676 © 2025 Conscientia Beam. All Rights Reserved. Examining the reliability and validity of adapted LASRS-2 in the Chinese context using the AMOS-SEM approach Li Yanyan1 Yoon Fah Lay2+ Gao Tongtong3 Li Lihua4 Hou Xiujuan5 1,2,3Faculty of Social Sciences and Liberal Arts, UCSI University, Kuala Lumpur, Malaysia. 1Email: 1002163732@ucsiuniversity.edu.my 2Email: layyf@ums.edu.my 3Email: 717963493@qq.com 2Faculty of Education and Sports Studies, Universiti Malaysia Sabah, Kota Kinabalu, Sabah, Malaysia. 2School of Education and Liberal Arts, Taylor’s University, Kuala Lumpur, Malaysia 1,4,5School of Education, Xinyang College, Xinyang, China. 4Email: 715888737@qq.com 5Email: 824418793@qq.com (+ Corresponding author) ABSTRACT Article History Received: 12 December 2024 Revised: 23 June 2025 Accepted: 4 July 2025 Published: 17 July 2025 Keywords Academic stress response Academic stress AMOS-SEM Chinese undergraduate students LASRS-2 Partial least squares structural equation modeling Reliability Validity. This pilot study aimed to examine the reliability and validity of the Lakaev Academic Stress Response Scale-2 (LASRS-2) in the context of Chinese college students. 186 undergraduate students from Xinyang College, China were enlisted for this research. Confirmatory Factor Analysis (CFA) was used to analyze data using the Amos Structural Equation Modeling (AMOS-SEM) methodology. Factor loading and composite reliability (CR) were used to identify the reliability criteria. Moreover, the average variance extracted (AVE) was used as an index of convergent validity and the heterotrait-monotrait criterion (HTMT) as the index of discriminant validity. The research results showed that the adapted LASRS-2 has good reliability and validity indicators after minor modifications for Chinese college students. The adapted LASRS- 2 can be used in the future related to research in the Chinese context. The adapted LASRS-2 can measure college students' academic stress response involving four domains (affective response, behavioral response, cognitive response, and physiological response). Contribution/Originality: This study translated and organized the original LASRS-2 into the Chinese language and is the first pilot study conducted on undergraduate students at Xinyang College. The adapted LASRS-2 has shown good reliability and validity indicators based on the collected data and item analysis. 1. INTRODUCTION The COVID-19 epidemic, which broke out at the end of 2019 is a challenge to all mankind. This sudden worldwide public health crisis is one of the most widespread and deadly public health disasters that has had a substantial impact on all aspects of human society, including education, economy, politics, culture, etc. (Chakraborty & Maity, 2020; Fernandes, 2020; Miyah, Benjelloun, Lairini, & Lahrichi, 2022; Onyeaka, Anumudu, Al-Sharify, Egele-Godswill, & Mbaegbu, 2021; Reuge et al., 2021; Zancajo, Verger, & Bolea, 2022). During this stage, lots of empirical studies have shown that in different occupations and age groups, stressors and stress responses are significantly negatively correlated with the mental health of the subjects, such as their level of well-being (Birditt, Turkelson, Fingerman, Polenick, & Oya, 2021; Brodeur, Clark, Fleche, & Powdthavee, 2021; Carroll et al., 2022; Humanities and Social Sciences Letters 2025 Vol. 13, No. 2, pp. 676-690 ISSN(e): 2312-4318 ISSN(p): 2312-5659 DOI: 10.18488/73.v13i2.4294 © 2025 Conscientia Beam. All Rights Reserved. mailto:1002163732@ucsiuniversity.edu.my mailto:layyf@ums.edu.my mailto:717963493@qq.com mailto:715888737@qq.com mailto:824418793@qq.com https://orcid.org/0009-0003-1355-9065 https://orcid.org/0000-0002-5219-6696 https://orcid.org/0009-0006-0796-7275 https://orcid.org/0009-0005-8688-6141 https://orcid.org/0009-0009-5057-8664 https://www.doi.org/10.18488/73.v13i2.4294 Humanities and Social Sciences Letters, 2025, 13(2): 676-690 677 © 2025 Conscientia Beam. All Rights Reserved. Cusinato et al., 2020; de la Fuente et al., 2021; Evanoff et al., 2020; Gilleen, Santaolalla, Valdearenas, Salice, & Fusté, 2021). Academic stress is one of the many types of stress they face daily especially for undergraduate students. The online learning or e-exam mode that had to be adapted because of isolation in school or hometown would significantly improve the academic stress level (Elsalem et al., 2020; Han, Eum, Kang, & Karsten, 2022; Lee, Jeong, & Kim, 2021; She et al., 2021; Wong & Yuen, 2023; Yang, Chen, & Chen, 2021). Therefore, it is necessary to pay attention to the psychological health of undergraduate students, especially their academic stress state in the global post-pandemic period. 2. SIGNIFICANCE OF THE STUDY Investigating the academic stress of Chinese undergraduate students during the post-pandemic period has theoretical and practical significance. Theoretically, understanding students' academic stress can indirectly help understand the mechanisms of stress and the extent to which stress affects students, leading to a series of emotional, physiological, and cognitive responses in educational psychology. This helps enrich the theories of more effective teaching strategies and support systems in education and psychology, helping students better cope with stress and improve learning achievement. Practically, studying academic stress provides insights into the psychological, emotional, and physical well-being of students. It contributes to the broader understanding of how educational environments impact mental health. Moreover, high academic stress is often linked to academic burnout and even dropout rates (Basri, Hawaldar, Nayak, & Rahiman, 2022; de la Fuente et al., 2021; Hathaisaard, Wannarit, & Pattanaseri, 2022; Hish et al., 2019; Qin et al., 2022; Sharififard, Asayesh, Hosseini, & Sepahvandi, 2020; Walburg, 2014). Understanding academic stress levels can help institutions implement measures to prevent these negative outcomes. Reducing academic stress can also have positive long-term effects on students' mental health leading to improved social well-being as these undergraduates enter the workforce (Alsultan, Alharbi, Mahmoud, & Elsharkasy, 2023; Barbayannis et al., 2022; Green, Faizi, Jalal, & Zadran, 2022; Li, Yang, Zhou, Zhao, & Liu, 2022; Yang, Xiang, Zheng, & Liang, 2022). 