Gore, J. M., Miller, A., Fray, L., Harris, J. & Prieto, E. Improving student achievement through professional development: Results from a randomised controlled trial of Quality Teaching Rounds. Teach. Teach. Educ. 101, 103297 (2021).
Becker, M., Kocaj, A., Jansen, M., Dumont, H. & Lüdtke, O. Class-average achievement and individual achievement development: Testing achievement composition and peer spillover effects using five German longitudinal studies. J. Educ. Psychol. 114, 177 (2022).
Conaghan, D. Instrumental music education in Ireland: How subsidiarity and choice can perpetuate structural inequalities. Irish Educ. Stud. https://doi.org/10.1080/03323315.2022.2093255 (2022).
Du, J. & Leung, B.-W. The sustainability of multicultural music education in Guizhou Province, China. Int. J. Music Educ. 40, 131–148 (2022).
Xu, N. Analysis on improvement of comprehensive competency in undergraduates by music education. Educ. Sci. Theory Pract. 18, 2062–2068 (2018).
Freer, E. & Evans, P. Choosing to study music in high school: Teacher support, psychological needs satisfaction, and elective music intentions. Psychol. Music 47, 781–799 (2019).
Behbehani, S. & Steffens, J. Musical DIAMONDS: The influence of situational classes and characteristics on music listening behavior. Psychol. Music 49, 1532–1545 (2021).
Gallardo, I., Iturra, C., Bustamante, M., Pérez, I. & Clavijo, M. Empirically based decisions: The effect of musical and humanistic activities on self-efficacy and student academic performance. Revista de Psicodidáctica (English ed.) 26, 105–112 (2021).
Oliveira, A., McPherson, G., Mota Ribeiro, L. & Oliveira-Silva, P. Musical achievement during a lockdown: The parental support miracle. Res. Stud. Music Educ. 45, 211–226 (2023).
Loepthien, T. & Leipold, B. Flow in music performance and music-listening: Differences in intensity, predictors, and the relationship between flow and subjective well-being. Psychol. Music 50, 111–126 (2022).
Schäfer, K. & Eerola, T. How listening to music and engagement with other media provide a sense of belonging: An exploratory study of social surrogacy. Psychol. Music 48, 232–251 (2020).
Cuny, C., Fornerino, M. & Helme-Guizon, A. Can music improve e-behavioral intentions by enhancing consumers’ immersion and experience?. Inf. Manag. 52, 1025–1034 (2015).
Reybrouck, M., Vuust, P. & Brattico, E. Neural correlates of music listening: Does the music matter?. Brain Sci. 11, 1553 (2021).
Urruzola, M.-V. & Bernaras, E. Music performance anxiety in 8-to 12-year-old children. Revista de Psicodidáctica (English ed.) 25, 76–83 (2020).
Jian, Z. Sustainable engagement and academic achievement under impact of academic self-efficacy through mediation of learning agility—evidence from music education students. Front. Psychol. https://doi.org/10.3389/fpsyg.2022.899706 (2022).
Faran, M., Akram, S., Tahir, N. & Malik, F. Uses of Music and Flourish: Mediating Role of Emotion Regulation in University Students (2021).
Hwang, A.H.-C. & Oh, J. Interacting with background music engages E-Customers more: The impact of interactive music on consumer perception and behavioral intention. J. Retail. Consumer Serv. 54, 101928 (2020).
Halliday, A. J. Bridging music and organizational psychology: Everyday music uses and preferences and the prediction of organizational behaviour. Pers. Individ. Differ. 139, 263–276 (2019).
Müllensiefen, D., Harrison, P., Caprini, F. & Fancourt, A. Investigating the importance of self-theories of intelligence and musicality for students’ academic and musical achievement. Front. Psychol. 6, 1702 (2015).
Leung, M. C. & Cheung, R. Y. Music engagement and well-being in Chinese adolescents: Emotional awareness, positive emotions, and negative emotions as mediating processes. Psychol. Music 48, 105–119 (2020).
Koehler, F., Warth, M., Ditzen, B. & Neubauer, A. B. Motivation to make music matters: Daily autonomous motivation, flow, and well-being in hobby musicians. Psychol. Aesthet. Creativity Arts 17, 682–693 (2023).
Brattico, E., Bogert, B. & Jacobsen, T. Toward a neural chronometry for the aesthetic experience of music. Front. Psychol. 4, 206 (2013).
Faran, M., Akram, S., Tahir, N. & Malik, F. Uses of music and flourish: mediating role of emotion regulation in university students. J. Behav. Sci. 31, 25 (2021).
Greb, F., Steffens, J. & Schlotz, W. Modeling music-selection behavior in everyday life: A multilevel statistical learning approach and mediation analysis of experience sampling data. Front. Psychol. 10, 390 (2019).
