Analysis of university professors in economic sciences: PMH scale and technostress as main antecedents of academic self-perception

In order to establish the relationship between the academic self-perception of university professors according to their gender, which takes into account the internal and external factors, such as technostress, the PMH scale (unidimensional Positive Mental Health Scale) and the factors that are related to an organization, which is understood to be a university, are the climate and the commitment of the professor, which are the constructs that were used in our research. The research was conducted by using a sample of 161 active university professors of economics from both sexes. The analysis of the results that were obtained were conducted via a mixed analysis using symmetric methodology (partial least squares structural equation modeling “PLS-SEM”). In addition, a multigroup analysis (Partial Least Squares Multi-Group Analysis “PLS-MGA”) was performed according to the sex as well as asymmetric (Fuzzy-set Qualitative Comparative Analysis “fs/QCA”), which is where the different combinations of the antecedents that lead to the common result are established. Technostress is unequally related to the model variables. It is significant with respect to Academic Self-perception (AS), Organizational Climate (OC), and PMH-Scale (PMH), which even results in a positive relationship with OC and PMH This indicates that in academia certain levels of technostress can generate positive results. This fact is also demonstrated by the presence of the variable in the solutions that were generated using the asymmetric method. The demands of the new technological adoptions among university professors are generating the modification of perceptions and therefore behavior. Therefore, it is necessary to control the level of technostress assumed by men from the teaching centers as well as regulating the technological contributions and their introduction in the classrooms. The study proposes a novel approach due to the implementation of a mixed methodology of analyses. Most previous analyses have focused on case studies or students. The conclusions are relevant for the necessary technological implementation in university classrooms.

High education; Men; Technostress; PMH scale; Organizational climate; fs/QCA

[1] Bilbao Aiastui E, Arruti Gómez A, Carballedo Morillo R. A systematic literature review about the level of digital competences defined by DigCompEdu in higher education. Aula Abierta. 2021; 50: 841–850.

[2] Rapanta C, Botturi L, Goodyear P, Guàrdia L, Koole M. Online university teaching during and after the Covid-19 crisis: refocusing teacher presence and learning activity. Postdigital Science and Education. 2020; 2: 923–945.

[3] Ramos-Pla A, del Arco I, Flores Alarcia Ò. University professor training in times of COVID-19: analysis of training programs and perception of impact on teaching practices. Education Sciences. 2021; 11: 684.

[4] López-Valenciano A, Suárez-Iglesias D, Sanchez-Lastra MA, Ayán C. Impact of COVID-19 pandemic on university students’ physical activity levels: an early systematic review. Frontiers in Psychology. 2021; 11: 624567.

[5] Almhdawi KA, Obeidat D, Kanaan SF, Hajela N, Bsoul M, Arabiat A, et al. University professors’ mental and physical well-being during the COVID-19 pandemic and distance teaching. Work. 2021; 69: 1153–1161.

[6] Turugare M, Rudhumbu N. Integrating technology in teaching and learning in universities in Lesotho: opportunities and challenges. Education and Information Technologies. 2020; 25: 3593–3612.

[7] Penado Abilleira M, Rodicio-García M, Ríos-de Deus MP, Mosquera-González MJ. Technostress in Spanish university teachers during the COVID-19 pandemic. Frontiers in Psychology. 2021; 12: 617650.

[8] Li L, Wang X. Technostress inhibitors and creators and their impacts on university teachers’ work performance in higher education. Cognition, Technology & Work. 2021; 23: 315–330.

[9] Wang X, Li B. Technostress among university teachers in higher education: a study using multidimensional person-environment misfit theory. Frontiers in Psychology. 2019; 10: 1791.

[10] dos Santos GMRF, da Silva ME, Belmonte BDR. COVID-19: emergency remote teaching and university professors’ mental health. Brazilian Journal of Mother and Child Health. 2021; 21: 237–243.

