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Tynan M, Virzi N, Wooldridge JS, Morse JL, Herbert MS. Examining the Association Between Objective Physical Activity and Momentary Pain: A Systematic Review of Studies Using Ambulatory Assessment. THE JOURNAL OF PAIN 2024; 25:862-874. [PMID: 37914094 DOI: 10.1016/j.jpain.2023.10.021] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 09/22/2023] [Accepted: 10/21/2023] [Indexed: 11/03/2023]
Abstract
Chronic pain (CP) is a debilitating and increasingly common health condition that adversely impacts function, including physical activity (PA). Research using ambulatory assessment (AA) methods (eg, ecological momentary assessment, actigraphy) offers promise for elucidating the relationship between momentary pain and objective PA in CP populations. This study aimed to systematically review articles assessing the association between momentary pain and PA in adults with CP as measured using AA and to make recommendations for the measurement and study of this relationship. Five databases were systematically searched, and 13 unique records (N = 768) met the inclusion criteria. CP conditions included mixed/nonspecific CP (k = 3), low back pain (k = 2), fibromyalgia (k = 1), unspecified arthritis (k = 1), and hip/knee osteoarthritis (k = 6). The average age of participants across studies was 55.29 years, and the majority identified as women (60.68%) and White (83.16%). All studies measured objective PA via actigraphy, and momentary pain with either a diary/log or ratings on an actigraph. Studies varied in the quantification of PA (ie, activity counts, step count, moderate-vigorous PA), statistical method (ie, correlation, regression, multilevel modeling), and inclusion of moderators (eg, pain acceptance). Studies reported mixed results for the pain-PA relationship. This heterogeneity suggests that no summarizing conclusions can be drawn about the pain-PA relationship without further investigation into its complex nuances. More within-person and exploratory examinations that maximize the richness of AA data are needed. A greater understanding of this relationship can inform psychotherapeutic and behavioral recommendations to improve CP outcomes. PERSPECTIVE: This article presents a systematic review of the literature on the association between momentary pain and PA in adults with CP as measured using AA methods. A better understanding of this nuanced relationship could help elucidate areas for timely intervention and may inform clinical recommendations to improve CP outcomes. PROSPERO REGISTRATION NUMBER: CRD42023389913.
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Affiliation(s)
- Mara Tynan
- San Diego State University/UC San Diego Joint Doctoral Program in Clinical Psychology, San Diego, California
| | - Nicole Virzi
- San Diego State University/UC San Diego Joint Doctoral Program in Clinical Psychology, San Diego, California
| | - Jennalee S Wooldridge
- VA San Diego Healthcare System, San Diego, California; Department of Psychiatry, University of California, San Diego, California
| | - Jessica L Morse
- VA San Diego Healthcare System, San Diego, California; Department of Psychiatry, University of California, San Diego, California
| | - Matthew S Herbert
- VA San Diego Healthcare System, San Diego, California; Department of Psychiatry, University of California, San Diego, California; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, California
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Kenning C, Bower P, Small N, Ali SM, Brown B, Dempsey K, Mackey E, McMillan B, Sanders C, Serafimova I, Van der Veer SN, Dixon WG, McBeth J. Users' views on the use of a smartwatch app to collect daily symptom data in individuals with multiple long-term conditions (Multimorbidity): A qualitative study. JOURNAL OF MULTIMORBIDITY AND COMORBIDITY 2024; 14:26335565231220202. [PMID: 38223165 PMCID: PMC10785716 DOI: 10.1177/26335565231220202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 11/27/2023] [Indexed: 01/16/2024]
Abstract
Introduction Long-term conditions are a major burden on health systems. One way to facilitate more research and better clinical care among patients with long-term conditions is to collect accurate data on their daily symptoms (patient-generated health data) using wearable technologies. Whilst evidence is growing for the use of wearable technologies in single conditions, there is less evidence of the utility of frequent symptom tracking in those who have more than one condition. Aims To explore patient views of the acceptability of collecting daily patient-generated health data for three months using a smartwatch app. Methods Watch Your Steps was a longitudinal study which recruited 53 patients to track over 20 symptoms per day for a 90-day period using a study app on smartwatches. Semi-structured interviews were conducted with a sub-sample of 20 participants to explore their experience of engaging with the app. Results In a population of older people with multimorbidity, patients were willing and able to engage with a patient-generated health data app on a smartwatch. It was suggested that to maintain engagement over a longer period, more 'real-time' feedback from the app should be available. Participants did not seem to consider the management of more than one condition to be a factor in either engagement or use of the app, but the presence of severe or chronic pain was at times a barrier. Conclusion This study has provided preliminary evidence that multimorbidity was not a major barrier to engagement with patient-generated health data via a smartwatch symptom tracking app.
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Affiliation(s)
- Cassandra Kenning
- Centre for Primary Care and Health Services Research, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Peter Bower
- Centre for Primary Care and Health Services Research, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Nicola Small
- Centre for Primary Care and Health Services Research, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Syed Mustafa Ali
- Centre for Epidemiology Versus Arthritis, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
| | - Benjamin Brown
- Centre for Primary Care and Health Services Research, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
- Centre for Health Informatics, Division of Informatics, Imaging and Data Sciences, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
| | - Katherine Dempsey
- Centre for Epidemiology Versus Arthritis, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
| | - Elaine Mackey
- Centre for Epidemiology Versus Arthritis, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
| | - Brian McMillan
- Centre for Primary Care and Health Services Research, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Caroline Sanders
- Centre for Primary Care and Health Services Research, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Ilina Serafimova
- Centre for Epidemiology Versus Arthritis, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
| | - Sabine N Van der Veer
- Centre for Health Informatics, Division of Informatics, Imaging and Data Sciences, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
| | - William G Dixon
- Centre for Epidemiology Versus Arthritis, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
| | - John McBeth
- Centre for Epidemiology Versus Arthritis, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
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