| 1. |
- Ahlstrand, Inger, et al.
(författare)
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Health-promoting factors among students in higher education within health care and social work : a cross-sectional analysis of baseline data in a multicentre longitudinal study
- 2022
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Ingår i: BMC Public Health. - London : BioMed Central. - 1471-2458. ; 22:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Educational environments are considered important in strengthening students’ health status and knowledge, which are associated with good educational outcomes. It has been suggested to establish healthy universities based on a salutogenic approach – namely, health promotion. The aim of this study was to describe health-promoting resources and factors among first-semester students in higher education in healthcare and social work.Methods: This cross-sectional study is based on a survey distributed among all students in seven healthcare and social work programmes at six universities in southern Sweden. The survey was carried out in 2018 using a self-reported, web-based questionnaire focussing on general health and well-being, lifestyle factors together with three validated instruments measuring health-promoting factors and processes: the Sense of Coherence (SOC) scale, Salutogenic Health Indicator Scale (SHIS) and Occupational Balance Questionnaire (OBQ).Results: Of 2283 students, 851 (37.3%) completed the survey, of whom 742 (87.1%) were women; 722 (84.8%) were enrolled on healthcare programmes, and 129 (15.2%) were enrolled on social work programmes. Most reported good general health and well-being (88.1% and 83.7%, respectively). The total mean scores for the SOC scale, SHIS and OBQ were, respectively, 59.09 (SD = 11.78), 44.04 (SD = 9.38) and 26.40 (SD = 7.07). Well-being and several healthy lifestyles were related to better general health and higher SOC, SHIS and OBQ scores. Multiple linear and logistic regressions showed that perceived well-being and no sleeping problems significantly predicted higher general health and higher SOC, SHIS and OBQ scores. Being less sedentary and non-smoking habits were significant predictors of higher SOC.Conclusions: Swedish students in higher education within the healthcare and social work sector report good general health and well-being in the first semester, as well as health-promoting resources (i.e. SOC, SHIS and OBQ), and in some aspects, a healthy lifestyle. High-intensity exercise, no sleeping problems and non-smoking seem to be of importance to both general health and health-promotive resources. This study contributes to knowledge about the health promotive characteristics of students in the healthcare and social work fields, which is of importance for planning universities with a salutogenic approach.
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| 2. |
- Larsson, Jonas, 1968-, et al.
(författare)
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Swedish soccer coaches' experiences and application of physical training in male elite soccer : A qualitative content analysis study
- 2021
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Ingår i: Scandinavian Sport Studies Forum. - Malmö : Malmö University. - 2000-088X. ; 12, s. 159-181
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Tidskriftsartikel (refereegranskat)abstract
- In elite soccer, training becomes more systematic and soccer clubs try to optimise their physiological training programs. Previous research has investigated many aspects of soccer, but research into the coaches’ own experiences and continuous improvement of physical training is lacking. The aim of this study was to describe the coaches’ experiences and their application of physical training in male elite soccer. The design of the study was explorative and based on a qualitative content analysis with an abductive approach based on a custom version of the four-step quality model—the plan-do-check-act (PDCA) cycle. Fifteen elite soccer coaches in Sweden were interviewed. The result showed that physical training in male elite soccer is an ongoing continuously improvement process that contains four different categories: 1) planning, containing gained experiences, teamwork, and lack of resources; 2) executing with different training methods, weekly rotation, and individual training; 3) evaluating containing monitor training load and physiological testing, and 4) improving with search for knowledge and long-term development. The coaches try to absorb new knowledge and continuously improve their training methods, although lack of resources sometimes does not allow them to introduce new training methods.
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| 3. |
- Karnehed, Sara, 1979-, et al.
(författare)
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Kan samproduktion av framtidens teknik bidra till en hållbar arbetsmiljö för sjuksköterskor?