[11] Hurtado-Pardos B, Moreno-Arroyo C, Casas I, Lluch-Canut T, Lleixà-Fortuño M, Farrés-Tarafa M, et al. Positive mental health and prevalence of psychological ill-being in university nursing professors in Catalonia, Spain. Journal of Psychosocial Nursing and Mental Health Services. 2017; 55: 38–48.

[12] Çeçen AR, Vatandaşlar SE. Psychometric properties of the positive mental health scale (PMH-scale) among Turkish university students. European Journal of Health Psychology. 2021; 28: 71–78.

[13] Khaiyom JHA, Ariffin AHT, Rosli ANM. Islam, iman, and ihsan: the role of religiosity on quality of life and mental health of muslim undergraduate students in Islamic university. IIUM Medical Journal Malaysia. 2022; 21: 2047.

[14] Almubaddel A. Psychometric properties of a Saudi Arabian version of the Positive Mental Health (PMH) scale. Psychology: Reflection and Critique. 2022; 35: 29.

[15] Velten J, BrailovskaiaJ, Margraf J. Positive mental health scale: validation and measurement invariance across eight countries, genders, and age groups. Psychological Assessment. 2022; 34: 332–340.

[16] Basantes-Andrade M, Cabezas-González M, Casillas-Martín S. Digital competences relationship between gender and generation of university professors. International Journal on Advanced Science, Engineering and Information Technology. 2020; 10: 205–211.

[17] Collie RJ, Shapka JD, Perry NE. Predicting teacher commitment: the impact of school climate and social-emotional learning. Psychology in the Schools. 2011; 48: 1034–1048.

[18] Hsiao K, Shu Y, Huang T. Exploring the effect of compulsive social app usage on technostress and academic performance: perspectives from personality traits. Telematics and Informatics. 2017; 34: 679–690.

[19] Keyes CLM. Mental health in adolescence: is America’s youth flourishing? American Journal of Orthopsychiatry. 2006; 76: 395–402.

[20] Lukat J, Margraf J, Lutz R, van der Veld WM, Becker ES. Psychometric properties of the positive mental health scale (PMH-scale). BMC Psychology. 2016; 4: 8.

[21] World Health Organization. The World health report: 2001: Mental health : new understanding, new hope. (mis-20697). Geneva; 01 January 2001. 178p. 2001.

[22] Burrows T, Teasdale S, Rocks T, Whatnall M, Schindlmayr J, Plain J, et al. Effectiveness of dietary interventions in mental health treatment: a rapid review of reviews. Nutrition & Dietetics. 2022; 79: 279–290.

[23] Samji H, Wu J, Ladak A, Vossen C, Stewart E, Dove N, et al. Mental health impacts of the COVID-19 pandemic on children and youth—a systematic review. Child and Adolescent Mental Health. 2022; 27: 173–189.

[24] Mousa M, Samara G. Mental health of business academics within the COVID-19 era: can meaningful work help? A qualitative study. Employee Relations. 2022; 44: 764–784.

[25] Budhiraja S, Rathi N. Determinants of positive mental health during organizational change: role of continuous learning, mindfulness and change-efficacy. Foresight. 2022. [Preprint].

[26] Hubert P, Abdel Hadi S, Mojzisch A, Häusser JA. The effects of organizational climate on adherence to guidelines for COVID-19 prevention. Social Science & Medicine. 2022; 292: 114622.

[27] Chauhan RS, Howe DC, Nachmias S. Organizational commitment: an ever-shifting concept forever changed by COVID-19. Human Resource Development International. 2022; 1–8.

[28] Soto-Crofford CA, Deroncele-Acosta A. Salud mental positiva en una comunidad de docentes en Ecuador. Teacher and Society. 2021; 18: 1633–1654.

[29] Cruz CM, Lamb MM, Giri P, Vanderburg J, Ferrarone P, Bhattarai S, et al. Perceptions, attitudes, and knowledge of teachers serving as mental health lay counselors in a low and middle income country: a mixed methods pragmatic pilot study. International Journal of Mental Health Systems. 2021; 15: 40.

