Authors:
John M. Inadomi, Rachel B. Issaka, & Beverly B. Green
University of Washington affiliated authors are displayed in bold.
✪ Open Access
Published: April 2021
John M. Inadomi, Rachel B. Issaka, & Beverly B. Green
University of Washington affiliated authors are displayed in bold.
Published: April 2021
Justin D. Smith, Cady Berkel, Allison J. Carroll, Emily Fu, Kevin J. Grimm, Anne M. Mauricio, Jenna Rudo-Stern, Emily Winslow, Thomas J. Dishion, Neil Jordan, David C. Atkins, Shrikanth S. Narayanan, Carlos Gallo, Meg M. Bruening, Charlton Wilson, Farah Lokey, & Kristen Samaddar
University of Washington affiliated authors are displayed in bold.
Published: March 2021
Cameo Stanick, Heather Halko, Kayne Mettert, Caitlin Dorsey, Joanna Moullin, Bryan Weiner, Byron Powell, and Cara C. Lewis
University of Washington affiliated authors are displayed in bold.
Published: March 2021
Identification of psychometrically strong implementation measures could (1) advance researchers’ understanding of how individual characteristics impact implementation processes and outcomes, and (2) promote the success of real-world implementation efforts. The current study advances the work that our team published in 2015 by providing an updated and enhanced systematic review that identifies and evaluates the psychometric properties of implementation measures that assess individual characteristics.
A full description of our systematic review methodology, which included three phases, is described in a previously published protocol paper. Phase I focused on data collection and involved search string generation, title and abstract screening, full-text review, construct assignment, and measure forward searches. During Phase II, we completed data extraction (i.e., coding psychometric information). Phase III involved data analysis, where two trained specialists independently rated each measurement tool using our psychometric rating criteria.
Our team identified 124 measures of individual characteristics used in mental or behavioral health research, and 123 of those measures were deemed suitable for rating using Psychometric and Pragmatic Evidence Rating Scale. We identified measures of knowledge and beliefs about the intervention (n = 76), self-efficacy (n = 24), individual stage of change (n = 2), individual identification with organization (n = 7), and other personal attributes (n = 15). While psychometric information was unavailable and/or unreported for many measures, information about internal consistency and norms were the most commonly identified psychometric data across all individual characteristics’ constructs. Ratings for all psychometric properties predominantly ranged from “poor” to “good.”
The majority of research that develops, uses, or examines implementation measures that evaluate individual characteristics does not include the psychometric properties of those measures. The development and use of psychometric reporting standards could advance the use of valid and reliable tools within implementation research and practice, thereby enhancing the successful implementation and sustainment of evidence-based practice in community care.
Measurement is the foundation for advancing practice in health care and other industries. In the field of implementation science, the state of measurement is only recently being targeted as an area for improvement, given that high-quality measures need to be identified and utilized in implementation work to avoid developing another research to practice gap. For the current study, we utilized the Consolidated Framework for Implementation Research to identify measures related to individual characteristics’ constructs, such as knowledge and beliefs about the intervention, self-efficacy, individual identification with the organization, individual stage of change, and other personal attributes. Our review showed that many measures exist for certain constructs (e.g., measures related to assessing providers’ attitudes and perceptions about evidence-based practice interventions), while others have very few (e.g., an individual’s stage of change). Also, we rated measures for their psychometric strength utilizing an anchored rating system and found that most measures assessing individual characteristics are in need of more research to establish their evidence of quality. It was also clear from our results that frequency of use/citations does not equate to high quality, psychometric strength. Ultimately, the state of the literature has demonstrated that assessing individual characteristics of implementation stakeholders is an area of strong interest in implementation work. It will be important for future research to focus on clearly delineating the psychometric properties of existing measures for saturated constructs, while for the others the emphasis should be on developing new, high-quality measures and make these available to stakeholders.
**This abstract is posted with permission under the Creative Commons Attribution 4.0 International License**
Sheree R. Schwartz, J. D. Smith, Christopher Hoffmann, Bhakti Hansoti, Sharmistha Mishra, Arianna Rubin Means, Vivian Go, Kenneth Sherr, Denis Nash, Patrick Sullivan & Stefan Baral
University of Washington affiliated authors are displayed in bold.
