Development of a Reappraisal Flexibility Scale and Examination of Its Reliability and Validity

Development of a Reappraisal Flexibility Scale and Examination of Its Reliability and Validity | 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 Development of a Reappraisal Flexibility Scale and Examination of Its Reliability and Validity Megumi Oikawa, Ryota Kobayashi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8214974/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 Reappraisal is widely recognized as an adaptive emotion regulation strategy; however, recent research suggests that it comprises several substrategies, whose effectiveness can vary across different stress-related contexts. These findings suggest that the ability to use reappraisal flexibly in response to stressful situations may play a crucial role in promoting psychosocial adjustment. This study aimed to develop a reappraisal flexibility scale. Based on previous research on emotion regulation models, the present study developed a scale for measuring four aspects of reappraisal flexibility scale (RFS), namely, context sensitivity, repertoire, monitoring, and modification. Two online surveys were conducted, each collecting data from 300 adults. For each set of data, confirmatory factor analysis confirmed the assumed four-factor structure. The reliability obtained for each subscale was satisfactory. Relationships with existing scales demonstrated that the associations were generally as expected, thus indicating the validity of the proposed scale. This scale accurately elucidates the criticality of reappraisal flexibility in psychosocial adjustment. reappraisal flexibility reliability validity emotion regulation Introduction Emotion regulation is defined as intentional (but not necessarily conscious) attempts to change the intensity, duration, and frequency/type of a current or an anticipated affect (Gross et al., 2019 ). Among the various approaches to emotion regulation research, one of the most typical focuses on emotion regulation strategies. For the process model of emotion regulation, various strategies are also available, such as reappraisal, distraction, and suppression of expression (Gross, 1998 , 2014 ). Previous studies on emotion regulation strategies demonstrate that each strategy exerts a different effect on emotional experience and mental health (e.g., Aldao et al., 2010 ; Webb et al., 2012 ). Reappraisal is an effective emotion regulation strategy for reducing negative emotions and facilitating mental health. Reappraisal is defined as the process of reinterpreting emotions, emotion-evoking situations, or causes, and of altering the goals of a situation (Gross, 2015 ; Uusberg et al., 2023 ). A meta-analysis on experimental studies reported that reappraisal could significantly decrease negative emotions compared with conditions that employed other emotion regulation strategies or control conditions (Webb et al., 2012 ). Similar results were also confirmed in a meta-analysis on studies that employed ecological momentary assessments (Boemo et al., 2022 ). In addition, research using questionnaires demonstrated that people with a high reappraisal tendency exhibit positive mental health (Hu et al., 2014 ). Recent studies have noted that reappraisal features substrategies (Sakakibara, 2014 ), and McRae et al. ( 2012 ) proposed eight distinctions. For example, the explicitly positive substrategy refers to a reinterpretation that actively identifies the positive aspects of a stressful event, while the distancing substrategy denotes a reinterpretation that views a stressful event from a distant perspective. Importantly, each substrategy exerts different effects on emotional experience and mental health (e.g., Webb et al., 2012 ). Suzuki and Oikawa ( 2018 ) experimentally examined and reported that the explicitly positive and distancing strategies decrease negative emotions. Out of the two, however, only the explicitly positive strategy increases positive emotion. A notable limitation of reappraisal research is its narrow focus on the implementation or frequency of reappraisal strategies and its lack of consideration for flexibility in using these strategies. Previous studies implicitly assume that reappraisal attempts are successful and lead to desirable outcomes (e.g., downregulation of negative emotions) for most people. Contrary to this assumption, recent research indicates that attempts at reappraisal are not always successful (Ford & Troy, 2019 ). In general, after a serious failure, expressing an explicitly positive reinterpretation immediately, such as “this will lead to my growth,” would be difficult, and even if it came to mind, believing it will be difficult. However, from the perspective of the reappraisal substrategy, distancing substrategy may be possible in the same scenario, although the explicitly positive substrategy is difficult. Moreover, if one reinterpretation is not convincing, then some people end reappraisal, while others attempt to give another reinterpretation. Thus, considering not only whether to perform reappraisal but also whether to use reappraisal substrategies flexibly according to a situation may be necessary. The current study points out the necessity of adding the perspective of flexibility to reappraisal research. In this regard, research on emotional regulation flexibility (ERF), which has attracted scholarly attention as an important aspect of emotion regulation, is suggestive. ERF refers to the process of changing emotion regulation according to a situation and purpose (Aldao et al., 2015 ; Bonanno & Burton, 2013 ; Cheng et al., 2014 ). Bonanno and Burton ( 2013 ) proposed one of the typical models of ERF, which can be mainly distinguished into three sequential components, namely, context sensitivity, repertoire, and feedback (Kalokerinos & Koval, 2024 ; Usukura, 2023 ). Context sensitivity is defined as follows: the ability to perceive impinging demands and opportunities from the situational context as they emerge over and above the normative background of ongoing regulatory concerns and processes and to determine the most appropriate regulatory strategy in response to those demands or opportunities. (Bonanno & Burton, 2013 ). Context sensitivity is the first step in ERF, and an accurate perception of a situation will lead to the selection of an emotion regulation strategy that is appropriate to the situation in the next step (i.e., repertorire). At this stage, the situation is appraised in terms of its controllability, importance, urgency, and the intensity of emotions it evokes (Bonanno et al., 2020 ; Cheng, 2001 ). For example, distraction is more likely to be implemented than reappraisal in situations evaluated as evoking high-intensity negative emotions (Sheppes, 2020 ; Sheppes et al., 2011 ). The repertoire component refers to “the ability to utilize a wide range of regulatory strategies that might accommodate divergent contextual demands and opportunities” (Bonanno & Burton, 2013 ). Even if a situation is properly assessed, an appropriate strategy will not be implemented unless it is in the repertoire. An experience sampling study found that the greater the repertoire of emotion regulation, the lower the levels of depression and anxiety (Chen et al., 2024 ). The final step in the ERF model is the feedback component, which is defined as “the ability to monitor and use feedback about the efficacy of a chosen regulatory strategy over time so as to adjust or correct behavior when needed.” As implied by the definition, two important aspects are involved in feedback, namely, monitoring and modifying the implementation of emotion regulation. A flexible regulation of emotions requires monitoring whether emotions are changing according to the desired direction due to the use of specific strategies. If this attempt is unsuccessful, then contextual information is reevaluated, and the strategy is adjusted or switched. The feedback component supports the monitoring of an ongoing adjustment process and adjusting and switching strategies. Individuals with better performance in switching from unsuccessful strategies to other strategies tend to exhibit high levels of well-being (Birk & Bonanno, 2016 ). Based on this discussion, the current study aims to incorporate the ERF perspective into reappraisal research and to examine reappraisal flexibility. Since ERF research typically focuses on variations or repertoires among strategies (e.g., Li et al., 2024 ) or does not focus on any specific strategy (e.g., Kato, 2020 ), research on the flexible implementation of reappraisal remains limited. In this context, Weber et al. ( 2013 ) and Marciniak et al. ( 2024 ) are among the few studies examining flexibility in reappraisal. In Weber et al. ( 2013 ), participants were presented with vignettes depicting anger-evoking scenes and asked to write down as many reappraisals as possible. The number of descriptions, termed “reappraisal inventiveness,” was found to relate to divergent thinking task performance. Marciniak et al. ( 2024 ) used the experience sampling method, asking participants to reinterpret a recent stressful situation. Individuals who adapted reappraisal use to the emotional intensity of situations showed decreased stress scores from baseline to follow-up. Although previous studies have examined reappraisal flexibility, they addressed only specific aspects of flexibility. Therefore, we aim to formulate a scale for measuring reappraisal flexibility (i.e., reappraisal flexibility scale [RFS]) and to examine its reliability and validity. We define reappraisal flexibility as selecting and implementing appropriate reappraisal substrategies based on contextual information and monitoring and adjusting such processes as necessary. Based on the ERF model of Bonanno and Burton ( 2013 ), the RFS was created assuming a four-factor structure, namely, context sensitivity, repertoire, monitoring, and modification. Context sensitivity refers to the ability to perceive a situation and goal and to select reappraisal substrategies given this contextual information. Careful judgment is required to use reappraisal effectively in situations that evoke high-intensity negative emotions (e.g., Sheppes et al., 2011 ) or situations with controllable stressors (e.g., Troy et al., 2013 ). Individuals that possess this ability would be capable of noticing such contextual information and selecting appropriate substrategies. Repertoire