Introduction: Illness Perceptions (IPs) may play a role in the management of persistent low back pain. The mediation and/or moderation effect of IPs on primary outcomes in physiotherapy treatment is unknown. Methods: A multiple single-case experimental design, using a matched care physiotherapy intervention, with three phases (phases A-B-A’) was used including a 3 month follow up (phase A’). Primary outcomes: pain intensity, physical functioning and pain interference in daily life. Analyzes: linear mixed models, adjusted for fear of movement, catastrophizing, avoidance, sombreness and sleep. Results: Nine patients were included by six different primary care physiotherapists. Repeated measures on 196 data points showed that IPs Consequences, Personal control, Identity, Concern and Emotional response had a mediation effect on all three primary outcomes. The IP Personal control acted as a moderator for all primary outcomes, with clinically relevant improvements at 3 month follow up. Conclusion: Our study might indicate that some IPs have a mediating or a moderating effect on the outcome of a matched care physiotherapy treatment. Assessing Personal control at baseline, as a relevant moderator for the outcome prognosis of successful physiotherapy management of persistent low back pain, should be further eplored.
The adaptation of urbanised areas to climate change is currently one of the key challenges in the domain of urban policy. The diversity of environmental determinants requires the formulation of individual plans dedicated to the most significant local issues. This article serves as a methodic proposition for the stage of retrieving data (with the PESTEL and the Delphi method), systemic diagnosis (evaluation of risk and susceptibility), prognosis (goal trees, goal intensity map) and the formulation of urban adaptation plans. The suggested solution complies with the Polish guidelines for establishing adaptation plans. The proposed methodological approach guarantees the participation of various groups of stakeholders in the process of working on urban adaptation plans, which is in accordance with the current tendencies to strengthen the role of public participation in spatial management. https://doi.org/10.12911/22998993/81658
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Low back pain is the leading cause of disability worldwide and a significant contributor to work incapacity. Although effective therapeutic options are scarce, exercises supervised by a physiotherapist have shown to be effective. However, the effects found in research studies tend to be small, likely due to the heterogeneous nature of patients' complaints and movement limitations. Personalized treatment is necessary as a 'one-size-fits-all' approach is not sufficient. High-tech solutions consisting of motions sensors supported by artificial intelligence will facilitate physiotherapists to achieve this goal. To date, physiotherapists use questionnaires and physical examinations, which provide subjective results and therefore limited support for treatment decisions. Objective measurement data obtained by motion sensors can help to determine abnormal movement patterns. This information may be crucial in evaluating the prognosis and designing the physiotherapy treatment plan. The proposed study is a small cohort study (n=30) that involves low back pain patients visiting a physiotherapist and performing simple movement tasks such as walking and repeated forward bending. The movements will be recorded using sensors that estimate orientation from accelerations, angular velocities and magnetometer data. Participants complete questionnaires about their pain and functioning before and after treatment. Artificial analysis techniques will be used to link the sensor and questionnaire data to identify clinically relevant subgroups based on movement patterns, and to determine if there are differences in prognosis between these subgroups that serve as a starting point of personalized treatments. This pilot study aims to investigate the potential benefits of using motion sensors to personalize the treatment of low back pain. It serves as a foundation for future research into the use of motion sensors in the treatment of low back pain and other musculoskeletal or neurological movement disorders.