Measurement Invariance of the Affective Reactivity Index Across Five Countries

Measurement Invariance of the Affective Reactivity Index Across Five Countries | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Measurement Invariance of the Affective Reactivity Index Across Five Countries Jamilah Silver, Diogo DeSousa, Lourdes Ezpeleta, Daniel Klein, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9066353/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Objective Irritability is a globally relevant dimension of youth psychopathology, yet cross-national comparisons require evidence that assessment tools function equivalently across countries and languages. We examined the reliability, factor structure, and measurement invariance of the Affective Reactivity Index (ARI) across Brazil, China, Japan, Spain, and the United States (US). Method Community samples (N = 6,195; ages 6–18 years) completed parent- or youth-report ARI versions. Single-factor confirmatory factor analyses evaluated model fit and internal consistency. Multi-group CFA tested measurement invariance across countries. Where invariance was supported, cross-country differences and age and sex associations were examined. Results Internal consistency was acceptable to good across countries and informants. A single-factor structure was broadly supported. For parent report, measurement invariance was established across China and Japan using the original response format and across China, Japan, and the United States when items had to be dichotomized due to lack of endorsement of the highest category in item 4 by US parents. For youth report, threshold and loading invariance were supported, but scalar invariance was not, indicating cross-country differences in intercepts. Parent-reported irritability was higher in China and Japan than in the United States, whereas youth-reported irritability was highest in Brazil. Parents reported higher irritability in boys and younger youth; youth self-report showed no significant age or sex effects. Conclusion The ARI captures a broadly comparable irritability construct across countries, particularly for parent report. Cross-national mean comparisons using youth report should be interpreted cautiously. Establishing measurement invariance is essential for valid international research on pediatric irritability. Irritability measurement invariance cultural differences affective reactivity index youth Figures Figure 1 Figure 2 Introduction Irritability is one of the most common reasons for youth mental health referrals [ 12 ] and a robust predictor of adverse outcomes [ 21 , 37 ]. Importantly, recent large-scale international work demonstrates that irritability is not confined to a single national context, but is observed at comparable levels across multiple countries, with broadly consistent associations with depression, anxiety, bullying, and life satisfaction [ 29 ]. These findings underscore irritability as a globally relevant dimension of youth psychopathology and highlight the need for assessment tools that function equivalently across countries and languages. As interest in cross-country research on irritability increases [ 35 ], a critical methodological question emerges: can irritability be measured in a way that means the same thing across different countries and languages? Before comparisons of irritability levels or correlates can be interpreted, it is necessary to establish that the scale assesses the same general construct (i.e., has the same dimensional structure) across countries (configural invariance), that individual items relate to the underlying construct of irritability similarly across groups (loading invariance), and that respondents use the response options in comparable ways (threshold invariance). When these conditions are met, observed scores can be meaningfully compared across countries (scalar invariance). If these requirements are not satisfied, apparent cross-country differences may reflect measurement artifacts rather than true differences in irritability, leading to inaccurate conclusions [ 32 ]. These issues are formally evaluated through tests of measurement invariance. The Affective Reactivity Index [ARI; 30] is a concise, 7-item measure of irritability with parent- and youth-report versions and is among the most widely used instruments for assessing irritability in young people. Over the past decade, the ARI has been employed in dozens of studies and has accumulated a substantial psychometric literature, particularly in the United States, the United Kingdom (UK) [ 1 ], Australia, and Western Europe [ 11 , 15 , 16 , 18 ], including validation in both clinical and community samples [ 11 , 25 , 30 ]. In addition, the ARI has been translated, and psychometrically evaluated in a growing number of non-Western contexts, including Brazil, Spain, China, Japan, and Turkey [ 10 , 13 , 23 , 25 , 27 , 36 ]. To date, the ARI has been translated into at least 20 languages, with all versions freely available through an open-access repository. However, despite this expanding international use, prior research has not systematically examined whether the ARI measures irritability equivalently across countries and languages, which is a prerequisite for valid cross-national comparisons. This gap is particularly important given recent evidence from UK samples that levels, correlates, and even interpretation of irritability vary by age and sex [ 1 , 38 ]. Developmental expectations and sex norms differ across countries and cultures [ 8 ] and may influence how irritability is expressed, perceived, and reported [ 4 ]. Without establishing that irritability is measured equivalently across countries and languages, it is unclear whether observed differences in age or sex associations reflect true developmental or sex variation or differences in measurement. Accordingly, the primary objective of the present study was to determine whether the parent- and youth-report versions of the Affective Reactivity Index function equivalently across countries and language versions. In practical terms, this means testing whether the ARI measures irritability consistently across groups, such that scores have comparable meaning regardless of the country or language in which the scale is administered. We evaluated this by examining multiple levels of measurement invariance across five countries, Brazil, China, Japan, Spain, and the US, spanning South America, Asia, Europe, and North America. Establishing measurement invariance is a prerequisite for meaningful cross-country comparisons, as it allows researchers to distinguish true differences in irritability from those arising from how items are interpreted or endorsed. Nevertheless, demonstrating measurement invariance alone does not establish that cross-country comparisons are substantively meaningful. Rather, it provides the foundation for interpreting such comparisons. Therefore, contingent on evidence of measurement invariance, a secondary aim of this study was to examine whether associations between irritability and age and sex vary across countries. This step allows us to evaluate whether known developmental correlates of irritability operate similarly across contexts once measurement equivalence is established. By pairing tests of measurement invariance with follow-up analyses of age and sex associations, the present study seeks to move beyond psychometric adequacy alone and toward a more informative understanding of how irritability manifests and relates to development across countries. Method Sample and procedure The present study used child and adolescent samples (Mean age = 12.4, SD = 3.1, range 6–18 years; 50% female) from five countries. Sample sizes ranged from 133 (Brazil) to 4800 (Japan) participants, with an aggregated sample size of 6195 participants. China, Japan, and the United States included parent-reported irritability data; Brazil, China, Spain, and the United States included youth-reported irritability data. Data collection was approved by Ethics Committees from institutions of each country. A detailed description of the sample and procedure for each country is provided in the supplemental. Measures The ARI [ARI; 30] has two versions, a parent-reported and a self- reported version. Parents receive the following instruction: "In the last 6 months and compared to others of the same age, how well does each of the following statements describe the behavior/feelings of your child? Please try to answer all questions." The self-report version mirrors this instruction but pertains to "your behavior/feelings." After the introductory statement, respondents encounter six items related to feelings/behaviors specific to irritability. These include being "Easily annoyed by others", "Often loses temper", "Stays angry for a long time", "Angry most of the time", "Gets angry frequently", and "Loses temper easily". Additionally, a seventh item evaluates impairment due to irritability: "Overall, irritability causes him/her (or 'me' in the self-report) problems." Importantly, the parent- and self-report scales consist of identical items. Each item is scored on a 3-point Likert scale: 'not true' (scored as '0'), 'somewhat true' (scored as '1'), and 'certainly true' (scored as '2'). The total score is calculated as the sum of the first six items, with the impairment item not contributing to the total score. Consequently, the possible score range for each respondent spans from 0 to 12. This composite score provides a quantitative representation of affective reactivity, specifically focusing on irritability-related behaviors and feelings as reported by either the parent or the individual themselves. Statistical Analyses All analyses were preregistered on the Open Science Framework ( https://osf.io/d2zfp/overview ). Any deviations from the preregistered plan are documented in Supplementary Table 1 . Analyses were conducted separately by informant. Parent-reported irritability data were available from China, Japan, and the United States, whereas youth-reported irritability data were available from Brazil, China, Spain, and the United States. Because both informants were available only in China and the United States, formal analyses of informant effects were not conducted. First, descriptive statistics were calculated for each sample and country, including item-level distributions for irritability measured by the Affective Reactivity Index (ARI), reported separately for parents and young people. Ordinal logistic regression models were used to compare item responses across countries, with post-hoc Bonferroni-corrected comparisons. Next, we evaluated the factor structure of the ARI within each country and informant using confirmatory factor analysis (CFA) for ordered categorical indicators. Internal consistency was assessed using McDonald’s omega, estimated separately for parents and young people within each country. Measurement invariance of the ARI across countries was then tested using a multiple-group CFA framework for categorical indicators. We evaluated increasingly restrictive models including configural invariance, threshold and loading invariance, and threshold, loading, and intercept invariance. Establishing intercept invariance allows meaningful comparison of latent means across countries. Finally, we examined between-country variability and the effects of sex and age on irritability severity using linear regression models with ARI total scores as the outcome. Confirmatory factor analyses and measurement invariance tests were conducted in Mplus version 8.8 [ 26 ]. All remaining analyses were conducted in R [ 34 ]. Additional details regarding estimation procedures, model fit indices, and invariance testing criteria are provided in the Supplementary Methods. Results Descriptive statistics Table 1 provides the sample characteristics. Figure 1 shows a plot with the relative frequencies of the categories for each ARI item by country and informant. The exact relative frequencies of endorsement of the response options for each ARI item, as well as item corrected comparison across countries, separately for youth and parent reports are reported in Supplementary Table 2 . Table 1 Characteristics of the Samples N for youth report Brazil China Japan Spain US 133 395 - 384 467 N for parent report - 403 4,800 - 475 Female, n (%) 72 (54) 194 (48) 2400 (50) 202 (53) 224 (47) Age, M (SD) range 11 (1.6) 8–17 13.4 (2.5) 9–17 12.4 (3.5) 6–18 12 12.7 (0.5) 11–14 Year(s) of data collection 2013 2022 2020 2018-19 2014/2016 Across the three countries, parents in China consistently reported higher irritability scores than those in Japan and the US. For Item 1 (“Annoyed”), Chinese parents rated their children higher than both Japanese