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Baptist AP, Krishnan JA, Gerald LB, Maye M, Feldman JM, Dixon AE. Implementation of a remote behavioral intervention for older adults with asthma - a pilot study. J Asthma 2024:1-8. [PMID: 39007921 DOI: 10.1080/02770903.2024.2380517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Accepted: 07/10/2024] [Indexed: 07/16/2024]
Abstract
OBJECTIVE Older adults with asthma (OAA) have elevated asthma morbidity rates. A six-session intervention based on self-regulation theory was shown to improve outcomes. However, wide-spread implementation was difficult due to the in-person design. Our objective was to determine the feasibility and acceptability of an updated intervention for OAA that is completely remote, includes a physician component, and utilizes shared decision-making (SDM). METHODS A pilot study of 12 OAA with uncontrolled asthma and their asthma providers was conducted at three health centers. The remote intervention (titled SOAR) consisted of 4 sessions (2 groups and 2 individual). Asthma providers (both specialists and primary care) were sent updates of progress along with information on how to incorporate SDM into the visit. Implementation (feasibility, acceptability, and appropriateness) and clinical (asthma control, asthma quality of life, perceived control, depression, and self-confidence) outcomes were measured. RESULTS SOAR was found to be feasible, acceptable, and appropriate, with values on validated implementation scales similar to those of in-person behavioral interventions. Asthma providers found the program helpful and intended to change care based on the updates. Asthma control scores improved significantly from baseline (14.2 to 16.8, p = 0.04), as did asthma quality of life (4.2 to 4.9, p = 0.03) and self-confidence to manage asthma (7.1 to 8.5, p = 0.02). There was no change in depression nor perceived control scores. CONCLUSION A remote behavioral intervention appeared feasible and acceptable for OAA and their health care providers, and can improve outcomes. Larger scale implementation trials are warranted.
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Affiliation(s)
- Alan P Baptist
- Division of Allergy and Clinical Immunology, Henry Ford Health and MI State University Health Sciences (HFH + MSU), Detroit, MI, USA
| | - Jerry A Krishnan
- Breathe Chicago Center, Division of Pulmonary, Critical Care, Sleep, and Allergy; Office of Population Health Sciences, University of IL Chicago, IL, USA
| | - Lynn B Gerald
- Breathe Chicago Center, Division of Pulmonary, Critical Care, Sleep, and Allergy; Office of Population Health Sciences, University of IL Chicago, IL, USA
| | - Melissa Maye
- Henry Ford Health and Michigan State University Health Sciences (HFH + MSU), Center for Health Policy and Health Services Research, Henry Ford Health, Detroit, MI, USA
| | | | - Anne E Dixon
- Department of Medicine, University of VT, Burlington, USA
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Cuba L, Dürr P, Gessner K, Häcker B, Fietkau R, Siebler J, Pavel M, Neurath MF, Berking C, Wullich B, Brückl V, Beckmann MW, Fromm MF, Dörje F. A Hybrid Type III Effectiveness-Implementation Trial to Optimize Medication Safety With Oral Antitumor Therapy in Real-World: The AMBORA Competence and Consultation Center. JCO Oncol Pract 2024:OP2300694. [PMID: 38848539 DOI: 10.1200/op.23.00694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 01/30/2024] [Accepted: 04/18/2024] [Indexed: 06/09/2024] Open
Abstract
PURPOSE Implementation science endeavors to facilitate the translation of evidence-based research into clinical routine. The clinical pharmacological/pharmaceutical care program evaluated in the randomized AMBORA trial on medication safety with oral antitumor therapeutics (OAT) optimizes care delivery and provides significant benefits for patients, treatment teams, and health care systems. Thus, we aimed to investigate the implementation of this care program within the AMBORA Competence and Consultation Center (AMBORA Center). METHODS The AMBORA Center within a University Comprehensive Cancer Center offered several services (eg, patient consultations) and was evaluated according to the RE-AIM framework. This multicenter hybrid type III trial focused on implementation outcomes (eg, patient recruitment, referring units, evaluation of services) while concurrently investigating effectiveness (eg, side effects, medication errors). Quantitative and qualitative assessments were combined. RESULTS The AMBORA Center conducted over 800 consultations with 420 patients in seven institutions. The primary end point of counseling 70% of patients treated with OAT was not reached. Patients were referred by 15 treatment units compared with 11 units in the AMBORA trial. On the basis of heterogeneous referral rates and characteristics across the institutions, barriers and facilitators of the implementation process were derived. Several survey results (eg, stakeholder interviews, online/paper-based questionnaires) reflected a high appreciation of services by patients and health care professionals. The severity of 60.1% (178 of 296) of detected side effects improved, and 86.3% (297 of 344) of medication errors were resolved. CONCLUSION Despite not reaching the primary implementation outcome, the AMBORA Center included more treatment units and demonstrated patient benefit of the AMBORA care program by meeting all effectiveness outcomes. We outlined quantitative and qualitative implementation characteristics to enhance outreach and foster further dissemination of centers to optimize medication safety with OAT.
