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Fehily C, Jackson B, Hansen V, Stettaford T, Bartlem K, Clancy R, Bowman J. Increasing chronic disease preventive care in community mental health services: clinician-generated strategies. BMC Psychiatry 2023; 23:933. [PMID: 38082423 PMCID: PMC10714530 DOI: 10.1186/s12888-023-05311-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 10/26/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND People with a mental health condition experience a high prevalence of chronic disease risk behaviours e.g., tobacco smoking and physical inactivity. Recommended 'preventive care' to address these risks is infrequently provided by community mental health services. This study aimed to elucidate, among community mental health managers and clinicians, suggestions for strategies to support provision of preventive care. METHODS Three qualitative focus groups (n = 14 clinicians) were undertaken in one regional community mental health service to gather perspectives of barriers to preventive care provision, deductively coded against the domains of the Theoretical Domains Framework (TDF). Drawing on the learnings from the focus groups, individual interviews (n = 15 managers and clinicians) were conducted in two services to identify suggestions for strategies to increase preventive care. Strategies were inductively coded and mapped into TDF domains. RESULTS Barriers were identified across a wide range of TDF domains, most notably knowledge and environmental context and resources. Nine strategies were identified across three themes: training, resources and systems changes; mapping to all 14 TDF domains. CONCLUSION Future research seeking to increase implementation of preventive care may be guided by these findings. There is need for greater recognition and resourcing of preventive care as a priority and integral component of mental health treatment.
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Affiliation(s)
- Caitlin Fehily
- School of Psychological Sciences, College of Engineering, Science and Environment, The University of Newcastle, Callaghan, NSW, Australia.
- Hunter Medical Research Institute, Clinical Research Centre, New Lambton Heights, NSW, Australia.
| | - Belinda Jackson
- School of Psychological Sciences, College of Engineering, Science and Environment, The University of Newcastle, Callaghan, NSW, Australia
| | - Vibeke Hansen
- School of Psychological Sciences, College of Engineering, Science and Environment, The University of Newcastle, Callaghan, NSW, Australia
| | - Tegan Stettaford
- School of Psychological Sciences, College of Engineering, Science and Environment, The University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute, Clinical Research Centre, New Lambton Heights, NSW, Australia
- School of Medicine and Public Health, The University of Newcastle, Callaghan, NSW, Australia
| | - Kate Bartlem
- School of Psychological Sciences, College of Engineering, Science and Environment, The University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute, Clinical Research Centre, New Lambton Heights, NSW, Australia
| | - Richard Clancy
- Hunter Medical Research Institute, Clinical Research Centre, New Lambton Heights, NSW, Australia
- Hunter New England Mental Health, Hunter New England Local Health District, NSW Health, New Lambton, NSW, Australia
- School of Nursing and Midwifery, College of Health, Medicine & Wellbeing, The University of Newcastle, Callaghan, NSW, Australia
| | - Jenny Bowman
- School of Psychological Sciences, College of Engineering, Science and Environment, The University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute, Clinical Research Centre, New Lambton Heights, NSW, Australia
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Curran E, Palmer VJ, Ellis KA, Chong TWH, Rego T, Cox KL, Anstey KJ, Westphal A, Moorhead R, Southam J, Lai R, You E, Lautenschlager NT. Physical Activity for Cognitive Health: A Model for Intervention Design for People Experiencing Cognitive Concerns and Symptoms of Depression or Anxiety. J Alzheimers Dis 2023:JAD221216. [PMID: 37334591 PMCID: PMC10357152 DOI: 10.3233/jad-221216] [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: 06/20/2023]
Abstract
BACKGROUND People experiencing cognitive concerns and symptoms of depression or anxiety are at risk for Alzheimer's disease and dementia. We know physical activity can benefit cognition but understanding how to best support engagement is an ongoing challenge. Evidence-based conceptual models of factors underpinning physical activity engagement in target populations can inform intervention tailoring to address this challenge. OBJECTIVE This study (part of a pragmatic physical activity implementation trial) aimed to develop a specified model of physical activity engagement in people experiencing depressive or anxiety symptoms and cognitive concerns, to enable optimized dementia risk reduction intervention tailoring. METHODS We employed a qualitative design, triangulating data from three sources: semi-structured individual interviews with people experiencing cognitive concerns and mild to moderate depressive or anxiety symptoms; review of published evidence; and the Capability, Opportunity and Motivation system of behavior, an existing behavioral science model. Findings were integrated to develop a contextualized model of mechanisms of action for optimizing engagement. RESULTS Twenty-one participants were interviewed, and 24 relevant papers included. Convergent and complementary themes extended understanding of intervention needs. Findings highlighted emotional regulation, capacities to enact intentions despite barriers, and confidence in existing skills as areas of population-specific need that have not previously been emphasized. The final model provides specificity, directionality, and linked approaches for intervention tailoring. CONCLUSION This study demonstrated that people experiencing cognitive concerns and symptoms of depression or anxiety require different interventions to improve physical activity engagement. The novel model can enable more precise intervention tailoring, and, ultimately, benefits for a key at-risk population.