3. LITERATURE REVIEW 3.1. Stress The public and scholars have paid attention to the stress of human society's development. It is described as a relationship between an individual and their surroundings that they perceive as exhausting or beyond their resources and posing a risk to their well-being (Lazarus & Folkman, 1984). There are currently three main traditions concerning the different stages of linking stress and disease: epidemiological, psychological, and biological (Cohen, Gianaros, & Manuck, 2016). Higher levels of stress have also been linked to certain physical diseases such as cardiovascular diseases, obesity, and immune system problems (Cohen, Edmondson, & Kronish, 2015; Dhabhar, 2014; Kivimäki & Steptoe, 2018; Tomiyama, 2019) with mental health disorders such as depressive disorder, psychiatric disorders and posttraumatic stress disorder (Boyraz & Legros, 2020; Carr, Martins, Stingel, Lemgruber, & Juruena, 2013; Slavich & Irwin, 2014). Some negative stress responses are predictors of human health and disease outcomes, and they may indicate a mechanism through which psychological stress influences the emergence of future health and disease consequences (Turner et al., 2020). 3.2. Academic Stress Academic stress is a form of stress that has been studied extensively (Cahir & Morris, 1991). Putwain (2007) believes that academic stress is a state of anxiety related to the results or consequences of students' future academic performance. Humanities and Social Sciences Letters, 2025, 13(2): 676-690 678 © 2025 Conscientia Beam. All Rights Reserved. Stankovska, Dimitrovski, Angelkoska, Ibraimi, and Uka (2018) and others put forward the definition of academic stress as anxiety and stress from school and education. Academic stress is related to students and their learning environment and makes students have a negative emotional experience. Academic stress is defined in this study as a sense of tension and discomfort brought about by people's ability to manage expectations in educational settings because the study is part of the authors' larger investigation into the relationship between academic stress response and other relevant factors (Sarafino & Smith, 2014). This includes biology and psychosocial response (cognitive, emotional, and social behavior). Previous studies have shown that there is a significant relationship between students' academic stress and academic performance, academic burnout and other factors in the educational text (Fariborz, Hadi, & Ali, 2019; Gao, 2023; Qian & Fuqiang, 2018; Ye, Posada, & Liu, 2018). Studies on college students worldwide have shown that academic stress is a major predictor of college students' mental health and academic achievement especially during the COVID-19 pandemic. Moreover, the pandemic has raised academic, health, and lifestyle-related concerns among college students with more negative pronounced impacts on students' academic performance, social isolation, fear of contagion, and mental health (Al Mamun, Hosen, Misti, Kaggwa, & Mamun, 2021; O'Byrne, Gavin, Adamis, Lim, & McNicholas, 2021; Prowse et al., 2021; Wang et al., 2020). These issues require further research and attention given the outbreak's length and intensity. 3.3. Academic Stress Response Stressors and stress response are both related to stress. Stress is any external or internal stimulus that triggers a biological reaction. The stress response is the body's coping mechanism (Yaribeygi, Panahi, Sahraei, Johnston, & Sahebkar, 2017). The difference is that the stressors focus on the objective stress events while the stress response research focuses on the subjective feelings of individuals about the stress events, that is, the subjective feelings generated by individuals after making cognitive judgments about the stress events such as the feeling of losing control and feeling of tension (Zhang & Zheng, 2017). According to the model proposed by Lazarus and Folkman (1984), stress response is considered the result of an individual's cognitive evaluation of a stressful situation or event which is the ultimate response of the individual under the influence of a stressor. Stress response or reaction to stress is also seen as the body’s non-specific responses to the experience of stress, including the physiological, behavioral, and emotional reactions (Crum, Jamieson, & Akinola, 2020). Generally, in this study, the definition of academic stress response is the subjective and negative reactions in both physical and mental aspects that can be consciously produced by individuals under the continuous influence of stress sources in academic environments. 3.4. Relevant Scale of Academic Stress In general, the current measurement scales for academic stress among college students can be divided into the following two categories. The first type of scale targets students but is not limited to student groups, such as the Depression Anxiety Stress Scale (DASS-21), and Perceived Stress Scale (PSS). The second type of scale is only applicable to measuring the academic stress of college students in a specific educational environment, such as LASRS-2, freshmen stress scale, university stress scale , Student Stress Inventory (SSI), the Academic Stress Scale (ASS), and College Student Stress Scale (CSSS). The second type of scale which is specifically designed for student groups to measure their academic stress can also be divided into three different types of questionnaires, according to the variables of stress they measure: stressors, stress responses or symptoms, and measurements of both stressors and stress responses or reactions. Table 1 shows the names of scales, authors, target respondents and measured variables of academic stress. Humanities and Social Sciences Letters, 2025, 13(2): 676-690 679 © 2025 Conscientia Beam. All Rights Reserved. Table 1. Relevant information on the scale of academic stress. Name of scales Authors and developers Target respondents Measured variables Self-reported stress- related growth (SRG) Frazier and Kaler (2006) Undergraduate students Stressors Freshmen stress scale Boujut and Bruchon- Schweitzer (2009) University freshmen Stressors University stress scale Stallman and Hurst (2016) University students Stressors Perceived stress scale (PSS) Cohen, Kamarck, and Mermelstein (1983) Adult (Age above 18) Stress responses Lakaev academic stress response scale-2 (LASRS-2) Lakaev (2009) University students Stress responses Lipp's stress symptom inventory (LSS) Lipp and Guevara (1994) Adult (Age above 18) Stress symptoms Chinese stress symptom checklist. Cheng and Hamid (1996) Adult (Age above 18) Stress symptoms Depression anxiety stress scale (DASS-21) Henry and Crawford (2005) Adults and adolescents (Age above 12) Stress symptoms Student-life stress inventory scale. Morris (1990) College students Stressors and stress responses College student stress scale (CSSS) Feldt (2008) College freshmen Stressors and stress responses Student stress inventory (SSI) Arip et al. (2015) Undergraduate students Stressors and stress responses 4. MATERIALS AND METHODS 4.1. Sample This study adopts quantitative research methods, specifically the survey method. Convenient sampling methods are used in non-probability sampling. This research was conducted at Xinyang College, a comprehensive private university in Xinyang City, Henan Province, China. 