The full AUDIT scale showed good or very good accuracy for all outcome measures for males and females, except for alcohol abuse which had sufficient accuracy. In a screening scenario where sensitivity might be prioritized, the optimal cut-point is lower than established AUDIT cut-points of 8+ for men and 6+ for women. Bayes' Theorem to calculate individual probabilities for problem drinking offers an alternative to arbitrary cut-point threshold scores in screening and brief intervention programmes.

We estimated the degree to which language used in the high profile medical/public health/epidemiology literature implied causality using language linking exposures to outcomes and action recommendations; examined disconnects between language and recommendations; identified the most common linking phrases; and estimated how strongly linking phrases imply causality. We searched and screened for 1,170 articles from 18 high-profile journals (65 per journal) published from 2010-2019. Based on written framing and systematic guidance, three reviewers rated the degree of causality implied in abstracts and full text for exposure/outcome linking language and action recommendations. Reviewers rated the causal implication of exposure/outcome linking language as None (no causal implication) in 13.8%, Weak 34.2%, Moderate 33.2%, and Strong 18.7% of abstracts. The implied causality of action recommendations was higher than the implied causality of linking sentences for 44.5% or commensurate for 40.3% of articles. The most common linking word in abstracts was "associate" (45.7%). Reviewers’ ratings of linking word roots were highly heterogeneous; over half of reviewers rated "association" as having at least some causal implication. This research undercuts the assumption that avoiding "causal" words leads to clarity of interpretation in medical research.

This framework challenges researchers to investigate the goals of the potential participants when designing a study's advertising and procedures.

Women are an important public health focus, because they are more likely to experience some social determinants of disease, and they influence family health. Little research has explored the sociodemographic representativeness of women in research studies. We examined the representativeness of female respondents across four sociodemographic factors in UK population surveys and cohort studies. Six UK population-based health surveys (from 2009-2013) and eight Medical Research Council cohort studies (from 1991 to 2014) were included. Percentages of women respondents by age, income/occupation, education status, and ethnicity were compared against contemporary population estimates. Women aged <35 years were under-represented. The oldest women were under-represented in four of nine studies. Within income/occupation, at the highest deprivation level, the range was 4 percent under-representation to 43 percent over-representation; at the lowest level, it was 6 percent under-representation to 21 percent over representation. Of nine studies reporting educational level, four under-represented women without school qualifications, and three under-represented women with degrees. One of five studies over-represented non-white groups and under-represented white women (by 9 percent). Response patterns varied by topic and recruitment and data collection methods. Future research should focus upon the methods used to identify, reach, and engage women to improve representativeness in studies addressing health behaviors.

Background: Avoiding "causal" language with observational study designs is common publication practice, often justified as being a more cautious approach to interpretation. Objectives: We aimed to i) estimate the degree to which causality was implied by both the language linking exposures to outcomes and by action recommendations in the high-profile health literature ii) examine disconnects between language and recommendations, iii) identify which linking phrases were most common, and iv) generate estimates by which these phrases imply causality. Methods: We identified 18 of the most prominent general medical/public health/epidemiology journals, and searched and screened for articles published from 2010 to 2019 that investigated exposure/outcome pairs until we reached 65 non-RCT articles per journal (n=1,170). Two reviewers and an arbitrating reviewer rated the degree to which they believed causality had been implied by the language in abstracts based on written guidance. Reviewers then rated causal implications of linking words in isolation. For comparison, additional review was performed for full texts and for a secondary sample of RCTs. Results: Reviewers rated the causal implication of the sentence and phrase linking the exposure and outcome as None (i.e. makes no causal implication) in 13.8%, Weak in 34.2%, Moderate in 33.2%, and Strong in 18.7% of abstracts. Reviewers identified an action recommendation in 34.2% of abstracts. Of these action recommendations, reviewers rated the causal implications as None in 5.3%, Weak in 19.0%, Moderate in 42.8% and Strong in 33.0% of cases. The implied causality of action recommendations was often higher than the implied causality of linking sentences (44.5%) or commensurate (40.3%), with 15.3% being weaker. The most common linking word root identified in abstracts was "associate" (n=535/1,170; 45.7%) (e.g. "association," "associated," etc). There were only 16 (1.4%) abstracts using "cause" in the linking or modifying phrases. Reviewer ratings for causal implications of word roots were highly heterogeneous, including those commonly considered non-causal. Discussion: We found substantial disconnects between causal implications used to link an exposure to an outcome vs action implications made. This undercuts common assumptions about what words are often considered non-causal and that policing them eliminates causal implications. We recommend that instead of policing words; editors, researchers, and communicators should increase efforts at making research questions, as well as the potential of studies to answer them, more transparent.