refers to the ability to produce various interpretations of emotions and their causes. Individuals with this ability would be capable of presenting different interpretations such as “there is something to learn from the mistake,” “it was not such a bad failure,” or “I accept that I made a mistake” in failure situations. Monitoring and modification are the two components that distinguish feedback in the ERF model. Monitoring refers to the ability to monitor whether emotions have changed toward the desired direction, while modification refers to the ability to explore different reappraisal substrategies while considering the evaluation. Individuals with this ability would be capable of constructing new interpretations instead of retaining old ineffective ones. To examine the construct validity of the scale, we examine its relationship with the following scales. First, the Multifaceted Reappraisal Questionnaire (Oikawa et al., 2021 ) is a scale based on the eight categories of reappraisal presented by McRae et al. ( 2012 ) and measures the tendency to use various reappraisal substrategies. We expected a positive association with this measure (Hypothesis 1) because the repertoire factor of the RFS is assumed to reflect the ability to construct various reinterpretations. Second, the Coping Flexibility Scale-Revised (Kato, 2020 ) measures overall coping flexibility and consists of three subscales, namely, abandonment, recoping, and meta-coping. Abandonment refers to the ability to discontinue ineffective strategies, while recoping reflects the ability to initiate new and different strategies. Meta-coping refers to the ability to monitor the process and effects of coping and to determine whether to continue, abandon, or change strategies. Based on these definitions, the current study predicts that these three subscales will be positively associated with the monitoring and modification factors of the RFS (Hypothesis 2). Third, the Meta-Social Skill Measurement measures the skills to metarecognize one’s skills and interpersonal situation, and chooses an appropriate skill (Ishii, 2007 ). In this measurement, a scale about the meta-recognition of situations focuses on interpersonal situations but includes aspects such as understanding situations and acting with a consideration of desired outcomes. The context sensitivity of RFS is expected to be positively related to this measure (Hypothesis 3), because it reflects the consideration of context and purpose when using reappraisal. Finally, given that overall flexibility in emotion regulation exerts positive effects on mental health (e.g., Birk & Bonanno, 2016 ; Chen et al., 2024 ), we predict that RFS will be significantly associated with depressive tendencies and well-being (Hypothesis 4). Method Participants and Procedure In this study, two surveys were conducted separately, and two sets of data were obtained (Data 1 and 2) to verify the stability of factor analysis. All surveys were conducted in Japanese. The participants belong to the general adults aged 18–60 years in Japan (Data 1: N = 300 [men: 140, women: 155, nonbinary: 2, unwilling to answer: 3, age: 21–60], mean age = 41.54 years, SD = 8.66; Data 2: N = 300 [men: 115, women: 181, nonbinary: 2, unwilling to answer: 2, age: 18–60], mean age = 41.49 years, SD = 9.53). The participants were recruited through CrowdWorks, a crowdsourcing company, and data were collected via an online survey. The questionnaire was designed using Qualtrics, an online survey tool, and the participants were asked to complete the questionnaire. The items were presented randomly on each scale. This study was conducted in accordance with the principles of the Declaration of Helsinki. Informed consent was obtained from all participants, and this study was approved by the research ethics committee of [blinded for review]. Measures Reappraisal flexibility. Based on the theory of regulatory flexibility (Bonanno & Burton, 2013; Usukura, 2023), this study operationalized the concept and drafted items referencing Kato (2020). Three graduate students majoring in clinical psychology reviewed the items for conceptual alignment, clarity, and necessary revisions. We prepared five context sensitivity items, four repertoire items, four monitoring items, and four modification items for a total of 17 items in the RFS (Appendix A). The items were rated using a five-point scale (1 = not applicable, 5 = applicable). The following scales were measured to examine the validity of the proposed scale. Reappraisal substrategies. We used the 32-items of the Multifaceted Reappraisal Questionnaire (Oikawa et al., 2021). The scores range from 32 to 160. The total high scores indicate the use of various reappraisal substrategies. Items were rated using a five-point scale (1 = not applicable, 5 = applicable). Coping flexibility. The study employed the 12-item Coping Flexibility Scale-Revised (Kato, 2020). This scale features three subscales (i.e., abandonment, recoping, and meta-coping), and each consists of four items. This scale measures overall coping flexibility. Items were rated using a four-point scale (0 = not applicable, 3 = very applicable). Meta- recognition of situations. We used 10 items of the Meta-Recognition of Situations in the Meta-Social Skill Measurement (Ishii, 2007). This measure includes aspects such as adopting attitudes and actions with consideration of a situation and desired outcomes. Items were rated using a four-point scale (1 = not at all applicable, 4 = very applicable). Depression . We used the six-item Kessler-6 (Furukawa et al., 2008) to measure depression. Items were rated using a five-point scale (0 = none of the time, 4 = all of the time) Well- being. We used the five-item WHO Five Well-Being Index (Awata et al., 2007) to measure well-being. Items were rated using a six-point scale (0 = no time, 5 = all of the time). Stressful events. Recently experienced stressful events may also influence the association between reappraisal flexibility and mental health; therefore, we used a 30-item scale to measure daily hassles (Munakata, 1996). Items were rated using a three-point scale (0 = not so, 2 = very much so). For Data 1, the researchers measured reappraisal flexibility, reappraisal substrategies, coping flexibility, and meta-recognition of situations. For Data 2, reappraisal flexibility, depression, well-being, and stressful events were measured. Data analysis Analyses were conducted using JASP (JASP Team, 2025) and R (version 4.5.1; R Core Team, 2025). Although we hypothesized a four-factor model, we first confirmed the appropriateness of the number of factors through an exploratory factor analysis of Data 1, and then conducted a confirmatory factor analysis assuming a four-factor structure. Internal consistency and correlations with relevant existing scales were assessed for each dataset. For mental health variables (depression and well-being), partial correlations controlling for stressful events were examined. Discriminant validity among the factors was evaluated using the heterotrait–monotrait ratio of correlations (HTMT; Henseler et al., 2015). HTMT analyses were performed in R using the lavaan (version 0.6-19; Rosseel, 2012) and semTools (version 0.5-7; Jorgensen et al., 2025) packages, and all other analyses were conducted in JASP. Results Exploratory factor analysis (maximum likelihood method, promax rotation) for Data 1 indicated goodness-of-fit (RMSEA, CFI) values of 0.096 and 0.884 for two factors, 0.081 and 0.929 for three factors, and 0.060 and 0.967 for four factors, with the four-factor analysis showing the best fit. In the four-factor analysis using Data 1, only one item loaded strongly on a non-hypothesized factor; in Data 2, all items loaded on the expected factors. These results supported the four-factor structure for this study. Confirmatory factor analysis was conducted on the RFS, assuming a four-factor structure (Table 1). Although one item in context sensitivity produced a slightly lower factor loading than the others, the factor loading of the other items was generally higher overall. Based on the goodness-of-fit indices (Data 1: CFI =.938, RMSEA =.068; 90% CI [.057,.078]; Data 2: CFI =.963, RMSEA =.050; 90 %CI [.038, 061]), the model fit was considered acceptable (Hooper et al., 2008). The descriptive statistics of the RFS subscale scores by gender and age are presented in Appendix B. The reliability of all subscales was sufficient for the two datasets (Tables 2 and 3). The repertoire factor of the RFS was significantly and positively correlated with the total of the reappraisal substrategies[1], while the monitoring and modification factors of the RFS were significantly positively correlated with each subscale of the Coping Flexibility Scale-Revised. Lastly, the context sensitivity factor of the RFS was significantly and positively correlated with the meta-recognition of situations. The study obtained partial correlations that omitted the effects of stressful events between reappraisal flexibility and mental health. Each subscale of the RFS was negatively associated with depression, except for context sensitivity, and all subscales were significantly positively correlated with well-being. In Data 1, the HTMT values ranged from 0.617 to 0.834, and in Data 2, from 0.580 to 0.801. All construct pairs in both datasets had HTMT values below the recommended threshold of 0.85, indicating satisfactory discriminant validity and supporting the empirical distinctiveness of the latent constructs. [1] Correlations between repertoire and substrategies ranged from .144 to .655, all of which were significant. Discussion and Conclusion This study aimed to develop the RFS. Confirmatory factor analysis was performed on both datasets, and similar results were obtained. The results indicate the reproducibility of the factor analysis on the developed scale. The results were acceptable in considering the goodness-of-fit indices. The reliability of each subscale was adequate. The study also confirmed the validity of the scale. First, the repertoire factor of the RFS displayed a positive association with the total number of reappraisal substrategies, which reflects the tendency to use various substrategies (Hypothesis 1). Second, the monitoring and modification factors of the RFS exhibited a positive association with each subscale of the Coping Flexibility Scale-Revised, which measures the abilities to discontinue ineffective strategies, to initiate