[30] Desai M, Pandit U, Nerurkar A, Verma C. Perception of educational environment as a predictor of academic performance in physiotherapy students. Journal of Education and Health Promotion. 2022; 11: 174.

[31] Hasan MM, Jankowski KS, Khan MHA. Morningness-eveningness preference and shift in chronotype during COVID-19 as predictors of mood and well-being in university students. Personality and Individual Differences. 2022; 191: 111581.

[32] Cheshmehzangi A, Zou T, Su Z. The digital divide impacts on mental health during the COVID-19 pandemic. Brain, Behavior, and Immunity. 2022; 101: 211–213.

[33] Spanakis P, Peckham E, Mathers A, Shiers D, Gilbody S. The digital divide: amplifying health inequalities for people with severe mental illness in the time of COVID-19. The British Journal of Psychiatry. 2021; 219: 529–531.

[34] Gjoneska B, Potenza MN, Jones J, Corazza O, Hall N, Sales CMD, et al. Problematic use of the internet during the COVID-19 pandemic: good practices and mental health recommendations. Comprehensive Psychiatry. 2022; 112: 152279.

[35] Camacho S, Barrios A. Teleworking and technostress: early conse-quences of a COVID-19 lockdown. Cognition, Technology & Work. 2022; 24: 441–457.

[36] Brod C. The Human Cost of the Computer Revolution. 9th ed. Addison-WesleyReading: Mass. 1984.

[37] Wu W, Chin W, Liu Y. Technostress and the smart hospitality employee. Journal of Hospitality and Tourism Technology. 2022; 13: 404–426.

[38] Gabr HM, Soliman SS, Allam HK, Raouf SYA. Effects of remote virtual work environment during COVID-19 pandemic on technostress among Menoufia university staff, egypt: a cross-sectional study. Environmental Science and Pollution Research. 2021; 28: 53746–53753.

[39] Balducci C, Conway PM, van Heugten K. The contribution of organi-zational factors to workplace bullying, emotional abuse and harassment. Pathways of Job-Related Negative Behaviour. 2021; 2: 3–28.

[40] Mao H, Wang L, Qin M, Wei J, Liu S. Exploring the perceptions of the educational environment in online acupuncture learning during the COVID-19 pandemic. Acupuncture in Medicine. 2022; 40: 186–190.

[41] Nang AFM, Maat SM, Mahmud MS. Teacher technostress and coping mechanisms during Covid-19 pandemic: a systematic review. Pegem Journal of Education and Instruction. 2022; 12: 200–212.

[42] Chen CC, Lim S. Examining the effect of COVID-19 pandemic on exercise behavior and perceived academic stress among US college students. Journal of American College Health. 2022; 1–7.

[43] Santana LDL, Ramos TH, Ziesemer NDB, Pedrolo TPDCE. Intervening factors in the quality of teacher life during the COVID-19 pandemic. Current Research in Education. 2022; 22: 219–250.

[44] Ramírez Mera UN, Barragán López JF. University students’ self-perception on the use of digital technologies for learning. Apertura. 2018; 10: 94–109.

[45] Chevalier A, Gibbons S, Thorpe A, Snell M, Hoskins S. Students’ academic self-perception. Economics of Education Review. 2009; 28: 716–727.

[46] Granda AH, YepesSM, Granada WFM, Zuluaga JA. Students’ self-perception of social, emotional, and intercultural competences in a public higher education institution in Colombia. Journal for Multicultural Education. 2022. [Preprint].

[47] Yulianti P, Sridadi R, Lestari YD. Fostering creative performance in public universities. The Journal of Behavioral Science. 2022; 17: 15–26.

[48] Deka MJ, Jain PK. Perception of faculty members regarding various dimensions of organizational climate of central universities of assam. Journal of Positive School Psychology. 2022; 6: 3186–3191.