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Affiliation(s)
- Lisa Cuba
- Pharmacy Department, Universitätsklinikum Erlangen and Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN, Universitätsklinikum Erlangen, Erlangen, Germany
- Bavarian Cancer Research Center (BZKF), Erlangen, Germany
| | - Pauline Dürr
- Pharmacy Department, Universitätsklinikum Erlangen and Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN, Universitätsklinikum Erlangen, Erlangen, Germany
- Bavarian Cancer Research Center (BZKF), Erlangen, Germany
| | - Katja Gessner
- Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN, Universitätsklinikum Erlangen, Erlangen, Germany
- Bavarian Cancer Research Center (BZKF), Erlangen, Germany
| | | | - Rainer Fietkau
- Comprehensive Cancer Center Erlangen-EMN, Universitätsklinikum Erlangen, Erlangen, Germany
- Bavarian Cancer Research Center (BZKF), Erlangen, Germany
- Department of Radiation Oncology, Universitätsklinikum Erlangen and Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Jürgen Siebler
- Comprehensive Cancer Center Erlangen-EMN, Universitätsklinikum Erlangen, Erlangen, Germany
- Bavarian Cancer Research Center (BZKF), Erlangen, Germany
- Department of Medicine 1, Gastroenterology, Pneumology and Endocrinology, Universitätsklinikum Erlangen and Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Marianne Pavel
- Comprehensive Cancer Center Erlangen-EMN, Universitätsklinikum Erlangen, Erlangen, Germany
- Bavarian Cancer Research Center (BZKF), Erlangen, Germany
- Department of Medicine 1, Gastroenterology, Pneumology and Endocrinology, Universitätsklinikum Erlangen and Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Markus F Neurath
- Comprehensive Cancer Center Erlangen-EMN, Universitätsklinikum Erlangen, Erlangen, Germany
- Bavarian Cancer Research Center (BZKF), Erlangen, Germany
- Department of Medicine 1, Gastroenterology, Pneumology and Endocrinology, Universitätsklinikum Erlangen and Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Carola Berking
- Comprehensive Cancer Center Erlangen-EMN, Universitätsklinikum Erlangen, Erlangen, Germany
- Bavarian Cancer Research Center (BZKF), Erlangen, Germany
- Department of Dermatology, Universitätsklinikum Erlangen and Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Bernd Wullich
- Comprehensive Cancer Center Erlangen-EMN, Universitätsklinikum Erlangen, Erlangen, Germany
- Bavarian Cancer Research Center (BZKF), Erlangen, Germany
| | - Valeska Brückl
- Comprehensive Cancer Center Erlangen-EMN, Universitätsklinikum Erlangen, Erlangen, Germany
- Bavarian Cancer Research Center (BZKF), Erlangen, Germany
- Department of Medicine 5, Hematology and Oncology, Universitätsklinikum Erlangen and Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Matthias W Beckmann
- Comprehensive Cancer Center Erlangen-EMN, Universitätsklinikum Erlangen, Erlangen, Germany
- Bavarian Cancer Research Center (BZKF), Erlangen, Germany
- Department of Obstetrics and Gynecology, Universitätsklinikum Erlangen and Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Martin F Fromm
- Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN, Universitätsklinikum Erlangen, Erlangen, Germany
- Bavarian Cancer Research Center (BZKF), Erlangen, Germany
- FAU NeW - Research Center New Bioactive Compounds, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Frank Dörje
- Pharmacy Department, Universitätsklinikum Erlangen and Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN, Universitätsklinikum Erlangen, Erlangen, Germany
- Bavarian Cancer Research Center (BZKF), Erlangen, Germany
- FAU NeW - Research Center New Bioactive Compounds, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
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Yoong SL, Lum M, Wolfenden L, Jackson J, Barnes C, Hall AE, McCrabb S, Pearson N, Lane C, Jones JZ, Nolan E, Dinour L, McDonnell T, Booth D, Grady A. Healthy eating interventions delivered in early childhood education and care settings for improving the diet of children aged six months to six years. Cochrane Database Syst Rev 2023; 8:CD013862. [PMID: 37606067 PMCID: PMC10443896 DOI: 10.1002/14651858.cd013862.pub3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/23/2023]
Abstract
BACKGROUND Dietary intake during early childhood can have implications on child health and developmental trajectories. Early childhood education and care (ECEC) services are recommended settings to deliver healthy eating interventions as they provide access to many children during this important period. Healthy eating interventions delivered in ECEC settings can include strategies targeting the curriculum (e.g. nutrition education), ethos and environment (e.g. menu modification) and partnerships (e.g. workshops for families). Despite guidelines supporting the delivery of healthy eating interventions in this setting, little is known about their impact on child health. OBJECTIVES To assess the effectiveness of healthy eating interventions delivered in ECEC settings for improving dietary intake in children aged six months to six years, relative to usual care, no intervention or an alternative, non-dietary intervention. Secondary objectives were to assess the impact of ECEC-based healthy eating interventions on physical outcomes (e.g. child body mass index (BMI), weight, waist circumference), language and cognitive outcomes, social/emotional and quality-of-life outcomes. We also report on cost and adverse consequences of ECEC-based healthy eating interventions. SEARCH