Weight Loss in Short-Term Interventions for Physical Activity and Nutrition Among Adults With Overweight or Obesity: A Systematic Review and Meta-Analysis.

Introduction: Reaching, enrolling, and retaining participants in lengthy lifestyle change interventions for weight loss is a major challenge. The objective of our meta-analysis was to investigate whether lifestyle interventions addressing nutrition and physical activity lasting 6 months or less are effective for weight loss. Methods: We searched for peer-reviewed studies on lifestyle change interventions of 6 months or less published from 2012 through 2023. Studies were screened based on inclusion criteria, including randomized controlled trials (RCTs) for adults with overweight or obesity. We used a random-effects model to pool the mean difference in weight loss between intervention and control groups. We also performed subgroup analyses by intervention length and control type. Results: Fourteen RCTs were identified and included in our review. Half had interventions lasting less than 13 weeks, and half lasted from 13 to 26 weeks. Seven were delivered remotely, 4 were delivered in person, and 3 used combined methods. The pooled mean difference in weight change was -2.59 kg (95% CI, -3.47 to -1.72). The pooled mean difference measured at the end of the intervention was -2.70 kg (95% CI, -3.69 to -1.71) among interventions lasting less than 13 weeks and -2.40 kg (95% CI, -4.44 to -0.37) among interventions of 13 to 26 weeks. Conclusion: Short-term multicomponent interventions involving physical activity and nutrition can achieve weight loss for adults with overweight or obesity. Offering short-term interventions as alternatives to long-term ones may reach people who otherwise would be unwilling or unable to enroll in or complete longer programs.

Integrating the Consolidated Framework for Implementation Research (CFIR) into a Culturally Responsive Evaluation (CRE) Approach to Conduct Mixed-Method Evaluations of Diabetes Prevention and Management Programs Reaching Underresourced Populations and Communities.

Diabetes is a significant population health threat. Evidence-based interventions, such as the Centers for Disease Control and Prevention's National Diabetes Prevention Program and diabetes self-management education and support programs, can help prevent, delay, or manage the disease. However, participation is suboptimal, especially among populations who are at an increased risk of developing diabetes. Evaluations of programs reaching populations who are medically underserved or people with lower incomes can help elucidate how best to tailor evidence-based interventions, but it is also important for evaluations to account for cultural and contextual factors. Culturally responsive evaluation (CRE) is a framework for centering an evaluation in the culture of the programs being evaluated. We integrated CRE with implementation and outcome constructs from the Adapted Consolidated Framework for Implementation Research (CFIR) to ensure that the evaluation produced useful evidence for putting evidence-based diabetes interventions to use in real-world settings, reaching populations who are at an increased risk of developing diabetes. The paper provides an overview of how we integrated CRE and CFIR approaches to conduct mixed-methods evaluations of evidence-based diabetes interventions.

Determining the predictors of innovation implementation in healthcare: a quantitative analysis of implementation effectiveness.

BACKGROUND: The failure rates for implementing complex innovations in healthcare organizations are high. Estimates range from 30% to 90% depending on the scope of the organizational change involved, the definition of failure, and the criteria to judge it. The innovation implementation framework offers a promising approach to examine the organizational factors that determine effective implementation. To date, the utility of this framework in a healthcare setting has been limited to qualitative studies and/or group level analyses. Therefore, the goal of this study was to quantitatively examine this framework among individual participants in the National Cancer Institute's Community Clinical Oncology Program using structural equation modeling. METHODS: We examined the innovation implementation framework using structural equation modeling (SEM) among 481 physician participants in the National Cancer Institute's Community Clinical Oncology Program (CCOP). The data sources included the CCOP Annual Progress Reports, surveys of CCOP physician participants and administrators, and the American Medical Association Physician Masterfile. RESULTS: Overall the final model fit well. Our results demonstrated that not only did perceptions of implementation climate have a statistically significant direct effect on implementation effectiveness, but physicians' perceptions of implementation climate also mediated the relationship between organizational implementation policies and practices (IPP) and enrollment (p <0.05). In addition, physician factors such as CCOP PI status, age, radiological oncologists, and non-oncologist specialists significantly influenced enrollment as well as CCOP organizational size and structure, which had indirect effects on implementation effectiveness through IPP and implementation climate. CONCLUSIONS: Overall, our results quantitatively confirmed the main relationship postulated in the innovation implementation framework between IPP, implementation climate, and implementation effectiveness among individual physicians. This finding is important, as although the model has been discussed within healthcare organizations before, the studies have been predominately qualitative in nature and/or at the organizational level. In addition, our findings have practical applications. Managers looking to increase implementation effectiveness of an innovation should focus on creating an environment that physicians perceive as encouraging implementation. In addition, managers should consider instituting specific organizational IPP aimed at increasing positive perceptions of implementation climate. For example, IPP should include specific expectations, support, and rewards for innovation use.

