder trait in child psychiatry predicting quality of life and required treatment duration

https://doi.org/10.21203/rs.3.rs-2009062/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Background

Emotion dysregulation (ED) is increasingly under investigation as a cross-disorder trait, and is by some considered as the core feature in mental disorders. The underlying assumptions are that ED is a trait that manifests similarly across disorders and with similar impact. The aims of this study are to examine the shared and specific features of ED in relation to DSM-categories in a large sample of clinically referred youth.

Methods

Information on clinical diagnosis (Attention Deficit/Hyperactivity Disorder ADHD, Autism Spectrum Disorder, Oppositional Defiant Disorder/Conduct Disorder, Anxiety and Mood Disorders), ED (measured by the CBCL-Emotion Dysregulation Index), Quality of Life (Qol, measured by the Kidscreen-27), and treatment duration (measured by Electronic Health Records) was retrieved from two large samples of toddlers (1.5-5 year old; N = 1,544) and school aged children (6–18 year old; N = 7,259). Frequency scores and logistic regression were used to study symptom profiles of ED, as measured with CBCL-EDI, across all disorders. Linear regression was used to determine the predictive value of ED (CBCL-EDI total score) regarding QoL and treatment duration in addition to - and in interaction with - clinical diagnosis.

Results

Across disorders, equal levels of total ED were found, which predicted lower QoL and a longer treatment duration in addition to clinical diagnosis. The majority of items (11/15 and 16/18) were of equal relevance to the disorders; items that were not, largely reflected disorder specific DSM definitions (i.e. externalizing symptoms in ODD/CD and internalizing symptoms in Anxiety and Mood disorders).

Conclusions

ED is a clinically useful cross-disorder trait to predict severity of impairment as well as required treatment duration. In addition, ED is largely composed of shared features across disorders, with certain disorder specific coloured elements.

Emotion dysregulation

Quality of Life

ADHD

ODD

Depression

Anxiety

Children and adolescents can be easily overwhelmed by emotions. This holds in particular for children and adolescents with mental disorders. There is increasing research and clinical interest in Emotion Dysregulation (ED) as a cross-disorder trait. ED is commonly defined as emotional impulsivity and deficient emotional self-regulation [1] (Faraone et al., 2019) and in most definitions includes symptoms of heightened reactivity and quickness to angry, anxious or depressed affect [2 - 3](Reimherr et al., 2010; Spencer et al., 2011). Successful emotion regulation is associated with good mental and somatic health outcomes, social relationships, academic performance and work functioning [4 – 5] (Brackett & Salovey, 2004; John & Gross, 2004). ED may potentially be relevant in understanding the general risk for the development of psychopathology (‘p-factor’) [6 -7](Caspi, & Moffitt, 2018; Cole, Michel, & Teti, 1994) as well as be a relevant target for treatment regardless of disorder [8-10] (Bekh Bradley, et al., 2011; Garofalo, Neumann, & Velotti, 2020; Schirda, Nicholas & Prakash, 2015). Indeed, emotion dysregulation is more prevalent in youth with Attention Deficit/Hyperactivity Disorder (ADHD) [2] (Reimherr et al., 2010), Autism Spectrum Disorder (ASD) [11] (Joshi et al., 2018), Conduct Disorder/Oppositional Defiant Disorder (CD/OCC) [12] (Muratori et al., 2017), mood disorders [13] (Nolen-Hoeksema, Wisco, & Lyubomirsky, 2008) and anxiety disorders [14] (Mennin & Farach, 2007). In addition, ED may have prognostic value: higher levels of ED may be seen as a severity index and thus predictive of a more complicated treatment course [15] (Hopwood, et al., 2015). However, previous studies have also suggested that ED is more prevalent in some disorders than others in addition to disorder-specific patterns of ED, suggesting potential relevant information is missed when merely focusing on shared ED aspects across disorders [16] (Cole, Hall and Hajal, 2017). Therefore, by scrutinizing the overlapping and distinct characteristics of emotion dysregulation for childhood-onset disorders, we may be able to identify the most pertinent ED characteristics to guide clinicians in treatment choice.

