39 resultados para Non-practitioners of physical exercise

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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SYSTEMATIC REVIEW AND META-ANALYSIS: EFFECTS OF WALKING EXERCISE IN CHRONIC MUSCULOSKELETAL PAIN O'Connor S.R.1, Tully M.A.2, Ryan B.3, Baxter D.G.3, Bradley J.M.1, McDonough S.M.11University of Ulster, Health & Rehabilitation Sciences Research Institute, Newtownabbey, United Kingdom, 2Queen's University, UKCRC Centre of Excellence for Public Health (NI), Belfast, United Kingdom, 3University of Otago, Centre for Physiotherapy Research, Dunedin, New ZealandPurpose: To examine the effects of walking exercise on pain and self-reported function in adults with chronic musculoskeletal pain.Relevance: Chronic musculoskeletal pain is a major cause of morbidity, exerting a substantial influence on long-term health status and overall quality of life. Current treatment recommendations advocate various aerobic exercise interventions for such conditions. Walking may represent an ideal form of exercise due to its relatively low impact. However, there is currently limited evidence for its effectiveness.Participants: Not applicable.Methods: A comprehensive search strategy was undertaken by two independent reviewers according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) and the recommendations of the Cochrane Musculoskeletal Review Group. Six electronic databases (Medline, CINAHL, PsychINFO, PEDro, Sport DISCUS and the Cochrane Central Register of Controlled Trials) were searched for relevant papers published up to January 2010 using MeSH terms. All randomised or non-randomised studies published in full were considered for inclusion. Studies were required to include adults aged 18 years or over with a diagnosis of chronic low back pain, osteoarthritis or fibromyalgia. Studies were excluded if they involved peri-operative or post-operative interventions or did not include a comparative, non exercise or non-walking exercise control group. The U.S. Preventative Services Task Force system was used to assess methodological quality. Data for pain and self-reported function were extracted and converted to a score out of 100.Analysis: Data were pooled and analyzed using RevMan (v.5.0.24). Statistical heterogeneity was assessed using the X2 and I2 test statistics. A random effects model was used to calculate the mean differences and 95% CIs. Data were analyzed by length of final follow-up which was categorized as short (≤8 weeks post randomisation), mid (2-12 months) or long-term (>12 months).Results: A total of 4324 articles were identified and twenty studies (1852 participants) meeting the inclusion criteria were included in the review. Overall, studies were judged to be of at least fair methodological quality. The most common sources of likely bias were identified as lack of concealed allocation and failure to adequately address incomplete data. Data from 12 studies were suitable for meta-analysis. Walking led to reductions in pain at short (<8 weeks post randomisation) (-8.44 [-14.54, -2.33]) and mid-term (>8 weeks - 12 month) follow-up (-9.28 [-16.34, -2.22]). No effect was observed for long-term (>12 month) data (-2.49 [-7.62, 2.65]). For function, between group differences were observed for short (-11.57 [-16.06, -7.08]) and mid-term data (-13.26 [-16.91, -9.62]). A smaller effect was also observed at long-term follow-up (-5.60 [-7.70, -3.50]).Conclusions: Walking interventions were associated with statistically significant improvements in pain and function at short and mid-term follow-up. Long-term data were limited but indicated that these effects do not appear to be maintained beyond twelve months.Implications: Walking may be an effective form of exercise for individuals with chronic musculoskeletal pain. However, further research is required which examines longer term follow-up and dose-response issues in this population.Key-words: 1. Walking exercise 2. Musculoskeletal pain 3. Systematic reviewFunding acknowledgements: Department of Employment and Learning, Northern Ireland.Ethics approval: Not applicable.

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Objectives: To assess the levels of physical activity and other health related behaviours of General Practitioners (GPs) and compare their reported levels of physical activity with those of the general population. Study Design: Cross sectional postal questionnaire survey. Methods: A questionnaire, which did not allow identification of individual respondents, was posted to all 1074 (GPs) in Northern Ireland. It included the validated International Physical Activity Questionnaire (IPAQ) and questions relating to smoking and alcohol consumption. A national survey of a representative sample of the general population of similar age (29-67 years; n = 3010) provided comparative data. Results: 735 GPs responded (68.4%). IPAQ data indicated that fewer GPs (43.4%) were “physically inactive” compared to the general population (56.2%) (p