- 2023
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Konferensbidrag (refereegranskat)abstract
- Svensk primärvård står inför stora utmaningar med en åldrande befolkning och ett ökat antal personer som vårdas i hemmet (Landers et al., 2016). Digital teknik implementeras med förhoppning om att förbättra kommunikationen mellan vårdpersonal och underlätta möjligheterna till egenvård och tillgänglighet för patienter (Socialstyrelsen, 2021). Tidigare studier visar att användningen av digital teknik kan förändra det professionella landskapet (Petersson, 2020) och påverka arbetsmiljö och arbetets innehåll (Ertner, 2019). Trots att teknik som implementeras inom vården bör vara anpassad till hälso- och sjukvårdspersonalens arbete och värderingar (Palmer et al., 2019; Reed et al., 2019) är sjuksköterskor sällan involverade i beslut kring utformning eller implementering av ny teknik (von Gerich et al., 2022). Det behövs mer kunskap om hur digitaliseringen kan ske i samproduktion med sjuksköterskor och utformas så att en god arbetsmiljö bibehålls.Presentationen syftar till att beskriva sjuksköterskors arbete och arbetsmiljö inom hemsjukvården och hur dessa kunskaper kan användas vid utvecklingen och implementeringen av framtida digital teknik.Individuella semi-strukturerade intervjuer har genomförts med 20 sjuksköterskor som arbetar på vårdcentral och inom hemsjukvård i två halländska kommuner. Intervjuerna har analyserats genom kvalitativ innehållsanalys (Hsieh & Shannon, 2005). Implementeringsteoretiska ramverk används för att undersöka hur kunskapen kan inkorporeras vid innovation och implementering av digitala tekniker inom vårdverksamheter (Nilsen, 2015).Preliminära resultat kommer att presenteras vid konferensen.ReferenserErtner, S. M. (2019). Enchanting, evoking, and affecting: the invisible work of technology implementation in homecare. Nordic Journal of Working Life Studies, 9(S5), 33-47.Hsieh, H.-F., & Shannon, S. E. (2005). Three Approaches to Qualitative Content Analysis. Qualitative health research, 15(9), 1277-1288.Landers, S., Madigan, E., Leff, B., Rosati, R. J., McCann, B. A., Hornbake, R., MacMillan, R., Jones, K., Bowles, K., Dowding, D., Lee, T., Moorhead, T., Rodriguez, S., & Breese, E. (2016). The Future of Home Health Care: A Strategic Framework for Optimizing Value. Home Health Care Management & Practice, 28(4), 262-278.Nilsen, P. (2015). Making sense of implementation theories, models and frameworks. Implementation science : IS, 10(1), 53-53.Palmer, V. J., Weavell, W., Callander, R., Piper, D., Richard, L., Maher, L., Boyd, H., Herrman, H., Furler, J., & Gunn, J. (2019). The Participatory Zeitgeist: an explanatory theoretical model of change in an era of coproduction and codesign in healthcare improvement. Medical humanities, 45(3), 247-257.Petersson, L. (2020). Paving the way for transparency: How eHealth technology can change boundaries in healthcare Lund University].Reed, J. E., Howe, C., Doyle, C., & Bell, D. (2019). Successful healthcare improvements from translating evidence in complex systems (SHIFT-Evidence): simple rules to guide practice and research. International journal for quality in health care, 31(3), 238-244.Socialstyrelsen. (2021). E-hälsa och välfärdsteknik i kommunerna 2021. Uppföljning av den digitala utvecklingen i socialtjänsten och den kommunala hälso-och sjukvården.von Gerich, H., Moen, H., Block, L. J., Chu, C. H., DeForest, H., Hobensack, M., Michalowski, M., Mitchell, J., Nibber, R., & Olalia, M. A. (2022). Artificial Intelligence-based technologies in nursing: A scoping literature review of the evidence. International Journal of Nursing Studies, 127, 104153.
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| 4. |
- Larsson, Ingrid, 1968-, et al.
