Search

Many preventive trials randomize individuals to intervention condition which is then delivered in a group setting. Other trials randomize higher levels, say organizations, and then use learning collaboratives comprised of multiple organizations to support improved implementation or sustainment. Other trials randomize or expand existing social networks and use key opinion leaders to deliver interventions through these networks. We use the term contextually driven to refer generally to such trials (traditionally referred to as clustering, where groups are formed either pre-randomization or post-randomization - i.e., a cluster-randomized trial), as these groupings or networks provide fixed or time-varying contexts that matter both theoretically and practically in the delivery of interventions. While such contextually driven trials can provide efficient and effective ways to deliver and evaluate prevention programs, they all require analytical procedures that take appropriate account of non-independence, something not always appreciated. Published analyses of many prevention trials have failed to take this into account. We discuss different types of contextually driven designs and then show that even small amounts of non-independence can inflate actual Type I error rates. This inflation leads to rejecting the null hypotheses too often, and erroneously leading us to conclude that there are significant differences between interventions when they do not exist. We describe a procedure to account for non-independence in the important case of a two-arm trial that randomizes units of individuals or organizations in both arms and then provides the active treatment in one arm through groups formed after assignment. We provide sample code in multiple programming languages to guide the analyst, distinguish diverse contextually driven designs, and summarize implications for multiple audiences.

U.S. health care systems are tasked with alleviating the burden of mental health, but are frequently underprepared and lack workforce and resource capacity to deliver services to all in need. Digital mental health interventions (DMHIs) can increase access to evidence-based mental health care. However, DMHIs commonly do not fit into the day-to-day activities of the people who engage with them, resulting in a research-to-practice gap for DMHI implementation. For health care settings, differences between digital and traditional mental health services make alignment and integration challenging. Specialized attention is needed to improve the implementation of DMHIs in health care settings so that these services yield high uptake, engagement, and sustainment. The purpose of this article is to enhance efforts to integrate DMHIs in health care settings by proposing implementation strategies, selected and operationalized based on the discrete strategies established in the Expert Recommendations for Implementing Change project, that align to DMHI-specific barriers in these settings. Guidance is offered in how these strategies can be applied to DMHI implementation across four phases commonly distinguished in implementation science using the Exploration, Preparation, Implementation, Sustainment Framework. Next steps to advance research in this area and improve the research-to-practice gap for implementing DMHIs are recommended. Applying implementation strategies to DMHI implementation will enable psychologists to systematically evaluate this process, which can yield an enhanced understanding of the factors that facilitate implementation success and improve the translation of DMHIs from controlled trials to real-world settings. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Purpose of reviewDespite tremendous potential for public health impact and continued investments in development and evaluation, it is rare for eHealth behavioral interventions to be implemented broadly in practice. Intervention developers may not be planning for implementation when designing technology-enabled interventions, thus creating greater challenges for real-world deployment following a research trial. To facilitate faster translation to practice, we aimed to provide researchers and developers with an implementation-focused approach and set of design considerations as they develop new eHealth programs.Recent findingsUsing the Accelerated Creation-to-Sustainment model as a lens, we examined challenges and successes experienced during the development and evaluation of four diverse eHealth HIV prevention programs for young men who have sex with men: Keep It Up!, Harnessing Online Peer Education, Guy2Guy, and HealthMindr. HIV is useful for studying eHealth implementation because of the substantial proliferation of diverse eHealth interventions with strong evidence of reach and efficacy and the responsiveness to rapid and radical disruptions in the field. Rather than locked-down products to be disseminated, eHealth interventions are complex sociotechnical systems that require continual optimization, vigilance to monitor and troubleshoot technological issues, and decision rules to refresh content and functionality while maintaining fidelity to core intervention principles. Platform choice and sociotechnical relationships (among end users, implementers, and the technology) heavily influence implementation needs and challenges. We present a checklist of critical implementation questions to address during intervention development. In the absence of a clear path forward for eHealth implementation, deliberate design of an eHealth intervention's service and technological components in tandem with their implementation plans is critical to mitigating barriers to widespread use. The design considerations presented can be used by developers, evaluators, reviewers, and funders to prioritize the pragmatic scalability of eHealth interventions in research.

