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Camp K, Murphy S, Pate B. Integrating Fall Prevention Strategies into EMS Services to Reduce Falls and Associated Healthcare Costs for Older Adults. Clin Interv Aging 2024; 19:561-569. [PMID: 38533419 PMCID: PMC10964786 DOI: 10.2147/cia.s453961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Accepted: 03/13/2024] [Indexed: 03/28/2024] Open
Abstract
Purpose The purpose of this study is to detail the implementation of fall prevention initiatives through emergency medical services (EMS) and associated outcomes. Methods Paramedics with MedStar Mobile Healthcare utilized the Stopping Elderly Accidents, Deaths, and Injuries (STEADI) fall prevention model to screen and direct intervention through 9-1-1 emergency response, High Utilization Group (HUG), and 30-day Hospital Readmission Avoidance (HRA) programs. Outcomes from 9-1-1 calls measured the number of older adults screened for falls and identified risk factors. The HUG and HRA programs measured change in quality of life with EuroQol-5D, referral service utilization, falls, emergent healthcare utilization, and hospital readmission data. Analysis included costs associated with reduced healthcare usage. Results Emergency paramedics provided fall risk screening for 50.5% (n=45,090) of adults aged 65 and older and 59.3% were at risk of falls, with 48.1% taking medications known to increase the risk of falls. Services provided through the HUG and HRA programs, along with additional needed referral services, resulted in a 37.2% reduction in fall-related 9-1-1 calls and a 29.5% increase in overall health status related to quality of life. Analysis of the HUG program revealed potential savings of over $1 million with a per-patient enrolled savings of $19,053. The HRA program demonstrated a 16.4% hospital readmission rate, in comparison to a regional average of 30.2%, and a cost-savings of $4.95 million or $15,618 per enrolled patient. Conclusion Implementation of the STEADI model into EMS services provides an effective and cost-saving model for addressing fall prevention for older adults, provides meaningful and impactful improvement for older adults, and could serve as a model for other EMS programs.
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Affiliation(s)
- Kathlene Camp
- Department of Internal Medicine and Geriatrics, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Sara Murphy
- Department of Internal Medicine and Geriatrics, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Brandon Pate
- Mobile Integrated Healthcare, MedStar Mobile Healthcare, Fort Worth, TX, USA
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2
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Zheng Z, Bird SR, Layton J, Hyde A, Moreland A, Wong Lit Wan D, Stupans I. Patient engagement as a core element of translating clinical evidence into practice- application of the COM-B model behaviour change model. Disabil Rehabil 2023; 45:4517-4526. [PMID: 36476254 DOI: 10.1080/09638288.2022.2153935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 11/27/2022] [Indexed: 12/13/2022]
Abstract
BACKGROUND The results of rehabilitation trials are often not fully attained when the intervention is implemented beyond the initial trial. One of the key reasons is that a patients' ability and/or capacity to take part in their own healthcare is not considered in the trial design yet has significant impact on the outcomes during the implementation phase. BODY OF TEXT We propose a shift from a therapist-focus to patient-focus in trial design, through addressing patient engagement as a core consideration in trials. We argue that engaging patients in any rehabilitation program is a process of behavioural change. Exercise prescription is used as an example to illustrate how the Behaviour Change Wheel can be applied to analyse barriers and facilitators associated with patients' capabilities, opportunities and motivations in integrating trial interventions into their daily life. We propose a framework to assist in this shift. CONCLUSION A core part of implementing rehabilitation interventions at the primary care level requires patient engagement. Related aspects of interventions should be identified and assessed using the COM-B model at the outset of trial design to ensure that the results are realistic, meaningful and transferable, so as to enable real impact.