and US parents (all p < 0.001). A similar pattern emerged for “Often loses temper”, with scores highest in China, followed by Japan, and lowest in the US (all p < 0.001). For Items 3–5 (“Stays angry”; “Angry most of the time”; “Angry frequent”), both China and Japan scored higher than the US (all p < 0.001). Item 6 (“Loses temper easily”) again showed higher scores in China compared with Japan and the US (all p < 0.001). Finally, for the impairment item (Item 7), Chinese parents reported more irritability‑related problems than both US (p < 0.001) and Japanese parents (p < 0.001), and Japanese parents also reported more impairment than US parents (p = 0.013). Overall, parent‑reported irritability was consistently highest in China, intermediate in Japan, and lowest in the US. Youth‑reported irritability showed a different cross‑national pattern, with Brazilian youth consistently endorsing the highest levels across items. For Item 1 (“Annoyed”), Brazil, China, and the US all scored higher than Spain (all p < 0.001). For “Often loses temper”, Brazil scored higher than China, Spain, and the US (all p < 0.001), while China scored higher than the US (p = 0.011) and Spain scored higher than the US (p = 0.017). Item 3 (“Stays angry”) showed the clearest gradient, with Brazil scoring higher than Spain, which in turn scored higher than China and the US (all p < 0.001). For Item 4 (“Angry most of the time”), Brazil again exceeded China, Spain, and the US (all p < 0.001). Item 5 (“Angry frequent”) showed Brazil scoring higher than China, the US, and Spain (all p ≤ 0.001), and Spain scoring higher than the US (p = 0.008). For Item 6 (“Loses temper easily”), Brazil scored higher than China, Spain, and the US (all p < 0.001), with China and Spain also scoring higher than the US (p < 0.001 and p = 0.048, respectively). Finally, for the impairment item (Item 7), both Brazil and China reported more irritability‑related problems than Spain and the US (all p < 0.001). Overall, youth reports indicated the highest irritability in Brazil, followed by China, with Spain and the US generally showing lower levels. Single Factor CFA Item loadings are depicted in Fig. 2 by country and informant and provided in full in Supplementary Table 3 . “Often loses temper” was, consistently across countries and informants, one of the items with the strongest loadings (0.81 to 0.98), except for parent report in Japan, where “Loses temper easily” had the strongest loading (0.95). On the other hand, “Stays angry for a long time” was consistently the item with the weakest loading (0.49 to 0.86), with the exceptions of parent report in the US and youth report in Brazil, where “Easily annoyed by others” had a weaker loading (0.79 and 0.69, respectively). Results of goodness of fit of single-factor CFA for each country and by informant are shown in Table 2 . McDonald´s Omega reliability coefficients were good for parent report in all countries (Japan: 0.81; China: 0.89; US: 0.87), and for youth report in most countries (China: 0.82; US: 0.81; Brazil: 0.84) except Spain (0.73), for which the coefficient showed a lower, but acceptable reliability. For parent report across countries, CFI and TLI demonstrated good fit (> 0.950) for Japan, China, and the US. However, whereas RMSEA was acceptable for China (0.074) and good for the US (0.040), it was poor for Japan (0.097). For youth report, CFI and TLI demonstrated good fit (> 0.950) for China, US, and Brazil. However, whereas RMSEA was good for China (0.056) and Brazil (< 0.001), it was poor for the US (0.101). In the case of youth report in Spain, all fit indices demonstrated a poor fit. Modification indices for US and Spain suggested that model fit would improve considerably if items “Often loses temper” and “Loses temper easily” were allowed to correlate. Effectively, this modification led to a better fit for US (CFI = 0.991, TLI = 0.983, RMSEA = 0.065) and Spain (CFI = 0.993, TLI = 0.988, RMSEA = 0.043). This modified model was used as a configural model to test measurement invariance for child report. Table 2 Fit Indices of Confirmatory Factor Analysis (CFA) for One-Factor Solution of ARI Items for Parent and Youth Report Parent report Japan China US Brazil Spain CFI 0.993 0.990 0.999 - - TLI 0.988 0.984 0.998 - - RMSEA 0.097 0.074 0.040 - - McDonald's ω 0.81 0.89 0.87 - - Youth report Japan China US Brazil Spain CFI - 0.995 0.975 1.000 0.913 TLI - 0.992 0.958 1.000 0.855 RMSEA - 0.056 0.101 < 0.001 0.147 McDonald's ω - 0.82 0.81 0.84 0.73 Measurement Invariance Results of measurement invariance assessment are displayed in Table 3 . For parent report, none of the parents from the US endorsed a score of 2 in item 4, which did not allow us to include the US when testing MI with the ARI using the original 3-level structure of the items. Therefore, for parent report, we assessed MI for 3-level items for China and Japan only, and then for 2-level items (by combining scores 1 and 2) for China, Japan and the US. For parent report, invariance across countries was established at all levels; across China and Japan with the 3-level items, and across China, Japan, and the US with the dichotomized items. Although values of chi-square differences in the comparison of models suggested otherwise, possibly driven by the large sample from Japan, differences in CFI and RMSEA were within the limits to achieve invariance. For youth report, threshold and loading invariance was established across Brazil, China, Spain, and the US. However, after fixing intercepts, invariance was not achieved, according to differences in chi-square, CFI, and RMSEA. Modification indices suggested that freeing the intercept means of item 1 (“Annoyed by others”) produced the most improvement in fit (CFI = 0.982, TLI = 0.982, RMSEA = 0.068); nevertheless, although differences in RMSEA were acceptable, differences in CFI in reference to the configural model were still over the threshold. Table 3 Fit indices of measurement invariance of single-factor model of ARI Parent-report (3-level items) across China (n = 403), and Japan (referent group, n = 4,800) Model (M) χ 2 (df) CFI TLI RMSEA SRMR Comp. ΔCFI ΔRMSEA ΔSRMR Δ χ 2 (df), p -value M1: Configural (all free) 421.6 (18) 0.993 0.989 0.093 0.031 - - - - - M2: Threshold invariance 421.6 (18) 0.993 0.989 0.093 0.031 - - - - - M3: Threshold and loading invariance 366.1 (23) 0.994 0.993 0.076 0.031 M1/M2 0.001 -0.017 0.000 10.9 (5), p = 0.053 M4: Threshold, loading, and intercept invariance 481.8 (28) 0.993 0.992 0.079 0.035 M1/M2 0.000 -0.014 0.004 129.9 (10), p < 0.001 M3 -0.001 0.003 0.004 126.2 (5), p < 0.001 Parent-report (2-level items) across China (n = 403), Japan (n = 4,800), and US (referent group, n = 475) Model (M) χ 2 (df) CFI TLI RMSEA SRMR Comp. ΔCFI ΔRMSEA ΔSRMR Δ χ 2 (df) , p -value M1: Configural (all free) 235.8 (27) 0.996 0.994 0.064 0.033 - - - - - M2: Threshold invariance 235.8 (27) 0.996 0.994 0.064 0.033 - - - - - M3: Threshold and loading invariance 217.9 (37) 0.997 0.996 0.051 0.042 M1/M2 0.001 -0.013 0.009 38.4 (10), p < 0.001 M4: Threshold, loading, and intercept invariance 417.7 (47) 0.993 0.994 0.065 0.047 M1/M2 -0.003 0.001 0.014 202.3 (20), p < 0.001 M3 -0.004 0.014 0.005 271.2 (10), p < 0.001 Youth-report (3-level items) across Brazil (n = 133), China (n = 395), Spain (n = 384), and US (referent group, n = 467) Model (M) χ 2 (df) CFI TLI RMSEA SRMR Comp. ΔCFI ΔRMSEA ΔSRMR Δ χ 2 (df) , p -value M1: Configural (all free) 64.3 (32) 0.994 0.989 0.054 0.033 - - - - - M2: Threshold invariance 64.3 (32) 0.994 0.989 0.054 0.033 - - - - - M3: Threshold and loading invariance 88.7 (47) 0.992 0.990 0.051 0.037 M1/M2 -0.002 -0.003 0.004 27.0 (15), p < 0.001 M4: Threshold, loading, and intercept invariance 288.1 (62) 0.958 0.960 0.103 0.056 M1/M2 -0.036 0.049 0.023 204.9 (30), p < 0.001 M3 -0.034 0.052 0.019 179.4 (15), p < 0.001 M5: M4 + free intercept of item 1 154.0 (59) 0.982 0.982 0.068 0.047 M1/M2 -0.012 0.014 0.014 87.4 (27), p < 0.001 Variation of irritability by Country, Sex and Age For parent report, irritability total scores were significantly higher in Japan (M = 1.77, SD = 2.63; b = 0.62, SE = 0.12, p < 0.001) and China (M = 2.49, SD = 2.31; b = 1.34, SE = 0.17, p < 0.001) compared to US (M = 1.15, SD = 1.95), and higher in China than Japan (b = 0.72, SE = 0.13, p < 0.001). Across countries, parents scored higher levels of irritability in males (b=-0.17, SE = 0.07, p = 0.012) and at younger ages (b=-0.03, SE = 0.01, p = 0.007) (Table 4 ). For youth report, irritability total scores were significantly higher in Brazil (M = 3.96, SD = 3.36) compared to US (M = 1.79, SD = 2.11; b = 2.18, SE = 0.22, p < 0.001), Spain (M = 1.94, SD = 1.94; b = 2.03, SE = 0.23, p < 0.001) and China (M = 2.06, SD = 2.21; b = 1.91, SE = 0.23, p < 0.001). However, no effects on irritability were evident for sex (b = 0.06, SE = 0.12, p = 0.625) or age (b=-0.04, SE = 0.04, p = 0.327) (Table 4 ). Table 4 Model Estimates for Effects of Sex and Age on ARI Total Score Across Countries for Parent and Youth Report Parent report Model results for child sex Term Estimate SE t p-value Intercept 1.40 0.15 9.10 < 0.001 Japan (vs US) 0.63 0.12 5.10 < 0.001 China (vs US) 1.34 0.17 7.77 < 0.001 Sex -0.17 0.07 -2.51 0.012 Model results for child age Term Estimate SE t p-value Intercept 1.51 0.18 8.52 < 0.001 Japan (vs US) 0.61 0.12 4.96 < 0.001 China (vs US) 1.36 0.17 7.84 < 0.001 Age -0.03 0.01 -2.69 0.007 Child report Model results for child sex Term Estimate SE t p-value Intercept 1.70 0.21 8.21 < 0.001 Brazil (vs US) 2.18 0.22 9.85 < 0.001 Spain (vs US) 0.15 0.16 0.98 0.325 China (vs US) 0.27 0.15 1.75 0.081 Sex 0.06 0.12 0.49 0.625 Model results for child age Term Estimate SE t p-value Intercept 2.31 0.54 4.29 < 0.001 Brazil (vs US) 2.11 0.23 9.11 < 0.001 Spain (vs US) 0.12 0.16 0.79 0.430 China (vs US) 0.30 0.16 1.88 0.060 Age -0.04 0.04 -0.98 0.327 Discussion The present study systematically examined the measurement properties of the ARI across multiple countries and informants. Using community samples from Brazil, China, Japan, Spain, and the US, we evaluated reliability, factor structure, and measurement invariance, and then examined cross-country differences in irritability levels, associated impairment, and age and sex correlates. Overall, findings provide encouraging support for the ARI across diverse cultural contexts, while highlighting important caveats, particularly for youth self-report and interpretation of mean differences. Across countries and informants, the ARI showed good internal consistency and a largely robust single-factor structure. McDonald’s omega values were acceptable to good in all samples, with slightly lower reliability for Spanish youth. Items indexing frequent and explosive anger (e.g., “Often loses temper,” “Loses temper easily”) showed the strongest loadings across settings, whereas “Stays angry for a long time” loaded more weakly. The rank ordering of standardized loadings was largely preserved across countries, strengthening confidence that a common irritability dimension was being captured despite differences in language and context. This pattern aligns with conceptualizations emphasizing high-arousal, rapidly escalating anger as central to pediatric irritability [ 2 , 31 ], whereas more chronic anger may overlap with other affective constructs. In Spanish youth, a residual correlation between the two temper-loss items suggests additional covariance beyond the latent factor. This may reflect shared behavioral expression (youth who lose temper easily often do so frequently), contextual triggers, or potential sample enrichment for oppositional behavior given the two-phase design. Regardless of mechanism, this finding underscores the importance of item-level evaluation in cross-cultural psychometric work. Measurement invariance analyses indicated that the ARI could support meaningful cross-country comparisons under certain conditions. For parent report, invariance was achieved across China and Japan using the original 3-level structure, and across China, Japan, and the US when items had to be treated as binary indicators due to lack of endorsement of the highest response category in item 4 in the US sample. Although dichotomization reduces variability, these results suggest that parent-reported ARI scores reflect a comparable latent irritability construct across these contexts. Sparse endorsement of the highest category in community samples also highlights a practical consideration: the 3-level format may be less sensitive to upper-range variation in lower-risk populations, whereas it may be more informative in clinical or high-risk samples. For youth self-report, threshold and loading invariance were supported across