TRAINING AND READS

Training and educational materials

MENHIR is a Research and Innovation Staff Exchange (RISE) project. The RISE programme represents a unique opportunity for individuals to expand their horizons, enlarge their networks, receive innovative research training and develop new career opportunities.

Thus, one of the main dimensions of MENHIR is training doctoral researchers, post-doctoral fellows as well as technicians, managerial and administrative staff in the multiple disciplines involved, which include information and communication technologies, psychology and cognitive science, conversational systems, user and conversation modelling, knowledge representation, storage and annotation, and cross-modal analysis.

The training materials developed within MENHIR are shared here openly for anybody who is interested in these topics.

Conversational systems for mental e-health

The materials presented in this section have been generated for the MENHIR 2020 Summer Doctoral School. You can find all the details in the Doctoral School website.

https://youtu.be/mheapFTw6lM

Open Educational resources

MENHIR Scientific publications, videos and slides

You can find our scientific publications in the dissemination section, and videos and slides at the end of the downloads section.

Training events organized by MENHIR

MENHIR International Doctoral Summer School in Conversational Systems for Mental e-health

Dates: 5-9 October 2020 Web: https://menhir-project.eu/index.php/summer-school-home/ The summer school on Conversational Systems for Mental e-health aims to provide innovative training for early stage researchers ​ (ESR) ​ in the application of conversational systems to the e-health and wellbeing domains​ . The school is mainly targeting postgraduate students (PhD and master), but it is also open …

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Training on Open Educational Resources

Zoraida Callejas has participated as lecturer in the course “Digital Educational Resources in the Universitary Context”, as part of the Plan for Teacher Training and Innovation of the University of Granada. She has described Creative Common (CC) licences, explained how to search for CC multimedia resources, and how to use them. She has also introduced …

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Fería de las ingenierías

MENHIR inspiring scientific and technological vocations

Our colleague David Griol from University of Granada (UGR) has participated today in the event Feria de las Ingenierías, organized by UGR to develop scientific and technological vocations in middle and high school students. The students have visited different schools at UGR related to science and technology studies, where they have been engaged in different …

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RTTHSS2019: Summer School on Speech Technologies

María Inés Torres (UPV) will give a lecture on VoiceBots in the RTTH Summer School 2019 (RTTHSS2019). The school is sponsored by the Spanish Red Temática en Tecnologías del Habla (RTTH) and organized by the Speech and Natural Language Technologies Department of Vicomtech. The RTTHSS2019 will take place in Donostia-San Sebastián (Spain), from July 2nd to July 5th …

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Reading list

We have a Zotero group to share interesting papers, books, and web pages related to MENHIR topics. The contents of the group are public and listed below. You can also check them here.

If you want to know about the publications produced within MENHIR, please check the dissemination section or subscribe to our newsletter.