21,649 full-time undergraduates from 20 provinces in China are receiving higher education in this school where 53 undergraduate majors are offered in this college (Xinyang College, 2022). The minimum sample size for this study must be established using estimates based on G*Power software version 3 since it is a pilot study on the interaction between the five variables of academic stress, academic resilience, social support, coping styles, and well-being among undergraduate students at Xinyang College. G*Power is a popular statistical software program whose main purpose is to help researchers and scientists make informed decisions about the appropriate sample size for their studies or calculation of the required power level for a statistical test which is critical to optimize research efficiency and avoid under- or over-powered experiments (Faul, Erdfelder, Buchner, & Lang, 2009). According to calculations, a total of 109 minimum sample sizes were proposed for the reference structural model in this study. However, according to earlier studies, 100–200 samples are a good starting point for path estimation analysis in structural equation models (Hoyle, 1995). Therefore, researchers used a convenient sampling method to select three undergraduate classes from Xinyang College and collected data from 190 samples, of which 4 samples were excluded due to missing data to meet this requirement. Therefore, a total of 186 valid data were collected in this study. Table 2 provides an overview of the demographic features of the total samples in this study. Humanities and Social Sciences Letters, 2025, 13(2): 676-690 680 © 2025 Conscientia Beam. All Rights Reserved. Table 2. Demographic features of the participants. Variables Options Total sample(n) Percent (%) Gender Male 21 11.3 Female 165 88.7 Age range ≤18 years old 29 15.6 19-20 years old 152 81.7 21-22 years old 5 2.7 ≥23 years old 0 0 Grade Freshman 122 65.6 Sophomore 64 34.4 Junior 0 0 Senior 0 0 Place of birth Countryside 41 22.0 City 145 78.5 Subject Social science 122 65.6 Natural science 64 34.4 4.2. Instrument The rating scale is widely used in surveys related to social behavior research, especially in the measurement of attitudes and other subjective phenomena (Alwin, 1997). The main purpose of using the rating scale is to obtain effective information through the use of reliable procedures. The respondents were given a set of simulated questions, and they were asked to choose a point in the order corresponding to their attitude. The questionnaires used in this study, namely the Lakaev Academic Stress Response Scale-2 (LASRS-2) were developed based on the Lakaev Academic Stress Response Scale-1 (LASRS-1) by adding items and changing the wording of some items (Lakaev, 2009). The LASRS-1 is one of the most statistically established stress measurement tools used in educational filed including English-speaking and non-English-speaking countries as a well-developed modern psychometric tool for academic study (Bernstein & Chemaly, 2017). LASRS-1 examines how academic stress responses are perceived by college students in educational environments rather than concentrating on academic stressors. Lakaev (2009) analyzed the literature on academic and general stress (Cohen et al., 1983) and then he provided the items for the list, and 27 of them were tested in pilot research involving college students. Kessler et al. (2002) after undergoing principal component analysis (PCA), a 4-factor component structure (affective, behavioral, cognitive, and physiological domains) was identified. However, in previous studies, there has been little involvement in introducing the applicability of LASRS-1 or LASRS-2 in the context of Chinese college students. Therefore, it is necessary to test the reliability and validity of the LASRS-2 in the context of Chinese college students to determine its applicability in the Chinese environment. Researchers followed the guidelines proposed by Hambleton, Merenda, and Spielberger (2004) in a book entitled, Adaptive Educational and Psychological Tests for Cross- Cultural Assessment for the adaptation and translation of the questionnaire. This is a very critical process to ensure that the questionnaire is clearly translated without loss of information or misunderstanding. In this study, the original scales of LASRS-2 were all translated into Chinese. Two teachers from two universities in Henan Province who are proficient in English and Chinese assisted the researchers in translating and proofreading the research instruments. These two qualified language teachers have been teaching English and Chinese for more than 10 years. They are proficient in both languages, reducing measurement errors in the translation process. Table 3 shows the codes used in this scale. The final project and its English code abbreviation are shown in Appendix A for reference. Humanities and Social Sciences Letters, 2025, 13(2): 676-690 681 © 2025 Conscientia Beam. All Rights Reserved. Table 3. Code of variables and dimensions used in this scale. Variables Code Academic stress AS Affective academic stress AAS Behavioral academic stress BAS Cognitive academic stress CAS Physiological academic stress PAS 4.3. Procedures The first step in the process of carrying out this study was to request approval from Xinyang College's Academic Integrity Association. After obtaining the admission permit from the association, the translated and examined questionnaire was uploaded to one of the most widely used online survey platforms in China: Wen Juan Xing. The data collection process was conducted in May 2023 at Xinyang College. The online scale was distributed to participants in each classroom of the three selected classes. Participants could use their mobile app to scan and fill out the form. Before data collection, the researcher gave students a necessary introduction to the study, such as emphasizing the anonymity and confidentiality of the measurement results of the subjects. The measurement results are only for research purposes, and there is no difference between good and bad results to reduce the psychological stress of participants when completing the questionnaire. Participants were also given sufficient time to complete each item due to 26 items on the scale. 