(författare)
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Patient Empowerment and Associations with Disease Activity and Pain‐Related and Lifestyle Factors in Patients With Rheumatoid Arthritis
- 2021
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Ingår i: ACR Open Rheumatology. - Hoboken, NJ : John Wiley & Sons. - 2578-5745. ; 3:12, s. 842-849
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Tidskriftsartikel (refereegranskat)abstract
- Background: Empowerment is important to patients with rheumatoid arthritis (RA) because most care is in the form of self-management. The aim was to study levels of empowerment and associated variables in patients with RA and to investigate longitudinal clinical data in patients with low and high empowerment.Methods: A postal survey was sent in 2017 to patients with RA from the BARFOT (Better Anti-Rheumatic Pharmacotherapy) cohort that included questions about disease activity, pain-related factors, lifestyle habits, and contained the Swedish Rheumatic Disease Empowerment Scale (SWE-RES-23). The 844 patients who answered the SWE-RES-23 made up the cohort of the present study. Differences in level of empowerment between groups (low, moderate, and high empowerment) were analyzed with ANOVA. Logistic regression analysis was used to study variables associated with low empowerment. Thirdly, we performed comparisons in longitudinal data (15 years) of disease activity, pain, and physical function between the three empowerment groups (low, moderate, and high empowerment).Results: Patients with low empowerment (n = 282) were significantly older, more often women, and reported worse pain-related factors and physical function and lower moderate and vigorous physical activity compared with those with high empowerment (n = 270). An analysis of longitudinal data found that patients with low empowerment had worse pain and physical function at all time points.Conclusion: Patients with low empowerment have more pain-related symptoms, poorer physical function, and are less physically active. To promote patient empowerment in rehabilitation interventions it is important to identify and support self-management. © 2021 The Authors.
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| 5. |
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| 6. |
- Lindmark, Ulrika, 1965-, et al.
(författare)
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Health-promoting factors in higher education for a sustainable working life : protocol for a multicenter longitudinal study
- 2020
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Ingår i: BMC Public Health. - London : BioMed Central. - 1471-2458. ; 20:1
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The World Health Organization has highlighted the importance of health promotion for health service providers in order to ensure sustainable working life for individuals involved in providing health services. Such sustainability begins when students are preparing to manage their own future health and welfare in working life. It has been suggested that universities, employees and trainee health professionals should adopt or follow a salutogenic approach that not only complements the providing of information on known health risks but also favors health promotion strategies. This paper describes the study design and data collection methods in a planned study aiming to explore health-promoting factors for a sustainable working life among students in higher education within healthcare and social work. METHODS: This protocol describes a multicenter longitudinal study involving Swedish students on higher education programs in the healthcare and social work sectors. In 2018, the study invited students on seven education programs at six universities to participate. These programs were for qualification as: biomedical laboratory scientists (n = 121); dental hygienists (n = 87); nurses (n = 1411); occupational therapists (n = 111); physiotherapists (n = 48); radiographers (n = 60); and, social workers (n = 443). In total, 2283 students were invited to participate. Participants completed a baseline, a self-reported questionnaire including six validated instruments measuring health-promoting factors and processes. There are to be five follow-up questionnaires. Three while the students are studying, one a year after graduating, and one three years after graduating. Each questionnaire captures different health-promoting dimensions, namely: health-promoting resources (i.e. sense of coherence); occupational balance; emotional intelligence; health and welfare; social interaction; and work and workplace experiences/perceptions. DISCUSSION: This study focuses on the vastly important aspect of promoting a sustainable working life for healthcare and social work employees. In contrast to previous studies in this area, the present study uses different, validated instruments in health promotion, taking a salutogenic approach. It is hoped that, by stimulating the implementation of new strategies, the study's findings will lead to education programs that prepare students better for a sustainable working life in healthcare and social work.
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| 7. |
- Neher, Margit, 1959-, et al.
