Alexandra Löwe

Zusammenfassung: Der Übergang in das Studium ist eine kritische Lebensphase, die durch die Ablösung vom Elternhaus, die Gestaltung des beruflichen Werdegangs und den Aufbau eines unabhängigen Lebens geprägt ist. Globale Krisen (Klima, Pandemie, Kriege) sind weitere potenzielle Stressfaktoren, die sich negativ auf die Gesundheit (GZ) auswirken können. Das Gesundheitsverhalten (GV) und die Gesundheitskompetenz (GK) sind wichtige Ressourcen zur Erhaltung der Gesundheit und zur Bewältigung des Studiums. Ziel der Studie ist es, 1.) den aktuellen GZ, das GV und die GK von Studierenden zu erfassen sowie 2.) Zusammenhänge von Geschlecht, studienbezogenen Faktoren, GV und GZ bzw. GK zu identifizieren.An einer deutschen Hochschule (FH) wurde eine Querschnittsstudie, orientiert an der STROBE-Checkliste, durchgeführt. Die Daten wurden vom Mai bis November 2022 mittels eines Online-Fragebogens erhoben. Es wurden Daten zum GZ (bestehend aus Lebenszufriedenheit, Schlafqualität und wahrgenommener Stress), zum GV (bestehend körperlicher Aktivität, Ernährungs- und Rauchverhalten, Alkohol- und Suchtmittelkonsum) und der GK erfasst. Die Auswertung inkludierte deskriptive Statistiken sowie multiple lineare Regressionsanalysen zur Bewertung der Zusammenhänge.Es wurden N=550 Teilnehmer (♀: 74%) einbezogen. Der GZ wurde als gut bis sehr gut empfunden (81,3%), die Lebenszufriedenheit von 13% als hoch eingestuft, der Stress als hoch (62,6%) und die Schlafqualität (58,1%) als gut wahrgenommen. Das GV offenbarte ein ausreichend körperliches Aktivitätsniveau (57,4%), ein gutes Ernährungs- (58,6%) und Alkoholkonsumverhalten (70,4%). Die GK zeigte sich bei 42,7% als ausreichend. Ein hoher GZ (p<0,004, korr. R²: ,254; f²: 0,34) war mit männlichem Geschlecht (β=0,124, p=0,031), höherer Lebenszufriedenheit (β=0,050, p<0,001), besserer Schlafqualität (β=–0,044, p<0,001) und gesunder Ernährung (β=0,016, p=0,005) assoziiert. Die GK (p=0,022, korr. R²: 0,076; f²: 0,08) war mit dem Masterabschluss (β=0,505, p=0,049), besserer Schlafqualität (β=–0,158, p=0,004), gesunder Ernährung (β=0,059, p=0,031), geringerem Alkoholkonsum (β=–0,209, p=0,017) und höherer Lebenszufriedenheit (β=0,067, p=0,022) assoziiert.Die Ergebnisse belegen einen guten Gesundheitszustand, offenbaren zugleich gezielten Handlungsbedarf beim Gesundheitsverhalten und der Gesundheitskompetenz. Hochschulen sollten daher bei der Interventionsplanung den Fokus nicht ausschließlich auf den Gesundheitszustand legen.

Background: The rapid proliferation of medical apps has transformed the health care landscape by giving patients and health care providers unprecedented access to personalized health information and services. However, concerns regarding the effectiveness and safety of medical apps have raised questions regarding the efficacy of randomized controlled trials (RCTs) in the evaluation of such apps and as a requirement for their regulation as mobile medical devices. Objective: This study aims to address this issue by investigating alternative methods, apart from RCTs, for evaluating and regulating medical apps. Methods: Using a qualitative approach, a focus group study with 46 international and multidisciplinary public health experts was conducted at the 17th World Congress on Public Health in May 2023 in Rome, Italy. The group was split into 3 subgroups to gather in-depth insights into alternative approaches for evaluating and regulating medical apps. We conducted a policy analysis on the current regulation of medical apps as mobile medical devices for the 4 most represented countries in the workshop: Italy, Germany, Canada, and Australia. We developed a logic model that combines the evaluation and regulation domains on the basis of these findings. Results: The focus group discussions explored the strengths and limitations of the current evaluation and regulation methods and identified potential alternatives that could enhance the quality and safety of medical apps. Although RCTs were only explicitly mentioned in the German regulatory system as one of many options, an analysis of chosen evaluation methods for German apps on prescription pointed toward a “scientific reflex” where RCTs are always the chosen evaluation method. However, this method has substantial limitations when used to evaluate digital interventions such as medical apps. Comparable results were observed during the focus group discussions, where participants expressed similar experiences with their own evaluation approaches. In addition, the participants highlighted numerous alternatives to RCTs. These alternatives can be used at different points during the life cycle of a digital intervention to assess its efficacy and potential harm to users. Conclusions: It is crucial to recognize that unlike analog tools, digital interventions constantly evolve, posing challenges to inflexible evaluation methods such as RCTs. Potential risks include high dropout rates, decreased adherence, and nonsignificant results. However, existing regulations do not explicitly advocate for other evaluation methodologies. Our research highlighted the necessity of overcoming the gap between regulatory demands to demonstrate safety and efficacy of medical apps and evolving scientific practices, ensuring that digital health innovation is evaluated and regulated in a way that considers the unique characteristics of mobile medical devices.