BackgroundImplementing treatments and interventions with demonstrated effectiveness is critical for improving patient health outcomes at a reduced cost. When an evidence-based intervention (EBI) is implemented with fidelity in a setting that is very similar to the setting wherein it was previously found to be effective, it is reasonable to anticipate similar benefits of that EBI. However, one goal of implementation science is to expand the use of EBIs as broadly as is feasible and appropriate in order to foster the greatest public health impact. When implementing an EBI in a novel setting, or targeting novel populations, one must consider whether there is sufficient justification that the EBI would have similar benefits to those found in earlier trials.DiscussionIn this paper, we introduce a new concept for implementation called "scaling-out" when EBIs are adapted either to new populations or new delivery systems, or both. Using existing external validity theories and multilevel mediation modeling, we provide a logical framework for determining what new empirical evidence is required for an intervention to retain its evidence-based standard in this new context. The motivating questions are whether scale-out can reasonably be expected to produce population-level effectiveness as found in previous studies, and what additional empirical evaluations would be necessary to test for this short of an entirely new effectiveness trial. We present evaluation options for assessing whether scaling-out results in the ultimate health outcome of interest.ConclusionIn scaling to health or service delivery systems or population/community contexts that are different from the setting where the EBI was originally tested, there are situations where a shorter timeframe of translation is possible. We argue that implementation of an EBI in a moderately different setting or with a different population can sometimes "borrow strength" from evidence of impact in a prior effectiveness trial. The collection of additional empirical data is deemed necessary by the nature and degree of adaptations to the EBI and the context. Our argument in this paper is conceptual, and we propose formal empirical tests of mediational equivalence in a follow-up paper.

HIV continues to significantly impact the health of communities, particularly affecting racially and ethnically diverse men who have sex with men and transgender women. In response, health departments often fund a number of community organizations to provide each of these subgroups with comprehensive and culturally responsive services. To this point, evaluators have focused on individual interventions but have largely overlooked the complex environment in which these interventions are implemented, including other programs funded to do similar work. The Evaluation Center was funded by the City of Chicago in 2015 to conduct a citywide evaluation of all HIV prevention programming. This article will describe our novel approach to adapt the principles and methods of the empowerment evaluation approach, to effectively engage with 20 city-funded prevention programs to collect and synthesize multisite evaluation data, and ultimately build capacity at these organizations to foster a learning-focused community.

Objective: For implementation of an evidence-based program to be effective, efficient, and equitable across diverse populations, we propose that researchers adopt a systems approach that is often absent in efficacy studies. To this end, we describe how a computer-based monitoring system can support me delivery of the New Beginnings Program (NBP), a parent-focused evidence-based prevention program for divorcing parents. Method: We present NBP from a novel systems approach that incorporates social system informatics and engineering, both necessary when utilizing feedback loops, ubiquitous in implementation research and practice. Examples of two methodological challenges are presented: how to monitor implementation, and how to provide feedback by evaluating system-level changes due to implementation. Results: We introduce and relate systems concepts to these two methodologic issues that are at the center of implementation metliods. We explore how these system-level feedback loops address effectiveness, efficiency, and equity principles. These key principles are provided for designing an automated, low-burden, low-intrusive measurement system to aid fidelity monitoring and feedback that can be used in practice. Discussion: As the COVTD-19 pandemic now demands fewer face-to-face delivery systems, their replacement with more virtual systems for parent training interventions requires constructing new implementation measurement systems based on social system informatics approaches. These approaches include the automatic monitoring of quality and fidelity in parent training interventions. Finally, we present parallels of producing generalizable and local knowledge bridging systems science and engineering method. This comparison improves our understanding of system-level changes, facilitates a program's implementation, and produces knowledge for the field. Public Significance Statement The successful implementation of EBIs has the potential to change critical public health disparities and inequities. We show how social system informatics facilitates the monitoring and feedback on EBFs implementation. Such computational methods enhance implementation's monitoring in an efficient, scalable, and non-obtrusive manner, particularly within the virtual, on-line context generated by COVTD-19 pandemic. Keywords: social systems informatics, implementation science, systems science, computational linguistics, fidelity, To improve population's health requires a directed, systematic, and expedited approach to ensure that evidence-based programs (EBPs) are delivered with a high fidelity at scale. Scientists have built most of [...]

