Skip to main content
NCBI home page
International Journal of Methods in Psychiatric Research logoLink to International Journal of Methods in Psychiatric Research
. 2023 Sep 15;32(Suppl 1):e1985. doi: 10.1002/mpr.1985

Developmentally specified characterization of the irritability spectrum at early school age: Implications for pragmatic mental health screening

Emily Hirsch 1, Tasmia Alam 2, Nathan Kirk 2, Katherine B Bevans 3, Margaret Briggs‐Gowan 4, Lauren S Wakschlag 5, Jillian L Wiggins 2,6, Amy K Roy 1,7,✉
PMCID: PMC10654842  PMID: 37712753

Abstract

Objectives

Developmentally specified measures that identify clinically salient irritability are needed for early school‐age youth to meaningfully capture this transdiagnostic risk factor for psychopathology. Thus, the current study modeled the normal:abnormal irritability spectrum and generated a clinically optimized screening tool for this population.

Methods

The irritability spectrum was modeled via the youth version of the Multidimensional Assessment Profile Scales—Temper Loss Scale (MAPS‐TL‐Youth) in children (n = 474; 6.0–8.9 years) using item response theory (IRT). Both cross‐cutting core irritability items from the early childhood version and new developmentally specific items were included. Items uniquely associated with impairment were identified and used to derive a brief, clinically optimized irritability screener. Longitudinal data were then utilized to test the predictive utility of this clinically optimized screener in preadolescence (n = 348; 8.0–12.9 years).

Results

Most children exhibit irritability regularly, but daily occurrence was rare. Of the top 10 most severe items from the IRT analyses, 9 were from the developmentally specific items added for the MAPS‐TL Youth version. Two items associated with concurrent impairment were identified for the clinically optimized irritability screener (“Become frustrated easily” and “Act irritable”). The MAPS‐TL‐Youth clinically optimized screener demonstrated good sensitivity (69%) and specificity (84%) in relation to concurrent DSM 5 irritability‐related diagnoses. Youth with elevated scores on the screener at early school age (ESA) had more than 7x greater odds of irritability‐related psychopathology at pre‐adolescence.

Conclusions

The MAPS‐TL‐Youth characterized the developmental spectrum of irritability at ESA and a clinically optimized screener showed promise at predicting psychopathology risk. Rigorous testing of clinical applications is a critical next step.

Keywords: assessment, developmental psychopathology, pediatric irritability

1. INTRODUCTION

Pediatric irritability, when frequent, dysregulated, and disproportionate to context, is one of the most common reasons for treatment referral and predictive of future psychopathology, suicidality, and impairment (Dougherty et al., 2013; Evans et al., 2022; Hawes et al., 2020; Orri et al., 2019; Sorcher et al., 2022; Stringaris et al., 2009; Vidal‐Ribas et al., 2016). As such, modeling the normal: abnormal spectrum of irritability and generating clinically optimized screening tools that allow for quick and efficient identification of clinically significant irritability are paramount for researchers and clinicians (Wiggins, Roy, et al., 2023). Given developmental shifts in both the phasic (i.e., temper tantrums) and tonic (i.e., angry, grumpy, or grouchy mood) components of irritability throughout childhood (Brotman et al., 2017; Roy et al., 2013; Wakschlag et al., 2012), the characterization and assessment of irritability must occur within developmental context (Wakschlag et al., 2010). We have previously conducted extensive work along these lines in the context of early childhood, a time when temper tantrums occur normatively (Krogh‐Jespersen et al., 2021; Wakschlag et al., 2012, 2018; Wiggins et al., 2018). However, despite the detrimental sequelae of irritability, little is known about the spectrum of irritability as expressed in early school‐age youth, and developmentally specific screening tools are lacking during this developmental period.

Characterizing irritability along a severity spectrum, differentiating normal from abnormal, and efficiently identifying clinically salient irritability in early school‐age youth are foundational steps toward the effective assessment and screening of irritability. To date, studies utilizing these approaches have been conducted in early childhood (Krogh‐Jespersen et al., 2021; Wakschlag et al., 2012, 2014, 2015, 2018), with a relative paucity of research on irritability during the subsequent developmental period when children enter and attend elementary or primary school, termed here, early school age (ESA). Typically, there is a sharp decrease in irritability as children approach school age (Yu et al., 2022), likely because they develop more self‐regulatory capacities and learn to adapt behaviors to the demands of their environments (Zeman et al., 2006). As a result, normative irritability in this age group has received little attention despite the need for its characterization based on expectable developmental patterns in order to determine when irritability deviates from what is normative to provide a transdiagnostic indicator of youth at higher risk for psychopathology who could benefit from preventive intervention (Wakschlag et al., 2012, 2014, 2015). To date, studies in school‐age and adolescent youth have focused primarily on clinically elevated irritability associated with adverse outcomes (Orri et al., 2019; Savage et al., 2015; Stringaris et al., 2009). Many of these studies relied on post hoc analyses of counts of DSM‐based oppositional defiant irritability symptoms or utilized irritability‐specific items from pre‐existing measures (Brotman et al., 2006; Burke et al., 2014; Dougherty et al., 2021; Evans et al., 2017, 2020; Hawes et al., 2020; Vidal‐Ribas et al., 2016). More recently, measures have been developed to assess clinical irritability in children, including the Affective Reactivity Index (Stringaris et al., 2012), which assesses phasic and tonic irritability but only reliably captures severe levels of irritability (Dougherty et al., 2021); the Emotional Outburst Inventory (Carlson et al., 2022), which focuses exclusively on phasic irritability; and the Cranky Thermometer (Melvin et al., 2018), which is a visual analog scale that focuses on current and peak irritability. These advances are important and offer burgeoning options for assessment of clinical irritability in youth. However, they are not developmentally specific nor designed to characterize the full normal: abnormal spectrum. As a result, prodromal expressions of irritability (which are more malleable to intervention) in ESA youth may be missed.

The Multidimensional Assessment Profile Scales—Temper Loss (MAPS‐TL) scale is grounded in a novel developmental specification theory that posits that atypicality should be defined based on deviation from normative patterns within a developmental period (Wakschlag et al., 2010). While it was initially designed for use with preschoolers to characterize the dimensional spectrum of irritability within the rapidly changing context of early childhood (Wakschlag et al., 2012), developmentally specified versions of the MAPS‐TL were subsequently developed, including modified versions for infants/toddlers (see Wiggins, Urena Rosario, Zhang et al., 2023), and for older youth (i.e., school‐age through adolescence) and has been extended to include internalizing dimensions (see Wakschlag et al., this issue). Each version includes core items that are consistent across age groups as well as additional items conceptualized to be specific expressions of irritability at particular ages. The MAPS‐TL's developmental specification has been previously modeled in infant‐toddlers (Krogh‐Jespersen et al., 2021) and preschoolers (Wakschlag et al., 2012, 2014, 2018) and has demonstrated predictive validity (see Wiggins, Urena Rosario, MacNeill et al., 2023; Wiggins, Urena Rosario, Zhang et al., 2023). Here and in multiple papers in this special issue, we apply this approach to older youth (see Alam et al., 2023; Kirk et al., 2023).

The youth version of the MAPS‐TL (MAPS‐TL‐Youth) includes 22 core items and 16 additional items specifically conceptualized to reflect behaviors theorized to be important as children's contexts expand to include school and peers, and tonic symptoms of irritability (grumpy, angry mood) become more salient. To date, there has only been one psychometric examination of the MAPS‐TL‐Youth in ESA children. Specifically, Kaat et al. (2019) used the core items to generate a common scoring metric with the Child Behavior Checklist (CBCL; Achenbach & Ruffle, 2000). However, this work did not model the severity spectrum and only included core items. Thus, there is still a need for more detailed examinations of the MAPS‐TL‐Youth, including modeling of the normal:abnormal irritability spectrum in ESA youth. Indeed, the assessment of irritability in these youth is particularly crucial as the school‐age period is marked by significant transitions and challenges as children are expected to exhibit greater behavioral control in school settings and learn new academic and interpersonal skills. These transitions coupled with research showing a normative decline in irritability after early childhood (Wiggins et al., 2014; Yu et al., 2022) are suggestive of changes in the manifestation and patterns of irritability and underscore the need for developmental specificity in irritability assessment.

