David A Drew
Dados Biográficos
| ID | 5484988 |
|---|---|
| NOME | David A Drew |
| PRENOMES | David A |
| SOBRENOME | Drew |
| ASSINATURA | DREW D A |
| AFILIAÇÕES | Harvard University |
| ORCID | 0000-0002-8813-0816 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 8 |
| TOTAL DE CITAÇÕES | 0 |
| TOTAL COMO AUTOR | 8 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2001 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2022 |
| ÍNDICE H | 0 |
Knowledge barriers in a national symptomatic-Covid-19 testing programme
Symptomatic testing programmes are crucial to the COVID-19 pandemic response. We sought to examine United Kingdom (UK) testing rates amongst individuals with test-qualifying symptoms, and factors associated with not testing. We analysed a cohort of untested symptomatic app users (N = 1,237), nested in the Zoe COVID Symptom Study (Zoe, N = 4,394,948); and symptomatic respondents who wanted, but did not have a test (N = 1,956), drawn from a Univers…
Attributes and predictors of long Covid
Religion and spirituality in clinical practice
This study explored whether license-holding mental health professionals exhibit comfort/discomfort in addressing religion and spirituality (RS) in practice. Through snowball sampling, 52 clinicians across different fields were recruited across Southern California. The participants were measured descriptively based on (a) comfort in their ability to integrate clients’ RS in treatment and (b) their comfort discussing clients’ RS strengths and strug…
Real-time tracking of self-reported symptoms to predict potential Covid-19
Risk of Covid-19 among front-line health-care workers and the general community
BACKGROUND: Data for front-line health-care workers and risk of COVID-19 are limited. We sought to assess risk of COVID-19 among front-line health-care workers compared with the general community and the effect of personal protective equipment (PPE) on risk. METHODS: We did a prospective, observational cohort study in the UK and the USA of the general community, including front-line health-care workers, using self-reported data from the COVID Sym…
Markevitch, Igor
Lenya [Lenja], Lotte
Weill, Kurt
Sem obras proeminentes nesta página.
Markevitch, Igor
Lenya [Lenja], Lotte
Weill, Kurt
Real-time tracking of self-reported symptoms to predict potential Covid-19
Risk of Covid-19 among front-line health-care workers and the general community
BACKGROUND: Data for front-line health-care workers and risk of COVID-19 are limited. We sought to assess risk of COVID-19 among front-line health-care workers compared with the general community and the effect of personal protective equipment (PPE) on risk. METHODS: We did a prospective, observational cohort study in the UK and the USA of the general community, including front-line health-care workers, using self-reported data from the COVID Sym…
Attributes and predictors of long Covid
Religion and spirituality in clinical practice
This study explored whether license-holding mental health professionals exhibit comfort/discomfort in addressing religion and spirituality (RS) in practice. Through snowball sampling, 52 clinicians across different fields were recruited across Southern California. The participants were measured descriptively based on (a) comfort in their ability to integrate clients’ RS in treatment and (b) their comfort discussing clients’ RS strengths and strug…
Knowledge barriers in a national symptomatic-Covid-19 testing programme
Symptomatic testing programmes are crucial to the COVID-19 pandemic response. We sought to examine United Kingdom (UK) testing rates amongst individuals with test-qualifying symptoms, and factors associated with not testing. We analysed a cohort of untested symptomatic app users (N = 1,237), nested in the Zoe COVID Symptom Study (Zoe, N = 4,394,948); and symptomatic respondents who wanted, but did not have a test (N = 1,956), drawn from a Univers…
Medicine (5 obras) · Disease (4 obras) · Coronavirus disease 2019 (COVID-19) (3 obras) · Internal Medicine (3 obras) · Pandemic (3 obras) · 2019-20 coronavirus outbreak (2 obras) · Betacoronavirus (2 obras) · Cohort (2 obras) · Computer Science (2 obras) · COVID-19 and Mental Health (2 obras)