METHODS We searched eight electronic databases including CENTRAL, MEDLINE, Embase, CINAHL, PsycINFO, ERIC, Scopus and SportDiscus on 24 February 2022. We searched reference lists of included studies, reference lists of relevant systematic reviews, the World Health Organization International Clinical Trials Registry Platform, ClinicalTrials.gov and Google Scholar, and contacted authors of relevant papers. SELECTION CRITERIA We included randomised controlled trials (RCTs), including cluster-RCTs, stepped-wedge RCTs, factorial RCTs, multiple baseline RCTs and randomised cross-over trials, of healthy eating interventions targeting children aged six months to six years that were conducted within the ECEC setting. ECEC settings included preschools, nurseries, kindergartens, long day care and family day care. To be included, studies had to include at least one intervention component targeting child diet within the ECEC setting and measure child dietary or physical outcomes, or both. DATA COLLECTION AND ANALYSIS Pairs of review authors independently screened titles and abstracts and extracted study data. We assessed risk of bias for all studies against 12 criteria within RoB 1, which allows for consideration of how selection, performance, attrition, publication and reporting biases impact outcomes. We resolved discrepancies via consensus or by consulting a third review author. Where we identified studies with suitable data and homogeneity, we performed meta-analyses using a random-effects model; otherwise, we described findings using vote-counting approaches and via harvest plots. For measures with similar metrics, we calculated mean differences (MDs) for continuous outcomes and risk ratios (RRs) for dichotomous outcomes. We calculated standardised mean differences (SMDs) for primary and secondary outcomes where studies used different measures. We applied GRADE to assess certainty of evidence for dietary, cost and adverse outcomes. MAIN RESULTS We included 52 studies that investigated 58 interventions (described across 96 articles). All studies were cluster-RCTs. Twenty-nine studies were large (≥ 400 participants) and 23 were small (< 400 participants). Of the 58 interventions, 43 targeted curriculum, 56 targeted ethos and environment, and 50 targeted partnerships. Thirty-eight interventions incorporated all three components. For the primary outcomes (dietary outcomes), we assessed 19 studies as overall high risk of bias, with performance and detection bias being most commonly judged as high risk of bias. ECEC-based healthy eating interventions versus usual practice or no intervention may have a positive effect on child diet quality (SMD 0.34, 95% confidence interval (CI) 0.04 to 0.65; P = 0.03, I2 = 91%; 6 studies, 1973 children) but the evidence is very uncertain. There is moderate-certainty evidence that ECEC-based healthy eating interventions likely increase children's consumption of fruit (SMD 0.11, 95% CI 0.04 to 0.18; P < 0.01, I2 = 0%; 11 studies, 2901 children). The evidence is very uncertain about the effect of ECEC-based healthy eating interventions on children's consumption of vegetables (SMD 0.12, 95% CI -0.01 to 0.25; P =0.08, I2 = 70%; 13 studies, 3335 children). There is moderate-certainty evidence that ECEC-based healthy eating interventions likely result in little to no difference in children's consumption of non-core (i.e. less healthy/discretionary) foods (SMD -0.05, 95% CI -0.17 to 0.08; P = 0.48, I2 = 16%; 7 studies, 1369 children) or consumption of sugar-sweetened beverages (SMD -0.10, 95% CI -0.34 to 0.14; P = 0.41, I2 = 45%; 3 studies, 522 children). Thirty-six studies measured BMI, BMI z-score, weight, overweight and obesity, or waist circumference, or a combination of some or all of these. ECEC-based healthy eating interventions may result in little to no difference in child BMI (MD -0.08, 95% CI -0.23 to 0.07; P = 0.30, I2 = 65%; 15 studies, 3932 children) or in child BMI z-score (MD -0.03, 95% CI -0.09 to 0.03; P = 0.36, I2 = 0%; 17 studies; 4766 children). ECEC-based healthy eating interventions may decrease child weight (MD -0.23, 95% CI -0.49 to 0.03; P = 0.09, I2 = 0%; 9 studies, 2071 children) and risk of overweight and obesity (RR 0.81, 95% CI 0.65 to 1.01; P = 0.07, I2 = 0%; 5 studies, 1070 children). ECEC-based healthy eating interventions may be cost-effective but the evidence is very uncertain (6 studies). ECEC-based healthy eating interventions may have little to no effect on adverse consequences but the evidence is very uncertain (3 studies). Few studies measured language and cognitive skills (n = 2), social/emotional outcomes (n = 2) and quality of life (n = 3). AUTHORS' CONCLUSIONS ECEC-based healthy eating interventions may improve child diet quality slightly, but the evidence is very uncertain, and likely increase child fruit consumption slightly. There is uncertainty about the effect of ECEC-based healthy eating interventions on vegetable consumption. ECEC-based healthy eating interventions may result in little to no difference in child consumption of non-core foods and sugar-sweetened beverages. Healthy eating interventions could have favourable effects on child weight and risk of overweight and obesity, although there was little to no difference in BMI and BMI z-scores. Future studies exploring the impact of specific intervention components, and describing cost-effectiveness and adverse outcomes are needed to better understand how to maximise the impact of ECEC-based healthy eating interventions.