Nuanced characterization of irritability is key for empirical examinations of etiology, underlying mechanisms, and longitudinal change. However, clinicians also require developmentally meaningful transdiagnostic screening tools that can quickly and efficiently flag youth with clinically salient irritability. Indeed, there is a growing trend in the field to develop ultra‐brief scales for use in busy clinic settings to indicate when further evaluation or referral is needed (Abramovitch et al., 2022; Jo et al., 2020; Rivera‐Riquelme et al., 2019). In line with this, Wiggins et al. (2018) utilized the MAPS‐TL to generate a developmentally specific, two‐item clinically optimized screener to flag preschoolers with clinically concerning irritability. Similar screeners have been developed for infants/toddlers (Wiggins, Urena Rosario, Zhang et al., 2023), preadolescents (ages 8–12 years; Alam et al., 2023), and adolescents (ages 12–17 years; Kirk et al., 2023.). Currently, there is no such developmentally based irritability screener for use with 6–8‐year‐old children, despite evidence that elevated irritability persisting into school age puts children on a path to mental disorder and functional impairment across the lifespan (Brotman et al., 2006; Copeland et al., 2014; Stringaris et al., 2009).

The present study had two primary aims to facilitate the assessment of irritability in ESA children (ages 6.9–8.9 years) in research and clinical settings using the MAPS‐TL‐Youth. The first aim was to model the normal: abnormal spectrum of irritability in ESA youth, including the added value of developmentally specific items. To do this, we identified commonly occurring and atypical manifestations of irritability in ESA children and used item response theory (IRT) to model irritability along a severity spectrum in this group. The second aim was to create a pragmatic tool designed to enable real world irritability screening at ESA. We first identified the features of irritability that are uniquely associated with cross‐domain impairment to create a clinically optimized screener and then empirically derived a total score cutoff that is the most sensitive and specific indicator of irritability‐related DSM disorders, including oppositional defiant disorder (ODD), disruptive mood dysregulation disorder (DMDD), major depressive disorder (MDD), and persistent depressive disorder (PDD). The clinical utility of this screener was further evaluated by using longitudinal data to test the predictive validity of the empirical cutoff score by examining the likelihood of meeting criteria for irritability‐related DSM disorders at the transition to adolescence (ages 8.0–12.9 years).

2. METHODS

2.1. Participants

Data were obtained from parents of children who completed the ESA and preadolescent (PA) waves of the Multidimensional Assessment of Preschoolers Study (MAPS), a multi‐wave longitudinal study followed from preschool age (For details, see: Wakschlag et al., 2012; Wakschlag et al., 2015). The current study included 474 (95%) parents of ESA youth (Mean Age = 7.23, SD = 0.75, Range = 6.0–8.9 years). Data were also included from 348 of these parents (73% of ESA participants) who also completed study measures when their children were preadolescents (Mean Age = 9.3, SD = 2.84, Range = 8.0–12.9 years). Diagnostic interviews were conducted with 306 parents of ESA wave youth and 273 parents of PA wave youth. See Table 1 for participant demographic information. Of note, families who participated in the PA wave did not differ from those who only participated in the ESA wave on child gender, maternal education, and poverty status. However, compared to those who participated in both waves, participants who only participated in the ESA wave had lower mean levels of irritability (t [472] = 1.52, p = 0.040), tended to be older (t [472] = 3.05, p = 0.006), and were more likely to be Non‐Hispanic White and less likely to be Non‐Hispanic Black (χ 2 [3] = 16.98 p < 0.001).

TABLE 1.

MAPS study sample characteristics by wave.

Variable Early school‐age wave (N = 474) Preadolescent wave (N = 348)
Child age, M (SD) 7.23 (0.75) 9.3 (2.84)
Child gender, % Female 54.4 52.6
Child race/Ethnicity, %
Hispanic 27.6 29.3
Non‐Hispanic Black 44.9 46.3
Non‐Hispanic White 25.3 19.5
Non‐Hispanic other 2.1 4.0
Poverty status, % poor 32.8 33.2
Maternal education, %
Less than high school 4.2 4.4
High School/GED 18.5 19.6
Some college 34.3 32.7
Associate's degree 17.9 14.3
Bachelor's degree 14.3 14.9
Graduate degree 10.7 14.0
Open in a new tab

2.2. Measures

2.2.1. Irritability

Multidimensional assessment profile scales—Temper loss scale (MAPS‐TL; Wakschlag et al., 2014; Wakschlag et al., 2012)

The MAPS‐TL is an irritability scale that is part of a suite of MAPS dimensional scales. The MAPS‐TL is a parent‐report measure of developmental expressions of irritability including behavior (i.e., tantrums) and mood (e.g., sullen, grumpy). Although multi‐faceted, items fall along a single dimension (Wakschlag et al., 2014; Wakschlag et al., 2012; Wakschlag et al., 2015, see also Alam et al., 2023; Kirk et al., 2023). Items capture the expression, context, and triggers of irritability along a severity spectrum, from normative, typically occurring behaviors to severe, clinically concerning (atypical) behaviors. The MAPS‐TL also employs an objective (e.g., times per week/day) rather than subjective (e.g., “sometimes,” “often”) 6‐point rating scale (i.e., 0 = Never in the past month; 1 = Rarely [Less than once per week]; 2 = Some [1–3] days of the week; 3 = Most [4–6] days of the week; 4 = Every day of the week; and 5 = Many times per day) to reduce reporting biases and increase the ability to generate severity thresholds based on actual frequency, which may be more informative for ultimate translation to real world settings (e.g., for screening). The current study utilized the Youth version of the MAPS‐TL (MAPS‐TL‐Youth), which includes the 22 core items that are included in all versions of the MAPS‐TL and 16 items that were developed to capture expressions of irritability theorized to capture salient facets in school age and adolescent youth. See Table 2 for a list of MAPS‐TL‐Youth core and additional developmentally specific items.

TABLE 2.

Distribution of MAPS‐TL‐youth items.

