The impact of scaffolded and non-scaffolded suicidal virtual human interaction training on clinician emotional self-awareness, empathic communication, and clinical efficacy.
Clinical efficacy
Negative emotional responses
Scaffolded instructions
Suicidal virtual patient
Verbal empathic communication training
Journal
BMC medical education
ISSN: 1472-6920
Titre abrégé: BMC Med Educ
Pays: England
ID NLM: 101088679
Informations de publication
Date de publication:
15 Apr 2024
15 Apr 2024
Historique:
received:
14
08
2023
accepted:
29
03
2024
medline:
16
4
2024
pubmed:
16
4
2024
entrez:
15
4
2024
Statut:
epublish
Résumé
Clinicians working with patients at risk of suicide often experience high stress, which can result in negative emotional responses (NERs). Such negative emotional responses may lead to less empathic communication (EC) and unintentional rejection of the patient, potentially damaging the therapeutic alliance and adversely impacting suicidal outcomes. Therefore, clinicians need training to effectively manage negative emotions toward suicidal patients to improve suicidal outcomes. This study investigated the impact of virtual human interaction (VHI) training on clinicians' self-awareness of their negative emotional responses, assessed by the Therapist Response Questionnaire Suicide Form, clinicians' verbal empathic communication assessed by the Empathic Communication and Coding System, and clinical efficacy (CE). Clinical efficacy was assessed by the likelihood of subsequent appointments, perceived helpfulness, and overall interaction satisfaction as rated by individuals with lived experience of suicide attempts. Two conditions of virtual human interactions were used: one with instructions on verbal empathic communication and reminders to report negative emotional responses during the interaction (scaffolded); and the other with no such instructions or reminders (non-scaffolded). Both conditions provided pre-interaction instructions and post-interaction feedback aimed at improving clinicians' empathic communication and management of negative emotions. Sixty-two clinicians participated in three virtual human interaction sessions under one of the two conditions. Linear mixed models were utilized to evaluate the impact on clinicians' negative emotional responses, verbal empathic communication, and clinical efficacy; and to determine changes in these outcomes over time, as moderated by the training conditions. Clinician participants' negative emotional responses decreased after two training sessions with virtual human interactions in both conditions. Participants in the scaffolded condition exhibited enhanced empathic communication after one training session, while two sessions were required for participants in the non-scaffolded condition. Surprisingly, after two training sessions, clinical efficacy was improved in the non-scaffolded group, while no similar improvements were observed in the scaffolded group. Lower clinical efficacy after virtual human interaction training in clinicians with higher verbal empathic communication suggests that nonverbal expressions of empathy are critical when interacting with suicidal patients. Future work should explore virtual human interaction training in both nonverbal and verbal empathic communication.
Sections du résumé
BACKGROUND
BACKGROUND
Clinicians working with patients at risk of suicide often experience high stress, which can result in negative emotional responses (NERs). Such negative emotional responses may lead to less empathic communication (EC) and unintentional rejection of the patient, potentially damaging the therapeutic alliance and adversely impacting suicidal outcomes. Therefore, clinicians need training to effectively manage negative emotions toward suicidal patients to improve suicidal outcomes.
METHODS
METHODS
This study investigated the impact of virtual human interaction (VHI) training on clinicians' self-awareness of their negative emotional responses, assessed by the Therapist Response Questionnaire Suicide Form, clinicians' verbal empathic communication assessed by the Empathic Communication and Coding System, and clinical efficacy (CE). Clinical efficacy was assessed by the likelihood of subsequent appointments, perceived helpfulness, and overall interaction satisfaction as rated by individuals with lived experience of suicide attempts. Two conditions of virtual human interactions were used: one with instructions on verbal empathic communication and reminders to report negative emotional responses during the interaction (scaffolded); and the other with no such instructions or reminders (non-scaffolded). Both conditions provided pre-interaction instructions and post-interaction feedback aimed at improving clinicians' empathic communication and management of negative emotions. Sixty-two clinicians participated in three virtual human interaction sessions under one of the two conditions. Linear mixed models were utilized to evaluate the impact on clinicians' negative emotional responses, verbal empathic communication, and clinical efficacy; and to determine changes in these outcomes over time, as moderated by the training conditions.