A1 Introduction to the 8th Annual Conference on the Science of Dissemination and Implementation: Optimizing Personal and Population Health David Chambers, Lisa Simpson D1 Discussion forum: Population health D&I research Felicia Hill-Briggs D2 Discussion forum: Global health D&I research Gila Neta, Cynthia Vinson D3 Discussion forum: Precision medicine and D&I research David Chambers S1 Predictors of community therapists’ use of therapy techniques in a large public mental health system Rinad Beidas, Steven Marcus, Gregory Aarons, Kimberly Hoagwood, Sonja Schoenwald, Arthur Evans, Matthew Hurford, Ronnie Rubin, Trevor Hadley, Frances Barg, Lucia Walsh, Danielle Adams, David Mandell S2 Implementing brief cognitive behavioral therapy (CBT) in primary care: Clinicians' experiences from the field Lindsey Martin, Joseph Mignogna, Juliette Mott, Natalie Hundt, Michael Kauth, Mark Kunik, Aanand Naik, Jeffrey Cully S3 Clinician competence: Natural variation, factors affecting, and effect on patient outcomes Alan McGuire, Dominique White, Tom Bartholomew, John McGrew, Lauren Luther, Angie Rollins, Michelle Salyers S4 Exploring the multifaceted nature of sustainability in community-based prevention: A mixed-method approach Brittany Cooper, Angie Funaiole S5 Theory informed behavioral health integration in primary care: Mixed methods evaluation of the implementation of routine depression and alcohol screening and assessment Julie Richards, Amy Lee, Gwen Lapham, Ryan Caldeiro, Paula Lozano, Tory Gildred, Carol Achtmeyer, Evette Ludman, Megan Addis, Larry Marx, Katharine Bradley S6 Enhancing the evidence for specialty mental health probation through a hybrid efficacy and implementation study Tonya VanDeinse, Amy Blank Wilson, Burgin Stacey, Byron Powell, Alicia Bunger, Gary Cuddeback S7 Personalizing evidence-based child mental health care within a fiscally mandated policy reform Miya Barnett, Nicole Stadnick, Lauren Brookman-Frazee, Anna Lau S8 Leveraging an existing resource for technical assistance: Community-based supervisors in public mental health Shannon Dorsey, Michael Pullmann S9 SBIRT implementation for adolescents in urban federally qualified health centers: Implementation outcomes Shannon Mitchell, Robert Schwartz, Arethusa Kirk, Kristi Dusek, Marla Oros, Colleen Hosler, Jan Gryczynski, Carolina Barbosa, Laura Dunlap, David Lounsbury, Kevin O'Grady, Barry Brown S10 PANEL: Tailoring Implementation Strategies to Context - Expert recommendations for tailoring strategies to context Laura Damschroder, Thomas Waltz, Byron Powell S11 PANEL: Tailoring Implementation Strategies to Context - Extreme facilitation: Helping challenged healthcare settings implement complex programs Mona Ritchie S12 PANEL: Tailoring Implementation Strategies to Context - Using menu-based choice tasks to obtain expert recommendations for implementing three high-priority practices in the VA Thomas Waltz S13 PANEL: The Use of Technology to Improve Efficient Monitoring of Implementation of Evidence-based Programs - Siri, rate my therapist: Using technology to automate fidelity ratings of motivational interviewing David Atkins, Zac E. Imel, Bo Xiao, Doğan Can, Panayiotis Georgiou, Shrikanth Narayanan S14 PANEL: The Use of Technology to Improve Efficient Monitoring of Implementation of Evidence-based Programs - Identifying indicators of implementation quality for computer-based ratings Cady Berkel, Carlos Gallo, Irwin Sandler, C. Hendricks Brown, Sharlene Wolchik, Anne Marie Mauricio S15 PANEL: The Use of Technology to Improve Efficient Monitoring of Implementation of Evidence-based Programs - Improving implementation of behavioral interventions by monitoring emotion in spoken speech Carlos Gallo, C. Hendricks Brown, Sanjay Mehrotra S16 Scorecards and dashboards to assure data quality of health management information system (HMIS) using R Dharmendra Chandurkar, Siddhartha Bora, Arup Das, Anand Tripathi, Niranjan Saggurti, Anita Raj S17 A big data approach for discovering and implementing patient safety insights Eric Hughes, Brian Jacobs, Eric Kirkendall S18 Improving the efficacy of a depression registry for use in a collaborative care model Danielle Loeb, Katy Trinkley, Michael Yang, Andrew Sprowell, Donald Nease S19 Measurement feedback systems as a strategy to support implementation of measurement-based care in behavioral health Aaron Lyon, Cara Lewis, Meredith Boyd, Abigail Melvin, Semret Nicodimos, Freda Liu, Nathanial Jungbluth S20 PANEL: Implementation Science and Learning Health Systems: Intersections and Commonalities - Common loop assay: Methods of supporting learning collaboratives Allen Flynn S21 PANEL: Implementation Science and Learning Health Systems: Intersections and Commonalities - Innovating audit and feedback using message tailoring models for learning health systems Zach Landis-Lewis S22 PANEL: Implementation Science and Learning Health Systems: Intersections and Commonalities - Implementation science and learning health systems: Connecting the dots Anne Sales S23 Facilitation activities of Critical Access Hospitals during TeamSTEPPS implementation Jure Baloh, Marcia Ward, Xi Zhu S24 Organizational and social context of federally qualified health centers and variation in maternal depression outcomes Ian Bennett, Jurgen Unutzer, Johnny Mao, Enola Proctor, Mindy Vredevoogd, Ya-Fen Chan, Nathaniel Williams, Phillip Green S25 Decision support to enhance treatment of hospitalized smokers: A randomized trial Steven Bernstein, June-Marie Rosner, Michelle DeWitt, Jeanette Tetrault, James Dziura, Allen Hsiao, Scott Sussman, Patrick O’Connor, Benjamin Toll S26 PANEL: Developing Sustainable Strategies for the Implementation of Patient-Centered Care across Diverse US Healthcare Systems - A patient-centered approach to successful community transition after catastrophic injury Michael Jones, Julie Gassaway S27 PANEL: Developing Sustainable Strategies for the Implementation of Patient-Centered Care across Diverse US Healthcare Systems - Conducting PCOR to integrate mental health and cancer screening services in primary care Jonathan Tobin S28 PANEL: Developing Sustainable Strategies for the Implementation of Patient-Centered Care across Diverse US Healthcare Systems - A comparative effectiveness trial of optimal patient-centered care for US trauma care systems Douglas Zatzick S29 Preferences for in-person communication among patients in a multi-center randomized study of in-person versus telephone communication of genetic test results for cancer susceptibility Angela R Bradbury, Linda Patrick-Miller, Brian Egleston, Olufunmilayo I Olopade, Michael J Hall, Mary B Daly, Linda Fleisher, Generosa Grana, Pamela Ganschow, Dominique Fetzer, Amanda Brandt, Dana Farengo-Clark, Andrea Forman, Rikki S Gaber, Cassandra Gulden, Janice Horte, Jessica Long, Rachelle Lorenz Chambers, Terra Lucas, Shreshtha Madaan, Kristin Mattie, Danielle McKenna, Susan Montgomery, Sarah Nielsen, Jacquelyn Powers, Kim Rainey, Christina Rybak, Michelle Savage, Christina Seelaus, Jessica Stoll, Jill Stopfer, Shirley Yao and Susan Domchek S30 Working towards de-implementation: A mixed methods study in breast cancer surveillance care Erin Hahn, Corrine Munoz-Plaza, Jianjin Wang, Jazmine Garcia Delgadillo, Brian Mittman Michael Gould S31Integrating evidence-based practices for increasing cancer screenings in safety-net primary care systems: A multiple case study using the consolidated framework for implementation research Shuting (Lily) Liang, Michelle C. Kegler, Megan Cotter, Emily Phillips, April Hermstad, Rentonia Morton, Derrick Beasley, Jeremy Martinez, Kara Riehman S32 Observations from implementing an mHealth intervention in an FQHC David Gustafson, Lisa Marsch, Louise Mares, Andrew Quanbeck, Fiona McTavish, Helene McDowell, Randall Brown, Chantelle Thomas, Joseph Glass, Joseph Isham, Dhavan Shah S33 A multicomponent intervention to improve primary care provider adherence to chronic opioid therapy guidelines and reduce opioid misuse: A cluster randomized controlled trial protocol Jane Liebschutz, Karen Lasser S34 Implementing collaborative care for substance use disorders in primary care: Preliminary findings from the summit study Katherine Watkins, Allison Ober, Sarah Hunter, Karen Lamp, Brett Ewing S35 Sustaining a task-shifting strategy for blood pressure control in Ghana: A stakeholder analysis Juliet Iwelunmor, Joyce Gyamfi, Sarah Blackstone, Nana Kofi Quakyi, Jacob Plange-Rhule, Gbenga Ogedegbe S36 Contextual adaptation of the consolidated framework for implementation research (CFIR) in a tobacco cessation study in Vietnam Pritika Kumar, Nancy Van Devanter, Nam Nguyen, Linh Nguyen, Trang Nguyen, Nguyet Phuong, Donna Shelley S37 Evidence check: A knowledge brokering approach to systematic reviews for policy Sian Rudge S38 Using Evidence Synthesis to Strengthen Complex Health Systems in Low- and Middle-Income Countries Etienne Langlois S39 Does it matter: timeliness or accuracy of results? The choice of rapid reviews or systematic reviews to inform decision-making Andrea Tricco S40 Evaluation of the veterans choice program using lean six sigma at a VA medical center to identify