Redman, D. J. & Bugos, J. A. Motivational factors in adult, auditioned community choirs: The power of aesthetic experiences. Psychol. Music 47, 694–705 (2019).
Chang, J., Lin, P. & Hoffman, E. Music major, affects, and positive music listening experience. Psychol. Music 49, 841–854 (2021).
Deci, E. L. & Ryan, R. M. Optimizing students’ motivation in the era of testing and pressure: A self-determination theory perspective. In Building Autonomous Learners: Perspectives from Research and Practice Using Self-Determination Theory, 9–29 (2016).
Santana-Monagas, E., Putwain, D. W., Núnez, J. L., Loro, J. F. & León, J. Do teachers’ engaging messages predict motivation to learn and performance?. Revista De Psicodidáctica (English Ed.) 27, 86–95 (2022).
Deci, E. L. & Ryan, R. M. “Facilitating optimal motivation and psychological well-being across life’s domains”: Correction to Deci and Ryan. (2008).
Groarke, J. M. & Hogan, M. J. Development and psychometric evaluation of the adaptive functions of music listening scale. Front. Psychol. 9, 516 (2018).
Giordano, F. et al. Receptive music therapy to reduce stress and improve wellbeing in Italian clinical staff involved in COVID-19 pandemic: A preliminary study. Arts Psychother. 70, 101688 (2020).
Vajpeyee, M. et al. Yoga and music intervention to reduce depression, anxiety, and stress during COVID-19 outbreak on healthcare workers. Int. J. Soc. Psychiatry 68, 798–807 (2022).
Krause, A. E., Dimmock, J., Rebar, A. L. & Jackson, B. Music listening predicted improved life satisfaction in university students during early stages of the COVID-19 pandemic. Front. Psychol. 11, 631033 (2021).
Malhotra, N. K. Essentials of Marketing Research: A Hands-on Orientation (Pearson Essex, 2015).
Creswell, J. W. & Creswell, J. D. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (Sage Publications, 2017).
Cheng, X., Zhang, Z., Yang, Y. & Yan, Z. Open collaboration between universities and enterprises: A case study on GitHub. Internet Res. 30, 1251–1279 (2020).
Dai, B., Ali, A. & Wang, H. Exploring information avoidance intention of social media users: A cognition–affect–conation perspective. Internet Res. 30, 1455–1478 (2020).
Yassin, A. A., Razak, N. A., Saeed, M. A., Al-Maliki, M. A. A. & Al-Habies, F. A. Psychological impact of the COVID-19 pandemic on local and international students in Malaysian universities. Asian Educ. Dev. Stud. 10, 574–586 (2021).
Yoo, B. & Donthu, N. Developing and validating a multidimensional consumer-based brand equity scale. J. Bus. Res. 52, 1–14 (2001).
Kim, D. J. A study of the multilevel and dynamic nature of trust in e-commerce from a cross-stage perspective. Int. J. Electron. Commerce 19, 11–64 (2014).
Comrey, A. L., Backer, T. E. & Glaser, E. M. A sourcebook for mental health measures. (1973).
Worthington, R. L. & Whittaker, T. A. Scale development research: A content analysis and recommendations for best practices. Couns. Psychol. 34, 806–838 (2006).
Hair, J. F., Ringle, C. M. & Sarstedt, M. Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long Range Plan. 46, 1–12 (2013).
Hair, J. F. Jr., Hult, G. T. M., Ringle, C. M. & Sarstedt, M. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (Sage Publications, 2021).
Soper, D. (2021).
Westland, J. C. Lower bounds on sample size in structural equation modeling. Electron. Commerce Res. Appl. 9, 476–487 (2010).
Vidas, D., Nelson, N. L. & Dingle, G. A. Music listening as a coping resource in domestic and international university students. Psychol. Music 50, 1816–1836 (2022).
Rosenberg, N., Greenberg, D. M. & Lamb, M. E. Musical engagement is linked to posttraumatic resilience: The role of gender, personality, and music listening styles after childhood trauma. Music Sci. 4, 2059204321993731 (2021).
Taherdoost, H. What is the best response scale for survey and questionnaire design; review of different lengths of rating scale/attitude scale/Likert scale. Int. J. Acad. Res. Manag. 8, 1–12 (2019).
Ramli, N. A., Latan, H. & Nartea, G. V. Why should PLS-SEM be used rather than regression? Evidence from the capital structure perspective. In Partial Least Squares Structural Equation Modeling: Recent Advances in Banking and Finance, 171–209 (2018).
Preacher, K. J. & Hayes, A. F. Assessing Mediation in Communication Research (The Sage Sourcebook of Advanced Data Analysis Methods for Communication, 2008).