Kraus, M., Wagner, N., Callejas, Z., & Minker, W. (2021). The Role of Trust in Proactive Conversational Assistants. IEEE Access, 9, 112821–112836. https://doi.org/10.1109/ACCESS.2021.3103893
Greco, C., Matarazzo, O., Cordasco, G., Vinciarelli, A., Callejas, Z., & Esposito, A. (2021). Discriminative Power of EEG-Based Biomarkers in Major Depressive Disorder: A Systematic Review. IEEE Access, 9, 112850–112870. https://doi.org/10.1109/ACCESS.2021.3103047
Callejas, Z., & Griol, D. (2021). Conversational Agents for Mental Health and Wellbeing. In T. Lopez-Soto (Ed.), Dialog Systems: A Perspective from Language, Logic and Computation (pp. 219–244). Springer International Publishing. https://doi.org/10.1007/978-3-030-61438-6_11
D’Alfonso, S. (2020). AI in mental health. Current Opinion in Psychology, 36, 112–117. https://doi.org/10.1016/j.copsyc.2020.04.005
McTear, M. (2020). Conversational AI: Dialogue Systems, Conversational Agents, and Chatbots. Morgan & Claypool.
Vaughn, L. M., & Jacquez, F. (2020). Participatory Research Methods – Choice Points in the Research Process. Journal of Participatory Research Methods, 1(1), 13244. https://doi.org/10.35844/001c.13244
Kearns, W. R., Kaura, N., Divina, M., Vo, C., Si, D., Ward, T., & Yuwen, W. (2020). A Wizard-of-Oz Interface and Persona-based Methodology for Collecting Health Counseling Dialog. Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, 1–9. https://doi.org/10.1145/3334480.3382902
Fusar-Poli, P., Salazar de Pablo, G., De Micheli, A., Nieman, D. H., Correll, C. U., Kessing, L. V., Pfennig, A., Bechdolf, A., Borgwardt, S., Arango, C., & van Amelsvoort, T. (2020). What is good mental health? A scoping review. European Neuropsychopharmacology, 31, 33–46. https://doi.org/10.1016/j.euroneuro.2019.12.105
Yalamanchili, B., Kota, N. S., Abbaraju, M. S., Nadella, V. S. S., & Alluri, S. V. (2020). Real-time Acoustic based Depression Detection using Machine Learning Techniques. 2020 International Conference on Emerging Trends in Information Technology and Engineering (Ic-ETITE), 1–6. https://doi.org/10.1109/ic-ETITE47903.2020.394
Abd-Alrazaq, A., Safi, Z., Alajlani, M., Warren, J., Househ, M., & Denecke, K. (2020). Technical Metrics Used to Evaluate Health Care Chatbots: Scoping Review. Journal of Medical Internet Research, 22(6), undefined-undefined. https://doi.org/10.2196/18301
Abd-Alrazaq, A. A., Rababeh, A., Alajlani, M., Bewick, B. M., & Househ, M. (2020). Effectiveness and Safety of Using Chatbots to Improve Mental Health: Systematic Review and Meta-Analysis. Journal of Medical Internet Research, 22(7), undefined-undefined. https://doi.org/10.2196/16021 Download
Denecke, K., Vaaheesan, S., & Arulnathan, A. (2020). A Mental Health Chatbot for Regulating Emotions (SERMO) - Concept and Usability Test. IEEE Transactions on Emerging Topics in Computing, 1–1. https://doi.org/10.1109/TETC.2020.2974478
Abd-alrazaq, A. A., Alajlani, M., Alalwan, A. A., Bewick, B. M., Gardner, P., & Househ, M. (2019). An overview of the features of chatbots in mental health: A scoping review. International Journal of Medical Informatics, 132, 103978. https://doi.org/10.1016/j.ijmedinf.2019.103978
Montenegro, J. L. Z., da Costa, C. A., & da Rosa Righi, R. (2019). Survey of conversational agents in health. Expert Systems with Applications, 129, 56–67. https://doi.org/10.1016/j.eswa.2019.03.054
Bendig, E., Erb, B., Schulze-Thuesing, L., & Baumeister, H. (2019). The Next Generation: Chatbots in Clinical Psychology and Psychotherapy to Foster Mental Health – A Scoping Review. Verhaltenstherapie, 1–13. https://doi.org/10.1159/000501812 Download
Vaidyam, A. N., Wisniewski, H., Halamka, J. D., Kashavan, M. S., & Torous, J. B. (2019). Chatbots and Conversational Agents in Mental Health: A Review of the Psychiatric Landscape. The Canadian Journal of Psychiatry, 64(7), 456–464. https://doi.org/10.1177/0706743719828977
Chen, A. T., Wu, S., Tomasino, K. N., Lattie, E. G., & Mohr, D. C. (2019). A multi-faceted approach to characterizing user behavior and experience in a digital mental health intervention. Journal of Biomedical Informatics, 94, 103187. https://doi.org/10.1016/j.jbi.2019.103187 Download