Organizational and physician factors associated with patient enrollment in cancer clinical trials.

BACKGROUND: Our purpose was to identify physicians' individual characteristics, attitudes, and organizational contextual factors associated with higher enrollment of patients in cancer clinical trials among physician participants in the National Cancer Institute's Community Clinical Oncology Program (CCOP). We hypothesized that physicians' individual characteristics, such as age, medical specialty, tenure, CCOP organizational factors (i.e. policies and procedures to encourage enrollment), and attitudes toward participating in CCOP would directly determine enrollment. We also hypothesized that physicians' characteristics and CCOP organizational factors would influence physicians' attitudes toward participating in CCOP, which in turn would predict enrollment. METHODS: We evaluated enrollment in National Cancer Institute-sponsored cancer clinical trials in 2011 among 481 physician participants using Structural Equation Modeling. The data sources include CCOP Annual Progress Reports, two surveys of CCOP administrators and physician participants, and the American Medical Association Masterfile. RESULTS: Physicians with more positive attitudes toward participating in CCOP enrolled more patients than physicians with less positive attitudes. In addition, physicians who practiced in CCOPs that had more supportive policies and practices in place to encourage enrollment (i.e. offered trainings, provided support to screen and enroll patients, gave incentives to enroll patients, instituted minimum accrual expectations) also significantly enrolled more patients. Physician status as CCOP Principal Investigator had a positive direct effect on enrollment, while physician age and non-oncology medical specialty had negative direct effects on enrollment. Neither physicians' characteristics nor CCOP organizational factors indirectly influenced enrollment through an effect on physician attitudes. CONCLUSION: We examined whether individual physicians' characteristics and attitudes, as well as CCOP organizational factors, influenced patient enrollment in cancer clinical trials among CCOP physicians. Physician attitudes and CCOP organizational factors had positive direct effects, but not indirect effects, on physician enrollment of patients. Our results could be used to develop physician-directed strategies aimed at increasing involvement in clinical research. For example, administrators may want to ensure physicians have access to support staff to help screen and enroll patients or institute minimum accrual expectations. Our results also highlight the importance of recruiting physicians for volunteer clinical research programs whose attitudes and values align with programmatic goals. Given that physician involvement is a key determinant of patient enrollment in clinical trials, these interventions could expand the overall number of patients involved in cancer research. These strategies will be increasingly important as the CCOP network continues to evolve.

Assessing the feasibility of a virtual tumor board program: a case study.

Multidisciplinary tumor boards involve various providers (e.g., oncology physicians, nurses) in patient care. Although many community hospitals have local tumor boards that review all types of cases, numerous providers, particularly in rural areas and smaller institutions, still lack access to tumor boards specializing in a particular type of cancer (e.g., hematologic). Videoconferencing technology can connect providers across geographic locations and institutions; however, virtual tumor board (VTB) programs using this technology are uncommon. In this study, we evaluated the feasibility of a new VTB program at the University of North Carolina (UNC) Lineberger Comprehensive Cancer Center, which connects community-based clinicians to UNC tumor boards representing different cancer types. Methods included observations, interviews, and surveys. Our findings suggest that participants were generally satisfied with the VTB. Cases presented to the VTB were appropriate, sufficient information was available for discussion, and technology problems were uncommon. UNC clinicians viewed the VTB as a service to patients and colleagues and an opportunity for clinical trial recruitment. Community-based clinicians presenting at VTBs valued the discussion, even if it simply confirmed their original treatment plan or did not yield consensus recommendations. Barriers to participation for community-based clinicians included timing of the VTB and lack of reimbursement. To maximize benefits of the VTB, these barriers should be addressed, scheduling and preparation processes optimized, and appropriate measures for evaluating impact identified.

