5 research outputs found
Chronic Sufferers and Environmental Conditions
No full textEnvironmental conditions are associated with the onset of pain or the recurrence of symptoms of chronic sufferers either with musculoskeletal pathologies or neurological diseases. Recent research has indicated that physiotherapy also appears to be helpful in dealing with the symptoms of climate change. The purpose of this study was to investigate how temperature and precipitation are associated with referrals for physical therapy. All the data were collected retrospectively for three years, 2020–2022. A total of 2164 referrals were studied, 78% of which were female cases. Our results highlighted that (a) referrals with musculoskeletal problems are associated with the weather indicators of temperature and precipitation, (b) this relation was found to be stronger for females, and (c) there were slightly differentiated trends between them and those with neurological problems. These results suggest that low temperatures and high precipitation are strongly associated with increased referrals for chronic musculoskeletal pain and that females are more vulnerable to precipitation. Moreover, the increased number of referrals with chronic neurological problems was found to be associated with extreme temperatures. Considering these findings, rehabilitation centers and healthcare systems have the opportunity to immediately provide reliable and qualitative services, guided always by the safety and maximum relief of chronic sufferers
The Correlation between the Temperature, Precipitation, and Referrals for Physical Therapy for Patients with Chronic Musculoskeletal Problems
No full textThe aim of this study was to investigate how temperature and precipitation are associated with the number of referrals for physical therapy. Material and Methods: Weather data and monthly referrals were collected retrospectively for three years (2020–2022). A total of 937 referrals were studied. Trend analysis was conducted to identify patterns and trends in data over time, including correlation analysis to discover relationships and multivariate linear regression analyses to model the direction and strength of this. Results: Monthly referrals were found to be strongly associated with weather indicators (rs = −0.744, p < 0.001 for temperature and rs = 0.894, p < 0.001 for precipitation). Multivariate regression analyses verified this significant correlation (b = −0.763, p < 0.025 and b = 0.598, p < 0.001, respectively). A stronger correlation was found for female referrals (b = 0.509, p < 0.001) compared to that found for male referrals (b = 0.089, p < 0.001). Conclusion: Low temperatures and high precipitation rates were found to be associated with an increased number of referrals. Females were more vulnerable to precipitation increases
Comparison of Machine Learning Algorithms and Hybrid Computational Intelligence Algorithms for Rehabilitation Classification and Prognosis in Reverse Total Shoulder Arthroplasty
No full textDespite the increasing application of machine learning and computational intelligence algorithms in medicine and physiotherapy, accurate classification and prognosis algorithms for postoperative patients in the rehabilitation phase are still lacking. The present study was carried out in two phases. In Phase I, classification performance of simple machine learning algorithms applied on data of patients suffering of reverse total shoulder arthroplasty (RTSA), examining algorithms’ classification accuracy and patients’ rehabilitation prognosis. In Phase II, hybrid computational intelligence algorithms were developed and applied in order to search for the minimum possible training set that achieves the maximum classification and prognostic performance. The data included features like age and gender, passive range of available motion of all movements (preoperative and postoperative), visual analog pain scale (preoperative and postoperative), and total rehabilitation time. In Phase I, K-nearest neighbors (ΚΝΝ) classification algorithm and K-means clustering algorithm (GAKmeans) were applied. Also, a genetic algorithm (GA)-based clustering algorithm (GAClust) was also applied. To achieve 100% performance on the test set, KNN used 80% of the data in the training set, whereas K-means and GAClust used 90% and 53.3%, respectively. In Phase II, additional computational intelligence algorithms were developed, namely, GAKNN (Genetic Algorithm K-nearest neighbors), GAKmeans, and GA2Clust (genetic algorithm-based clustering algorithm 2), for genetic algorithm optimization of the training set. Genetic algorithm optimization of the training set using hybrid algorithms in Phase II resulted in 100% performance on the test set by using only 35% of the available data for training. The proposed hybrid algorithms can reliably be used for patients’ rehabilitation prognosis
Can Exercise Affect the Pain Characteristics in Patients with Fibromyalgia? A Randomized Controlled Trial
No full textExercise is often recommended for fibromyalgia. The aim of this study was to investigate the possible influence and change in the pain characteristics of fibromyalgia patients when breathing exercises were added to their exercise program. A total of 106 patients were included and randomly divided into two groups. Τhe first group of patients followed a program of active exercises up to the limits of pain, lasting 30 min with a repetition of two times a week. Patients of the second group followed the same program with the addition of diaphragmatic breaths when they reached the pain limit. The patients completed three questionnaires: the Fibromyalgia Rapid Screening Tool (FiRST), the Brief Pain Inventory (BPI), and the Pain Quality Assessment Scale (PQAS)—once at the beginning, once again after three weeks of exercise, and again 3 months since the beginning of the program. Independent t-tests for the mean total change scores in pain scales demonstrated that for the second group there was a greater improvement in all pain scales, except for the PQAS Deep Pain subscale (p = 0.38). In conclusion, both groups showed significant improvement in all characteristics of the pain scales; however, the improvement of the second group was significantly higher
Abstracts of the 9th International Organisation of Physical Therapy in Mental Health Conference
Get PDFThis book contains the abstracts of the papers presented at the 9th International Organisation of Physical Therapy in Mental Health Conference, Organized by the International Organisation of Physical Therapy in Mental Health and Greek Scientific Section “Physiotherapy in Mental Health” of PanHellenic Physiotherapists’ Association, held on 4–6 May 2022. It is the biannual conference of the International Organization of Physical Therapy in Mental Health (IOPTMH), and we answered with success the question: Physiotherapy in mental health; what’s next? The highly qualified scientific program, the reputable presenters, and the venue altogether form a powerful motivation for both physiotherapists and other mental health professionals to attend this conference.
Conference Title: 9th International Organisation of Physical Therapy in Mental Health ConferenceConference Theme: Physiotherapy in mental health; what’s next?Conference Date: 4–6 May 2022Conference Location: Crowne Plaza Athens - City Centre Hotel, 50, Michalakopoulou Str. GR 11528 AthensConference Organizer: International Organisation of Physical Therapy in Mental Health and Greek Scientific Section “Physiotherapy in Mental Health” of PanHellenic Physiotherapists’ AssociationConference Secretariat - Public Relations: Alpha Public Relations and Integrated Marketing S.A., 55, Pytheou Str. GR 11743 Athen