benefits and overcome obstacles Sherry Ball, Anne Lambert-Kerzner, Christine Sulc, Carol Simmons, Jeneen Shell-Boyd, Taryn Oestreich, Ashley O'Connor, Emily Neely, Marina McCreight, Amy Labebue, Doreen DiFiore, Diana Brostow, P. Michael Ho, David Aron S41 The influence of local context on multi-stakeholder alliance quality improvement activities: A multiple case study Jillian Harvey, Megan McHugh, Dennis Scanlon S42 Increasing physical activity in early care and education: Sustainability via active garden education (SAGE) Rebecca Lee, Erica Soltero, Nathan Parker, Lorna McNeill, Tracey Ledoux S43 Marking a decade of policy implementation: The successes and continuing challenges of a provincial school food and nutrition policy in Canada Jessie-Lee McIsaac, Kate MacLeod, Nicole Ata, Sherry Jarvis, Sara Kirk S44 Use of research evidence among state legislators who prioritize mental health and substance abuse issues Jonathan Purtle, Elizabeth Dodson, Ross Brownson S45 PANEL: Effectiveness-Implementation Hybrid Designs: Clarifications, Refinements, and Additional Guidance Based on a Systematic Review and Reports from the Field - Hybrid type 1 designs Brian Mittman, Geoffrey Curran S46 PANEL: Effectiveness-Implementation Hybrid Designs: Clarifications, Refinements, and Additional Guidance Based on a Systematic Review and Reports from the Field - Hybrid type 2 designs Geoffrey Curran S47 PANEL: Effectiveness-Implementation Hybrid Designs: Clarifications, Refinements, and Additional Guidance Based on a Systematic Review and Reports from the Field - Hybrid type 3 designs Jeffrey Pyne S48 Linking team level implementation leadership and implementation climate to individual level attitudes, behaviors, and implementation outcomes Gregory Aarons, Mark Ehrhart, Elisa Torres S49 Pinpointing the specific elements of local context that matter most to implementation outcomes: Findings from qualitative comparative analysis in the RE-inspire study of VA acute stroke care Edward Miech S50 The GO score: A new context-sensitive instrument to measure group organization level for providing and improving care Edward Miech S51 A research network approach for boosting implementation and improvement Kathleen Stevens, I.S.R.N. Steering Council S52 PANEL: Qualitative methods in D&I Research: Value, rigor and challenge - The value of qualitative methods in implementation research Alison Hamilton S53 PANEL: Qualitative methods in D&I Research: Value, rigor and challenge - Learning evaluation: The role of qualitative methods in dissemination and implementation research Deborah Cohen S54 PANEL: Qualitative methods in D&I Research: Value, rigor and challenge - Qualitative methods in D&I research Deborah Padgett S55 PANEL: Maps & models: The promise of network science for clinical D&I - Hospital network of sharing patients with acute and chronic diseases in California Alexandra Morshed S56 PANEL: Maps & models: The promise of network science for clinical D&I - The use of social network analysis to identify dissemination targets and enhance D&I research study recruitment for pre-exposure prophylaxis for HIV (PrEP) among men who have sex with men Rupa Patel S57 PANEL: Maps & models: The promise of network science for clinical D&I - Network and organizational factors related to the adoption of patient navigation services among rural breast cancer care providers Beth Prusaczyk S58 A theory of de-implementation based on the theory of healthcare professionals’ behavior and intention (THPBI) and the becker model of unlearning David C. Aron, Divya Gupta, Sherry Ball S59 Observation of registered dietitian nutritionist-patient encounters by dietetic interns highlights low awareness and implementation of evidence-based nutrition practice guidelines Rosa Hand, Jenica Abram, Taylor Wolfram S60 Program sustainability action planning: Building capacity for program sustainability using the program sustainability assessment tool Molly Hastings, Sarah Moreland-Russell S61 A review of D&I study designs in published study protocols Rachel Tabak, Alex Ramsey, Ana Baumann, Emily Kryzer, Katherine Montgomery, Ericka Lewis, Margaret Padek, Byron Powell, Ross Brownson S62 PANEL: Geographic variation in the implementation of public health services: Economic, organizational, and network determinants - Model simulation techniques to estimate the cost of implementing foundational public health services Cezar Brian Mamaril, Glen Mays, Keith Branham, Lava Timsina S63 PANEL: Geographic variation in the implementation of public health services: Economic, organizational, and network