1
|
Reese PP, Shah S, Funsten E, Amaral S, Audrain-McGovern J, Koepsell K, Wessells H, Harper JD, McCune R, Scales CD, Kirkali Z, Maalouf NM, Lai HH, Desai AC, Al-Khalidi HR, Tasian GE. Using structured problem solving to promote fluid consumption in the prevention of urinary stones with hydration (PUSH) trial. BMC Nephrol 2024; 25:183. [PMID: 38807063 PMCID: PMC11134957 DOI: 10.1186/s12882-024-03605-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 05/09/2024] [Indexed: 05/30/2024] Open
Abstract
BACKGROUND Structured Problem Solving (SPS) is a patient-centered approach to promoting behavior change that relies on productive collaboration between coaches and participants and reinforces participant autonomy. We aimed to describe the design, implementation, and assessment of SPS in the multicenter Prevention of Urinary Stones with Hydration (PUSH) randomized trial. METHODS In the PUSH trial, individuals with a history of urinary stone disease and low urine output were randomized to control versus a multicomponent intervention including SPS that was designed to promote fluid consumption and thereby prevent recurrent stones. We provide details specifically about training and fidelity assessment of the SPS coaches. We report on implementation experiences related to SPS during the initial conduct of the trial. RESULTS With training and fidelity assessment, coaches in the PUSH trial applied SPS to help participants overcome barriers to fluid consumption. In some cases, coaches faced implementation barriers such as variable participant engagement that required tailoring their work with specific participants. The coaches also faced challenges including balancing rapport with problem solving, and role clarity for the coaches. CONCLUSIONS We adapted SPS to the setting of kidney stone prevention and overcame challenges in implementation, such as variable patient engagement. Tools from the PUSH trial may be useful to apply to other health behavior change settings in nephrology and other areas of clinical care. TRIAL REGISTRATION ClinicalTrials.gov Identifier NCT03244189.
Collapse
Affiliation(s)
- Peter P Reese
- Renal-Electrolyte and Hypertension Division, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, 917 Blockley Hall | 423 Guardian Drive, Philadelphia, PA, 19104, USA.
| | - Salima Shah
- Division of Urology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Emily Funsten
- University of New Mexico School of Medicine, Albuquerque, NM, USA
| | - Sandra Amaral
- Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | | | - Hunter Wessells
- Department of Urology, University of Washington, Seattle, WA, USA
| | | | - Rebecca McCune
- Division of Urology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Charles D Scales
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA
- Department of Surgery (Urology), Duke Surgical Center for Outcomes Research & Equity in Surgery, Duke University School of Medicine, Durham, NC, USA
- Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC, USA
| | - Ziya Kirkali
- National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA
| | - Naim M Maalouf
- Department of Internal Medicine and Charles and Jane Pak Center for Mineral Metabolism and Clinical Research, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - H Henry Lai
- Department of Surgery (Urology), Washington University in St. Louis, St. Louis, MO, USA
- Department of Anesthesiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Alana C Desai
- Department of Surgery (Urology), Washington University in St. Louis, St. Louis, MO, USA
| | - Hussein R Al-Khalidi
- Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC, USA
- Department of Biostatistics & Bioinformatics, Duke University School of Medicine, Durham, NC, USA
| | - Gregory E Tasian
- Division of Urology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- University of New Mexico School of Medicine, Albuquerque, NM, USA
| |
Collapse
|
2
|
Diévart F, Bruckert E, Aboyans V, Bekka S, Boccara F, Bourdon Baron Munoz B, Emmerich J, Farnier M, Gallo A, Lemesle G, Paillard F, Schiele F, Kownator S. Management of lipid variables in primary cardiovascular prevention: A position paper from the Heart, Vessels and Metabolism Group of the French Society of Cardiology. Arch Cardiovasc Dis 2024; 117:358-378. [PMID: 38762344 DOI: 10.1016/j.acvd.2024.02.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 02/15/2024] [Accepted: 02/15/2024] [Indexed: 05/20/2024]
Abstract
Low-density lipoprotein cholesterol has been established as a powerful cardiovascular risk factor; its reduction provides a clinical benefit in primary cardiovascular prevention, irrespective of the characteristics of the patients treated. It is useful to tailor low-density lipoprotein cholesterol targets according to the magnitude of cardiovascular risk (low, high or very high) in order to reduce the cardiovascular risk as fully as possible. In order to provide a uniform approach, it is necessary to propose recommendations for good practice, defining strategies for reducing low-density lipoprotein cholesterol. It is also necessary to know their merits, to analyse their practical limits and to propose adaptations, taking into account limitations and national specifics. This position paper aims to analyse the contribution and limits, as well as the adaptation to French practice, of 2019 and 2021 European Society of Cardiology recommendations for the management of lipid variables and cardiovascular prevention.