countries, but intercept invariance was not. Elevated intercepts in Brazil indicate that, for a given level of latent irritability, Brazilian youth were more likely to endorse higher response categories. Thus, cross-country differences in youth-reported mean levels may partly reflect differences in endorsement thresholds rather than latent severity. Within this psychometrically constrained framework, we observed clear cross-country differences in irritability and associated impairment. At the item level, parents in China consistently endorsed higher irritability across ARI items, followed by Japan, with the US showing the lowest endorsement rates. In contrast, Brazilian youth reported the highest irritability across most items, with Spain and the US generally showing lower endorsement. Total ARI score comparisons, conducted after establishing measurement invariance, showed a parallel pattern, with higher parent-reported irritability in China and Japan relative to the US, and higher youth-reported irritability in Brazil relative to the other countries. The impairment item followed similar cross-country patterns, with China and Japan scoring higher than US for parent report and Brazil and China scoring higher than Spain and US for youth report, indicating that perceptions of irritability-related problems varied across settings. However, because impairment was examined at the item level rather than modeled as an outcome adjusted for total severity, these findings reflect co-occurring differences in symptom endorsement and perceived problems rather than impairment independent of symptom level. These patterns may reflect both contextual and cultural influences. Contextual stressors, such as economic inequality, neighborhood violence, or academic pressure, may amplify the functional consequences of irritability in certain environments. Cultural models of the self further suggest that collectivistic contexts emphasizing interdependence and social harmony may discourage socially disengaging emotions such as anger more strongly than individualistic contexts [ 19 , 24 ]. In such settings, even moderate anger may be more norm-violating and therefore more likely to be labeled as problematic. Prior cross-national research using measures such as the Child Behavior Checklist and the Strengths and Difficulties Questionnaire similarly shows that symptom endorsement and perceived impairment do not map neatly onto disorder prevalence [ 14 , 28 ]. Our findings extend this literature by demonstrating that even when a unidimensional irritability factor is supported, item-level endorsement patterns and perceived impairment can vary across settings, underscoring the importance of distinguishing latent severity from culturally shaped endorsement thresholds. Regarding developmental correlates, parent report indicated higher irritability in boys and younger children, consistent with prior research on externalizing manifestations of irritability [ 7 ]. In contrast, youth self-report showed no significant associations with age or sex. These discrepancies suggest that developmental patterns may be informant-dependent and shaped by culturally specific expectations regarding anger expression, highlighting the importance of multi-informant assessment[ 1 ]. Taken together, the findings provide substantial support for the ARI as a cross-culturally applicable measure of irritability, particularly for parent report. Youth-report mean differences should be interpreted with care given the lack of full intercept invariance. In cross-national designs, parent report may be preferable for mean comparisons, whereas youth report may be better suited for within-country analyses and association testing. The observation that impairment endorsement varied across countries alongside differences in symptom severity further supports calls for culture-sensitive thresholds for clinically significant irritability [ 21 ]. Several limitations should be considered when interpreting these findings. First, the country samples differed in recruitment strategy, setting, and likely enrichment for behavior problems (e.g., school-based convenience samples, online panels, and multistage or enriched recruitment designs). Because sampling influences both the distribution of irritability and thresholds for labeling behaviors as impairing, observed differences between countries may partly reflect sampling variation rather than cultural context per se. Accordingly, mean differences should be interpreted as differences between these specific samples rather than definitive population-level cross-national differences. At the same time, despite these differences in recruitment approaches, the ARI demonstrated broadly similar reliability and factor-loading patterns across settings. This convergence suggests that the core irritability construct captured by the ARI is relatively robust to heterogeneity in sampling, even if mean levels and endorsement thresholds vary across samples. Second, the samples were not nationally representative of their countries of origin and were drawn from different time periods, which may further limit generalizability. Third, some countries contributed data from only one informant, limiting the ability to fully test multi-informant measurement invariance across all sites. Fourth, for the U.S. parent-report data, lack of endorsement of the highest response category for one item required dichotomization. Although this approach is psychometrically defensible, it reduces variability and may obscure finer-grained distinctions in irritability at lower levels. More broadly, this pattern highlights a limitation of the ARI: although the measure was originally developed for clinical and high-risk populations, it may be less sensitive to variation at the lower end of the irritability distribution in community samples. Finally, because the present study focused exclusively on community samples, future research should examine whether similar measurement properties hold in clinical populations, where the distribution, severity, and meaning of irritability may differ and where the ARI may demonstrate greater sensitivity to higher levels of symptom expression. Despite these limitations, this study provides one of the most comprehensive examinations to date of the cross-cultural measurement properties of a widely used irritability scale. By integrating item-level psychometrics, multi-group CFA, and analyses of developmental correlates and impairment, we provide a foundation for more rigorous cross-cultural research on pediatric irritability. The ARI appears to capture a broadly similar latent construct across diverse cultural and linguistic contexts, particularly for parent report, while also revealing meaningful variation in endorsement thresholds and perceived impairment. As international collaborations in irritability research expand, including coordinated efforts such as the Cross-Cultural Consortium on Irritability [ 35 ], careful attention to measurement invariance and cultural interpretation will be essential to ensure that observed differences reflect true variation rather than artifacts of sampling or response style. Declarations Author Contribution J.S., A.S., and P.V.-R.B. conceived and designed the study, coordinated data pooling, conducted the analyses, and contributed to drafting and revising the manuscript. J.S. wrote the initial draft of the manuscript. D.D., L.E., D.N.K., E.L., S.L., E.M., G.A.S., F.T., and W.-L.T. contributed data and critically revised the manuscript for important intellectual content. All authors reviewed and approved the final manuscript. Data Availability The datasets analyzed in the current study are not publicly available because they originate from multiple independent studies across countries and are subject to local ethical and institutional restrictions. Data may be available from the corresponding author upon reasonable request and with permission from the relevant data custodians and ethics committees. References Bekiropoulou A, Eyre O, Heron J, Thapar A, Riglin L (2025) Measuring irritability across childhood, adolescence, and young adulthood: an investigation of measurement invariance by age, sex, and informant. European child & adolescent psychiatry:1–12 Brotman MA, Kircanski K, Stringaris A, Pine DS, Leibenluft E (2017) Irritability in youths: A translational model. Am J Psychiatry 174:520–532 Brown TA (2015) Confirmatory factor analysis for applied research. Guilford Chaplin TM (2015) Gender and emotion expression: A developmental contextual perspective. Emot Rev 7:14–21 Chen FF (2007) Sensitivity of goodness of fit indexes to lack of measurement invariance. Struct equation modeling: multidisciplinary J 14:464–504 Cheung GW, Rensvold RB (2002) Evaluating goodness-of-fit indexes for testing measurement invariance. Struct Equ Model 9:233–255 Chin M, Robson DA, Woodbridge H, Hawes DJ (2025) Irritability as a transdiagnostic construct across childhood and adolescence: a systematic review and meta-analysis. Clin Child Fam Psychol Rev 28:101–124 Davis E, Greenberger E, Charles S, Chen C, Zhao L, Dong Q (2012) Emotion experience and regulation in China and the United States: how do culture and gender shape emotion responding? Int J Psychol 47:230–239 DeSousa DA, Stringaris A, Leibenluft E, Koller SH, Manfro GG, Salum GA (2013) Adaptação transcultural e propriedades psicométricas preliminares do Affective Reactivity Index em jovens brasileiros: implicações para a irritabilidade medida pelo DSM-5. Trends Psychiatry Psychother 35:171–180 DeSousa DA, Stringaris A, Leibenluft E, Koller SH, Manfro GG, Salum GA (2013) Cross-cultural adaptation and preliminary psychometric properties of the Affective Reactivity Index in Brazilian Youth: implications for DSM-5 measured irritability. Trends Psychiatry Psychother 35:171–180 Evans SC, Abel MR, Doyle RL, Skov H, Harmon SL (2021) Measurement and correlates of irritability in clinically referred youth: Further examination of the Affective Reactivity Index. J Affect Disord 283:420–429 Evans SC, Corteselli KA, Edelman A, Scott H, Weisz JR (2023) Is irritability a top problem in youth mental health care? A multi-informant, multi-method investigation. Child Psychiatry Hum Dev 54:1027–1041 Ezpeleta L, Penelo E, de la Osa N, Navarro JB, Trepat E (2020) How the Affective Reactivity Index (ARI) works for teachers as informants. J Affect Disord 261:40–48 Goodman A, Heiervang E, Fleitlich-Bilyk B, Alyahri A, Patel V, Mullick MS, Slobodskaya H, Dos Santos DN, Goodman R (2012) Cross-national differences in questionnaires do not necessarily reflect comparable differences in disorder prevalence. Soc Psychiatry Psychiatr Epidemiol 47:1321–1331 Grassi ML, Valente D, Berardi A, Tofani M, Galeoto G (2023) Validation and Analysis of the Psychometric Properties of Two Irritability-Measuring Tools: The Affective Reactivity Index (ARI) and the Born-Steiner Irritability Scale (BSIS) in the Italian Adult and Adolescent Populations. Int J Environ Res Public Health 20:4607 Haller SP, Kircanski K, Stringaris A, Clayton M, Bui H, Agorsor C, Cardenas SI, Towbin KE, Pine DS, Leibenluft E (2020) The Clinician Affective Reactivity Index: validity and reliability of a clinician-rated assessment of irritability. Behav Ther 51:283–293 Lt H, Bentler PM (1999) Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct equation modeling: multidisciplinary J 6:1–55 Kalvin CB, Gladstone TR, Jordan R, Rowley S, Marsh CL, Ibrahim K, Sukhodolsky DG (2021) Assessing irritability in children with autism spectrum disorder using the affective reactivity index. J Autism Dev Disord 51:1496–1507 Kitayama S, Mesquita B, Karasawa M (2006) Cultural affordances and emotional experience: socially engaging and disengaging emotions in Japan and the United States. J Personal Soc Psychol 91:890 Klein DN, Finsaas MC (2017) The Stony Brook Temperament Study: Early antecedents and pathways to emotional disorders. Child Dev Perspect 11:257–263 Leibenluft E, Allen LE, Althoff RR, Brotman MA, Burke JD, Carlson GA, Dickstein DP, Dougherty LR, Evans SC, Kircanski K (2024) Irritability in youths: A critical integrative review. Am J Psychiatry 181:275–290 Li C-H (2016) Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares. Behav Res Methods 48:936–949 Lu B, Fang Y, Cai J, Chen Z (2024) Psychometric Evaluation of the Affective Reactivity Index Among Children and Adolescents in China: A Multi-Method Assessment Approach. Assessment 31:1020–1037 Markus HR, Kitayama S (2014) Culture and the self: Implications for cognition, emotion, and motivation. College student development and academic life. Routledge, pp 264–293 Mulraney MA, Melvin GA, Tonge BJ (2014) Psychometric properties of the affective reactivity index