Item Percent (frequency)
Never in past month Rarely (less than once per week) Some (1–3) days of the week Most (4–6) days of the week Every day of the week Many times each day
Have difficulty calming down when angry 50.42 (239) 29.32 (139) 13.08 (62) 4.22 (20) 1.05 (5) 1.90 (9)
Become frustrated easily 28.27 (134) 36.50 (173) 22.15 (105) 6.33 (30) 2.74 (13) 4.01 (19)
Have a short fuse (become angry quickly) 51.16 (242) 27.70 (131) 11.63 (55) 5.07 (24) 2.33 (11) 2.11 (10)
Yell angrily at someone 39.83 (188) 31.36 (148) 20.97 (99) 4.24 (20) 1.27 (6) 2.33 (11)
Stamp feet or hold breath during a temper tantrum, 'fall‐out', or melt‐down 62.79 (297) 19.87 (94) 10.57 (50) 3.17 (15) 1.90 (9) 1.69 (8)
Lose temper or have a tantrum when frustrated, angry, or upset 47.68 (226) 30.38 (144) 14.35 (68) 2.95 (14) 2.53 (12) 2.11 (10)
Lose temper or have a tantrum when tired, hungry, or sick 56.75 (269) 25.74 (122) 11.6 (55) 1.90 (9) 1.9 (9) 2.11 (10)
Lose temper or have a tantrum to get something he/she wanted 54.03 (255) 27.12 (128) 12.08 (57) 3.18 (15) 1.91 (9) 1.69 (8)
Act irritable 43.04 (204) 35.44 (168) 15.19 (72) 3.16 (15) 1.27 (6) 1.90 (9)
Lose temper or have a tantrum during daily routines, such as bedtime, mealtime, or getting dressed 60.55 (287) 23.63 (112) 9.70 (46) 2.74 (13) 1.69 (8) 1.69 (8)
Break or destroy things during a temper tantrum, 'fall‐out', or melt‐down 86.5 (410) 8.65 (41) 2.53 (12) 1.27 (6) 0.21 (1) 0.84 (4)
Have a temper tantrum, 'fall‐out', or melt‐down 64.35 (305) 19.62 (93) 9.49 (45) 2.32 (11) 2.32 (11) 1.90 (9)
Stay angry for a long time 72.36 (343) 19.20 (91) 5.70 (27) 1.27 (6) 0.63 (3) 0.84 (4)
Have a temper tantrum, 'fall‐out', or melt‐down that lasted longer than 5 min 74.47 (353) 16.46 (78) 4.64 (22) 2.11 (10) 0.84 (4) 1.48 (7)
Lose temper or have a tantrum with other adults (e.g., teacher, babysitter, family member) 78.18 (369) 13.35 (63) 5.93 (28) 1.06 (5) 0.42 (2) 1.06 (5)
Lose temper or have a tantrum with you or other parent 61.78 (291) 21.66 (102) 11.25 (53) 2.12 (10) 1.70 (8) 1.49 (7)
Keep on having a temper tantrum, 'fall‐out', or melt‐down even when you tried to help him/her calm down 77.33 (365) 13.98 (66) 5.08 (24) 1.48 (7) 1.06 (5) 1.06 (5)
Have a hot or explosive temper 71.82 (339) 15.25 (72) 8.69 (41) 1.69 (8) 1.69 (8) 0.85 (4)
Have a temper tantrum, fall‐out, or melt‐down until exhausted 84.99 (402) 8.25 (39) 4.23 (20) 1.48 (7) 0.21 (1) 0.85 (4)
Get extremely angry 68.78 (326) 20.68 (98) 7.38 (35) 1.05 (5) 1.27 (6) 0.84 (4)
Lose temper or have a tantrum 'out of the blue' or for no reason 84.18 (399) 10.97 (52) 2.32 (11) 0.84 (4) 0.63 (3) 1.05 (5)
Hit, bite, or kick during a tantrum, 'fall‐out', or melt‐down 90.51 (429) 5.70 (27) 2.32 (11) 0.42 (2) 0.21 (1) 0.84 (4)
Lose temper or have a tantrum when doing schoolwork* 53.91 (255) 25.79 (122) 14.38 (68) 2.96 (14) 1.90 (9) 1.06 (5)
Make you feel that you have to 'walk on eggshells' to avoid setting him/her off* 84.75 (400) 8.26 (39) 4.24 (20) 0.85 (4) 1.48 (7) 0.42 (2)
Act angry, irritable, or grouchy throughout most of the day* 68.92 (326) 21.78 (103) 5.71 (27) 1.27 (6) 1.27 (6) 1.06 (5)
Act angry, irritable, or grouchy no matter what you do* 75.26 (356) 17.97 (85) 5.29 (25) 0.63 (3) 0.42 (2) 0.42 (2)
Get in a bad mood even during fun activities* 74.21 (351) 20.30 (96) 4.02 (19) 0.63 (3) 0.63 (3) 0.21 (1)
Seem sullen* 80.89 (381) 14.86 (70) 2.76 (13) 0.42 (2) 1.06 (5) 0.00 (0)
Get annoyed easily* 46.30 (219) 35.10 (166) 11.63 (55) 4.23 (20) 1.48 (7) 1.27 (6)
Lose temper easily* 67.23 (318) 19.66 (93) 7.61 (36) 2.96 (14) 1.48 (7) 1.06 (5)
Have less expected of him/her than other children in the family because of angry mood* 87.10 (412) 7.82 (37) 3.59 (17) 0.42 (2) 0.85 (4) 0.21 (1)
Act grumpy or grouchy* 50.74 (239) 31.85 (150) 12.1 (57) 2.34 (11) 1.70 (8) 1.27 (6)
Complain about others, activities; not satisfied by anything* 71.40 (337) 19.70 (93) 5.51 (26) 1.48 (7) 1.48 (7) 0.42 (2)
Act grouchy most of the day* 78.86 (373) 15.01 (71) 4.23 (20) 0.42 (2) 1.27 (6) 0.21 (1)
Have tantrums (temper outburst, "fall‐out," or melt‐down) that get in the way of getting along with other children* 83.93 (397) 11.42 (54) 2.33 (11) 1.06 (5) 0.63 (3) 0.63 (3)
Spoil something for your family because of his/her bad mood* 68.86 (325) 23.09 (109) 5.93 (28) 0.85 (4) 0.21 (1) 1.06 (5)
Cause family outings/activities to revolve around preventing him/her from having outbursts* 84.53 (399) 10.81 (51) 2.33 (11) 1.06 (5) 0.42 (2) 0.85 (4)
Act angry all day long* 92.16 (435) 5.93 (28) 1.27 (6) 0.21 (1) 0.21 (1) 0.21 (1)
Open in a new tab

Note: Asterisks indicate items that are developmentally based additions to the MAPS‐TL‐Youth version.

2.2.2. Psychiatric diagnoses

Schedule of affective disorders and schizophrenia for children—Present and lifetime version (KSADS‐PL; Kaufman et al., 2016)

The K‐SADS‐PL, a semi‐structured clinical interview that assesses current and lifetime DSM‐5 psychiatric disorders, was conducted with parents during both waves of the MAPS. Minor developmental modifications were made for the ESA wave based on the Early Childhood version of the KSADS (KSADS‐EC; Gaffrey & Luby, 2012) to enhance face validity for this age group. For the current study, our clinical outcomes from the KSADS‐PL were any irritability‐related diagnoses (i.e., ODD, DMDD, MDD, and PDD), in ESA and PA waves. 11.4% met criteria for any irritability‐related diagnosis at ESA wave, and 13.2% at PA wave.

2.2.3. Impairment

Family life impairment scale (FLIS; Mian et al., 2018)

The FLIS is a 19‐item parent‐report measure that assesses the degree to which children's emotions and behaviors lead to impairment across three domains: child functioning, family interactions, and childcare/school. Items are rated on a 3‐point scale (i.e., 0 or “Not true,” 1 or “Somewhat true,” 2 or “Very true”). Cross‐domain impairment at the ESA wave was considered present if one or more items were endorsed (score ≥1) across at least two FLIS impairment domains, as in Wiggins et al. (2018).

2.3. Data analytic plan

2.3.1. Aim 1: Characterization of the normal: Abnormal spectrum

Item response percentages and frequencies

Descriptive statistics were used to calculate item response percentages and frequencies across the six response categories of the MAPS‐TL‐Youth. This information was used to identify commonly occurring manifestations of irritability. In line with previous research (Wakschlag et al., 2018), expressions of irritability were considered common if they occurred regularly (sometime in the past month) in at least 50% of children.

Item response theory analyses

Item response theory analyses were conducted using a Graded Response Model (GRM) (Samejima, 1969) to scale ESA irritability along a severity spectrum. Item response theory involves various models that provide information about the relationship between individuals' levels of a latent underlying trait, or theta, and their item responses. The GRM is used for ordinal, polytomous data; for each item, it yields one slope parameter and n ‐ 1 (n = number of response options) category threshold parameters. The slope parameter (a) provides information about how well each item discriminates individuals with varying levels of the underlying trait. Specifically, the slope provides the rate at which the likelihood of endorsing a given response category or higher changes as the underlying irritability severity level changes. Thus, items with lower slopes are less able to discriminate irritability severity levels because the likelihood of endorsing various response categories is similar for both low and high irritability severity levels. The category threshold parameters (b) reflect the point along the latent trait severity dimension at which an individual has a 50% probability of endorsing an item response category compared to all higher response categories. Additionally, item locations, which represent each item's severity, are derived from the mean of the item's category thresholds.

