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Edwardson CL, Abell L, Clarke-Cornwell A, Dunstan DW, Gray LJ, Healy GN, Hadjiconstantinou M, Wilson P, Maylor B, Munir F, Biddle SJ. Implementation and engagement of the SMART Work & Life sitting reduction intervention: an exploratory analysis on intervention effectiveness. Int J Behav Nutr Phys Act 2023; 20:148. [PMID: 38115044 PMCID: PMC10729557 DOI: 10.1186/s12966-023-01548-5] [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: 06/26/2023] [Accepted: 12/09/2023] [Indexed: 12/21/2023] Open
Abstract
BACKGROUND To enhance the impact of interventions, it is important to understand how intervention engagement relates to study outcomes. We report on the level of implementation and engagement with the SMART Work & Life (SWAL) programme (delivered with (SWAL plus desk) and without a height-adjustable desk (SWAL)) and explore the effects of different levels of this on change in daily sitting time in comparison to the control group. METHODS The extent of intervention delivery by workplace champions and the extent of engagement by champions and participants (staff) with each intervention activity was assessed by training attendance logs, workplace champion withdrawal dates, intervention activities logs and questionnaires. These data were used to assess whether a cluster met defined criteria for low, medium, or high implementation and engagement or none of these. Mixed effects linear regression analyses tested whether change in sitting time varied by: (i) the number of intervention activities implemented and engaged with, and (ii) the percentage of implementation and engagement with all intervention strategies. RESULTS Workplace champions were recruited for all clusters, with 51/52 (98%) attending training. Overall, 12/27 (44.4%) SWAL and 9/25 (36.0%) SWAL plus desk clusters implemented all main intervention strategies. Across remaining clusters, the level of intervention implementation varied. Those in the SWAL (n = 8 (29.6%) clusters, 80 (32.1%) participants) and SWAL plus desk (n = 5 (20.0%) clusters, 41 (17.1%) participants) intervention groups who implemented and engaged with the most intervention strategies and had the highest percentage of cluster implementation and engagement with all intervention strategies sat for 30.9 (95% CI -53.9 to -7.9, p = 0.01) and 75.6 (95% CI -103.6 to -47.7, p < 0.001) fewer minutes/day respectively compared to the control group at 12 month follow up. These differences were larger than the complete case analysis. The differences in sitting time observed for the medium and low levels were similar to the complete case analysis. CONCLUSIONS Most intervention strategies were delivered to some extent across the clusters although there was large variation. Superior effects for sitting reduction were seen for those intervention groups who implemented and engaged with the most intervention components and had the highest level of cluster implementation and engagement. TRIAL REGISTRATION ISRCTN11618007. Registered on 24 January 2018. https://www.isrctn.com/ISRCTNISRCTN11618007 .
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Affiliation(s)
- Charlotte L Edwardson
- Diabetes Research Centre, University of Leicester, Leicester, LE5 4PW, UK.
- NIHR Leicester Biomedical Research Centre, Leicester, LE5 4PW, UK.
| | - Lucy Abell
- Department of Population Health Sciences, University of Leicester, Leicester, LE1 7RH, UK
| | - Alex Clarke-Cornwell
- School of Health & Society, University of Salford, Salford, Greater Manchester, M6 6PU, UK
| | - David W Dunstan
- Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, VIC, 3125, Australia
| | - Laura J Gray
- NIHR Leicester Biomedical Research Centre, Leicester, LE5 4PW, UK
- Department of Population Health Sciences, University of Leicester, Leicester, LE1 7RH, UK
| | - Genevieve N Healy
- School of Human Movement and Nutrition Sciences, The University of Queensland, Brisbane, QLD, 4072, Australia
| | | | - Panna Wilson
- Leicester Diabetes Centre, University Hospitals of Leicester, Leicester, LE5 4PW, UK
| | - Benjamin Maylor
- Diabetes Research Centre, University of Leicester, Leicester, LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, Leicester, LE5 4PW, UK
| | - Fehmidah Munir
- School of Sport, Exercise and Health Sciences, Loughborough University, Leicestershire, LE11 3TU, UK
| | - Stuart Jh Biddle
- Centre for Health Research, University of Southern Queensland, Springfield Central, QLD, 4300, Australia
- Faculty of Sport & Health Sciences, University of Jyväskylä, Jyväskylä, FI-40014, Finland
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Lane-Fall MB, Koilor CB, Givan K, Klaiman T, Barg FK. Patient- and Team-Level Characteristics Associated with Handoff Protocol Fidelity in a Hybrid Implementation Study: Results from a Qualitative Comparative Analysis. Jt Comm J Qual Patient Saf 2023; 49:356-364. [PMID: 37208240 PMCID: PMC10524533 DOI: 10.1016/j.jcjq.2023.04.003] [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: 09/02/2022] [Revised: 04/14/2023] [Accepted: 04/17/2023] [Indexed: 05/21/2023]
Abstract
BACKGROUND Standardization is an evidence-based approach to improve handoffs. The factors underpinning fidelity (that is, adherence) to standardized handoff protocols are not well specified, which hampers implementation and sustainability efforts. METHODS The Handoffs and Transitions in Critical Care (HATRICC) study (2014-2017) involved the creation and implementation of a standardized protocol for operating room (OR)-to-ICU handoffs in two mixed surgical ICUs. The present study used fuzzy-set qualitative comparative analysis (fsQCA) to characterize combinations of conditions associated with fidelity to the HATRICC protocol. Conditions were derived from postintervention handoff observations yielding quantitative and qualitative data. RESULTS Sixty handoffs had complete fidelity data. Four conditions from the SEIPS 2.0 model were used to explain fidelity: (1) whether the patient was newly admitted to the ICU; (2) presence of an ICU provider; (3) observer ratings of attention-paying by the handoff team; and (4) whether the handoff took place in a quiet environment. None of the conditions were singly necessary or sufficient for high fidelity. Three combinations of conditions were sufficient for fidelity: (1) presence of the ICU provider and high attention ratings; (2) a newly admitted patient, presence of the ICU provider, and quiet environment; and (3) a newly admitted patient, high attention ratings, and quiet environment. These three combinations explained 93.5% of the cases demonstrating high fidelity. CONCLUSION In a study of OR-to-ICU handoff standardization, multiple combinations of contextual factors were associated with handoff protocol fidelity. Handoff implementation efforts should consider multiple fidelity-promoting strategies that support these combinations of conditions.
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