Bipolar Spectrum Disorder Risk and Positive Emotion Processes in Emerging Adults from India

Bipolar Spectrum Disorder Risk and Positive Emotion Processes in Emerging Adults from India | 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 Bipolar Spectrum Disorder Risk and Positive Emotion Processes in Emerging Adults from India Luiza Rosa, Tripti Kathuria, Prianca Thirumalai, Shanmukh Kamble, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6074756/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Bipolar spectrum disorders (BSDs) encompass an umbrella of severe affective disorders characterized by prominent positive emotion difficulties. Despite the prominence of emotion challenges among BSDs, little is known about relevant emotion goals and regulation processes among more diverse samples outside the United States. This lack of inclusive research in emotion and BSDs stymies our ability to assess the generalizability of findings and the critical influence of cultural context on emotional processes. Given the prominence of positive emotion experiences and values among Southeast Asian (i.e., Indian) cultural contexts, they represent an ideal entry point to better understand potential sources of cultural-variation on BSD risk and relevant positive emotion processes. The present investigation examined BSD risk dimensions with emotion experience (actual and ideal) and emotion regulatory processes among emerging adults from India. Results suggested some sources of cultural divergence (i.e., for ideal affect and BSD risk) as well as potential cross-cultural generalizability (i.e., for emotion regulation processes) when compared to previous studies among Westernized U.S. young adult samples. This work underscores the importance of expanding emotion and psychopathology research to more diverse and global populations. Psychology Bipolar Disorder Emotion Regulation Affect Valuation Culture India Introduction Bipolar spectrum disorders (BSDs) encompass a serious class of emotional disorders characterized by periods of hypomania/mania (abnormally persistent elevated or expansive mood) and often periods of depression (low and sad mood; American Psychiatric Association, 2022). BSDs are marked by heightened and persistent emotion intensity (e.g., Gruber, 2011; Johnson, 2005), contributing to functional impairments and high rates of global disability (e.g., Fagiolini et al., 2013; Coryell et al., 2003; Dean et al., 2004; Michalak et al., 2007). Despite the severe consequences of BSD, relatively little is known about emotion-related processes in samples outside of WEIRD (i.e., Western, Educated, Industrialized, Rich, and Democratic; e.g., Muthukrishna et al., 2020) contexts. The present investigation is one of the first to examine associations of continuous BSD risk dimensions with emotional experience and regulation in emerging adults from India. Cross-Cultural Approach to BSD Risk and Emotion BSDs are characterized by emotional reactivity and regulation challenges. Concerning emotion reactivity, findings suggest those at risk for or diagnosed with BSDs, self-report greater positive emotion across contexts (Gruber, 2011; Johnson, 2005). Other research employing experience-sampling paradigms suggests elevated positive and negative emotion outside of the laboratory (e.g., Gruber et al., 2013) and greater instability or variability in emotion intensity in everyday life (e.g., Sperry & Kwapil, 2022). With respect to emotion regulation, or the ability and effort to shift or modulate one’s emotion response, BSD has been associated with trouble regulating positive and negative emotions as well as the maladaptive use of regulation strategies in everyday life and the laboratory, including rumination and emotion-relevant impulsivity (Gruber et al., 2012; Gruber et al., 2013). Yet despite the apparent importance of emotional challenges in BSDs, research on mood disorders to date has primarily focused on Westernized and primarily White samples within the United States (e.g., Ryder, Zhao, Chentsova-Dutton, 2017; Gruber, Kogan, Quoidbach & Mauss, 2013), limiting our ability to understand emotion and BSDs in more diverse cultural contexts (e.g., Villanueva et al., 2023). This work underscores the importance of expanding research to consider the critical role of cultural influence from more collectivistic contexts. Examining the role of cultural context on BSDs and emotions is particularly important given the robust literature base documenting the influence of culture on positive emotion processes (e.g., Tsai, 2007; Miyamoto, Uchida, & Ellsworth, 2010). Concerning emotional experience, in more Western and traditionally individualistic contexts, there is a greater emphasis on autonomy and assertiveness, which are guided by one’s inner psychological attributes (Markus & Kitayama, 2010), as well as a higher valuation of high-arousal positive emotions (e.g., excitement, joy, elation). By contrast, in more Eastern and relatively collectivistic contexts, there is a greater emphasis on emotions that promote interpersonal relatedness (Kitayama, Mesquita, & Karasawa, 2006; Matsumoto et al., 2008). The more people want to adjust to others, the more they value low arousal positive emotions (e.g., serenity, calmness, content; Tsai et al., 2006; Tsai, 2007). Cross-cultural research on emotion regulation suggests that some forms of maladaptive emotion regulation, such as rumination, may have less detrimental effects in East Asian cultures (e.g., Japan, China, and Korea), where rumination is more common than in Western or European American cultures. To our knowledge, other strategies, such as emotion-related impulsivity, that have been strongly associated with BSDs, have not yet been studied outside of the United States. An Ideal Entry Point: BSDs and Emotion in India Examining emotions among individuals from India presents an ideal entry point to explore the role of cultural context on BSDs and positive emotions. Specifically, India is the second most populous nation globally and an eminent example of a collectivistic culture that emphasizes group cohesion, where group goals are prioritized over individual needs (e.g., Markus & Kitayama, 1991; Mascolo et al., 2004). Furthermore, traditional Indian cultural ideals warrant both the experience and the expression of certain positive emotions; for example, sukha (happiness), which is believed to be an immature emotion, transitory in nature that may interfere with the larger Hindu life goal moksha (enlightenment) . The goal of well-being (hitta) is emphasized over happiness (Shweder & Haidt, 2000). Although an estimated 7.6 million Indian adults are diagnosed with BSDs and represents a significant public health concern in India (e.g., Pillai et al., 2021; Ramdurg & Kumar, 2013; Dhiman et al., 2022), we are aware of no studies to date examining emotion and BSDs in an Indian sample of emerging adults. The Present Investigation The present investigation was the first to examine associations between self-reported BSD risk with (a) emotion-related experience (i.e., actual and ideal positive emotion experience) as well as (b) maladaptive emotion regulation processes (i.e., rumination and emotion-relevant impulsivity) in a cross-sectional sample of emerging adults from India enrolled in undergraduate courses in Karnataka University. Karnataka is the largest state in Southern India, where English is a widely used language in higher educational institutes. This enabled us to examine two non-mutually exclusive perspectives on the association between BSD risk and emotional experience and goals among Indian emerging adults. One perspective, referred to as “BSD emotion generalizability,” suggests that the links between emotion processes and BSD risk can be generalized across U.S. and Indian young adult samples. According to this perspective, and based on previous work among emerging adults from U.S. we predict that among Indian emerging adults, BSD risk should be associated with greater high-arousal positive actual affect (Hypothesis 1a), high-arousal positive ideal affect (Hypothesis 1b), positive rumination (Hypothesis 1c), and increased positive emotion-relevant impulsivity (Hypothesis 1d). A second perspective, referred to as “BSD emotion specificity,” is grounded in cross-cultural research on emotions that highlights the unique influence of culture on positive emotion experience and well-being, predicting distinct patterns of findings in collectivistic versus more individualistic communities. According to this perspective, we predict that although BSD risk should be associated with greater high-arousal positive actual emotion experience based on clinical symptom presentation of BSD risk (Hypothesis 1a), we should expect divergent associations in an Indian young adult sample whereby BSD risk is associated with greater low-arousal positive ideal affect (Hypothesis 2b), lower positive rumination (Hypothesis 2c), and lower positive emotion-relevant impulsivity (Hypothesis 2d). Methods Participants and Procedure Participants were emerging adults from Karnataka University, Dharwad, India between the ages of 19–29, consistent with emerging adult age range cutoffs among Indian adults (e.g., Mitra & Arnett, 2019 ). Participants were recruited in Spring 2018 by posting flyers on various departments’ notice boards at Karnataka University. Students who were interested in participating contacted the Department of Psychology. The study received Institutional Review Board approval from the KLE Academy of Higher Education & Research, Dharwad, Karnataka. Informed consent was obtained from all individual participants included in the study. Participants with missing data or data entry errors on any of the main study measures that could not be reconciled were excluded. The final sample