Data were scaled to the existing MAPS‐TL scoring metric (Wakschlag et al., 2012) using fixed anchor item calibration (Baker, 2001). For the 22 core items, item parameters were fixed to the parameter values from the Preschool version of the MAPS‐TL (MAPS‐TL‐PS; Wakschlag et al., 2012) to allow estimation of the ESA sample mean and standard deviation on the scale of the existing MAPS‐TL‐PS parameters. Item response theory parameters for the 16 Temper Loss items that are unique to the Youth version were estimated.

Of note, given that the dimensionality of items impacts IRT, prior to conducting the IRT, a confirmatory factor analysis (CFA) was conducted to test whether the data fit a unidimensional model as shown in previous studies of the MAPS‐TL (Wakschlag et al., 2014; Wakschlag et al., 2012; Wakschlag et al., 2015, see also Alam et al., 2023; Kirk et al., 2023). The comparative fit index (CFI), Tucker–Lewis index (TLI), and root mean square error of approximation (RMSEA) were examined to determine the extent to which the model was a good fit to the data. Comparative fit index and TLI values greater than 0.90, and RMSEA values less than 0.08 are considered indicators of acceptable fit (Browne & Cudeck, 1993; Hu & Bentler, 1999).

2.3.2. Aim 2: Development of a clinically optimized screener

Identification of clinically optimized items

Stepwise logistic regression analyses using forward entry with likelihood ratio comparison of models were utilized to identify the predictive value of each irritability item from the MAPS‐TL‐Youth scale using FLIS cross‐domain impairment as a broad impairment indicator.

Derivation of cutoff score for clinically optimized screener

Receiver operating characteristic analyses were conducted to identify an irritability cutoff score that balances sensitivity and specificity in relation to having any DSM irritability‐related diagnoses (i.e., ODD, DMDD, MDD, and/or PDD). The criterion variable was the sum score of the irritability items most related to FLIS cross‐domain impairment. The classification variable was a dichotomous variable that reflected the presence or absence of any concurrent DSM irritability‐related diagnoses, thereby allowing for the creation of a transdiagnostic cutoff point for irritability‐related disorders at school age. Youden index values were utilized to optimize the highest level of sensitivity (i.e., true positive rate) and specificity (i.e., true negative rate).

Test of predictive utility

A hierarchical linear regression analysis was conducted to examine the extent to which scoring above the irritability threshold on the Youth MAPS‐TL clinically optimized screener at the ESA wave increased the likelihood of a pre‐adolescent irritability‐related diagnosis. Block 1 consisted of covariates to account for potential confounding variables (i.e., age, gender, race/ethnicity, maternal education, ESA irritability‐related diagnoses, ESA cross‐domain impairment), and Block 2 consisted of a dichotomized variable reflecting whether youth fell above or below the cutoff score.

2.4. Statistical software

Statistical analyses were conducted using IBM SPSS statistical software (version 28.0.1.1) and RStudio (version 2022.07.0). IBM SPSS statistical software was used for descriptive statistics and regression analyses. For analyses in RStudio, the Psych package was used to conduct the CFA (Revelle, 2022) and the Plink package was used for linking (Weeks, 2010) as part of the IRT analyses; the OptimalCutpoints package was used to derive empirical cutoff scores (López‐Ratón et al., 2014).

3. RESULTS

3.1. Aim 1: Characterization of the normal: Abnormal spectrum

3.1.1. Item response percentages and frequencies

Table 2 shows item response percentages and frequencies across response categories. While parents did not generally report that irritability was common, five items were endorsed by at least 50% of parents as occurring regularly (at least monthly): “Become frustrated easily,” “Yell angrily at someone,” “Lose temper or have a tantrum when frustrated, angry, or upset,” “Act irritable,” and “Get annoyed easily,” suggesting that these may be relatively normative behaviors in this age group. Items that were never or rarely endorsed by most parents and may therefore be suggestive of atypical behaviors in this age group tended to involve irritability lasting for an extended period of time (e.g., “Act angry all day long,”), occurring in unexpected contexts (e.g., “Get in a bad mood even during fun activities”), manifesting as aggressive or destructive behavior (e.g., “Hit, bite, or kick during a tantrum, 'fall‐out', or melt‐down,”), and leading to impaired peer and/or family functioning (e.g., “Cause family outings/activities to revolve around preventing him/her from having outbursts”).

3.1.2. Item response theory analyses

Results from the CFA showed that a one‐factor model was a good fit, CFI = 0.97, TLI = 0.97, RMSEA = 0.06. Table 3 displays IRT anchor estimates for the 22 core Temper Loss items from the preschool calibration as well as IRT parameters for the 16 youth specific items. Item response theory parameters include item slopes, category thresholds, and item locations. Item slopes on the MAPS‐TL‐Youth ranged from 1.46 to 3.71, indicating that items varied on their ability to differentiate irritability severity levels. The item with the lowest slope was “Lose temper or have a tantrum when doing schoolwork,” indicating that it provides relatively poor discrimination of underlying severity. The item with the highest slope was “Lose temper or have a tantrum when frustrated, angry, or upset,” indicating that it provides relatively good discrimination of underlying severity. While this item was endorsed to a relatively high degree in this age group (by 52.32% of parents as occurring in the last month), IRT analyses indicate that it was also good at differentiating children across the severity spectrum.

TABLE 3.

Graded response model (GRM) item parameter estimates for temper loss items.

Items Category thresholds
Slope (a) Rarely or higher (b1) Some days of week or higher (b2) Most days of week or higher (b3) Every day or higher (b4) Many times a day (b5) Item location mean (b)
Have difficulty calming down when angry 2.23 −0.09 1.00 1.86 2.45 2.87 1.62
Become frustrated easily 1.94 −0.51 0.68 1.66 2.27 2.75 1.37
Have a short fuse (become angry quickly) 2.51 −0.07 0.92 1.69 2.22 2.70 1.49
Yell angrily at someone 2.08 −0.41 0.85 1.79 2.38 2.88 1.50
Stamp feet or hold breath during a temper tantrum, 'fall‐out', or melt‐down 1.90 0.11 1.07 1.94 2.57 2.99 1.74
Lose temper or have a tantrum when frustrated, angry, or upset 3.71 −0.28 0.75 1.45 2.00 2.41 1.27
Lose temper or have a tantrum when tired, hungry, or sick 2.76 −0.29 0.71 1.56 2.16 2.57 1.34
Lose temper or have a tantrum to get something he/she wanted 3.12 −0.24 0.77 1.53 2.09 2.50 1.33
Act irritable 1.99 −0.25 0.96 1.99 2.66 3.18 1.71
Lose temper or have a tantrum during daily routines, such as bedtime, mealtime, or getting dressed 2.78 −0.24 0.74 1.66 2.09 2.61 1.37
Break or destroy things during a temper tantrum, 'fall‐out', or melt‐down 2.48 0.63 1.53 2.17 2.54 2.93 1.96
Have a temper tantrum, 'fall‐out', or melt‐down 3.38 −0.15 0.80 1.53 1.98 2.43 1.32
Stay angry for a long time 2.00 0.61 1.97 2.69 3.13 3.42 2.36
Have a temper tantrum, 'fall‐out', or melt‐down that lasted longer than 5 min 2.77 0.22 1.18 2.13 2.59 2.93 1.81
Lose temper or have a tantrum with other adults (e.g., teacher, babysitter, family member) 2.51 0.38 1.47 2.28 2.67 2.99 1.96
Lose temper or have a tantrum with you or other parent 3.34 −0.15 0.83 1.59 2.09 2.59 1.39
Keep on having a temper tantrum, 'fall‐out', or melt‐down even when you tried to help him/her calm down 3.26 0.43 1.33 2.02 2.41 2.73 1.78
Have a hot or explosive temper 3.18 0.45 1.26 1.84 2.25 2.69 1.70
Have a temper tantrum, 'fall‐out', or melt‐down until exhausted 2.77 0.69 1.51 2.16 2.57 2.94 1.98
Get extremely angry 3.11 0.33 1.21 1.92 2.31 2.71 1.70
Lose temper or have a tantrum 'out of the blue' or for no reason 2.91 0.67 1.53 2.21 2.60 3.02 2.00
Hit, bite, or kick during a tantrum, 'fall‐out', or melt‐down 2.44 0.81 1.62 2.16 2.74 3.10 2.09
Lose temper or have a tantrum when doing schoolwork* 1.46 −0.13 1.00 2.19 2.84 3.77 1.93
Make you feel that you have to 'walk on eggshells' to avoid setting him/her off* 2.10 1.08 1.73 2.42 2.71 3.68 2.32
Act angry, irritable, or grouchy throughout most of the day* 2.25 0.36 1.50 2.22 2.58 3.16 1.96
Act angry, irritable, or grouchy no matter what you do* 2.36 0.58 1.68 2.71 3.10 3.52 2.32
Get in a bad mood even during fun activities* 2.19 0.56 1.83 2.82 3.21 4.02 2.49
Seem sullen* 1.60 1.02 2.40 3.24 3.50 3.67 2.77
Get annoyed easily* 2.32 −0.43 0.84 1.68 2.45 2.99 1.51
Lose temper easily* 3.07 0.24 1.08 1.70 2.26 2.81 1.62
Have less expected of him/her than other children in the family because of angry mood* 2.05 1.26 2.00 2.88 3.11 4.10 2.67
Act grumpy or grouchy* 1.91 −0.28 0.98 2.05 2.54 3.19 1.70
Complain about others, activities; not satisfied by anything* 2.00 0.46 1.55 2.32 2.74 3.79 2.17
Act grouchy most of the day* 2.32 0.74 1.77 2.63 2.80 3.89 2.37
Have tantrums (temper outburst, 'fall‐out', or melt‐down) that get in the way of getting along with other children* 2.87 0.93 1.78 2.22 2.61 3.10 2.13
Spoil something for your family because of his/her bad mood* 1.97 0.39 1.68 2.70 3.07 3.19 2.21
Cause family outings/activities to revolve around preventing him/her from having outbursts* 2.84 0.97 1.83 2.30 2.76 3.07 2.18
Act angry all day long* 2.18 1.63 2.59 3.25 3.49 3.93 2.98
Open in a new tab