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Affiliation(s)
- Zhen Zheng
- School of Health and Biomedical Sciences, RMIT University, Bundoora, Australia
| | - Stephen R Bird
- School of Health and Biomedical Sciences, RMIT University, Bundoora, Australia
| | - Jennifer Layton
- School of Health and Biomedical Sciences, RMIT University, Bundoora, Australia
| | - Anna Hyde
- School of Health and Biomedical Sciences, RMIT University, Bundoora, Australia
| | - Ash Moreland
- School of Health and Biomedical Sciences, RMIT University, Bundoora, Australia
| | - Dawn Wong Lit Wan
- School of Health and Biomedical Sciences, RMIT University, Bundoora, Australia
| | - Ieva Stupans
- School of Health and Biomedical Sciences, RMIT University, Bundoora, Australia
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Morris RL, Hill KD, Ackerman IN, Ayton D, Arendts G, Brand C, Cameron P, Etherton-Beer CD, Flicker L, Hill AM, Hunter P, Lowthian JA, Morello R, Nyman SR, Redfern J, Smit DV, Barker AL. Correction: A mixed methods process evaluation of a person-centred falls prevention program. BMC Health Serv Res 2023; 23:695. [PMID: 37370149 DOI: 10.1186/s12913-023-09743-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/29/2023] Open
Affiliation(s)
- Rebecca L Morris
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
| | - Keith D Hill
- Rehabilitation, Ageing and Independent Living (RAIL) Research Centre, Monash University, Melbourne, Australia
- School of Physiotherapy and Exercise Science, Curtin University, Perth, Australia
| | - Ilana N Ackerman
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Darshini Ayton
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
| | - Glenn Arendts
- University of Western Australia, Perth, Australia
- Harry Perkins Institute of Medical Research, Perth, Australia
| | - Caroline Brand
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
- Melbourne EpiCentre, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Peter Cameron
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
- Alfred Health, Melbourne, Australia
| | | | - Leon Flicker
- University of Western Australia, Perth, Australia
- Royal Perth Hospital, Perth, Australia
| | - Anne-Marie Hill
- School of Physiotherapy and Exercise Science, Curtin University, Perth, Australia
| | - Peter Hunter
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
- Alfred Health, Melbourne, Australia
| | - Judy A Lowthian
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
- Bolton Clarke Research Institute, Bolton Clarke, Melbourne, Australia
| | - Renata Morello
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Samuel R Nyman
- Department of Psychology and Ageing & Dementia Research Centre, now at Department of Medical Science and Public Health, Bournemouth University, Dorset, UK
| | - Julie Redfern
- Westmead Applied Research Centre, Faculty of Medicine and Health, the George Institute for Global Health, University of Sydney, Sydney, Australia
| | - De Villiers Smit
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
- Alfred Health, Melbourne, Australia
| | - Anna L Barker
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
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4
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Ayton D, Pirotta S, Morello R, Rosenich E, Barton C, Lavale A, Pase MP, Maruff P, Yassi N, Brodtmann A, Lim YY, Barker A. Protocol for a Mixed-Methods Process Evaluation of BetterBrains: A Person-Centered Online Intervention to Delay Cognitive Decline in Adults at Risk of Dementia. J Alzheimers Dis 2022; 90:1689-1703. [PMID: 36314199 DOI: 10.3233/jad-220341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
BACKGROUND The BetterBrains Randomized Controlled Trial (RCT) will evaluate the effectiveness of an online, person-centered, risk factor management, coaching intervention in community-dwelling, healthy adults at risk of cognitive decline. Multi-component interventions are challenging to evaluate due to program complexity and personalization to individual needs and contexts. This paper describes a multi-level process evaluation conducted alongside the BetterBrains RCT. OBJECTIVE To understand how and why the BetterBrains intervention was effective or ineffective at reducing cognitive decline in healthy adults whilst considering the context in which it was implemented. METHODS 1,510 non cognitively-deteriorated community-dwelling adults aged 40-70 years old at risk of cognitive decline will be recruited and randomly assigned to the intervention or control group. All BetterBrains intervention participants, coaches, and the research team will be included in the evaluation. A mixed-methods design will be used, guided by The Framework for Implementation Fidelity and the program logic model. Data will be sourced from interviews, focus groups, surveys, BetterBrains coach notes, participant weekly check-in surveys, and audio recordings of intervention coaching sessions. Quantitative data will be analyzed via descriptive and inferential statistics and qualitative data will be analyzed using content and thematic analysis. RESULTS The process evaluation will provide information about contextual and influencing factors related to the implementation of BetterBrains and the RCT outcomes. CONCLUSION Understanding how BetterBrains was implemented and its associated impacts will inform the translation of the program into community and clinical settings, providing easy access to online, personalized dementia prevention services.