size for our main analyses was N = 221 (for the actual and ideal affect measures) and N = 219 (for the emotion regulation measures). See Table 1 for participant descriptives. Table 1 Participant Characteristics Study Participants ( N = 221) Ideal & Actual Affect Measures Study Participants ( N = 219) Emotion Regulation Measures Age (Years) 22.02 (1.19) 22.0 (1.21) Sex (% Female) 64.3% 64.8% Socioeconomic Status Rating 4.38 (1.87) 4.40 (1.80) HPS-48 23.29 (5.41) 23.01 (5.39) ASRM 11.17 (3.92) 11.04 (3.95) BDI-SF 4.82 (4.29) 4.72 (4.27) HAP_ideal 3.64 (0.86) -- LAP_ideal 3.53 (0.85) -- HAN_ideal 2.53 (0.94) -- LAN_ideal 2.67 (0.96) -- HAP_actual 3.44 (0.88) -- LAP_actual 3.33 (0.88) -- HAN_actual 2.67 (0.96) -- LAN_actual 2.78 (0.84) -- RRS-Brooding -- 14.00 (3.56) PUM -- 30.51 (8.92) Note : Socioeconomic Ladder rated from 1 (people who are the worst off, those who have the least money, least education, and worst jobs or no job) and 10 (people who are the best off - those who have the most money, the most education, and best jobs). HPS-48: Hypomanic Personality Scale, 48-item full version; ASRM: Altman Self-Rating Mania Scale; BDI-SF: Beck Depression Inventory, Short-Form; RRS-Brooding: Ruminative Response Scale, Brooding subscale; PUM: Positive Urgency Measure. Values reflect mean values with standard deviations in parentheses unless otherwise noted. Measures Measures included survey scales completed by hand assessing mood and symptom risk dimensions, as well as actual and ideal affect, and emotion regulation measures (i.e., rumination and emotion-related impulsivity). Additional measures that are not part of the present study were also collected (see Supplementary Materials ). Risk for BSDs. To measure risk for BSDs, the Hypomanic Personality Scale (HPS; Eckblad & Chapman, 1986 ) was used. The HPS-48 is a validated and well-used measure, which is composed of 48 true-false items about shifts in emotion, behavior, and energy associated with mania (α = 0.67 in the present sample). Sample items include “I am frequently so “hyper” that my friends kiddingly ask me what drug I’m taking.” Current Symptoms. Current mania symptoms were measured using the Altman Self-Rating Mania Scale (ASRM; Altman, Hedeker, Peterson, & Davis, 1997 ), which is a 5-item self-report inventory scored from 0 to 4 and total scores ranging from 0 to 20 (α = 0.58), with higher scores indicating greater mania severity. Sample items include “I do not feel happier or more cheerful than usual” and “I can go all day or night without any sleep and still not feel tired.” The Beck Depression Inventory-Short Form (BDI-SF; Beck & Beck, 1972 ) is a 13-item self-report scale used to measure current symptoms of depression scored from 0 to 3, with total summed scores ranging from 0 to 39 (α = 0.73 in the present study), with higher scores indicating greater depression severity. Sample items include “I do not feel that the future is hopeless and that things cannot improve” and “I feel I am a complete failure as a person .” Actual and Ideal Affect. To measure differences in actual and ideal affect, the Affect Valuation Index (AVI) by Tsai et al. ( 2006 ) was used. Participants were asked how much they would ideally like to feel(for ideal affect) and how much they typically feel (for actual affect) regarding 28 different emotion items, rated on a scale from 1(very slightly or not at all) to 5 (extremely or all of the time). Individual emotion items were then scored into four categories, separately for actual and ideal affect, including High Arousal Positive (HAP; enthusiastic, elated), Low Arousal Positive (LAP; calm, relaxed, peaceful), High Arousal Negative (HAN; fearful, hostile, nervous), and Low Arousal Negative (LAN; dull, sleepy, sluggish). Both actual (HAP α = 0.60; LAP α =0.60; HAN α =0.58; LAN α =0.55) and ideal (HAP α =0.60; LAP α =0.55; HAN α =0.61; LAN α =0.56) affect had moderate internal consistency. Negative Rumination . Negative (or depressive) rumination was measured using the 5-item brooding subscale from the Ruminative Response Scale (RRS-brooding; Treynor et al., 2003 ). Items were rated on a 4-point Likert scale ranging from 1 ( never ) to 4 ( always ). Brooding has been conceptualized as a passive, self-criticizing aspect of repetitive thought, measured with items such as “Why do I have problems other people don’t have?” The RRS-brooding subscale demonstrated acceptable internal consistency in the current study (α = 0.65). Positive Emotion-Relevant Impulsivity. Positive emotion-relevant impulsivity (or positive urgency) was measured using the Positive Urgency Measure (PUM; Cyders et al., 2007 ), which assesses the tendency for a person to engage in harmful or risky behaviors in response to positive mood states. The PUM scale consists of 14 self-reported true-false items, such as “When I am very happy, I can't seem to stop myself from doing things that can have bad consequences . ” The PUM demonstrated good internal consistency in the current study (α = 0.82). Results Study analyses were pre-registered on the Open Science Framework initially for actual and ideal affect measures ( https://osf.io/2gctm ) and, subsequently, for the emotion regulation measures after the analyses for ideal and actual affect had been completed ( https://osf.io/8ycs9 ). Preliminary Analyses We first examined the skewness and kurtosis indices for all primary variables (HPS-48, ASRM, BDI-SF, AVI, PUM, RRS), and none of these departed from normality, so no transformations were applied. Second, we examined whether demographic variables (e.g., age, gender, SES) were associated with our BSD risk variable (HPS-48). HPS-48 was not significantly associated with age ( r (221) = − .059, p = .381) or socioeconomic status (SES; r (221) = − .132, p = .051), and male and female participants did not differ in HPS-48 scores ( F (1,220) = 1.03, p = .311). Hence, we did not control for these demographic variables in our main analyses. Third, we examined whether any of our primary variables had significant outliers, and a total of 4 cases (.002%) were Winsorized accordingly (i.e., assigned the next highest or lowest value at or below 3 SDs) 1 . Main Analyses Ideal and Actual Affect. Our main analyses used a hierarchical linear regression analysis with BD risk (HPS) as the dependent variable. Mood symptom covariates (ASRM, BDI-SF) were entered in Block 1, and the AVI-actual subscales (HAP, LAP, HAN, LAN) were entered together in Block 2. As seen in Table 2 , results suggested that BSD risk was not predicted by any of the AVI-actual subscales. For ideal affect, we entered the AVI-ideal subscales in Block 3 (while controlling for AVI-actual in Block 2), and results suggested that BSD risk was also not predicted by any of the AVI ideal subscales also. Table 2 Regression Analyses using AVI-Actual (Aim 1) and AVI-Ideal (Aim 2) subscales to Predict Bipolar Risk (HPS-48) Scores. HPS-48 AVI-Actual Affect AVI-Ideal Affect Predictor R 2 ∆R 2 β R 2 ∆R 2 β Block 1 .13 .13 .13 .13 ASRM .28** .29** BDI-SF .32** .32** Block 2 .14 .01 .14 .01 AVI-HAP actual − .09 − .11 AVI-LAP actual .02 − .01 AVI-HAN actual .03 .02 AVI-LAN actual − .05 .002 Block 3 .15 .01 AVI-HAP ideal .04 AVI-LAP ideal .02 AVI-HAN ideal .04 AVI-LAN ideal − .11 Note: ASRM = Altman Self-Rating Mania Scale; BDI-SF = Beck Depression Inventory, Short-Form; AVI = Affect Valuation Index; HAP = High Arousal Positive; LAP = Low Arousal Positive; HAN = High Arousal Negative; LAN = Low Arousal Negative; β = Standardized beta coefficients (Beta values are from Model 2 for Aim 1 and Beta values are from Model 3 for Aim 2). * p < .05, ** p < .01. We conducted three sets of post-hoc exploratory, non-pre-registered analyses to better understand links between actual and ideal affect with current symptom severity (See Supplementary Materials for additional details). First, we examined whether BSD risk was associated with any of the AVI-actual and AVI-ideal subscales when symptoms were not controlled for, and no significant associations emerged (see Table S2A ). Second, we examined bivariate correlations between current symptoms (ASRM, BDI-SF) with the AVI-actual and AVI-ideal subscales (see Table S2B ). No significant correlations emerged between current mood symptoms and AVI-ideal affect. However, ASRM scores were associated with increased AVI-HAP actual and increased AVI-LAP actual, and BDI-SF scores were associated with decreased AVI-HAP actual , decreased AVI-LAP actual , increased AVI-HAN actual , and increased AVI-LAN actual . Third, we examined associations between BSD risk and mood symptoms (BDI-SF, ASRM) with discrepancy (or difference) scores between AVI ideal and AVI actual subscales (see Table S2C ). Results suggested BSD risk was positively correlated to LAP actual-ideal and LAN actual-ideal , BDI-SF was positively correlated with LAP actual-ideal , and ASRM was negatively correlated with HAP actual-ideal and LAN actual-ideal . Emotion Regulation Processes. We used a hierarchical linear regression analysis with BSD risk (HPS-48) as the dependent variable. Mood symptom covariates (ASRM, BDI-SF) were entered in Block 1, and the RRS_brooding subscale was entered in Block 2. The second aim also used a similar regression analysis with HPS-48 as the dependent variable, ASRM and BDI-SF entered in Block 1, and the PUM scale entered in Block 2. This analytic plan allowed us to examine whether BSD risk is associated with the RRS_brooding subscale and PUM, respectively. As seen in Table 3 , results suggested that greater BD risk was predicted by increased negative (depressive) rumination and increased positive urgency. 