(författare)
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Innovation in healthcare : leadership perceptions about the innovation characteristics of artificial intelligence—a qualitative interview study with healthcare leaders in Sweden
- 2023
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Ingår i: Implementation Science Communications. - London : BioMed Central (BMC). - 2662-2211. ; 4
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Tidskriftsartikel (refereegranskat)abstract
- Background: Despite the extensive hopes and expectations for value creation resulting from the implementation of artificial intelligence (AI) applications in healthcare, research has predominantly been technology-centric rather than focused on the many changes that are required in clinical practice for the technology to be successfully implemented. The importance of leaders in the successful implementation of innovations in healthcare is well recognised, yet their perspectives on the specific innovation characteristics of AI are still unknown. The aim of this study was therefore to explore the perceptions of leaders in healthcare concerning the innovation characteristics of AI intended to be implemented into their organisation.Methods: The study had a deductive qualitative design, using constructs from the innovation domain in the Consolidated Framework for Implementation Research (CFIR). Interviews were conducted with 26 leaders in healthcare.Results: Participants perceived that AI could provide relative advantages when it came to care management, supporting clinical decisions, and the early detection of disease and risk of disease. The development of AI in the organisation itself was perceived as the main current innovation source. The evidence base behind AI technology was questioned, in relation to its transparency, potential quality improvement, and safety risks. Although the participants acknowledged AI to be superior to human action in terms of effectiveness and precision in some situations, they also expressed uncertainty about the adaptability and trialability of AI. Complexities such as the characteristics of the technology, the lack of conceptual consensus about AI, and the need for a variety of implementation strategies to accomplish transformative change in practice were identified, as were uncertainties about the costs involved in AI implementation.Conclusion: Healthcare leaders not only saw potential in the technology and its use in practice, but also felt that AI’s opacity limits its evidence strength and that complexities in relation to AI itself and its implementation influence its current use in healthcare practice. More research is needed based on actual experiences using AI applications in real-world situations and their impact on clinical practice. New theories, models, and frameworks may need to be developed to meet challenges related to the implementation of AI in healthcare. © 2023, The Author(s).
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| 8. |
- Nilsen, Per, 1960-, et al.
(författare)
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A Framework to Guide Implementation of AI in Health Care : Protocol for a Cocreation Research Project
- 2023
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Ingår i: JMIR Research Protocols. - Toronto : JMIR Publications. - 1929-0748. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- Background: Artificial intelligence (AI) has the potential in health care to transform patient care and administrative processes, yet health care has been slow to adopt AI due to many types of barriers. Implementation science has shown the importance of structured implementation processes to overcome implementation barriers. However, there is a lack of knowledge and tools to guide such processes when implementing AI-based applications in health care.Objective: The aim of this protocol is to describe the development, testing, and evaluation of a framework, “Artificial Intelligence-Quality Implementation Framework” (AI-QIF), intended to guide decisions and activities related to the implementation of various AI-based applications in health care.Methods: The paper outlines the development of an AI implementation framework for broad use in health care based on the Quality Implementation Framework (QIF). QIF is a process model developed in implementation science. The model guides the user to consider implementation-related issues in a step-by-step design and plan and perform activities that support implementation. This framework was chosen for its adaptability, usability, broad scope, and detailed guidance concerning important activities and considerations for successful implementation. The development will proceed in 5 phases with primarily qualitative methods being used. The process starts with phase I, in which an AI-adapted version of QIF is created (AI-QIF). Phase II will produce a digital mockup of the AI-QIF. Phase III will involve the development of a prototype of the AI-QIF with an intuitive user interface. Phase IV is dedicated to usability testing of the prototype in health care environments. Phase V will focus on evaluating the usability and effectiveness of the AI-QIF. Cocreation is a guiding principle for the project and is an important aspect in 4 of the 5 development phases. The cocreation process will enable the use of both on research-based and practice-based knowledge.Results: The project is being conducted within the frame of a larger research program, with the overall objective of developing theoretically and empirically informed frameworks to support AI implementation in routine health care. The program was launched in 2021 and has carried out numerous research activities. The development of AI-QIF as a tool to guide the implementation of AI-based applications in health care will draw on knowledge and experience acquired from these activities. The framework is being developed over 2 years, from January 2023 to December 2024. It is under continuous development and refinement.Conclusions: The development of the AI implementation framework, AI-QIF, described in this study protocol aims to facilitate the implementation of AI-based applications in health care based on the premise that implementation processes benefit from being well-prepared and structured. The framework will be coproduced to enhance its relevance, validity, usefulness, and potential value for application in practice. © 2023 The Author(s).
