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      Mobile and Web-Based Partnered Intervention to Improve Remote Access to Pain and Posttraumatic Stress Disorder Symptom Management: Recruitment and Attrition in a Randomized Controlled Trial

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          Abstract

          Background

          Increasing access to nonpharmacological interventions to manage pain and posttraumatic stress disorder (PTSD) is essential for veterans. Complementary and integrative health (CIH) interventions can help individuals manage symptom burden with enhanced accessibility via remotely delivered health care. Mission Reconnect (MR) is a partnered, self-directed intervention that remotely teaches CIH skills.

          Objective

          The purpose of this paper is to describe the recruitment, onboarding phase, and attrition of a fully remote randomized controlled trial (RCT) assessing the efficacy of a self-directed mobile and web-based intervention for veterans with comorbid chronic pain and PTSD and their partners.

          Methods

          A total of 364 veteran-partner dyads were recruited to participate in a mixed methods multisite waitlist control RCT. Qualitative attrition interviews were conducted with 10 veterans with chronic pain and PTSD, and their self-elected partners (eg, spouse) who consented but did not begin the program.

          Results

          At the point of completing onboarding and being randomized to the 2 treatment arms, of the 364 recruited dyads, 97 (26.6%) failed to complete onboarding activities. Reported reasons for failure to complete onboarding include loss of self-elected partner buy-in (n=8, 8%), difficulties with using remote data collection methods and interventions (n=30, 31%), and adverse health experiences unrelated to study activities (n=23, 24%). Enrolled veterans presented at baseline with significant PTSD symptom burden and moderate-to-severe pain severity, and represented a geographically and demographically diverse population. Attrition interviews (n=10) indicated that misunderstanding MR including the intent of the intervention or mistaking the surveys as the actual intervention was a reason for not completing the MR registration process. Another barrier to MR registration was that interviewees described the mailed study information and registration packets as too confusing and excessive. Competing personal circumstances including health concerns that required attention interfered with MR registration. Common reasons for attrition following successful MR registration included partner withdrawal, adverse health issues, and technological challenges relating to the MR and electronic data collection platform (Qualtrics). Participant recommendations for reducing attrition included switching to digital forms to reduce participant burden and increasing human interaction throughout the registration and baseline data collection processes.

          Conclusions

          Challenges, solutions, and lessons learned for study recruitment and intervention delivery inform best practices of delivering remote self-directed CIH interventions when addressing the unique needs of this medically complex population. Successful recruitment and enrollment of veterans with chronic pain and PTSD, and their partners, to remote CIH programs and research studies requires future examination of demographic and symptom-associated access barriers. Accommodating the unique needs of this medically complex population is essential for improving the effectiveness of CIH programs. Disseminating lessons learned and improving access to remotely delivered research studies and CIH programs is paramount in the post–COVID-19 climate.

          Trial Registration

          ClinicalTrials.gov NCT03593772; https://clinicaltrials.gov/ct2/show/NCT03593772

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          Most cited references43

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          The Posttraumatic Stress Disorder Checklist for DSM-5 (PCL-5): Development and Initial Psychometric Evaluation.

          The Posttraumatic Stress Disorder Checklist (PCL) is a widely used DSM-correspondent self-report measure of PTSD symptoms. The PCL was recently revised to reflect DSM-5 changes to the PTSD criteria. In this article, the authors describe the development and initial psychometric evaluation of the PCL for DSM-5 (PCL-5). Psychometric properties of the PCL-5 were examined in 2 studies involving trauma-exposed college students. In Study 1 (N = 278), PCL-5 scores exhibited strong internal consistency (α = .94), test-retest reliability (r = .82), and convergent (rs = .74 to .85) and discriminant (rs = .31 to .60) validity. In addition, confirmatory factor analyses indicated adequate fit with the DSM-5 4-factor model, χ2 (164) = 455.83, p < .001, standardized root mean square residual (SRMR) = .07, root mean squared error of approximation (RMSEA) = .08, comparative fit index (CFI) = .86, and Tucker-Lewis index (TLI) = .84, and superior fit with recently proposed 6-factor, χ2 (164) = 318.37, p < .001, SRMR = .05, RMSEA = .06, CFI = .92, and TLI = .90, and 7-factor, χ2 (164) = 291.32, p < .001, SRMR = .05, RMSEA = .06, CFI = .93, and TLI = .91, models. In Study 2 (N = 558), PCL-5 scores demonstrated similarly strong reliability and validity. Overall, results indicate that the PCL-5 is a psychometrically sound measure of PTSD symptoms. Implications for use of the PCL-5 in a variety of assessment contexts are discussed.
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            Psychometric properties of the PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (PCL-5) in veterans.