2 Table 3 Regression Analyses using RRS (Aim 1) and PUM (Aim 2) subscales to Predict Bipolar Risk (HPS-48) Scores. HPS-48 Aim 1 (RRS) Aim 2 (PUM) Predictor R 2 ∆R 2 β R 2 ∆R 2 β Block 1 .14 .14 .14 .14 ASRM .29** .28** BDI-SF .30** .27** Block 2 .17 .03 .20 .05 RRS-brooding (or PUM) .16* .24** Note: ASRM = Altman Self-Rating Mania Scale; BDI-SF = Beck Depression Inventory, Short Form; RRS-Brooding; PUM = Positive Urgency Measure; β = Standardized beta coefficients (Beta values are from Model 2 for Aim 1 and 2). * p < .05, ** p < .01. We conducted additional non-preregistered analyses examining potential demographic differences in our primary variables, as shown in Supplementary Materials Table S3 . Results indicated that HPS, PUM, and RRS-brooding were not significantly associated with age, socio-economic status, or gender differences (see Table S3). However, women scored higher than men on the RRS-brooding subscale, consistent with past research. Discussion Bipolar spectrum disorders are common and costly affective disturbances marked by prominent emotion difficulties. Yet current research has largely focused on studying emotions and bipolar disorders in largely Westernized contexts, which stymies our ability to understand a more diverse range of human experiences. This is particularly important given the influence of cultural values on the experience and management of emotions. The present study hence examined associations between BSD risk and mood symptoms with emotion experience and regulation in a sample of emerging adults from India. Notably, India remains a relatively understudied collectivistic society centered mainly on East Asian populations. We sought to understand better the cultural generalizability versus specificity in examining links between BSD risk with emotion experience and regulation among emerging adults from India. No Cross-Cultural Associations between BSD and Emotion Experience and Values in Indian Adult Sample. Our overarching aim was to extend prior work on emotion experience and values related to BSD by expanding to a sample of Indian emerging adults. Contrary to our predictions, risk for developing bipolar disorder was not significantly associated with either actual or ideal positive emotional experiences. This finding partially supports the BSD emotion specificity perspective, which posits that the emotional patterns seen in BSD risk may vary across cultural contexts. Specifically, while Western samples have shown strong associations between BSD risk and heightened actual positive emotion experience (Gruber, 2011 ; Johnson, 2005 ), our results suggest that in India, this association may be less pronounced. This lack of association could reflect cultural differences in how positive emotions are experienced and expressed. For instance, in more collectivistic societies like India, low-arousal positive emotions such as calmness and contentment may be more valued, making high-arousal positive emotions (often associated with BSD symptoms) less relevant to the experience of BSD risk. Indeed, when exploring our post-hoc exploratory analysis, we observed additional patterns that align with the BSD emotion specificity perspective. Specifically, misalignments between ideal and actual low-arousal positive emotions (calm, relaxed) showed relevance to BSD risk. These findings are consistent with those observed in East Asian collectivistic populations (e.g., China, Japan, South Korea) regarding their relationship with depression. Tsai ( 2007 ) found that in a Chinese sample, discrepancies between actual and ideal high-arousal positive emotions were not correlated with depression, but discrepancies in low-arousal positive emotions were. To further understand these results, future research should focus on two key areas: (1) examining how ideal and actual emotions are conceptualized in the Indian cultural context, and (2) ensuring that the psychometric properties of emotion measures are parallel across cultural contexts. These steps will be crucial for clarifying the role of emotional misalignment in BSD risk and ensuring that research on emotional experiences and regulation is culturally sensitive and valid. Additionally, improving the reliability and validity of the measures used to assess emotional experiences and regulation across diverse cultural contexts will help refine our understanding of the cultural nuances that influence BSD risk. Cross-Cultural Replication of BSD Risk and Emotion Regulation. Our overarching aim in this section was to replicate previous findings on emotion regulation in BSD risk, extending them to a cross-cultural sample of Indian emerging adults. Consistent with the BSD emotion generalizability perspective, our study found that increased BSD risk was associated with maladaptive emotion regulation strategies, such as positive emotion-relevant impulsivity and negative rumination. These findings align with previous research in U.S. samples, where similar patterns of emotion regulation were linked to BSD risk (Gruber et al., 2012 ; Cyders et al., 2007 ). This suggests that trait BSD risk may be tied to maladaptive emotion regulation patterns, which are stable markers of BSD risk across individualistic and collectivistic cultural contexts. The findings highlight cross-cultural generalizability, which suggests that maladaptive emotion regulation strategies are not exclusive to Western contexts but may be a universal feature of BSD risk, irrespective of cultural differences in emotional experience and expression. As such, it underscores the importance of considering cultural specificity and generalizability in future research on BSD and emotion regulation. Future work should explore whether these maladaptive emotion regulation strategies are universally associated with BSD or if cultural factors shape how these strategies are expressed and their impact on the disorder. Limitations and Future Directions The present investigation should be interpreted with several key limitations. First, the present study relied solely on self-report measures of emotion-related experience and regulation processes. Future work adopting multi-method approaches employing behavioral and psychophysiological indices of emotion processes is warranted to ensure the robustness of the observed findings. Second, we note that the internal consistency (i.e., alpha) values were low for the actual and ideal affect measures, suggesting potential limitations with the validity of the measurements in this context. Future work employing rigorous psychometric approaches to establish the validity of this measure among Indian adults is warranted. Third, the present study was well-sized but limited to one specific cross-cultural (i.e., India) context. Replications in larger samples, with a specific focus on cross-cultural comparisons between other collectivistic cultures like East Asian (e.g., China) and Latin American (e.g., Mexico) cultures, as well as more Westernized (e.g., United States), would allow a more direct cross-cultural comparison. Furthermore, considering India's diversity in languages, cultures, and regional variations, future work within Indian samples could explore how these diverse cultural norms and social pressures influence emotional experiences and regulation. Finally, as the present investigation used a continuous measure of bipolar risk and symptoms and did not include a specifically clinically recruited or diagnosed population, future work examining more severe at-risk or diagnosed populations is warranted to extend this work into a more severe clinical context. Taken together, the present investigation provides initial proof-of-concept findings underscoring the need to adopt a cross-cultural approach to understanding emotion and psychopathology with bipolar disorders and more generally. Such approaches will help determine the consistency of these associations across different cultural contexts and enhance the generalizability of emotion and mood findings. Declarations Availability of Data and Materials. The de-identified dataset and syntax used in the present investigation is available online: https://github.com/GruberPEPLab/IndiaPaper_Rosaetal. Human Ethics and Consent to Participate Declarations The study received Institutional Review Board approval from the KLE Academy of Higher Education & Research, Dharwad, Karnataka. Informed consent was obtained from all individual participants included in the study. Competing Interests The authors declare that they have no competing interests. Funding No funding was received for conducting this study. Acknowledgments The authors would like to thank Lilla Kovacs for her input, assistance with data analysis design, and feedback on the manuscript draft. We would also like to thank the Positive Emotion and Psychopathology Laboratory for their feedback on previous drafts. References Altman, E. G., Hedeker, D., Peterson, J. L., & Davis, J. M. (1997). The Altman self-rating mania scale. Biological Psychiatry, 42 (10), 948-955. https://doi.org/10.1016/S0006-3223(96)00548-3 American Psychiatric Association. (2022). Diagnostic and statistical manual of mental disorders (5th ed., text rev.). https://doi.org/10.1176/appi.books.9780890425787. Beck, A. T., & Beck, R. W. (1972). Screening depressed patients in family practice: A rapid technique. Postgraduate Medicine, 52 (6), 81-85. https://doi.org/10.1080/00325481.1972.11713319 Coryell, W., Solomon, D., Turvey, C., Keller, M., Leon, A. 