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Affiliation(s)
- Eleanor Curran
- Academic Unit for Psychiatry of Old Age, Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Parkville, Australia
- North Western Mental Health, Royal Melbourne Hospital, Parkville, Australia
| | - Victoria J Palmer
- ALIVE National Centre for Mental Health Research Translation, Department of General Practice, Melbourne Medical School, The University of Melbourne Faculty of Medicine, Dentistry and Health Sciences, Melbourne, Australia
- Primary Care Mental Health Research Program, Department of General Practice, Melbourne Medical School, The University of Melbourne Faculty of Medicine, Dentistry and Health Sciences, Melbourne, Australia
| | - Kathryn A Ellis
- Academic Unit for Psychiatry of Old Age, Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Parkville, Australia
- Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, Australia
| | - Terence W H Chong
- Academic Unit for Psychiatry of Old Age, Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Parkville, Australia
- North Western Mental Health, Royal Melbourne Hospital, Parkville, Australia
- St Vincent's Hospital Melbourne, St George's Campus, Melbourne, Australia
| | - Thomas Rego
- Academic Unit for Psychiatry of Old Age, Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Parkville, Australia
- North Western Mental Health, Royal Melbourne Hospital, Parkville, Australia
| | - Kay L Cox
- Medical School, The University of Western Australia, Perth, Australia
| | - Kaarin J Anstey
- University of New South Wales Ageing Futures Institute, Sydney, Australia
- Neuroscience Research Australia, Sydney, Australia
| | - Alissa Westphal
- Academic Unit for Psychiatry of Old Age, Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Parkville, Australia
| | - Rebecca Moorhead
- Academic Unit for Psychiatry of Old Age, Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Parkville, Australia
| | - Jenny Southam
- Academic Unit for Psychiatry of Old Age, Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Parkville, Australia
| | - Rhoda Lai
- Academic Unit for Psychiatry of Old Age, Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Parkville, Australia
| | - Emily You
- Academic Unit for Psychiatry of Old Age, Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Parkville, Australia
| | - Nicola T Lautenschlager
- Academic Unit for Psychiatry of Old Age, Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Parkville, Australia
- North Western Mental Health, Royal Melbourne Hospital, Parkville, Australia
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Gingrich N, Bosancich J, Schmidt J, Sakakibara BM. Capability, opportunity, motivation, and social participation after stroke. Top Stroke Rehabil 2022; 30:423-435. [PMID: 35510695 DOI: 10.1080/10749357.2022.2070358] [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: 10/18/2022]
Abstract
BACKGROUND Stroke survivors report limited social participation, despite it being an important rehabilitation outcome. Interdisciplinary interventions for increasing social participation amongst stroke survivors lack theoretical guidance and evidence-based approaches. The Behavior Change Wheel (BCW) theorizes that capability, opportunity, and motivation contribute to behavior change. OBJECTIVES This study applied the BCW to understand the relationship between social participation and stroke survivors' capability, opportunity, and motivation. METHODS In this cross-sectional study, we recruited 30 community-dwelling adult stroke survivors. Assessments explored the frequency and satisfaction of social participation; physical and psychological capability; environmental accessibility and social opportunity; and motivation. A linear regression analysis was done. RESULTS Motivation (R2 change = 29.3%, ß = 0.55) and environmental opportunity (R2 change = 11%, ß = 0.39) were statistically significant predictors of social participation frequency. Motivation (R2 change = 36.9%, ß = 0.61) was the only statistically significant predictor of satisfaction with social performance. CONCLUSIONS Motivation and environmental accessibility are statistically significant independent predictors of frequency of social participation after stroke. Motivation is the strongest predictor of satisfaction with social participation. Clinicians may support stroke survivors to promote social participation using approaches that increase motivation and environmental accessibility. Development of such theoretically sound interventions may be guided by the BCW.
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Affiliation(s)
- Nicole Gingrich
- Department of Occupational Science and Occupational Therapy, University of British Columbia, Vancouver, British Columbia, Canada
| | - Jacob Bosancich
- Department of Occupational Science and Occupational Therapy, University of British Columbia, Vancouver, British Columbia, Canada
| | - Julia Schmidt
- Department of Occupational Science and Occupational Therapy, University of British Columbia, Vancouver, British Columbia, Canada.,Rehabilitation Research Program, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada
| | - Brodie M Sakakibara
- Department of Occupational Science and Occupational Therapy, University of British Columbia, Vancouver, British Columbia, Canada.,Rehabilitation Research Program, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada.,Centre for Chronic Disease Prevention and Management, University of British Columbia Okanagan, Kelowna, British Columbia, Canada
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Using the COM-B model to identify barriers and facilitators towards adoption of a diet associated with cognitive function (MIND diet). Public Health Nutr 2020; 24:1657-1670. [PMID: 32799963 PMCID: PMC8094434 DOI: 10.1017/s1368980020001445] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
OBJECTIVE The aim of the study was to identify components of the COM-B (capability, opportunity, motivation and behaviour) model that influences behaviour to modify dietary patterns in 40-55-year-olds living in the UK, in order to influence the risk of cognitive decline in later life. DESIGN This is a qualitative study using the COM-B model and theoretical domains framework (TDF) to explore beliefs to adopting the Mediterranean-DASH Intervention for Neurodegenerative delay (MIND) diet. SETTING Northern Ireland. PARTICIPANTS Twenty-five participants were recruited onto the study to take part in either a focus group or an interview. Participants were men and women aged between 40 and 55 years. Participants were recruited via email, Facebook and face to face. RESULTS Content analysis revealed that the main perceived barriers to the adoption of the MIND diet were time, work environment, taste preference and convenience. The main perceived facilitators reported were improved health, memory, planning and organisation, and access to good quality food. CONCLUSIONS This study provides insight into the personal, social and environmental factors that participants report as barriers and facilitators to the adoption of the MIND diet among middle-aged adults living in the UK. More barriers to healthy dietary change were found than facilitators. Future interventions that increase capability, opportunity and motivation may be beneficial. The results from this study will be used to design a behaviour change intervention using the subsequent steps from the Behaviour Change Wheel.
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