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Affiliation(s)
- Darshini Ayton
- Health and Social Care Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Stephanie Pirotta
- Health and Social Care Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Renata Morello
- Health and Social Care Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Emily Rosenich
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Chris Barton
- Department of General Practice, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Alexandra Lavale
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Matthew P Pase
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Paul Maruff
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC, Australia.,Cogstate Ltd., Melbourne, VIC, Australia
| | - Nawaf Yassi
- Department of Medicine and Neurology, Melbourne Brain Centre at The Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia.,Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
| | - Amy Brodtmann
- Department of Neuroscience, Central Clinical School, Monash University, The Alfred Centre, Melbourne, VIC, Australia
| | - Yen Ying Lim
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Anna Barker
- Silver Chain Group, Melbourne, VIC, Australia
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Teo JL, Zheng Z, Bird SR. Identifying the factors affecting 'patient engagement' in exercise rehabilitation. BMC Sports Sci Med Rehabil 2022; 14:18. [PMID: 35130940 PMCID: PMC8819209 DOI: 10.1186/s13102-022-00407-3] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 01/20/2022] [Indexed: 11/13/2022]
Abstract
Background Despite the proven benefits of exercise rehabilitation for numerous health conditions, musculoskeletal injuries and recovery from surgery, patient adherence to such programs is reported to often be less than 35%. Increasing patient engagement therefore has the potential to improve patient health outcomes, benefiting the patient, their carers and the services that support them. The aims of this review were to identify the factors that contribute to ‘patient’ engagement in prescribed exercise rehabilitation using the COM-B (capability, opportunity, motivation-behaviour) framework of behavioural analysis. Methods Five electronic databases (PubMed, Embase, Cochrane, Web of Science, and ClinicalTrials.gov) were searched. ‘COM-B’ was the key word searched for specifically within titles and abstracts, combined with either ‘physical activity’ OR ‘exercise’ included using the ‘AND’ operation. Records were then filtered and excluded following full-text screening based on the predetermined eligibility criteria. Results Twenty studies were included in the review. The main COM-B themes highlighted for improving patient engagement were: capability—improving patient knowledge and cognitive skills for behavioural regulation, such as ‘action planning’ and ‘action control’, which could also benefit time-management; opportunity—a balanced life situation that enabled time to be devoted to the exercise program, social support, easily accessible and affordable resources and services; and motivation—increasing patient levels of self-efficacy and autonomous motivation, which were noted to be influenced by levels of perceived ‘capability’, additionally ‘motivation’ was noted to be influenced by patients perceiving the benefits of the exercise, and adherence to the program was promoted by ‘goal-setting’. Other issues in the ‘capability’ domain included a fear and/or dislike of exercise. Conclusion Patient engagement behavior has been shown to be influenced by both external (opportunity) and intrapersonal variables (capability and motivation). Those prescribing exercises within a rehabilitation program need to discuss these factors with their patients and co-design the exercise rehabilitation program in partnership with the patient, since this is likely to improve patient engagement, and thereby result in superior health outcomes. Furthermore, these factors need to be a consideration in clinical trials, if the findings from such trials are to translate into mainstream healthcare settings. Supplementary Information The online version contains supplementary material available at 10.1186/s13102-022-00407-3.
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Affiliation(s)
- Junsheng L Teo
- School of Health and Biomedical Sciences, RMIT University, Melbourne, 3083, Australia
| | - Zhen Zheng
- School of Health and Biomedical Sciences, RMIT University, Melbourne, 3083, Australia
| | - Stephen R Bird
- School of Health and Biomedical Sciences, RMIT University, Melbourne, 3083, Australia.