Hinkin, T. R. A brief tutorial on the development of measures for use in survey questionnaires. Organ. Res. Methods 1, 104–121 (1998).
Hair, J., Black, W., Babin, B. & Anderson, R. Exploratory factor analysis. Multivariate data analysis, 7th Pearson new international ed. (Pearson Education, 2014).
Anderson, J. C. & Gerbing, D. W. Structural equation modeling in practice: A review and recommended two-step approach. Psychol. Bull. 103, 411 (1988).
Kline, R. B. Principles and Practice of Structural Equation Modeling (Guilford Publications, 2023).
Teo, T. & Zhou, M. Explaining the intention to use technology among university students: A structural equation modeling approach. J. Comput. High. Educ. 26, 124–142 (2014).
Chin, W. W. vii-xvi (JSTOR, 1998).
Baron, R. M. & Kenny, D. A. The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. J. Pers. Soc. Psychol. 51, 1173 (1986).
Rucker, D. D., Preacher, K. J., Tormala, Z. L. & Petty, R. E. Mediation analysis in social psychology: Current practices and new recommendations. Soc. Pers. Psychol. Compass 5, 359–371 (2011).
Armstrong, J. S. & Overton, T. S. Estimating nonresponse bias in mail surveys. J. Market. Res. 14, 396–402 (1977).
Chen, L. & Fu, L. Let’s fight the infodemic: The third-person effect process of misinformation during public health emergencies. Internet Res. 32, 1357–1377 (2022).
Moqbel, M., Bartelt, V. L., Topuz, K. & Gehrt, K. L. Enterprise social media: Combating turnover in businesses. Internet Res. 30, 591–610 (2020).
Abraham, V., Bremser, K., Carreno, M., Crowley-Cyr, L. & Moreno, M. Exploring the consequences of COVID-19 on tourist behaviors: Perceived travel risk, animosity and intentions to travel. Tour. Rev. 76, 701–717 (2021).
Bhukya, R. & Singh, S. The effect of perceived risk dimensions on purchase intention: An empirical evidence from Indian private labels market. Am. J. Bus. 30, 218–230 (2015).
Kutner, M. H., Nachtsheim, C. J., Neter, J. & Wasserman, W. Applied Linear Regression Models Vol. 4 (McGraw-Hill/Irwin New York, 2004).
Koufteros, X. A. Testing a model of pull production: A paradigm for manufacturing research using structural equation modeling. J. Oper. Manag. 17, 467–488 (1999).
MacCallum, R. C., Browne, M. W. & Sugawara, H. M. Power analysis and determination of sample size for covariance structure modeling. Psychol. Methods 1, 130 (1996).
Henseler, J., Ringle, C. M. & Sinkovics, R. R. New Challenges to International Marketing (Emerald Group Publishing Limited, 2009).
Henseler, J., Ringle, C. M. & Sarstedt, M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. J. Acad. Market. Sci. 43, 115–135 (2015).
Fornell, C. & Larcker, D. F. Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 18, 39–50 (1981).
Hair, J., Black, B., Babin, B. & Anderson, R. Multivariate Data Analysis 7th edn, 629–686 (Pearson Prentice Hall, 2010).
Rehman, S.-U., Mohamed, R. & Ayoup, H. The mediating role of organizational capabilities between organizational performance and its determinants. J. Glob. Entrepreneurship Res. 9, 1–23 (2019).
Hu, L. T. & Bentler, P. M. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct. Equ. Model. Multidiscip. J. 6, 1–55 (1999).
Kamalzadeh, M., Baur, D. & Möller, T. Listen or interact? A large-scale survey on music listening and management behaviours. J. New Music Res. 45, 42–67 (2016).
Hallam, S. The power of music: Its impact on the intellectual, social and personal development of children and young people. Int. J. Music Educ. 28, 269–289 (2010).
Mohan, A. & Thomas, E. Effect of background music and the cultural preference to music on adolescents’ task performance. Int. J. Adolesc. Youth 25, 562–573 (2020).
Dingle, G. A. et al. How do music activities affect health and well-being? A scoping review of studies examining psychosocial mechanisms. Front. Psychol. 12, 3689 (2021).
Nichols, B. E. & Springer, D. G. Interval identification predicts success in melodic dictation. J. Res. Music Educ. 70, 109–126 (2022).
Loveday, C., Musgrave, G. & Gross, S.-A. Predicting anxiety, depression, and wellbeing in professional and nonprofessional musicians. Psychol. Music 51, 508–522 (2023).
Musgrave, G. Music and wellbeing vs. musicians’ wellbeing: examining the paradox of music-making positively impacting wellbeing, but musicians suffering from poor mental health. Cult. Trends 32, 280–295 (2023).