[49] Parmar V, Channar ZA, Ahmed RR, Streimikiene D, Pahi MH, Streimikis J. Assessing the organizational commitment, subjective vitality and burnout effects on turnover intention in private universities. Oeconomia Copernicana. 2022; 13: 251–286.

[50] Fuglseth AM, Sørebø Ø. The effects of technostress within the context of employee use of ICT. Computers in Human Behavior. 2014; 40: 161–170.

[51] Arónica SF. Las TICs en la enseñanza de las Ciencias Económicas. Sociedad Argentina de Informática e Investigación Operativa. XLIII Jornadas Argentinas de Informática e Investigación Operativa (43JAIIO)-I Simposio Argentino de Tecnología y Sociedad (STS) (Buenos Aires, 2014). Sociedad Argentina de Informática e Investigación Operativa: Buenos Aires. 2014.

[52] Liao H, Shi Y, Liu X, Shen N, Deng Q. A non-probabilistic model of carbon footprints in remanufacture under multiple uncertainties. Journal of Cleaner Production. 2019; 211: 1127–1140.

[53] Richter NF, Cepeda G, Roldán JL, Ringle CM. European management research using partial least squares structural equation modeling (PLS-SEM). European Management Journal. 2015; 33: 1–3.

[54] Chin WW, Dibbern J. An introduction to a permutation based procedure for multi-group pls analysis: results of tests of differences on simulated data and a cross cultural analysis of the sourcing of information system services between germany and the USA. Handbook of Partial least Squares. 2010; 50: 171–193.

[55] Hair JF, Sarstedt M, Ringle CM, Mena JA. An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science. 2012; 40: 414–433.

[56] Douglas EJ, Shepherd DA, Prentice C. Using fuzzy-set qualitative com-parative analysis for a finer-grained understanding of entrepreneurship. Journal of Business Venturing. 2020; 35: 105970.

[57] Misangyi VF, Greckhamer T, Furnari S, Fiss PC, Crilly D, Aguilera R. Embracing causal complexity: the emergence of a neo-configurational perspective. Journal of Management. 2017; 43: 255–282.

[58] Rippa P, Ferruzzi G, Holienka M, Capaldo G, Coduras A. What drives university engineering students to become entrepreneurs? Finding different recipes using a configuration approach. Journal of Small Business Management. 2020; 1–31.

[59] Roig-Tierno N, Gonzalez-Cruz TF, Llopis-Martinez J. An overview of qualitative comparative analysis: a bibliometric analysis. Journal of Innovation & Knowledge. 2017; 2: 15–23.

[60] Kusa R, Duda J, Suder M. How to sustain company growth in times of crisis: the mitigating role of entrepreneurial management. Journal of Business Research. 2022; 142: 377–386.

[61] Fornell C, Larcker DF. Structural equation models with unobservable variables and measurement error: algebra and statistics. Journal of Marketing Research. 1981; 18: 382–388.

[62] Henseler J, Hubona G, Ray PA. Partial least squares path modeling: updated guidelines. Partial Least Squares Path Modeling. 2017; 19–39.

[63] Sarstedt M, Ringle CM, Hair JF. Partial least squares structural equation modeling. Handbook of Market Research. 2017; 13: 1–40.

[64] Henseler J, Ringle CM, Sarstedt M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science. 2015; 43: 115–135.

[65] Hair JF, Hult JTM, Ringle CM, Sarstedt M, Apraiz JC, Cepeda-Carrion GA, et al. Manual de partial least squares structural equation modeling (PLS-SEM). 2nd ed. Omnia Science: Spain. 2019.

[66] Rihoux B, Álamos-Concha P, Lobe B. Qualitative Comparative Analysis (QCA): An integrative approach suited for diverse Mixed Methods and Multimethod research strategies. In The Routledge Reviewer’s Guide to Mixed Methods Analysis. 2021; 185–197.

[67] Fernández-Esquinas M, Sánchez-Rodríguez MI, Pedraza-Rodríguez JA, Muñoz-Benito R. The use of QCA in science, technology and innovation studies: a review of the literature and an empirical application to knowledge transfer. Scientometrics. 2021; 126: 6349–6382.