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Affiliation(s)
- Sze Lin Yoong
- Global Centre for Preventive Health and Nutrition, Institute for Health Transformation, School of Health and Social Development, Faculty of Health, Deakin University, Victoria, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Melanie Lum
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Luke Wolfenden
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Jacklyn Jackson
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Courtney Barnes
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Alix E Hall
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Sam McCrabb
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Nicole Pearson
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Cassandra Lane
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Jannah Z Jones
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Erin Nolan
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Lauren Dinour
- College of Education and Human Services, Montclair State University, Montclair, New Jersey, USA
| | - Therese McDonnell
- School of Nursing, Midwifery and Health Systems, University College Dublin, Dublin, Ireland
| | - Debbie Booth
- Auchmuty Library, University of Newcastle, Callaghan, Australia
| | - Alice Grady
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
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4
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Yoong SL, Lum M, Wolfenden L, Jackson J, Barnes C, Hall AE, McCrabb S, Pearson N, Lane C, Jones JZ, Dinour L, McDonnell T, Booth D, Grady A. Healthy eating interventions delivered in early childhood education and care settings for improving the diet of children aged six months to six years. Cochrane Database Syst Rev 2023; 6:CD013862. [PMID: 37306513 PMCID: PMC10259732 DOI: 10.1002/14651858.cd013862.pub2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
BACKGROUND Dietary intake during early childhood can have implications on child health and developmental trajectories. Early childhood education and care (ECEC) services are recommended settings to deliver healthy eating interventions as they provide access to many children during this important period. Healthy eating interventions delivered in ECEC settings can include strategies targeting the curriculum (e.g. nutrition education), ethos and environment (e.g. menu modification) and partnerships (e.g. workshops for families). Despite guidelines supporting the delivery of healthy eating interventions in this setting, little is known about their impact on child health. OBJECTIVES To assess the effectiveness of healthy eating interventions delivered in ECEC settings for improving dietary intake in children aged six months to six years, relative to usual care, no intervention or an alternative, non-dietary intervention. Secondary objectives were to assess the impact of ECEC-based healthy eating interventions on physical outcomes (e.g. child body mass index (BMI), weight, waist circumference), language and cognitive outcomes, social/emotional and quality-of-life outcomes. We also report on cost and adverse consequences of ECEC-based healthy eating interventions. SEARCH METHODS We searched eight electronic databases including CENTRAL, MEDLINE, Embase, CINAHL, PsycINFO, ERIC, Scopus and SportDiscus on 24 February 2022. We searched reference lists of included studies, reference lists of relevant systematic reviews, the World Health Organization International Clinical Trials Registry Platform, ClinicalTrials.gov and Google Scholar, and contacted authors of relevant papers. SELECTION CRITERIA We included randomised controlled trials (RCTs), including cluster-RCTs, stepped-wedge RCTs, factorial RCTs, multiple baseline RCTs and randomised cross-over trials, of healthy eating interventions targeting children aged six months to six years that were conducted within the ECEC setting. ECEC settings included preschools, nurseries, kindergartens, long day care and family day care. To be included, studies had to include at least one intervention component targeting child diet within the ECEC setting and measure child dietary or physical outcomes, or both. DATA COLLECTION AND ANALYSIS Pairs of review authors independently screened titles and abstracts and extracted study data. We assessed risk of bias for all studies against 12 criteria within RoB 1, which allows for consideration of how selection, performance, attrition, publication and reporting biases impact outcomes. We resolved discrepancies via consensus or by consulting a third review author. Where we identified studies with suitable data and homogeneity, we performed meta-analyses using a random-effects model; otherwise, we described findings using vote-counting approaches and via harvest plots. For measures with similar metrics, we calculated mean differences (MDs) for continuous outcomes and risk ratios (RRs) for dichotomous outcomes. We calculated standardised mean differences (SMDs) for primary and secondary outcomes where studies used different measures. We applied GRADE to assess certainty of evidence for dietary, cost and adverse outcomes. MAIN RESULTS: We included 52 studies that investigated 58 interventions (described across 96 articles). All studies were cluster-RCTs. Twenty-nine studies were large (≥ 400 participants) and 23 were small (< 400 participants). Of the 58 interventions, 43 targeted curriculum, 56 targeted ethos and environment, and 50 targeted partnerships. Thirty-eight interventions incorporated all three components. For the primary outcomes (dietary outcomes), we assessed 19 studies as overall high risk of bias, with performance and detection bias being most commonly judged as high risk of bias. ECEC-based healthy eating interventions versus usual practice or no intervention may have a positive effect on child diet quality (SMD 0.34, 95% confidence interval (CI) 0.04 to 0.65; P = 0.03, I2 = 91%; 6 studies, 1973 children) but the evidence is very uncertain. There is moderate-certainty evidence that ECEC-based healthy eating interventions likely increase children's consumption of fruit (SMD 0.11, 95% CI 0.04 to 0.18; P < 0.01, I2 = 0%; 11 studies, 2901 children). The evidence is very uncertain about the effect of ECEC-based healthy eating interventions on children's consumption of vegetables (SMD 0.12, 95% CI -0.01 to 0.25; P =0.08, I2 = 70%; 13 studies, 3335 children). There is moderate-certainty evidence that ECEC-based healthy eating interventions likely result in little to no difference in children's consumption of non-core (i.e. less healthy/discretionary) foods (SMD -0.05, 95% CI -0.17 to 0.08; P = 0.48, I2 = 16%; 7 studies, 1369 children) or consumption of sugar-sweetened beverages (SMD -0.10, 95% CI -0.34 to 0.14; P = 0.41, I2 = 45%; 3 studies, 522 children). Thirty-six studies measured BMI, BMI z-score, weight, overweight and obesity, or waist circumference, or a combination of some or all of these. ECEC-based healthy eating interventions may result in little to no difference in child BMI (MD -0.08, 95% CI -0.23 to 0.07; P = 0.30, I2 = 65%; 15 studies, 3932 children) or in child BMI z-score (MD -0.03, 95% CI -0.09 to 0.03; P = 0.36, I2 = 0%; 17 studies; 4766 children). ECEC-based healthy eating interventions may decrease child weight (MD -0.23, 95% CI -0.49 to 0.03; P = 0.09, I2 = 0%; 9 studies, 2071 children) and risk of overweight and obesity (RR 0.81, 95% CI 0.65 to 1.01; P = 0.07, I2 = 0%; 5 studies, 1070 children). ECEC-based healthy eating interventions may be cost-effective but the evidence is very uncertain (6 studies). ECEC-based healthy eating interventions may have little to no effect on adverse consequences but the evidence is very uncertain (3 studies). Few studies measured language and cognitive skills (n = 2), social/emotional outcomes (n = 2) and quality of life (n = 3). AUTHORS' CONCLUSIONS ECEC-based healthy eating interventions may improve child diet quality slightly, but the evidence is very uncertain, and likely increase child fruit consumption slightly. There is uncertainty about the effect of ECEC-based healthy eating interventions on vegetable consumption. ECEC-based healthy eating interventions may result in little to no difference in child consumption of non-core foods and sugar-sweetened beverages. Healthy eating interventions could have favourable effects on child weight and risk of overweight and obesity, although there was little to no difference in BMI and BMI z-scores. Future studies exploring the impact of specific intervention components, and describing cost-effectiveness and adverse outcomes are needed to better understand how to maximise the impact of ECEC-based healthy eating interventions.
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Affiliation(s)
- Sze Lin Yoong
- Global Centre for Preventive Health and Nutrition, Institute for Health Transformation, School of Health and Social Development, Faculty of Health, Deakin University, Victoria, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Melanie Lum
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Luke Wolfenden
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Jacklyn Jackson
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Courtney Barnes
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Alix E Hall
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Sam McCrabb
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Nicole Pearson
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Cassandra Lane
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Jannah Z Jones
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
| | - Lauren Dinour
- College of Education and Human Services, Montclair State University, Montclair, New Jersey, USA
| | - Therese McDonnell
- School of Nursing, Midwifery and Health Systems, University College Dublin, Dublin, Ireland
| | - Debbie Booth
- Auchmuty Library, University of Newcastle, Callaghan, Australia
| | - Alice Grady
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter Medical Research Institute, New Lambton, Australia
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Gelman R, Whelan J, Spiteri S, Duric D, Oakhill W, Cassar S, Love P. Adoption, implementation, and sustainability of early childhood feeding, nutrition and active play interventions in real-world settings: a systematic review. Int J Behav Nutr Phys Act 2023; 20:32. [PMID: 36941649 PMCID: PMC10029282 DOI: 10.1186/s12966-023-01433-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 03/05/2023] [Indexed: 03/23/2023] Open
Abstract
BACKGROUND Instilling healthy dietary habits and active play in early childhood is an important public health focus. Interventions supporting the establishment of nutrition and active play behaviours in the first years of life have shown positive outcomes and long-term cost-effectiveness, however, most are research trials, with limited evidence regarding real-world application. Implementation science theories, models and frameworks (TMFs) can guide the process of research translation from trial to real-world intervention. The application of TMFs within nutrition and active play intervention studies in early childhood (< 5 years) is currently unknown. This systematic review identified the use of TMFs and barriers/ enablers associated with intervention adoption, implementation, and sustainability in early childhood nutrition and active play interventions implemented under real-world conditions. METHODS Six databases were searched for peer-reviewed publications between 2000-2021. Studies were included if primary outcomes reported improvement in diet, physical activity or sedentary behaviours amongst children aged < 5 years and interventions were delivered under real-world conditions within a community and/or healthcare setting. Two reviewers extracted and evaluated studies, cross checked by a third and verified by all authors. Quality assessment of included studies was completed by two authors using the Mixed Methods Appraisal Tool (MMAT). RESULTS Eleven studies comprising eleven unique interventions were included. Studies represented low, middle and high-income countries, and were conducted across a range of settings. Five TMFs were identified representing four of Nilsen's implementation model categories, predominantly 'evaluation models'. Ninety-nine barriers/facilitators were extracted across the three intervention phases-Implementation (n = 33 barriers; 33 facilitators), Sustainability (n = 19 barriers; n = 9 facilitators), Adoption (n = 2 barriers; n = 3 facilitators). Identified barriers/facilitators were mapped to the five domains of the Durlak and DuPre framework, with 'funding', 'compatibility' and 'integration of new programming' common across the three intervention phases. CONCLUSIONS Findings demonstrate that there is no systematic application of TMFs in the planning, implementation and/or evaluation of early childhood nutrition and active play interventions in real-world settings, and selective and sporadic application of TMFs occurs across the intervention lifespan. This apparent limited uptake of TMFs is a missed opportunity to enhance real-world implementation success. TRIAL REGISTRATION PROSPERO (CRD42021243841).