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Abstract
Background Physical inactivity is a major public health concern, and more innovative approaches are urgently needed to address it. The UK Government supports the use of incentives and so-called nudges to encourage healthy behaviour changes, and has encouraged business sector involvement in public health through the Public Health Responsibility Deal. To test the effectiveness of provision of incentives to encourage adults to increase their physical activity, we
recruited 406 adults from a workplace setting (office-based) to take part in an assessor-blind randomised controlled trial.
Methods
We developed the physical activity loyalty card scheme, which integrates a novel physical activity tracking system with web-based monitoring (palcard). Participants were recruited from two buildings at Northern Ireland’s main
government offices and were randomly allocated (grouped by building [n=2] to reduce contamination) to either incentive group (n=199) or no incentive group (n=207). We included participants aged 16–65 years, based at the worksite 4 days or more per week and for 6 h or more per day, and able to complete 15 min of moderate-paced walking (self-report). Exclusion criteria included having received specific advice by a general practitioner not to exercise. A statistician not involved in administration of the trial prepared a computer-generated random allocation sequence. Random assignments were placed in individually numbered, sealed envelopes by the statistician to ensure concealment of allocation. Only the assessor was masked to assignment. Sensors were placed along footpaths and the gym in the workplace. Participants scanned their loyalty card at the sensor when undertaking physical activity (eg, walking), which logged activity. Participants in the incentive group monitored their physical activity, collected points, and received rewards (retail vouchers) for minutes of physical activity completed over the 12-week intervention. Rewards were vouchers sponsored by local retailers. Participants in the no incentive group used their loyalty card to self-monitor their physical activity but were not able to earn points or receive rewards. The primary outcome was change in minutes of moderate to vigorous physical activity with the Global Physical Activity Questionnaire, measured at baseline, week 12, and 6 months. Activity was objectively measured with the tracking system over the 12-week intervention. Mann Whitney U tests were done to assess change between groups.
Findings
The mean age of participants was 43·32 years (SD 9·37), and 272 (67%) were women. We obtained follow-up data from 353 (87%) participants at week 12 and 341 (84%) at 6 months. At week 12, participants in the incentive group increased moderate to vigorous physical activity by a median of 60 min per week (IQR –10 to 120) compared with 30 min per week (–60 to 90) in the no incentive group (p=0·05). At 6 months, participants in the incentive group had
increased their moderate to vigorous physical activity by 30 min per week (–60 to 100) from baseline compared with 0 min per week (–115 to 1110) in the no incentive group (p=0·099). We noted no significant differences between groups
for use of loyalty card (p=0·18). Participants in the incentive group recorded a mean of 60·22 min (95% CI 50·90–69·55) of physical activity per week with their loyalty card on week 1 and 23·56 min (17·06–30·06) at week 12, which was similar to that for those in the no incentive group (59·74 min, 51·24–68·23, at week 1; 20·25 min, 14·45–26·06, at week 12; p=0·94 for differences between groups at week 1; p=0·45 for differences between groups at week 12).
Interpretation:
Financial incentives showed a short-term behaviour change in physical activity. This innovative study contributes to the necessary evidence base, and has important implications for physical activity promotion and business engagement in health. The optimum incentive-based approach needs to be established. Results should be interpreted with some caution as the analyses of secondary outcomes were not adjusted for multiple comparisons.

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Despite several decades of decline, cardiovascular diseases are still the most common causes of death in Western societies. Sedentary living and high fat diets contribute to the prevalence of cardiovascular diseases. This paper analyses the trade-offs between lifestyle choices defined in terms of diet, physical activity, cost, and risk of cardiovascular disease that a representative sample of the population of Northern Ireland aged 40-65 are willing to make. Using computer assisted personal interviews, we survey 493 individuals at their homes using a Discrete Choice Experiment (DCE) questionnaire administered between February and July 2011 in Northern Ireland. Unlike most DCE studies for valuing public health programs, this questionnaire uses a tailored exercise, based on the individuals’ baseline choices. A “fat screener” module in the questionnaire links personal cardiovascular disease risk to each specific choice set in terms of dietary constituents. Individuals are informed about their real status quo risk of a fatal cardiovascular event, based on an initial set of health questions. Thus, actual risks, real diet and exercise choices are the elements that constitute the choice task. Our results show that our respondents are willing to pay for reducing mortality risk and, more importantly, are willing to change physical exercise and dietary behaviours. In particular, we find that to improve their lifestyles, overweight and obese people would be more likely to do more physical activity than to change their diets. Therefore, public policies aimed to target obesity and its related illnesses in Northern Ireland should invest public money in promoting physical activity rather than healthier diets.

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We investigate the conditions under which the trace distance between two different states of a given open system increases in time due to the interaction with an environment, therefore signaling non-Markovianity. We find that the finite-time difference in trace distance is bounded by two sharply defined quantities that are strictly linked to the occurrence of system-environment correlations created throughout their interaction and affecting the subsequent evolution of the system. This allows us to shed light on the origin of non-Markovian behaviors in quantum dynamics. We best illustrate our findings by tackling two physically relevant examples: a non-Markovian dephasing mechanism that has been the focus of a recent experimental endeavor and the open-system dynamics experienced by a spin connected to a finite-size quantum spin chain.

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Abstract
Publicly available, outdoor webcams continuously view the world and share images. These cameras include traffic cams, campus cams, ski-resort cams, etc. The Archive of Many Outdoor Scenes (AMOS) is a project aiming to geolocate, annotate, archive, and visualize these cameras and images to serve as a resource for a wide variety of scientific applications. The AMOS dataset has archived over 750 million images of outdoor environments from 27,000 webcams since 2006. Our goal is to utilize the AMOS image dataset and crowdsourcing to develop reliable and valid tools to improve physical activity assessment via online, outdoor webcam capture of global physical activity patterns and urban built environment characteristics.
This project’s grand scale-up of capturing physical activity patterns and built environments is a methodological step forward in advancing a real-time, non-labor intensive assessment using webcams, crowdsourcing, and eventually machine learning. The combined use of webcams capturing outdoor scenes every 30 min and crowdsources providing the labor of annotating the scenes allows for accelerated public health surveillance related to physical activity across numerous built environments. The ultimate goal of this public health and computer vision collaboration is to develop machine learning algorithms that will automatically identify and calculate physical activity patterns.