Background: Artificial intelligence (AI) is an umbrella term for various algorithms and rapidly emerging technologies with huge potential for workplace health promotion and prevention (WHPP). WHPP interventions aim to improve people’s health and well-being through behavioral and organizational measures or by minimizing the burden of workplace-related diseases and associated risk factors. While AI has been the focus of research in other health-related fields, such as public health or biomedicine, the transition of AI into WHPP research has yet to be systematically investigated. Objective: The systematic scoping review aims to comprehensively assess an overview of the current use of AI in WHPP. The results will be then used to point to future research directions. The following research questions were derived: (1) What are the study characteristics of studies on AI algorithms and technologies in the context of WHPP? (2) What specific WHPP fields (prevention, behavioral, and organizational approaches) were addressed by the AI algorithms and technologies? (3) What kind of interventions lead to which outcomes? Methods: A systematic scoping literature review (PRISMA-ScR [Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews]) was conducted in the 3 academic databases PubMed, Institute of Electrical and Electronics Engineers, and Association for Computing Machinery in July 2023, searching for papers published between January 2000 and December 2023. Studies needed to be (1) peer-reviewed, (2) written in English, and (3) focused on any AI-based algorithm or technology that (4) were conducted in the context of WHPP or (5) an associated field. Information on study design, AI algorithms and technologies, WHPP fields, and the patient or population, intervention, comparison, and outcomes framework were extracted blindly with Rayyan and summarized. Results: A total of 10 studies were included. Risk prevention and modeling were the most identified WHPP fields (n=6), followed by behavioral health promotion (n=4) and organizational health promotion (n=1). Further, 4 studies focused on mental health. Most AI algorithms were machine learning-based, and 3 studies used combined deep learning algorithms. AI algorithms and technologies were primarily implemented in smartphone apps (eg, in the form of a chatbot) or used the smartphone as a data source (eg, Global Positioning System). Behavioral approaches ranged from 8 to 12 weeks and were compared to control groups. Additionally, 3 studies evaluated the robustness and accuracy of an AI model or framework. Conclusions: Although AI has caught increasing attention in health-related research, the review reveals that AI in WHPP is marginally investigated. Our results indicate that AI is promising for individualization and risk prediction in WHPP, but current research does not cover the scope of WHPP. Beyond that, future research will profit from an extended range of research in all fields of WHPP, longitudinal data, and reporting guidelines. Trial Registration: OSF Registries osf.io/bfswp; https://osf.io/bfswp