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Affiliation(s)
- Rivka Gelman
- School of Exercise and Nutrition Science, Deakin University, Geelong, VIC, 3220, Australia.
| | - Jillian Whelan
- School of Medicine, Institute of Health Transformation, Deakin University, Geelong, VIC, 3220, Australia
| | - Sheree Spiteri
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Science, Deakin University, Geelong, VIC, 3220, Australia
| | - Danijela Duric
- School of Exercise and Nutrition Science, Deakin University, Geelong, VIC, 3220, Australia
| | - Winnie Oakhill
- School of Exercise and Nutrition Science, Deakin University, Geelong, VIC, 3220, Australia
| | - Samuel Cassar
- Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, 3052, Australia
| | - Penelope Love
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Science, Deakin University, Geelong, VIC, 3220, Australia
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Rosenkranz RR, Dixon PM, Dzewaltowski DA, McLoughlin GM, Lee JA, Chen S, Vazou S, Lanningham-Foster LM, Gentile DA, Welk GJ. A cluster-randomized trial comparing two SWITCH implementation support strategies for school wellness intervention effectiveness. JOURNAL OF SPORT AND HEALTH SCIENCE 2023; 12:87-96. [PMID: 34871789 PMCID: PMC9923427 DOI: 10.1016/j.jshs.2021.12.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 10/25/2021] [Accepted: 11/15/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND The School Wellness Integration Targeting Child Health (SWITCH) intervention has demonstrated feasibility as an implementation approach to help schools facilitate changes in students' physical activity (PA), sedentary screen time (SST), and dietary intake (DI). This study evaluated the comparative effectiveness of enhanced (individualized) implementation and standard (group-based) implementation. METHODS Twenty-two Iowa elementary schools participated, with each receiving standardized training (wellness conference and webinars). Schools were matched within region and randomized to receive either individualized or group implementation support. The PA, SST, and DI outcomes of 1097 students were assessed at pre- and post-intervention periods using the Youth Activity Profile. Linear mixed models evaluated differential change in outcomes by condition, for comparative effectiveness, and by gender. RESULTS Both implementation conditions led to significant improvements in PA and SST over time (p < 0.01), but DI did not improve commensurately (p value range: 0.02‒0.05). There were no differential changes between the group and individualized conditions for PA (p = 0.51), SST (p = 0.19), or DI (p = 0.73). There were no differential effects by gender (i.e., non-significant condition-by-gender interactions) for PA (pfor interaction = 0.86), SST (pfor interaction = 0.46), or DI (pfor interaction = 0.15). Effect sizes for both conditions equated to approximately 6 min more PA per day and approximately 3 min less sedentary time. CONCLUSION The observed lack of difference in outcomes suggests that group implementation of SWITCH is equally effective as individualized implementation for building capacity in school wellness programming. Similarly, the lack of interaction by gender suggests that SWITCH can be beneficial for both boys and girls. Additional research is needed to understand the school-level factors that influence implementation (and outcomes) of SWITCH.
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Affiliation(s)
- Richard R Rosenkranz
- Department of Food, Nutrition, Dietetics & Health, Kansas State University, Manhattan, KS 66506, USA.
| | - Philip M Dixon
- Department of Statistics, Snedecor Hall, Iowa State University, Ames, IA 50011-1210, USA
| | - David A Dzewaltowski
- Department of Health Promotion, University of Nebraska, Omaha, NE 68198-4365, USA
| | - Gabriella M McLoughlin
- Implementation Science Center for Cancer Control and Prevention Research Center, Brown School, Washington University in St. Louis, St. Louis, MO 63130, USA; Division of Public Health Sciences (Department of Surgery), Washington University School of Medicine, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Joey A Lee
- Department of Health Sciences, University of Colorado Colorado Springs, Colorado Springs, CO 80918, USA
| | - Senlin Chen
- Department of Kinesiology, Iowa State University, Ames, IA 50011-4008, USA
| | - Spyridoula Vazou
- Department of Kinesiology, Iowa State University, Ames, IA 50011-4008, USA
| | | | - Doug A Gentile
- Department of Psychology, Iowa State University, Ames, IA 50011-1041, USA
| | - Gregory J Welk
- Department of Kinesiology, Iowa State University, Ames, IA 50011-4008, USA
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Jurczuk M, Thakar R, Carroll FE, Phillips L, van der Meulen J, Gurol-Urganci I, Sevdalis N. Design and management considerations for control groups in hybrid effectiveness-implementation trials: Narrative review & case studies. FRONTIERS IN HEALTH SERVICES 2023; 3:1059015. [PMID: 36926502 PMCID: PMC10012616 DOI: 10.3389/frhs.2023.1059015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 02/06/2023] [Indexed: 03/12/2023]
Abstract
Hybrid effectiveness-implementation studies allow researchers to combine study of a clinical intervention's effectiveness with study of its implementation with the aim of accelerating the translation of evidence into practice. However, there currently exists limited guidance on how to design and manage such hybrid studies. This is particularly true for studies that include a comparison/control arm that, by design, receives less implementation support than the intervention arm. Lack of such guidance can present a challenge for researchers both in setting up but also in effectively managing participating sites in such trials. This paper uses a narrative review of the literature (Phase 1 of the research) and comparative case study of three studies (Phase 2 of the research) to identify common themes related to study design and management. Based on these, we comment and reflect on: (1) the balance that needs to be struck between fidelity to the study design and tailoring to emerging requests from participating sites as part of the research process, and (2) the modifications to the implementation strategies being evaluated. Hybrid trial teams should carefully consider the impact of design selection, trial management decisions, and any modifications to implementation processes and/or support on the delivery of a controlled evaluation. The rationale for these choices should be systematically reported to fill the gap in the literature.