determinants - Inter-organizational network effects on the implementation of public health services Glen Mays, Rachel Hogg S64 PANEL: Building capacity for implementation and dissemination of the communities that care prevention system at scale to promote evidence-based practices in behavioral health - Implementation fidelity, coalition functioning, and community prevention system transformation using communities that care Abigail Fagan, Valerie Shapiro, Eric Brown S65 PANEL: Building capacity for implementation and dissemination of the communities that care prevention system at scale to promote evidence-based practices in behavioral health - Expanding capacity for implementation of communities that care at scale using a web-based, video-assisted training system Kevin Haggerty, David Hawkins S66 PANEL: Building capacity for implementation and dissemination of the communities that care prevention system at scale to promote evidence-based practices in behavioral health - Effects of communities that care on reducing youth behavioral health problems Sabrina Oesterle, David Hawkins, Richard Catalano S68 When interventions end: the dynamics of intervention de-adoption and replacement Virginia McKay, M. Margaret Dolcini, Lee Hoffer S69 Results from next-d: can a disease specific health plan reduce incident diabetes development among a national sample of working-age adults with pre-diabetes? Tannaz Moin, Jinnan Li, O. Kenrik Duru, Susan Ettner, Norman Turk, Charles Chan, Abigail Keckhafer, Robert Luchs, Sam Ho, Carol Mangione S70 Implementing smoking cessation interventions in primary care settings (STOP): using the interactive systems framework Peter Selby, Laurie Zawertailo, Nadia Minian, Dolly Balliunas, Rosa Dragonetti, Sarwar Hussain, Julia Lecce S71 Testing the Getting To Outcomes implementation support intervention in prevention-oriented, community-based settings Matthew Chinman, Joie Acosta, Patricia Ebener, Patrick S Malone, Mary Slaughter S72 Examining the reach of a multi-component farmers’ market implementation approach among low-income consumers in an urban context Darcy Freedman, Susan Flocke, Eunlye Lee, Kristen Matlack, Erika Trapl, Punam Ohri-Vachaspati, Morgan Taggart, Elaine Borawski S73 Increasing implementation of evidence-based health promotion practices at large workplaces: The CEOs Challenge Amanda Parrish, Jeffrey Harris, Marlana Kohn, Kristen Hammerback, Becca McMillan, Peggy Hannon S74 A qualitative assessment of barriers to nutrition promotion and obesity prevention in childcare Taren Swindle, Geoffrey Curran, Leanne Whiteside-Mansell, Wendy Ward S75 Documenting institutionalization of a health communication intervention in African American churches Cheryl Holt, Sheri Lou Santos, Erin Tagai, Mary Ann Scheirer, Roxanne Carter, Janice Bowie, Muhiuddin Haider, Jimmie Slade, Min Qi Wang S76 Reduction in hospital utilization by underserved patients through use of a community-medical home Andrew Masica, Gerald Ogola, Candice Berryman, Kathleen Richter S77 Sustainability of evidence-based lay health advisor programs in African American communities: A mixed methods investigation of the National Witness Project Rachel Shelton, Lina Jandorf, Deborah Erwin S78 Predicting the long-term uninsured population and analyzing their gaps in physical access to healthcare in South Carolina Khoa Truong S79 Using an evidence-based parenting intervention in churches to prevent behavioral problems among Filipino youth: A randomized pilot study Joyce R. Javier, Dean Coffey, Sheree M. Schrager, Lawrence Palinkas, Jeanne Miranda S80 Sustainability of elementary school-based health centers in three health-disparate southern communities Veda Johnson, Valerie Hutcherson, Ruth Ellis S81 Childhood obesity prevention partnership in Louisville: creative opportunities to engage families in a multifaceted approach to obesity prevention Anna Kharmats, Sandra Marshall-King, Monica LaPradd, Fannie Fonseca-Becker S82 Improvements in cervical cancer prevention found after implementation of evidence-based Latina prevention care management program Deanna Kepka, Julia Bodson, Echo Warner, Brynn Fowler S83 The OneFlorida data trust: Achieving health equity through research & training capacity building Elizabeth Shenkman, William Hogan, Folakami Odedina, Jessica De Leon, Monica Hooper, Olveen Carrasquillo, Renee Reams, Myra Hurt, Steven Smith, Jose Szapocznik, David Nelson, Prabir Mandal S84 Disseminating and sustaining medical-legal partnerships: Shared value and social return on investment James Teufel