in Australian adults and adolescents. Psychol Assess 26:148 Muthén LK, Muthén B (2017) Mplus user's guide: Statistical analysis with latent variables, user's guide. Muthén & Muthén Osada M, Mori H, Takahashi M, Shinkawa H, Adachi M, Adachi M, Saito T, Nakamura K (2025) Psychometric properties and cross-cultural adaptation of the Japanese version of the Affective Reactivity Index: A community‐based study of adolescent irritability. Psychiatry Clin Neurosciences Rep 4:e70169 Roessner V, Becker A, Rothenberger A, Rohde LA, Banaschewski T (2007) A cross-cultural comparison between samples of Brazilian and German children with ADHD/HD using the Child Behavior Checklist. Eur Arch Psychiatry Clin NeuroSci 257:352–359 Silver J, Leibenluft E, Tseng WL, Klein DN, Vidal-Ribas P, Naim R, Patalay P, McElroy E, Stringaris A (2025) A large multinational study of irritability in adolescents. Child Adolesc Mental Health 30:352–363 Stringaris A, Goodman R, Ferdinando S, Razdan V, Muhrer E, Leibenluft E, Brotman MA (2012) The Affective Reactivity Index: a concise irritability scale for clinical and research settings. J Child Psychol Psychiatry 53:1109–1117 Stringaris A, Vidal-Ribas P, Brotman MA, Leibenluft E (2018) Practitioner review: definition, recognition, and treatment challenges of irritability in young people. J Child Psychol Psychiatry 59:721–739 Svetina D, Rutkowski L, Rutkowski D (2020) Multiple-group invariance with categorical outcomes using updated guidelines: An illustration using M plus and the lavaan/semtools packages. Struct equation modeling: multidisciplinary J 27:111–130 Takahashi F, Honda H (2021) Prevalence of clinical-level emotional/behavioral problems in schoolchildren during the coronavirus disease 2019 pandemic in Japan: A prospective cohort study. JCPP Adv 1:e12007 Team RC (2020) RA language and environment for statistical computing. R Foundation for Statistical, Computing Tseng W-L, Bellaert N, Benton TD, Brotman MA, Evans SC, Herrington JD, Jha MK, Lansford JE, Linke JO, Michalska KJ (2025) Cross-Cultural Consortium on Irritability (C3I): An International Network for Research on Cultural Similarities and Differences in Irritability. JAACAP open Turan S, Ermiş Ç, Eray Ş, Yavuz BE, Uzman S, Ozbek MM, Tunçtürk M, Çıray RO, İnal N (2022) Psychometric properties of The Clinician Affective Reactivity Index for Assessment of Irritability in a clinical sample of Turkish children and adolescents. Scandinavian J Child Adolesc Psychiatry Psychol 10:24 Vidal-Ribas P, Brotman MA, Valdivieso I, Leibenluft E, Stringaris A (2016) The status of irritability in psychiatry: a conceptual and quantitative review. J Am Acad Child Adolesc Psychiatry 55:556–570 Vidal-Ribas P, Krebs G, Silver J, Tseng W-L, Ford T, Stringaris A (2025) The hidden burden: self-reported irritability in adolescent girls signals higher psychiatric risk. BMC Public Health 25:1832 Wu H, Estabrook R (2016) Identification of confirmatory factor analysis models of different levels of invariance for ordered categorical outcomes. Psychometrika 81:1014–1045 Additional Declarations No competing interests reported. Supplementary Files ARIMISupplementalMaterial2026FINALcopy.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 02 May, 2026 Reviews received at journal 28 Apr, 2026 Reviewers agreed at journal 11 Apr, 2026 Reviewers agreed at journal 08 Apr, 2026 Reviewers agreed at journal 21 Mar, 2026 Reviewers invited by journal 19 Mar, 2026 Editor assigned by journal 11 Mar, 2026 Submission checks completed at journal 11 Mar, 2026 First submitted to journal 08 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Recerca","correspondingAuthor":false,"prefix":"","firstName":"Pablo","middleName":"Vidal-Ribas","lastName":"Belil","suffix":""}],"badges":[],"createdAt":"2026-03-08 20:08:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9066353/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9066353/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105319632,"identity":"4afad9cc-ef89-4199-ac29-e3161527eac6","added_by":"auto","created_at":"2026-03-24 17:05:59","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":739368,"visible":true,"origin":"","legend":"\u003cp\u003eRelative frequency of ARI items scores by country and informant.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9066353/v1/f93e607f30f4f4a9b7a2ff69.jpeg"},{"id":105319631,"identity":"73a2be47-c769-4094-81f2-47cd358b70e7","added_by":"auto","created_at":"2026-03-24 17:05:58","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":11003,"visible":true,"origin":"","legend":"\u003cp\u003eLoadings of ARI items in a single-factor CFA by country and informant\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9066353/v1/7b33d3a7045fbdf26b0677a6.png"},{"id":105565087,"identity":"be0798fc-9ac7-4fce-b8de-ace255823d7c","added_by":"auto","created_at":"2026-03-27 12:51:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1932558,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9066353/v1/b0b0e688-8ee2-4ef6-8a14-36be1dbad988.pdf"},{"id":105319630,"identity":"8f574174-f2e0-4af6-851d-5e07c3a3f656","added_by":"auto","created_at":"2026-03-24 17:05:58","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":57592,"visible":true,"origin":"","legend":"","description":"","filename":"ARIMISupplementalMaterial2026FINALcopy.docx","url":"https://assets-eu.researchsquare.com/files/rs-9066353/v1/78d64112724c10e8f8357f84.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Measurement Invariance of the Affective Reactivity Index Across Five Countries","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIrritability is one of the most common reasons for youth mental health referrals [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and a robust predictor of adverse outcomes [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Importantly, recent large-scale international work demonstrates that irritability is not confined to a single national context, but is observed at comparable levels across multiple countries, with broadly consistent associations with depression, anxiety, bullying, and life satisfaction [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. These findings underscore irritability as a globally relevant dimension of youth psychopathology and highlight the need for assessment tools that function equivalently across countries and languages.\u003c/p\u003e \u003cp\u003eAs interest in cross-country research on irritability increases [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], a critical methodological question emerges: can irritability be measured in a way that means the same thing across different countries and languages? Before comparisons of irritability levels or correlates can be interpreted, it is necessary to establish that the scale assesses the same general construct (i.e., has the same dimensional structure) across countries (configural invariance), that individual items relate to the underlying construct of irritability similarly across groups (loading invariance), and that respondents use the response options in comparable ways (threshold invariance). When these conditions are met, observed scores can be meaningfully compared across countries (scalar invariance). If these requirements are not satisfied, apparent cross-country differences may reflect measurement artifacts rather than true differences in irritability, leading to inaccurate conclusions [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. These issues are formally evaluated through tests of measurement invariance.\u003c/p\u003e \u003cp\u003eThe Affective Reactivity Index [ARI; 30] is a concise, 7-item measure of irritability with parent- and youth-report versions and is among the most widely used instruments for assessing irritability in young people. Over the past decade, the ARI has been employed in dozens of studies and has accumulated a substantial psychometric literature, particularly in the United States, the United Kingdom (UK) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], Australia, and Western Europe [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], including validation in both clinical and community samples [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In addition, the ARI has been translated, and psychometrically evaluated in a growing number of non-Western contexts, including Brazil, Spain, China, Japan, and Turkey [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. To date, the ARI has been translated into at least 20 languages, with all versions freely available through an open-access repository. However, despite this expanding international use, prior research has not systematically examined whether the ARI measures irritability equivalently across countries and languages, which is a prerequisite for valid cross-national comparisons.\u003c/p\u003e \u003cp\u003eThis gap is particularly important given recent evidence from UK samples that levels, correlates, and even interpretation of irritability vary by age and sex [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Developmental expectations and sex norms differ across countries and cultures [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and may influence how irritability is expressed, perceived, and reported [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Without establishing that irritability is measured equivalently across countries and languages, it is unclear whether observed differences in age or sex associations reflect true developmental or sex variation or differences in measurement.\u003c/p\u003e \u003cp\u003eAccordingly, the primary objective of the present study was to determine whether the parent- and youth-report versions of the Affective Reactivity Index function equivalently across countries and language versions. In practical terms, this means testing whether the ARI measures irritability consistently across groups, such that scores have comparable meaning regardless of the country or language in which the scale is administered. We evaluated this by examining multiple levels of measurement invariance across five countries, Brazil, China, Japan, Spain, and the US, spanning South America, Asia, Europe, and North America. Establishing measurement invariance is a prerequisite for meaningful cross-country comparisons, as it allows researchers to distinguish true differences in irritability from those arising from how items are interpreted or endorsed. Nevertheless, demonstrating measurement invariance alone does not establish that cross-country comparisons are substantively meaningful. Rather, it provides the foundation for interpreting such comparisons. Therefore, contingent on evidence of measurement invariance, a secondary aim of this study was to examine whether associations between irritability and age and sex vary across countries. This step allows us to evaluate whether known developmental correlates of irritability operate similarly across contexts once measurement equivalence is established. By pairing tests of measurement invariance with follow-up analyses of age and sex associations, the present study seeks to move beyond psychometric adequacy alone and toward a more informative understanding of how irritability manifests and relates to development across countries.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSample and procedure\u003c/h2\u003e \u003cp\u003eThe present study used child and adolescent samples (Mean age\u0026thinsp;=\u0026thinsp;12.4, SD\u0026thinsp;=\u0026thinsp;3.1, range 6\u0026ndash;18 years; 50% female) from five countries. Sample sizes ranged from 133 (Brazil) to 4800 (Japan) participants, with an aggregated sample size of 6195 participants. China, Japan, and the United States included parent-reported irritability data; Brazil, China, Spain, and the United States included youth-reported irritability data. Data collection was approved by Ethics Committees from institutions of each country. A detailed description of the sample and procedure for each country is provided in the supplemental.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cp\u003eThe ARI [ARI; 30] has two versions, a parent-reported and a self- reported version. Parents receive the following instruction: \"In the last 6 months and compared to others of the same age, how well does each of the following statements describe the behavior/feelings of your child? Please try to answer all questions.\" The self-report version mirrors this instruction but pertains to \"your behavior/feelings.