Note: Asterisks indicate items that are developmentally based additions to the MAPS‐TL‐Youth version.

Category thresholds (b1–5) indicate the approximate irritability severity level at which the transition from one response category to the next (e.g., from “Never in the past month” to “Rarely [less than once per week]”) is likely to take place. Items that were endorsed more frequently by parents tended to have lower thresholds at a given response category, indicating that lower levels of irritability severity are needed to endorse these items at a given response category or higher. For example, for the response category of “Some (1–3) days of the week,” the item “Become frustrated easily” had a threshold of b 2 = 0.68, while the item “Act angry all day long” had a threshold of b 2 = 2.59. This indicates that endorsing this response category or higher for “Become frustrated easily” is associated with lower irritability severity, and endorsing this response category or higher for “Act angry all day long” is associated with much greater irritability severity. Moreover, within each item, thresholds were higher at response categories reflecting greater frequency ratings. For example, the thresholds for the item “Lose temper or have a tantrum with you or other parent” were b 2 = 0.83 and b 4 = 2.09, indicating that for this item, only modest irritability severity is needed to endorse “Some (1–3) days of the week” or higher, whereas greater severity is needed to endorse “Every day of the week” or higher.

The mean of the category thresholds provides information about each item's location along the irritability severity dimension, with higher values indicating greater irritability severity. As shown in Figure 1, item means ranged from 1.27 (“Lose temper or have a tantrum when frustrated, angry, or upset”) to 2.98 (“Act angry all day long”). Notably, of the top 10 most severe items, nine are from the developmentally specific items added for the MAPS‐TL Youth version.

FIGURE 1.

FIGURE 1

Open in a new tab

Irritability Severity Spectrum for MAPS‐TL‐Youth Temper Loss Items. Asterisks indicate items that are developmentally based additions to the MAPS‐TL‐Youth version.

3.2. Aim 2: Development of a clinically optimized screener

3.2.1. Identification of clinically optimized items

The final stepwise logistic regression model identified two of the 38 MAPS‐TL‐Youth items that were predictive of FLIS cross‐domain impairment: “Become frustrated easily” (p = 0.019) and “Act irritable” (p = 0.025); this final model performed significantly better than the baseline model (Δχ2 = 30.14, df = 2, p < 0.001) as well as the step 1 model, which included “Act irritable” with the baseline model (Δχ2 = 5.43, df = 1, p = 0.020). For each unit increase in the frequencies of “Become frustrated easily” and “Act irritable,” the odds of observing cross‐domain impairment also increased by 1.39 and 1.43, respectively. These two items explained 15.0% of the variance in cross‐domain impairment, and the model was a good fit (Hosmer and Lemeshow: χ2 = 1.59, df = 5, p = 0.902).

3.2.2. Derivation of cutoff score for clinically optimized screener

A clinically optimized cutoff score was derived using the sum of the ratings from the two MAPS‐TL‐Youth items identified in the previous logistic regression, “Become frustrated easily” and “Act irritable” (Mean = 2.21, SD = 2.01, Range = 0–10). Based on Receiver operating characteristic analyses, an optimal cutoff score of 4 was a sensitive and specific indicator of DSM irritability‐related diagnoses (i.e., ODD, DMDD, MDD, and PDD). Area under the curve for irritability‐related diagnoses (Area under the curve = 0.82, p < 0.001) indicated good classification accuracy of the irritability cutoff score. The cutoff score of 4 (peak Youden Index = 0.53) optimally balanced sensitivity (69%) and specificity (84%). In other words, using the derived cutoff score, 69% of children who were diagnosed with an irritability‐related diagnosis were correctly classified as meeting the cutoff criteria, and 84% of children who were not diagnosed with an irritability‐related diagnosis were correctly classified as not meeting the cutoff criteria (See Figure 2).

FIGURE 2.

FIGURE 2

Open in a new tab

Receiver Operating Characteristic (ROC) Curve for Clinically Optimized Irritability Screener (Criterion Variable) and DSM Irritability‐Related Diagnosis (Classification Variable). Arrow shows peak sensitivity and specificity.

3.2.3. Test of predictive utility

A multivariate linear regression model showed that scoring above the optimized irritability cutoff score at ESA was predictive of an irritability‐related diagnosis in preadolescence (p < 0.001), even after including age, sex, race, maternal education, and ESA irritability‐related diagnoses and cross‐domain impairment as covariates in block 1 (final model: χ2 = 58.92, df = 8, p < 0.001). The addition of the MAPS‐TL‐Youth irritability cutoff score accounted for an additional 9.2% of the variance in preadolescent irritability‐related diagnoses (the final model accounted for 39% of the variance) and was a good fit for the data (Hosmer and Lemeshow: χ2 = 6.42, df = 8, p = 0.600). Youth who scored above the irritability cutoff score at ESA were 7.27 times more likely (95% CI = 2.66—19.85) to have a DSM irritability‐related diagnosis at preadolescence.

4. DISCUSSION

The present investigation is the first to model the normal:abnormal spectrum of irritability at ESA; specifically testing the utility of developmentally specific items for youth. We also demonstrated the reliability and validity of a clinically optimized irritability screener for ESA, with the goal of providing a clinically useful transdiagnostic indicator of psychopathology risk. Modeling irritability along a severity spectrum allows for the prodromal identification of irritability as it unfolds, enabling earlier identification of at‐risk patterns, such as children who fall in the “gray area’ of concern who would benefit from preventive intervention to mitigate escalation. Of note, this screener had substantial incremental utility for prediction of subsequent psychopathology, above and beyond concurrent diagnosis. The current study expands operationalization of RDOC's neurodevelopmental, dimensional and transdiagnostic approach to measurement at ESA. This builds on its validation in previous early childhood studies (Krogh‐Jespersen et al., 2021; Wakschlag et al., 2012, 2014, 2018; Wiggins et al., 2018). A developmental lens is particularly useful for identifying irritabilty patterns that are cause for concern at ESA, a time when irritability typically begins to decrease (Wiggins et al., 2014; Yu et al., 2022) due to the development of improved self‐regulatory capacities (Zeman et al., 2006). We have identified frequences and qualities of behavior during this developmental period indicates cause for concern.