Prioritizing research needs and opportunities at the intersection of implementation science and engagement science.

BACKGROUND: There has been increased attention to the need for, and the positive impact of, engaged or participatory science in recent years. Implementation scientists have an opportunity to leverage and contribute to engagement science (ES) through the systematic integration of engagement into implementation science (IS). The purpose of this study was to gather information from researchers and others to develop a prioritized list of research needs and opportunities at the intersection of IS and ES. METHODS: We conducted three Zoom-based focus groups with 20 researchers to generate a list of unmet needs, barriers, and to describe normative themes about use of ES and IS. Then a panel of nine experts in IS and/or engagement ranked the needs and barriers using a survey and met via a Zoom meeting to discuss and generate research opportunities and questions, with reference to the focus group outputs. RESULTS: Respondents and experts concurred on the importance of engagement in IS. Focus group participants reported 28 needs and barriers under the themes of 1) need for best practice guidance related to engagement processes and outcomes and 2) structural barriers to integrating ES in IS. The expert panel prioritized six structural barriers and four barriers related to generating best practice guidance, with corresponding recommendations on research opportunities. Example research opportunities related to engagement processes included: define "successful" engagement in IS contexts; adapt engagement tools and best practices from other disciplines into IS. Example research opportunities related to outcomes included: assess the impact of engagement on IS outcomes; examine engagement practices that lead to optimal engaged research. Example research opportunities related to structural barriers included: leverage research evidence to create structural changes needed to expand support for engaged IS; examine factors that influence institutional buy-in of engagement in IS. CONCLUSIONS: Research needs exist that relate to engagement processes, outcomes, and structural barriers, even for scientists who value engaged research. Expert panelists recommended sequential and reinforcing research opportunities that implementation and engagement scientists can tackle together to advance both fields and health equity. Future work should assess insights from broader invested parties, particularly patients and community members.

Recruitment Strategies in the Integration of Mobile Health Into Sickle Cell Disease Care to Increase Hydroxyurea Utilization Study (meSH): Multicenter Survey Study.

BACKGROUND: Hydroxyurea is an evidence-based disease-modifying therapy for sickle cell disease (SCD) but is underutilized. The Integration of Mobile Health into Sickle Cell Disease Care to Increase Hydroxyurea Utilization (meSH) multicenter study leveraged mHealth to deliver targeted interventions to patients and providers. SCD studies often underenroll; and recruitment strategies in the SCD population are not widely studied. Unanticipated events can negatively impact enrollment, making it important to study strategies that ensure adequate study accrual. OBJECTIVE: The goal of this study was to evaluate enrollment barriers and the impact of modified recruitment strategies among patients and providers in the meSH study in response to a global emergency. METHODS: Recruitment was anticipated to last 2 months for providers and 6 months for patients. The recruitment strategies used with patients and providers, new recruitment strategies, and recruitment rates were captured and compared. To document recruitment adaptations and their reasons, study staff responsible for recruitment completed an open-ended 9-item questionnaire eliciting challenges to recruitment and strategies used. Themes were extrapolated using thematic content analysis. RESULTS: Total enrollment across the 7 sites included 89 providers and 293 patients. The study acceptance rate was 85.5% (382/447) for both patients and providers. The reasons patients declined participation were most frequently a lack of time and interest in research, while providers mostly declined because of self-perceived high levels of SCD expertise, believing they did not need the intervention. Initially, recruitment involved an in-person invitation to participate during clinic visits (patients), staff meetings (providers), or within the office (providers). We identified several important recruitment challenges, including (1) lack of interest in research, (2) lack of human resources, (3) unavailable physical space for recruitment activities, and (4) lack of documentation to verify eligibility. Adaptive strategies were crucial to alleviate enrollment disruptions due to the COVID-19 pandemic. These included remote approaching and consenting (eg, telehealth, email, and telephone) for patients and providers. Additionally, for patients, recruitment was enriched by simplification of enrollment procedures (eg, directly approaching patients without a referral from the provider) and a multitouch method (ie, warm introductions with flyers, texts, and patient portal messages). We found that patient recruitment rates were similar between in-person and adapted (virtual with multitouch) approaches (167/200, 83.5% and 126/143, 88.1%, respectively; P=.23). However, for providers, recruitment was significantly higher for in-person vs remote recruitment (48/50, 96% and 41/54, 76%, respectively, P<.001). CONCLUSIONS: We found that timely adaptation in recruitment strategies secured high recruitment rates using an assortment of enriched remote recruitment strategies. Flexibility in approach and reducing the burden of enrollment procedures for participants aided enrollment. It is important to continue identifying effective recruitment strategies in studies involving patients with SCD and their providers and the impact and navigation of recruitment challenges. TRIAL REGISTRATION: ClinicalTrials.Gov NCT03380351; https://clinicaltrials.gov/study/NCT03380351. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/16319.