\" After the introductory statement, respondents encounter six items related to feelings/behaviors specific to irritability. These include being \"Easily annoyed by others\", \"Often loses temper\", \"Stays angry for a long time\", \"Angry most of the time\", \"Gets angry frequently\", and \"Loses temper easily\". Additionally, a seventh item evaluates impairment due to irritability: \"Overall, irritability causes him/her (or 'me' in the self-report) problems.\" Importantly, the parent- and self-report scales consist of identical items. Each item is scored on a 3-point Likert scale: 'not true' (scored as '0'), 'somewhat true' (scored as '1'), and 'certainly true' (scored as '2'). The total score is calculated as the sum of the first six items, with the impairment item not contributing to the total score. Consequently, the possible score range for each respondent spans from 0 to 12. This composite score provides a quantitative representation of affective reactivity, specifically focusing on irritability-related behaviors and feelings as reported by either the parent or the individual themselves.\u003c/p\u003e\n\u003ch3\u003eStatistical Analyses\u003c/h3\u003e\n\u003cp\u003eAll analyses were preregistered on the Open Science Framework (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://osf.io/d2zfp/overview\u003c/span\u003e\u003cspan address=\"https://osf.io/d2zfp/overview\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Any deviations from the preregistered plan are documented in \u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e. Analyses were conducted separately by informant. Parent-reported irritability data were available from China, Japan, and the United States, whereas youth-reported irritability data were available from Brazil, China, Spain, and the United States. Because both informants were available only in China and the United States, formal analyses of informant effects were not conducted.\u003c/p\u003e \u003cp\u003eFirst, descriptive statistics were calculated for each sample and country, including item-level distributions for irritability measured by the Affective Reactivity Index (ARI), reported separately for parents and young people. Ordinal logistic regression models were used to compare item responses across countries, with post-hoc Bonferroni-corrected comparisons.\u003c/p\u003e \u003cp\u003eNext, we evaluated the factor structure of the ARI within each country and informant using confirmatory factor analysis (CFA) for ordered categorical indicators. Internal consistency was assessed using McDonald\u0026rsquo;s omega, estimated separately for parents and young people within each country.\u003c/p\u003e \u003cp\u003eMeasurement invariance of the ARI across countries was then tested using a multiple-group CFA framework for categorical indicators. We evaluated increasingly restrictive models including configural invariance, threshold and loading invariance, and threshold, loading, and intercept invariance. Establishing intercept invariance allows meaningful comparison of latent means across countries.\u003c/p\u003e \u003cp\u003eFinally, we examined between-country variability and the effects of sex and age on irritability severity using linear regression models with ARI total scores as the outcome.\u003c/p\u003e \u003cp\u003eConfirmatory factor analyses and measurement invariance tests were conducted in Mplus version 8.8 [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. All remaining analyses were conducted in R [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Additional details regarding estimation procedures, model fit indices, and invariance testing criteria are provided in the Supplementary Methods.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eDescriptive statistics\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e provides the sample characteristics. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows a plot with the relative frequencies of the categories for each ARI item by country and informant. The exact relative frequencies of endorsement of the response options for each ARI item, as well as item corrected comparison across countries, separately for youth and parent reports are reported in \u003cb\u003eSupplementary Table\u0026nbsp;2\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of the Samples\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eN for youth report\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eJapan\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSpain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e395\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e384\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e467\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN for parent report\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e475\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72 (54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e194 (48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2400 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e202 (53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e224 (47)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, M (SD) range\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (1.6)\u003c/p\u003e \u003cp\u003e8\u0026ndash;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.4 (2.5)\u003c/p\u003e \u003cp\u003e9\u0026ndash;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.4 (3.5)\u003c/p\u003e \u003cp\u003e6\u0026ndash;18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.7 (0.5) 11\u0026ndash;14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear(s) of data collection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2018-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2014/2016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAcross the three countries, parents in China consistently reported higher irritability scores than those in Japan and the US. For Item 1 (\u0026ldquo;Annoyed\u0026rdquo;), Chinese parents rated their children higher than both Japanese and US parents (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). A similar pattern emerged for \u0026ldquo;Often loses temper\u0026rdquo;, with scores highest in China, followed by Japan, and lowest in the US (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). For Items 3\u0026ndash;5 (\u0026ldquo;Stays angry\u0026rdquo;; \u0026ldquo;Angry most of the time\u0026rdquo;; \u0026ldquo;Angry frequent\u0026rdquo;), both China and Japan scored higher than the US (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Item 6 (\u0026ldquo;Loses temper easily\u0026rdquo;) again showed higher scores in China compared with Japan and the US (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Finally, for the impairment item (Item 7), Chinese parents reported more irritability‑related problems than both US (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and Japanese parents (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and Japanese parents also reported more impairment than US parents (p\u0026thinsp;=\u0026thinsp;0.013). Overall, parent‑reported irritability was consistently highest in China, intermediate in Japan, and lowest in the US.\u003c/p\u003e \u003cp\u003eYouth‑reported irritability showed a different cross‑national pattern, with Brazilian youth consistently endorsing the highest levels across items. For Item 1 (\u0026ldquo;Annoyed\u0026rdquo;), Brazil, China, and the US all scored higher than Spain (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). For \u0026ldquo;Often loses temper\u0026rdquo;, Brazil scored higher than China, Spain, and the US (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while China scored higher than the US (p\u0026thinsp;=\u0026thinsp;0.011) and Spain scored higher than the US (p\u0026thinsp;=\u0026thinsp;0.017). Item 3 (\u0026ldquo;Stays angry\u0026rdquo;) showed the clearest gradient, with Brazil scoring higher than Spain, which in turn scored higher than China and the US (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). For Item 4 (\u0026ldquo;Angry most of the time\u0026rdquo;), Brazil again exceeded China, Spain, and the US (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Item 5 (\u0026ldquo;Angry frequent\u0026rdquo;) showed Brazil scoring higher than China, the US, and Spain (all p\u0026thinsp;\u0026le;\u0026thinsp;0.001), and Spain scoring higher than the US (p\u0026thinsp;=\u0026thinsp;0.008). For Item 6 (\u0026ldquo;Loses temper easily\u0026rdquo;), Brazil scored higher than China, Spain, and the US (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with China and Spain also scoring higher than the US (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and p\u0026thinsp;=\u0026thinsp;0.048, respectively). Finally, for the impairment item (Item 7), both Brazil and China reported more irritability‑related problems than Spain and the US (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Overall, youth reports indicated the highest irritability in Brazil, followed by China, with Spain and the US generally showing lower levels.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSingle Factor CFA\u003c/h2\u003e \u003cp\u003eItem loadings are depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e by country and informant and provided in full in \u003cb\u003eSupplementary Table\u0026nbsp;3\u003c/b\u003e. \u0026ldquo;Often loses temper\u0026rdquo; was, consistently across countries and informants, one of the items with the strongest loadings (0.81 to 0.98), except for parent report in Japan, where \u0026ldquo;Loses temper easily\u0026rdquo; had the strongest loading (0.95). On the other hand, \u0026ldquo;Stays angry for a long time\u0026rdquo; was consistently the item with the weakest loading (0.49 to 0.86), with the exceptions of parent report in the US and youth report in Brazil, where \u0026ldquo;Easily annoyed by others\u0026rdquo; had a weaker loading (0.79 and 0.69, respectively).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eResults of goodness of fit of single-factor CFA for each country and by informant are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. McDonald\u0026acute;s Omega reliability coefficients were good for parent report in all countries (Japan: 0.81; China: 0.89; US: 0.87), and for youth report in most countries (China: 0.82; US: 0.81; Brazil: 0.84) except Spain (0.73), for which the coefficient showed a lower, but acceptable reliability.\u003c/p\u003e \u003cp\u003eFor parent report across countries, CFI and TLI demonstrated good fit (\u0026gt;\u0026thinsp;0.950) for Japan, China, and the US. However, whereas RMSEA was acceptable for China (0.074) and good for the US (0.040), it was poor for Japan (0.097). For youth report, CFI and TLI demonstrated good fit (\u0026gt;\u0026thinsp;0.950) for China, US, and Brazil. However, whereas RMSEA was good for China (0.056) and Brazil (\u0026lt;\u0026thinsp;0.001), it was poor for the US (0.101). In the case of youth report in Spain, all fit indices demonstrated a poor fit. Modification indices for US and Spain suggested that model fit would improve considerably if items \u0026ldquo;Often loses temper\u0026rdquo; and \u0026ldquo;Loses temper easily\u0026rdquo; were allowed to correlate. Effectively, this modification led to a better fit for US (CFI\u0026thinsp;=\u0026thinsp;0.991, TLI\u0026thinsp;=\u0026thinsp;0.983, RMSEA\u0026thinsp;=\u0026thinsp;0.065) and Spain (CFI\u0026thinsp;=\u0026thinsp;0.993, TLI\u0026thinsp;=\u0026thinsp;0.988, RMSEA\u0026thinsp;=\u0026thinsp;0.043). This modified model was used as a configural model to test measurement invariance for child report.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e Fit Indices of Confirmatory Factor Analysis (CFA) for One-Factor Solution of ARI Items for Parent and Youth Report\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParent report\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJapan\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBrazil\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSpain\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCFI\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTLI\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRMSEA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMcDonald's ω\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYouth report\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eJapan\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eChina\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eUS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eBrazil\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eSpain\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCFI\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.995\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.913\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTLI\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.958\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.855\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRMSEA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMcDonald's ω\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMeasurement Invariance\u003c/h3\u003e\n\u003cp\u003eResults of measurement invariance assessment are displayed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. For parent report, none of the parents from the US endorsed a score of 2 in item 4, which did not allow us to include the US when testing MI with the ARI using the original 3-level structure of the items. Therefore, for parent report, we assessed MI for 3-level items for China and Japan only, and then for 2-level items (by combining scores 1 and 2) for China, Japan and the US.