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6
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Wiertsema SH, Donker MH, van Dongen JM, Geleijn E, Bloemers FW, Ostelo RW, de Groot V. The Transmural Trauma Care Model can be implemented well but some barriers and facilitators should be considered during implementation: a mixed methods study. J Physiother 2021; 67:298-307. [PMID: 34511380 DOI: 10.1016/j.jphys.2021.08.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 08/19/2021] [Accepted: 08/31/2021] [Indexed: 10/20/2022] Open
Abstract
QUESTIONS What is the reach, dose delivered, dose received and fidelity of the Transmural Trauma Care Model (TTCM)? What are the barriers and facilitators associated with the implementation of the TTCM? DESIGN Mixed-methods process evaluation with quantitative evaluation of the extent to which the TTCM was implemented as intended and qualitative evaluation of barriers and facilitators to its implementation. PARTICIPANTS Focus group participants included trauma patients, trauma surgeons, hospital-based physiotherapists and primary care network physiotherapists. OUTCOME MEASURES Implementation was assessed with reach, dose delivered, dose received and fidelity. DATA ANALYSIS A framework method was used to analyse the focus groups and the 'constellation approach' was used to categorise barriers and facilitators into three categories: structure, culture and practice. RESULTS The TTCM's reach was 81%, its dose delivered was 99% and 100%, and its dose received was 95% and 96% for the multidisciplinary TTCM consultation hours at the outpatient clinic for trauma patients and the primary care network physiotherapists, respectively. Various fidelity scores ranged from 66 to 93%. Numerous barriers and facilitators associated with the implementation of the TTCM were identified and categorised. CONCLUSION This process evaluation showed that the TTCM was largely implemented as intended. Furthermore, various facilitators and barriers were identified that need to be considered when implementing the TTCM more widely. Differences were found among stakeholders but they were generally of the opinion that if the barriers were overcome, the quality of care and patient satisfaction were likely to improve significantly after implementing the TTCM. REGISTRATION NTR5474.
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Affiliation(s)
- Suzanne H Wiertsema
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Rehabilitation Medicine, Amsterdam Movement Sciences, Amsterdam, Netherlands.
| | - Marianne H Donker
- Vrije Universiteit Amsterdam, Department of Health Sciences, Faculty of Science, Amsterdam Movement Sciences, Amsterdam, Netherlands
| | - Johanna M van Dongen
- Vrije Universiteit Amsterdam, Department of Health Sciences, Faculty of Science, Amsterdam Movement Sciences, Amsterdam, Netherlands
| | - Edwin Geleijn
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Rehabilitation Medicine, Amsterdam Movement Sciences, Amsterdam, Netherlands
| | - Frank W Bloemers
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Trauma Surgery, Amsterdam Movement Sciences, Amsterdam, Netherlands
| | - Raymond Wjg Ostelo
- Vrije Universiteit Amsterdam, Department of Health Sciences, Faculty of Science, Amsterdam Movement Sciences, Amsterdam, Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Biostatistics, Amsterdam Movement Sciences, Amsterdam, Netherlands
| | - Vincent de Groot
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Rehabilitation Medicine, Amsterdam Movement Sciences, Amsterdam, Netherlands
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7
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Lim YY, Ayton D, Perin S, Lavale A, Yassi N, Buckley R, Barton C, Bruns L, Morello R, Pirotta S, Rosenich E, Rajaratnam SMW, Sinnott R, Brodtmann A, Bush AI, Maruff P, Churilov L, Barker A, Pase MP. An Online, Person-Centered, Risk Factor Management Program to Prevent Cognitive Decline: Protocol for A Prospective Behavior-Modification Blinded Endpoint Randomized Controlled Trial. J Alzheimers Dis 2021; 83:1603-1622. [PMID: 34420970 DOI: 10.3233/jad-210589] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
BACKGROUND Several modifiable risk factors for dementia have been identified, although the extent to which their modification leads to improved cognitive outcomes remains unclear. OBJECTIVE The primary aim is to test the hypothesis that a behavior modification intervention program targeting personalized risk factors prevents cognitive decline in community-dwelling, middle-aged adults with a family history of dementia. METHODS This is a prospective, risk factor management, blinded endpoint, randomized, controlled trial, where 1510 cognitively normal, community-dwelling adults aged 40-70 years old will be recruited. Participants will be screened for risk factors related to vascular health (including physical inactivity), mental health, sleep, and cognitive/social engagement. The intervention is an online person-centered risk factor management program: BetterBrains. Participants randomized to intervention will receive telehealth-based person-centered goal setting, motivational interviewing, and follow-up support, health care provider communication and community linkage for management of known modifiable risk factors of dementia. Psychoeducational health information will be provided to both control and intervention groups. RESULTS The primary outcome is favorable cognitive performance at 24-months post-baseline, defined as the absence of decline on one or more of the following cognitive tests: (a) Cogstate Detection, (b) Cogstate One Card Learning, (c) Cogstate One Back, and (d) Cognitive Function Instrument total score. CONCLUSION We will test the hypothesis that the BetterBrains intervention program can prevent cognitive decline. By leveraging existing community services and using a risk factor management pathway that tailors the intervention to each participant, we maximize likelihood for engagement, long-term adherence, and for preserving cognitive function in at-risk individuals.