The aims of this study were to examine the shared and specific features of ED in relation to DSM-categories (ADHD, ASD, ODD/CD, Anxiety or Mood disorders) in a large sample of clinically referred youth (N=8,803, 1.5-18 years). In addition, the clinical relevance of ED was examined in predicting quality of life and treatment duration in addition to - and in interaction with - clinical diagnosis. ED was operationalized using the 18-item Emotion Dysregulation Index of the Child Behaviour Checklist (CBCL-EDI) [17] (Samson et al. 2014). The CBCL-EDI was constructed by twenty-three clinicians and experts working in the field of psychiatry and emotion dysregulation research, by examining each item of the CBCL and assessed to what degree they found the item relevant for emotion dysregulation. Eighteen items were selected from different subscales (aggressive, social problems, anxious/depressed, withdrawn/depressed and thought problems) and represent both problematic externalizing and internalizing behaviours. Internal consistency was proven to be excellent (Cronbach’s alpha = .90) [17] (Samson et al., 2014).

Sample

The sample consists of N=8,803 children and adolescents who were referred to Karakter Child- and Adolescent Psychiatry in The Netherlands, between March 2012 and May 2017. The sample included N=6,299 (71.6%) boys, M_age at entry = 9.1 years, SD = 3.7, and N=2,504 (28.4%) girls, M_age at entry = 10.7 years, SD = 4.2. Karakter offers academic, highly specialized care and is specialized in neurodevelopmental disorders.

Clinical DSM-IV-TR [18] (APA, 2000) and DSM-5 diagnoses [19] (2014 and later; APA, 2014) were established by a multidisciplinary team based on information gathered by a child psychiatrist (developmental history, child observation and psychiatric assessment), by a child psychologist, and review of clinical and prior records, including information available from school or other professional institutions involved with the child. Thus, a consensus diagnosis was assigned, which is seen as most reliable, compared to structured interviews when broad diagnostic categories are investigated [20] (Leckman, Sholomkas, Thompson, Belanger, & Weissman, 1982). We focused on 5 main disorders: Attention Deficit/Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD), Conduct Disorder/Oppositional Defiant Disorder (CD/ODD), Anxiety disorders and Mood disorders.

Before the first appointment at the clinic, parents were invited to complete several questionnaires using a Routine Outcome Monitoring system (ROM), to assess a range of variables, such as age, gender and country of birth. The questionnaires included the Child Behaviour Checklist (CBCL) [21] (Achenbach & Rescorla, 2007), to asses current psychopathology and problem behaviour, and Kidscreen-27 [22] (Ravens-Sieberer, et al., 2011) for assessing quality of life. Treatment was monitored with an Electronic Health Record system (EHR). Data on total treatment minutes were derived from the EHR. The present study was approved by the institutional review board of Karakter Child- and Adolescent Psychiatry on June 20^th 2017.

Procedures

All data was derived from ROM and EHR. Cases were pseudoanonymized upon withdrawal and therefore no individual health records were assessed and privacy remained secured. Data was directly put into an IBM SPSS statistics 25 file.

Measurements

Emotion dysregulation

An 18-item emotion dysregulation construct was created based on expert ratings of relevance for ED in all CBCL items [17] (Samson et al., 2014). In this study, the CBCL preschool version (age 1.5-5) and school age version (age 6-18) was used. Item 18 (self-harm and suicidal tendencies), 91 (contemplating suicide) and 97 (threatening people) are missing from the preschool CBCL-EDI and therefore, the CBCL-EDI for this age group consisted of 15 items instead of 18 (See table 1). Internal consistency in the present study was proven to be very good (Cronbach’s alpha =.82 and .85 respectively). See table S1.