4.4. Data Analysis Confirmatory Factor Analysis (CFA), one of the primary techniques for factor analysis is used to evaluate the indicators (items) and the structural validity and reliability of the constituents that produce the latent structure. Moreover, Structural Equation Modeling (SEM) is used to analyze relationships between observed and (latent) unobservable variables (Byrne, 2010). In this study, the software tool AMOS 26.0 which is widely used for conducting SEM analyses, provides a user- friendly interface for specifying and estimating complex SEM. It is worth mentioning that additional plug-ins were downloaded and installed into AMOS 26.0 to provide more comprehensive index information on the reliability and validity of the questionnaire (Gaskin, James, & Lim, 2019). 5. RESULTS AND DISCUSSION 5.1. Reliability of the Adapted LASRS-2 Factor loading and composite reliability (CR) were used in this study to establish reliability standards. Specifically, composite reliability (CR) acts as the index of internal consistency reliability, and factor loading acts as the index of indicator reliability. According to Nunnally and Bernstein (1994) the satisfied level of CR is 0.6-0.9. However, different scholars have slightly different opinions on the ideal value standard for factor loading. According to Byrne (2010) the satisfactory level of factor loading is above 0.7 while some others suggest that items with factor loadings higher than 0.5 are also acceptable (Hair, Black, Babin, Anderson, & Tatham, 2006). It’s also claimed that items with factor loading below 0.4 should be deleted (Bagozzi, Yi, & Phillips, 1991). As for items with factor loading between 0.4 and 0.7, if the deletion will increase the VAE value, then they should be removed (Hair, Ringle, & Sarstedt, 2011). According to the above criteria, all items with factor loads below 0.4 in Table 4 have been deleted and items with factor loads between 0.4 and 0.7 have been adjusted. Tables 4 and 5 show the factor loading and CR before and after deletion respectively. Humanities and Social Sciences Letters, 2025, 13(2): 676-690 682 © 2025 Conscientia Beam. All Rights Reserved. Table 4. Factor loading and composite reliability of LASRS-2 (Before item deletion). First-order construct Items Factor loading Composite reliability Affective academic stress (AAS) AAS -1 0.759 0.899 AAS -2 0.662 AAS -3 0.805 AAS -4 0.812 AAS -5 0.757 AAS -6 0.851 AAS -7 0.756 Behavioral academic stress (BAS) BAS -1 0.755 0.773 BAS -2 0.527 BAS -3 0.400 BAS -4 0.667 BAS -5 0.551 BAS -6 0.688 Cognitive academic stress (CAS) CAS-1 0.818 0.901 CAS-2 0.683 CAS-3 0.693 CAS-4 0.699 CAS-5 0.685 CAS-6 0.831 CAS-7 0.842 Physiological academic stress (PAS) PAS-1 0.658 0.898 PAS-2 0.761 PAS-3 0.779 PAS-4 0.789 PAS-5 0.783 PAS-6 0.850 According to Table 4, all 26 items from the original LASRS-2 have factor loading values greater than 0.4 among which 16 of them are greater than 0.7. Therefore, the remaining 10 items with factor loading values in the range of 0.4 to 0.7 will be considered for removal or retained based on their impact on VAE values (Hair et al., 2011). After the calculations, 7 items (AAS-2, BAS-2, BAS-3, BAS-5, CAS-2, CAS-5, PAS-1) are removed from the original LASRS-2. All four factors have ideal values for composite reliability (CR). Table 5. Factor loading and composite reliability of LASRS-2 (After item deletion). First-order construct Items Factor loading Composite reliability Affective academic stress (AAS) AAS -1 0.750 0.894 AAS -3 0.813 AAS -4 0.824 AAS -5 0.776 AAS -6 0.868 AAS -7 0.743 Behavioral academic stress (BAS) BAS -1 0.770 0.751 BAS -4 0.700 BAS -6 0.651 Cognitive academic stress (CAS) CAS-1 0.822 CAS-3 0.678 CAS-4 0.718 0.885 CAS-6 0.823 CAS-7 0.841 Physiological academic stress (PAS) PAS-2 0.735 PAS-3 0.743 PAS-4 0.806 0.892 PAS-5 0.782 PAS-6 0.876 Humanities and Social Sciences Letters, 2025, 13(2): 676-690 683 © 2025 Conscientia Beam. All Rights Reserved. Table 5 clearly shows that after the deletion of relevant items, the adapted LASRS-2 consists of 19 items each of which has a better value of factor loading and composite reliability. 5.2. Validity of the Adapted LASRS-2 Convergent and discriminant validity were used in this study to determine the validity criteria. The heterotrait-monotrait criterion (HTMT) was utilized as the index of discriminant validity and the average variance extracted (AVE) as the index of convergent validity. According to Bagozzi and Yi (1988) an acceptable value for the AVE is over 0.5 indicating that reflective indicators with a variance of more than 50% have been regarded as being able to explain the latent variable. Table 6 shows the AVE before and after item deletion of LASRS-2. It is obvious that after combining the standards of factor loading and AVE value, the deletion of the 7 items has increased the AVE value. Table 6. AVE value of the LASRS-2 and adapted LASRS-2. First-order construct AVE of LASRS-2 AVE of adapted LASRS-2 Affective academic stress (AAS) 0.599 0.635 Behavioral academic stress (BAS) 0.372 0.502 Cognitive academic stress (CAS) 0.568 0.607 Physiological academic stress (PAS) 0.596 0.624 Before and after some items’ deletion, the values of HTMT are presented in Tables 7 and 8, respectively. For the HTMT, a value below 0.85 is seen as a stringent criterion (Kline, 2015). Table 7. Heterotrait-monotrait (HTMT) criterion of LASRS-2 (Before deletion). First-order construct AAS BAS CAS PAS AAS BAS 0.710 CAS 0.836 0.740 PAS 0.762 0.753 0.536 Table 8. Heterotrait-monotrait (HTMT) criterion of adapted LASRS-2 (After deletion). First-order construct AAS BAS CAS PAS AAS BAS 0.706 CAS 0.837 0.643 PAS 0.697 0.707 0.517 Table 7 shows that the HTMT of original LASRS-2 consisted of 26 items meets the criterion of a value lower than 0.85. The same goes for the adapted LASRS-2 with 19 items in Table 8. After the deletion of 7 items, the adapted LASRS-2 has a satisfying validity. 5.3. Structural Equation Modeling According to confirmatory factor analysis, the final model derived from the item deletions exhibited an excellent fit for the data (see Figure 1), chi-squared test (p=0.000, df=149.000 and chi-square=387.182). Additionally, a good match to the data was shown by absolute fit indices, comparative fit indices, and parsimonious fit indices. GFI = 0.912, CMIN/DF = 2.599, SRMR = 0.045, CFI = 0.930, NFI = 0.918, AGFI = 0.904, RMSEA = 0.043. According to Hair et al. (2006) this model fits well in relevant indexes. Humanities and Social Sciences Letters, 2025, 13(2): 676-690 684 © 2025 Conscientia Beam. All Rights Reserved. Figure 1. Confirmatory factor analysis of adapted LASRS-2. This result is consistent with the research findings of Lakaev who conducted confirmatory factor analysis (CFA) on LASRS-1. LASRS-1 was composed of four factors (affective response, behavioral response, cognitive response, and physiological response) that explained 54% of the variance (Lakaev, 2009). In his other research, LASRS-2 is considered an effective and reliable psychological measurement tool for clinical, educational, and other scenarios. However, this scale is considered a one-dimensional structure (Lakaev, 2022). 