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Affiliation(s)
- Yen Ying Lim
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Darshini Ayton
- Health and Social Care Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Stephanie Perin
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Alexandra Lavale
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Nawaf Yassi
- Department of Medicine and Neurology, Melbourne Brain Centre at The Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia.,Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
| | - Rachel Buckley
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC, Australia.,Melbourne School of Psychological Sciences, University of Melbourne, Parkville, VIC Australia.,Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.,Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - Christopher Barton
- Department of General Practice, School of Primary and Allied Health Care, Monash University, Clayton, VIC, Australia
| | - Loren Bruns
- School of Computing and Information Systems, University of Melbourne, Parkville, VIC, Australia
| | - Renata Morello
- Health and Social Care Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Stephanie Pirotta
- Health and Social Care Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Emily Rosenich
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Shantha M W Rajaratnam
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Richard Sinnott
- School of Computing and Information Systems, University of Melbourne, Parkville, VIC, Australia
| | - Amy Brodtmann
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC, Australia
| | - Ashley I Bush
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC, Australia
| | - Paul Maruff
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC, Australia.,Cogstate Ltd., Melbourne, VIC, Australia
| | - Leonid Churilov
- Melbourne Medical School, University of Melbourne, Parkville, VIC, Australia
| | - Anna Barker
- Health and Social Care Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Matthew P Pase
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia.,Harvard T.H. Chan School of Public Health, Boston, MA, USA
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8
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Macniven R, Coombes J, Wilson R, Simon A, Mackean T, Hunter K, Ma T, Gwynn J, Sherrington C, Tiedemann A, Hill AM, Delbaere K, Lewis C, Bennett-Brook K, Howie A, Stewart G, Shakespeare M, Rogers K, Ivers RQ, Clapham K. Understanding implementation factors and participant experiences of a cluster randomised controlled trial to prevent falls among older Aboriginal people: a process evaluation protocol. Inj Prev 2021; 27:injuryprev-2020-043980. [PMID: 33402353 DOI: 10.1136/injuryprev-2020-043980] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Revised: 12/07/2020] [Accepted: 12/10/2020] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Process evaluations examining programme implementation are often conducted in conjunction with effectiveness studies. Their inclusion in studies with Aboriginal participants can give an understanding of programme delivery in Aboriginal community contexts. The Ironbark: Standing Strong and Tall programme was codesigned with Aboriginal communities and includes exercise and facilitated 'yarning' discussion about fall risk and prevention strategies. The programme pilot showed favourable outcomes and acceptability for Aboriginal people aged 45 years and over. The Ironbark: Standing Strong and Tall programme is now being compared with a 'Healthy Community' programme in a cluster randomised controlled trial within Aboriginal health and community services. An embedded process evaluation aims to explore relationships between participation and programme outcomes and the quality of programme implementation. METHODS AND ANALYSIS The process evaluation will use a mixed methods design, guided by Indigenous research methodology. It will evaluate quantitative data (number of completed sessions, site coaching checklist tool, participant and facilitator questionnaire data and a participant habit formation scale), as well as qualitative data (open-ended responses from project and site staff and semistructured interviews using yarning with study participants and site managers). A programme logic model was developed to explain the intended inputs, activities, outputs and outcomes, which guided this process evaluation design. CONCLUSION This process evaluation of a fall prevention programme for older Aboriginal people using a mixed methods design and data triangulation will allow for a comprehensive understanding of study findings. Multiple study sites allow for generalisability of findings and exploration of variation across sites. TRIAL REGISTRATION NUMBER ACTRN12619000349145.
