eLearning for Suicide Prevention

Formative Evaluation of an eLearning Approach to Suicide Prevention Training

Project WISE (Workplace Integrated Support & Education) includes developmental and pilot research to create an e-learning training in suicide safety planning enhanced with novel skill-building technologies that can be integrated into the routine workflow of nurses serving patients hospitalized for medical, surgical, or traumatic injury reasons. This study pilots an initial version of this eLearning training and collects data on the acceptability of the training and its components as well as engagement of nurses in the training. The evaluation will inform iterations of the training.

Study Overview

• Status: Completed
• Conditions: Suicide
• Intervention / Treatment: Behavioral: eLearning Training in Suicide Safety Planning

• Study Type: Interventional
• Enrollment (Actual): 19
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • Washington
    • Seattle, Washington, United States, 98104
      • Harborview Medical Center

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

• Nurses working in acute or intensive care units at Harborview Medical Center

Exclusion Criteria:

-

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Prevention
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Project WISE eLearning Training in Suicide Safety Planning	Behavioral: eLearning Training in Suicide Safety Planning; The training includes a web-based didactic in suicide safety planning, interactive practice in counseling microskills with a chat bot, role-playing safety planning with a standardized patient, and reviewing automated feedback on safety planning counseling skills generated from a computer coding system.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Training Acceptability Self-Report - Post-Training	A 4-item self-report measure created for this study will assess satisfaction with all of the training components using a Likert-type scale of 0 = Not at all satisfied to 4 = Completely satisfied.	Immediately after completing the training
Training Acceptability Self-Report - 6-Month Follow-up	A 4-item self-report measure created for this study will assess satisfaction with all of the training components using a Likert-type scale of 0 = Not at all satisfied to 4 = Completely satisfied.	6-months after completing the training
Training Engagement Self-Report - Post-Training	Investigators will collect self-reported completion of the training activities using a 4-item measure. Participants will report on a sliding scale from 0-100, what percent of each training activity they believe they completed.	Immediately after participants indicate they have completed the training activities
Participant Retention	Percent of participants retained throughout study follow-up	6 Months after completing the training
Training Acceptability - System Usability Scale for Client Bot Emily	The System Usability Scale, a self-report measure using a Likert-type rating scale, will assess acceptability of the two technologic training components: Client Bot Emily and Lyssn Advisor. Client Bot Emily is a virtual patient/chat bot with the persona of a suicidal patient. Nurses chat with Emily and practice skills of asking open-ended questions and making reflections about statements Emily makes. Lyssn Advisor is an online platform that automatically codes transcripts of audio or video recorded role-plays for counseling skills; nurses then log in to the platform to see their scores, which provides feedback on their counseling performance. Scores on the SUS range from 0-100, which higher scores indicating greater usability or acceptability.	Once, immediately after engaging with each of the training technologies
Training Engagement With Client Bot User Data - Post-Training	Data is collected from the technologic platform on whether and how often participants accessed the training technologies. Engagement is indicated by participants accessing the platform using their unique login and interacting with the webpage associated with the Client Bot. The unit of measurement will be the number of participants who accessed the Client Bot during the training period.	Immediately after participants indicate they have completing the training activities
Training Engagement With Lyssn Advisor User Data - Post-Training	Data is collected from the technologic platform on whether and how often participants accessed the training technologies. Engagement is indicated by participants accessing the platform using their unique login and interacting with the webpage associated with the Lyssn Advisor. The unit of measurement will be the frequency of times participants visits the Lyssn Advisor webpage.	Immediately after participants indicate they have completing the training activities
Training Engagement With Client Bot User Data - 6-Month Follow-up	Data is collected from the technologic platform on whether and how often participants accessed the training technologies. Engagement is indicated by participants accessing the platform using their unique login and interacting with the webpage associated with the Client Bot. The unit of measurement will be the number of participants who logged on and interacted with the Client Bot after the training period and before completing the 6-month survey.	6-months after participants indicate they have completed the training activities
Training Engagement With Lyssn Advisor User Data - 6-Month Follow-up	Data is collected from the technologic platform on whether and how often participants accessed the training technologies. Engagement is indicated by participants accessing the platform using their unique login and interacting with the webpage associated with the Lyssn Advisor. The unit of measurement will be the frequency of times participants visits the Lyssn Advisor webpage during the 6-month follow-up period.	6-months after participants indicate they have completed the training activities
Client Bot Training Engagement Self-Report - 6 Month Follow-up	Participants will self-report whether or not they accessed any of the training technologies during the follow-up period.	6-months after participants indicate they have completed the training activities
Training Acceptability - System Usability Scale for Lyssn Advisor	The System Usability Scale, a self-report measure using a Likert-type rating scale, will assess acceptability of the two technologic training components: Client Bot Emily and Lyssn Advisor. Client Bot Emily is a virtual patient/chat bot with the persona of a suicidal patient. Nurses chat with Emily and practice skills of asking open-ended questions and making reflections about statements Emily makes. Lyssn Advisor is an online platform that automatically codes transcripts of audio or video recorded role-plays for counseling skills; nurses then log in to the platform to see their scores, which provides feedback on their counseling performance. Scores on the SUS range from 0-100, which higher scores indicating greater usability or acceptability.	Once, immediately after engaging with each of the training technologies
Lyssn Advisor Training Engagement Self-Report - 6 Month Follow-up	Participants will self-report whether or not they accessed any of the training technologies during the follow-up period.	6-months after participants indicate they have completed the training activities

Collaborators and Investigators

• Sponsor: University of Washington
• Collaborators: National Institute of Mental Health (NIMH)
• Investigators: Principal Investigator: Doyanne A Darnell, PhD, University of Washington

Publications and helpful links

Helpful Links

• NIH Reporter

Study record dates

Study Major Dates

• Study Start (Actual): November 1, 2021
• Primary Completion (Actual): March 1, 2023
• Study Completion (Actual): March 1, 2023

Study Registration Dates

• First Submitted: October 8, 2021
• First Submitted That Met QC Criteria: December 15, 2021
• First Posted (Actual): January 5, 2022

Study Record Updates

• Last Update Posted (Estimated): December 18, 2023
• Last Update Submitted That Met QC Criteria: November 25, 2023
• Last Verified: November 1, 2023

More Information

Terms related to this study

• Keywords: Artificial Intelligence; Education; Suicide Prevention; Fidelity
• Additional Relevant MeSH Terms: Behavioral Symptoms; Self-Injurious Behavior; Suicide; Suicide Prevention
• Other Study ID Numbers: STUDY00013577; K23MH118361-01A1 (U.S. NIH Grant/Contract)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No