Lee, M., Ackermans, S., van As, N., Chang, H., Lucas, E., & IJsselsteijn, W. (2019). Caring for Vincent: A Chatbot for Self-Compassion. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 1–13. https://doi.org/10.1145/3290605.3300932
11 Healthcare Chatbots Which Improve Patient Experience. (2019, March 9). ReferralMD. https://getreferralmd.com/2019/03/11-healthcare-chatbots-that-improve-patient-experience/
Nadarzynski, T., Miles, O., Cowie, A., & Ridge, D. (2019). Acceptability of artificial intelligence (AI)-led chatbot services in healthcare: A mixed-methods study. DIGITAL HEALTH, 5, 2055207619871808. https://doi.org/10.1177/2055207619871808 Download
Baumel, A., Muench, F., Edan, S., & Kane, J. M. (2019). Objective User Engagement With Mental Health Apps: Systematic Search and Panel-Based Usage Analysis. Journal of Medical Internet Research, 21(9), e14567. https://doi.org/10.2196/14567 Download
Code of conduct for data-driven health and care technology. (2019). GOV.UK. https://www.gov.uk/government/publications/code-of-conduct-for-data-driven-health-and-care-technology
Palanica, A., Flaschner, P., Thommandram, A., Li, M., & Fossat, Y. (2019). Physicians’ Perceptions of Chatbots in Health Care: Cross-Sectional Web-Based Survey. Journal of Medical Internet Research, 21(4), e12887. https://doi.org/10.2196/12887
D’Alfonso, S., Carpenter, N., & Alvarez-Jimenez, M. (2018). Making the MOST out of smartphone opportunities for mental health. Proceedings of the 30th Australian Conference on Computer-Human Interaction, 577–581. https://doi.org/10.1145/3292147.3292230 Download
Ayoola, I., Wetzels, M., Peters, P., van Berlo, S., & Feijs, L. (2018). Do CHANGE platform: A service-based architecture for secure aggregation and distribution of health and wellbeing data. International Journal of Medical Informatics, 117, 103–111. https://doi.org/10.1016/j.ijmedinf.2018.06.004
Laranjo, L., Dunn, A. G., Tong, H. L., Kocaballi, A. B., Chen, J., Bashir, R., Surian, D., Gallego, B., Magrabi, F., Lau, A. Y. S., & Coiera, E. (2018). Conversational agents in healthcare: a systematic review. Journal of the American Medical Informatics Association : JAMIA, 25(9), 1248–1258. https://doi.org/10.1093/jamia/ocy072
Ravichander, A., & Black, A. W. (2018). An Empirical Study of Self-Disclosure in Spoken Dialogue Systems. 253–263. https://aclweb.org/anthology/papers/W/W18/W18-5030/
Maimone, R., Guerini, M., Dragoni, M., Bailoni, T., & Eccher, C. (2018). PerKApp: A general purpose persuasion architecture for healthy lifestyles. Journal of Biomedical Informatics, 82, 70–87. https://doi.org/10.1016/j.jbi.2018.04.010
Kyriazakos, S., Valentini, V., Cesario, A., & Zachariae, R. (2018). FORECAST – A cloud-based personalized intelligent virtual coaching platform for the well-being of cancer patients. Clinical and Translational Radiation Oncology, 8, 50–59. https://doi.org/10.1016/j.ctro.2017.11.006
Morris, R. R., Kouddous, K., Kshirsagar, R., & Schueller, S. M. (2018). Towards an Artificially Empathic Conversational Agent for Mental Health Applications: System Design and User Perceptions. Journal of Medical Internet Research, 20(6), e10148. https://doi.org/10.2196/10148
Kopeć, W., Nielek, R., & Wierzbicki, A. (2018). Guidelines towards better participation of older adults in software development processes using a new SPIRAL method and participatory approach. Proceedings of the 11th International Workshop on Cooperative and Human Aspects of Software Engineering  - CHASE ’18, 49–56. https://doi.org/10.1145/3195836.3195840
Kocielnik, R., Hsieh, G., & Avrahami, D. (2018). Helping Users Reflect on Their Own Health-Related Behaviors. In R. J. Moore, M. H. Szymanski, R. Arar, & G.-J. Ren (Eds.), Studies in Conversational UX Design (pp. 85–115). Springer International Publishing. https://doi.org/10.1007/978-3-319-95579-7_5
Bickmore, T., Trinh, H., Asadi, R., & Olafsson, S. (2018). Safety First: Conversational Agents for Health Care. In R. J. Moore, M. H. Szymanski, R. Arar, & G.-J. Ren (Eds.), Studies in Conversational UX Design (pp. 33–57). Springer International Publishing. https://doi.org/10.1007/978-3-319-95579-7_3