There are many advantages to individual participant data meta-analysis for combining data from multiple studies. These advantages include greater power to detect effects, increased sample heterogeneity, and the ability to perform more sophisticated analyses than meta-analyses that rely on published results. However, a fundamental challenge is that it is unlikely that variables of interest are measured the same way in all of the studies to be combined. We propose that this situation can be viewed as a missing data problem in which some outcomes are entirely missing within some trials and use multiple imputation to fill in missing measurements. We apply our method to five longitudinal adolescent depression trials where four studies used one depression measure and the fifth study used a different depression measure. None of the five studies contained both depression measures. We describe a multiple imputation approach for filling in missing depression measures that makes use of external calibration studies in which both depression measures were used. We discuss some practical issues in developing the imputation model including taking into account treatment group and study. We present diagnostics for checking the fit of the imputation model and investigate whether external information is appropriately incorporated into the imputed values.

There is a growing interest in examining network processes with a mix of qualitative and quantitative network data. Research has consistently shown that free recall name generators entail recall bias and result in missing data that affects the quality of social network data. This study describes a mixed methods approach for collecting social network data, combining a free recall name generator in the context of an online survey with network relations data coded from transcripts of semi-structured qualitative interviews. The combined network provides substantially more information about the network space, both quantitatively and qualitatively. While network density was relatively stable across networks generated from different data collection methodologies, there were noticeable differences in centrality and component structure across networks. The approach presented here involved limited participant burden and generated more complete data than either technique alone could provide. We make suggestions for further development of this method.

BackgroundGiven the importance of influence networks in the implementation of evidence-based practices and interventions, it is unclear whether such networks continue to operate as sources of information and advice when they are segmented and disrupted by randomization to different implementation strategy conditions. The present study examines the linkages across implementation strategy conditions of social influence networks of leaders of youth-serving systems in 12 California counties participating in a randomized controlled trial of community development teams (CDTs) to scale up use of an evidence-based practice.MethodsSemi-structured interviews were conducted with 38 directors, assistant directors, and program managers of county probation, mental health, and child welfare departments. A web-based survey collected additional quantitative data on information and advice networks of study participants. A mixed-methods approach to data analysis was used to create a sociometric data set (n = 176) to examine linkages between treatment and standard conditions.ResultsOf those network members who were affiliated with a county (n = 137), only 6 (4.4%) were directly connected to a member of the opposite implementation strategy condition; 19 (13.9%) were connected by two steps or fewer to a member of the opposite implementation strategy condition; 64 (46.7%) were connected by three or fewer steps to a member of the opposite implementation strategy condition. Most of the indirect steps between individuals who were in different implementation strategy conditions were connections involving a third non-county organizational entity that had an important role in the trial in keeping the implementation strategy conditions separate. When these entities were excluded, the CDT network exhibited fewer components and significantly higher betweenness centralization than did the standard condition network.ConclusionAlthough the integrity of the RCT in this instance was not compromised by study participant influence networks, RCT designs should consider how influence networks may extend beyond boundaries established by the randomization process in implementation studies.Trial registrationNCT00880126.