6. CONCLUSION The primary objective of this pilot study which is part of the author's PhD thesis in education is to evaluate the validity and reliability of several research tools that would be employed in a formal study. Since the research subjects of this research project are undergraduate students at Xinyang College in Xinyang City, China whose Humanities and Social Sciences Letters, 2025, 13(2): 676-690 685 © 2025 Conscientia Beam. All Rights Reserved. academic stress levels need to be measured in the post-epidemic period. In contrast, LASRS-1 has been translated for usage in non-English speaking countries including Iran, the Philippines, Pakistan, and India, and is referred to in several peer-reviewed scientific papers (Bernstein & Chemaly, 2017; Chouhan & Kumar, 2011; Kumar, Bhanagari, Mohile, & Limaye, 2016). More evidence for the reliability and validity of LASRS-2 is needed. This research provides a practical empirical study collecting data in a Chinese environment. The 26 items in the original LASRS-2 were translated, modified, and adjusted before being presented to participants in Xinyang College. Moreover, the scale that has been translated into Chinese must be rigorously tested for reliability as well as validity testing in the Chinese context taking into account the possible inapplicability of research tools due to language differences in cross-cultural research. The current research results indicate that the revised LASRS-2 has good reliability and validity among undergraduate students at Xinyang College in China. According to certain criteria, seven items were removed from the original version, and 19 items were retained. Compared to the original 26 items, the revised questionnaire has fewer items which greatly reduce the burden on participants. In addition, the four-factor model has acceptable model adaptation indicators. Thus, the adapted LASRS-2 with 19 items can be used as an ideal tool to measure the academic stress level of undergraduates during the post-epidemic stage in China. The applicability of the revised scale in other Chinese undergraduate student groups outside of this college requires further empirical research to improve data and information due to the fact that this study only focuses on undergraduate students from Xinyang College as the research population. In addition, more data targeting Chinese undergraduate students should also be collected more widely and deeply to verify the reliability and validity of this scale, as well as to explore the quantity and nature of its factor(s). Funding: This study received no specific financial support. Institutional Review Board Statement: The Ethical Committee of the Xinyang College, China has granted approval for this study on 9 May 2023 (Ref. No. XYCLLSC-20230032). Transparency: The authors state that the manuscript is honest, truthful, and transparent, that no key aspects of the investigation have been omitted, and that any differences from the study as planned have been clarified. This study followed all writing ethics. Competing Interests: The authors declare that they have no competing interests. Authors’ Contributions: All authors contributed equally to the conception and design of the study. All authors have read and agreed to the published version of the manuscript. REFERENCES Al Mamun, F., Hosen, I., Misti, J. M., Kaggwa, M. M., & Mamun, M. A. (2021). Mental disorders of Bangladeshi students during the COVID-19 pandemic: A systematic review. Psychology Research and Behavior Management, 14, 645-654. https://doi.org/10.2147/PRBM.S315961 Alsultan, A., Alharbi, A., Mahmoud, S., & Elsharkasy, A. (2023). The mediating role of psychological capital between academic stress and well-being among University students. Pegem Journal of Education and Instruction, 13(2), 335-344. https://doi.org/10.47750/pegegog.13.02.37 Alwin, D. F. (1997). Feeling thermometers versus 7-point scales: Which are better? Sociological Methods & Research, 25(3), 318- 340. https://doi.org/10.1177/0049124197025003003 Arip, M., Kamaruzaman, D., Roslan, A., Ahmad, A., Rahman, M., & Malim, T. (2015). Development, validity and reliability of student stress inventory (SSI). The Social Sciences, 10(7), 1631-1638. Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16, 74-94. https://doi.org/10.1007/BF02723327 Bagozzi, R. P., Yi, Y., & Phillips, L. W. (1991). Assessing construct validity in organizational research. Administrative Science Quarterly, 36(3), 421-458. https://doi.org/10.2307/2393203 https://doi.org/10.2147/PRBM.S315961 https://doi.org/10.47750/pegegog.13.02.37 https://doi.org/10.1177/0049124197025003003 https://doi.org/10.1007/BF02723327 https://doi.org/10.2307/2393203 Humanities and Social Sciences Letters, 2025, 13(2): 676-690 686 © 2025 Conscientia Beam. All Rights Reserved. Barbayannis, G., Bandari, M., Zheng, X., Baquerizo, H., Pecor, K. W., & Ming, X. (2022). Academic stress and mental well-being in college students: Correlations, affected groups, and COVID-19. Frontiers in Psychology, 13, 886344. https://doi.org/10.3389/fpsyg.2022.886344 Basri, S., Hawaldar, I. T., Nayak, R., & Rahiman, H. U. (2022). Do academic stress, burnout and problematic internet use affect perceived learning? Evidence from India during the COVID-19 pandemic. Sustainability, 14(3), 1409. https://doi.org/10.3390/su14031409 Bernstein, C., & Chemaly, C. (2017). Sex role identity, academic stress and wellbeing of first-year university students. Gender and Behaviour, 15(1), 8045-8069. Birditt, K. S., Turkelson, A., Fingerman, K. L., Polenick, C. A., & Oya, A. (2021). Age differences in stress, life changes, and social ties during the COVID-19 pandemic: Implications for psychological well-being. The Gerontologist, 61(2), 205-216. https://doi.org/10.1093/geront/gnaa204 Boujut, E., & Bruchon-Schweitzer, M. (2009). A construction and validation of a freshman stress questionnaire: An exploratory study. Psychological Reports, 104(2), 680-692. https://doi.org/10.2466/pr0.104.2.680-692 Boyraz, G., & Legros, D. N. (2020). Coronavirus disease (COVID-19) and traumatic stress: Probable risk factors and correlates of posttraumatic stress disorder. Journal of Loss and Trauma, 25(6-7), 503-522. https://doi.org/10.1080/15325024.2020.1763556 Brodeur, A., Clark, A. E., Fleche, S., & Powdthavee, N. (2021). COVID-19, lockdowns and well-being: Evidence from Google Trends. Journal of Public Economics, 193, 104346. https://doi.org/10.1016/j.jpubeco.2020.104346 Byrne, B. M. (2010). Structural equation modeling with AMOS: Basic concepts, applications, and programming (2nd ed.). New York: Routledge. Cahir, N., & Morris, R. D. (1991). The psychology student stress questionnaire. Journal of Clinical Psychology, 47(3), 414-417. Carr, C. P., Martins, C. M. S., Stingel, A. M., Lemgruber, V. B., & Juruena, M. F. (2013). The role of early life stress in adult psychiatric disorders: A systematic review according to childhood trauma subtypes. The Journal of Nervous and Mental Disease, 201(12), 1007-1020. https://doi.org/10.1097/NMD.0000000000000049 Carroll, A., Forrest, K., Sanders-O’Connor, E., Flynn, L., Bower, J. M., Fynes-Clinton, S., . . . Ziaei, M. (2022). Teacher stress and burnout in Australia: Examining the role of intrapersonal and environmental factors. Social Psychology of Education, 25(2), 441-469. https://doi.org/10.1007/s11218-022-09686-7 Chakraborty, I., & Maity, P. (2020). COVID-19 outbreak: Migration, effects on society, global environment and prevention. Science of the Total Environment, 728, 138882. https://doi.org/10.1016/j.scitotenv.2020.138882 Cheng, S. T., & Hamid, P. N. (1996). A Chinese symptom checklist: Preliminary data concerning reliability and validity. Journal of Social Behavior and Personality, 11(2), 241 –252. Chouhan, S., & Kumar, S. (2011). Comparative study between effectiveness of dance movement therapy and progressive relaxation therapy with music for stress management in college students. Indian J. Physiother. Occup. Ther, 5, 179-182. Cohen, B. E., Edmondson, D., & Kronish, I. M. (2015). State of the art review: Depression, stress, anxiety, and cardiovascular disease. American Journal of Hypertension, 28(11), 1295-1302. https://doi.org/10.1093/ajh/hpv047 Cohen, S., Gianaros, P. J., & Manuck, S. B. (2016). A stage model of stress and disease. Perspectives on Psychological Science, 11(4), 456-463. https://doi.org/10.1177/1745691616646305 Cohen, S., Kamarck, T., & Mermelstein, R. (1983). A global measure of perceived stress. Journal of Health and Social Behavior, 24(4), 385-396. https://doi.org/10.2307/2136404 Crum, A. J., Jamieson, J. P., & Akinola, M. (2020). Optimizing stress: An integrated intervention for regulating stress responses. Emotion, 20(1), 120. https://doi.org/10.1037/emo0000670 Cusinato, M., Iannattone, S., Spoto, A., Poli, M., Moretti, C., Gatta, M., & Miscioscia, M. (2020). Stress, resilience, and well- being in Italian children and their parents during the COVID-19 pandemic. International Journal of Environmental Research and Public Health, 17(22), 8297. https://doi.org/10.3390/ijerph17228297 https://doi.org/10.3389/fpsyg.2022.886344 https://doi.org/10.3390/su14031409 https://doi.org/10.1093/geront/gnaa204 https://doi.org/10.2466/pr0.104.2.680-692 https://doi.org/10.1080/15325024.2020.1763556 https://doi.org/10.1016/j.jpubeco.2020.104346 https://doi.org/10.1097/NMD.0000000000000049 https://doi.org/10.1007/s11218-022-09686-7 https://doi.org/10.1016/j.scitotenv.2020.138882 https://doi.org/10.1093/ajh/hpv047 https://doi.org/10.1177/1745691616646305 https://doi.org/10.2307/2136404 https://doi.org/10.1037/emo0000670 https://doi.org/10.3390/ijerph17228297 Humanities and Social Sciences Letters, 2025, 13(2): 676-690 687 © 2025 Conscientia Beam. All Rights Reserved. de la Fuente, J., Pachón-Basallo, M., Santos, F. H., Peralta-Sánchez, F. J., González-Torres, M. C., Artuch-Garde, R., . . . Gaetha, M. L. (2021). How has the COVID-19 crisis affected the academic stress of university students? The role of teachers and students. Frontiers in Psychology, 12, 626340. https://doi.org/10.3389/fpsyg.2021.626340 Dhabhar, F. S. (2014). Effects of stress on immune function: The good, the bad, and the beautiful. Immunologic Research, 58, 193- 210. https://doi.org/10.1007/s12026-014-8517-0 Elsalem, L., Al-Azzam, N., Jum'ah, A. A., Obeidat, N., Sindiani, A. M., & Kheirallah, K. A. (2020). Stress and behavioral changes with remote E-exams during the Covid-19 pandemic: A cross-sectional study among undergraduates of medical sciences. Annals of Medicine and Surgery, 60, 271-279. https://doi.org/10.1016/j.amsu.2020.10.058 Evanoff, B. A., Strickland, J. R., Dale, A. M., Hayibor, L., Page, E., Duncan, J. G., . . . Gray, D. L. (2020). Work-related and personal factors associated with mental well-being during the COVID-19 response: Survey of health care and other workers. Journal of Medical Internet Research, 22(8), e21366. https://doi.org/10.2196/21366 Fariborz, N., Hadi, J., & Ali, T. N. (2019). Students’ academic stress, stress response and academic burnout: Mediating role of self-efficacy. Pertanika Journal of Social Sciences & Humanities, 27(4), 2441-2454. Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statistical power analyses using G* Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149-1160. https://doi.org/10.3758/BRM.41.4.1149 Feldt, R. C. (2008). Development of a brief measure of college stress: The college student stress scale. Psychological Reports, 102(3), 855-860. https://doi.org/10.2466/pr0.102.3.855-860 Fernandes, N. (2020). Economic effects of coronavirus outbreak (COVID-19) on the world economy. IESE Business School Working Paper No. WP-1240-E. Retrieved from http://dx.doi.org/10.2139/ssrn.3557504 Frazier, P. A., & Kaler, M. E. (2006). Assessing the validity of self-reported stress-related growth. Journal of Consulting and Clinical Psychology, 74(5), 859. https://doi.org/10.1037/0022-006X.74.5.859 Gao, X. (2023). Academic stress and academic burnout in adolescents: A moderated mediating model. Frontiers in Psychology, 14, 1133706. https://doi.org/10.3389/fpsyg.2023.1133706 Gaskin, J., James, M., & Lim, J. (2019). Master validity tool. AMOS Plugin in: Gaskination’s StatWiki. Retrieved from https://statwiki.kolobkreations.com Gilleen, J., Santaolalla, A., Valdearenas, L., Salice, C., & Fusté, M. (2021). Impact of the COVID-19 pandemic on the mental health and well-being of UK healthcare workers. BJPsych open, 7(3), e88. https://doi.org/10.1192/bjo.2021.42 Green, Z. A., Faizi, F., Jalal, R., & Zadran, Z. (2022). Emotional support received moderates academic stress and mental well- being in a sample of Afghan university students amid COVID-19. International Journal of Social Psychiatry, 68(8), 1748- 1755. https://doi.org/10.1177/00207640211057729 Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (6th ed.). New Jersey: Prentice-Hall Inc. Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139-152. https://doi.org/10.2753/MTP1069-6679190202 Hambleton, R. K., Merenda, P. F., & Spielberger, C. D. (2004). Adapting educational and psychological tests for cross-cultural assessment. Mahwah, NJ: Lawrence Erlbaum. Han, S., Eum, K., Kang, H. S., & Karsten, K. (2022). Factors influencing academic self-efficacy among nursing students during COVID-19: A path analysis. Journal of Transcultural Nursing, 33(2), 239-245. https://doi.org/10.1177/10436596211061683 Hathaisaard, C., Wannarit, K., & Pattanaseri, K. (2022). Mindfulness-based interventions reducing and preventing stress and burnout in medical students: A systematic review and meta-analysis. Asian Journal of Psychiatry, 69, 102997. https://doi.org/10.1016/j.ajp.2021.102997 Henry, J. D., & Crawford, J. R. (2005). The short‐form version of the Depression Anxiety Stress Scales (DASS‐21): Construct validity and normative data in a large non‐clinical sample. British Journal of Clinical Psychology, 44(2), 227-239. https://doi.org/10.1348/014466505X29657 https://doi.org/10.3389/fpsyg.2021.626340 https://doi.org/10.1007/s12026-014-8517-0 https://doi.org/10.1016/j.amsu.2020.10.058 https://doi.org/10.2196/21366 https://doi.org/10.3758/BRM.41.4.1149 https://doi.org/10.2466/pr0.102.3.855-860 http://dx.doi.org/10.2139/ssrn.3557504 https://doi.org/10.1037/0022-006X.74.5.859 https://doi.org/10.3389/fpsyg.2023.1133706 https://statwiki.kolobkreations.com/ https://doi.org/10.1192/bjo.2021.42 https://doi.org/10.1177/00207640211057729 https://doi.org/10.2753/MTP1069-6679190202 https://doi.org/10.1177/10436596211061683 https://doi.org/10.1016/j.ajp.2021.102997 https://doi.org/10.1348/014466505X29657 Humanities and Social Sciences Letters, 2025, 13(2): 676-690 688 © 2025 Conscientia Beam. All Rights Reserved. Hish, A. J., Nagy, G. A., Fang, C. M., Kelley, L., Nicchitta, C. V., Dzirasa, K., & Rosenthal, M. Z. (2019). Applying the stress process model to stress–burnout and stress–depression relationships in biomedical doctoral students: A cross-sectional pilot study. CBE—Life Sciences Education, 18(4), ar51. https://doi.org/10.1187/cbe.19-03-0060 Hoyle, R. H. (1995). Structural equation modeling: Concepts, issues, and applications. London, Sage Publications: Thousand Oaks. Kessler, R. C., Andrews, G., Colpe, L. J., Hiripi, E., Mroczek, D. K., Normand, S.-L., . . . Zaslavsky, A. M. (2002). Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychological Medicine, 32(6), 959-976. Kivimäki, M., & Steptoe, A. (2018). Effects of stress on the development and progression of cardiovascular disease. Nature Reviews Cardiology, 15(4), 215-229. https://doi.org/10.1038/nrcardio.2017.189 Kline, P. (2015). A handbook of test construction (Psychology revivals): Introduction to psychometric design. New York: Routledge. Kumar, S., Bhanagari, A. H., Mohile, A. S., & Limaye, A. H. (2016). Effect of aerobic exercises, yoga and mental imagery on stress in college students: A comparative study. Indian J Physiother Occup Ther, 10, 69-74. Lakaev, N. (2009). Validation of an Australian academic stress questionnaire. Australian Journal of Guidance and Counselling, 19(1), 56-70. https://doi.org/10.1375/ajgc.19.1.56 Lakaev, N. (2022). Refinement of the Lakaev academic stress response scale (LASRS-2) for research, clinical, and educational settings using rasch modeling. SAGE Open, 12(4), 21582440221102440. https://doi.org/10.1177/21582440221102440 Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping. New York: Springer Publishing Company. Lee, J., Jeong, H. J., & Kim, S. (2021). Stress, anxiety, and depression among undergraduate students during the COVID-19 pandemic and their use of mental health services. Innovative Higher Education, 46, 519-538. https://doi.org/10.1007/s10755-021-09552-y Li, P., Yang, J., Zhou, Z., Zhao, Z., & Liu, T. (2022). The influence of college students' academic stressors on mental health during COVID-19: The mediating effect of social support, social well-being, and self-identity. Frontiers in Public Health, 10, 917581. https://doi.org/10.3389/fpubh.2022.917581 Lipp, M. E. N., & Guevara, A. J. (1994). Empirical validation of the stress symptom inventory (ISS). Estudos de Psicologia, 11(1-3), 43-49. Miyah, Y., Benjelloun, M., Lairini, S., & Lahrichi, A. (2022). COVID‐19 impact on public health, environment, human psychology, global Socioeconomy, and education. The Scientific World Journal, 2022(1), 5578284. https://doi.org/10.1155/2022/5578284 Morris, C. G. (1990). Contemporary psychology and effective behavior (7th ed.). Glenview, IL: Scott Foresman. Nunnally, B., & Bernstein, L. R. (1994). Psychometric theory (3rd ed.). New York: McGraw-Hill. O'Byrne, L., Gavin, B., Adamis, D., Lim, Y. X., & McNicholas, F. (2021). Levels of stress in medical students due to COVID-19. Journal of Medical Ethics, 47(6), 383-388. https://doi.org/10.1136/medethics-2020-107155 Onyeaka, H., Anumudu, C. K., Al-Sharify, Z. T., Egele-Godswill, E., & Mbaegbu, P. (2021). COVID-19 pandemic: A review of the global lockdown and its far-reaching effects. Science Progress, 104(2), 00368504211019854. https://doi.org/10.1177/00368504211019854 Prowse, R., Sherratt, F., Abizaid, A., Gabrys, R. L., Hellemans, K. G., Patterson, Z. R., & McQuaid, R. J. (2021). Coping with the COVID-19 pandemic: Examining gender differences in stress and mental health among university students. Frontiers in Psychiatry, 12, 650759. https://doi.org/10.3389/fpsyt.2021.650759 Putwain, D. (2007). Researching academic stress and anxiety in students: Some methodological considerations. British Educational Research Journal, 33(2), 207-219. https://doi.org/10.1080/01411920701208258 Qian, L., & Fuqiang, Z. (2018). Academic stress, academic procrastination and academicperformance: A moderated dual- mediation model. Journal on Innovation and Sustainability RISUS, 9(2), 38-46. https://doi.org/10.24212/2179- 3565.2018v9i2p38-46 Qin, L., Lu, J., Zhou, Y., Wijaya, T. T., Huang, Y., & Fauziddin, M. (2022). Reduction of academic burnout in preservice teachers: PLS-SEM approach. Sustainability, 14(20), 13416. https://doi.org/10.3390/su142013416 https://doi.org/10.1187/cbe.19-03-0060 https://doi.org/10.1038/nrcardio.2017.189 https://doi.org/10.1375/ajgc.19.1.56 https://doi.org/10.1177/21582440221102440 https://doi.org/10.1007/s10755-021-09552-y https://doi.org/10.3389/fpubh.2022.917581 https://doi.org/10.1155/2022/5578284 https://doi.org/10.1136/medethics-2020-107155 https://doi.org/10.1177/00368504211019854 https://doi.org/10.3389/fpsyt.2021.650759 https://doi.org/10.1080/01411920701208258 https://doi.org/10.24212/2179-3565.2018v9i2p38-46 https://doi.org/10.24212/2179-3565.2018v9i2p38-46 https://doi.org/10.3390/su142013416 Humanities and Social Sciences Letters, 2025, 13(2): 676-690 689 © 2025 Conscientia Beam. All Rights Reserved. Reuge, N., Jenkins, R., Brossard, M., Soobrayan, B., Mizunoya, S., Ackers, J., . . . Taulo, W. G. (2021). Education response to COVID 19 pandemic, a special issue proposed by UNICEF: Editorial review. International Journal of Educational Development, 87, 102485. https://doi.org/10.1016/j.ijedudev.2021.102485 