The first aim of this study was to examine the normal:abnormal spectrum of irritability in ESA children. Consistent with prior work in early childhood (Wakschlag et al., 2012) irritability was common but not predominant. While some behaviors were exhibited regularly by most children (e.g., “Become frustrated easily,” “Lose temper or have a tantrum when frustrated, angry, or upset”), daily occurrence was rare‐a pattern detected as early as the transition to toddlerhood (Krogh‐Jespersen et al., 2021). This highlights that a marker of atypical irritability is heightened frequency for normative expressions. Moreover, as previously described for young children (Wakschlag et al., 2018), certain features of irritability are pathognomonic indicators in their very occurrence and were not commonly occurring in most children—i.e., irritability that lasts for an extended period of time, occurs in unexpected contexts, manifests as aggressive or destructive behavior, and leads to impaired peer and/or family functioning. This is consistent with the findings of Alam et al., 2023) and Kirk et al. (2023) validating the MAPS‐TL‐Youth with preadolescent and adolescent samples, respectively and broadly mirrored as early as toddlerhood as shown by Wiggins, Urena Rosario and Zhang et al. (2023). These results highlight the utility of anchoring reports in objective frequency ratings as well as capturing irritability features, as markers of atypicality will vary based on the behavior and developmental period in question.

Results from the IRT analysis corroborate the above‐mentioned findings and provide additional information about each item's location along the severity dimension. Of the top 10 most severe items, nine were specific to the Youth version of the MAPS‐TL. Notably, many of these items are characteristic of tonic rather than phasic irritability, in contrast to early childhood when dysregulated tantrums are key to demarcation of atypicality. This suggests that features of tonic irritability may be more informative for clinical discrimination of greater underlying irritability severity in school age children. Replication in independent and clinical samples will be an important next step. These findings also underscore the importance of a developmentally specified model, demonstrating the incremental utility of items that capture the developmental phenotype of irritability within this age period. Indeed, without these Youth‐specific items, the highest irritability severity in this developmental period would not be captured.

The second aim of the study was to develop a clinically optimized screener to quickly and efficiently identify children who may require further assessment and/or treatment. We generated a parsimonious model that reflects two irritability features that are uniquely associated with concurrent cross‐domain impairment as well as an irritability cutoff score that has good sensitivity and specificity in relation to DSM irritability‐related diagnoses and is predictive of future diagnostic status. Interestingly, the two items that comprise the screener (i.e., “Become frustrated easily” and “Act irritable”) are not the most severe based on IRT analyses. In fact, both items occur normatively, reported to occur in ≥50% of youth at least monthly, and are only clinically informative at higher frequencies. This suggests that the frequency of these features of irritability, rather than simply their presence, demarcates clinically salient irritability. Notably, “become frustrated easily” was also empirically identified for MAPS‐TL clinically optimized screeners developed for preschoolers (Wiggins et al., 2018), preadolescents (Alam et al., 2023), and adolescents (Kirk et al., 2023). This item may be a clinical indicator of irritability across age groups because low frustration tolerance is the substrate of irritable behavior, without which dysregulated, frequent or pervasive irritability is not likely. The current study also identified the item, “Act irritable,” which is substantially different from the one identified in preschoolers (“Break or destroy things during a temper tantrum, 'fall‐out', or melt‐down”). While acting irritable reflects tonic irritability, destructive tantrums reflect phasic irritability. This supports the IRT model suggesting that severe irritability in ESA youth requires consideration of tonic irritability.

There are several limitations in the current study that suggest avenues for future research. Common method variance may have biased the results as mothers were informants for irritability, impairment, and clinical diagnoses. Although this was mitigated to some extent by the different measures and methods used (e.g., parent‐report measure, clinician interview), multimethod and multi‐informant assessments should be used to replicate and extend findings in large population‐based samples, and in clinical populations. Despite the sociodemographic diversity of the current sample, there was insufficient power to examine variation in irritability features across sex, race, ethnicity, or SES. This is an important area for future work.

In summary, the current study is the first to characterize the irritability spectrum, from normative misbehaviors to markers of atypicality, and to develop a clinically optimized screener within the developmental context of ESA. Findings demonstrate the need for developmental specification in the assessment of irritability as the manifestation of irritability changes as children develop. Indeed, questions pertaining to tonic irritability in this age group may capture youth with more severe levels of irritability, as demonstrated in the IRT analysis. This is a foundational step toward the developmentally specific assessment of irritability in ESA children, highlighting the potential utility of the MAPS‐TL‐Youth. Direct examination of the utility of the full scale for specifying atypical irritability trajectories and elucidating brain:behavior linkages in mechanistic research in neurodevelopmental studies, and of the feasibility and utility of the clinically optimized screener in real‐world clinical settings are important next steps.

AUTHOR CONTRIBUTIONS

Emily Hirsch: Conceptualization; Writing—original draft; Writing—review and editing. Tasmia Alam: Conceptualization; Writing—original draft. Nathan Kirk: Conceptualization; Formal analysis; Writing—original draft. Katherine B. Bevans: Formal analysis. Margaret Briggs‐Gowan: Funding acquisition; Investigation; Project administration. Lauren S. Wakschlag: Conceptualization; Funding acquisition; Investigation; Supervision; Writing—original draft; Writing—review and editing. Jillian Lee Wiggins: Conceptualization; Supervision; Writing—original draft; Writing—review and editing. Amy Roy: Conceptualization; Supervision; Writing—original draft; Writing—review and editing.

CONFLICT OF INTEREST STATEMENT

The authors declare that they have no conflicts of interest.

ACKNOWLEDGMENTS

The authors gratefully acknowledge the contribution of Erica Anderson (Northwestern University) for outstanding oversight of clinical measurements. The MAPS study was supported by NIMH grants: R01MH082830, 2U01MH082830 to Lauren Wakschlag and U01MH090301 to Margaret Briggs‐Gowan. The other authors received no additional funding that contributed to this work. The funder (NIH) had no role in the design or conduct of the study.

Hirsch, E. , Alam, T. , Kirk, N. , Bevans, K. B. , Briggs‐Gowan, M. , Wakschlag, L. S. , Wiggins, J. L. , & Roy, A. K. (2023). Developmentally specified characterization of the irritability spectrum at early school age: Implications for pragmatic mental health screening. International Journal of Methods in Psychiatric Research, 32(S1), e1985. 10.1002/mpr.1985

Jillian L. Wiggins and Amy K. Roy should be considered joint senior authors.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.