\u003c/p\u003e \u003cp\u003eFor parent report, invariance across countries was established at all levels; across China and Japan with the 3-level items, and across China, Japan, and the US with the dichotomized items. Although values of chi-square differences in the comparison of models suggested otherwise, possibly driven by the large sample from Japan, differences in CFI and RMSEA were within the limits to achieve invariance.\u003c/p\u003e \u003cp\u003eFor youth report, threshold and loading invariance was established across Brazil, China, Spain, and the US. However, after fixing intercepts, invariance was not achieved, according to differences in chi-square, CFI, and RMSEA. Modification indices suggested that freeing the intercept means of item 1 (\u0026ldquo;Annoyed by others\u0026rdquo;) produced the most improvement in fit (CFI\u0026thinsp;=\u0026thinsp;0.982, TLI\u0026thinsp;=\u0026thinsp;0.982, RMSEA\u0026thinsp;=\u0026thinsp;0.068); nevertheless, although differences in RMSEA were acceptable, differences in CFI in reference to the configural model were still over the threshold.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFit indices of measurement invariance of single-factor model of ARI\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003eParent-report (3-level items) across China (n\u0026thinsp;=\u0026thinsp;403), and Japan (referent group, n\u0026thinsp;=\u0026thinsp;4,800)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel (M)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e(df)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCFI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTLI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRMSEA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSRMR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eComp.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eΔCFI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eΔRMSEA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eΔSRMR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eΔ χ\u003csup\u003e2\u003c/sup\u003e(df), \u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM1: Configural (all free)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e421.6 (18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM2: Threshold invariance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e421.6 (18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM3: Threshold and loading invariance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e366.1 (23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eM1/M2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e10.9 (5), \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.053\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM4: Threshold, loading, and intercept invariance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e481.8 (28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eM1/M2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e129.9 (10), \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eM3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e126.2 (5), \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eParent-report (2-level items) across China (n\u0026thinsp;=\u0026thinsp;403), Japan (n\u0026thinsp;=\u0026thinsp;4,800), and US (referent group, n\u0026thinsp;=\u0026thinsp;475)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel (M)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e(df)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eCFI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eTLI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eRMSEA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eSRMR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eComp.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eΔCFI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eΔRMSEA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eΔSRMR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003eΔ χ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e(df)\u003c/b\u003e, \u003cb\u003ep\u003c/b\u003e\u003cb\u003e-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM1: Configural (all free)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e235.8 (27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM2: Threshold invariance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e235.8 (27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM3: Threshold and loading invariance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e217.9 (37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eM1/M2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e38.4 (10), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM4: Threshold, loading, and intercept invariance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e417.7 (47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eM1/M2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e202.3 (20), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eM3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e271.2 (10), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYouth-report (3-level items) across Brazil (n\u0026thinsp;=\u0026thinsp;133), China (n\u0026thinsp;=\u0026thinsp;395), Spain (n\u0026thinsp;=\u0026thinsp;384), and US (referent group, n\u0026thinsp;=\u0026thinsp;467)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel (M)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e(df)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eCFI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eTLI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eRMSEA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eSRMR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eComp.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eΔCFI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eΔRMSEA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eΔSRMR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003eΔ χ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e(df)\u003c/b\u003e, \u003cb\u003ep\u003c/b\u003e\u003cb\u003e-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM1: Configural (all free)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64.3 (32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM2: Threshold invariance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64.3 (32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM3: Threshold and loading invariance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88.7 (47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eM1/M2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e27.0 (15), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM4: Threshold, loading, and intercept invariance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e288.1 (62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.958\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eM1/M2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e204.9 (30), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eM3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e179.4 (15), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM5: M4\u0026thinsp;+\u0026thinsp;free intercept of item 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e154.0 (59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eM1/M2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e87.4 (27), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eVariation of irritability by Country, Sex and Age\u003c/h3\u003e\n\u003cp\u003eFor parent report, irritability total scores were significantly higher in Japan (M\u0026thinsp;=\u0026thinsp;1.77, SD\u0026thinsp;=\u0026thinsp;2.63; b\u0026thinsp;=\u0026thinsp;0.62, SE\u0026thinsp;=\u0026thinsp;0.12, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and China (M\u0026thinsp;=\u0026thinsp;2.49, SD\u0026thinsp;=\u0026thinsp;2.31; b\u0026thinsp;=\u0026thinsp;1.34, SE\u0026thinsp;=\u0026thinsp;0.17, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to US (M\u0026thinsp;=\u0026thinsp;1.15, SD\u0026thinsp;=\u0026thinsp;1.95), and higher in China than Japan (b\u0026thinsp;=\u0026thinsp;0.72, SE\u0026thinsp;=\u0026thinsp;0.13, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Across countries, parents scored higher levels of irritability in males (b=-0.17, SE\u0026thinsp;=\u0026thinsp;0.07, p\u0026thinsp;=\u0026thinsp;0.012) and at younger ages (b=-0.03, SE\u0026thinsp;=\u0026thinsp;0.01, p\u0026thinsp;=\u0026thinsp;0.007) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFor youth report, irritability total scores were significantly higher in Brazil (M\u0026thinsp;=\u0026thinsp;3.96, SD\u0026thinsp;=\u0026thinsp;3.36) compared to US (M\u0026thinsp;=\u0026thinsp;1.79, SD\u0026thinsp;=\u0026thinsp;2.11; b\u0026thinsp;=\u0026thinsp;2.18, SE\u0026thinsp;=\u0026thinsp;0.22, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), Spain (M\u0026thinsp;=\u0026thinsp;1.94, SD\u0026thinsp;=\u0026thinsp;1.94; b\u0026thinsp;=\u0026thinsp;2.03, SE\u0026thinsp;=\u0026thinsp;0.23, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and China (M\u0026thinsp;=\u0026thinsp;2.06, SD\u0026thinsp;=\u0026thinsp;2.21; b\u0026thinsp;=\u0026thinsp;1.91, SE\u0026thinsp;=\u0026thinsp;0.23, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). However, no effects on irritability were evident for sex (b\u0026thinsp;=\u0026thinsp;0.06, SE\u0026thinsp;=\u0026thinsp;0.12, p\u0026thinsp;=\u0026thinsp;0.625) or age (b=-0.04, SE\u0026thinsp;=\u0026thinsp;0.04, p\u0026thinsp;=\u0026thinsp;0.327) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eModel Estimates for Effects of Sex and Age on ARI Total Score Across Countries for Parent and Youth Report\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eParent report\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eModel results for child sex\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTerm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEstimate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJapan (vs US)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChina (vs US)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel results for child age\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTerm\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eEstimate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eSE\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003et\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJapan (vs US)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChina (vs US)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChild report\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel results for child sex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTerm\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eEstimate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eSE\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003et\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrazil (vs US)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpain (vs US)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.325\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChina (vs US)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.081\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.625\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel results for child age\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTerm\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eEstimate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eSE\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003et\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrazil (vs US)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpain (vs US)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.430\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChina (vs US)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.327\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study systematically examined the measurement properties of the ARI across multiple countries and informants. Using community samples from Brazil, China, Japan, Spain, and the US, we evaluated reliability, factor structure, and measurement invariance, and then examined cross-country differences in irritability levels, associated impairment, and age and sex correlates. Overall, findings provide encouraging support for the ARI across diverse cultural contexts, while highlighting important caveats, particularly for youth self-report and interpretation of mean differences.