new and different strategies, and to monitor the process and effects of coping (Hypothesis 2). Third, the context sensitivity of the RFS is positively related to the Meta-Recognition of Situations Scale, which measures the adoption of attitudes and actions given a situation and desired outcomes (Hypothesis 3). Finally, each subscale of the RFS was associated with depression and well-being, except for context sensitivity (Hypothesis 4). Apart from a few, the results were as hypothesized. The scale was generally associated with the existing scales as hypothesized, although context sensitivity was relatively weakly associated with mental health. Although context sensitivity is the first stage of the emotion regulation process, and this stage is important in selecting appropriate strategies (Bonanno & Burton, 2013 ), considering the nature of a situation and the purpose of coping may be indirectly related to mental health; instead, the effectivity of the selected strategy may be important. The associations between other subscales of the RFS and mental health were also significant but not high. Thus, the relationship between the RFS and mental health should be further examined in the future. In addition to the correlation predicted in the hypotheses, the study observed correlations between the RFS subscales and the existing measures. RFS subscales measure the components of emotional regulation through reappraisal, may be interrelated, and exhibit similar characteristics. For example, context sensitivity and monitoring are similar in that they undergo an evaluation process. However, these two components are different because context sensitivity focuses on understanding a situation that evokes emotions to select reappraisal strategies, while the evaluation component focuses on assessing whether the implemented reappraisal strategies have been effective (Bonanno & Burton, 2013 ). In addition, although the correlation between repertoire and modification was high, the notion that the two subscales are likely to be strongly related to each other given that repertoire is necessary for changing coping when it is ineffective may be natural. The observed moderate correlations between the subscales and the values of HTMT imply that each subscale measures a different concept. The proposed scale is useful for measuring in addition to other scales because it can measure reappraisal flexibility using a relatively small number of items. Further research should investigate the relationship between reappraisal flexibility and other individual characteristics as well as psychosocial adjustment. To enhance the value of this scale, comparisons with existing reappraisal scales are needed. For example, comparison with a trait reappraisal use scale may reveal that reappraisal flexibility has greater relevance to mental health than simple reappraisal use. Moreover, further studies should elucidate the process of the effective use of reappraisal by, for example, examining which reappraisal substrategies are used in specific stressful situations among individuals with high levels of reappraisal flexibility. Although the present study addressed various stressors and controlled for them, the specific context of each stressor was unclear. Measuring contextual factors such as emotional intensity and controllability in defined stress situations could clarify how these factors alter the relationship between flexibility and mental health. In this study, context sensitivity measured the extent of contextual considerations, such as emotional intensity or type of emotion, and repertoire measured the range of thoughts. However, it did not assess how individuals with high reappraisal flexibility adjust their thoughts in different contexts or the resulting effects. This process warrants investigation through experiments or experience sampling (Chen et al., 2024 ). Conducting surveys on participants from diverse cultures is another important issue concerning emotional regulation. Examination of specific situations and contexts may crucial for clarifying the role of context sensitivity. Identifying effective reappraisal substrategies according to the nature of a situation would be helpful in interventions for the effective use of reappraisal. Declarations Acknowledgments The authors would like to thank Enago (www.enago.jp) for the English language review. Funding This work was supported by JSPS KAKENHI Grant Number JP24K06495. Conflicts of interest The authors declare no conflicts of interest associated with this manuscript. Data availability The data supporting this study's findings are available from the corresponding author upon reasonable request. Autho r contributions All authors contributed to the conception and design of the study. MO was responsible for project administration, funding acquisition, and data collection. MO and RK contributed to conceptualization, methodology, data analysis, and writing of the manuscript. All authors read and approved the final manuscript. Ethics approval and consent to participate This study was conducted in accordance with the principles of the Declaration of Helsinki, and informed consent was obtained from all participants. Approval was granted by the research ethics committee of Tokyo Gakugei University. Consent of Publish All participants provided informed consent for their anonymized data to be used in this study and for the results to be published. References Aldao, A., Nolen-Hoeksema, S., & Schweizer, S. (2010). Emotion-regulation strategies across psychopathology: A meta-analytic review. Clinical Psychology Review , 30 (2), 217-237. https://doi.org/10.1016/j.cpr.2009.11.004 Aldao, A., Sheppes, G., & Gross, J. J. (2015). Emotion regulation flexibility. Cognitive Therapy and Research , 39 , 263-278. https://doi.org/10.1007/s10608-014-9662-4 Awata, S., Bech, P., Koizumi, Y., Seki, T., Kuriyama, S., Hozawa, A., Ohmori, K., Nakaya, N., Matsuoka, H., & Tsuji, I. (2007). Validity and utility of the Japanese version of the WHO-Five Well-Being Index in the context of detecting suicidal ideation in elderly community residents. International Psychogeriatrics, 19 (1), 77–88. https://doi.org/10.1017/S1041610206004212 Birk, J. L., & Bonanno, G. A. (2016). When to throw the switch: The adaptiveness of modifying emotion regulation strategies based on affective and physiological feedback. Emotion , 16 (5), 657- 670. https://doi.org/10.1037/emo0000157 Boemo, T., Nieto, I., Vazquez, C., & Sanchez-Lopez, A. (2022). Relations between emotion regulation strategies and affect in daily life: A systematic review and meta-analysis of studies using ecological momentary assessments. Neuroscience and Biobehavioral Reviews , 139 , 104747. https://doi.org/10.1016/j.neubiorev.2022.104747 Bonanno, G. A., & Burton, C. L. (2013). Regulatory flexibility: An individual differences perspective on coping and emotion regulation. Perspectives on Psychological Science , 8 (6), 591-612. https://doi.org/10.1177/1745691613504116 Bonanno, G. A., Maccallum, F., Malgaroli, M., & Hou, W. K. (2020). The Context Sensitivity Index (CSI): Measuring the ability to identify the presence and absence of stressor context cues. Assessment , 27 (2), 261-273. https://doi.org/10.1177/1073191118820131 Chen, M. S., Bi, K., Han, X., Sun, P., & Bonanno, G. A. (2024). Emotion regulation flexibility and momentary affect in two cultures. Nature Mental Health , 2 (4), 450-459. https://doi.org/10.1038/s44220-024-00215-3 Cheng, C. (2001). Assessing coping flexibility in real-life and laboratory settings: A multimethod approach. Journal of Personality and Social Psychology , 80 (5), 814-833. https://doi.org/10.1037/0022-3514.80.5.814 Cheng, C., Lau, H. P. B., & Chan, M. P. S. (2014). Coping flexibility and psychological adjustment to stressful life changes: A meta-analytic review. Psychological Bulletin , 140 (6), 1582-1607. https://doi.org/10.1037/a0037913. Ford, B. Q., & Troy, A. S. (2019). Reappraisal reconsidered: A closer look at the costs of an acclaimed emotion-regulation strategy. Current Directions in Psychological Science , 28 (2), 195-203. https://doi.org/10.1177/0963721419827526 Furukawa, T. A., Kawakami, N., Saitoh, M., Ono, Y., Nakane, Y., Nakamura, Y., Tachimori, H., Iwata, N., Uda, H., Nakane, H., Watanabe, M., Naganuma, Y., Hata, Y., Kobayashi, M., Miyake, Y., Takeshima, T., & Kikkawa, T. (2008). The performance of the Japanese version of the K6 and K10 in the World Mental Health Survey Japan. International journal of methods in psychiatric research , 17 (3), 152–158. https://doi.org/10.1002/mpr.257 Gross, J. J. (1998). The emerging field of emotion regulation: An integrative review. Review of General Psychology , 2 (3), 271-299. https://doi.org/10.1037/1089-2680.2.3.271 Gross, J. J. (2014). Emotion regulation: Conceptual and empirical foundations. In J. J. Gross (Ed.), Handbook of Emotion Regulation (2nd ed., pp. 3–20). The Guilford Press. Gross, J. J. (2015). Emotion regulation: Current status and future prospects. Psychological Inquiry , 26 (1), 1-26. https://doi.org/10.1080/1047840X.2014.940781 Gross, J. J., Uusberg, H., & Uusberg, A. (2019). Mental illness and well‐being: An affect regulation perspective. World Psychiatry , 18 (2), 130-139. https://doi.org/10.1002/wps.20618 Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43 (1), 115–135. https://doi.org/10.1007/s11747-014-0403-8 Hooper, D, Coughlan, J., & Mullen, M. (2008). Structural equation modelling: Guidelines for determining model fit. Electronic Journal of Business Research Methods , 6 (1), 53-60. https://doi.org/10.21427/D7CF7R Hu, T., Zhang, D., Wang, J., Mistry, R., Ran, G., & Wang, X. (2014). Relation between emotion regulation and mental health: A meta-analysis review. Psychological Reports , 114 (2), 341-362. https://doi.org/10.2466/03.20.PR0.114k22w4 Ishii, Y. (2007). Development of “meta-social skill” measurement. Kyoto University Research Studies in Education , 53, 286-298. JASP Team. (2025). JASP (Version 0.95.1) [Computer software]. https://jasp-stats.org Jorgensen, T. D., Pornprasertmanit, S., Schoemann, A. M., & Rosseel, Y. (2025). semTools: Useful tools for structural equation modeling. R package version 0.5-7. Retrieved from https://CRAN.R-project.org/package=semTools Kalokerinos, E. K., & Koval, P. (2024). Emotion regulation flexibility. In J. J. Gross & B. Q. Ford (Eds.), Handbook of emotion regulation (3rd ed., pp. 265–273). The Guilford Press. Kato, T. (2020). Examination of the coping flexibility hypothesis using the coping flexibility scale-revised. Frontiers in Psychology , 11, 561731. https://doi.org/10.3389/fpsyg.2020.561731 Li, X., Vaessen, T., Lafit, G., van Aubel, E., Hiekkaranta, A. P., Houben, M., Beijer-Klippel, A., de Haan, L., Schirmbeck, F., Reininghaus, U., & Myin-Germeys, I. (2024). Higher emotion regulation flexibility predicts more stable negative emotions and faster affective recovery in early psychosis: An experience sampling study. Psychological Medicine , 54 (9), 2063-2072. ttps://doi.org/10.1017/S0033291724000151 Marciniak, M. A., Homan, S., Zerban, M., Schrade, G., Yuen, K. S. L., Kobylińska, D., Wieser, M. J., Walter, H., Hermans, E. J., Shanahan, L., Kalisch, R., & Kleim, B. (2024). Positive cognitive reappraisal flexibility is associated with lower levels of perceived stress. Behaviour Research and Therapy , 183 , 104653. https://doi.org/10.1016/j.brat.2024.104653 McRae, K., Ciesielski, B., & Gross, J. J. (2012). Unpacking cognitive reappraisal: Goals, tactics, and outcomes. Emotion , 12 (2), 250-255. https://doi.org/10.1037/a0026351 Munakata, T. (1996). Health and disease from the latest behavioral science . Medical Friend.co., Ltd. (In Japanese, translated by the author of this article.) Oikawa, M., Sakakibara, R., Todo, N., & Osada, Y. (2021). Development of a Multifaceted Reappraisal Questionnaire. Bulletin of Tokyo Gakugei University. Division of Comprehensive Educational Science , 72 , 169-176 R Core Team (2025). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/ Rosseel, Y. (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software , 48 (2), 1-36. https://doi.org/10.18637/jss.v048.i02 Sakakibara, R. (2014). Emotion regulation effects of reappraisal and its influences on psychological well-being: Review of research trends and discussions from the perspective of the subtypes of reappraisal. Japanese Journal of Research on Emotions , 22 (1), 40-49. https://doi.org/10.4092/jsre.22.1_40 Sheppes, G. (2020). Transcending the “good & bad” and “here & now” in emotion regulation: Costs and benefits of strategies across regulatory stages. In B. Gawronski (Ed.), Advances in experimental social psychology (1st ed., Vol. 61, pp. 1–81). Academic Press. Sheppes, G., Scheibe, S., Suri, G., & Gross, J. J. (2011). Emotion-regulation choice. Psychological Science , 22 (11), 1391-1396. https://doi.org/10.1177/0956797611418350 Suzuki，M. & Oikawa, M. (2018). Effects of reappraisal on affect change: Focusing on the subtypes of reappraisal. Bulletin of Tokyo Gakugei University . Division of Comprehensive Educational Science , 69, 225-230. Troy, A. S., Shallcross, A. J., & Mauss, I. B. (2013). A person-by-situation approach to emotion regulation: Cognitive reappraisal can either help or hurt, depending on the context. Psychological Science , 24 (12), 2505-2514. https://doi.org/10.1177/0956797613496434 Usukura, H. (2023). A literature review about emotion regulation flexibility. Faculty of Liberal Arts review, Tohoku Gakuin University , 193 , 35-50. (In Japanese.) Uusberg, A., Ford, B., Uusberg, H., & Gross, J. J. (2023). Reappraising reappraisal: An expanded view. Cognition and Emotion , 37 (3), 357-370. https://doi.org/10.1080/02699931.2023.2208340 Webb, T. L., Miles, E., & Sheeran, P. (2012). Dealing with feeling: A meta-analysis of the effectiveness of strategies derived from the process model of emotion regulation. Psychological Bulletin , 138 (4), 775-808. https://doi.org/10.1037/a0027600 Weber, H., Loureiro de Assunção, V., Martin, C., Westmeyer, H., & Geisler, F. C. (2013). Reappraisal inventiveness: The ability to create different reappraisals of critical situations. Cognition and Emotion , 28 (2), 345-360. https://doi.org/10.1080/02699931.2013.832152 Tables Tables 1 to 3 are available in the supplementary files section Supplementary Files Tables.docx Appendix.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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-8214974","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":556274370,"identity":"647ffdfa-c57d-41b1-99c5-f2dc792005b9","order_by":0,"name":"Megumi Oikawa","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBUlEQVRIiWNgGAWjYDACZjYwJQciGBuABITPQ1iLMQlaoEoSG2BaCAJ+drY0qRu/tqVvOMB+8ePMtlo5Pgbmhx8YZO7g1CLZzHZMOrfvdu6GAzzFkhvbjhuzMbAZSzDwPMOpxeAwe9vt3B6glvtvEiQfth1LbGNgMAP65TBBLekGB3iSfwK11LcxsH8joIXt2O2cH7cTDA6wHwM6rCaBjYEHvy1Av6T/zm24bTjzAA+b5YxzBwzbmHmKJRLw+IWf/5ixcc6f2/J8B9gf3+wpq5OXb2/f+OFjD+4QAwPGNhDJYwAkgO5hBlKJPQfwa2H4AyLYHwCJOqjID0JaRsEoGAWjYAQBAFiyWBys/tueAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0009-0003-2430-5431","institution":"Tokyo Gakugei University: Tokyo Gakugei Daigaku","correspondingAuthor":true,"prefix":"","firstName":"Megumi","middleName":"","lastName":"Oikawa","suffix":""},{"id":556274371,"identity":"f8e34803-5c1d-4c71-aef5-9680f0f12abb","order_by":1,"name":"Ryota Kobayashi","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Ryota","middleName":"","lastName":"Kobayashi","suffix":""}],"badges":[],"createdAt":"2025-11-26 16:35:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8214974/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8214974/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":99788977,"identity":"d36a525c-6d5f-43b9-80e8-68a688ee3a66","added_by":"auto","created_at":"2026-01-08 12:48:27","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":7007,"visible":true,"origin":"","legend":"","description":"","filename":"cupsCUPSD2512233.xml","url":"https://assets-eu.researchsquare.com/files/rs-8214974/v1/52566930b73dbcfa01b617d9.xml"},{"id":99788982,"identity":"27f40a68-6049-4f0c-8237-4bf88c4bc55a","added_by":"auto","created_at":"2026-01-08 12:48:27","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":967,"visible":true,"origin":"","legend":"","description":"","filename":"CUPSD2512233160597.go.xml","url":"https://assets-eu.researchsquare.com/files/rs-8214974/v1/92e0d14e58f5942c08c5980f.xml"},{"id":99373628,"identity":"9526f988-7efa-41dd-99b5-e666dbd2fe30","added_by":"auto","created_at":"2026-01-02 07:04:23","extension":"xml","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":884,"visible":true,"origin":"","legend":"","description":"","filename":"CUPSD2512233Import.xml","url":"https://assets-eu.researchsquare.com/files/rs-8214974/v1/8848fe179fdc6f309169491e.xml"},{"id":99373629,"identity":"b54fbecd-89b8-4da6-aeee-d7c9d4af0c7d","added_by":"auto","created_at":"2026-01-02 07:04:23","extension":"xml","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":135979,"visible":true,"origin":"","legend":"","description":"","filename":"CUPSD25122331enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8214974/v1/5f4a06d9aa9a70606691e2c0.xml"},{"id":99373630,"identity":"9387c427-fbe2-462c-a789-3b920967c335","added_by":"auto","created_at":"2026-01-02 07:04:23","extension":"xml","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":135379,"visible":true,"origin":"","legend":"","description":"","filename":"CUPSD25122331structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8214974/v1/8b736813f4d3adf45a52d12d.xml"},{"id":99788859,"identity":"679a64fa-ec05-4dba-9a10-ca5d1e44824f","added_by":"auto","created_at":"2026-01-08 12:48:06","extension":"html","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":146328,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8214974/v1/701952bf112b0470e544db98.html"},{"id":100356339,"identity":"7aa6c2ea-4be0-42d7-b653-c8f0ae2d5c8b","added_by":"auto","created_at":"2026-01-16 07:03:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":504262,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8214974/v1/1d6d5e60-d5da-43cb-aebc-d08496fdea1b.pdf"},{"id":99373624,"identity":"fba45428-f3c2-4c79-8b5a-4d17520e9e9b","added_by":"auto","created_at":"2026-01-02 07:04:23","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":21824,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-8214974/v1/e758dfff50af4ac3c96cf6ea.docx"},{"id":99789360,"identity":"1ed561cc-5c46-47aa-a2fd-681b59d6cfbc","added_by":"auto","created_at":"2026-01-08 12:49:28","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":19375,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-8214974/v1/c3ea011aa5ba178a3874a4ee.docx"}],"financialInterests":"","formattedTitle":"Development of a Reappraisal Flexibility Scale and Examination of Its Reliability and Validity","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEmotion regulation is defined as intentional (but not necessarily conscious) attempts to change the intensity, duration, and frequency/type of a current or an anticipated affect (Gross et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Among the various approaches to emotion regulation research, one of the most typical focuses on emotion regulation strategies. For the process model of emotion regulation, various strategies are also available, such as reappraisal, distraction, and suppression of expression (Gross, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1998\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Previous studies on emotion regulation strategies demonstrate that each strategy exerts a different effect on emotional experience and mental health (e.g., Aldao et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Webb et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eReappraisal is an effective emotion regulation strategy for reducing negative emotions and facilitating mental health. Reappraisal is defined as the process of reinterpreting emotions, emotion-evoking situations, or causes, and of altering the goals of a situation (Gross, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Uusberg et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). A meta-analysis on experimental studies reported that reappraisal could significantly decrease negative emotions compared with conditions that employed other emotion regulation strategies or control conditions (Webb et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Similar results were also confirmed in a meta-analysis on studies that employed ecological momentary assessments (Boemo et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In addition, research using questionnaires demonstrated that people with a high reappraisal tendency exhibit positive mental health (Hu et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRecent studies have noted that reappraisal features substrategies (Sakakibara, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), and McRae et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) proposed eight distinctions. For example, the explicitly positive substrategy refers to a reinterpretation that actively identifies the positive aspects of a stressful event, while the distancing substrategy denotes a reinterpretation that views a stressful event from a distant perspective. Importantly, each substrategy exerts different effects on emotional experience and mental health (e.g., Webb et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Suzuki and Oikawa (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) experimentally examined and reported that the explicitly positive and distancing strategies decrease negative emotions. Out of the two, however, only the explicitly positive strategy increases positive emotion.