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      Harnessing Innovative Technologies to Train Nurses in Suicide Safety Planning With Hospitalized Patients: Protocol for Formative and Pilot Feasibility Research

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          Abstract

          Background

          Suicide is the 10th leading cause of death in the United States, with >47,000 deaths in 2019. Most people who died by suicide had contact with the health care system in the year before their death. Health care provider training is a top research priority identified by the National Action Alliance for Suicide Prevention; however, evidence-based approaches that target skill-building are resource intensive and difficult to implement. Advances in artificial intelligence technology hold promise for improving the scalability and sustainability of training methods, as it is now possible for computers to assess the intervention delivery skills of trainees and provide feedback to guide skill improvements. Much remains to be known about how best to integrate these novel technologies into continuing education for health care providers.

          Objective

          In Project WISE (Workplace Integrated Support and Education), we aim to develop 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 or surgical reasons or traumatic injury. The research aims include identifying strategies for the implementation and workflow integration of both the training and safety planning with patients, adapting 2 existing technologies to enhance general counseling skills for use in suicide safety planning (a conversational agent and an artificial intelligence–based feedback system), observing training acceptability and nurse engagement with the training components, and assessing the feasibility of recruitment, retention, and collection of longitudinal self-report and electronic health record data for patients identified as at risk of suicide.

          Methods

          Our developmental research includes qualitative and observational methods to explore the implementation context and technology usability, formative evaluation of the training paradigm, and pilot research to assess the feasibility of conducting a future cluster randomized pragmatic trial. The trial will examine whether patients hospitalized for medical or surgical reasons or traumatic injury who are at risk of suicide have better suicide-related postdischarge outcomes when admitted to a unit with nurses trained using the skill-building technology than those admitted to a unit with untrained nurses. The research takes place at a level 1 trauma center, which is also a safety-net hospital and academic medical center.

          Results

          Project WISE was funded in July 2019. As of September 2021, we have completed focus groups and usability testing with 27 acute care and 3 acute and intensive care nurses. We began data collection for research aims 3 and 4 in November 2021. All research has been approved by the University of Washington institutional review board.

          Conclusions

          Project WISE aims to further the national agenda to improve suicide prevention in health care settings by training nurses in suicide prevention with medically hospitalized patients using novel e-learning technologies.

          International Registered Report Identifier (IRRID)

          DERR1-10.2196/33695

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          Most cited references102

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          The PHQ-9: validity of a brief depression severity measure.

          While considerable attention has focused on improving the detection of depression, assessment of severity is also important in guiding treatment decisions. Therefore, we examined the validity of a brief, new measure of depression severity. The Patient Health Questionnaire (PHQ) is a self-administered version of the PRIME-MD diagnostic instrument for common mental disorders. The PHQ-9 is the depression module, which scores each of the 9 DSM-IV criteria as "0" (not at all) to "3" (nearly every day). The PHQ-9 was completed by 6,000 patients in 8 primary care clinics and 7 obstetrics-gynecology clinics. Construct validity was assessed using the 20-item Short-Form General Health Survey, self-reported sick days and clinic visits, and symptom-related difficulty. Criterion validity was assessed against an independent structured mental health professional (MHP) interview in a sample of 580 patients. As PHQ-9 depression severity increased, there was a substantial decrease in functional status on all 6 SF-20 subscales. Also, symptom-related difficulty, sick days, and health care utilization increased. Using the MHP reinterview as the criterion standard, a PHQ-9 score > or =10 had a sensitivity of 88% and a specificity of 88% for major depression. PHQ-9 scores of 5, 10, 15, and 20 represented mild, moderate, moderately severe, and severe depression, respectively. Results were similar in the primary care and obstetrics-gynecology samples. In addition to making criteria-based diagnoses of depressive disorders, the PHQ-9 is also a reliable and valid measure of depression severity. These characteristics plus its brevity make the PHQ-9 a useful clinical and research tool.
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            Three approaches to qualitative content analysis.

            Content analysis is a widely used qualitative research technique. Rather than being a single method, current applications of content analysis show three distinct approaches: conventional, directed, or summative. All three approaches are used to interpret meaning from the content of text data and, hence, adhere to the naturalistic paradigm. The major differences among the approaches are coding schemes, origins of codes, and threats to trustworthiness. In conventional content analysis, coding categories are derived directly from the text data. With a directed approach, analysis starts with a theory or relevant research findings as guidance for initial codes. A summative content analysis involves counting and comparisons, usually of keywords or content, followed by the interpretation of the underlying context. The authors delineate analytic procedures specific to each approach and techniques addressing trustworthiness with hypothetical examples drawn from the area of end-of-life care.
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              Validation and standardization of the Generalized Anxiety Disorder Screener (GAD-7) in the general population.