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Culture and mixed emotions: co-occurrence of positive and negative emotions in Japan and the United States. Emotion , 10 (3), 404-415. https://doi.org/10.1037/a0018430 Mascolo, M. F., Misra, G., & Rapisardi, C. (2004). Individual and relational conceptions of self-experience in India and the US. In M. F. Mascolo & J. Li (Eds.), Culture and self: Beyond dichotomization (pp. 9–26). New Directions in Child and Adolescent Development Series (W. Damon, Series Ed.). Jossey-Bass. https://doi.org/10.1002/cd.101 Muthukrishna, M., Bell, A. V., Henrich, J., Curtin, C. M., Gedranovich, A., McInerney, J., & Thue, B. (2020). Beyond Western, Educated, Industrial, Rich, and Democratic (WEIRD) psychology: Measuring and mapping scales of cultural and psychological distance. Psychological Science, 31 (6), 678-701. https://doi.org/10.1177/0956797620916782 Pillai, M., Munoli, R.N., Praharaj, S.K., & Bhat, S.M., (2021). Gender differences in clinical characteristics and comorbidities in bipolar disorder: A study from South India. Psychiatric Quarterly, 92 , 693–702. https://doi.org/10.1007/s11126-020-09838-y Ramdurg S, & Kumar S. (2013). Study of socio-demographic profile, phenomenology, course and outcome of bipolar disorder in Indian population. International Journal of Health & Allied Sciences, 2 (4), 260-263. https://doi.org/10.4103/2278-344X.126729 Ryder, A. G., Zhao, Y., & Chentsova-Dutton, Y. E. (2017). Disordered mood in cultural-historical context. In R. J. DeRubeis & D. R. Strunk (Eds.), The Oxford handbook of mood disorders (p. 71). Oxford University Press. Shweder, R. A., & Haidt, J. (2000). The cultural psychology of emotions: Ancient and new. In M. Lewis & J. M. Haviland-Jones (Ed.), Handbook of emotions, (2nd ed., pp.397-414). Guilford. Sperry, S. H., & Kwapil, T. R. (2022). Bipolar spectrum psychopathology is associated with altered emotion dynamics across multiple timescales. Emotion , 22 (4), 627-640. https://doi.org/10.1037/emo0000759 Treynor, W., Gonzalez, R., & Nolen-Hoeksema, S. (2003). Rumination reconsidered: A psychometric analysis. Cognitive Therapy and Research, 27 (3), 247–259. https://doi.org/10.1023/A:1023910315561 Tsai, J. L. (2007). Ideal affect: cultural causes and behavioral consequences. Perspectives on Psychological Science, 2, 242-259. https://doi.org/10.1111/j.1745-6916.2007.00043.x Tsai, J.L., Knutson, B., & Fung, H. H. (2006). Cultural variation in affect valuation. Journal of Personality and Social Psychology, 90 (2) , 288-307. https://doi.org/10.1037/0022-3514.90.2.288 Villanueva, C. M., Swerdlow, B. A., & Gruber, J. (2023). The challenge of emotion regulation in bipolar disorder. In J. J. Gross & B. Q. Ford (Eds.), Handbook of emotion regulation (3rd edition). Guilford Press. Footnotes For the analysis on emotion regulation in a slightly smaller subsample of the same participants ( N = 219), HPS-48 was still not significantly associated with age ( r (219) = .04, p = .55) or SES ( r (219) = − .10, p = .12). Furthermore, for Winsorizing a total of 4 cases (approximately .004%) of the data was Winsorized. We were unable to analyze one of our original pre-registered study aims focusing on positive rumination due to a data entry error that was irreconcilable. Additional Declarations The authors declare no competing interests. Supplementary Files INDIAHypomaniaRiskProjectSupplementary.docx Cite Share Download PDF Status: Posted Version 1 posted 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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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6074756","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":418762671,"identity":"c0edc6be-54b4-49af-ae6b-8096a50f5d28","order_by":0,"name":"Luiza Rosa","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIiWNgGAWjYBACPhAhUfGvnp+BgfEAkM3YABLAp4UNRFicOZAgCVRKgpbKtgMJBgeI1iKR+/DBjTN38oyPHz5w4OMeO9l+BuaDt3nwakk3NpxR8azY7ExawsEZz5KNZzawJVvj15LGJi1xhplx2w0eg8M8B5gTNxzgMZMmqOVvGzPj5hlgLfVALfzfCGqRkGw7nLhBAqzlMMgWNvxaeJ4xG0icSTOWAPvlwHHjmc1sxpZz8GjhZ09jfCBRYSPH33744IMPB6pl+9mbH954g0cLFsBMmvJRMApGwSgYBVgAAE28Tv+s1N0HAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0009-0006-6479-9300","institution":"University of Colorado Boulder, Boulder, Colorado, U.S.A.","correspondingAuthor":true,"prefix":"","firstName":"Luiza","middleName":"","lastName":"Rosa","suffix":""},{"id":418762672,"identity":"fc3b73bc-133d-4b97-952c-89dac0ea6299","order_by":1,"name":"Tripti Kathuria","email":"","orcid":"","institution":"University of Colorado Boulder, Boulder, Colorado, U.S.A.","correspondingAuthor":false,"prefix":"","firstName":"Tripti","middleName":"","lastName":"Kathuria","suffix":""},{"id":418762673,"identity":"73e93acb-a2c4-4ee7-92e0-ce8c8374997d","order_by":2,"name":"Prianca Thirumalai","email":"","orcid":"","institution":"University of Colorado Boulder, Boulder, U.S.A./ University of Stirling, Stirling, Scottland","correspondingAuthor":false,"prefix":"","firstName":"Prianca","middleName":"","lastName":"Thirumalai","suffix":""},{"id":418762674,"identity":"99bd11d5-f839-492e-ae07-39355cd3477a","order_by":3,"name":"Shanmukh Kamble","email":"","orcid":"","institution":"Karnatak University, Dharwad, Karnataka, India","correspondingAuthor":false,"prefix":"","firstName":"Shanmukh","middleName":"","lastName":"Kamble","suffix":""},{"id":418762675,"identity":"9efa1f49-b114-4b27-86b4-d527eac00396","order_by":4,"name":"June Gruber","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIiWNgGAWjYBACxgYowwDIfsDAYAFlMzATpYUZiCUIa4EDoDI2CaK0MM/IPfiA4de9xO3svc8qflRIyJm3H974gKHCOrEBhxbGGXnJBox9xYk7e46b3ew5I2Escyat2IDhTDoeLTlmEow9CYkbbqSx3WZsk0icwQASaTuMT4v5D7CW+8/YisFa+N8AtfzDq8WMgeEHyBY2NmawFgmQLQ14tPS8MZZIbEgw3tmTxiwJ8ouExLNig4Rj6ca4tBi25xh++PAnQXY7+zHGDz8qbOQk+JM3PvhQYy2LUwtIIrENXTgBh3IQkAeTf/CoGAWjYBSMglEAAIlLV1KuRyPMAAAAAElFTkSuQmCC","orcid":"","institution":"University of Colorado Boulder, Boulder, Colorado, U.S.A.","correspondingAuthor":true,"prefix":"","firstName":"June","middleName":"","lastName":"Gruber","suffix":""}],"badges":[],"createdAt":"2025-02-20 21:36:01","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6074756/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6074756/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":79739703,"identity":"41866192-fbe5-4eb8-9df8-48b1a4a9d873","added_by":"auto","created_at":"2025-04-02 07:40:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":894780,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6074756/v1/75b86221-204c-41e8-ab5e-63c191d9b58e.pdf"},{"id":79738722,"identity":"2c05392a-d67a-4fd1-b432-ae73a4d6135c","added_by":"auto","created_at":"2025-04-02 07:32:34","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":20854,"visible":true,"origin":"","legend":"","description":"","filename":"INDIAHypomaniaRiskProjectSupplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-6074756/v1/8dfd347836103abf4b6f1303.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eBipolar Spectrum Disorder Risk and Positive Emotion Processes in Emerging Adults from India\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBipolar spectrum disorders (BSDs) encompass a serious class of emotional disorders characterized by periods of hypomania/mania (abnormally persistent elevated or expansive mood) and often periods of depression (low and sad mood; American Psychiatric Association, 2022).\u0026nbsp;BSDs are marked by heightened and persistent emotion intensity (e.g., Gruber, 2011; Johnson, 2005), contributing to functional impairments and high rates of global disability (e.g., Fagiolini et al., 2013; Coryell et al., 2003; Dean et al., 2004; Michalak et al., 2007). Despite the severe consequences of BSD, relatively little is known about emotion-related processes in samples outside of WEIRD (i.e., Western, Educated, Industrialized, Rich, and Democratic; e.g., Muthukrishna et al., 2020) contexts. The present investigation is one of the first to examine associations of continuous BSD risk dimensions with emotional experience and regulation in emerging adults from India.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCross-Cultural Approach to BSD Risk and Emotion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBSDs are characterized by emotional reactivity and regulation challenges. Concerning emotion reactivity, findings suggest those at risk for or diagnosed with BSDs, self-report greater positive emotion across contexts (Gruber, 2011; Johnson, 2005). Other research employing experience-sampling paradigms suggests elevated positive and negative emotion outside of the laboratory (e.g., Gruber et al., 2013) and greater instability or variability in emotion intensity in everyday life (e.g., Sperry \u0026amp; Kwapil, 2022). With respect to emotion regulation, or the ability and effort to shift or modulate one’s emotion response, BSD has been associated with trouble regulating positive and negative emotions as well as the maladaptive use of regulation strategies in everyday life and the laboratory, including rumination and emotion-relevant impulsivity (Gruber et al., 2012; Gruber et al., 2013). Yet despite the apparent importance of emotional challenges in BSDs, research on mood disorders to date has primarily focused on Westernized and primarily White samples within the United States (e.g., Ryder, Zhao, Chentsova-Dutton, 2017; Gruber, Kogan, Quoidbach \u0026amp; Mauss, 2013), limiting our ability to understand emotion and BSDs in more diverse cultural contexts (e.g., Villanueva et al., 2023). This work underscores the importance of expanding research to consider the critical role of cultural influence from more collectivistic contexts.\u003c/p\u003e\n\u003cp\u003eExamining the role of cultural context on BSDs and emotions is particularly important given the robust literature base documenting the influence of culture on positive emotion processes (e.g., Tsai, 2007; Miyamoto, Uchida, \u0026amp; Ellsworth, 2010). Concerning emotional experience, in more Western and traditionally individualistic contexts, there is a greater emphasis on autonomy and assertiveness, which are guided by one’s inner psychological attributes (Markus \u0026amp; Kitayama, 2010), as well as a higher valuation of\u0026nbsp;high-arousal positive emotions (e.g., excitement, joy, elation). By contrast, in more Eastern and relatively collectivistic contexts, there is a greater emphasis on emotions that promote interpersonal relatedness (Kitayama, Mesquita, \u0026amp; Karasawa, 2006; Matsumoto et al., 2008). The more people want to adjust to others, the more they value low arousal positive emotions (e.g., serenity, calmness, content; Tsai et al., 2006; Tsai, 2007).