Sarafino, E. P., & Smith, T. W. (2014). Health psychology: Biopsychosocial interactions. USA: John Wiley & Sons. Sharififard, F., Asayesh, H., Hosseini, M. H. M., & Sepahvandi, M. (2020). Motivation, self-efficacy, stress, and academic performance correlation with academic burnout among nursing students. Journal of Nursing and Midwifery Sciences, 7(2), 88-93. She, R., Wong, K., Lin, J., Leung, K., Zhang, Y., & Yang, X. (2021). How COVID-19 stress related to schooling and online learning affects adolescent depression and Internet gaming disorder: Testing Conservation of Resources theory with sex difference. Journal of Behavioral Addictions, 10(4), 953-966. https://doi.org/10.1556/2006.2021.00069 Slavich, G. M., & Irwin, M. R. (2014). From stress to inflammation and major depressive disorder: A social signal transduction theory of depression. Psychological Bulletin, 140(3), 774. https://doi.org/10.1037/a0035302 Stallman, H. M., & Hurst, C. P. (2016). The university stress scale: Measuring domains and extent of stress in university students. Australian Psychologist, 51(2), 128-134. https://doi.org/10.1111/ap.12127 Stankovska, G., Dimitrovski, D., Angelkoska, S., Ibraimi, Z., & Uka, V. (2018). Emotional intelligence, test anxiety and academic stress among university students. Bulgarian Comparative Education Society, 16, 157-164 Tomiyama, A. J. (2019). Stress and obesity. Annual Review of Psychology, 70(1), 703-718. https://doi.org/10.1146/annurev-psych- 010418-102936 Turner, A. I., Smyth, N., Hall, S. J., Torres, S. J., Hussein, M., Jayasinghe, S. U., . . . Clow, A. J. (2020). Psychological stress reactivity and future health and disease outcomes: A systematic review of prospective evidence. Psychoneuroendocrinology, 114, 104599. https://doi.org/10.1016/j.psyneuen.2020.104599 Walburg, V. (2014). Burnout among high school students: A literature review. Children and Youth Services Review, 42, 28-33. https://doi.org/10.1016/j.childyouth.2014.03.020 Wang, X., Hegde, S., Son, C., Keller, B., Smith, A., & Sasangohar, F. (2020). Investigating mental health of US college students during the COVID-19 pandemic: Cross-sectional survey study. Journal of medical Internet Research, 22(9), e22817. https://doi.org/10.2196/22817 Wong, W.-l. L., & Yuen, K.-w. A. (2023). Online learning stress and Chinese college students’ academic coping during COVID- 19: the role of academic Hope and academic self-efficacy. The Journal of Psychology, 157(2), 95-120. https://doi.org/10.1080/00223980.2022.2148087 Xinyang College. (2022). General situation of Xinyang college. Retrieved from https://www.xyu.edu.cn/xxgk.htm Yang, C., Chen, A., & Chen, Y. (2021). College students’ stress and health in the COVID-19 pandemic: The role of academic workload, separation from school, and fears of contagion. PloS One, 16(2), e0246676. https://doi.org/10.1371/journal.pone.0246676 Yang, J., Xiang, L., Zheng, S., & Liang, H. (2022). Learning stress, involvement, academic concerns, and mental health among university students during a pandemic: Influence of fear and moderation of self-efficacy. International Journal of Environmental Research and Public Health, 19(16), 10151. https://doi.org/10.3390/ijerph191610151 Yaribeygi, H., Panahi, Y., Sahraei, H., Johnston, T. P., & Sahebkar, A. (2017). The impact of stress on body function: A review. EXCLI Journal, 16, 1057. https://doi.org/10.17179/excli2017-480 Ye, L., Posada, A., & Liu, Y. (2018). The moderating effects of gender on the relationship between academic stress and academic self-efficacy. International Journal of Stress Management, 25(S1), 56. https://doi.org/10.1037/str0000089 Zancajo, A., Verger, A., & Bolea, P. (2022). Digitalization and beyond: The effects of Covid-19 on post-pandemic educational policy and delivery in Europe. Policy and Society, 41(1), 111-128. https://doi.org/10.1093/polsoc/puab016 Zhang, J., & Zheng, Y. (2017). How do academic stress and leisure activities influence college students' emotional well-being? A daily diary investigation. Journal of Adolescence, 60, 114-118. https://doi.org/10.1016/j.adolescence.2017.08.003 https://doi.org/10.1016/j.ijedudev.2021.102485 https://doi.org/10.1556/2006.2021.00069 https://doi.org/10.1037/a0035302 https://doi.org/10.1111/ap.12127 https://doi.org/10.1146/annurev-psych-010418-102936 https://doi.org/10.1146/annurev-psych-010418-102936 https://doi.org/10.1016/j.psyneuen.2020.104599 https://doi.org/10.1016/j.childyouth.2014.03.020 https://doi.org/10.2196/22817 https://doi.org/10.1080/00223980.2022.2148087 https://www.xyu.edu.cn/xxgk.htm https://doi.org/10.1371/journal.pone.0246676 https://doi.org/10.3390/ijerph191610151 https://doi.org/10.17179/excli2017-480 https://doi.org/10.1037/str0000089 https://doi.org/10.1093/polsoc/puab016 https://doi.org/10.1016/j.adolescence.2017.08.003 Humanities and Social Sciences Letters, 2025, 13(2): 676-690 690 © 2025 Conscientia Beam. All Rights Reserved. APPENDIX A. The scale was used with the presence of dimensions and code abbreviations. Table A. Code and item description of original LASRS-2. Item description Code Item Dimension 1: Affective academic stress (AAS) AAS -l I feel overwhelmed by the demands of study. AAS -2* There is so much going on that I can’t think straight. AAS -3 I felt worried about coping with my studies. AAS -4 I felt angry about unreasonable demands being asked of me. AAS -5 I felt emotionally drained by university. AAS -6 I felt anxious / Stressed by university. AAS -7 My work built up so much that I felt like crying. Dimension 2: Behavioral academic stress (BAS) BAS -1 I used alcohol, drugs, or socializing to avoid anxiety / Stress. BAS -2* I wanted to sleep all the time or slept all day. BAS -3* I avoided class. BAS -4 I yelled at family or friends. BAS -5* I stayed away from friends and / Or family. BAS -6 I have had a lot of trouble sleeping. Dimension 3: Cognitive academic stress (CAS) CAS -l I had trouble concentrating in class. CAS -2* I felt I was lazy when it came to university work. CAS -3 My emotions stop me from studying. CAS -4 I have trouble remembering my notes. CAS -5* I procrastinated on assignments. CAS -6 I was unable to study. CAS -7 I was distracted in class. Dimension 4: Physiological academic stress (PAS) PAS -1* I felt uncomfortable in the stomach. PAS -2 I couldn't breathe. PAS -3 I had headaches. PAS -4 My hands were sweaty and / Or trembling. PAS -5 I had difficulty eating. PAS -6 My heart pounded. Note: * Item removed in the adapted LASRS-2. Views and opinions expressed in this article are the views and opinions of the author(s), Humanities and Social Sciences Letters shall not be responsible or answerable for any loss, damage or liability etc. caused in relation to/arising out of the use of the content.