Quality of life

Kidscreen-27 was used to assess quality of life (Physical well-being, Psychological well-being, Autonomy and Parent relation, Peers and social support and School environment) in children and adolescents according to parent reports [22] (Ravens-Sieberer et al., 2001). Low scores on one of the subscales or a low total score indicate low subjective health and well-being. Age norms for Kidscreen-27 range from 8-18 years old. Therefore, in the current study, Qol was not assessed for the preschool age group.

Treatment duration
Treatment information for all referred children was registered in EHR system User. Treatment duration was calculated as the total amount of minutes spend on finalized (in)direct treatments of the child as registered by clinicians. As this registration is vital to receive financial compensation for offered services, monthly reminders were send to clinicians to accurately register their appointments in addition to individual reminders in case certain planned patient appointments have not been registered by the end of the month. Therefore, this information was considered to be complete and accurate.

Statistical analyses

IBM SPSS statistics 25 was used for statistical analysis. Dichotomous disorder categories were created for each clinical diagnosis (e.g. ADHD, yes = 1, no = 0). Therefore, children with comorbidities could be in more than one disorder category. (e.g. ADHD = yes, ASD = yes). Cases were deleted from analysis only when age was entered incorrectly (e.g. parent answered with own age instead of the child’s) or when data was missing for CBCL, Kidscreen-27 or treatment duration (e.g. end of treatment was unknown because of ongoing treatment; Table S2 and S3). Analyses were run separately for the preschool age and school age, because the items in the two CBCL versions were not fully compatible. Descriptives were used to provide an overview of demographics, CBCL-EDI, Kidscreen-27 and treatment minutes for the disorder categories. Two separate sets of logistic regression analyses were performed for each of the five dichotomous disorder categories: (1) CBCL-EDI total score as independent variable to compare the relative strength of association between total ED and each disorder category versus all others, (2) each CBCL-EDI item as independent variable to examine the ED aspects that were relatively most distinguishable for each disorder category versus all others. For each disorder-category, items were ordered by most prevalent to least prevalent based on frequency scores of ‘often/clearly present’ ratings.

In addition, linear regression analyses were performed to predict Qol and treatment duration. First, we evaluated if the CBCL-EDI total score predicted Qol and treatment duration as such. Next, we evaluated if the CBCL-EDI total score had additive predictive value for Qol and treatment duration beyond diagnosis. Finally, we examined if the CBCL-EDI total score predicted Qol and treatment duration more in the context of any of the specific disorder categories by adding the interaction between diagnosis and CBCL-EDI in the regression analyses. Age and gender were entered by default in all regression analyses. Linear regression results were corrected for multiple testing by False Discovery Rate (FDR), [23] (FDR; Benjamini, Krieger, & Yekutieli, 2006).

Descriptive results of the study sample

In the preschool sample, 39.6% met diagnostic criteria for ADHD, 60.3% for ASD, 8.6% for ODD/CD and 6.5% for Anxiety disorders. Numbers exceed 100% as patients can have more than one diagnosis. Age varied over disorder categories groups from 3.5 in ASD to 4.2 in ADHD. In all disorder categories, the majority were boys (79.7%-57.0%). Treatment duration varied from 105.7 hours in ADHD to 75.9 hours in Anxiety. In the school age sample, 52.6% met diagnostic criteria for ADHD, 49.4 for ASD, 9.9% for ODD/CD, 14.5% for Anxiety disorders and 12.90% for Mood disorders. Age varied from 14.0 years old in Mood to 9.6 in ADHD. In ADHD, ASD and ODD/CD the majority were boys (78.1%-76.0%). In disorder categories Anxiety and Mood, boys (49.4%-46.0%) were outnumbered by girls (50.6–54.0). ANCOVA was used to study estimated marginal means for all subscales in disorder categories. Kidscreen-27 subscale levels were equal in all disorder. Estimated marginal means for all subscales were relatively lower in the disorder categories compared to norm scores. See figure S1.