Collapse
Affiliation(s)
- François Diévart
- Elsan clinique Villette, 18, rue Parmentier, 59240 Dunkerque, France.
| | | | | | - Saïd Bekka
- Institut de diabétologie et nutrition du centre, 28300 Mainvilliers, France
| | | | | | | | - Michel Farnier
- Institut de recherche cardiovasculaire, CHU François-Mitterrand, 21000 Dijon, France
| | | | - Gilles Lemesle
- Institut cœur-poumon, CHRU de Lille, 59000 Lille, France
| | | | | | | |
Collapse
|
3
|
Lin S, Zimmerman E, Datta S, Selby M, Chan T, Fant A. Curated collections for educators: Nine key articles and article series for teaching qualitative research methods. AEM EDUCATION AND TRAINING 2023; 7:e10862. [PMID: 37013134 PMCID: PMC10066497 DOI: 10.1002/aet2.10862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 02/13/2023] [Accepted: 02/23/2023] [Indexed: 06/19/2023]
Abstract
Background Qualitative research explains observations, focusing on how and why phenomena and experiences occur. Qualitative methods go beyond quantitative data and provide critical information inaccessible through quantitative methods. However, at all levels of medical education, there is insufficient exposure to qualitative research. As a result, residents and fellows complete training ill-equipped to appraise and conduct qualitative studies. As a first step to increasing education in qualitative methods, we sought to create a curated collection of papers for faculty to use in teaching qualitative research at the graduate medical education (GME) level. Methods We conducted literature searches on the topic of teaching qualitative research to residents and fellows and queried virtual medical education and qualitative research communities for relevant articles. We searched the reference lists of all articles found through the literature searches and online queries for additional articles. We then conducted a three-round modified Delphi process to select papers most relevant to faculty teaching qualitative research. Results We found no articles describing qualitative research curricula at the GME level. We identified 74 articles on the topic of qualitative research methods. The modified Delphi process identified the top nine articles or article series most relevant for faculty teaching qualitative research. Several articles explain qualitative methods in the context of medical education, clinical care, or emergency care research. Two articles describe standards of high-quality qualitative studies, and one article discusses how to conduct the individual qualitative interview to collect data for a qualitative study. Conclusions While we identified no articles reporting already existing qualitative research curricula for residents and fellows, we were able to create a collection of papers on qualitative research relevant to faculty seeking to teach qualitative methods. These papers describe key qualitative research concepts important in instructing trainees as they appraise and begin to develop their own qualitative studies.
Collapse
Affiliation(s)
- Sophia Lin
- Department of Emergency MedicineWeill Cornell MedicineNew YorkNew YorkUSA
| | - Elise Zimmerman
- Division of Emergency Medicine, Department of PediatricsUniversity of California at San DiegoSan DiegoCaliforniaUSA
| | - Suchismita Datta
- Department of Emergency MedicineNew York University Long Island School of MedicineMineolaNew YorkUSA
| | - Maurice Selby
- Department of Emergency MedicineEmory University School of MedicineAtlantaGeorgiaUSA
| | - Teresa Chan
- Division of Emergency Medicine, Division of Education and Innovation, Department of MedicineMcMaster UniversityHamiltonOntarioCanada
| | - Abra Fant
- Department of Emergency MedicineNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
| |
Collapse
|
4
|
Dodson JA, Schoenthaler A, Fonceva A, Gutierrez Y, Shimbo D, Banco D, Maidman S, Olkhina E, Hanley K, Lee C, Levy NK, Adhikari S. Study design of BETTER-BP: Behavioral economics trial to enhance regulation of blood pressure. INTERNATIONAL JOURNAL OF CARDIOLOGY. CARDIOVASCULAR RISK AND PREVENTION 2022; 15:200156. [PMID: 36573193 PMCID: PMC9789360 DOI: 10.1016/j.ijcrp.2022.200156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 07/19/2022] [Accepted: 10/27/2022] [Indexed: 11/06/2022]
Abstract
Background Nonadherence to antihypertensive medications remains a persistent problem that leads to preventable morbidity and mortality. Behavioral economic strategies represent a novel way to improve antihypertensive medication adherence, but remain largely untested especially in vulnerable populations which stand to benefit the most. The Behavioral Economics Trial To Enhance Regulation of Blood Pressure (BETTER-BP) was designed in this context, to test whether a digitally-enabled incentive lottery improves antihypertensive adherence and reduces systolic blood pressure (SBP). Design BETTER-BP is a pragmatic randomized trial conducted within 3 safety-net clinics in New York City: Bellevue Hospital Center, Gouveneur Hospital Center, and NYU Family Health Centers - Park Slope. The trial will randomize 435 patients with poorly controlled hypertension and poor adherence (<80% days adherent) in a 2:1 ratio (intervention:control) to receive either an incentive lottery versus passive monitoring. The incentive lottery is delivered via short messaging service (SMS) text messages that are delivered based on (1) antihypertensive adherence tracked via a wireless electronic monitoring device, paired with (2) a probability of lottery winning with variable incentives and a regret component for nonadherence. The study intervention lasts for 6 months, and ambulatory systolic blood pressure (SBP) will be measured at both 6 and 12 months to evaluate immediate and durable lottery effects. Conclusions BETTER-BP will generate knowledge about whether an incentive lottery is effective in vulnerable populations to improve antihypertensive medication adherence. If successful, this could lead to the implementation of this novel strategy on a larger scale to improve outcomes.
