Assessing risk of bias in prevalence studies: modification of an existing tool and evidence of interrater agreement.

By D. Hoy, P. Brooks, A. Woolf, F. Blyth, L. March, C. Bain, Peter Baker, E. Smith, Rachelle Buchbinder. Journal of Clinical Epidemiology, 2012

2,242 citations recorded by the source corpus.

Subfields: Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/52cb45bd278ac210f5083cb10955e0753c5145a1

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Citations in the corpus

Antibiotic prescribing in patients with COVID-19: rapid review and meta-analysis (2021, background): “[15], there are no tools that are directly relevant to our research question addressing the prevalence of antibiotic prescribing.”
Global prevalence of sarcopenia and severe sarcopenia: a systematic review and meta‐analysis (2021, background): “20 The tool has 10 questions and evaluates both ex-ternal (Questions 1 to 4) and internal (Questions 5 to 10) validity.”
A systematic review of the reporting of tinnitus prevalence and severity. (2016, neutral): “All three are important sources of bias for prevalence studies (Hoy et al., 2012).”
Measuring inter-rater reliability for nominal data – which coefficients and confidence intervals are appropriate? (2016, methodology): “As bootstrap confidence intervals are not implemented in standard statistical packages, it must be assumed that asymptotic confidence intervals were used, although sample sizes were in some studies as low as 10 to 50 subjects [34, 35].”
The prevalence of symptoms in 24,410 adults infected by the novel coronavirus (SARS-CoV-2; COVID-19): A systematic review and meta-analysis of 148 studies from 9 countries (2020, background): “The risk of bias for included studies was not assessed for two main reasons: firstly, there is no consensus on ideal tool, nor one designed specifically for studies of prevelance [26] and secondly, such assessments would not change the approach to the modelling or presentation of the data, as per ou”
The development of a critical appraisal tool for use in systematic reviews addressing questions of prevalence. (2014, background): “(20)] contain similar questions to our tool but there are important differences.”
The prevalence and phenotypic features of polycystic ovary syndrome: a systematic review and meta-analysis. (2016, methodology): “…external validity, we kept the versions as in the original tool from Munn et al. For the assessment of internal validity, since Q6 was not defined in Munn et al., we instead used the question found in the latter tool (Hoy et al., 2012) to evaluate the mode of data collection used for all subjects.”
Bacterial co-infection and secondary infection in patients with COVID-19: a living rapid review and meta-analysis (2020, methodology): “Although a risk-of-bias tool has been developed for meta-analyses of disease prevalence [14], many aspects of the tool are not directly relevant to our research question.”