RESULTS
RESULTS
Clinician participants' negative emotional responses decreased after two training sessions with virtual human interactions in both conditions. Participants in the scaffolded condition exhibited enhanced empathic communication after one training session, while two sessions were required for participants in the non-scaffolded condition. Surprisingly, after two training sessions, clinical efficacy was improved in the non-scaffolded group, while no similar improvements were observed in the scaffolded group.
CONCLUSION
CONCLUSIONS
Lower clinical efficacy after virtual human interaction training in clinicians with higher verbal empathic communication suggests that nonverbal expressions of empathy are critical when interacting with suicidal patients. Future work should explore virtual human interaction training in both nonverbal and verbal empathic communication.
Identifiants
pubmed: 38622653
doi: 10.1186/s12909-024-05371-9
pii: 10.1186/s12909-024-05371-9
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
413Subventions
Organisme : American Foundation for Suicide Prevention
ID : LSRG-1-050-18
Organisme : American Foundation for Suicide Prevention
ID : LSRG-1-050-18
Organisme : American Foundation for Suicide Prevention
ID : LSRG-1-050-18
Organisme : American Foundation for Suicide Prevention
ID : LSRG-1-050-18
Informations de copyright
© 2024. The Author(s).
Références
Facts About Suicide. Centers for Disease Control and Prevention; 2023. https://www.cdc.gov/suicide/facts/index.html . Accessed 7 July 2023.
Newkirk S. Galynker I. Clinician Emotional Response to Patients at Risk of Suicide: A Review of the Extant Literature. Suicide Risk Assess Prev; 2023. p. 167–81.
Michaud L, Greenway KT, Corbeil S, Bourquin C, Richard-Devantoy S. Countertransference towards suicidal patients: a systematic review. Curr Psychol. 2023;42(1):416–30.
Barzilay S, Yaseen ZS, Hawes M, Gorman B, Altman R, Foster A, et al. Emotional responses to suicidal patients: factor structure, construct, and predictive validity of the Therapist Response Questionnaire-Suicide Form. Front Psychiatry. 2018;9:104.
doi: 10.3389/fpsyt.2018.00104
Yaseen ZS, Galynker II, Cohen LJ, Briggs J. Clinicians’ conflicting emotional responses to high suicide-risk patients–Association with short-term suicide behaviors: a prospective pilot study. Compr Psychiatry. 2017;76:69–78.
doi: 10.1016/j.comppsych.2017.03.013
Hawes M, Yaseen Z, Briggs J, Galynker I. The Modular Assessment of Risk for Imminent Suicide (MARIS): a proof of concept for a multi-informant tool for evaluation of short-term suicide risk. Compr Psychiatry. 2017;72:88–96.
doi: 10.1016/j.comppsych.2016.10.002
Barzilay S, Schuck A, Bloch-Elkouby S, Yaseen ZS, Hawes M, Rosenfield P, et al. Associations between clinicians’ emotional responses, therapeutic alliance, and patient suicidal ideation. Depression Anxiety. 2020;37(3):214–23.
doi: 10.1002/da.22973
Neumann M, Bensing J, Mercer S, Ernstmann N, Ommen O, Pfaff H. Analyzing the “nature” and “specific effectiveness” of clinical empathy: a theoretical overview and contribution towards a theory-based research agenda. Patient Educ Couns. 2009;74(3):339–46.
Kim SS, Kaplowitz S, Johnston MV. The effects of physician empathy on patient satisfaction and compliance. Eval Health Prof. 2004;27(3):237–51.
doi: 10.1177/0163278704267037
Kozlowski D, Hutchinson M, Hurley J, Rowley J, Sutherland J. The role of emotion in clinical decision making: an integrative literature review. BMC Med Educ. 2017;17:1–13.
doi: 10.1186/s12909-017-1089-7
Bijani M, Abedi S, Karimi S, Tehranineshat B. Major challenges and barriers in clinical decision-making as perceived by emergency medical services personnel: a qualitative content analysis. BMC Emerg Med. 2021;21:1–12.
