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Cuesta-Vargas AI, Biró A, Escriche-Escuder A, Trinidad-Fernández M, García-Conejo C, Roldán Jiménez CR, Tang W, Salvatore A, Nikolova B, Muro-Culebras A, Martín-Martín J, González-Sánchez M, Ruiz-Muñoz M, Mayoral F. Effectiveness of a gamified digital intervention based on lifestyle modification (iGAME) in secondary prevention: a protocol for a randomised controlled trial. BMJ Open 2023; 13:e066669. [PMID: 37316318 DOI: 10.1136/bmjopen-2022-066669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/16/2023] Open
Abstract
INTRODUCTION Combating physical inactivity and reducing sitting time are one of the principal challenges proposed by public health systems. Gamification has been seen as an innovative, functional and motivating strategy to encourage patients to increase their physical activity (PA) and reduce sedentary lifestyles through behaviour change techniques (BCT). However, the effectiveness of these interventions is not usually studied before their use. The main objective of this study will be to analyse the effectiveness of a gamified mobile application (iGAME) developed in the context of promoting PA and reducing sitting time with the BCT approach, as an intervention of secondary prevention in sedentary patients. METHODS AND ANALYSIS A randomised clinical trial will be conducted among sedentary patients with one of these conditions: non-specific low back pain, cancer survivors and mild depression. The experimental group will receive a 12-week intervention based on a gamified mobile health application using BCT to promote PA and reduce sedentarism. Participants in the control group will be educated about the benefits of PA. The International Physical Activity Questionnaire will be considered the primary outcome. International Sedentary Assessment Tool, EuroQoL-5D, MEDRISK Instruments and consumption of Health System resources will be evaluated as secondary outcomes. Specific questionnaires will be administered depending on the clinical population. Outcomes will be assessed at baseline, at 6 weeks, at the end of the intervention (12 weeks), at 26 weeks and at 52 weeks. ETHICS AND DISSEMINATION The study has been approved by the Portal de Ética de la Investigación Biomédica de Andalucía Ethics Committee (RCT-iGAME 24092020). All participants will be informed about the purpose and content of the study and written informed consent will be completed. The results of this study will be published in a peer-reviewed journal and disseminated electronically and in print. TRIAL REGISTRATION NUMBER NCT04019119.
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Affiliation(s)
- Antonio I Cuesta-Vargas
- Departamento de Fisioterapia, Universidad de Malaga, Andalucia Tech, Malaga, España
- Instituto de Investigacion Biomédica de Málaga (IBIMA), Malaga, España
| | - Attila Biró
- Departamento de Fisioterapia, Universidad de Malaga, Andalucia Tech, Malaga, España
- Instituto de Investigacion Biomédica de Málaga (IBIMA), Malaga, España
- ITware, Budapest, Hungary
- Department of Electrical Engineering and Information Technology, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, Targu Mures, Romania
| | - Adrian Escriche-Escuder
- Departamento de Fisioterapia, Universidad de Malaga, Andalucia Tech, Malaga, España
- Instituto de Investigacion Biomédica de Málaga (IBIMA), Malaga, España
| | - Manuel Trinidad-Fernández
- Departamento de Fisioterapia, Universidad de Malaga, Andalucia Tech, Malaga, España
- Instituto de Investigacion Biomédica de Málaga (IBIMA), Malaga, España
| | - Celia García-Conejo
- Departamento de Fisioterapia, Universidad de Malaga, Andalucia Tech, Malaga, España
- Instituto de Investigacion Biomédica de Málaga (IBIMA), Malaga, España
| | - Cristina Roldán Roldán Jiménez
- Departamento de Fisioterapia, Universidad de Malaga, Andalucia Tech, Malaga, España
- Instituto de Investigacion Biomédica de Málaga (IBIMA), Malaga, España
| | - Wen Tang
- Bournemouth University, Poole, UK
| | | | | | - Antonio Muro-Culebras
- Departamento de Fisioterapia, Universidad de Malaga, Andalucia Tech, Malaga, España
- Instituto de Investigacion Biomédica de Málaga (IBIMA), Malaga, España
| | - Jaime Martín-Martín
- Instituto de Investigacion Biomédica de Málaga (IBIMA), Malaga, España
- Departamento de Medicina Legal, Universidad de Malaga, Málaga, España
| | | | - María Ruiz-Muñoz
- Departamento de Enfermeria, Universidad de Malaga, Malaga, España
| | - Fermin Mayoral
- Instituto de Investigacion Biomédica de Málaga (IBIMA), Malaga, España
- Salud Mental, Hospital Regional Universitario de Malaga, Malaga, Spain
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Wu C, Wang B, Shen G. Unobtrusive monitoring of sedentary behaviors with fusion of bluetooth and ballistocardiogram signals. Methods 2022; 202:152-163. [PMID: 34090972 DOI: 10.1016/j.ymeth.2021.06.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Revised: 05/03/2021] [Accepted: 06/01/2021] [Indexed: 11/23/2022] Open
Abstract
Intensive and lasting stress may induce severe damage to a human's physical and mental health. Successful stress management depends on the effective monitoring of people's everyday activities, in particular, their sedentary behaviors. Here, we propose an unobtrusive office sedentary behavior monitoring system that combines Bluetooth signals and ballistocardiogram (BCG) signals to classify an individual's sitting modes into four categories: off-seat, sedate, working, and in-motion. The proposed monitoring system simultaneously reads received signal strength indicators (RSSI) from several fixed Bluetooth Low Energy (BLE) beacons and BCG data from the piezoelectric sensor placed underneath the chair cushion, with distinct sampling frequencies. The raw signals are first denoised with local subspace projection. Then we extract the local spectral features from the reconstructed signal and the signal differences for a two-stage stacking learning algorithm. The temporally classified results establish a desk-based worker's sedentary profile and make possible the timely intervention of physical inactivity. We tested the prototype system for 15 subjects, and the preliminary results achieved 95% accuracy, demonstrating its potential in a real-world application.
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Affiliation(s)
- Chuanmin Wu
- School of Computer Science, Huazhong University of Science and Technology, Wuhan, China
| | - Bingcheng Wang
- School of Software Engineering, Huazhong University of Science and Technology, Wuhan, China
| | - Gang Shen
- School of Software Engineering, Huazhong University of Science and Technology, Wuhan, China.
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