\u003c/p\u003e \u003cp\u003eA notable limitation of reappraisal research is its narrow focus on the implementation or frequency of reappraisal strategies and its lack of consideration for flexibility in using these strategies. Previous studies implicitly assume that reappraisal attempts are successful and lead to desirable outcomes (e.g., downregulation of negative emotions) for most people. Contrary to this assumption, recent research indicates that attempts at reappraisal are not always successful (Ford \u0026amp; Troy, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In general, after a serious failure, expressing an explicitly positive reinterpretation immediately, such as \u0026ldquo;this will lead to my growth,\u0026rdquo; would be difficult, and even if it came to mind, believing it will be difficult. However, from the perspective of the reappraisal substrategy, distancing substrategy may be possible in the same scenario, although the explicitly positive substrategy is difficult. Moreover, if one reinterpretation is not convincing, then some people end reappraisal, while others attempt to give another reinterpretation. Thus, considering not only whether to perform reappraisal but also whether to use reappraisal substrategies flexibly according to a situation may be necessary.\u003c/p\u003e \u003cp\u003eThe current study points out the necessity of adding the perspective of flexibility to reappraisal research. In this regard, research on emotional regulation flexibility (ERF), which has attracted scholarly attention as an important aspect of emotion regulation, is suggestive. ERF refers to the process of changing emotion regulation according to a situation and purpose (Aldao et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Bonanno \u0026amp; Burton, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Cheng et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Bonanno and Burton (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) proposed one of the typical models of ERF, which can be mainly distinguished into three sequential components, namely, context sensitivity, repertoire, and feedback (Kalokerinos \u0026amp; Koval, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Usukura, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eContext sensitivity is defined as follows:\u003c/p\u003e \u003cp\u003ethe ability to perceive impinging demands and opportunities from the situational context as they emerge over and above the normative background of ongoing regulatory concerns and processes and to determine the most appropriate regulatory strategy in response to those demands or opportunities. (Bonanno \u0026amp; Burton, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eContext sensitivity is the first step in ERF, and an accurate perception of a situation will lead to the selection of an emotion regulation strategy that is appropriate to the situation in the next step (i.e., repertorire). At this stage, the situation is appraised in terms of its controllability, importance, urgency, and the intensity of emotions it evokes (Bonanno et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Cheng, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). For example, distraction is more likely to be implemented than reappraisal in situations evaluated as evoking high-intensity negative emotions (Sheppes, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sheppes et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe repertoire component refers to \u0026ldquo;the ability to utilize a wide range of regulatory strategies that might accommodate divergent contextual demands and opportunities\u0026rdquo; (Bonanno \u0026amp; Burton, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Even if a situation is properly assessed, an appropriate strategy will not be implemented unless it is in the repertoire. An experience sampling study found that the greater the repertoire of emotion regulation, the lower the levels of depression and anxiety (Chen et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe final step in the ERF model is the feedback component, which is defined as \u0026ldquo;the ability to monitor and use feedback about the efficacy of a chosen regulatory strategy over time so as to adjust or correct behavior when needed.\u0026rdquo; As implied by the definition, two important aspects are involved in feedback, namely, monitoring and modifying the implementation of emotion regulation. A flexible regulation of emotions requires monitoring whether emotions are changing according to the desired direction due to the use of specific strategies. If this attempt is unsuccessful, then contextual information is reevaluated, and the strategy is adjusted or switched. The feedback component supports the monitoring of an ongoing adjustment process and adjusting and switching strategies. Individuals with better performance in switching from unsuccessful strategies to other strategies tend to exhibit high levels of well-being (Birk \u0026amp; Bonanno, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBased on this discussion, the current study aims to incorporate the ERF perspective into reappraisal research and to examine reappraisal flexibility. Since ERF research typically focuses on variations or repertoires among strategies (e.g., Li et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) or does not focus on any specific strategy (e.g., Kato, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), research on the flexible implementation of reappraisal remains limited. In this context, Weber et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and Marciniak et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) are among the few studies examining flexibility in reappraisal. In Weber et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), participants were presented with vignettes depicting anger-evoking scenes and asked to write down as many reappraisals as possible. The number of descriptions, termed \u0026ldquo;reappraisal inventiveness,\u0026rdquo; was found to relate to divergent thinking task performance. Marciniak et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) used the experience sampling method, asking participants to reinterpret a recent stressful situation. Individuals who adapted reappraisal use to the emotional intensity of situations showed decreased stress scores from baseline to follow-up. Although previous studies have examined reappraisal flexibility, they addressed only specific aspects of flexibility.\u003c/p\u003e \u003cp\u003eTherefore, we aim to formulate a scale for measuring reappraisal flexibility (i.e., reappraisal flexibility scale [RFS]) and to examine its reliability and validity. We define reappraisal flexibility as selecting and implementing appropriate reappraisal substrategies based on contextual information and monitoring and adjusting such processes as necessary. Based on the ERF model of Bonanno and Burton (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), the RFS was created assuming a four-factor structure, namely, context sensitivity, repertoire, monitoring, and modification.\u003c/p\u003e \u003cp\u003eContext sensitivity refers to the ability to perceive a situation and goal and to select reappraisal substrategies given this contextual information. Careful judgment is required to use reappraisal effectively in situations that evoke high-intensity negative emotions (e.g., Sheppes et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) or situations with controllable stressors (e.g., Troy et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Individuals that possess this ability would be capable of noticing such contextual information and selecting appropriate substrategies. Repertoire refers to the ability to produce various interpretations of emotions and their causes. Individuals with this ability would be capable of presenting different interpretations such as \u0026ldquo;there is something to learn from the mistake,\u0026rdquo; \u0026ldquo;it was not such a bad failure,\u0026rdquo; or \u0026ldquo;I accept that I made a mistake\u0026rdquo; in failure situations. Monitoring and modification are the two components that distinguish feedback in the ERF model. Monitoring refers to the ability to monitor whether emotions have changed toward the desired direction, while modification refers to the ability to explore different reappraisal substrategies while considering the evaluation. Individuals with this ability would be capable of constructing new interpretations instead of retaining old ineffective ones.