Collapse
Affiliation(s)
- John A. Dodson
- NYU Langone Medical Center, New York, NY, USA
- Corresponding author. New York University Grossman School of Medicine, 227 East 30th Street, TRB 851, New York, NY, 10016, USA.
| | | | - Ana Fonceva
- NYU Langone Medical Center, New York, NY, USA
| | | | - Daichi Shimbo
- Columbia University Irving Medical Center, New York, NY, USA
| | - Darcy Banco
- NYU Langone Medical Center, New York, NY, USA
| | | | | | | | - Carson Lee
- NYU Langone Medical Center, New York, NY, USA
| | | | | |
Collapse
|
5
|
Aschbrenner KA, Kruse G, Gallo JJ, Plano Clark VL. Applying mixed methods to pilot feasibility studies to inform intervention trials. Pilot Feasibility Stud 2022; 8:217. [PMID: 36163045 PMCID: PMC9511762 DOI: 10.1186/s40814-022-01178-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 09/15/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Pilot feasibility studies serve a uniquely important role in preparing for larger scale intervention trials by examining the feasibility and acceptability of interventions and the methods used to test them. Mixed methods (collecting, analyzing, and integrating quantitative and qualitative data and results) can optimize what can be learned from pilot feasibility studies to prepare rigorous intervention trials. Despite increasing use of mixed method designs in intervention trials, there is limited guidance on how to apply these approaches to address pilot feasibility study goals. The purpose of this article is to offer methodological guidance for how investigators can plan to integrate quantitative and qualitative methods within pilot feasibility studies to comprehensively address key research questions. METHODS We used an informal consensus-based process informed by key methodological resources and our team's complementary expertise as intervention researchers and mixed methodologists to develop guidance for applying mixed methods to optimize what can be learned from pilot feasibility studies. We developed this methodological guidance as faculty in the Mixed Methods Research Training Program (MMRTP) for the Health Sciences (R25MH104660) funded by the National Institutes of Health through the Office of Behavioral and Social Science Research. RESULTS We provide the following guidance for applying mixed methods to optimize pilot feasibility studies: (1) identify feasibility domain(s) that will be examined using mixed methods, (2) align quantitative and qualitative data sources for the domain(s) selected for mixing methods, (3) determine the timing of the quantitative and qualitative data collection within the flow of the pilot study, (4) plan integrative analyses using joint displays to understand feasibility, and (5) prepare to draw meta-inferences about feasibility and implications for the future trial from the integrated data. CONCLUSIONS By effectively integrating quantitative and qualitative data within pilot feasibility studies, investigators can harness the potential of mixed methods for developing comprehensive and nuanced understandings about feasibility. Our guidance can help researchers to consider the range of key decisions needed during intervention pilot feasibility testing to achieve a rigorous mixed methods approach generating enhanced insights to inform future intervention trials.
