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      Study protocol for the implementation and evaluation of a digital-robotic-based intervention for nurses and patients in a hospital: a quantitative and qualitative triangulation based on the Medical Research Council (MRC) framework for developing and evaluating complex interventions

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          Abstract

          Background

          Nurses spend part of their working time on non-nursing tasks. Unnecessary walking distances and the assumption of service activities and other non-care-related tasks take up a lot of space, which reduces the time for direct patient care and demonstrably increases the dissatisfaction of the persons involved. The REsPonSe project aims to relieve nursing staff by using a smartphone app for communication in combination with an autonomous service robot to reduce walking distances and service activities. The technical systems are tested on a nuclear medicine ward and are intended to reduce the radiation exposure of the staff. The aim of this study is to test and evaluate the use and intervention of the technical systems, the acceptance of the users and the change in the utilisation of the nursing service. In addition to findings on usability and manageability, effects on nursing practice, as well as facilitating and inhibiting contextual factors for implementation, will be identified.

          Methods

          The Medical Research Council (MRC) Framework for Developing and Evaluating for Complex Interventions was chosen as the theoretical basis. The data collection in the Feasibility and Evaluation phase is a triangulation of quantitative and qualitative methods. Standardised observations are planned to collect data on non-care activities and walking distances, and a survey of utilisation by use of a questionnaire based on the NASA TLX. Qualitative individual interviews with patients and group discussions with nursing staff will be conducted. Statements on the subjective experiences, as well as the evaluation of the use of the digital-robotic system in the clinical setting, will be collected. The descriptive evaluation of the usage and retrieval data will provide information on duration, time, requests, and reduced contact times, as well as error and fault messages.

          Discussion

          The evaluation study will make it possible to represent a variety of perspectives from different interest groups. The results should contribute to the definition of implementation and evaluation criteria and facilitate the integration of digital-robotic assistance systems in nursing acute inpatient settings.

          Trial registration

          The trial was registered with the German Clinical Trials Register (DRKS) on 16.02.2022: DRKS00028127.

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          Most cited references42

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          A new framework for developing and evaluating complex interventions: update of Medical Research Council guidance

          The UK Medical Research Council’s widely used guidance for developing and evaluating complex interventions has been replaced by a new framework, commissioned jointly by the Medical Research Council and the National Institute for Health Research, which takes account of recent developments in theory and methods and the need to maximise the efficiency, use, and impact of research.
            Bookmark
            • Record: found
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            Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research

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              Qualitative Inhaltsanalyse. Methoden, praxis, Computerunterstützung

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                Author and article information

                Contributors
                Christoph.Ohneberg@ku.de
                Journal
                BMC Nurs
                BMC Nurs
                BMC Nursing
                BioMed Central (London )
                1472-6955
                9 December 2022
                9 December 2022
                2022
                : 21
                : 349
                Affiliations
                [1 ]GRID grid.440923.8, ISNI 0000 0001 1245 5350, Professorship of Nursing Science, Faculty of Social Work, , Catholic University of Eichstätt-Ingolstadt, ; Kapuzinergasse 2, 85072 Eichstätt, Germany
                [2 ]GRID grid.411095.8, ISNI 0000 0004 0477 2585, Clinical Nursing Research and Quality Management Unit, , University Hospital LMU Munich, ; Marchioninistr. 15, 81377 Munich, Germany
                [3 ]Cliniserve GmbH, Balanstr. 73/10, 81541 Munich, Germany
                [4 ]Robotise AG, Otto-Hahn-Ring 6, Building 60, 81739 Munich, Germany
                Article
                1088
                10.1186/s12912-022-01088-6
                9733387
                36494679
                04fb4acf-55b6-4d32-9d80-d8fb8b88ad66
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 1 August 2022
                : 27 October 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100002347, Bundesministerium für Bildung und Forschung;
                Award ID: 16SV8416
                Award ID: 16SV8416
                Award Recipient :
                Funded by: Katholische Universität Eichstätt-Ingolstadt (3115)
                Categories
                Study Protocol
                Custom metadata
                © The Author(s) 2022

                Nursing
                nursing robotics,assistive robotics,digitalization,technology implementation,inpatient care,nursing science

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