[68] Ragin CC. Set relations in social research: evaluating their consistency and coverage. Political Analysis. 2006; 14: 291–310.

[69] Rippa P, Ferruzzi G, Holienka M, Capaldo G, Coduras A. What drives university engineering students to become entrepreneurs? Finding different recipes using a configuration approach. Journal of Small Business Management. 2020; 1–31.

[70] Ragin CC, Patros T, Strand SI, Rubinson C. User’s guide to fuzzy-set/qualitative comparative analysis. University of Arizona. 2008; 87: 1–87.

[71] Ragin CC. Qualitative comparative analysis using fuzzy sets (fsQCA). Configurational comparative methods: qualitative comparative analysis (QCA) and related techniques. 2009; 51: 87–121.

[72] Kraus S, Ribeiro-Soriano D, Schüssler M. Fuzzy-set qualitative comparative analysis (fsQCA) in entrepreneurship and innovation research—the rise of a method. International Entrepreneurship and Management Journal. 2018; 14: 15–33.

[73] Schneider CQ. Realists and Idealists in QCA. Political Analysis. 2018; 26: 246–254.

[74] Schneider CQ, Wagemann C. Standards of good practice in qualitative comparative analysis (QCA) and fuzzy-sets. Comparative Sociology. 2010; 9: 397–418.

[75] Greckhamer T, Misangyi VF, Fiss PC. The two QCAs: from a small-N to a large-N set theoretic approach. Configurational theory and Methods in Organizational Research, Emerald Group Publishing Limited. 2013; 38: 49–75.

[76] Fiss PC. Building better causal theories: a fuzzy set approach to typologies in organization research. Academy of Management Journal. 2011; 54: 393–420.

[77] Cruz CM, Lamb MM, Giri P, Vanderburg J, Ferrarone P, Bhattarai S, et al. Perceptions, attitudes, and knowledge of teachers serving as mental health lay counselors in a low and middle income country: a mixed methods pragmatic pilot study. International Journal of Mental Health Systems. 2021; 15: 40.

[78] Akin U. Exploring the relationship between emotional labor and organizational commitment levels of teachers. Eurasian Journal of Educational Research. 2021; 91: 61–82.

[79] Hassan N, Yaakob SA, Mat Halif M, Abdul Aziz R, Abdul Majid A, Sumardi NA. The effects of technostress creators and organizational commitment among school teachers. Asian Journal of University Education. 2019; 15: 92–102.

[80] Magistra SN, Santosa S, Indriayu M. Effect of self-efficacy and technostress on teacher performance through organizational commitments. Dinamika Pendidikan. 2021; 16: 75–82.

[81] Wahyuni EAB, Wening C. Investigating the effect of forced technology use on teachers’ stress and mental health during the covid-19 pandemic in indonesia. proceeding: 2nd auckland international conference on social sciences, education, entrepreneurship and technology. Auckland, New Zealand and 24–25 November 2021. New Zealand Global Academic Trust (NZGAT): New Zealand. 2021.

[82] Dragano N, Lunau T. Technostress at work and mental health: concepts and research results. Current Opinion in Psychiatry. 2020; 33: 407–413.

[83] Khan AA, Jamil A, Bakhsh K. Role of organizational environment in reducing the effect of techno-stress on work behavior of the university teachers. Global Social Sciences Review. 2020; V: 313–321.

[84] Yao N, Wang Q. Technostress from smartphone use and its impact on university students’ sleep quality and academic performance. The Asia-Pacific Education Researcher. 2022; 1–10.

[85] Upadhyaya P, Vrinda. Impact of technostress on academic productivity of university students. Education and Information Technologies. 2021; 26: 1647–1664.

[86] Woodside AG. Embraceꞏperformꞏmodel: complexity theory, contrarian case analysis, and multiple realities. Journal of Business Research. 2014; 67: 2495–2503.