Collapse
Affiliation(s)
| | - Gina Kruse
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, USA
| | - Joseph J Gallo
- Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, USA
| | - Vicki L Plano Clark
- School of Education Research Methods, University of Cincinnati, Cincinnati, USA
| |
Collapse
|
6
|
Reese PP, Barankay I, Putt M, Russell LB, Yan J, Zhu J, Huang Q, Loewenstein G, Andersen R, Testa H, Mussell AS, Pagnotti D, Wesby LE, Hoffer K, Volpp KG. Effect of Financial Incentives for Process, Outcomes, or Both on Cholesterol Level Change: A Randomized Clinical Trial. JAMA Netw Open 2021; 4:e2121908. [PMID: 34605920 PMCID: PMC8491106 DOI: 10.1001/jamanetworkopen.2021.21908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Accepted: 06/15/2021] [Indexed: 11/14/2022] Open
Abstract
Importance Financial incentives may improve health behaviors. It is unknown whether incentives are more effective if they target a key process (eg, medication adherence), an outcome (eg, low-density lipoprotein cholesterol [LDL-C] levels), or both. Objective To determine whether financial incentives awarded daily for process (adherence to statins), awarded quarterly for outcomes (personalized LDL-C level targets), or awarded for process plus outcomes induce reductions in LDL-C levels compared with control. Design, Setting, and Participants A randomized clinical trial was conducted from February 12, 2015, to October 3, 2018; data analysis was performed from October 4, 2018, to May 27, 2021, at the University of Pennsylvania Health System, Philadelphia. Participants included 764 adults with an active statin prescription, elevated risk of atherosclerotic cardiovascular disease, suboptimal LDL-C level, and evidence of imperfect adherence to statin medication. Interventions Interventions lasted 12 months. All participants received a smart pill bottle to measure adherence and underwent LDL-C measurement every 3 months. In the process group, daily financial incentives were awarded for statin adherence. In the outcomes group, participants received incentives for achieving or sustaining at least a quarterly 10-mg/dL LDL-C level reduction. The process plus outcomes group participants were eligible for incentives split between statin adherence and quarterly LDL-C level targets. Main Outcomes and Measures Change in LDL-C level from baseline to 12 months, determined using intention-to-treat analysis. Results Of the 764 participants, 390 were women (51.2%); mean (SD) age was 62.4 (10.0) years, 310 (40.6%) had diabetes, 298 (39.0%) had hypertension, and mean (SD) baseline LDL-C level was 138.8 (37.6) mg/dL. Mean LDL-C level reductions from baseline to 12 months were -36.9 mg/dL (95% CI, -42.0 to -31.9 mg/dL) among control participants, -40.0 mg/dL (95% CI, -44.7 to -35.4 mg/dL) among process participants, -41.6 mg/dL (95% CI, -46.3 to -37.0 mg/dL) among outcomes participants, and -42.8 mg/dL (95% CI, -47.4 to -38.1 mg/dL) among process plus outcomes participants. In exploratory analysis among participants with diabetes and hypertension, no spillover effects of incentives were detected compared with the control group on hemoglobin A1c level and blood pressure over 12 months. Conclusions and Relevance In this randomized clinical trial, process-, outcomes-, or process plus outcomes-based financial incentives did not improve LDL-C levels vs control. Trial Registration ClinicalTrials.gov Identifier: NCT02246959.
Collapse
Affiliation(s)
- Peter P. Reese
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Leonard Davis Institute, University of Pennsylvania, Philadelphia
- Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia
- Department of Medical Ethics and Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Iwan Barankay
- Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia
- Department of Management, Department of Business Economics and Public Policy, The Wharton School, University of Pennsylvania, Philadelphia
| | - Mary Putt
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia
| | - Louise B. Russell
- Leonard Davis Institute, University of Pennsylvania, Philadelphia
- Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia
- Department of Medical Ethics and Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Jiali Yan
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia
| | - Jingsan Zhu
- Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia
- Department of Medical Ethics and Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Qian Huang
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia
| | - George Loewenstein
- Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia
- Department of Social and Decision Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania
| | - Rolf Andersen
- The Heart Group, Lancaster General Health/Penn Medicine, Lancaster, Pennsylvania
- Research Institute, Lancaster General Health/Penn Medicine, Lancaster, Pennsylvania
| | - Heidi Testa
- The Heart Group, Lancaster General Health/Penn Medicine, Lancaster, Pennsylvania
- Research Institute, Lancaster General Health/Penn Medicine, Lancaster, Pennsylvania
| | - Adam S. Mussell
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia
| | - David Pagnotti
- Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia
- Department of Medical Ethics and Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Lisa E. Wesby
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Karen Hoffer
- Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia
- Department of Medical Ethics and Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Kevin G. Volpp
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Leonard Davis Institute, University of Pennsylvania, Philadelphia
- Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia
- Department of Medical Ethics and Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| |
Collapse
|