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCross-cultural research on emotion regulation suggests that some forms of maladaptive emotion regulation, such as rumination, may have less detrimental effects in East Asian cultures (e.g., Japan, China, and Korea), where rumination is more common than in Western or European American cultures. To our knowledge, other strategies, such as emotion-related impulsivity, that have been strongly associated with BSDs, have not yet been studied outside of the United States.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAn Ideal Entry Point: BSDs and Emotion in India\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExamining emotions among individuals from India presents an ideal entry point to explore the role of cultural context on BSDs and positive emotions. Specifically, India is the second most populous nation globally and an eminent example of a collectivistic culture that emphasizes group cohesion, where group goals are prioritized over individual needs (e.g., Markus \u0026amp; Kitayama, 1991; Mascolo et al., 2004). Furthermore, traditional Indian cultural ideals warrant both the experience and the expression of certain positive emotions; for example, \u003cem\u003esukha\u0026nbsp;\u003c/em\u003e(happiness), which is believed to be an immature emotion, transitory in nature that may interfere with the larger Hindu life goal \u003cem\u003emoksha\u0026nbsp;\u003c/em\u003e(enlightenment)\u003cem\u003e.\u0026nbsp;\u003c/em\u003eThe goal of well-being \u003cem\u003e(hitta)\u0026nbsp;\u003c/em\u003eis emphasized over happiness (Shweder \u0026amp; Haidt, 2000). Although an estimated 7.6 million Indian adults are diagnosed with BSDs and represents a significant public health concern in India (e.g., Pillai et al., 2021; Ramdurg \u0026amp; Kumar, 2013; Dhiman et al., 2022), we are aware of no studies to date examining emotion and BSDs in an Indian sample of emerging adults.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Present Investigation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present investigation was the first to examine associations between self-reported BSD risk with (a) emotion-related experience (i.e., actual and ideal positive emotion experience) as well as (b) maladaptive emotion regulation processes (i.e., rumination and emotion-relevant impulsivity) in a cross-sectional sample of emerging adults from India enrolled in undergraduate courses in Karnataka University. Karnataka is the largest state in Southern India, where English is a widely used language in higher educational institutes. This enabled us to examine two non-mutually exclusive perspectives on the association between BSD risk and emotional experience and goals among Indian emerging adults.\u003c/p\u003e\n\u003cp\u003eOne perspective, referred to as “BSD emotion generalizability,” suggests that the links between emotion processes and BSD risk can be generalized across U.S. and Indian young adult samples. According to this perspective, and based on previous work among emerging adults from U.S. we predict that among Indian emerging adults, BSD risk should be associated with greater high-arousal positive actual affect (Hypothesis 1a), high-arousal positive ideal affect (Hypothesis 1b), positive rumination (Hypothesis 1c), and increased positive emotion-relevant impulsivity (Hypothesis 1d).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA second perspective, referred to as “BSD emotion specificity,” is grounded in cross-cultural research on emotions that highlights the unique influence of culture on positive emotion experience and well-being, predicting distinct patterns of findings in collectivistic versus more individualistic communities. According to this perspective, we predict that although BSD risk should be associated with greater high-arousal positive actual emotion experience based on clinical symptom presentation of BSD risk (Hypothesis 1a), we should expect divergent associations in an Indian young adult sample whereby BSD risk is associated with greater low-arousal positive ideal affect \u0026nbsp;(Hypothesis 2b), lower positive rumination (Hypothesis 2c), and lower positive emotion-relevant impulsivity (Hypothesis 2d).\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eParticipants and Procedure\u003c/h2\u003e \u003cp\u003eParticipants were emerging adults from Karnataka University, Dharwad, India between the ages of 19\u0026ndash;29, consistent with emerging adult age range cutoffs among Indian adults (e.g., Mitra \u0026amp; Arnett, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Participants were recruited in Spring 2018 by posting flyers on various departments\u0026rsquo; notice boards at Karnataka University. Students who were interested in participating contacted the Department of Psychology. The study received Institutional Review Board approval from the KLE Academy of Higher Education \u0026amp; Research, Dharwad, Karnataka. Informed consent was obtained from all individual participants included in the study. Participants with missing data or data entry errors on any of the main study measures that could not be reconciled were excluded. The final sample size for our main analyses was \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;221 (for the actual and ideal affect measures) and \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;219 (for the emotion regulation measures). See Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e for participant descriptives.\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\u003e\u003cem\u003eParticipant Characteristics\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudy Participants\u003c/p\u003e \u003cp\u003e(\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;221)\u003c/p\u003e \u003cp\u003eIdeal \u0026amp; Actual Affect Measures\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStudy Participants\u003c/p\u003e \u003cp\u003e(\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;219)\u003c/p\u003e \u003cp\u003eEmotion Regulation Measures\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (Years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.02 (1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.0 (1.21)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (% Female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocioeconomic Status Rating\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.38 (1.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.40 (1.80)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHPS-48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.29 (5.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.01 (5.39)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASRM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.17 (3.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.04 (3.95)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBDI-SF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.82 (4.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.72 (4.27)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHAP_ideal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.64 (0.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAP_ideal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.53 (0.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHAN_ideal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.53 (0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAN_ideal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.67 (0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHAP_actual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.44 (0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAP_actual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.33 (0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHAN_actual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.67 (0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAN_actual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.78 (0.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRRS-Brooding\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\u003e14.00 (3.56)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePUM\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\u003e30.51 (8.92)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cem\u003eNote\u003c/em\u003e: Socioeconomic Ladder rated from 1 (people who are the worst off, those who have the least money, least education, and worst jobs or no job) and 10 (people who are the best off - those who have the most money, the most education, and best jobs). HPS-48: Hypomanic Personality Scale, 48-item full version; ASRM: Altman Self-Rating Mania Scale; BDI-SF: Beck Depression Inventory, Short-Form; RRS-Brooding: Ruminative Response Scale, Brooding subscale; PUM: Positive Urgency Measure. Values reflect mean values with standard deviations in parentheses unless otherwise noted.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMeasures\u003c/h2\u003e \u003cp\u003eMeasures included survey scales completed by hand assessing mood and symptom risk dimensions, as well as actual and ideal affect, and emotion regulation measures (i.e., rumination and emotion-related impulsivity). Additional measures that are not part of the present study were also collected (see \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eSupplementary Materials\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eRisk for BSDs.