Special Section: Information Technology to Improve Mental Health

[1] Califf C.B., Sarker S., Sarker S., The bright and dark sides of technostress: A mixed-methods study involving healthcare IT, MIS Quarterly, 44, 2, pp. 809-856, (2020)

[2] Chau M., Li T.M.H., Wong P.W.C., Xu J.J., Yip P.S.F., Chen H., Finding people with emotional distress in online social media: A design combining machine learning and rule-based classification, MIS Quarterly, 44, 2, pp. 933-955, (2020)

[3] Cram W.A., Wiener M., Tarafdar M., Benlian A., Examining the impact of algorithmic control on Uber drivers’ technostress, Journal of Management Information Systems, 39, 2, pp. 426-453, (2022)

[4] James T.L., Lowry P.B., Wallace L., Warkentin M., The effect of belongingness on obsessive-compulsive disorder in the use of online social networks, Journal of Management Information Systems, 34, 2, pp. 560-596, (2017)

[5] Peng F., Zhang D., Yan, Z.I Digital Phenotyping-based depression detection in the presence of comorbidity: An uncertainty reasoning approach, Journal of Management Information Systems

[6] Pirkkalainen H., Salo M., Tarafdar M., Makkonen M., Deliberate or instinctive? Proactive and reactive coping for technostress, Journal of Management Information Systems, 36, 4, pp. 1179-1212, (2019)

[7] Reinert M., Fritze D., Nguyen T., The State of Mental Health in America 2023, Mental Health America, (2022)

[8] Spohrer K., Fallon M., Hoehle H., Heinzl A., Designing effective mobile health apps: Does combining behavior change techniques really create synergies?, Journal of Management Information Systems, 38, 2, pp. 517-545, (2021)

[9] Tutun S., Topuz K., Tosyali A., Bhattacherjee A., Li K., Explainable artificial intelligence for mental disorder screening: A computational design science approach, Journal of Management Information Systems

[10] Windeler J.B., Maruping L., Venkatesh V., Technical systems development risk factors: The role of empowering leadership in lowering developers’ stress, Information Systems Research, 28, 4, pp. 775-796, (2017)

[1] Califf C.B., Sarker S., Sarker S., The bright and dark sides of technostress: A mixed-methods study involving healthcare IT, MIS Quarterly, 44, 2, pp. 809-856, (2020)

[2] Chau M., Li T.M.H., Wong P.W.C., Xu J.J., Yip P.S.F., Chen H., Finding people with emotional distress in online social media: A design combining machine learning and rule-based classification, MIS Quarterly, 44, 2, pp. 933-955, (2020)

[3] Cram W.A., Wiener M., Tarafdar M., Benlian A., Examining the impact of algorithmic control on Uber drivers’ technostress, Journal of Management Information Systems, 39, 2, pp. 426-453, (2022)

[4] James T.L., Lowry P.B., Wallace L., Warkentin M., The effect of belongingness on obsessive-compulsive disorder in the use of online social networks, Journal of Management Information Systems, 34, 2, pp. 560-596, (2017)

[5] Peng F., Zhang D., Yan, Z.I Digital Phenotyping-based depression detection in the presence of comorbidity: An uncertainty reasoning approach, Journal of Management Information Systems

[6] Pirkkalainen H., Salo M., Tarafdar M., Makkonen M., Deliberate or instinctive? Proactive and reactive coping for technostress, Journal of Management Information Systems, 36, 4, pp. 1179-1212, (2019)

[7] Reinert M., Fritze D., Nguyen T., The State of Mental Health in America 2023, Mental Health America, (2022)

[8] Spohrer K., Fallon M., Hoehle H., Heinzl A., Designing effective mobile health apps: Does combining behavior change techniques really create synergies?, Journal of Management Information Systems, 38, 2, pp. 517-545, (2021)

[9] Tutun S., Topuz K., Tosyali A., Bhattacherjee A., Li K., Explainable artificial intelligence for mental disorder screening: A computational design science approach, Journal of Management Information Systems

[10] Windeler J.B., Maruping L., Venkatesh V., Technical systems development risk factors: The role of empowering leadership in lowering developers’ stress, Information Systems Research, 28, 4, pp. 775-796, (2017)