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Affiliation(s)
- Magdalena Jurczuk
- Centre for Quality Improvement and Clinical Audit, Royal College of Obstetricians and Gynaecologists, London, United Kingdom
| | - Ranee Thakar
- Obstetrics & Gynaecology, Croydon University Hospitals NHS Trust, London, United Kingdom
| | - Fran E Carroll
- Centre for Quality Improvement and Clinical Audit, Royal College of Obstetricians and Gynaecologists, London, United Kingdom
| | - Lizzie Phillips
- Centre for Quality Improvement and Clinical Audit, Royal College of Obstetricians and Gynaecologists, London, United Kingdom.,Maternity Services, University Hospital Plymouth NHS Trust, Plymouth, United Kingdom
| | - Jan van der Meulen
- Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Ipek Gurol-Urganci
- Centre for Quality Improvement and Clinical Audit, Royal College of Obstetricians and Gynaecologists, London, United Kingdom.,Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Nick Sevdalis
- Centre for Implementation Science, Health Service and Population Research Department, King's College London, London, United Kingdom
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Swindle T, Rutledge JM, Zhang D, Martin J, Johnson SL, Selig JP, Yates AM, Gaulden DT, Curran GM. De-Implementation of Detrimental Feeding Practices in Childcare: Mixed Methods Evaluation of Community Partner Selected Strategies. Nutrients 2022; 14:nu14142861. [PMID: 35889818 PMCID: PMC9319894 DOI: 10.3390/nu14142861] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 07/05/2022] [Accepted: 07/11/2022] [Indexed: 02/05/2023] Open
Abstract
This pilot evaluated strategies to decrease detrimental feeding practices in early care and education, which are hypothesized to compete with evidence-based feeding and obesity prevention practices. This study made two key comparisons: (1) a between-site comparison of sites receiving (a) no implementation or de-implementation strategies (i.e., Basic Support; B), (b) implementation strategies only (i.e., Enhanced Support; E), and (c) implementation and de-implementation strategies (i.e., De-implementation + Enhanced Support; D + E) and (2) a within-site pre-post comparison among sites with D + E. At nutrition lessons, the D + E group had more Positive Comments (Hedege’s g = 0.60) and higher Role Model fidelity (Hedege’s g = 1.34) compared to the E group. At meals, assistant teachers in the D + E group had higher Positive Comments than in the B group (g = 0.72). For within-group comparisons, the D + E group decreased Negative Comments (t(19) = 2.842, p = 0.01), increased Positive Comments (t(20) = 2.314, p = 0.031), and improved use of the program mascot at nutrition lessons (t(21) = 3.899, p = 0.001). At meals, lead teachers’ Negative Comments decreased (t(22) = 2.73, p = 0.01). Qualitative data identified strengths and opportunities for iteration. Despite a COVID interruption, mid-point comparisons and qualitative feedback suggest promise of the de-implementation strategy package.
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Affiliation(s)
- Taren Swindle
- Department of Family and Preventive Medicine, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA; (D.Z.); (J.M.); (D.T.G.)
- Correspondence:
| | - Julie M. Rutledge
- College of Applied and Natural Sciences, School of Human Ecology, Louisiana Tech University, Ruston, LA 71272, USA; (J.M.R.); (A.M.Y.)
| | - Dong Zhang
- Department of Family and Preventive Medicine, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA; (D.Z.); (J.M.); (D.T.G.)
| | - Janna Martin
- Department of Family and Preventive Medicine, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA; (D.Z.); (J.M.); (D.T.G.)
| | - Susan L. Johnson
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA;
| | - James P. Selig
- College of Public Health, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA;
| | - Amy M. Yates
- College of Applied and Natural Sciences, School of Human Ecology, Louisiana Tech University, Ruston, LA 71272, USA; (J.M.R.); (A.M.Y.)
| | - Daphne T. Gaulden
- Department of Family and Preventive Medicine, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA; (D.Z.); (J.M.); (D.T.G.)