\u003c/p\u003e \u003cp\u003eTo examine the construct validity of the scale, we examine its relationship with the following scales. First, the Multifaceted Reappraisal Questionnaire (Oikawa et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) is a scale based on the eight categories of reappraisal presented by McRae et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and measures the tendency to use various reappraisal substrategies. We expected a positive association with this measure (Hypothesis 1) because the repertoire factor of the RFS is assumed to reflect the ability to construct various reinterpretations. Second, the Coping Flexibility Scale-Revised (Kato, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) measures overall coping flexibility and consists of three subscales, namely, abandonment, recoping, and meta-coping. Abandonment refers to the ability to discontinue ineffective strategies, while recoping reflects the ability to initiate new and different strategies. Meta-coping refers to the ability to monitor the process and effects of coping and to determine whether to continue, abandon, or change strategies. Based on these definitions, the current study predicts that these three subscales will be positively associated with the monitoring and modification factors of the RFS (Hypothesis 2). Third, the Meta-Social Skill Measurement measures the skills to metarecognize one\u0026rsquo;s skills and interpersonal situation, and chooses an appropriate skill (Ishii, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). In this measurement, a scale about the meta-recognition of situations focuses on interpersonal situations but includes aspects such as understanding situations and acting with a consideration of desired outcomes. The context sensitivity of RFS is expected to be positively related to this measure (Hypothesis 3), because it reflects the consideration of context and purpose when using reappraisal. Finally, given that overall flexibility in emotion regulation exerts positive effects on mental health (e.g., Birk \u0026amp; Bonanno, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Chen et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), we predict that RFS will be significantly associated with depressive tendencies and well-being (Hypothesis 4).\u003c/p\u003e"},{"header":"Method","content":"\u003ch2\u003e\u003cstrong\u003eParticipants and Procedure\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eIn this study, two surveys were conducted separately, and two sets of data were obtained (Data 1 and 2) to verify the stability of factor analysis. All surveys were conducted in Japanese.\u003c/p\u003e\n\u003cp\u003eThe participants belong to the general adults aged 18–60 years in Japan (Data 1: \u003cem\u003eN\u003c/em\u003e = 300 [men: 140, women: 155, nonbinary: 2, unwilling to answer: 3, age: 21–60], mean age = 41.54 years, \u003cem\u003eSD\u003c/em\u003e = 8.66; Data 2: \u003cem\u003eN\u003c/em\u003e = 300 [men: 115, women: 181, nonbinary: 2, unwilling to answer: 2,\u0026nbsp;age: 18–60], mean age = 41.49 years, \u003cem\u003eSD\u003c/em\u003e = 9.53). The participants were recruited through CrowdWorks, a crowdsourcing company, and data were collected via an online survey. The questionnaire was designed using Qualtrics, an online survey tool, and the participants were asked to complete the questionnaire. The items were presented randomly on each scale. This study was conducted in accordance with the principles of the Declaration of Helsinki. Informed consent was obtained from all participants, and this study was approved by the research ethics committee of [blinded for review].\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eMeasures\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eReappraisal\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eflexibility.\u0026nbsp;\u003c/strong\u003eBased on the theory of regulatory flexibility (Bonanno \u0026amp; Burton, 2013; Usukura, 2023), this study operationalized the concept and drafted items referencing Kato (2020). Three graduate students majoring in clinical psychology reviewed the items for conceptual alignment, clarity, and necessary revisions. We\u0026nbsp;prepared five context sensitivity items, four repertoire items, four monitoring items, and four modification items for a total of 17 items in the RFS (Appendix\u0026nbsp;A). The items were rated using a five-point scale (1 = not applicable, 5 = applicable).\u003c/p\u003e\n\u003cp\u003eThe following scales were measured to examine the validity of the proposed scale.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReappraisal\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003esubstrategies.\u0026nbsp;\u003c/strong\u003eWe used the 32-items of the Multifaceted Reappraisal Questionnaire (Oikawa et al., 2021). The scores range from 32 to 160. The total high scores indicate the use of various reappraisal substrategies. Items were rated using a five-point scale (1 = not applicable, 5 = applicable).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCoping\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eflexibility.\u0026nbsp;\u003c/strong\u003eThe study employed the 12-item Coping Flexibility Scale-Revised (Kato, 2020). This scale features three subscales (i.e., abandonment, recoping, and meta-coping), and each consists of four items. This scale measures overall coping flexibility. Items were rated using a four-point scale (0 = not applicable, 3 = very applicable).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeta-\u003c/strong\u003e\u003cstrong\u003erecognition\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003esituations.\u0026nbsp;\u003c/strong\u003eWe used 10 items of the Meta-Recognition of Situations in the Meta-Social Skill Measurement (Ishii, 2007). This measure includes aspects such as adopting attitudes and actions with consideration of a situation and desired outcomes. Items were rated using a four-point scale (1 = not at all applicable, 4 = very applicable).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepression\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eWe used the six-item Kessler-6 (Furukawa et al., 2008) to measure depression. Items were rated using a five-point scale (0 = none of the time, 4 = all of the time)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWell-\u003c/strong\u003e\u003cstrong\u003ebeing.\u0026nbsp;\u003c/strong\u003eWe used the five-item WHO Five Well-Being Index (Awata et al., 2007) to measure well-being. Items were rated using a six-point scale (0 = no time, 5 = all of the time).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStressful\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eevents.\u0026nbsp;\u003c/strong\u003eRecently experienced stressful events may also influence the association between reappraisal flexibility and mental health; therefore, we used a 30-item scale to measure daily hassles (Munakata, 1996). Items were rated using a three-point scale (0 = not so, 2 = very much so).\u003c/p\u003e\n\u003cp\u003eFor Data 1, the researchers measured reappraisal flexibility, reappraisal substrategies, coping flexibility, and meta-recognition of situations. For Data 2, reappraisal flexibility, depression, well-being, and stressful events were measured.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eData analysis\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eAnalyses were conducted using JASP (JASP Team, 2025) and R (version 4.5.1; R Core Team, 2025). Although we hypothesized a four-factor model, we first confirmed the appropriateness of the number of factors through an exploratory factor analysis of Data 1, and then conducted a confirmatory factor analysis assuming a four-factor structure. Internal consistency and correlations with relevant existing scales were assessed for each dataset. For mental health variables (depression and well-being), partial correlations controlling for stressful events were examined. Discriminant validity among the factors was evaluated using the heterotrait–monotrait ratio of correlations (HTMT; Henseler et al., 2015). HTMT analyses were performed in R using the lavaan (version 0.6-19; Rosseel, 2012) and semTools (version 0.5-7; Jorgensen et al., 2025) packages, and all other analyses were conducted in JASP.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eExploratory factor analysis (maximum likelihood method, promax rotation) for Data 1 indicated goodness-of-fit (RMSEA, CFI) values of 0.096 and 0.884 for two factors, 0.081 and 0.929 for three factors, and 0.060 and 0.967 for four factors, with the four-factor analysis showing the best fit. In the four-factor analysis using Data 1, only one item loaded strongly on a non-hypothesized factor; in Data 2, all items loaded on the expected factors. These results supported the four-factor structure for this study.\u0026nbsp;Confirmatory factor analysis was conducted on the RFS, assuming a four-factor structure (Table 1). Although one item in context sensitivity produced a slightly lower factor loading than the others, the factor loading of the other items was generally higher overall. Based on the goodness-of-fit indices (Data 1: CFI =.938, RMSEA =.068; 90% CI [.057,.078]; Data 2: CFI =.963, RMSEA =.050; 90 %CI [.038, 061]), the model fit was considered acceptable (Hooper et al., 2008). The descriptive statistics of the RFS subscale scores by gender and age are presented in Appendix\u0026nbsp;B.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe reliability of all subscales was sufficient for the two datasets (Tables 2 and 3). The repertoire factor of the RFS was significantly and positively correlated with the total of the reappraisal substrategies[1], while the monitoring and modification factors of the RFS were significantly positively correlated with each subscale of the Coping Flexibility Scale-Revised. Lastly, the context sensitivity factor of the RFS was significantly and positively correlated with the meta-recognition of situations.\u003c/p\u003e\n\u003cp\u003eThe study obtained partial correlations that omitted the effects of stressful events between reappraisal flexibility and mental health. Each subscale of the RFS was negatively associated with depression, except for context sensitivity, and all subscales were significantly positively correlated with well-being.\u003c/p\u003e\n\u003cp\u003eIn Data 1, the HTMT values ranged from 0.617 to 0.834, and in Data 2, from 0.580 to 0.801. All construct pairs in both datasets had HTMT values below the recommended threshold of 0.85, indicating satisfactory discriminant validity and supporting the empirical distinctiveness of the latent constructs.\u003c/p\u003e\n\u003cp\u003e[1] Correlations between repertoire and substrategies ranged from .144 to .655, all of which were significant.\u003c/p\u003e"},{"header":"Discussion and Conclusion","content":"\u003cp\u003eThis study aimed to develop the RFS. Confirmatory factor analysis was performed on both datasets, and similar results were obtained. The results indicate the reproducibility of the factor analysis on the developed scale. The results were acceptable in considering the goodness-of-fit indices. The reliability of each subscale was adequate.