\u003c/b\u003e To measure risk for BSDs, the Hypomanic Personality Scale (HPS; Eckblad \u0026amp; Chapman, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1986\u003c/span\u003e) was used. The HPS-48 is a validated and well-used measure, which is composed of 48 true-false items about shifts in emotion, behavior, and energy associated with mania (α\u0026thinsp;=\u0026thinsp;0.67 in the present sample). Sample items include \u003cem\u003e\u0026ldquo;I am frequently so \u0026ldquo;hyper\u0026rdquo; that my friends kiddingly ask me what drug I\u0026rsquo;m taking.\u0026rdquo;\u003c/em\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eCurrent Symptoms.\u003c/b\u003e Current mania symptoms were measured using the Altman Self-Rating Mania Scale (ASRM; Altman, Hedeker, Peterson, \u0026amp; Davis, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1997\u003c/span\u003e), which is a 5-item self-report inventory scored from 0 to 4 and total scores ranging from 0 to 20 (α\u0026thinsp;=\u0026thinsp;0.58), with higher scores indicating greater mania severity. Sample items include \u003cem\u003e\u0026ldquo;I do not feel happier or more cheerful than usual\u0026rdquo;\u003c/em\u003e and \u003cem\u003e\u0026ldquo;I can go all day or night without any sleep and still not feel tired.\u0026rdquo;\u003c/em\u003e The Beck Depression Inventory-Short Form (BDI-SF; Beck \u0026amp; Beck, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1972\u003c/span\u003e) is a 13-item self-report scale used to measure current symptoms of depression scored from 0 to 3, with total summed scores ranging from 0 to 39 (α\u0026thinsp;=\u0026thinsp;0.73 in the present study), with higher scores indicating greater depression severity. Sample items include \u003cem\u003e\u0026ldquo;I do not feel that the future is hopeless and that things cannot improve\u0026rdquo;\u003c/em\u003e and \u003cem\u003e\u0026ldquo;I feel I am a complete failure as a person\u003c/em\u003e.\u0026rdquo;\u003c/p\u003e \u003cp\u003e \u003cb\u003eActual and Ideal Affect.\u003c/b\u003e To measure differences in actual and ideal affect, the Affect Valuation Index (AVI) by Tsai et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) was used. Participants were asked how much they would ideally like to feel(for ideal affect) and how much they typically feel (for actual affect) regarding 28 different emotion items, rated on a scale from 1(very slightly or not at all) to 5 (extremely or all of the time). Individual emotion items were then scored into four categories, separately for actual and ideal affect, including High Arousal Positive (HAP; enthusiastic, elated), Low Arousal Positive (LAP; calm, relaxed, peaceful), High Arousal Negative (HAN; fearful, hostile, nervous), and Low Arousal Negative (LAN; dull, sleepy, sluggish). Both actual (HAP\u003csub\u003eα\u003c/sub\u003e= 0.60; LAP\u003csub\u003eα\u003c/sub\u003e=0.60; HAN\u003csub\u003eα\u003c/sub\u003e=0.58; LAN\u003csub\u003eα\u003c/sub\u003e=0.55) and ideal (HAP\u003csub\u003eα\u003c/sub\u003e=0.60; LAP\u003csub\u003eα\u003c/sub\u003e=0.55; HAN\u003csub\u003eα\u003c/sub\u003e=0.61; LAN\u003csub\u003eα\u003c/sub\u003e=0.56) affect had moderate internal consistency.\u003c/p\u003e \u003cp\u003e \u003cb\u003eNegative Rumination\u003c/b\u003e. Negative (or depressive) rumination was measured using the 5-item brooding subscale from the Ruminative Response Scale (RRS-brooding; Treynor et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Items were rated on a 4-point Likert scale ranging from 1 (\u003cem\u003enever\u003c/em\u003e) to 4 (\u003cem\u003ealways\u003c/em\u003e). Brooding has been conceptualized as a passive, self-criticizing aspect of repetitive thought, measured with items such as \u003cem\u003e\u0026ldquo;Why do I have problems other people don\u0026rsquo;t have?\u0026rdquo;\u003c/em\u003e The RRS-brooding subscale demonstrated acceptable internal consistency in the current study (α\u0026thinsp;=\u0026thinsp;0.65).\u003c/p\u003e \u003cp\u003e \u003cb\u003ePositive Emotion-Relevant Impulsivity.\u003c/b\u003e Positive emotion-relevant impulsivity (or positive urgency) was measured using the Positive Urgency Measure (PUM; Cyders et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), which assesses the tendency for a person to engage in harmful or risky behaviors in response to positive mood states. The PUM scale consists of 14 self-reported true-false items, such as \u003cem\u003e\u0026ldquo;When I am very happy, I can't seem to stop myself from doing things that can have bad consequences\u003c/em\u003e.\u003cem\u003e\u0026rdquo;\u003c/em\u003e The PUM demonstrated good internal consistency in the current study (α\u0026thinsp;=\u0026thinsp;0.82).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eStudy analyses were pre-registered on the Open Science Framework initially for actual and ideal affect measures (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://osf.io/2gctm\u003c/span\u003e\u003cspan address=\"https://osf.io/2gctm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and, subsequently, for the emotion regulation measures after the analyses for ideal and actual affect had been completed (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://osf.io/8ycs9\u003c/span\u003e\u003cspan address=\"https://osf.io/8ycs9\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003ePreliminary Analyses\u003c/h3\u003e\n\u003cp\u003eWe first examined the skewness and kurtosis indices for all primary variables (HPS-48, ASRM, BDI-SF, AVI, PUM, RRS), and none of these departed from normality, so no transformations were applied. Second, we examined whether demographic variables (e.g., age, gender, SES) were associated with our BSD risk variable (HPS-48). HPS-48 was not significantly associated with age (\u003cem\u003er\u003c/em\u003e(221)\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.059, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.381) or socioeconomic status (SES; \u003cem\u003er\u003c/em\u003e(221)\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.132, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.051), and male and female participants did not differ in HPS-48 scores (\u003cem\u003eF\u003c/em\u003e(1,220)\u0026thinsp;=\u0026thinsp;1.03, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.311). Hence, we did not control for these demographic variables in our main analyses. Third, we examined whether any of our primary variables had significant outliers, and a total of 4 cases (.002%) were Winsorized accordingly (i.e., assigned the next highest or lowest value at or below 3 SDs)\u003csup\u003e1\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eMain Analyses\u003c/h2\u003e \u003cp\u003e \u003cb\u003eIdeal and Actual Affect.\u003c/b\u003e Our main analyses used a hierarchical linear regression analysis with BD risk (HPS) as the dependent variable. Mood symptom covariates (ASRM, BDI-SF) were entered in Block 1, and the AVI-actual subscales (HAP, LAP, HAN, LAN) were entered together in Block 2. As seen in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, results suggested that BSD risk was not predicted by any of the AVI-actual subscales. For ideal affect, we entered the AVI-ideal subscales in Block 3 (while controlling for AVI-actual in Block 2), and results suggested that BSD risk was also not predicted by any of the AVI ideal subscales also.\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\u003cem\u003eRegression Analyses using AVI-Actual (Aim 1) and AVI-Ideal (Aim 2) subscales to Predict Bipolar Risk (HPS-48) Scores.\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eHPS-48\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eAVI-Actual Affect\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eAVI-Ideal Affect\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e∆R\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e∆R\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBlock 1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASRM\u003c/p\u003e \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 \u003cp\u003e\u003cb\u003e.28**\u003c/b\u003e\u003c/p\u003e \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\u003e\u003cb\u003e.29**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBDI-SF\u003c/p\u003e \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 \u003cp\u003e\u003cb\u003e.32**\u003c/b\u003e\u003c/p\u003e \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\u003e\u003cb\u003e.32**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBlock 2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAVI-HAP\u003csub\u003eactual\u003c/sub\u003e\u003c/p\u003e \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 \u003cp\u003e\u0026minus;\u0026thinsp;.09\u003c/p\u003e \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\u003e\u0026minus;\u0026thinsp;.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAVI-LAP\u003csub\u003eactual\u003c/sub\u003e\u003c/p\u003e \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 \u003cp\u003e.02\u003c/p\u003e \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\u003e\u0026minus;\u0026thinsp;.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAVI-HAN\u003csub\u003eactual\u003c/sub\u003e\u003c/p\u003e \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 \u003cp\u003e.03\u003c/p\u003e \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\u003e.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAVI-LAN\u003csub\u003eactual\u003c/sub\u003e\u003c/p\u003e \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 \u003cp\u003e\u0026minus;\u0026thinsp;.05\u003c/p\u003e \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\u003e.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBlock 3\u003c/b\u003e\u003c/p\u003e \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 \u003cp\u003e.