ED symptom profiles and disorder categories

Regression analysis showed that most CBCL-EDI items were significant in predicting the disorder categories (e.g. ADHD 1 = present, 0 = absent). In the preschool sample, fewer CBCL-EDI behaviors were significant for predicting the disorder category Anxiety (6/15) compared to all other disorder categories (ADHD 10/15, ASD 10/15 and ODD/CD 11/15). ‘Cries a lot’, ‘Nervous high-strung or tense’ and ‘Sudden changes in mood or feelings’ were insignificant for predicting 3/4 of the disorder categories. In the school age sample fewer CBCL-EDI behaviors were significant for predicting the disorder category Mood (11/18) compared to all others (ADHD 16/18, ASD 15/18, ODD/CD 15/18 and Anxiety 15/18). ‘Deliberately harms or attempts suicide’ was insignificant for predicting 3/5 of the disorder categories.

Frequency scores (e.g. 2 = often/clearly) showed that in the preschool sample, CBCL-EDI behaviors ‘Stubborn/Irritable’, ‘Screams a lot’, ‘Temper tantrums’ and ‘Sudden changes in mood/feelings’ were the most frequent in all disorder categories. ‘Clings / too dependent’ and ‘Nervous/tense’ were relatively more frequent in disorder category Anxiety compared to all others. In the school age sample, ‘Stubborn/Irritable’, ‘Sudden changes in mood/feelings’, ‘Temper tantrums’ and ‘Argues a lot’ were the most frequent in all disorder categories. ‘Too fearful/anxious’ was relatively more frequent in disorder category Anxiety and ‘Nervous/tense’, ‘Worries’ and ‘Unhappy/depressed’ were relatively more frequent in both Anxiety and Mood. Externalizing behaviors ‘Destroys own things’, ‘Destroys belongings of others’ and ‘Gets in many fights’ were more frequent in ODD/CD compared to all other disorder categories. In both samples, the most frequent CBCL-EDI behaviors were mainly similar, with some disorder specific exceptions (e.g. ‘Too fearful/anxious’ in Anxiety, ‘Unhappy/depressed’ in Mood). See Figs. 1 and 2, table S4, S5 and S6.

ED and quality of life

Linear regression predicting Qol from ED

Linear regression was used to predict Qol from ED. First, ED was used to predict overall QoL (Kidscreen-27 total score). More severe ED predicted lower Qol (β =-.49, p = .001). Adding disorder category and the interaction between disorder category and ED, revealed no significant interaction effects, indicating the predictive effect of ED regarding Qol was similar across disorders. Adding disorder category to predict Qol in specific domains (five Kidscreen-27 subscales), was followed by the examination of the interaction between ED and disorder category in predicting Qol in each domain. After correction for multiple testing by FDR, the predictive effect of ED was mostly similar across disorders regarding Qol in different domains. A small number of interactions remained significant for predicting a Qol domain. A higher level of ED predicted poorer Qol in Social support/peers in children with ADHD (β = − .20, q < .01 ) and ASD (β =-.13, q < .01), but not in ODD/CD, anxiety and mood (β = − .01; .01; .20, p > .1). A higher level of ED predicted poorer Qol in School environment in children with ADHD (β = − .13, q < .01) and anxiety (β =-.27, q < .01) but not in ASD, ODD/CD, and mood (β = − .02; .01; .01, p > .1). See table S8.

ED and treatment duration

Linear regression predicting treatment duration from ED

Linear regression was used to predict treatment duration from ED. More ED predicted longer treatment duration for preschoolers and school age children (preschool β = .19, p < .001 and school age β = .31, p < .001). Adding disorder category showed that the predictive effect of ED was similar across disorders regarding treatment duration. The interaction between disorder category and ED, revealed few significant interaction effects. After correction for multiple testing, a higher level of ED predicted a longer treatment duration in children with ASD (β = .31, q < .01) and mood (β = .17, q < .01), more so than for children with ADHD, ODD/CD, and anxiety (β = .04; .03; .06, q < .01 ). See Table S9.