\u003c/p\u003e \u003cp\u003eThe study also confirmed the validity of the scale. First, the repertoire factor of the RFS displayed a positive association with the total number of reappraisal substrategies, which reflects the tendency to use various substrategies (Hypothesis 1). Second, the monitoring and modification factors of the RFS exhibited a positive association with each subscale of the Coping Flexibility Scale-Revised, which measures the abilities to discontinue ineffective strategies, to initiate new and different strategies, and to monitor the process and effects of coping (Hypothesis 2). Third, the context sensitivity of the RFS is positively related to the Meta-Recognition of Situations Scale, which measures the adoption of attitudes and actions given a situation and desired outcomes (Hypothesis 3). Finally, each subscale of the RFS was associated with depression and well-being, except for context sensitivity (Hypothesis 4). Apart from a few, the results were as hypothesized.\u003c/p\u003e \u003cp\u003eThe scale was generally associated with the existing scales as hypothesized, although context sensitivity was relatively weakly associated with mental health. Although context sensitivity is the first stage of the emotion regulation process, and this stage is important in selecting appropriate strategies (Bonanno \u0026amp; Burton, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), considering the nature of a situation and the purpose of coping may be indirectly related to mental health; instead, the effectivity of the selected strategy may be important. The associations between other subscales of the RFS and mental health were also significant but not high. Thus, the relationship between the RFS and mental health should be further examined in the future.\u003c/p\u003e \u003cp\u003eIn addition to the correlation predicted in the hypotheses, the study observed correlations between the RFS subscales and the existing measures. RFS subscales measure the components of emotional regulation through reappraisal, may be interrelated, and exhibit similar characteristics. For example, context sensitivity and monitoring are similar in that they undergo an evaluation process. However, these two components are different because context sensitivity focuses on understanding a situation that evokes emotions to select reappraisal strategies, while the evaluation component focuses on assessing whether the implemented reappraisal strategies have been effective (Bonanno \u0026amp; Burton, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In addition, although the correlation between repertoire and modification was high, the notion that the two subscales are likely to be strongly related to each other given that repertoire is necessary for changing coping when it is ineffective may be natural. The observed moderate correlations between the subscales and the values of HTMT imply that each subscale measures a different concept.\u003c/p\u003e \u003cp\u003eThe proposed scale is useful for measuring in addition to other scales because it can measure reappraisal flexibility using a relatively small number of items. Further research should investigate the relationship between reappraisal flexibility and other individual characteristics as well as psychosocial adjustment. To enhance the value of this scale, comparisons with existing reappraisal scales are needed. For example, comparison with a trait reappraisal use scale may reveal that reappraisal flexibility has greater relevance to mental health than simple reappraisal use. Moreover, further studies should elucidate the process of the effective use of reappraisal by, for example, examining which reappraisal substrategies are used in specific stressful situations among individuals with high levels of reappraisal flexibility.\u003c/p\u003e \u003cp\u003eAlthough the present study addressed various stressors and controlled for them, the specific context of each stressor was unclear. Measuring contextual factors such as emotional intensity and controllability in defined stress situations could clarify how these factors alter the relationship between flexibility and mental health.\u003c/p\u003e \u003cp\u003eIn this study, context sensitivity measured the extent of contextual considerations, such as emotional intensity or type of emotion, and repertoire measured the range of thoughts. However, it did not assess how individuals with high reappraisal flexibility adjust their thoughts in different contexts or the resulting effects. This process warrants investigation through experiments or experience sampling (Chen et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eConducting surveys on participants from diverse cultures is another important issue concerning emotional regulation. Examination of specific situations and contexts may crucial for clarifying the role of context sensitivity. Identifying effective reappraisal substrategies according to the nature of a situation would be helpful in interventions for the effective use of reappraisal.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank Enago (www.enago.jp) for the English language review.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by JSPS KAKENHI Grant Number JP24K06495.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest associated with this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData\u0026nbsp;availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data supporting this study\u0026apos;s findings are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAutho\u003c/strong\u003e\u003cstrong\u003er contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the conception and design of the study. MO was responsible for project administration, funding acquisition, and data collection. MO and RK contributed to conceptualization, methodology, data analysis, and writing of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eapproval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the principles of the Declaration of Helsinki, and informed consent was obtained from all participants. Approval was granted by\u0026nbsp;the research ethics committee of Tokyo Gakugei University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent of Publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants provided informed consent for their anonymized data to be used in this study and for the results to be published.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAldao, A., Nolen-Hoeksema, S., \u0026amp; Schweizer, S. (2010). Emotion-regulation strategies across psychopathology: A meta-analytic review. \u003cem\u003eClinical Psychology Review\u003c/em\u003e, \u003cem\u003e30\u003c/em\u003e(2), 217-237. https://doi.org/10.1016/j.cpr.2009.11.004\u003c/li\u003e\n\u003cli\u003eAldao, A., Sheppes, G., \u0026amp; Gross, J. J. (2015). Emotion regulation flexibility. \u003cem\u003eCognitive Therapy and Research\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e, 263-278. https://doi.org/10.1007/s10608-014-9662-4\u003c/li\u003e\n\u003cli\u003eAwata, S., Bech, P., Koizumi, Y., Seki, T., Kuriyama, S., Hozawa, A., Ohmori, K., Nakaya, N., Matsuoka, H., \u0026amp; Tsuji, I. (2007). Validity and utility of the Japanese version of the WHO-Five Well-Being Index in the context of detecting suicidal ideation in elderly community residents. \u003cem\u003eInternational Psychogeriatrics,\u003c/em\u003e \u003cem\u003e19\u003c/em\u003e(1), 77\u0026ndash;88. https://doi.org/10.1017/S1041610206004212\u003c/li\u003e\n\u003cli\u003eBirk, J. L., \u0026amp; Bonanno, G. A. (2016). When to throw the switch: The adaptiveness of modifying emotion regulation strategies based on affective and physiological feedback. \u003cem\u003eEmotion\u003c/em\u003e, \u003cem\u003e16\u003c/em\u003e(5), 657- 670. https://doi.org/10.1037/emo0000157\u003c/li\u003e\n\u003cli\u003eBoemo, T., Nieto, I., Vazquez, C., \u0026amp; Sanchez-Lopez, A. (2022). Relations between emotion regulation strategies and affect in daily life: A systematic review and meta-analysis of studies using ecological momentary assessments. \u003cem\u003eNeuroscience and Biobehavioral Reviews\u003c/em\u003e, \u003cem\u003e139\u003c/em\u003e, 104747. https://doi.org/10.1016/j.neubiorev.2022.104747\u003c/li\u003e\n\u003cli\u003eBonanno, G. A., \u0026amp; Burton, C. L. (2013). Regulatory flexibility: An individual differences perspective on coping and emotion regulation.\u003cem\u003e \u003c/em\u003e\u003cem\u003ePerspectives on Psychological Science\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e(6), 591-612. https://doi.org/10.1177/1745691613504116\u003c/li\u003e\n\u003cli\u003eBonanno, G. A., Maccallum, F., Malgaroli, M., \u0026amp; Hou, W. K. (2020). The Context Sensitivity Index (CSI): Measuring the ability to identify the presence and absence of stressor context cues. \u003cem\u003eAssessment\u003c/em\u003e, \u003cem\u003e27\u003c/em\u003e(2), 261-273. https://doi.org/10.1177/1073191118820131\u003c/li\u003e\n\u003cli\u003eChen, M. S., Bi, K., Han, X., Sun, P., \u0026amp; Bonanno, G. A. (2024). Emotion regulation flexibility and momentary affect in two cultures. \u003cem\u003eNature Mental Health\u003c/em\u003e, \u003cem\u003e2\u003c/em\u003e(4), 450-459. https://doi.org/10.1038/s44220-024-00215-3\u003c/li\u003e\n\u003cli\u003eCheng, C. (2001). Assessing coping flexibility in real-life and laboratory settings: A multimethod approach. \u003cem\u003eJournal of Personality and Social Psychology\u003c/em\u003e, \u003cem\u003e80\u003c/em\u003e(5), 814-833. https://doi.org/10.1037/0022-3514.80.5.814\u003c/li\u003e\n\u003cli\u003eCheng, C., Lau, H. P. B., \u0026amp; Chan, M. P. S. (2014). Coping flexibility and psychological adjustment to stressful life changes: A meta-analytic review. \u003cem\u003ePsychological Bulletin\u003c/em\u003e, \u003cem\u003e140\u003c/em\u003e(6), 1582-1607. https://doi.org/10.1037/a0037913.\u003c/li\u003e\n\u003cli\u003eFord, B. Q., \u0026amp; Troy, A. S. (2019). Reappraisal reconsidered: A closer look at the costs of an acclaimed emotion-regulation strategy. \u003cem\u003eCurrent Directions in Psychological Science\u003c/em\u003e, \u003cem\u003e28\u003c/em\u003e(2), 195-203. https://doi.org/10.1177/0963721419827526\u003c/li\u003e\n\u003cli\u003eFurukawa, T. A., Kawakami, N., Saitoh, M., Ono, Y., Nakane, Y., Nakamura, Y., Tachimori, H., Iwata, N., Uda, H., Nakane, H., Watanabe, M., Naganuma, Y., Hata, Y., Kobayashi, M., Miyake, Y., Takeshima, T., \u0026amp; Kikkawa, T. (2008). The performance of the Japanese version of the K6 and K10 in the World Mental Health Survey Japan. \u003cem\u003eInternational journal of methods in psychiatric research\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(3), 152\u0026ndash;158. https://doi.org/10.1002/mpr.257\u003c/li\u003e\n\u003cli\u003eGross, J. J. (1998). The emerging field of emotion regulation: An integrative review. \u003cem\u003eReview of General Psychology\u003c/em\u003e, \u003cem\u003e2\u003c/em\u003e(3), 271-299. https://doi.org/10.1037/1089-2680.2.3.271\u003c/li\u003e\n\u003cli\u003eGross, J. J. (2014). Emotion regulation: Conceptual and empirical foundations. In J. J. Gross (Ed.), \u003cem\u003eHandbook of Emotion Regulation\u003c/em\u003e (2nd ed., pp. 3\u0026ndash;20). The Guilford Press.