The spread of COVID-19 has changed many aspects of people’s social lives, individual’s behaviors, and healthcare procedures. Furthermore, it has changed many physiological responses, and consequently, it is expected that many medical studies are influenced by multiple hidden biases posed by Covid-19 pandemic, mediated directly or indirectly by face mask wearing or by Covid-19 itself. For instance, face mask wearing has been reported to produce a drastic bias in studies of endocrinology, ophthalmology-particularly dry eye and ocular diseases-, sleep studies, cognitive biases (such as emotion-recognition accuracy studies, etc.), and sex-bias differences just to mention a few. It can be estimated that many of such biases have been left undiagnosed in other disciplines of medicine.
This Research Topic calls for papers reporting any type of unreported biases posed by Covid-19 pandemic and/or face mask wearing. It is expected that submitted manuscripts will help better and unbiased interpretation of clinical findings, methodological developments, registered clinical trials, cohort studies and comparative studies (pre and post Covid-19 pandemic).
1. Questionnaire studies: A broad range including cross-sectional to explorative longitudinal questionnaire studies linking incidence/prevalence/severity of diseases to Covid-19 and/or face mask wearing, or altered mental situation influenced by Covid-19 pandemic. For instance, Covid-19 infection directly reduces salivation through inducing xerostomia in diabetic patients, while some researchers attribute this situation only to diabetes duration/and or severity, ignoring role of face mask induced hyposalivation and direct damage of Covid-19 virus to salivary glands, thereby producing an explicit bias. 2. Brain imaging techniques: Studies linking/exploring medical image analysis from the perspective of Covid-19 pandemic. 3. COVID-19 pandemic and artificial intelligence and deep learning COVID-19 detection bias. 4. Cognitive bias, health anxiety and attentional bias, gender bias, collider bias, publication bias, etc. 5. Statistical biases induced by Covid-19 and/or face mask wearing (such as ascertainment bias, selection bias, surveillance bias, sampling bias minimization in disease frequency estimates etc.). 6. Prognostic/diagnostic/therapeutic and prophylactic biases posed by Covid-19 and/or face mask wearing.
The spread of COVID-19 has changed many aspects of people’s social lives, individual’s behaviors, and healthcare procedures. Furthermore, it has changed many physiological responses, and consequently, it is expected that many medical studies are influenced by multiple hidden biases posed by Covid-19 pandemic, mediated directly or indirectly by face mask wearing or by Covid-19 itself. For instance, face mask wearing has been reported to produce a drastic bias in studies of endocrinology, ophthalmology-particularly dry eye and ocular diseases-, sleep studies, cognitive biases (such as emotion-recognition accuracy studies, etc.), and sex-bias differences just to mention a few. It can be estimated that many of such biases have been left undiagnosed in other disciplines of medicine.
This Research Topic calls for papers reporting any type of unreported biases posed by Covid-19 pandemic and/or face mask wearing. It is expected that submitted manuscripts will help better and unbiased interpretation of clinical findings, methodological developments, registered clinical trials, cohort studies and comparative studies (pre and post Covid-19 pandemic).
1. Questionnaire studies: A broad range including cross-sectional to explorative longitudinal questionnaire studies linking incidence/prevalence/severity of diseases to Covid-19 and/or face mask wearing, or altered mental situation influenced by Covid-19 pandemic. For instance, Covid-19 infection directly reduces salivation through inducing xerostomia in diabetic patients, while some researchers attribute this situation only to diabetes duration/and or severity, ignoring role of face mask induced hyposalivation and direct damage of Covid-19 virus to salivary glands, thereby producing an explicit bias. 2. Brain imaging techniques: Studies linking/exploring medical image analysis from the perspective of Covid-19 pandemic. 3. COVID-19 pandemic and artificial intelligence and deep learning COVID-19 detection bias. 4. Cognitive bias, health anxiety and attentional bias, gender bias, collider bias, publication bias, etc. 5. Statistical biases induced by Covid-19 and/or face mask wearing (such as ascertainment bias, selection bias, surveillance bias, sampling bias minimization in disease frequency estimates etc.). 6. Prognostic/diagnostic/therapeutic and prophylactic biases posed by Covid-19 and/or face mask wearing.