Accuracy and reliability of self-reported weight and height in the Sister Study.

OBJECTIVE: To assess the accuracy and reliability of self-reported weight and height and identify the factors associated with reporting accuracy. DESIGN: Analysis of self-reported and measured weight and height from participants in the Sister Study (2003-2009), a nationwide cohort of 50 884 women aged 35-74 years in the USA with a sister with breast cancer. SETTING: Weight and height were reported via computer-assisted telephone interview (CATI) and self-administered questionnaires, and measured by examiners. SUBJECTS: Early enrolees in the Sister Study. There were 18 639 women available for the accuracy analyses and 13 316 for the reliability analyses. RESULTS: Using weighted kappa statistics, comparisons were made between CATI responses and examiner measures to assess accuracy and CATI and questionnaire responses to assess reliability. Polytomous logistic regression evaluated factors associated with over- or under-reporting. Compared with measured values, agreement was 96 % for reported height (±1 inch (±2·5 cm); weighted κ = 0·84) and 67 % for weight (±3 lb (±1·36 kg); weighted κ = 0·92). Obese women (BMI ≥ 30 kg/m2) were more likely than normal-weight women to under-report weight by ≥5 % and underweight women (BMI < 18·5 kg/m2) were more likely to over-report. Among normal-weight and overweight women (18·5 kg/m2 ≤ BMI < 30 kg/m2), weight cycling and lifetime weight difference ≥50 lb (≥22·68 kg) were associated with over-reporting. CONCLUSIONS: US women in the Sister Study were reasonably reliable and accurate in reporting weight and height. Women with normal-range BMI reported most accurately. Overweight and obese women and those with weight fluctuations were less accurate, but even among obese women, few under-reported their weight by >10 %.

A qualitative framework-based evaluation of radiology clinical decision support initiatives: eliciting key factors to physician adoption in implementation.

OBJECTIVES: To illustrate key contextual factors that may have effects on clinical decision support (CDS) adoption and, ultimately, success. MATERIALS AND METHODS: We conducted a qualitative evaluation of 2 similar radiology CDS innovations for near-term endpoints affecting adoption and present the findings using an evaluation framework. We identified key contextual factors between these 2 innovations and determined important adoption differences between them. RESULTS: Degree of electronic health record integration, approach to education and training, key drivers of adoption, and tailoring of the CDS to the clinical context were handled differently between the 2 innovations, contributing to variation in their relative degrees of adoption and use. Attention to these factors had impacts on both near and later-term measures of success (eg, patient outcomes). DISCUSSION: CDS adoption is a well-studied early-term measure of CDS success that directly impacts outcomes. Adoption requires attention throughout the design phases of an intervention especially to key factors directly affecting it, including how implementation across multiple sites and systems complicates adoption, which prior experience with CDS matters, and that practice guidelines invariably require tailoring to the clinical context. CONCLUSION: With better planning for the capture of early-term measures of successful CDS implementation, especially adoption, critical adjustments may be made to ensure that the CDS is effectively implemented to be successful.

Strategies for Successful Survivorship Care Plan Implementation: Results From a Qualitative Study.