doi: 10.1186/s12873-021-00408-4
Kleinsmith A, Rivera-Gutierrez D, Finney G, Cendan J, Lok B. Understanding empathy training with virtual patients. Comput Hum Behav. 2015;52:151–8.
doi: 10.1016/j.chb.2015.05.033
Stevens A, Hernandez J, Johnsen K, Dickerson R, Raij A, Harrison C, et al. The use of virtual patients to teach medical students history taking and communication skills. Am J Surg. 2006;191(6):806–11.
doi: 10.1016/j.amjsurg.2006.03.002
Olsen JK, Oertel C. Supporting empathy training through virtual patients. In: Artificial Intelligence in Education: 21st International Conference, AIED 2020, Ifrane, Morocco, July 6–10, 2020, Proceedings, Part II 21. Springer; 2020. p. 234–239.
Foster A, Alderman M, Safin D, Aponte X, McCoy K, Caughey M, et al. Teaching suicide risk assessment: spotlight on the therapeutic relationship. Acad Psychiatr. 2021;45:257–61.
doi: 10.1007/s40596-021-01421-2
Bylund CL, Makoul G. Empathic communication and gender in the physician-patient encounter. Patient Educ Couns. 2002;48(3):207–16.
doi: 10.1016/S0738-3991(02)00173-8
Bylund CL, Makoul G. Examining empathy in medical encounters: an observational study using the empathic communication coding system. Health Commun. 2005;18(2):123–40.
doi: 10.1207/s15327027hc1802_2
Foster A, Chaudhary N, Kim T, Waller JL, Wong J, Borish M, et al. Using virtual patients to teach empathy: a randomized controlled study to enhance medical students’ empathic communication. Simul Healthc. 2016;11(3):181–9.
doi: 10.1097/SIH.0000000000000142
Borish M, Cordar A, Foster A, Kim T, Murphy J, Lok B. Utilizing real-time human-assisted virtual humans to increase real-world interaction empathy. In: Proceedings of the 5th Kanesi Engineering and Emotion Research. KEER 2014. Linköping, Sweden: Linköping University Electronic Press; 2014. p. 441–455. Available from: https://ep.liu.se/en/conference-article.aspx?series=ecp&issue=100&Article_No=35 .
Guilera T, Batalla I, Soler-González J. Empathy and specialty preference in medical students. Follow-up study and feedback Educ Méd. 2018;19:153–61.
Barry Issenberg S, Mcgaghie WC, Petrusa ER, Lee Gordon D, Scalese RJ. Features and uses of high-fidelity medical simulations that lead to effective learning: a BEME systematic review. Med Teach. 2005;27(1):10–28.
doi: 10.1080/01421590500046924
Bosse HM, Mohr J, Buss B, Krautter M, Weyrich P, Herzog W, et al. The benefit of repetitive skills training and frequency of expert feedback in the early acquisition of procedural skills. BMC Med Educ. 2015;15:1–10.
doi: 10.1186/s12909-015-0286-5
Vygotsky LS, Cole M. Mind in society: development of higher psychological processes. Harvard University Press; 1978.
Verenikina I. Understanding scaffolding and the ZPD in educational research. University of Wollongong: Research Online, 2003. Available from: https://ro.uow.edu.au/edupapers/381/ .
Wells CG. Dialogic inquiry, vol. 10. Cambridge University Press Cambridge; 1999.
Azevedo R, Hadwin AF. Scaffolding self-regulated learning and metacognition-Implications for the design of computer-based scaffolds. Instr Sci. 2005;33(5/6):367–79.
doi: 10.1007/s11251-005-1272-9
Collins A, et al. Cognitive Apprenticeship: Teaching the Craft of Reading, Writing, and Mathematics. Technical Report No. 403. ERIC; 1987.
Larkin MJ. Using scaffolded instruction to optimize learning. ERIC Clearinghouse on Disabilities and Gifted Education Arlington; 2002.
