18 research outputs found

    Does the use of friction reducing devices actually reduce the exposure to high force lateral transfers?

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    The activity of transferring a person from lying to lying frequently occurs in healthcare, e.g. bed to trolley, treatment tables, theatre departments and ambulance services. These positional changes can include lateral transfers (bed to bed), moving up a bed (boosting), or supine to side lying (turning). Transferring patients has long been identified as a contributory cause of MSD in healthcare processes. This study explored routes to error in a UK national healthcare provider for the range of transfers indicated and investigated the level of knowledge within the workforce to complete these transfers. A survey (n=170) showed that a high percentage of staff reported that transfers that using slide sheet devices were being performed in a way which did not following the evidence based guidance. 31.6% of the descriptions of how to set up a transfer were incorrect and a further 13.0% were less than optimal. Only 31/170 respondents showed no errors in their survey responses. A secondary laboratory study quantified the force differences between a best practice transfer and the various erroneous methods. The additional forces were compared to show that there could be more than 100% increase in the amount of effort that healthcare workers have to use of the preparation of the transfer is not performed correctly. Processes and design considerations that enforce the compliance with best practice guidelines can assist in the reduction of the overall musculoskeletal effort that healthcare workers endure

    Does the use of friction reducing devices reduce the exposure to high-force horizontal transfers

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    Transferring a person from lying to lying frequently occurs in healthcare, e.g. bed to trolley, treatment tables, theatre departments and ambulance services. Transferring patients has long been identified as a contributory cause of MSD in healthcare processes. The provision of friction removing material is accepted as a sensible solution to reduce the biomechanical load for horizontal transfers. Little evidence has reported the consequences of not following best practice guidelines when using friction removing devices. This study explored routes to error in an NHS Trust for a range of horizontal transfers and investigated the level of knowledge within the workforce to complete these transfers. A questionnaire survey (n=170) showed that a high percentage of staff reported that horizontal transfers using slide sheet devices were not being performed optimally. A laboratory study quantified the force differences between a best practice transfer and the various erroneous methods. The additional forces showed up to 100% increase in the amount of effort for healthcare workers for each transfer not performed correctly. Based on the reported error an intervention was implemented that simplified the slide sheet protocol across the trust. Only one single slide sheet was provided in all areas to ensure full coverage of the bed and allowed all transfer types with a single tube sheet. Secondary data showed significant improvements in the ability of staff to follow the new protocol and reduce routes to error

    Data for Fodor, L.A., Cotet, C.D., Cuijpers, P, Szamoskozi, David, D. & Cristea, I.A. (2018). Scientific Reports

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    Effect size data for the article <br>Fodor, L.A., Cotet, C.D., Cuijpers, P, Szamoskozi, David, D. & Cristea, I.A. (2018) "<b>The effectiveness of virtual reality based interventions for symptoms of anxiety and depression: A meta-analysis". </b><i>Scientific Reports</i><b><br></b

    Social anxiety levels for the two groups throughout the iSOFIE program.

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    <p>Abbreviations: iSOFIE = the iSOFIE intervention group; WLCG = Wait List Control Group; Pre = Pre-intervention assessment, Post = Post-intervention assessment.</p

    The DREAM Dataset: Supporting a data-driven study of autism spectrum disorder and robot enhanced therapy

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    We present a dataset of behavioral data recorded from 61 children diagnosed with Autism Spectrum Disorder (ASD). The data was collected during a large-scale evaluation of Robot Enhanced Therapy (RET). The dataset covers over 3000 therapy sessions and more than 300 hours of therapy. Half of the children interacted with the social robot NAO supervised by a therapist. The other half, constituting a control group, interacted directly with a therapist. Both groups followed the Applied Behavior Analysis (ABA) protocol. Each session was recorded with three RGB cameras and two RGBD (Kinect) cameras, providing detailed information of children’s behavior during therapy. This public release of the dataset comprises body motion, head position and orientation, and eye gaze variables, all specified as 3D data in a joint frame of reference. In addition, metadata including participant age, gender, and autism diagnosis (ADOS) variables are included. We release this data with the hope of supporting further data-driven studies towards improved therapy methods as well as a better understanding of ASD in general
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