\u003c/li\u003e\n\u003cli\u003eGross, J. J. (2015). Emotion regulation: Current status and future prospects.\u003cem\u003e \u003c/em\u003e\u003cem\u003ePsychological Inquiry\u003c/em\u003e, \u003cem\u003e26\u003c/em\u003e(1), 1-26. https://doi.org/10.1080/1047840X.2014.940781\u003c/li\u003e\n\u003cli\u003eGross, J. J., Uusberg, H., \u0026amp; Uusberg, A. (2019). Mental illness and well‐being: An affect regulation perspective. \u003cem\u003eWorld Psychiatry\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e(2), 130-139. https://doi.org/10.1002/wps.20618\u003c/li\u003e\n\u003cli\u003eHenseler, J., Ringle, C. M., \u0026amp; Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. \u003cem\u003eJournal of the Academy of Marketing Science, 43\u003c/em\u003e(1), 115\u0026ndash;135. https://doi.org/10.1007/s11747-014-0403-8\u003c/li\u003e\n\u003cli\u003eHooper, D, Coughlan, J., \u0026amp; Mullen, M. (2008). Structural equation modelling: Guidelines for determining model fit. \u003cem\u003eElectronic Journal of Business Research Methods\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e(1), 53-60. https://doi.org/10.21427/D7CF7R\u003c/li\u003e\n\u003cli\u003eHu, T., Zhang, D., Wang, J., Mistry, R., Ran, G., \u0026amp; Wang, X. (2014). Relation between emotion regulation and mental health: A meta-analysis review. \u003cem\u003ePsychological Reports\u003c/em\u003e, \u003cem\u003e114\u003c/em\u003e(2), 341-362. https://doi.org/10.2466/03.20.PR0.114k22w4\u003c/li\u003e\n\u003cli\u003eIshii, Y. (2007). Development of \u0026ldquo;meta-social skill\u0026rdquo; measurement. \u003cem\u003eKyoto University Research Studies in Education\u003c/em\u003e, 53, 286-298.\u003c/li\u003e\n\u003cli\u003eJASP Team. (2025). \u003cem\u003eJASP (Version 0.95.1)\u003c/em\u003e [Computer software]. https://jasp-stats.org\u003c/li\u003e\n\u003cli\u003eJorgensen, T. D., Pornprasertmanit, S., Schoemann, A. M., \u0026amp; Rosseel, Y. (2025). semTools: Useful tools for structural equation modeling. R package version 0.5-7. Retrieved from https://CRAN.R-project.org/package=semTools\u003c/li\u003e\n\u003cli\u003eKalokerinos, E. K., \u0026amp; Koval, P. (2024). Emotion regulation flexibility. In J. J. Gross \u0026amp; B. Q. Ford (Eds.), \u003cem\u003eHandbook of emotion regulation\u003c/em\u003e (3rd ed., pp. 265\u0026ndash;273). The Guilford Press.\u003c/li\u003e\n\u003cli\u003eKato, T. (2020). Examination of the coping flexibility hypothesis using the coping flexibility scale-revised. \u003cem\u003eFrontiers in Psychology\u003c/em\u003e, 11, 561731. https://doi.org/10.3389/fpsyg.2020.561731\u003c/li\u003e\n\u003cli\u003eLi, X., Vaessen, T., Lafit, G., van Aubel, E., Hiekkaranta, A. P., Houben, M., Beijer-Klippel, A., de Haan, L., Schirmbeck, F., Reininghaus, U., \u0026amp; Myin-Germeys, I. (2024). Higher emotion regulation flexibility predicts more stable negative emotions and faster affective recovery in early psychosis: An experience sampling study. \u003cem\u003ePsychological Medicine\u003c/em\u003e, \u003cem\u003e54\u003c/em\u003e(9), 2063-2072. ttps://doi.org/10.1017/S0033291724000151\u003c/li\u003e\n\u003cli\u003eMarciniak, M. A., Homan, S., Zerban, M., Schrade, G., Yuen, K. S. L., Kobylińska, D., Wieser, M. J., Walter, H., Hermans, E. J., Shanahan, L., Kalisch, R., \u0026amp; Kleim, B. (2024). Positive cognitive reappraisal flexibility is associated with lower levels of perceived stress. \u003cem\u003eBehaviour Research and Therapy\u003c/em\u003e, \u003cem\u003e183\u003c/em\u003e, 104653. https://doi.org/10.1016/j.brat.2024.104653\u003c/li\u003e\n\u003cli\u003eMcRae, K., Ciesielski, B., \u0026amp; Gross, J. J. (2012). Unpacking cognitive reappraisal: Goals, tactics, and outcomes. \u003cem\u003eEmotion\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(2), 250-255. https://doi.org/10.1037/a0026351\u003c/li\u003e\n\u003cli\u003eMunakata, T. (1996). \u003cem\u003eHealth and disease from the latest behavioral science\u003c/em\u003e. Medical Friend.co., Ltd. (In Japanese, translated by the author of this article.)\u003c/li\u003e\n\u003cli\u003eOikawa, M., Sakakibara, R., Todo, N., \u0026amp; Osada, Y. (2021). Development of a Multifaceted Reappraisal Questionnaire. \u003cem\u003eBulletin of Tokyo Gakugei University. Division of Comprehensive Educational Science\u003c/em\u003e, \u003cem\u003e72\u003c/em\u003e, 169-176\u003c/li\u003e\n\u003cli\u003eR Core Team (2025). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/\u003c/li\u003e\n\u003cli\u003eRosseel, Y. (2012). lavaan: An R Package for Structural Equation Modeling. \u003cem\u003eJournal of Statistical Software\u003c/em\u003e, \u003cem\u003e48\u003c/em\u003e(2), 1-36. https://doi.org/10.18637/jss.v048.i02\u003c/li\u003e\n\u003cli\u003eSakakibara, R. (2014). Emotion regulation effects of reappraisal and its influences on psychological well-being: Review of research trends and discussions from the perspective of the subtypes of reappraisal. \u003cem\u003eJapanese Journal of Research on Emotions\u003c/em\u003e, \u003cem\u003e22\u003c/em\u003e(1), 40-49. https://doi.org/10.4092/jsre.22.1_40\u003c/li\u003e\n\u003cli\u003eSheppes, G. (2020). Transcending the \u0026ldquo;good \u0026amp; bad\u0026rdquo; and \u0026ldquo;here \u0026amp; now\u0026rdquo; in emotion regulation: Costs and benefits of strategies across regulatory stages. In B. Gawronski (Ed.), \u003cem\u003eAdvances in experimental social psychology\u003c/em\u003e (1st ed., Vol. 61, pp. 1\u0026ndash;81). Academic Press.\u003c/li\u003e\n\u003cli\u003eSheppes, G., Scheibe, S., Suri, G., \u0026amp; Gross, J. J. (2011). Emotion-regulation choice. \u003cem\u003ePsychological Science\u003c/em\u003e, \u003cem\u003e22\u003c/em\u003e(11), 1391-1396. https://doi.org/10.1177/0956797611418350\u003c/li\u003e\n\u003cli\u003eSuzuki，M. \u0026amp; Oikawa, M. (2018). Effects of reappraisal on affect change: Focusing on the subtypes of reappraisal. Bulletin of Tokyo Gakugei University\u003cem\u003e. Division of Comprehensive Educational Science\u003c/em\u003e, 69, 225-230. \u003c/li\u003e\n\u003cli\u003eTroy, A. S., Shallcross, A. J., \u0026amp; Mauss, I. B. (2013). A person-by-situation approach to emotion regulation: Cognitive reappraisal can either help or hurt, depending on the context. \u003cem\u003ePsychological Science\u003c/em\u003e, \u003cem\u003e24\u003c/em\u003e(12), 2505-2514. https://doi.org/10.1177/0956797613496434\u003c/li\u003e\n\u003cli\u003eUsukura, H. (2023). A literature review about emotion regulation flexibility. \u003cem\u003eFaculty of Liberal Arts review, Tohoku Gakuin University\u003c/em\u003e, \u003cem\u003e193\u003c/em\u003e, 35-50. (In Japanese.)\u003c/li\u003e\n\u003cli\u003eUusberg, A., Ford, B., Uusberg, H., \u0026amp; Gross, J. J. (2023). Reappraising reappraisal: An expanded view. \u003cem\u003eCognition and Emotion\u003c/em\u003e, \u003cem\u003e37\u003c/em\u003e(3), 357-370. https://doi.org/10.1080/02699931.2023.2208340\u003c/li\u003e\n\u003cli\u003eWebb, T. L., Miles, E., \u0026amp; Sheeran, P. (2012). Dealing with feeling: A meta-analysis of the effectiveness of strategies derived from the process model of emotion regulation. \u003cem\u003ePsychological Bulletin\u003c/em\u003e, \u003cem\u003e138\u003c/em\u003e(4), 775-808. https://doi.org/10.1037/a0027600\u003c/li\u003e\n\u003cli\u003eWeber, H., Loureiro de Assun\u0026ccedil;\u0026atilde;o, V., Martin, C., Westmeyer, H., \u0026amp; Geisler, F. C. (2013). Reappraisal inventiveness: The ability to create different reappraisals of critical situations. \u003cem\u003eCognition and Emotion\u003c/em\u003e, \u003cem\u003e28\u003c/em\u003e(2), 345-360. https://doi.org/10.1080/02699931.2013.832152\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 3 are available in the supplementary files section\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":true,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"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":"reappraisal flexibility, reliability, validity, emotion regulation","lastPublishedDoi":"10.21203/rs.3.rs-8214974/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8214974/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eReappraisal is widely recognized as an adaptive emotion regulation strategy; however, recent research suggests that it comprises several substrategies, whose effectiveness can vary across different stress-related contexts. These findings suggest that the ability to use reappraisal flexibly in response to stressful situations may play a crucial role in promoting psychosocial adjustment. This study aimed to develop a reappraisal flexibility scale. Based on previous research on emotion regulation models, the present study developed a scale for measuring four aspects of reappraisal flexibility scale (RFS), namely, context sensitivity, repertoire, monitoring, and modification. Two online surveys were conducted, each collecting data from 300 adults. For each set of data, confirmatory factor analysis confirmed the assumed four-factor structure. The reliability obtained for each subscale was satisfactory. Relationships with existing scales demonstrated that the associations were generally as expected, thus indicating the validity of the proposed scale. This scale accurately elucidates the criticality of reappraisal flexibility in psychosocial adjustment.\u003c/p\u003e","manuscriptTitle":"Development of a Reappraisal Flexibility Scale and Examination of Its Reliability and Validity","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-02 07:04:15","doi":"10.21203/rs.3.rs-8214974/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":"7a6e2ed5-d7d0-4ae7-b42b-a335d16e2a32","owner":[],"postedDate":"January 2nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-16T08:42:27+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-02 07:04:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8214974","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8214974","identity":"rs-8214974","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}