The aims of this study were to examine the shared and specific features of ED in relation to DSM-categories (ADHD, ASD, ODD/CD, Anxiety or Mood disorders) in a large sample of clinically referred youth (N = 8,803, 1.5–18 years). The total level of ED-behaviors was comparable across disorders and in both age groups, with several behaviors being highly prevalent across all disorders. At preschool age, ED typically manifested as externalizing behaviors: ‘Stubborn/irritable’, ‘Screams a lot’, ‘Temper tantrums’ and ‘Sudden changes in mood/feelings’. Over 30% of pre-schoolers often/clearly showing these behaviors regardless of diagnosis, with highest prevalence rates in preschoolers with ODD. Other ED behaviors were considerably less prevalent and/or more disorder specific, such as ‘Clings/Too dependent’ and ‘Nervous/Tense’ (anxiety) or ‘Destroys own things’ and ‘Destroys belongings of others’ (ODD). At school age, less cross-disorder ED-behaviors were found. Only ‘Stubborn/irritable’ was present often/clearly in over 30% of the clinical sample regardless of diagnosis. Other -predominantly externalizing- typical manifestations of ED were ‘Argues a lot’, ‘Temper tantrums’, ‘Sudden changes in mood/feelings’ and ‘Screams a lot’, although these behaviors were prototypical and highly prevalent in children/adolescents with ODD/CD (> 50%), ASD and ADHD (both > 30%) but not for children/adolescents with anxiety or mood disorder. Anxiety and mood disorder were best characterized by internalizing manifestation of ED: ‘Unhappy/sad/depressed’, ‘Worries’, ‘Nervous/tense’ and ‘Too fearful/Anxious’ were present in > 30%. Examining specific domains of Qol showed that more ED on top of ADHD or ASD was related to lower Qol in Social support and more ED on top ADHD and anxiety related to lower Qol in the domain School environment. In addition, a longer treatment duration was found for children that experienced more ED on top of ASD and mood disorders.

Our findings suggest that ED is an important cross-disorder marker as it is associated with several childhood disorders, characterized by several commonly shared features, present from early age onwards and predicting a lower quality of life and longer treatment duration. These findings are in line with claims for ED as the core feature in childhood onset disorders [24] (Thompson, 2019) and its importance in treatment for improving quality of life [10] (Schirda, et al., 2015) and overall outcome [15] (Hopwood, et al., 2015). Moreover, our findings suggest that the existence of externalizing behaviors of ED in early childhood are to be taken seriously by mental health professionals and to be reluctant of calling such behavior ‘typical temper tantrums’. Although the behaviors in itself are normative, a high frequency based on parental reports should raise clinical concern given the likelihood a non-normative development is ongoing. Moreover, the current study showed that with increasing age, a more internalizing manifestation of ED is unfolding. This may be caused by the fact that the externalizing manifestation of ED in preschoolers elicit more negative, unresponsive or punitive reactions from caregivers [25] (Steinberg, & Darbick, 2015). This may pave the way for the development of lower self-esteem and feelings of guilt and shame, until finally by late adolescence these become ‘incorporated’ into a stable negative sense of self-worth [26] (Di Giunta et al., 2022). Developing effective emotion regulation is highly dependent on safe and supportive parent-child relationships (i.e. secure attachment) in which parents provide a safe context and support and stimulate children’s emotion regulation abilities [25] (Steinberg & Drabick, 2015). Offering easy-access parent-child interaction interventions to reduce ED at preschool age may be considered an effective strategy to prevent this vicious cycle [27–28] (Rothbart, Sheese, Rueda, & Posner, 2011; Pauli-Pott, & Becker, 2015).