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Affiliation(s)
- Rona Macniven
- School of Population Health, The University of New South Wales, Sydney, New South Wales, Australia
- Poche Centre for Indigenous Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Julieann Coombes
- The George Institute for Global Health, The University of New South Wales, Sydney, New South Wales, Australia
| | - Roland Wilson
- Southgate Institute for Health, Society, and Equity, Flinders University, Adelaide, South Australia, Australia
| | - Aaron Simon
- School of Population Health, The University of New South Wales, Sydney, New South Wales, Australia
- The George Institute for Global Health, The University of New South Wales, Sydney, New South Wales, Australia
| | - Tamara Mackean
- The George Institute for Global Health, The University of New South Wales, Sydney, New South Wales, Australia
- Southgate Institute for Health, Society, and Equity, Flinders University, Adelaide, South Australia, Australia
| | - Kate Hunter
- The George Institute for Global Health, The University of New South Wales, Sydney, New South Wales, Australia
| | - Tracey Ma
- School of Population Health, The University of New South Wales, Sydney, New South Wales, Australia
- The George Institute for Global Health, The University of New South Wales, Sydney, New South Wales, Australia
| | - Josephine Gwynn
- Poche Centre for Indigenous Health, The University of Sydney, Sydney, New South Wales, Australia
- Faculty of Health Sciences, The University of Sydney, Sydney, New South Wales, Australia
| | - Catherine Sherrington
- Institute for Musculoskeletal Health, School of Public Health, The University of Sydney and Sydney Local Health District, Sydney, New South Wales, Australia
| | - Anne Tiedemann
- Institute for Musculoskeletal Health, School of Public Health, The University of Sydney and Sydney Local Health District, Sydney, New South Wales, Australia
| | - Anne-Marie Hill
- School of Physiotherapy and Exercise Science, Curtin University, Bentley, Perth, Australia
| | - Kim Delbaere
- School of Population Health, The University of New South Wales, Sydney, New South Wales, Australia
- Neuroscience Research Australia, University of New South Wales, Sydney, New South Wales, Australia
| | - Carolyn Lewis
- School of Physiotherapy and Exercise Science, Curtin University, Bentley, Perth, Australia
| | - Keziah Bennett-Brook
- The George Institute for Global Health, The University of New South Wales, Sydney, New South Wales, Australia
| | - Adam Howie
- School of Population Health, The University of New South Wales, Sydney, New South Wales, Australia
| | - Georgia Stewart
- Ngarruwan Ngadju First Peoples Health and Wellbeing Research Centre, Australian Health Services Research Institute, University of Wollongong, Wollongong, New South Wales, Australia
| | - Madison Shakespeare
- Southgate Institute for Health, Society, and Equity, Flinders University, Adelaide, South Australia, Australia
| | - Kris Rogers
- The George Institute for Global Health, The University of New South Wales, Sydney, New South Wales, Australia
- Graduate School of Health, University of Technology Sydney, Ultimo, New South Wales, Australia
| | - Rebecca Q Ivers
- School of Population Health, The University of New South Wales, Sydney, New South Wales, Australia
- The George Institute for Global Health, The University of New South Wales, Sydney, New South Wales, Australia
| | - Kathleen Clapham
- Ngarruwan Ngadju First Peoples Health and Wellbeing Research Centre, Australian Health Services Research Institute, University of Wollongong, Wollongong, New South Wales, Australia
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9
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Tsindos T, Ayton D, Soh SE, Ackerman IN. Perceptions of falls risk and falls prevention among people with osteoarthritis. Disabil Rehabil 2020; 44:1839-1846. [PMID: 32809876 DOI: 10.1080/09638288.2020.1806364] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