\u003c/p\u003e \u003cp\u003eAcross countries and informants, the ARI showed good internal consistency and a largely robust single-factor structure. McDonald\u0026rsquo;s omega values were acceptable to good in all samples, with slightly lower reliability for Spanish youth. Items indexing frequent and explosive anger (e.g., \u0026ldquo;Often loses temper,\u0026rdquo; \u0026ldquo;Loses temper easily\u0026rdquo;) showed the strongest loadings across settings, whereas \u0026ldquo;Stays angry for a long time\u0026rdquo; loaded more weakly. The rank ordering of standardized loadings was largely preserved across countries, strengthening confidence that a common irritability dimension was being captured despite differences in language and context. This pattern aligns with conceptualizations emphasizing high-arousal, rapidly escalating anger as central to pediatric irritability [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], whereas more chronic anger may overlap with other affective constructs.\u003c/p\u003e \u003cp\u003eIn Spanish youth, a residual correlation between the two temper-loss items suggests additional covariance beyond the latent factor. This may reflect shared behavioral expression (youth who lose temper easily often do so frequently), contextual triggers, or potential sample enrichment for oppositional behavior given the two-phase design. Regardless of mechanism, this finding underscores the importance of item-level evaluation in cross-cultural psychometric work.\u003c/p\u003e \u003cp\u003eMeasurement invariance analyses indicated that the ARI could support meaningful cross-country comparisons under certain conditions. For parent report, invariance was achieved across China and Japan using the original 3-level structure, and across China, Japan, and the US when items had to be treated as binary indicators due to lack of endorsement of the highest response category in item 4 in the US sample. Although dichotomization reduces variability, these results suggest that parent-reported ARI scores reflect a comparable latent irritability construct across these contexts. Sparse endorsement of the highest category in community samples also highlights a practical consideration: the 3-level format may be less sensitive to upper-range variation in lower-risk populations, whereas it may be more informative in clinical or high-risk samples.\u003c/p\u003e \u003cp\u003eFor youth self-report, threshold and loading invariance were supported across countries, but intercept invariance was not. Elevated intercepts in Brazil indicate that, for a given level of latent irritability, Brazilian youth were more likely to endorse higher response categories. Thus, cross-country differences in youth-reported mean levels may partly reflect differences in endorsement thresholds rather than latent severity.\u003c/p\u003e \u003cp\u003eWithin this psychometrically constrained framework, we observed clear cross-country differences in irritability and associated impairment. At the item level, parents in China consistently endorsed higher irritability across ARI items, followed by Japan, with the US showing the lowest endorsement rates. In contrast, Brazilian youth reported the highest irritability across most items, with Spain and the US generally showing lower endorsement. Total ARI score comparisons, conducted after establishing measurement invariance, showed a parallel pattern, with higher parent-reported irritability in China and Japan relative to the US, and higher youth-reported irritability in Brazil relative to the other countries. The impairment item followed similar cross-country patterns, with China and Japan scoring higher than US for parent report and Brazil and China scoring higher than Spain and US for youth report, indicating that perceptions of irritability-related problems varied across settings. However, because impairment was examined at the item level rather than modeled as an outcome adjusted for total severity, these findings reflect co-occurring differences in symptom endorsement and perceived problems rather than impairment independent of symptom level.\u003c/p\u003e \u003cp\u003eThese patterns may reflect both contextual and cultural influences. Contextual stressors, such as economic inequality, neighborhood violence, or academic pressure, may amplify the functional consequences of irritability in certain environments. Cultural models of the self further suggest that collectivistic contexts emphasizing interdependence and social harmony may discourage socially disengaging emotions such as anger more strongly than individualistic contexts [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In such settings, even moderate anger may be more norm-violating and therefore more likely to be labeled as problematic. Prior cross-national research using measures such as the Child Behavior Checklist and the Strengths and Difficulties Questionnaire similarly shows that symptom endorsement and perceived impairment do not map neatly onto disorder prevalence [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Our findings extend this literature by demonstrating that even when a unidimensional irritability factor is supported, item-level endorsement patterns and perceived impairment can vary across settings, underscoring the importance of distinguishing latent severity from culturally shaped endorsement thresholds.\u003c/p\u003e \u003cp\u003eRegarding developmental correlates, parent report indicated higher irritability in boys and younger children, consistent with prior research on externalizing manifestations of irritability [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In contrast, youth self-report showed no significant associations with age or sex. These discrepancies suggest that developmental patterns may be informant-dependent and shaped by culturally specific expectations regarding anger expression, highlighting the importance of multi-informant assessment[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTaken together, the findings provide substantial support for the ARI as a cross-culturally applicable measure of irritability, particularly for parent report. Youth-report mean differences should be interpreted with care given the lack of full intercept invariance. In cross-national designs, parent report may be preferable for mean comparisons, whereas youth report may be better suited for within-country analyses and association testing. The observation that impairment endorsement varied across countries alongside differences in symptom severity further supports calls for culture-sensitive thresholds for clinically significant irritability [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral limitations should be considered when interpreting these findings. First, the country samples differed in recruitment strategy, setting, and likely enrichment for behavior problems (e.g., school-based convenience samples, online panels, and multistage or enriched recruitment designs). Because sampling influences both the distribution of irritability and thresholds for labeling behaviors as impairing, observed differences between countries may partly reflect sampling variation rather than cultural context per se. Accordingly, mean differences should be interpreted as differences between these specific samples rather than definitive population-level cross-national differences. At the same time, despite these differences in recruitment approaches, the ARI demonstrated broadly similar reliability and factor-loading patterns across settings. This convergence suggests that the core irritability construct captured by the ARI is relatively robust to heterogeneity in sampling, even if mean levels and endorsement thresholds vary across samples. Second, the samples were not nationally representative of their countries of origin and were drawn from different time periods, which may further limit generalizability. Third, some countries contributed data from only one informant, limiting the ability to fully test multi-informant measurement invariance across all sites. Fourth, for the U.S. parent-report data, lack of endorsement of the highest response category for one item required dichotomization. Although this approach is psychometrically defensible, it reduces variability and may obscure finer-grained distinctions in irritability at lower levels. More broadly, this pattern highlights a limitation of the ARI: although the measure was originally developed for clinical and high-risk populations, it may be less sensitive to variation at the lower end of the irritability distribution in community samples. Finally, because the present study focused exclusively on community samples, future research should examine whether similar measurement properties hold in clinical populations, where the distribution, severity, and meaning of irritability may differ and where the ARI may demonstrate greater sensitivity to higher levels of symptom expression.\u003c/p\u003e \u003cp\u003eDespite these limitations, this study provides one of the most comprehensive examinations to date of the cross-cultural measurement properties of a widely used irritability scale. By integrating item-level psychometrics, multi-group CFA, and analyses of developmental correlates and impairment, we provide a foundation for more rigorous cross-cultural research on pediatric irritability. The ARI appears to capture a broadly similar latent construct across diverse cultural and linguistic contexts, particularly for parent report, while also revealing meaningful variation in endorsement thresholds and perceived impairment. As international collaborations in irritability research expand, including coordinated efforts such as the Cross-Cultural Consortium on Irritability [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], careful attention to measurement invariance and cultural interpretation will be essential to ensure that observed differences reflect true variation rather than artifacts of sampling or response style.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJ.S., A.S., and P.V.-R.B. conceived and designed the study, coordinated data pooling, conducted the analyses, and contributed to drafting and revising the manuscript. J.S. wrote the initial draft of the manuscript. D.D., L.E., D.N.K., E.L., S.L., E.M., G.A.S., F.T., and W.-L.T. contributed data and critically revised the manuscript for important intellectual content. All authors reviewed and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets analyzed in the current study are not publicly available because they originate from multiple independent studies across countries and are subject to local ethical and institutional restrictions. Data may be available from the corresponding author upon reasonable request and with permission from the relevant data custodians and ethics committees.