Furthermore, our findings suggest that ED on top of ADHD and ASD results in lower Qol in social support/peers and not in ODD/CD, anxiety and mood. The fact that ODD/CD, anxiety and mood have emotional symptoms incorporated in its diagnostic criteria, whereas for ADHD and ASD this is not the case [19] (APA, 2014) likely contributes to this finding. Additionally, we found that ED on top of ADHD or anxiety results in lower Qol in school environment. For ADHD, the defining features already put a strain on the teacher-student relationship and the addition of ED behaviors can simply be ‘too much to handle’ for a teacher, resulting in a cumulation of negative school-related experiences and explaining a decreased the likelihood of graduating from high school or college [29] (Surman et al., 2013). For anxiety, symptoms are predominantly internalizing. Accompanied by externalizing behaviors of ED (e.g. ‘Stubborn/irritable’), a similar negative teacher-student interaction pattern can develop, forming a risk factor in school disengagement in childhood and adolescence [30] (Olivier, Morin, Langlois, Tardif-Grenier, & Archambault). These findings suggest that despite the predominantly disorder specific colourings of ED in school age, ED manifestations that are not ‘disorder-defining’, deserve clinical concern and intervention to prevent additional significant problems at school that may have a long-lasting impact on life.

The main strengths of this study were two large clinical samples that were available for analyses of both pre-schoolers and children and adolescents. All data were derived from a Routine Outcome Monitoring (ROM) system and electronic health records (EHR), and were therefore highly clinically relevant for studying ED. ED was studied in multiple disorders, shedding light on the cross-disorder nature of this concept. Longitudinal data on treatment duration was available to study the predictive value of ED in clinical practice. A limitation was that our study had no typical developing control group. As a result, relative comparisons were made between disorder categories. However, relative comparisons are well suited to compare shared and specific features of ED, which was our aim. Another limitation was that clinical diagnoses were not based on a structured and validated clinical interview. However, as this was the case for all disorders studied in this study, it is unlikely that this has influenced the main results. Furthermore, the samples originated from the largest and highly specialized child and psychiatry centre in the Netherlands, with always two well-trained clinical professionals involved in the clinical diagnostic process. The reliability and validity of the disorder categories are most likely a reflection of good clinical practice.