REFERENCES

  1. Abramovitch, A. , Abramowitz, J. S. , McKay, D. , Cham, H. , Anderson, K. S. , Farrell, L. J. , Geller, D. A. , Hanna, G. L. , Mathieu, S. , McGuire, J. F. , Rosenberg, D. R. , Evelyn, S. S. , Storch, E. A. , & Wilhelm, S. (2022). An ultra‐brief screening scale for pediatric obsessive‐compulsive disorder: The OCI‐CV‐5. Journal of Affective Disorders, 312, 208–216. 10.1016/j.jad.2022.06.009 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Achenbach, T. M. , & Ruffle, T. M. (2000). The Child Behavior Checklist and related forms for assessing behavioral/emotional problems and competencies. Pediatrics in Review, 21(1), 265–271. 10.1542/pir.21-8-265 [DOI] [PubMed] [Google Scholar]
  3. Alam, T. , Kirk, N. , Hirsch, E. , Briggs‐Gowan, M. , Wakschlag, L. S. , Roy, A. K. , & Wiggins, J. L. (2023). Characterizing the spectrum of irritability in preadolescence: Dimensional and pragmatic applications. International Journal of Methods in Psychiatric Research. e1988. 10.1002/mpr.1988 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Baker, F. B. (2001). The basics of item response theory (2 ed.). ERIC. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Brotman, M. A. , Kircanski, K. , & Leibenluft, E. (2017). Irritability in children and adolescents. Annual Review of Clinical Psychology, 13(1), 317–341. 10.1146/annurev-clinpsy-032816-044941 [DOI] [PubMed] [Google Scholar]
  6. Brotman, M. A. , Schmajuk, M. , Rich, B. A. , Dickstein, D. P. , Guyer, A. E. , Costello, E. J. , Egger, H. L. , Angold, A. , Pine, D. S. , & Leibenluft, E. (2006). Prevalence, clinical correlates, and longitudinal course of severe mood dysregulation in children. Biological Psychiatry, 60(9), 991–997. 10.1016/j.biopsych.2006.08.042 [DOI] [PubMed] [Google Scholar]
  7. Browne, M. W. , & Cudeck, R. (1993). Alternative ways of assessing model fit. In Bollen K. A. & Long J. S. (Eds.), Testing structural equation models (pp. 136–162). Sage. [Google Scholar]
  8. Burke, J. D. , Boylan, K. , Rowe, R. , Duku, E. , Stepp, S. D. , Hipwell, A. E. , & Waldman, I. D. (2014). Identifying the irritability dimension of ODD: Application of a modified bifactor model across five large community samples of children. Journal of Abnormal Psychology, 123(4), 841–851. 10.1037/a0037898 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Carlson, G. A. , Silver, J. , & Klein, D. N. (2022). Psychometric properties of the Emotional Outburst Inventory (EMO‐I): Rating what children do when they are irritable. The Journal of Clinical Psychiatry, 83(2), 39382. Article 21m14015. 10.4088/JCP.21m14015 [DOI] [PubMed] [Google Scholar]
  10. Copeland, W. E. , Shanahan, L. , Egger, H. , Angold, A. , & Costello, E. J. (2014). Adult diagnostic and functional outcomes of DSM‐5 disruptive mood dysregulation disorder. American Journal of Psychiatry, 171(6), 668–674. 10.1176/appi.ajp.2014.13091213 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Dougherty, L. R. , Galano, M. M. , Chad‐Friedman, E. , Olino, T. M. , Bufferd, S. J. , & Klein, D. N. (2021). Using item response theory to compare irritability measures in early adolescent and childhood samples. Assessment, 28(3), 918–927. 10.1177/1073191120936363 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Dougherty, L. R. , Smith, V. C. , Bufferd, S. J. , Stringaris, A. , Leibenluft, E. , Carlson, G. A. , & Klein, D. N. (2013). Preschool irritability: Longitudinal associations with psychiatric disorders at age 6 and parental psychopathology. Journal of the American Academy of Child and Adolescent Psychiatry, 52(12), 1304–1313. 10.1016/j.jaac.2013.09.007 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Evans, S. C. , Bonadio, F. T. , Bearman, S. K. , Ugueto, A. M. , Chorpita, B. F. , & Weisz, J. R. (2020). Assessing the irritable and defiant dimensions of youth oppositional behavior using CBCL and YSR items. Journal of Clinical Child and Adolescent Psychology, 49(6), 804–819. 10.1080/15374416.2019.1622119 [DOI] [PubMed] [Google Scholar]
  14. Evans, S. C. , Burke, J. D. , Roberts, M. C. , Fite, P. J. , Lochman, J. E. , de la Peña, F. R. , & Reed, G. M. (2017). Irritability in child and adolescent psychopathology: An integrative review for ICD‐11. Clinical Psychology Review, 53, 29–45. 10.1016/j.cpr.2017.01.004 [DOI] [PubMed] [Google Scholar]
  15. Evans, S. C. , Corteselli, K. A. , Edelman, A. , Scott, H. , & Weisz, J. R. (2022). Is irritability a top problem in youth mental health care? A multi‐informant, multi‐method investigation. Child Psychiatry and Human Development, 54(4), 1027–1041. 10.1007/s10578-021-01301-8 [DOI] [PubMed] [Google Scholar]
  16. Gaffrey, M. S. , & Luby, J. L. (2012). Kiddie schedule for affective disorders and Schizophrenia ‐ early childhood version (KSADS‐EC). Washington University School of Medicine. [Google Scholar]
  17. Hawes, M. T. , Carlson, G. A. , Finsaas, M. C. , Olino, T. M. , Seely, J. R. , & Klein, D. N. (2020). Dimensions of irritability in adolescents: Longitudinal associations with psychopathology in adulthood. Psychological Medicine, 50(16), 2759–2767. 10.1017/S0033291719002903 [DOI] [PubMed] [Google Scholar]
  18. Hu, L. t. , & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. 10.1080/10705519909540118 [DOI] [Google Scholar]
  19. Jo, S.‐J. , Jeong, H. , Son, H. J. , Lee, H. K. , Lee, S.‐Y. , Kweon, Y.‐S. , & Yim, H. W. (2020). Diagnostic usefulness of an ultra‐brief screener to identify risk of online gaming disorder for children and adolescents. Psychiatry Investigation, 17(8), 762–768. 10.30773/pi.2019.0279 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Kaat, A. J. , Blackwell, C. K. , Estabrook, R. , Burns, J. L. , Petitclerc, A. , Briggs‐Gowan, M. J. , Gershon, R. C. , Cella, D. , Perlman, S. B. , & Wakschlag, L. S. (2019). Linking the child behavior checklist (CBCL) with the multidimensional assessment profile of disruptive behavior (MAP‐DB): Advancing a dimensional spectrum approach to disruptive behavior. Journal of Child and Family Studies, 28(2), 343–353. 10.1007/s10826-018-1272-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Kaufman, J. , Birmaher, B. , Axelson, D. , Perepletchikova, F. , Brent, D. , & Ryan, N. (2016). Schedule for affective disorders and Schizophrenia for school‐age children‐present and lifetime version DSM‐5 (KSADS‐PL DSM‐5). Western Psychiatric Institute and Clinic and Yale University. [Google Scholar]
  22. Kirk, N. , Hirsch, E. , Alam, T. , Wakschlag, L. S. , Wiggins, J. L. , & Roy, A. K. (2023). A pragmatic, clinically optimized approach to characterizing adolescent irritability: Validation of parent and adolescent reports on the MAPS Temper Loss Scale. International Journal of Methods in Psychiatric Research. e1986. 10.1002/mpr.1986 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Krogh‐Jespersen, S. , Kaat, A. J. , Petitclerc, A. , Perlman, S. B. , Briggs‐Gowan, M. J. , Burns, J. L. , Adam, H. , Nili, A. , Gray, L. , & Wakschlag, L. S. (2021). Calibrating temper loss severity in the transition to toddlerhood: Implications for developmental science. Applied Developmental Science, 26(4), 785–798. 10.1080/10888691.2021.1995386 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. López‐Ratón, M. , Rodríguez‐Álvarez, M. X. , Cadarso‐Suárez, C. , & Gude‐Sampedro, F. (2014). OptimalCutpoints: An R package for selecting optimal cutpoints in diagnostic tests. Journal of Statistical Software, 61(8), 1–36. 10.18637/jss.v061.i08 [DOI] [Google Scholar]
  25. Melvin, G. A. , Tonge, B. J. , Mulraney, M. , Gordon, M. , Taffe, J. , & Klimkeit, E. (2018). The Cranky Thermometers: Visual analogue scales measuring irritability in youth. Journal of Adolescence, 64(1), 146–154. 10.1016/j.adolescence.2018.02.008 [DOI] [PubMed] [Google Scholar]