INTRODUCTION: Care for US cancer survivors is often fragmented, contributing to poor health outcomes. Care and outcomes may improve when survivors and follow-up care providers receive survivorship care plans (SCPs), written documents containing information regarding cancer diagnosis, treatment, surveillance plans, and health promotion. However, implementing SCPs is challenging. As such, we sought to identify strategies for successfully implementing SCPs. METHODS: We measured SCP implementation using performance data from cancer programs participating in the American Society of Clinical Oncology Quality Oncology Practice Initiative, an oncologist-led quality assessment and improvement program. We used semistructured interviews with cancer program employees (eg, physicians) to identify strategies for successfully implementing SCPs by comparing approaches in cancer programs that, according to Quality Oncology Practice Initiative performance indicators, developed and delivered SCPs to a relatively small proportion of eligible survivors and their follow-up care providers (ie, low performers; n = 6 participants in five programs) with approaches among programs with better performance (ie, moderate performers; n = 15 participants in nine programs). RESULTS: Ten of 14 cancer programs developed SCPs for ≥ 50% of eligible survivors; two of 14 delivered SCPs to any survivors; and eight of 14 delivered SCPs to ≥ 25% of follow-up care providers. We found that moderate performers proactively addressed SCP requirements, leveraged requirements to improve survivorship care, set internal targets, automated implementation, had active leaders and champions, and tasked appropriate employees with SCP implementation. CONCLUSION: SCP implementation remains challenging. We identified strategies for successfully implementing SCPs. Future research should examine how cancer programs have achieved these strategies; findings could contribute to an understanding of the changes needed to implement comprehensive survivorship care.

Context matters: measuring implementation climate among individuals and groups.

BACKGROUND: It has been noted that implementation climate is positively associated with implementation effectiveness. However, issues surrounding the measurement of implementation climate, or the extent to which organizational members perceive that innovation use is expected, supported and rewarded by their organization remain. Specifically, it is unclear whether implementation climate can be measured as a global construct, whether individual or group-referenced items should be used, and whether implementation climate can be assessed at the group or organizational level. METHODS: This research includes two cross-sectional studies with data collected via surveys at the individual level. The first study assessed the implementation climate perceptions of physicians participating in the National Cancer Institute's (NCI) Community Clinical Oncology Program (CCOP), and the second study assessed the perceptions of children's behavioral health clinicians implementing a treatment innovation. To address if implementation climate is a global construct, we used confirmatory factor analysis. To address how implementation climate should be measured and at what level, we followed a five-step framework outlined by van Mierlo and colleagues. This framework includes exploratory factor analysis and correlations to assess differences between individual and group-referenced items and intraclass correlations, interrater agreements, and exploratory factor analysis to determine if implementation climate can be assessed at the organizational level. RESULTS: The confirmatory factor analysis demonstrated that implementation climate is a global construct consisting of items related to expectations, support and rewards. There are mixed results, however, as to whether implementation climate should be measured using individual or group-referenced items. In our first study, where physicians were geographically dispersed and practice independently, there were no differences based on the type of items used, and implementation climate was an individual level construct. However, in the second study, in which clinicians practice in a central location and interact more frequently, group-referenced items may be appropriate. In addition, implementation climate could be considered an organizational level construct. CONCLUSIONS: The results are context-specific. Researchers should carefully consider the study setting when measuring implementation climate. In addition, more opportunities are needed to validate this measure and understand how well it predicts and explains implementation effectiveness.

Organizational readiness for implementing change: a psychometric assessment of a new measure.

