The aetiology of bacterial vaginosis (BV), a biofilm-associated vaginal infection, remains unknown. Epidemiologic data suggest that it is sexually transmitted. BV is characterised by loss of lactic acid-producing lactobacilli and an increase in facultative and strict anaerobic bacteria. Gardnerella spp are present in 95%–100% of cases; Gardnerella vaginalis has been found to be more virulent than other BV-associated bacteria (BVAB) in vitro. However, G. vaginalis is found in women with normal vaginal microbiota and colonisation is not sufficient for BV development. We hypothesise that Gardnerella spp initiate BV biofilm formation, but incident BV (iBV) requires incorporation of other key BVAB (ie, Prevotella bivia, Fannyhessea vaginae) into the biofilm that alter the transcriptome of the polymicrobial consortium. This study will investigate the sequence of microbiologic events preceding iBV.

This study will enrol 150 women aged 18–45 years with normal vaginal microbiota and no sexually transmitted infections at a sexual health research clinic in Birmingham, Alabama. Women will self-collect twice daily vaginal specimens up to 60 days. A combination of 16S rRNA gene sequencing, qPCR for Gardnerella spp, P. bivia and F. vaginae, and broad range 16S rRNA gene qPCR will be performed on twice daily vaginal specimens from women with iBV (Nugent score 7–10 on at least 2 consecutive days) and controls (with comparable age, race, contraceptive method and menstrual cycle days) maintaining normal vaginal microbiota to investigate changes in the vaginal microbiota over time for women with iBV. Participants will complete daily diaries on multiple factors including sexual activity.

This protocol is approved by the University of Alabama at Birmingham Institutional Review Board (IRB-300004547) and written informed consent will be obtained from all participants. Findings will be presented at scientific conferences and published in peer-reviewed journals as well as disseminated to providers and patients in communities of interest.

Globally, incidence, prevalence and mortality rates of skin cancers are escalating. Earlier detection by well-trained primary care providers in techniques such as dermoscopy could reduce unnecessary referrals and improve longer term outcomes. A review of reviews is planned to compare and contrast the conduct, quality, findings and conclusions of multiple systematic and scoping reviews addressing the effectiveness of training primary care providers in dermoscopy, which will provide a critique and synthesis of the current body of review evidence.

Four databases (Cochrane, CINAHL, EMBASE and MEDLINE Complete) will be comprehensively searched from database inception to identify published, peer-reviewed English-language articles describing scoping and systematic reviews of the effectiveness of training primary care providers in the use of dermoscopy to detect skin cancers. Two researchers will independently conduct the searches and screen the results for potentially eligible studies using ‘Research Screener’ (a semi-automated machine learning tool). Backwards and forwards citation tracing will be conducted to supplement the search. A narrative summary of included reviews will be conducted. Study characteristics, for example, population; type of educational programme, including content, delivery method, duration and assessment; and outcomes for dermoscopy will be extracted into a standardised table. Data extraction will be checked by the second reviewer. Methodological quality will be evaluated by two reviewers independently using the Critical Appraisal Tool for Health Promotion and Prevention Reviews. Results of the assessments will be considered by the two reviewers and any discrepancies will be resolved by team consensus.

Ethics approval is not required to conduct the planned systematic review of peer-reviewed, published articles because the research does not involve human participants. Findings will be published in a peer-reviewed journal, presented at leading public health, cancer and primary care conferences, and disseminated via website postings and social media channels.

CRD42023396276.

Drug–drug interactions (DDIs) are common and can result in patient harm. Electronic health records warn clinicians about DDIs via alerts, but the clinical decision support they provide is inadequate. Little is known about clinicians’ real-world DDI decision-making process to inform more effective alerts.

Apply cognitive task analysis techniques to determine informational cues used by clinicians to manage DDIs and identify opportunities to improve alerts.

Clinicians submitted incident forms involving DDIs, which were eligible for inclusion if there was potential for serious patient harm. For selected incidents, we met with the clinician for a 60 min interview. Each interview transcript was analysed to identify decision requirements and delineate clinicians’ decision-making process. We then performed an inductive, qualitative analysis across incidents.

Inpatient and outpatient care at a major, tertiary Veterans Affairs medical centre.

Physicians, pharmacists and nurse practitioners.

Themes to identify informational cues that clinicians used to manage DDIs.

We conducted qualitative analyses of 20 incidents. Data informed a descriptive model of clinicians’ decision-making process, consisting of four main steps: (1) detect a potential DDI; (2) DDI problem-solving, sensemaking and planning; (3) prescribing decision and (4) resolving actions. Within steps (1) and (2), we identified 19 information cues that clinicians used to manage DDIs for patients. These cues informed their subsequent decisions in steps (3) and (4). Our findings inform DDI alert recommendations to improve clinicians’ decision-making efficiency, confidence and effectiveness.

Our study provides three key contributions. Our study is the first to present an illustrative model of clinicians’ real-world decision making for managing DDIs. Second, our findings add to scientific knowledge by identifying 19 cognitive cues that clinicians rely on for DDI management in clinical practice. Third, our results provide essential, foundational knowledge to inform more robust DDI clinical decision support in the future.