Jacoby LL. A process dissociation framework: Separating automatic from intentional uses of memory. J Mem Lang. 1991;30(5):513–41.
doi: 10.1016/0749-596X(91)90025-F
Yonelinas AP. The nature of recollection and familiarity: a review of 30 years of research. J Mem Lang. 2002;46(3):441–517.
doi: 10.1006/jmla.2002.2864
Finn B, Metcalfe J. Scaffolding feedback to maximize long-term error correction. Mem Cogn. 2010;38(7):951–61.
doi: 10.3758/MC.38.7.951
Yao H, de Siqueira AG, Bafna A, Peterkin D, Richards J, Rogers ML, et al. A virtual human interaction using scaffolded ping-pong feedback for healthcare learners to practice empathy skills. In: Proceedings of the 22nd ACM International Conference on Intelligent Virtual Agents. IVA ’22. New York, NY, USA: Association for Computing Machinery; 2022. p. 1–8. Available from: https://doi.org/10.1145/3514197.3549621 .
Shah H, Rossen B, Lok B, Londino D, Lind SD, Foster A. Interactive virtual-patient scenarios: an evolving tool in psychiatric education. Acad Psychiatr. 2012;36:146–50.
doi: 10.1176/appi.ap.10030049
Foster A, Harms J, Ange B, Rossen B, Lok B, Lind S, et al. Empathic communication in medical students’ interactions with mental health virtual patient scenarios: a descriptive study using the Empathic Communication Coding System. Austin J Psychiatr Behav Sci. 2014;1(3):6.
Yao H, de Siqueira AG, Foster A, Galynker I, Lok B. Toward Automated Evaluation of Empathetic Responses in Virtual Human Interaction Systems for Mental Health Scenarios. In: Proceedings of the 20th ACM International Conference on Intelligent Virtual Agents. IVA ’20. New York, NY, USA: Association for Computing Machinery; 2020. p. 1–8. Available from: https://doi.org/10.1145/3383652.3423916 .
Galynker I. The suicidal crisis: Clinical guide to the assessment of imminent suicide risk. Oxford University Press; 2023.
Foster A, Robb A, Cordar A, Chaudhary N, Noseworthy D, Lok B. Denise: A virtual patient. MedEdPORTAL. 2015;11:10145.
doi: 10.15766/mep_2374-8265.10145
Foster A, Chaudhary N, Murphy J, Lok B, Waller J, Buckley PF. The use of simulation to teach suicide risk assessment to health profession trainees–rationale, methodology, and a proof of concept demonstration with a virtual patient. Acad Psychiatr. 2015;39:620–9.
doi: 10.1007/s40596-014-0185-9
Jacobs DG, Baldessarini RJ, Conwell Y, Fawcett JA, Horton L, Meltzer H, et al. Assessment and treatment of patients with suicidal behaviors. APA Pract Guidel. 2010;1:183.
Rossen B, Lind S, Lok B. Human-centered distributed conversational modeling: Efficient modeling of robust virtual human conversations. In: Intelligent Virtual Agents: 9th International Conference, IVA 2009 Amsterdam, The Netherlands, September 14-16, 2009 Proceedings 9. Springer; 2009. p. 474–481.
Rossen B, Lok B. A crowdsourcing method to develop virtual human conversational agents. Int J Hum-Comput Stud. 2012;70(4):301–19.
doi: 10.1016/j.ijhcs.2011.11.004
Sabharwal N, Agrawal A. In: Introduction to Google Dialogflow. Berkeley, CA: Apress; 2020. p. 13–54. Available from: https://doi.org/10.1007/978-1-4842-5741-8_2 .
Abdellatif A, Badran K, Costa DE, Shihab E. A comparison of natural language understanding platforms for chatbots in software engineering. IEEE Trans Softw Eng. 2021;48(8):3087–102.
doi: 10.1109/TSE.2021.3078384
Wolf MH, Putnam SM, James SA, Stiles WB. The Medical Interview Satisfaction Scale: development of a scale to measure patient perceptions of physician behavior. J Behav Med. 1978;1(4):391–401. https://doi.org/10.1007/BF00846695 .
Raudenbush SW, Bryk AS. Hierarchical linear models: Applications and data analysis methods, vol. 1. Sage; 2002.
Bates DM. lme4: Mixed-effects modeling with R. New York: Springer; 2010.