Taken together, this study showed that at preschool age, ED is commonly present in children with non-normal developmental patterns and mostly manifests as cross-disorder externalizing behaviors (e.g. stubborn/irritable, screams a lot, temper tantrums). At school age, a more disorder-specific manifestation of ED emerged, with externalizing behaviors predominating in youngsters with ODD/CD, ADHD and ASD and internalizing in youngsters with anxiety and mood. However, ‘stubborn/irritable’ was one of few ED behaviors present regardless of diagnosis, indexing the inability to flexible adapt to / cope with situations that evoke difficult emotions (e.g. disappointment, humiliation, shame, anxiety). Higher levels of ED related to a lower quality of life and longer treatment duration and disproportionally influenced school functioning in youngsters that showed ED behaviors that were ‘out of character’ (i.e. stubborn/irritable in youngsters with anxiety disorder). As learning to regulate emotions is primarily based on co-regulation with attachments figures, offering easy-access parent-child interaction interventions to reduce ED at preschool age may be considered an effective strategy to prevent a vicious cycle. Future research should focus on the environmental susceptibility of ED and interventions for high risk children and caregivers.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Faraone, S.V., Rostain, A.L., Blader, J., Busch, B., Childress, A.C., Connor, D.F., & Newcorn J.H. (2019). Practitioner Review: Emotional dysregulation in attention-deficit/hyperactivity disorder – implications for clinical recognition and intervention Journal of Child Psychology and Psychiatry, 60, 133–150. doi:10.1111/jcpp.12899.
Reimherr, F.W., Marchant, B. K., Olsen, J. L., Halls, C., Kondo, D. G., Williams, E.D., & Robison, R.J. (2010). Emotional Dysregulation as a Core Feature of Adult ADHD: Its Relationship with Clinical Variables and Treatment Response in two Methylphenidate Trials. Journal of ADHD & Related disorders, 4. 53–64.
Spencer, T.J., Faraone, S.V., Surman, C.B.H., Petty, C., Clarke, A., Batchelder, H., Wozniak, J., & Biederman, J. (2011). Toward defining deficient emotional self-regulation in children with attention-deficit/hyperactivity disorder using the Child Behaviour Checklist: a controlled study. Postgraduate Medicine, 123. 50 – 9. doi: 10.3810/pgm.2011.09.2459.
Brackett, M.A., & Salovey, P. (2004). Measuring emotional intelligence as a mental ability with the Mayer–Salovey–Caruso Emotional Intelligence Test. In G. Geher (Ed.), Measurement of emotional intelligence, 179–194. Hauppauge, NY: Nova Science Publishers.
John, O. O., & Gross, J. J. (2004). Healthy and unhealthy emotion regulation: Personality process individual differences, and life span development. Journal of Personality, 72, 1301–1334.
Caspi, A. & Moffitt, T.E. (2018). All for one and one for all: Mental disorders in one dimension. American Journal of Psychiatry, 175:831–844. doi:10.1176/appi.ajp.2018.17121383.
Cole, P. M., Michel, M. K., & Teti, L. O. (1994). The development of emotion regulation and dysregulation: A clinical perspective. Monographs of the Society for Research in Child Development, 59. 73–100.
Bekh Bradley, D., DeFife, J. A., Guarnaccia, C., Phifer, M. J., Fani, M. N., Ressler, K. J., & Westen, D. (2011). Emotion dysregulation and negative affect: association with psychiatric symptoms. The Journal of clinical psychiatry, 72(5), 685.
Garofalo, C., Neumann, C. S., & Velotti, P. (2020). Psychopathy and Aggression: The Role of Emotion Dysregulation. Journal of Interpersonal Violence, 1. doi:10.1177/0886260519900946.
Schirda, B., Nicholas, J. A., & Prakash, R. S. (2015). Examining trait mindfulness, emotion dysregulation, and quality of life in multiple sclerosis. Health Psychology, 34(11), 1107.
Joshi, G., Wozniak, J., Fitzgerald, M., Faraone, S.V., Fried, R., Galdo, M., Furtak, S.L., Conroy, K., Kilcullen, J.R., Belser, A., & J. Biederman. (2018). High risk for severe emotional dysregulation in psychiatrically referred youth with Autism Spectrum Disorder: A controlled study. Journal of Autism and Developmental Disorders, 48. 3101–3115.
Muratori, P., Pisano, S., Milone, A., & Masi, G. (2017). Is emotional dysregulation a risk indicator for auto-aggression behaviors in adolescents with oppositional defiant disorder? Journal of Affective Disorders, 208. 110–112.