Published: March 2021
Inge Petersen, Christopher G. Kemp, Deepa Rao, Bradley H. Wagenaar, Kenneth Sherr, Merridy Grant, Max Bachmann, Ruanne V. Barnabas, Ntokozo Mntambo, Sithabisile Gigaba, André Van Rensburg, Zamasomi Luvuno, Ishmael Amarreh, Lara Fairall, Nikiwe N. Hongo, & Arvin Bhana
University of Washington affiliated authors are displayed in bold.
Published: March 2021
Stephanie Staras, Justin S. Tauscher, Natalie Rich, Esaa Samarah, Lindsay A. Thompson, Michelle M. Vinson, Michael J. Muszynski, & Elizabeth A. Shenkman
University of Washington affiliated authors are displayed in bold.
Published: March 2021
eHealth apps often fail to improve clinical outcomes due to poor integration with clinical workflow—the sequence and personnel needed to undertake a series of tasks for clinical care. Our central thesis is that eHealth interventions will be more effective if the clinical workflow is studied and taken into consideration for intervention implementation. This paper aims to provide an introductory tutorial on when and how to use a clinical workflow analysis to guide the implementation of eHealth interventions. The tutorial includes a step-by-step guide to conducting a clinical workflow analysis in planning for eHealth implementation.
We began with a description of why a clinical workflow analysis is best completed before the implementation of eHealth interventions. Next, we described 4 steps needed to perform the clinical workflow analysis: the identification of discrete workflow components, workflow assessment, triangulation, and the stakeholder proposal of intervention implementation. Finally, we presented a case study of a clinical workflow analysis, which was conducted during patient visits of patients aged 11 or 12 years from 4 diverse pediatric or family medicine clinics to plan the implementation of a tablet-based app for adolescent vaccination.
Investigators planning the implementation of new eHealth interventions in health care settings can use the presented steps to assess clinical workflow, thereby maximizing the match of their intervention with the clinical workflow. Conducting a prospective workflow study allows for evidence-based planning, identifying potential pitfalls, and increasing stakeholder buy-in and engagement. This tutorial should aid investigators in increasing the successful implementation of eHealth interventions.
**This abstract is posted with permission under the Creative Commons Attribution 4.0 International License**
Margaret E. Crane, Katherine E. Phillips, Colleen A. Maxwell, Lesley A. Norris, Lara S. Rifkin, Jacob M. Blank, Samantha D. Sorid, Kendra L. Read, Anna J. Swan, Philip C. Kendall & Hannah E. Frank
University of Washington affiliated authors are displayed in bold.
Published: March 2021
Sara J. Becker, Bryan R. Garner, Bryan J. Hartzler
University of Washington affiliated authors are displayed in bold.
Published: March 2021
Vivien D. Tsu, D. Scott LaMontagne, Phionah Atuhebwe, Paul N. Bloem, Cathy Ndiaye
University of Washington affiliated authors are displayed in bold.
Published: March 2021
More than 90% of cervical cancer deaths occur in low- and middle-income countries (LMICs), which have limited capacity to mount the comprehensive national screening and precancer treatment programs that could prevent most of these deaths. The development of vaccines against the human papillomavirus (HPV) has dramatically altered the landscape of cervical cancer prevention. As of mid-2020, 56 LMICs (41% of all LMICs) have initiated national HPV vaccination programs. This paper reviews the experience of LMICs that have introduced HPV vaccine into their national programs, key lessons learned, HPV vaccination sustainability and scale-up challenges, and future mitigation measures.
As international guidance evolved and countries accumulated experience, strategies for national introduction shifted with regard to target groups, delivery site and timing, preparation and planning, communications and social mobilization, and ultimately monitoring, supervision and evaluation. Despite the successes that LMICs have been able to achieve in reaching large proportions of eligible girls, there are still considerable challenges countries encounter in overcoming rumors, reaching out-of-school girls, completing the vaccine series, estimating target populations, monitoring program performance, and assuring vaccination sustainability. New opportunities, such as the entry of additional vaccine manufacturers and ongoing studies to evaluate one-dose delivery, could help overcome the outstanding barriers to higher coverage and financial sustainability. Effective use of the experience to date and advances on the horizon could enable all LMICs to move towards the coverage levels that are needed to achieve eventual elimination.
**This abstract is posted with permission under the Creative Commons Attribution 4.0 International License**
Jessica A. Chen, Theresa E. Matson, Keren Lehavot, Patrick J. Raue, Jessica P. Young, Molly C. Silvestrini, John C. Fortney, & Emily C. Williams
University of Washington affiliated authors are displayed in bold.
Published: February 2021