| | - Geoffrey M. Curran
- Department of Pharmacy Practice and Psychiatry, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA;
- Central Arkansas Veterans Healthcare System, Little Rock, AR 72205, USA
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Swindle T, Rutledge JM, Martin J, Curran GM. Implementation fidelity, attitudes, and influence: a novel approach to classifying implementer behavior. Implement Sci Commun 2022; 3:60. [PMID: 35668517 PMCID: PMC9171954 DOI: 10.1186/s43058-022-00307-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 05/05/2022] [Indexed: 11/30/2022] Open
Abstract
Background The current study sought to (1) describe a new classification approach for types of implementer behavior and (2) explore the implementer behavior change in response to tailored implementation facilitation based on the classifications. Methods A small-scale, cluster-randomized hybrid type III implementation trial was conducted in 38 early care and education classrooms that were part of the Together, We Inspire Smart Eating (WISE) program. WISE focuses on 4 evidence-based practices (EBPs), which are implemented by teachers to promote nutrition. External facilitators (N = 3) used a modified Rapid Assessment Procedure Informed Clinical Ethnography (RAPICE) to complete immersion (i.e., observations) and thematic content analyses of interviews to identify the characteristics of teachers’ behavior at varying levels of implementation fidelity. Three key factors—attitudes toward the innovation, fidelity/adaptations, and influence—were identified that the research team used to classify teachers’ implementation behavior. This process resulted in a novel classification approach. To assess the reliability of applying the classification approach, we assessed the percent agreement between the facilitators. Based on the teachers’ classification, the research team developed a tailored facilitation response. To explore behavior change related to the tailored facilitation, change in fidelity and classification across the school year were evaluated. Results The classifications include (1) enthusiastic adopters (positive attitude, meeting fidelity targets, active influence), (2) over-adapting adopters (positive attitude, not meeting fidelity targets, active influence), (3) passive non-adopters (negative attitude, not meeting fidelity targets, passive influence), and (4) active non-adopters (negative attitudes, not meeting fidelity targets, active influence). The average percent agreement among the three facilitators for classification was 75%. Qualitative data support distinct patterns of perceptions across the classifications. A positive shift in classification was observed for 67% of cases between the mid-point and final classification. Finally, we generated an expanded classification approach to consider additional combinations of the three factors beyond those observed in this study. Conclusions Data from this study support the ability to apply the classification approach with moderate to high reliability and to use the approach to tailor facilitation toward improved implementation. Findings suggest the potential of our approach for wider application and potential to improve tailoring of implementation strategies such as facilitation.
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Affiliation(s)
- Taren Swindle
- Department of Family and Preventive Medicine, University of Arkansas for Medical Sciences, 4301 W. Markham St., #530, Little Rock, AR, 72205-7199, USA.
| | - Julie M Rutledge
- Education and Research in Children's Health Center, College of Applied and Natural Sciences, Louisiana Tech University, Ruston, USA
| | - Janna Martin
- Department of Family and Preventive Medicine, University of Arkansas for Medical Sciences, 4301 W. Markham St., #530, Little Rock, AR, 72205-7199, USA
| | - Geoffrey M Curran
- Department of Pharmacy Practice and Psychiatry, University of Arkansas for Medical Sciences, 4301 W. Markham St, Little Rock, AR, #522-472205-7199, USA.,Central Arkansas Veterans Healthcare System, 4300 W 7th St, Little Rock, AR, 72205, USA
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Obesity prevention practices in early care and education settings: an adaptive implementation trial. Implement Sci 2022; 17:25. [PMID: 35303894 PMCID: PMC8932138 DOI: 10.1186/s13012-021-01185-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 12/28/2021] [Indexed: 11/10/2022] Open
Abstract
Background Despite the potential for Early Care and Education (ECE) settings to promote healthy habits, a gap exists between current practices and evidence-based practices (EBPs) for obesity prevention in childhood. Methods We will use an enhanced non-responder trial design to determine the effectiveness and incremental cost-effectiveness of an adaptive implementation strategy for Together, We Inspire Smart Eating (WISE), while examining moderators and mediators of the strategy effect. WISE is a curriculum that aims to increase children’s intake of carotenoid-rich fruits and vegetables through four evidence-based practices in the early care and education setting. In this trial, we will randomize sites that do not respond to low-intensity strategies to either (a) continue receiving low-intensity strategies or (b) receive high-intensity strategies. This design will determine the effect of an adaptive implementation strategy that adds high-intensity versus one that continues with low-intensity among non-responder sites. We will also apply explanatory, sequential mixed methods to provide a nuanced understanding of implementation mechanisms, contextual factors, and characteristics of sites that respond to differing intensities of implementation strategies. Finally, we will conduct a cost effectiveness analysis to estimate the incremental effect of augmenting implementation with high-intensity strategies compared to continuing low-intensity strategies on costs, fidelity, and child health outcomes. Discussion We expect our study to contribute to an evidence base for structuring implementation support in real-world ECE contexts, ultimately providing a guide for applying the adaptive implementation strategy in ECE for WISE scale-up. Our work will also provide data to guide implementation decisions of other interventions in ECE. Finally, we will provide the first estimate of relative value for different implementation strategies in this setting. Trial registration NCT05050539; 9/20/21.
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