PURPOSE To understand the perceptions of falls risk and falls prevention, and the perceived enablers and barriers to engaging in falls prevention strategies/activities among people with doctor-diagnosed hip and/or knee osteoarthritis. METHODS A qualitative study utilising semi-structured telephone interviews. Researchers independently analysed qualitative data using an inductive method guided by the COM-B framework. Interviews were analysed thematically using open, axial, and selective coding. Recruitment ceased at 20 interviews, once data saturation was evident. RESULTS Participants were 18 women and two men aged 52-84 years and half had fallen in the last 12 months. Main themes were the absence of recommendations to access activities after having a fall, inconsistencies between perceptions of the relationship between OA and falls, and individual beliefs of not being at risk of falling because of taking precautions. Knowledge about falls prevention programs was limited, the term "falls prevention" was considered stigmatising and only applicable to older frail people. Home modifications were perceived as broadcasting negativity; participants felt falls terminology should be changed from a negative to a positive focus. CONCLUSIONS Falls were often seen as inevitable consequence of keeping active. Re-framing the language used to discuss falls is recommended to promote uptake of falls prevention activities.Implications for rehabilitationDespite growing evidence that osteoarthritis (OA) is an independent risk factor for falls, people with OA do not perceive themselves to be at risk and falls prevention is for those who are "old and frail".Re-framing the language used to discuss falls and falls prevention to focus on positive messages may promote the uptake of falls prevention activities in this population.Improving the awareness of falls and falls risk among people with OA through effective health education is needed in order to foster the uptake of, and engagement with, falls prevention activities.
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Affiliation(s)
- Tess Tsindos
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia
| | - Darshini Ayton
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia
| | - Sze-Ee Soh
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia.,Department of Physiotherapy, Monash University, Melbourne, Australia
| | - Ilana N Ackerman
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia
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Saarijärvi M, Wallin L, Bratt EL. Process evaluation of complex cardiovascular interventions: How to interpret the results of my trial? Eur J Cardiovasc Nurs 2020; 19:269-274. [PMID: 32054300 PMCID: PMC7065447 DOI: 10.1177/1474515120906561] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Complex interventions of varying degrees of complexity are commonly used and evaluated in cardiovascular nursing and allied professions. Such interventions are increasingly tested using randomized trial designs. However, process evaluations are seldom used to better understand the results of these trials. Process evaluation aims to understand how complex interventions create change by evaluating implementation, mechanisms of impact, and the surrounding context when delivering an intervention. As such, this method can illuminate important mechanisms and clarify variation in results. In this article, process evaluation is described according to the Medical Research Council guidance and its use exemplified through a randomized controlled trial evaluating the effectiveness of a transition program for adolescents with chronic conditions.
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Affiliation(s)
- Markus Saarijärvi
- Institute of Health and Care Sciences, University of Gothenburg, Sweden.,Department of Public Health and Primary Care, KU Leuven, Belgium
| | - Lars Wallin
- Institute of Health and Care Sciences, University of Gothenburg, Sweden.,School of Education, Health and Social Studies, Dalarna University, Sweden.,Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Sweden
| | - Ewa-Lena Bratt
- Institute of Health and Care Sciences, University of Gothenburg, Sweden.,Department of Pediatric Cardiology, The Queen Silvia Children's Hospital, Sweden
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