              The 7-item Generalized Anxiety Disorder Scale (GAD-7) is a practical self-report anxiety questionnaire that proved valid in primary care. However, the GAD-7 was not yet validated in the general population and thus far, normative data are not available. To investigate reliability, construct validity, and factorial validity of the GAD-7 in the general population and to generate normative data. Nationally representative face-to-face household survey conducted in Germany between May 5 and June 8, 2006. Five thousand thirty subjects (53.6% female) with a mean age (SD) of 48.4 (18.0) years. The survey questionnaire included the GAD-7, the 2-item depression module from the Patient Health Questionnaire (PHQ-2), the Rosenberg Self-Esteem Scale, and demographic characteristics. Confirmatory factor analyses substantiated the 1-dimensional structure of the GAD-7 and its factorial invariance for gender and age. Internal consistency was identical across all subgroups (alpha = 0.89). Intercorrelations with the PHQ-2 and the Rosenberg Self-Esteem Scale were r = 0.64 (P < 0.001) and r = -0.43 (P < 0.001), respectively. As expected, women had significantly higher mean (SD) GAD-7 anxiety scores compared with men [3.2 (3.5) vs. 2.7 (3.2); P < 0.001]. Normative data for the GAD-7 were generated for both genders and different age levels. Approximately 5% of subjects had GAD-7 scores of 10 or greater, and 1% had GAD-7 scores of 15 or greater. Evidence supports reliability and validity of the GAD-7 as a measure of anxiety in the general population. The normative data provided in this study can be used to compare a subject's GAD-7 score with those determined from a general population reference group.
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                Author and article information

                Contributors
                Journal
                JMIR Res Protoc
                JMIR Res Protoc
                ResProt
                JMIR Research Protocols
                JMIR Publications (Toronto, Canada )
                1929-0748
                December 2021
                15 December 2021
                : 10
                : 12
                : e33695
                Affiliations
                [1 ] Department of Psychiatry & Behavioral Sciences University of Washington Seattle, WA United States
                [2 ] Department of Psychology University of Washington Seattle, WA United States
                [3 ] Social Research Institute University of Utah Salt Lake City, UT United States
                [4 ] College of Arts, Media, and Design Northeastern University Boston, MA United States
                [5 ] Department of Biomedical Informatics and Medical Education University of Washington Seattle, WA United States
                [6 ] University of Massachusetts Medical School Worcester, MA United States
                Author notes
                Corresponding Author: Doyanne Darnell darnelld@ 123456uw.edu
                Author information
                https://orcid.org/0000-0002-0309-8774
                https://orcid.org/0000-0001-5971-6319
                https://orcid.org/0000-0001-6240-0294
                https://orcid.org/0000-0002-5781-9880
                https://orcid.org/0000-0003-4347-6757
                https://orcid.org/0000-0003-1421-3544
                https://orcid.org/0000-0003-2654-0833
                https://orcid.org/0000-0002-3223-6371
                https://orcid.org/0000-0003-0398-4108
                Article
                v10i12e33695
                10.2196/33695
                8717131
                34914618
                d5993bb0-5adb-4be0-8f55-9a4d6ff8d0d2
                ©Doyanne Darnell, Patricia A Areán, Shannon Dorsey, David C Atkins, Michael J Tanana, Tad Hirsch, Sean D Mooney, Edwin D Boudreaux, Katherine Anne Comtois. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 15.12.2021.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on https://www.researchprotocols.org, as well as this copyright and license information must be included.

                History
                : 20 September 2021
                : 14 October 2021
                : 15 October 2021
                : 21 October 2021
                Categories
                Protocol
                Protocol
                Custom metadata
                This paper was externally peer reviewed by the Mental Health Services Research Committee - National Institute of Mental Health Initial Review Group (National Institutes of Health, USA). See Multimedia Appendix 1 for the peer-review report;

                suicide prevention,hospital,training,e-learning,artificial intelligence,implementation science,user-centered design,task-shifting,quality assessment,fidelity

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