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1.
Humanities & Social Sciences Communications ; 9(1), 2022.
Article in English | ProQuest Central | ID: covidwho-1758453

ABSTRACT

In the ongoing COVID-19 pandemic, non-pharmaceutical protective measures taken by individuals remain pivotal. This study aims to explore what motivates individuals to engage in such measures. Based on existing empirical findings as well as prominent behavioural theories, a partial least squares structural equation model (PLS-SEM) of predictors for pandemic protective behaviour was estimated using a representative German sample (n = 437). The study was preregistered at OSF. The model explains 69% of the variance for behavioural intention, which is strongly correlated with behaviour (ρ = 0.84). The most influential predictor for protective behaviour is its perceived efficacy, followed by normative beliefs and perceptions about costs for protective behaviour. Distrusting beliefs in science and scientists negatively predicted response perceptions and were also strongly and negatively correlated with behaviour. Knowledge about COVID-19 was weakly linked with perceived response efficacy, as well as with behaviour. These findings suggest that communication strategies surrounding COVID-19 should emphasise the efficacy of responses and foster a sense of responsibility.

2.
JMIR Mhealth Uhealth ; 10(1): e27095, 2022 01 18.
Article in English | MEDLINE | ID: covidwho-1662496

ABSTRACT

BACKGROUND: Mobile health (mHealth) care apps are a promising technology to monitor and control health individually and cost-effectively with a technology that is widely used, affordable, and ubiquitous in many people's lives. Download statistics show that lifestyle apps are widely used by young and healthy users to improve fitness, nutrition, and more. While this is an important aspect for the prevention of future chronic diseases, the burdened health care systems worldwide may directly profit from the use of therapy apps by those patients already in need of medical treatment and monitoring. OBJECTIVE: We aimed to compare the factors influencing the acceptance of lifestyle and therapy apps to better understand what drives and hinders the use of mHealth apps. METHODS: We applied the established unified theory of acceptance and use of technology 2 (UTAUT2) technology acceptance model to evaluate mHealth apps via an online questionnaire with 707 German participants. Moreover, trust and privacy concerns were added to the model and, in a between-subject study design, the influence of these predictors on behavioral intention to use apps was compared between lifestyle and therapy apps. RESULTS: The results show that the model only weakly predicted the intention to use mHealth apps (R2=0.019). Only hedonic motivation was a significant predictor of behavioral intentions regarding both app types, as determined by path coefficients of the model (lifestyle: 0.196, P=.004; therapy: 0.344, P<.001). Habit influenced the behavioral intention to use lifestyle apps (0.272, P<.001), while social influence (0.185, P<.001) and trust (0.273, P<.001) predicted the intention to use therapy apps. A further exploratory correlation analysis of the relationship between user factors on behavioral intention was calculated. Health app familiarity showed the strongest correlation to the intention to use (r=0.469, P<.001), stressing the importance of experience. Also, age (r=-0.15, P=.004), gender (r=-0.075, P=.048), education level (r=0.088, P=.02), app familiarity (r=0.142, P=.007), digital health literacy (r=0.215, P<.001), privacy disposition (r=-0.194, P>.001), and the propensity to trust apps (r=0.191, P>.001) correlated weakly with behavioral intention to use mHealth apps. CONCLUSIONS: The results indicate that, rather than by utilitarian factors like usefulness, mHealth app acceptance is influenced by emotional factors like hedonic motivation and partly by habit, social influence, and trust. Overall, the findings give evidence that for the health care context, new and extended acceptance models need to be developed with an integration of user diversity, especially individuals' prior experience with apps and mHealth.


Subject(s)
Mobile Applications , Telemedicine , Humans , Life Style , Motivation , Surveys and Questionnaires
3.
Lancet Reg Health Eur ; 13: 100294, 2022 Feb.
Article in English | MEDLINE | ID: covidwho-1587066

ABSTRACT

In the summer of 2021, European governments removed most NPIs after experiencing prolonged second and third waves of the COVID-19 pandemic. Most countries failed to achieve immunization rates high enough to avoid resurgence of the virus. Public health strategies for autumn and winter 2021 have ranged from countries aiming at low incidence by re-introducing NPIs to accepting high incidence levels. However, such high incidence strategies almost certainly lead to the very consequences that they seek to avoid: restrictions that harm people and economies. At high incidence, the important pandemic containment measure 'test-trace-isolate-support' becomes inefficient. At that point, the spread of SARS-CoV-2 and its numerous harmful consequences can likely only be controlled through restrictions. We argue that all European countries need to pursue a low incidence strategy in a coordinated manner. Such an endeavour can only be successful if it is built on open communication and trust.

4.
Lancet Reg Health Eur ; 8: 100185, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-1331031

ABSTRACT

How will the coronavirus disease 2019 (COVID-19) pandemic develop in the coming months and years? Based on an expert survey, we examine key aspects that are likely to influence the COVID-19 pandemic in Europe. The challenges and developments will strongly depend on the progress of national and global vaccination programs, the emergence and spread of variants of concern (VOCs), and public responses to non-pharmaceutical interventions (NPIs). In the short term, many people remain unvaccinated, VOCs continue to emerge and spread, and mobility and population mixing are expected to increase. Therefore, lifting restrictions too much and too early risk another damaging wave. This challenge remains despite the reduced opportunities for transmission given vaccination progress and reduced indoor mixing in summer 2021. In autumn 2021, increased indoor activity might accelerate the spread again, whilst a necessary reintroduction of NPIs might be too slow. The incidence may strongly rise again, possibly filling intensive care units, if vaccination levels are not high enough. A moderate, adaptive level of NPIs will thus remain necessary. These epidemiological aspects combined with economic, social, and health-related consequences provide a more holistic perspective on the future of the COVID-19 pandemic.

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