Nolen-Hoeksema, S., Wisco, B. E., & Lyubomirsky, S. (2008). Rethinking rumination. Perspectives on Psychological Science, 3, 400–424.
Mennin, D. S., & Farach, F. J. (2007). Emotion and evolving treatments for adult psychopathology. Clinical Psychology: Science and Practice, 14, 329–352.
Hopwood, C. J., Schade, N., Matusiewicz, A., Daughters, S. B., & Lejuez, C. W. (2015). Emotion regulation promotes persistence in a residential substance abuse treatment. Substance use & misuse, 50(2), 251–256.
Cole, P. M., Hall, S. E., & Hajal, N. J. (2017). Emotion dysregulation as a vulnerability to psychopathology. In T. P. Beauchaine & S. P. Hinshaw (Eds.), Child and adolescent psychopathology, 3rd ed. 346–386. Hoboken, NJ: Wiley.
Samson, A.C., Phillips, J.M., Parker, K.J., Shah, S., & Gross, J. (2014) Emotion Dysregulation and the Core Features of Autism Spectrum Disorder. J Autism DevDisord, 44, 1766–1772.
APA (2000) Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision. American Psychiatric Association, Washington, D.C.
APA (2014). Handboek voor de classificatie van psychische stoornissen (DSM-5). Nederlandse vertaling van Diagnostic and Statistical Manual of Mental Disorders 5th Edition. Arlington: American Psychiatric Association, Washington, D.C.
Leckman JF, Sholomkas D, Thompson WD, Belanger A, Weissman MM (1982). Best estimate of a lifetime psychiatric diagnosis: a methodological study. Archives of General Psychiatry 39, 879–883.
Achenbach, T.M., & Rescorla, L.A. (2007). Multicultural supplement to the manual for the ASEBA School-Age Forms & Profiles. Burlington, VT: University of Vermont, Research Center for Children, Youth, & Families.
Ravens-Sieberer, U., Gosch, A., Abel, T., Auquier, P., Bellach, B.-M., Dür, W., Rajmil, L., & the European KIDSCREEN Group (2001). Quality of life in children and adolescents:a European public health perspective. Social and Preventive Medicine, 46, 297–302.
Benjamini, Y., Krieger, A. & Yekutieli, D. (2006) Adaptive linear step-up procedures that control the false discovery rate. Biometrika, 93, 491–507.
Thompson, R.A., (2019). Emotion dysregulation: A theme in search of definition. Developmental Psychopathology, 1–11. doi: 10.1017/S0954579419000282.
Steinberg E. A., & Drabick D.A. (2015) A developmental psychopathology perspective on ADHD and comorbid conditions: The role of emotion regulation. Child Psychiatry Hum Dev. 46(6):951–966.
Di Giunta L., Lunetti C., Gliozzo G., Rothenberg W.A., Lansford J.E., Eisenberg N., Pastorelli C., Basili E., Fiasconaro I., Thartori E., Favini A., & Virzì A.T. (2022) Negative Parenting, Adolescents' Emotion Regulation, Self-Efficacy in Emotion Regulation, and Psychological Adjustment. Int J Environ Res Public Health. 16;19(4):2251. doi: 10.3390/ijerph19042251.
Rothbart, M.K., Sheese, B.E., Rueda, M.R., Posner, M.I. (2011). Developing mechanisms of self-regulation in early life Emot Rev.;3(2):207–213.
Pauli-Pott U., & Becker, K. (2015). Time windows matter in ADHD-related developing neuropsychological basic deficits: A comprehensive review and meta-regression analysis. Neurosci Biobehav Rev. 55:165–172.
Surman C.B., Biederman J., Spencer T., Miller C.A., McDermott K.M., Faraone S.V. (2013). Understanding deficient emotional self-regulation in adults with attention deficit hyperactivity disorder: a controlled study. Atten Defic Hyperact Disord. 273 – 81. doi: 10.1007/s12402-012-0100-8.
Olivier E., Morin A.J.S., Langlois J., Tardif-Grenier K., & Archambault I. (2020) Internalizing and Externalizing Behavior Problems and Student Engagement in Elementary and Secondary School Students. J Youth Adolesc. 49(11):2327–2346. doi:10.1007/s10964-020-01295-x.

No competing interests reported.

EmotiondysregulationasacrossdisordertraittablesfigSI.docx

Download PDF

Version 1

posted

You are reading this latest preprint version

Emotion dysregulation as cross-disorder trait in child psychiatry predicting quality of life and required treatment duration

Status:

Version 1

Abstract

Background

Methods

Results

Conclusions

Introduction

Method

Results

Descriptive results of the study sample

ED symptom profiles and disorder categories

ED and quality of life

Linear regression predicting Qol from ED

ED and treatment duration

Linear regression predicting treatment duration from ED

Discussion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1