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| 9. |
- Petersson, Lena, 1968-, et al.
(författare)
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Challenges to implementing artificial intelligence in healthcare : a qualitative interview study with healthcare leaders in Sweden
- 2022
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Ingår i: BMC Health Services Research. - London : BioMed Central (BMC). - 1472-6963. ; 22
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Tidskriftsartikel (refereegranskat)abstract
- Background: Artificial intelligence (AI) for healthcare presents potential solutions to some of the challenges faced by health systems around the world. However, it is well established in implementation and innovation research that novel technologies are often resisted by healthcare leaders, which contributes to their slow and variable uptake. Although research on various stakeholders’ perspectives on AI implementation has been undertaken, very few studies have investigated leaders’ perspectives on the issue of AI implementation in healthcare. It is essential to understand the perspectives of healthcare leaders, because they have a key role in the implementation process of new technologies in healthcare. The aim of this study was to explore challenges perceived by leaders in a regional Swedish healthcare setting concerning the implementation of AI in healthcare.Methods: The study takes an explorative qualitative approach. Individual, semi-structured interviews were conducted from October 2020 to May 2021 with 26 healthcare leaders. The analysis was performed using qualitative content analysis, with an inductive approach.Results: The analysis yielded three categories, representing three types of challenge perceived to be linked with the implementation of AI in healthcare: 1) Conditions external to the healthcare system; 2) Capacity for strategic change management; 3) Transformation of healthcare professions and healthcare practice.Conclusions: In conclusion, healthcare leaders highlighted several implementation challenges in relation to AI within and beyond the healthcare system in general and their organisations in particular. The challenges comprised conditions external to the healthcare system, internal capacity for strategic change management, along with transformation of healthcare professions and healthcare practice. The results point to the need to develop implementation strategies across healthcare organisations to address challenges to AI-specific capacity building. Laws and policies are needed to regulate the design and execution of effective AI implementation strategies. There is a need to invest time and resources in implementation processes, with collaboration across healthcare, county councils, and industry partnerships. © The Author(s) 2022.
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| 10. |
- Petersson, Lena, 1968-, et al.
(författare)
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Developing an ethical model for guidance the implementation of AI in healthcare
- 2023
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Ingår i: Nordic Health Promotion Research Conference 2023 Abstracts. - Halmstad.
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Konferensbidrag (refereegranskat)abstract
- Background: Artificial intelligence (AI) is predicted to improve healthcare, increase efficiency, save time andresources. However, research shows an urgent need to develop guidance to ensure that the use of AI in healthcare isethically acceptable.Purpose: To develop an ethical model to support AI implementation in practice.Methods: The study used an explorative and empirically driven qualitative design. Individual interviews wereconducted with 18 healthcare professionals from two emergency departments in Sweden where the county council hasdeveloped an AI application to predict the risk for unexpected mortality within 30 days after visiting an emergencydepartment. A deductive analysis based on ethical theory i.e virtue, deontology and consequentialism, was used.Findings: The developed model shows how the healthcare professionals use ethical reasoning in relation to theimplementation of AI. In relation to virtue ethics, moral considerations in relation to the use of AI were mentioned. Inrelation to deontology, considerations were mentioned on actions performed based on information acquired from thetechnology and adherence to specific duties, roles and responsibilities. In relation to consequentialism, considerationsabout how to provide better resources more rapidly in an equal way and how the technology can be adjusted to eachpatients’ individual needs and preferences in order to support decisions, self-determination, and actions that are in thepatients best interest.Conclusions: Our findings provide an ethical model demonstrating the relevance of virtue, deontology andconsequentialism when AI are to be implemented in practice.
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