Behavioral intervention technologies (BITs) are web-based and mobile interventions intended to support patients and consumers in changing behaviors related to health, mental health, and well-being. BITs are provided to patients and consumers in clinical care settings and commercial marketplaces, frequently with little or no evaluation. Current evaluation methods, including RCTs and implementation studies, can require years to validate an intervention. This timeline is fundamentally incompatible with the BIT environment, where technology advancement and changes in consumer expectations occur quickly, necessitating rapidly evolving interventions. However, BITs can routinely and iteratively collect data in a planned and strategic manner and generate evidence through systematic prospective analyses, thereby creating a system that can "learn." A methodologic framework, Continuous Evaluation of Evolving Behavioral Intervention Technologies (CEEBIT), is proposed that can support the evaluation of multiple BITs or evolving versions, eliminating those that demonstrate poorer outcomes, while allowing new BITs to be entered at any time. CEEBIT could be used to ensure the effectiveness of BITs provided through deployment platforms in clinical care organizations or BIT marketplaces. The features of CEEBIT are described, including criteria for the determination of inferiority, determination of BIT inclusion, methods of assigning consumers to BITs, definition of outcomes, and evaluation of the usefulness of the system. CEEBIT offers the potential to collapse initial evaluation and postmarketing surveillance, providing ongoing assurance of safety and efficacy to patients and consumers, payers, and policymakers.

BackgroundAdolescent depression carries a high burden of disease worldwide, but access to care for this population is limited. Prevention is one solution to curtail the negative consequences of adolescent depression. Internet interventions to prevent adolescent depression can overcome barriers to access, but few studies examine long-term outcomes. ObjectiveThis study compares CATCH-IT (Competent Adulthood Transition with Cognitive Behavioral Humanistic and Interpersonal Training), an internet-based intervention, to a general health education active control for depression onset at 12 and 24 months in adolescents presenting to primary care settings. MethodsA 2-site randomized trial, blinded to the principal investigators and assessors, was conducted comparing Competent Adulthood Transition with Cognitive Behavioral Humanistic and Interpersonal Training to health education to prevent depressive episodes in 369 adolescents (193 youths were randomly assigned to Competent Adulthood Transition with Cognitive Behavioral Humanistic and Interpersonal Training and 176 to health education) with subthreshold depressive symptoms or prior depressive episodes. Participants were recruited from primary care settings in the United States. The primary outcome was the occurrence of a depressive episode, determined by the Depression Symptom Rating. The secondary outcome was functioning, measured by the Global Assessment Scale. ResultsIn intention-to-treat analyses, the adjusted hazard ratio favoring Competent Adulthood Transition with Cognitive Behavioral Humanistic and Interpersonal Training for first depressive episode was not statistically significant at 12 months (hazard ratio 0.77, 95% CI 0.42-1.40, P=.39) and 24 months (hazard ratio 0.87, 95% CI 0.52-1.47, P=.61). Competent Adulthood Transition with Cognitive Behavioral Humanistic and Interpersonal Training provided preventive benefit for first depressive episode for those with mild hopelessness or at least moderate paternal monitoring at baseline. Global Assessment Scale scores improved comparably in both groups (intention-to-treat). ConclusionsA technology-based intervention for adolescent depression prevention implemented in primary care did not have additional benefit at 12 or 24 months. Further research is necessary to determine whether internet interventions have long-term benefit. Trial RegistrationClinicalTrials.gov NCT01893749; http://clinicaltrials.gov/ct2/show/NCT01893749.

The HIV epidemic continues to disproportionately affect ethnic minority youth. These disconcerting health disparities indicate that although existing HIV preventive strategies for ethnic minority youth have been efficacious, they have not significantly reduced the impact of the epidemic in this population. Macro-level interventions, such as structural or policy interventions, have the potential to impact the HIV epidemic at a population level, and thus reduce the HIV health disparities that exist among ethnic minority youth and other segments of the U.S. population. This article calls for a paradigm shift to develop, evaluate, and disseminate interventions that target upstream/macro-level factors or that, at a minimum, integrate both a macro and individual level perspective. The article also discusses the challenges in developing and evaluating such interventions. Psychologists and other behavioral scientists can play a critical role in reducing the impact of HIV on ethnic minority youth by integrating macro-level approaches to future HIV prevention strategies.