“I am always tired”: Perceptions on Mental Health and Productivity Metrics
Resumo
This study aims to gather insights from tech and health professionals regarding their perceptions about twelve proposed metrics designed to measure mental health and productivity in software development. These professionals were surveyed to rate the usefulness and appropriateness of each proposed metric. The findings offer valuable insights into the factors that influence the perceived utility and likability of these metrics. By leveraging developers perceptions, we can develop more effective strategies to promote a healthier and more productive work environment in software development. Thus, this study paves the way for the implementation of more targeted interventions and best practices within the industry.Referências
Canedo, E. D. and Santos, G. A. (2019). Factors affecting software development productivity: An empirical study. In Proceedings of the XXXIII Brazilian Symposium on Software Engineering, pages 307–316.
Ferran, F. M., Prudente, M. S., and Aguja, S. E. (2021). Google forms-based lesson playlist: Examining students’ attitude towards its use and its effect on academic performance. In Proceedings of the 2021 12th International Conference on E-Education, E-Business, E-Management, and E-Learning, pages 131–139.
Guerrero-Calvache, M. and Hernández, G. (2022). Team productivity in agile software development: a systematic mapping study. In International Conference on Applied Informatics, pages 455–471. Springer.
Islam, M. R. and Zibran, M. F. (2018). Sentistrength-se: Exploiting domain specificity for improved sentiment analysis in software engineering text. Journal of Systems and Software, 145:125–146.
Khalid, S., Qamar, U., Rahseed, U., and Butt, W. H. (2022). Relationship between organization’s physical and psychological environment and employees’ mental satisfaction: An empirical analysis of employee turnover in software industry. In 2022 16th International Conference on Open Source Systems and Technologies (ICOSST), pages 1–6.
Melo, C., Cruzes, D. S., Kon, F., and Conradi, R. (2011). Agile team perceptions of productivity factors. In 2011 Agile Conference, pages 57–66. IEEE.
Melo, C., Cruzes, D. S., Kon, F., and Conradi, R. (2013). Interpretative case studies on agile team productivity and management. Information and Software Technology, 55(2):412–427.
Mota, J. S., Tives, H. A., and Canedo, E. D. (2021). Tool for measuring productivity in software development teams. Information, 12(10):396.
Murphy-Hill, E., Jaspan, C., Sadowski, C., Shepherd, D., Phillips, M., Winter, C., Knight, A., Smith, E., and Jorde, M. (2019). What predicts software developers’ productivity? IEEE Transactions on Software Engineering, 47(3):582–594.
Oliveira, E., Fernandes, E., Steinmacher, I., Cristo, M., Conte, T., and Garcia, A. (2020). Code and commit metrics of developer productivity: a study on team leaders perceptions. Empirical Software Engineering, 25:2519–2549.
Organization, W. H. (2024). Mental health.
Woods, K. (2015). Exploring the relationship between employee turnover rate and customer satisfaction levels. The Exchange, 4(1).
Ferran, F. M., Prudente, M. S., and Aguja, S. E. (2021). Google forms-based lesson playlist: Examining students’ attitude towards its use and its effect on academic performance. In Proceedings of the 2021 12th International Conference on E-Education, E-Business, E-Management, and E-Learning, pages 131–139.
Guerrero-Calvache, M. and Hernández, G. (2022). Team productivity in agile software development: a systematic mapping study. In International Conference on Applied Informatics, pages 455–471. Springer.
Islam, M. R. and Zibran, M. F. (2018). Sentistrength-se: Exploiting domain specificity for improved sentiment analysis in software engineering text. Journal of Systems and Software, 145:125–146.
Khalid, S., Qamar, U., Rahseed, U., and Butt, W. H. (2022). Relationship between organization’s physical and psychological environment and employees’ mental satisfaction: An empirical analysis of employee turnover in software industry. In 2022 16th International Conference on Open Source Systems and Technologies (ICOSST), pages 1–6.
Melo, C., Cruzes, D. S., Kon, F., and Conradi, R. (2011). Agile team perceptions of productivity factors. In 2011 Agile Conference, pages 57–66. IEEE.
Melo, C., Cruzes, D. S., Kon, F., and Conradi, R. (2013). Interpretative case studies on agile team productivity and management. Information and Software Technology, 55(2):412–427.
Mota, J. S., Tives, H. A., and Canedo, E. D. (2021). Tool for measuring productivity in software development teams. Information, 12(10):396.
Murphy-Hill, E., Jaspan, C., Sadowski, C., Shepherd, D., Phillips, M., Winter, C., Knight, A., Smith, E., and Jorde, M. (2019). What predicts software developers’ productivity? IEEE Transactions on Software Engineering, 47(3):582–594.
Oliveira, E., Fernandes, E., Steinmacher, I., Cristo, M., Conte, T., and Garcia, A. (2020). Code and commit metrics of developer productivity: a study on team leaders perceptions. Empirical Software Engineering, 25:2519–2549.
Organization, W. H. (2024). Mental health.
Woods, K. (2015). Exploring the relationship between employee turnover rate and customer satisfaction levels. The Exchange, 4(1).
Publicado
30/09/2024
Como Citar
AZEVEDO, Júlia; SOUSA, Theo; ARRIEL, Johny; MANN, Paulo; GARCIA, Alessandro; PEREIRA, Juliana Alves.
“I am always tired”: Perceptions on Mental Health and Productivity Metrics. In: CONCURSO DE TRABALHOS DE INICIAÇÃO CIENTÍFICA - CONGRESSO BRASILEIRO DE SOFTWARE: TEORIA E PRÁTICA (CBSOFT), 15. , 2024, Curitiba/PR.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 79-88.
DOI: https://doi.org/10.5753/cbsoft_estendido.2024.4105.
