Overwhelmed by Technostress? Sensitive Archetypes and Effects in Times of Forced Digitalization.

This paper explores technostress and its dimensions, assessing the relationship with possible negative effects in the individual, social and professional sphere. The study uses a self-reported approach of undergraduate students in Spain (n = 337), forced to follow their academic life by using technology comprehensively because of social distancing, as a public health action necessary to reduce the spread of COVID-19. The analysis, based on the exploration of a system of archetypes of the use of social networks, presents insights into contemporary technostress management as a new approach that can suppose opportunities for the optimization of prevention plans. Pearson's correlation coefficients and structural equation modeling based on partial least squares (SEM-PLS) were the methods used for achieving the goals. The results reveal valid and reliable measures where technostress has a high impact on the individual sphere of students and there is a significant relationship between the type of user and techno-anxiety. The conclusions point to the imperative for developing a deeper understanding of technostress by archetypes, in both a higher education context (as antecedent) and the world of work, in an irreversible move towards a digital economy.

Tecnoestrés en población mexicana y su relación con variables sociodemográficas y laborales / Technostress in the Mexican population and its relationship with sociodemographic and labor variables

Resumen Objetivo: Medir la relación entre variables sociodemográficas, variables laborales y la frecuencia del uso de las tecnologías, con el nivel de tecnoansiedad, tecnofatiga y tecnoadicción como experiencias del tecnoestrés, en una muestra de adolescentes, jóvenes y adultos mexicanos. Método: Se aplicaron las escalas para medir tecnoestrés y tecnoadicción de Cazares & Villavicencio (2019) y un cuestionario de variables sociodemográficas y laborales de elaboración propia, a un total de 981 participantes mexicanos entre 13 y 69 años, utilizando la herramienta de formularios de Google. Los datos obtenidos fueron sometidos a un análisis de nivel descriptivo, correlacional e inferencial (Kerlinger & Lee, 2002), con ayuda del programa estadístico SPSS v.20. Resultados: Respecto a la tecnofatiga, los resultados arrojaron diferencias significativas por sexo (U = 104026.50, p=.037) y antigüedad en el trabajo [χ2(3) = 11.213, p = .011] y una significancia marginal por estado civil (U = 78329.00, p=.058). En cuanto a la tecnoadicción, se encontraron diferencias significativas por estado civil (U = 76121.50, p=.012) y ocupación [χ2(2) = 4.698, p =.008]. Con relación a la tecnoansiedad, fueron arrojadas diferencias significativas por tipo de empresa (U = 61348.00, p=.049). Finalmente, se encontró que las personas con mayor nivel de escolaridad, los directivos y los empresarios independientes, presentaron mayor tecnoansiedad, tecnofatiga y tecnoadicción. Conclusiones: Los resultados permiten afirmar que en México existe la presencia de tecnoestrés. Además, se demuestra la relación entre las experiencias del tecnoestrés y variables sociodemográficas (sexo, estado civil, ocupación y escolaridad) y laborales (antigüedad laboral, tipo de empresa y nivel de puesto). Los resultados constituyen las primeras aportaciones de la investigación del tecnoestrés en México, país que impulsa el uso de la tecnología.

Abstract Objective: To measure the relationship between sociodemographic variables, labor variables, and technology frequency of use with the level of technostress experiences such as techno-anxiety, techno-fatigue, and techno-addiction, using a sample of Mexican adolescents, youth, and adults. Method: The participants of the study were 981 Mexican nationals aged 13-69. The scales implemented to measure technostress and techno-addiction were the ones used in Cazares & Villavicencio (2019) and a sociodemographic and labor variables questionnaire created by the authors, implemented using Google's form tool. Data obtained were subjected to a descriptive, correlational, and inferential level analysis (Kerlinger & Lee, 2002), using the statistical software SPSS v.20. Results: Regarding techno-fatigue, the results showed significant differences on the basis of sex (U = 104026.50, p = 0.037) and seniority [χ2(3) = 11.213, p = 0.011] and a marginal significance on the basis of marital status (U = 78329.00, p = .058). Regarding techno-addiction, significant differences were found on the basis of marital status (U = 76121.50, p = 0.012) and occupation [χ2(2) = 4.698, p = 0.008]. Regarding techno-anxiety, significant differences were found on the basis of company type (U = 61348.00, p = 0.049). Finally, it was found that people who received better schooling, such as directors and independent entrepreneurs, showed greater techno-anxiety, techno-fatigue, and techno-addiction. Conclusions: The results confirm that technostress is prevalent in Mexico. In addition, there is a confirmed relationship between technostress experiences, sociodemographic variables (sex, marital status, occupation, and schooling), and labor variables (seniority, company type, and position level). The results constitute the first technostress research contributions in Mexico, a country that encourages the use of technology.

Data set on coping strategies in the digital age: The role of psychological well-being and social capital among university students in Java Timor, Surabaya, Indonesia.

The data article investigates the role of coping strategies, psychological and social well-being in the time of stress due to the effects of technology. Increased technology in the life of students introduces complexities, uncertainty, and overload in higher education institutes. This data provides an ideal research scope for examining the effects of coping strategies on social and psychological well-being. The present dataset includes three hundred and one (301) survey questionnaires from university students in Surabaya city, Java Timor province, by using simple random sampling techniques. This article includes information on reliability and factor loadings, as well as results of regression analyses.