Payton, F. C., Yarger, L. K., & Pinter, A. T. (2018). Text Mining Mental Health Reports for Issues Impacting Today’s College Students: Qualitative Study. JMIR Mental Health, 5(4), e10032. https://doi.org/10.2196/10032
Ly, K. H., Ly, A.-M., & Andersson, G. (2017). A fully automated conversational agent for promoting mental well-being: A pilot RCT using mixed methods. Internet Interventions, 10, 39–46. https://doi.org/10.1016/j.invent.2017.10.002 Download
Sebastian, J., & Richards, D. (2017). Changing stigmatizing attitudes to mental health via education and contact with embodied conversational agents. Computers in Human Behavior, 73, 479–488. https://doi.org/10.1016/j.chb.2017.03.071
Mohr, D. C., Weingardt, K. R., Reddy, M., & Schueller, S. M. (2017). Three Problems With Current Digital Mental Health Research . . . and Three Things We Can Do About Them. Psychiatric Services, 68(5), 427–429. https://doi.org/10.1176/appi.ps.201600541 Download
Lui, J. H. L., Marcus, D. K., & Barry, C. T. (2017). Evidence-based apps? A review of mental health mobile applications in a psychotherapy context. Professional Psychology: Research and Practice, 48(3), 199–210. https://doi.org/10.1037/pro0000122
Sedrati, H., Nejjari, C., Chaqsare, S., & Ghazal, H. (2016). Mental and Physical Mobile Health Apps: Review. Procedia Computer Science, 100, 900–906. https://doi.org/10.1016/j.procs.2016.09.241 Download
Menger, V., Spruit, M., Hagoort, K., & Scheepers, F. (2016). Transitioning to a Data Driven Mental Health Practice: Collaborative Expert Sessions for Knowledge and Hypothesis Finding. Computational and Mathematical Methods in Medicine, 2016. https://doi.org/10.1155/2016/9089321
Kamdar, M. R., & Wu, M. J. (2016). PRISM: A DATA-DRIVEN PLATFORM FOR MONITORING MENTAL HEALTH. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 21, 333–344.
Saeb, S., Zhang, M., Karr, C. J., Schueller, S. M., Corden, M. E., Kording, K. P., & Mohr, D. C. (2015). Mobile phone sensor correlates of depressive symptom severity in daily-life behavior: An exploratory study. Journal of Medical Internet Research, 17(7), undefined-undefined. https://doi.org/10.2196/jmir.4273
Jones, R. H. (2015). Discourse and Health Communication. In The Handbook of Discourse Analysis (pp. 841–857). John Wiley & Sons, Ltd. https://doi.org/10.1002/9781118584194.ch39
Hunt, D., & Harvey, K. (2015). Health Communication and Corpus Linguistics: Using Corpus Tools to Analyse Eating Disorder Discourse Online. In P. Baker & T. McEnery (Eds.), Corpora and Discourse Studies: Integrating Discourse and Corpora (pp. 134–154). Palgrave Macmillan UK. https://doi.org/10.1057/9781137431738_7
Hermens, H., op den Akker, H., Tabak, M., Wijsman, J., & Vollenbroek, M. (2014). Personalized Coaching Systems to support healthy behavior in people with chronic conditions. Journal of Electromyography and Kinesiology, 24(6), 815–826. https://doi.org/10.1016/j.jelekin.2014.10.003
Gratch, J., Artstein, R., Lucas, G., Stratou, G., Scherer, S., Nazarian, A., Wood, R., Boberg, J., DeVault, D., Marsella, S., Traum, D., Rizzo, A., & Morency, L.-P. (2014). The Distress Analysis Interview Corpus of human and computer interviews. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC 2014). LREC. http://ict.usc.edu/pubs/The%20Distress%20Analysis%20Interview%20Corpus%20of%20human%20and%20computer%20interviews.pdf
Papangelis, A., Gatchel, R., Metsis, V., & Makedon, F. (2013). An Adaptive Dialogue System for Assessing Post Traumatic Stress Disorder. Proceedings of the 6th International Conference on PErvasive Technologies Related to Assistive Environments, 49:1–49:4. https://doi.org/10.1145/2504335.2504387
Mohr, D., Cuijpers, P., & Lehman, K. (2011). Supportive Accountability: A Model for Providing Human Support to Enhance Adherence to eHealth Interventions. Journal of Medical Internet Research, 13(1), e30. https://doi.org/10.2196/jmir.1602 Download
Jesus, A. de. (n.d.). Chatbots for Mental Health and Therapy – Comparing 5 Current Apps and Use Cases. Emerj. Retrieved March 10, 2020, from https://emerj.com/ai-application-comparisons/chatbots-mental-health-therapy-comparing-5-current-apps-use-cases/
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