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBekiropoulou A, Eyre O, Heron J, Thapar A, Riglin L (2025) Measuring irritability across childhood, adolescence, and young adulthood: an investigation of measurement invariance by age, sex, and informant. European child \u0026amp; adolescent psychiatry:1\u0026ndash;12\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrotman MA, Kircanski K, Stringaris A, Pine DS, Leibenluft E (2017) Irritability in youths: A translational model. Am J Psychiatry 174:520\u0026ndash;532\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrown TA (2015) Confirmatory factor analysis for applied research. Guilford\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChaplin TM (2015) Gender and emotion expression: A developmental contextual perspective. Emot Rev 7:14\u0026ndash;21\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen FF (2007) Sensitivity of goodness of fit indexes to lack of measurement invariance. Struct equation modeling: multidisciplinary J 14:464\u0026ndash;504\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCheung GW, Rensvold RB (2002) Evaluating goodness-of-fit indexes for testing measurement invariance. Struct Equ Model 9:233\u0026ndash;255\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChin M, Robson DA, Woodbridge H, Hawes DJ (2025) Irritability as a transdiagnostic construct across childhood and adolescence: a systematic review and meta-analysis. Clin Child Fam Psychol Rev 28:101\u0026ndash;124\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavis E, Greenberger E, Charles S, Chen C, Zhao L, Dong Q (2012) Emotion experience and regulation in China and the United States: how do culture and gender shape emotion responding? Int J Psychol 47:230\u0026ndash;239\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDeSousa DA, Stringaris A, Leibenluft E, Koller SH, Manfro GG, Salum GA (2013) Adapta\u0026ccedil;\u0026atilde;o transcultural e propriedades psicom\u0026eacute;tricas preliminares do Affective Reactivity Index em jovens brasileiros: implica\u0026ccedil;\u0026otilde;es para a irritabilidade medida pelo DSM-5. Trends Psychiatry Psychother 35:171\u0026ndash;180\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDeSousa DA, Stringaris A, Leibenluft E, Koller SH, Manfro GG, Salum GA (2013) Cross-cultural adaptation and preliminary psychometric properties of the Affective Reactivity Index in Brazilian Youth: implications for DSM-5 measured irritability. Trends Psychiatry Psychother 35:171\u0026ndash;180\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEvans SC, Abel MR, Doyle RL, Skov H, Harmon SL (2021) Measurement and correlates of irritability in clinically referred youth: Further examination of the Affective Reactivity Index. J Affect Disord 283:420\u0026ndash;429\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEvans SC, Corteselli KA, Edelman A, Scott H, Weisz JR (2023) Is irritability a top problem in youth mental health care? A multi-informant, multi-method investigation. 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Int J Environ Res Public Health 20:4607\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaller SP, Kircanski K, Stringaris A, Clayton M, Bui H, Agorsor C, Cardenas SI, Towbin KE, Pine DS, Leibenluft E (2020) The Clinician Affective Reactivity Index: validity and reliability of a clinician-rated assessment of irritability. Behav Ther 51:283\u0026ndash;293\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLt H, Bentler PM (1999) Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct equation modeling: multidisciplinary J 6:1\u0026ndash;55\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKalvin CB, Gladstone TR, Jordan R, Rowley S, Marsh CL, Ibrahim K, Sukhodolsky DG (2021) Assessing irritability in children with autism spectrum disorder using the affective reactivity index. J Autism Dev Disord 51:1496\u0026ndash;1507\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKitayama S, Mesquita B, Karasawa M (2006) Cultural affordances and emotional experience: socially engaging and disengaging emotions in Japan and the United States. J Personal Soc Psychol 91:890\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlein DN, Finsaas MC (2017) The Stony Brook Temperament Study: Early antecedents and pathways to emotional disorders. Child Dev Perspect 11:257\u0026ndash;263\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeibenluft E, Allen LE, Althoff RR, Brotman MA, Burke JD, Carlson GA, Dickstein DP, Dougherty LR, Evans SC, Kircanski K (2024) Irritability in youths: A critical integrative review. Am J Psychiatry 181:275\u0026ndash;290\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi C-H (2016) Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares. Behav Res Methods 48:936\u0026ndash;949\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLu B, Fang Y, Cai J, Chen Z (2024) Psychometric Evaluation of the Affective Reactivity Index Among Children and Adolescents in China: A Multi-Method Assessment Approach. Assessment 31:1020\u0026ndash;1037\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarkus HR, Kitayama S (2014) Culture and the self: Implications for cognition, emotion, and motivation. College student development and academic life. Routledge, pp 264\u0026ndash;293\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMulraney MA, Melvin GA, Tonge BJ (2014) Psychometric properties of the affective reactivity index in Australian adults and adolescents. Psychol Assess 26:148\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMuth\u0026eacute;n LK, Muth\u0026eacute;n B (2017) Mplus user's guide: Statistical analysis with latent variables, user's guide. Muth\u0026eacute;n \u0026amp; Muth\u0026eacute;n\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOsada M, Mori H, Takahashi M, Shinkawa H, Adachi M, Adachi M, Saito T, Nakamura K (2025) Psychometric properties and cross-cultural adaptation of the Japanese version of the Affective Reactivity Index: A community‐based study of adolescent irritability. Psychiatry Clin Neurosciences Rep 4:e70169\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoessner V, Becker A, Rothenberger A, Rohde LA, Banaschewski T (2007) A cross-cultural comparison between samples of Brazilian and German children with ADHD/HD using the Child Behavior Checklist. Eur Arch Psychiatry Clin NeuroSci 257:352\u0026ndash;359\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSilver J, Leibenluft E, Tseng WL, Klein DN, Vidal-Ribas P, Naim R, Patalay P, McElroy E, Stringaris A (2025) A large multinational study of irritability in adolescents. Child Adolesc Mental Health 30:352\u0026ndash;363\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStringaris A, Goodman R, Ferdinando S, Razdan V, Muhrer E, Leibenluft E, Brotman MA (2012) The Affective Reactivity Index: a concise irritability scale for clinical and research settings. J Child Psychol Psychiatry 53:1109\u0026ndash;1117\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStringaris A, Vidal-Ribas P, Brotman MA, Leibenluft E (2018) Practitioner review: definition, recognition, and treatment challenges of irritability in young people. J Child Psychol Psychiatry 59:721\u0026ndash;739\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSvetina D, Rutkowski L, Rutkowski D (2020) Multiple-group invariance with categorical outcomes using updated guidelines: An illustration using M plus and the lavaan/semtools packages. Struct equation modeling: multidisciplinary J 27:111\u0026ndash;130\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTakahashi F, Honda H (2021) Prevalence of clinical-level emotional/behavioral problems in schoolchildren during the coronavirus disease 2019 pandemic in Japan: A prospective cohort study. JCPP Adv 1:e12007\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTeam RC (2020) RA language and environment for statistical computing. R Foundation for Statistical, Computing\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTseng W-L, Bellaert N, Benton TD, Brotman MA, Evans SC, Herrington JD, Jha MK, Lansford JE, Linke JO, Michalska KJ (2025) Cross-Cultural Consortium on Irritability (C3I): An International Network for Research on Cultural Similarities and Differences in Irritability. JAACAP open\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTuran S, Ermiş \u0026Ccedil;, Eray Ş, Yavuz BE, Uzman S, Ozbek MM, Tun\u0026ccedil;t\u0026uuml;rk M, \u0026Ccedil;ıray RO, İnal N (2022) Psychometric properties of The Clinician Affective Reactivity Index for Assessment of Irritability in a clinical sample of Turkish children and adolescents. Scandinavian J Child Adolesc Psychiatry Psychol 10:24\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVidal-Ribas P, Brotman MA, Valdivieso I, Leibenluft E, Stringaris A (2016) The status of irritability in psychiatry: a conceptual and quantitative review. J Am Acad Child Adolesc Psychiatry 55:556\u0026ndash;570\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVidal-Ribas P, Krebs G, Silver J, Tseng W-L, Ford T, Stringaris A (2025) The hidden burden: self-reported irritability in adolescent girls signals higher psychiatric risk. BMC Public Health 25:1832\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu H, Estabrook R (2016) Identification of confirmatory factor analysis models of different levels of invariance for ordered categorical outcomes. Psychometrika 81:1014\u0026ndash;1045\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-child-and-adolescent-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ecap","sideBox":"Learn more about [European Child \u0026 Adolescent Psychiatry](http://link.springer.com/journal/787)","snPcode":"787","submissionUrl":"https://submission.nature.com/new-submission/787/3","title":"European Child \u0026 Adolescent Psychiatry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Irritability, measurement invariance, cultural differences, affective reactivity index, youth","lastPublishedDoi":"10.21203/rs.3.rs-9066353/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9066353/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eIrritability is a globally relevant dimension of youth psychopathology, yet cross-national comparisons require evidence that assessment tools function equivalently across countries and languages. We examined the reliability, factor structure, and measurement invariance of the Affective Reactivity Index (ARI) across Brazil, China, Japan, Spain, and the United States (US).\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e \u003cp\u003eCommunity samples (N\u0026thinsp;=\u0026thinsp;6,195; ages 6\u0026ndash;18 years) completed parent- or youth-report ARI versions. Single-factor confirmatory factor analyses evaluated model fit and internal consistency. Multi-group CFA tested measurement invariance across countries. Where invariance was supported, cross-country differences and age and sex associations were examined.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eInternal consistency was acceptable to good across countries and informants. A single-factor structure was broadly supported. For parent report, measurement invariance was established across China and Japan using the original response format and across China, Japan, and the United States when items had to be dichotomized due to lack of endorsement of the highest category in item 4 by US parents. For youth report, threshold and loading invariance were supported, but scalar invariance was not, indicating cross-country differences in intercepts. Parent-reported irritability was higher in China and Japan than in the United States, whereas youth-reported irritability was highest in Brazil. Parents reported higher irritability in boys and younger youth; youth self-report showed no significant age or sex effects.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe ARI captures a broadly comparable irritability construct across countries, particularly for parent report. Cross-national mean comparisons using youth report should be interpreted cautiously. Establishing measurement invariance is essential for valid international research on pediatric irritability.\u003c/p\u003e","manuscriptTitle":"Measurement Invariance of the Affective Reactivity Index Across Five Countries","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-24 17:05:53","doi":"10.21203/rs.3.rs-9066353/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-02T08:29:46+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-29T00:39:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"261269588796965917590007347358598461269","date":"2026-04-11T22:12:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"254937693851037100510435643707261782901","date":"2026-04-08T21:51:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"217148589466091313473912723841983929724","date":"2026-03-21T20:39:01+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-19T19:19:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-11T04:56:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-11T04:55:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Child \u0026 Adolescent Psychiatry","date":"2026-03-08T19:54:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-child-and-adolescent-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ecap","sideBox":"Learn more about [European Child \u0026 Adolescent Psychiatry](http://link.springer.com/journal/787)","snPcode":"787","submissionUrl":"https://submission.nature.com/new-submission/787/3","title":"European Child \u0026 Adolescent Psychiatry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"22eea967-03ea-4770-987b-798a83178ed9","owner":[],"postedDate":"March 24th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-02T08:29:46+00:00","index":31,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-24T17:05:54+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-24 17:05:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9066353","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9066353","identity":"rs-9066353","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}