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAVI-HAP\u003csub\u003eideal\u003c/sub\u003e\u003c/p\u003e \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\u003e.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAVI-LAP\u003csub\u003eideal\u003c/sub\u003e\u003c/p\u003e \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\u003e.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAVI-HAN\u003csub\u003eideal\u003c/sub\u003e\u003c/p\u003e \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\u003e.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAVI-LAN\u003csub\u003eideal\u003c/sub\u003e\u003c/p\u003e \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\u003e\u0026minus;\u0026thinsp;.11\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\u003e\u003cem\u003eNote:\u0026nbsp;\u003c/em\u003eASRM = Altman Self-Rating Mania Scale; BDI-SF = Beck Depression Inventory, Short-Form; AVI = Affect Valuation Index; HAP = High Arousal Positive; LAP = Low Arousal Positive; HAN = High Arousal Negative; LAN = Low Arousal Negative; \u0026beta; = Standardized beta coefficients (Beta values are from Model 2 for Aim 1 and Beta values are from Model 3 for Aim 2). *\u003cem\u003ep\u003c/em\u003e \u0026lt; .05, **\u003cem\u003ep\u003c/em\u003e \u0026lt; .01.\u003c/p\u003e \u003cp\u003eWe conducted three sets of post-hoc exploratory, non-pre-registered analyses to better understand links between actual and ideal affect with current symptom severity (See \u003cb\u003eSupplementary Materials\u003c/b\u003e for additional details). First, we examined whether BSD risk was associated with any of the AVI-actual and AVI-ideal subscales when symptoms were not controlled for, and no significant associations emerged (see \u003cb\u003eTable S2A\u003c/b\u003e). Second, we examined bivariate correlations between current symptoms (ASRM, BDI-SF) with the AVI-actual and AVI-ideal subscales (see \u003cb\u003eTable S2B\u003c/b\u003e). No significant correlations emerged between current mood symptoms and AVI-ideal affect. However, ASRM scores were associated with increased AVI-HAP\u003csub\u003eactual\u003c/sub\u003e and increased AVI-LAP\u003csub\u003eactual,\u003c/sub\u003e and BDI-SF scores were associated with decreased AVI-HAP\u003csub\u003eactual\u003c/sub\u003e, decreased AVI-LAP\u003csub\u003eactual\u003c/sub\u003e, increased AVI-HAN\u003csub\u003eactual\u003c/sub\u003e, and increased AVI-LAN\u003csub\u003eactual\u003c/sub\u003e. Third, we examined associations between BSD risk and mood symptoms (BDI-SF, ASRM) with discrepancy (or difference) scores between AVI\u003csub\u003eideal\u003c/sub\u003e and AVI\u003csub\u003eactual\u003c/sub\u003e subscales (see \u003cb\u003eTable S2C\u003c/b\u003e). Results suggested BSD risk was positively correlated to LAP\u003csub\u003eactual-ideal\u003c/sub\u003e and LAN\u003csub\u003eactual-ideal\u003c/sub\u003e, BDI-SF was positively correlated with LAP\u003csub\u003eactual-ideal\u003c/sub\u003e, and ASRM was negatively correlated with HAP\u003csub\u003eactual-ideal\u003c/sub\u003e and LAN\u003csub\u003eactual-ideal\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eEmotion Regulation Processes.\u003c/b\u003e We used a hierarchical linear regression analysis with BSD risk (HPS-48) as the dependent variable. Mood symptom covariates (ASRM, BDI-SF) were entered in Block 1, and the RRS_brooding subscale was entered in Block 2. The second aim also used a similar regression analysis with HPS-48 as the dependent variable, ASRM and BDI-SF entered in Block 1, and the PUM scale entered in Block 2. This analytic plan allowed us to examine whether BSD risk is associated with the RRS_brooding subscale and PUM, respectively. As seen in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, results suggested that greater BD risk was predicted by increased negative (depressive) rumination and increased positive urgency.\u003csup\u003e2\u003c/sup\u003e\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\u003e\u003cem\u003eRegression Analyses using RRS (Aim 1) and PUM (Aim 2) subscales to Predict Bipolar Risk (HPS-48) Scores.\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eHPS-48\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eAim 1 (RRS)\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eAim 2 (PUM)\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e∆R\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e∆R\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBlock 1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASRM\u003c/p\u003e \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 \u003cp\u003e\u003cb\u003e.29**\u003c/b\u003e\u003c/p\u003e \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\u003e\u003cb\u003e.28**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBDI-SF\u003c/p\u003e \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 \u003cp\u003e\u003cb\u003e.30**\u003c/b\u003e\u003c/p\u003e \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\u003e\u003cb\u003e.27**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBlock 2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRRS-brooding\u003c/p\u003e \u003cp\u003e(or PUM)\u003c/p\u003e \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 \u003cp\u003e\u003cb\u003e.16*\u003c/b\u003e\u003c/p\u003e \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\u003e\u003cb\u003e.24**\u003c/b\u003e\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\u003e\u003cem\u003eNote:\u0026nbsp;\u003c/em\u003eASRM = Altman Self-Rating Mania Scale; BDI-SF = Beck Depression Inventory, Short Form; RRS-Brooding; PUM = Positive Urgency Measure; \u0026beta; = Standardized beta coefficients (Beta values are from Model 2 for Aim 1 and 2). *\u003cem\u003ep\u003c/em\u003e \u0026lt; .05, **\u003cem\u003ep\u003c/em\u003e \u0026lt; .01.\u003c/p\u003e \u003cp\u003eWe conducted additional non-preregistered analyses examining potential demographic differences in our primary variables, as shown in \u003cb\u003eSupplementary Materials Table S3\u003c/b\u003e. Results indicated that HPS, PUM, and RRS-brooding were not significantly associated with age, socio-economic status, or gender differences (see Table S3). However, women scored higher than men on the RRS-brooding subscale, consistent with past research.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eBipolar spectrum disorders are common and costly affective disturbances marked by prominent emotion difficulties. Yet current research has largely focused on studying emotions and bipolar disorders in largely Westernized contexts, which stymies our ability to understand a more diverse range of human experiences. This is particularly important given the influence of cultural values on the experience and management of emotions. The present study hence examined associations between BSD risk and mood symptoms with emotion experience and regulation in a sample of emerging adults from India. Notably, India remains a relatively understudied collectivistic society centered mainly on East Asian populations. We sought to understand better the cultural generalizability versus specificity in examining links between BSD risk with emotion experience and regulation among emerging adults from India.\u003c/p\u003e \u003cp\u003e \u003cb\u003eNo Cross-Cultural Associations between BSD and Emotion Experience and Values in Indian Adult Sample.\u003c/b\u003e Our overarching aim was to extend prior work on emotion experience and values related to BSD by expanding to a sample of Indian emerging adults. Contrary to our predictions, risk for developing bipolar disorder was not significantly associated with either actual or ideal positive emotional experiences. This finding partially supports the BSD emotion specificity perspective, which posits that the emotional patterns seen in BSD risk may vary across cultural contexts. Specifically, while Western samples have shown strong associations between BSD risk and heightened actual positive emotion experience (Gruber, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Johnson, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), our results suggest that in India, this association may be less pronounced. This lack of association could reflect cultural differences in how positive emotions are experienced and expressed. For instance, in more collectivistic societies like India, low-arousal positive emotions such as calmness and contentment may be more valued, making high-arousal positive emotions (often associated with BSD symptoms) less relevant to the experience of BSD risk.\u003c/p\u003e \u003cp\u003eIndeed, when exploring our post-hoc exploratory analysis, we observed additional patterns that align with the BSD emotion specificity perspective. Specifically, misalignments between ideal and actual low-arousal positive emotions (calm, relaxed) showed relevance to BSD risk. These findings are consistent with those observed in East Asian collectivistic populations (e.g., China, Japan, South Korea) regarding their relationship with depression. Tsai (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) found that in a Chinese sample, discrepancies between actual and ideal high-arousal positive emotions were not correlated with depression, but discrepancies in low-arousal positive emotions were.\u003c/p\u003e \u003cp\u003eTo further understand these results, future research should focus on two key areas: (1) examining how ideal and actual emotions are conceptualized in the Indian cultural context, and (2) ensuring that the psychometric properties of emotion measures are parallel across cultural contexts. These steps will be crucial for clarifying the role of emotional misalignment in BSD risk and ensuring that research on emotional experiences and regulation is culturally sensitive and valid. Additionally, improving the reliability and validity of the measures used to assess emotional experiences and regulation across diverse cultural contexts will help refine our understanding of the cultural nuances that influence BSD risk.