            This study examined the psychometric properties of the posttraumatic stress disorder (PTSD) Checklist for Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (PCL-5; Weathers, Litz, et al., 2013b) in 2 independent samples of veterans receiving care at a Veterans Affairs Medical Center (N = 468). A subsample of these participants (n = 140) was used to define a valid diagnostic cutoff score for the instrument using the Clinician-Administered PTSD Scale for DSM-5 (CAPS-5; Weathers, Blake, et al., 2013) as the reference standard. The PCL-5 test scores demonstrated good internal consistency (α = .96), test-retest reliability (r = .84), and convergent and discriminant validity. Consistent with previous studies (Armour et al., 2015; Liu et al., 2014), confirmatory factor analysis revealed that the data were best explained by a 6-factor anhedonia model and a 7-factor hybrid model. Signal detection analyses using the CAPS-5 revealed that PCL-5 scores of 31 to 33 were optimally efficient for diagnosing PTSD (κ(.5) = .58). Overall, the findings suggest that the PCL-5 is a psychometrically sound instrument that can be used effectively with veterans. Further, by determining a valid cutoff score using the CAPS-5, the PCL-5 can now be used to identify veterans with probable PTSD. However, findings also suggest the need for research to evaluate cluster structure of DSM-5. (PsycINFO Database Record
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              Sample size in qualitative research.

              A common misconception about sampling in qualitative research is that numbers are unimportant in ensuring the adequacy of a sampling strategy. Yet, simple sizes may be too small to support claims of having achieved either informational redundancy or theoretical saturation, or too large to permit the deep, case-oriented analysis that is the raison-d'être of qualitative inquiry. Determining adequate sample size in qualitative research is ultimately a matter of judgment and experience in evaluating the quality of the information collected against the uses to which it will be put, the particular research method and purposeful sampling strategy employed, and the research product intended.
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                Author and article information

                Contributors
                Journal
                J Med Internet Res
                J Med Internet Res
                JMIR
                Journal of Medical Internet Research
                JMIR Publications (Toronto, Canada )
                1439-4456
                1438-8871
                2023
                3 October 2023
                : 25
                : e49678
                Affiliations
                [1 ] James A. Haley Veterans' Hospital Research Service Tampa, FL United States
                [2 ] Division of Epidemiology Department of Internal Medicine University of Utah Salt Lake City, UT United States
                [3 ] Department of Psychiatry and Behavioral Neurosciences University of South Florida Tampa, FL United States
                [4 ] College of Public Health University of South Florida Tampa, FL United States
                [5 ] VA Ann Arbor Healthcare System Geriatric Research, Education, and Clinical Center Ann Arbor, MI United States
                [6 ] Division of Geriatric and Palliative Medicine Department of Internal Medicine Ann Arbor, MI United States
                [7 ] Department of Veterans Affairs Center of Innovation for Complex Chronic Healthcare Edward Hines, Jr. VA Hospital Hines, IL United States
                [8 ] Center for Health Services and Outcomes Research Feinberg School of Medicine Northwestern University Chicago, IL United States
                [9 ] Departments of Ophthalmology and Medical Social Sciences Feinberg School of Medicine Northwestern University Chicago, IL United States
                Author notes
                Corresponding Author: Rachel C Benzinger rachel.benzinger@ 123456VA.Gov
                Author information
                https://orcid.org/0000-0003-4075-3763
                https://orcid.org/0009-0003-8455-0965
                https://orcid.org/0000-0002-4460-8929
                https://orcid.org/0000-0003-3609-2595
                https://orcid.org/0000-0002-8688-3945
                https://orcid.org/0000-0002-1814-4534
                https://orcid.org/0000-0001-5834-7929
                https://orcid.org/0000-0003-4655-6605
                https://orcid.org/0000-0003-4118-219X
                https://orcid.org/0000-0002-6252-4235
                https://orcid.org/0000-0001-7458-1117
                https://orcid.org/0000-0003-4064-3206
                Article
                v25i1e49678
                10.2196/49678
                10582813
                37788078
                456455cc-e267-4668-b417-4f0a2d3ef062
                ©Jolie N Haun, Hari H Venkatachalam, Christopher A Fowler, Amy C Alman, Lisa M Ballistrea, Tali Schneider, Rachel C Benzinger, Christine Melillo, Neil B Alexander, S Angelina Klanchar, William Lapcevic, Dustin D French. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 03.10.2023.

                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 the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

                History
                : 5 June 2023
                : 2 August 2023
                : 22 August 2023
                : 29 August 2023
                Categories
                Original Paper
                Original Paper

                Medicine
                ptsd,pain,veteran,attrition,cih,randomized controlled trial,chronic pain,remote intervention,dyad,mobile health

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