BACKGROUND The rapid proliferation of medical apps has transformed the health care landscape by giving patients and health care providers unprecedented access to personalized health information and services. However, concerns regarding the effectiveness and safety of medical apps have raised questions regarding the efficacy of randomized controlled trials (RCTs) in the evaluation of such apps and as a requirement for their regulation as mobile medical devices. OBJECTIVE This study aims to address this issue by investigating alternative methods, apart from RCTs, for evaluating and regulating medical apps. METHODS Using a qualitative approach, a focus group study with 46 international and multidisciplinary public health experts was conducted at the 17th World Congress on Public Health in May 2023 in Rome, Italy. The group was split into 3 subgroups to gather in-depth insights into alternative approaches for evaluating and regulating medical apps. We conducted a policy analysis on the current regulation of medical apps as mobile medical devices for the 4 most represented countries in the workshop: Italy, Germany, Canada, and Australia. We developed a logic model that combines the evaluation and regulation domains on the basis of these findings. RESULTS The focus group discussions explored the strengths and limitations of the current evaluation and regulation methods and identified potential alternatives that could enhance the quality and safety of medical apps. Although RCTs were only explicitly mentioned in the German regulatory system as one of many options, an analysis of chosen evaluation methods for German apps on prescription pointed toward a “scientific reflex” where RCTs are always the chosen evaluation method. However, this method has substantial limitations when used to evaluate digital interventions such as medical apps. Comparable results were observed during the focus group discussions, where participants expressed similar experiences with their own evaluation approaches. In addition, the participants highlighted numerous alternatives to RCTs. These alternatives can be used at different points during the life cycle of a digital intervention to assess its efficacy and potential harm to users. CONCLUSIONS It is crucial to recognize that unlike analog tools, digital interventions constantly evolve, posing challenges to inflexible evaluation methods such as RCTs. Potential risks include high dropout rates, decreased adherence, and nonsignificant results. However, existing regulations do not explicitly advocate for other evaluation methodologies. Our research highlighted the necessity of overcoming the gap between regulatory demands to demonstrate safety and efficacy of medical apps and evolving scientific practices, ensuring that digital health innovation is evaluated and regulated in a way that considers the unique characteristics of mobile medical devices.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Artificial intelligence (AI) is an umbrella term for various algorithms and rapidly emerging technologies with huge potential for workplace health promotion and prevention (WHPP). WHPP interventions aim to improve people’s health and well-being through behavioral and organizational measures or by minimizing the burden of workplace-related diseases and associated risk factors. While AI has been the focus of research in other health-related fields, such as public health or biomedicine, the transition of AI into WHPP research has yet to be systematically investigated. Objective: The systematic scoping review aims to comprehensively assess an overview of the current use of AI in WHPP. The results will be then used to point to future research directions. The following research questions were derived: (1) What are the study characteristics of studies on AI algorithms and technologies in the context of WHPP? (2) What specific WHPP fields (prevention, behavioral, and organizational approaches) were addressed by the AI algorithms and technologies? (3) What kind of interventions lead to which outcomes? Methods: A systematic scoping literature review (PRISMA-ScR [Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews]) was conducted in the 3 academic databases PubMed, Institute of Electrical and Electronics Engineers, and Association for Computing Machinery in July 2023, searching for papers published between January 2000 and December 2023. Studies needed to be (1) peer-reviewed, (2) written in English, and (3) focused on any AI-based algorithm or technology that (4) were conducted in the context of WHPP or (5) an associated field. Information on study design, AI algorithms and technologies, WHPP fields, and the patient or population, intervention, comparison, and outcomes framework were extracted blindly with Rayyan and summarized. Results: A total of 10 studies were included. Risk prevention and modeling were the most identified WHPP fields (n=6), followed by behavioral health promotion (n=4) and organizational health promotion (n=1). Further, 4 studies focused on mental health. Most AI algorithms were machine learning-based, and 3 studies used combined deep learning algorithms. AI algorithms and technologies were primarily implemented in smartphone apps (eg, in the form of a chatbot) or used the smartphone as a data source (eg, Global Positioning System). Behavioral approaches ranged from 8 to 12 weeks and were compared to control groups. Additionally, 3 studies evaluated the robustness and accuracy of an AI model or framework. Conclusions: Although AI has caught increasing attention in health-related research, the review reveals that AI in WHPP is marginally investigated. Our results indicate that AI is promising for individualization and risk prediction in WHPP, but current research does not cover the scope of WHPP. Beyond that, future research will profit from an extended range of research in all fields of WHPP, longitudinal data, and reporting guidelines. Trial Registration: OSF Registries osf.io/hsu2w; https://osf.io/hsu2w/

Background and Objective: University students (US) face challenging times characterized by home detachment, identity exploration, academic demands, and additional stressors due to the current global situation that can negatively impact health. Health behaviors (HB) and health literacy (HL) are...

In der öffentlichen Wahrnehmung ist das Studieren in Deutschland seit der Bologna-Reform zunehmend durch ein hohes Stresslevel gekennzeichnet. Trägt die Umstellung auf die zweizyklischen Studienmodelle mit ihren Bachelor- und Masterabschlüssen Schuld am Stress im Studium? Untersuchungen haben gezeigt, dass diese Annahme nicht uneingeschränkt gilt und dass der gesamte Sachverhalt in hohem Maße ambivalent ist. Das macht dieses Forschungsfeld interdisziplinär vor allem von zwei Seiten anschlussfähig: Da ist einerseits die psychologische und pädagogische/bildungswissenschaftliche Fragestellung, wie Stress und Studienerfolg sich wechselseitig beeinflussen und wie diese Interdependenz aufzulösen ist oder zumindest gelockert werden kann. Anderseits ist der Studienerfolg – direkt oder indirekt – eine maßgebliche Größe für das Hochschulmarketing und spielt in der Folge auch eine wichtige Rolle in Hochschulrankings, in der Alumni-Arbeit, dem Fundraising und vielem mehr. Der vorliegende Band hat zum Ziel, verschiedene aktuelle Forschungen zum Thema Stress im Studium zusammenzuführen. Die Veröffentlichung stellt auf diese Weise den gegenwärtigen Forschungsstand anhand mehrerer Fallstudien dar. Es soll aufgezeigt werden, an welchen Stellen und inwieweit sich das Thema weiter nachhaltig bearbeiten lässt. Der Band will so einen Impuls oder eine Starthilfe geben für eine künftig verstärkte Beschäftigung mit dem Forschungsfeld als solchem und für eine breite Wahrnehmung des Themas in Wissenschaft und Öffentlichkeit. Die Herausgeber Prof. Dr. Matthias Johannes Bauer, volontierter Journalist, Germanist und Wirtschaftswissenschaftler, leitet den Masterstudiengang Kommunikationsmanagement an der IST-Hochschule für Management in Düsseldorf. Prof. Dr. Thomas Seppelfricke, Diplom-Psychologe, leitet den Bachelor- und Masterstudiengang Wirtschaftspsychologie an der Hochschule Fresenius in Düsseldorf.