BACKGROUND: Organizational readiness for change in healthcare settings is an important factor in successful implementation of new policies, programs, and practices. However, research on the topic is hindered by the absence of a brief, reliable, and valid measure. Until such a measure is developed, we cannot advance scientific knowledge about readiness or provide evidence-based guidance to organizational leaders about how to increase readiness. This article presents results of a psychometric assessment of a new measure called Organizational Readiness for Implementing Change (ORIC), which we developed based on Weiner's theory of organizational readiness for change. METHODS: We conducted four studies to assess the psychometric properties of ORIC. In study one, we assessed the content adequacy of the new measure using quantitative methods. In study two, we examined the measure's factor structure and reliability in a laboratory simulation. In study three, we assessed the reliability and validity of an organization-level measure of readiness based on aggregated individual-level data from study two. In study four, we conducted a small field study utilizing the same analytic methods as in study three. RESULTS: Content adequacy assessment indicated that the items developed to measure change commitment and change efficacy reflected the theoretical content of these two facets of organizational readiness and distinguished the facets from hypothesized determinants of readiness. Exploratory and confirmatory factor analysis in the lab and field studies revealed two correlated factors, as expected, with good model fit and high item loadings. Reliability analysis in the lab and field studies showed high inter-item consistency for the resulting individual-level scales for change commitment and change efficacy. Inter-rater reliability and inter-rater agreement statistics supported the aggregation of individual level readiness perceptions to the organizational level of analysis. CONCLUSIONS: This article provides evidence in support of the ORIC measure. We believe this measure will enable testing of theories about determinants and consequences of organizational readiness and, ultimately, assist healthcare leaders to reduce the number of health organization change efforts that do not achieve desired benefits. Although ORIC shows promise, further assessment is needed to test for convergent, discriminant, and predictive validity.

Achieving high cancer control trial enrollment in the community setting: an analysis of the Community Clinical Oncology Program.

Determining the factors that lead to successful enrollment of patients in cancer control clinical trials is essential as cancer patients are often burdened with side effects such as pain, nausea, and fatigue. One promising intervention for increasing enrollment in cancer control trials is the National Cancer Institute's Community Clinical Oncology Program (CCOP). In this article, we examined CCOP staffing, policies, and procedures associated with enrollment in control trials. Data were obtained from three sources: the online CCOP, MB-CCOP, and Research Base Management System, CCOP Annual Progress Reports, and a survey of CCOP Administrators conducted in 2011. We analyzed cancer control trial accrual in 2011 among 46 CCOPs using multivariate regression. Three factors were significant predictors of accrual. First, having a team of staff dedicated to enrolling patients in control and prevention trials, compared to having no dedicated staff, was associated on average with an additional 30 patients enrolled in control trials (p<0.05). Second, CCOPs that recognized physicians for enrolling a large number of patients compared to CCOPs that did not recognize high enrolling physicians enrolled on average an additional 25 patients in control trials (p<0.05). Lastly, the number of cancer control trials available was also associated with enrollment (ß=5.50, p<0.00). Our results indicate that CCOPs looking to increase enrollment in control trials should consider dedicating a team of staff to enroll patients in these types of trials. In addition, CCOPs or other volunteer research systems looking to increase physician participation should consider recognizing high enrolling physicians.

Organizational designs for achieving high treatment trial enrollment: a fuzzy-set analysis of the community clinical oncology program.

PURPOSE: To examine the organizational design features that were consistently associated in 2010 with high levels of patient enrollment onto National Cancer Institute (NCI) cancer treatment trials among the oncology practices and hospitals participating in the NCI Community Clinical Oncology Program (CCOP). METHODS: Fuzzy-set qualitative comparative analysis was used to identify the recipes (ie, combinations of organizational design features) that CCOPs used to achieve high levels of patient enrollment onto NCI treatment trials in 2010. Four organizational design features were examined: number of open treatment trials with at least one patient enrolled, number of newly diagnosed patients with cancer, number of CCOP-affiliated physicians, and number of CCOP-affiliated hospitals or practices where patient enrollment could occur. Data were obtained from NCI data systems and CCOP grant progress reports. RESULTS: Two recipes were consistently associated with high levels of patient enrollment onto NCI treatment trials in 2010: having many open treatment trials and many new patients with cancer, and having many open treatment trials and many affiliated hospitals or practices. Together, these recipes accounted for nearly two thirds of CCOP membership in the high-performance set in 2010. CONCLUSION: No single organizational design feature, by itself, was consistently associated with high levels of patient enrollment onto NCI treatment trials in 2010. Having a large menu of active treatment trials may be necessary to achieve high-patient enrollment performance, but this is not sufficient unless combined with either large patient volume or many participating sites.