  26. Mian, N. D. , Soto, T. W. , Briggs‐Gowan, M. J. , & Carter, A. S. (2018). The Family Life Impairment Scale: Factor structure and clinical utility with young children. Journal of Clinical Child and Adolescent Psychology, 47(Supp 1), S530–S541. 10.1080/15374416.2018.1458313 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Orri, M. , Galera, C. , Turecki, G. , Boivin, M. , Tremblay, R. E. , Geoffroy, M.‐C. , & Côté, S. M. (2019). Pathways of association between childhood irritability and adolescent suicidality. Journal of the American Academy of Child and Adolescent Psychiatry, 58(1), 99–107.e103. 10.1016/j.jaac.2018.06.034 [DOI] [PubMed] [Google Scholar]
  28. Revelle, W. (2022). psych: Procedures for psychological, psychometric, and personality research. Northwestern University. Retrieved from https://CRAN.R‐project.org/package=psych [Google Scholar]
  29. Rivera‐Riquelme, M. , Piqueras, J. A. , & Cuijpers, P. (2019). The Revised Mental Health Inventory‐5 (MHI‐5) as an ultra‐brief screening measure of bidimensional mental health in children and adolescents. Psychiatry Research, 274, 247–253. 10.1016/j.psychres.2019.02.045 [DOI] [PubMed] [Google Scholar]
  30. Roy, A. K. , Klein, R. G. , Angelosante, A. , Bar‐Haim, Y. , Leibenluft, E. , Hulvershorn, L. , Dixon, E. , Dodds, A. , & Spindel, C. (2013). Clinical features of young children referred for impairing temper outbursts. Journal of Child and Adolescent Psychopharmacology, 23(9), 588–596. 10.1089/cap.2013.0005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Samejima, F. (1969). Estimation of latent ability using a response pattern of graded scores. Psychometrika monograph supplement, 34(1), 1–97. 10.1007/BF03372160 [DOI] [Google Scholar]
  32. Savage, J. , Verhulst, B. , Copeland, W. , Althoff, R. R. , Lichtenstein, P. , & Roberson‐Nay, R. (2015). A genetically informed study of the longitudinal relation between irritability and anxious/depressed symptoms. Journal of the American Academy of Child and Adolescent Psychiatry, 54(5), 377–384. 10.1016/j.jaac.2015.02.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Sorcher, L. K. , Goldstein, B. L. , Finsaas, M. C. , Carlson, G. A. , Klein, D. N. , & Dougherty, L. R. (2022). Preschool irritability predicts adolescent psychopathology and functional impairment: A 12‐year prospective study. Journal of the American Academy of Child and Adolescent Psychiatry, 61(4), 554–564.e551. 10.1016/j.jaac.2021.08.016 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Stringaris, A. , Cohen, P. , Pine, D. S. , & Leibenluft, E. (2009). Adult outcomes of youth irritability: A 20‐year prospective community‐based study. American Journal of Psychiatry, 166(9), 1048–1054. 10.1176/appi.ajp.2009.08121849 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Stringaris, A. , Goodman, R. , Ferdinando, S. , Razdan, V. , Muhrer, E. , Leibenluft, E. , & Brotman, M. A. (2012). The affective reactivity index: A concise irritability scale for clinical and research settings. Journal of Child Psychology and Psychiatry, 53(11), 1109–1117. 10.1111/j.1469-7610.2012.02561.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Vidal‐Ribas, P. , Brotman, M. A. , Valdivieso, I. , Leibenluft, E. , & Stringaris, A. (2016). The status of irritability in psychiatry: A conceptual and quantitative review. Journal of the American Academy of Child and Adolescent Psychiatry, 55(7), 556–570. 10.1016/j.jaac.2016.04.014 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Wakschlag, L. S. , Briggs‐Gowan, M. J. , Choi, S. W. , Nichols, S. R. , Kestler, J. , Burns, J. L. , Carter, A. S. , & Henry, D. (2014). Advancing a multidimensional, developmental spectrum approach to preschool disruptive behavior. Journal of the American Academy of Child and Adolescent Psychiatry, 53(1), 82–96. 10.1016/j.jaac.2013.10.011 [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Wakschlag, L. S. , Choi, S. W. , Carter, A. S. , Hullsiek, H. , Burns, J. , McCarthy, K. , Leibenluft, E. , & Briggs‐Gowan, M. J. (2012). Defining the developmental parameters of temper loss in early childhood: Implications for developmental psychopathology. Journal of Child Psychology and Psychiatry, 53(11), 1099–1108. 10.1111/j.1469-7610.2012.02595.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Wakschlag, L. S. , Estabrook, R. , Petitclerc, A. , Henry, D. , Burns, J. L. , Perlman, S. B. , Voss, J. L. , Pine, D. S. , Leibenluft, E. , & Briggs‐Gowan, M. L. (2015). Clinical implications of a dimensional approach: The normal: Abnormal spectrum of early irritability. Journal of the American Academy of Child and Adolescent Psychiatry, 54(8), 626–634. 10.1016/j.jaac.2015.05.016 [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Wakschlag, L. S. , Perlman, S. B. , Blair, R. J. , Leibenluft, E. , Briggs‐Gowan, M. J. , & Pine, D. S. (2018). The neurodevelopmental basis of early childhood disruptive behavior: Irritable and callous phenotypes as exemplars. American Journal of Psychiatry, 175(2), 114–130. 10.1176/appi.ajp.2017.17010045 [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Wakschlag, L. S. , Tolan, P. H. , & Leventhal, B. L. (2010). Research review: ‘Ain’t misbehavin’: Towards a developmentally‐specified nosology for preschool disruptive behavior. Journal of Child Psychology and Psychiatry, 51(1), 3–22. 10.1111/j.1469-7610.2009.02184.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Weeks, J. P. (2010). plink: An R package for linking mixed‐format tests using IRT‐based methods. Journal of Statistical Software, 35(12), 1–33. 10.18637/jss.v035.i12 21603108 [DOI] [Google Scholar]
  43. Wiggins, J. L. , Briggs‐Gowan, M. J. , Estabrook, R. , Brotman, M. A. , Pine, D. S. , Leibenluft, E. , & Wakschlag, L. S. (2018). Identifying clinically significant irritability in early childhood. Journal of the American Academy of Child and Adolescent Psychiatry, 57(3), 191–199. 10.1016/j.jaac.2017.12.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Wiggins, J. L. , Mitchell, C. , Stringaris, A. , & Leibenluft, E. (2014). Developmental trajectories of irritability and bidirectional associations with maternal depression. Journal of the American Academy of Child and Adolescent Psychiatry, 53(11), 1191–1205. 10.1016/j.jaac.2014.08.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Wiggins, J. L. , Roy, A. K. , & Wakschlag, L. S. (2023a). Introduction to special issue: MAPping affective dimensions of behavior: Methodologic and pragmatic advancement of the multidimensional assessment profile scales (MAPS) scales. International Journal of Methods in Psychiatric Research. e1990. 10.1002/mpr.1990 [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Wiggins, J. L. , Ureña Rosario, A. , Zhang, Y. , MacNeill, L. , Yu, Q. , Norton, E. , Smith, J. D. , & Wakschlag, L. S. (2023b). Advancing earlier transdiagnostic identification of mental health risk: A pragmatic approach at the transition to toddlerhood. International Journal of Methods in Psychiatric Research. e1989. 10.1002/mpr.1989 [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Yu, Q. , Hodgdon, E. A. , Kryza‐Lacombe, M. , Osuna, L. , Bozzetto, L. , Ciro, D. , Wakschlag, L. S. , & Wiggins, J. L. (2022). Roads diverged: Developmental trajectories of irritability from toddlerhood through adolescence. Journal of the American Academy of Child and Adolescent Psychiatry, 62(4), 457–471. 10.1016/j.jaac.2022.07.849 [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Zeman, J. , Cassano, M. , Perry‐Parrish, C. , & Stegall, S. (2006). Emotion regulation in children and adolescents. Journal of Developmental and Behavioral Pediatrics, 27(2), 155–168. 10.1097/00004703-200604000-00014 [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Articles from International Journal of Methods in Psychiatric Research are provided here courtesy of Wiley

RESOURCES