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCross-Cultural Replication of BSD Risk and Emotion Regulation.\u003c/b\u003e Our overarching aim in this section was to replicate previous findings on emotion regulation in BSD risk, extending them to a cross-cultural sample of Indian emerging adults. Consistent with the BSD emotion generalizability perspective, our study found that increased BSD risk was associated with maladaptive emotion regulation strategies, such as positive emotion-relevant impulsivity and negative rumination. These findings align with previous research in U.S. samples, where similar patterns of emotion regulation were linked to BSD risk (Gruber et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Cyders et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). This suggests that trait BSD risk may be tied to maladaptive emotion regulation patterns, which are stable markers of BSD risk across individualistic and collectivistic cultural contexts. The findings highlight cross-cultural generalizability, which suggests that maladaptive emotion regulation strategies are not exclusive to Western contexts but may be a universal feature of BSD risk, irrespective of cultural differences in emotional experience and expression. As such, it underscores the importance of considering cultural specificity and generalizability in future research on BSD and emotion regulation. Future work should explore whether these maladaptive emotion regulation strategies are universally associated with BSD or if cultural factors shape how these strategies are expressed and their impact on the disorder.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eLimitations and Future Directions\u003c/h2\u003e \u003cp\u003eThe present investigation should be interpreted with several key limitations. First, the present study relied solely on self-report measures of emotion-related experience and regulation processes. Future work adopting multi-method approaches employing behavioral and psychophysiological indices of emotion processes is warranted to ensure the robustness of the observed findings. Second, we note that the internal consistency (i.e., alpha) values were low for the actual and ideal affect measures, suggesting potential limitations with the validity of the measurements in this context. Future work employing rigorous psychometric approaches to establish the validity of this measure among Indian adults is warranted. Third, the present study was well-sized but limited to one specific cross-cultural (i.e., India) context. Replications in larger samples, with a specific focus on cross-cultural comparisons between other collectivistic cultures like East Asian (e.g., China) and Latin American (e.g., Mexico) cultures, as well as more Westernized (e.g., United States), would allow a more direct cross-cultural comparison. Furthermore, considering India's diversity in languages, cultures, and regional variations, future work within Indian samples could explore how these diverse cultural norms and social pressures influence emotional experiences and regulation. Finally, as the present investigation used a continuous measure of bipolar risk and symptoms and did not include a specifically clinically recruited or diagnosed population, future work examining more severe at-risk or diagnosed populations is warranted to extend this work into a more severe clinical context.\u003c/p\u003e \u003cp\u003eTaken together, the present investigation provides initial proof-of-concept findings underscoring the need to adopt a cross-cultural approach to understanding emotion and psychopathology with bipolar disorders and more generally. Such approaches will help determine the consistency of these associations across different cultural contexts and enhance the generalizability of emotion and mood findings.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe de-identified dataset and syntax used in the present investigation is available online: https://github.com/GruberPEPLab/IndiaPaper_Rosaetal.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman Ethics and Consent to Participate Declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study received Institutional Review Board approval from the KLE Academy of Higher Education \u0026amp; Research, Dharwad, Karnataka. Informed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received for conducting this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank Lilla Kovacs for her input, assistance with data analysis design, and feedback on the manuscript draft. We would also like to thank the Positive Emotion and Psychopathology Laboratory for their feedback on previous drafts.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAltman, E. G., Hedeker, D., Peterson, J. L., \u0026amp; Davis, J. M. (1997). 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Lewis \u0026amp; J. M. Haviland-Jones (Ed.), Handbook of emotions, (2nd ed., pp.397-414). Guilford.\u003c/li\u003e\n\u003cli\u003eSperry, S. H., \u0026amp; Kwapil, T. R. (2022). Bipolar spectrum psychopathology is associated with altered emotion dynamics across multiple timescales. \u003cem\u003eEmotion\u003c/em\u003e, \u003cem\u003e22\u003c/em\u003e(4), 627-640. https://doi.org/10.1037/emo0000759\u003c/li\u003e\n\u003cli\u003eTreynor, W., Gonzalez, R., \u0026amp; Nolen-Hoeksema, S. (2003). Rumination reconsidered: A psychometric analysis. \u003cem\u003eCognitive Therapy and Research, 27\u003c/em\u003e(3), 247\u0026ndash;259. https://doi.org/10.1023/A:1023910315561\u003c/li\u003e\n\u003cli\u003eTsai, J. L. (2007). Ideal affect: cultural causes and behavioral consequences. \u003cem\u003ePerspectives on Psychological Science, 2,\u003c/em\u003e 242-259. https://doi.org/10.1111/j.1745-6916.2007.00043.x\u003c/li\u003e\n\u003cli\u003eTsai, J.L., Knutson, B., \u0026amp; Fung, H. H. (2006). Cultural variation in affect valuation. \u003cem\u003eJournal of Personality and Social Psychology, 90 \u003c/em\u003e(2)\u003cem\u003e,\u003c/em\u003e 288-307. https://doi.org/10.1037/0022-3514.90.2.288\u003c/li\u003e\n\u003cli\u003eVillanueva, C. M., Swerdlow, B. A., \u0026amp; Gruber, J. (2023). The challenge of emotion regulation in bipolar disorder. In J. J. Gross \u0026amp; B. Q. Ford (Eds.),\u003cem\u003e Handbook of emotion regulation\u003c/em\u003e (3rd edition). Guilford Press.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e For the analysis on emotion regulation in a slightly smaller subsample of the same participants (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;219), HPS-48 was still not significantly associated with age (\u003cem\u003er\u003c/em\u003e(219)\u0026thinsp;=\u0026thinsp;.04, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.55) or SES (\u003cem\u003er\u003c/em\u003e(219)\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.10, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.12). Furthermore, for Winsorizing a total of 4 cases (approximately .004%) of the data was Winsorized.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e We were unable to analyze one of our original pre-registered study aims focusing on positive rumination due to a data entry error that was irreconcilable.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Colorado Boulder","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Bipolar Disorder, Emotion Regulation, Affect Valuation, Culture, India","lastPublishedDoi":"10.21203/rs.3.rs-6074756/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6074756/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBipolar spectrum disorders (BSDs) encompass an umbrella of severe affective disorders characterized by prominent positive emotion difficulties. Despite the prominence of emotion challenges among BSDs, little is known about relevant emotion goals and regulation processes among more diverse samples outside the United States. This lack of inclusive research in emotion and BSDs stymies our ability to assess the generalizability of findings and the critical influence of cultural context on emotional processes. Given the prominence of positive emotion experiences and values among Southeast Asian (i.e., Indian) cultural contexts, they represent an ideal entry point to better understand potential sources of cultural-variation on BSD risk and relevant positive emotion processes. The present investigation examined BSD risk dimensions with emotion experience (actual and ideal) and emotion regulatory processes among emerging adults from India. Results suggested some sources of cultural divergence (i.e., for ideal affect and BSD risk) as well as potential cross-cultural generalizability (i.e., for emotion regulation processes) when compared to previous studies among Westernized U.S. young adult samples. This work underscores the importance of expanding emotion and psychopathology research to more diverse and global populations.\u003c/p\u003e","manuscriptTitle":"Bipolar Spectrum Disorder Risk and Positive Emotion Processes in Emerging Adults from India","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-02 07:24:29","doi":"10.21203/rs.3.rs-6074756/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7da375ad-8613-47dc-8a6c-9fbe7f2c6735","owner":[],"postedDate":"April 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":44650863,"name":"Psychology"}],"tags":[],"updatedAt":"2025-04-02T07:24:29+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-02 07:24:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6074756","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6074756","identity":"rs-6074756","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}