Kuznetsova A, Brockhoff PB, Christensen RH. lmerTest package: tests in linear mixed effects models. J Stat Softw. 2017;82:1–26.
doi: 10.18637/jss.v082.i13
Lenth R, Lenth MR. Package ‘lsmeans’. Am Stat. 2018;34(4):216–21.
Hirumi A, Kleinsmith A, Johnsen K, Kubovec S, Eakins M, Bogert K, et al. Advancing virtual patient simulations through design research and interPLAY: part I: design and development. Educ Technol Res Dev. 2016;64:763–85.
doi: 10.1007/s11423-016-9429-6
Hirumi A, Johnson T, Reyes RJ, Lok B, Johnsen K, Rivera-Gutierrez DJ, et al. Advancing virtual patient simulations through design research and inter PLAY: part II–integration and field test. Educ Technol Res Dev. 2016;64:1301–35.
doi: 10.1007/s11423-016-9461-6
Shapiro SL, Astin JA, Bishop SR, Cordova M. Mindfulness-based stress reduction for health care professionals: results from a randomized trial. Int J Stress Manag. 2005;12(2):164.
doi: 10.1037/1072-5245.12.2.164
Kabat-Zinn J. Mindfulness-based stress reduction (MBSR). Constructivism Hum Sci. 2003;8(2):73.
Grossman P, Niemann L, Schmidt S, Walach H. Mindfulness-based stress reduction and health benefits: a meta-analysis. J Psychosom Res. 2004;57(1):35–43.
doi: 10.1016/S0022-3999(03)00573-7
Gomes de Siqueira A, Yao H, Bafna A, Bloch-Elkouby S, Richards J, Lloveras LB, et al. Investigating the Effects of Virtual Patients’ Nonsensical Responses on Users’ Facial Expressions in Mental Health Training Scenarios. In: Proceedings of the 27th ACM Symposium on Virtual Reality Software and Technology. VRST ’21. New York, NY, USA: Association for Computing Machinery; 2021. p. 1–10. Available from: https://doi.org/10.1145/3489849.3489864 .
Mehrabian A, Wiener M. Decoding of inconsistent communications. J Pers Soc Psychol. 1967;6(1):109.
doi: 10.1037/h0024532
Mehrabian A, et al. Silent messages, vol. 8. Wadsworth Belmont; 1971.
Knapp ML, Hall JA, Horgan TG. Nonverbal communication in human interaction. Cengage Learning; 2013.
Salmon P, Young B. Creativity in clinical communication: from communication skills to skilled communication. Med Educ. 2011;45(3):217–26.
doi: 10.1111/j.1365-2923.2010.03801.x
Zoppi K, Epstein RM. Is Com m unification a Skill? Com mu nication Behaviors and Being in Relation. Fam Med. 2002;34(5):319–24.
Egener B, Cole-Kelly K. Satisfying the patient, but failing the test. Acad Med. 2004;79(6):508–10.
doi: 10.1097/00001888-200406000-00003
Makoul G. The SEGUE Framework for teaching and assessing communication skills. Patient Educ Couns. 2001;45(1):23–34.
doi: 10.1016/S0738-3991(01)00136-7
Hatem D, Mazor K, Fischer M, Philbin M, Quirk M. Applying patient perspectives on caring to curriculum development. Patient Educ Couns. 2008;72(3):367–73.
doi: 10.1016/j.pec.2008.05.020
Dwamena F, Holmes-Rovner M, Gaulden CM, Jorgenson S, Sadigh G, Sikorskii A, Lewin S, Smith RC, Coffey J, Olomu A. Interventions for providers to promote a patient-centred approach in clinical consultations. Cochrane Database Syst Rev. 2012;12(12):CD003267. https://doi.org/10.1002/14651858.CD003267.pub2 .
Hulsman RL, Ros WJ, Winnubst JA, Bensing JM. The effectiveness of a computer-assisted instruction programme on communication skills of medical specialists in oncology. Med Educ. 2002;36(2):125–34.
doi: 10.1046/j.1365-2923.2002.01074.x
Thomsen DK, Pedersen AF, Johansen MB, Jensen AB, Zachariae R. Breast cancer patients’ narratives about positive and negative communication experiences. Acta Oncol. 2007;46(7):900–8.
doi: 10.1080/02841860701261550