Optimising referral letters for the dental practitioner.

Referrals are defined as 'a process in which a health worker at one level of the health system, having insufficient resources (drugs, equipment, skills) to manage a clinical condition, seeks the help of a better or differently resourced facility at the same or higher level to assist in patient management'. Within the UK, the NHS dental service is divided into nationally defined levels of care, which provide treatment based upon complexity and patient modifying factors. Having a sound knowledge of these levels will help general dental practitioners (GDPs) make appropriate and efficient onward referrals to the correct service.This article aims to outline the key information required for all strong GDP referrals, as well as highlighting information that may be specific to each speciality. This is with the hope of creating a key list for GDPs to use on clinic when writing referrals to reduce the incidence of missed information and subsequent rejection. The article also aims to outline the levels of NHS dental care and what factors and treatments are suitable for each to aid GDPs during their referral decision-making process.

Gender Discrimination and Mental Health Among Health Care Workers: Findings from a Mixed Methods Study.

Background: Gender discrimination among healthcare workers (HCWs) negatively impacts their mental health and career development; however, few studies have explored how experiences of gender discrimination change during times of health system strain. Methods: This survey-based study assesses the associations between gender discrimination and four stress-related mental health outcomes (posttraumatic stress, depression, anxiety, and burnout), as well as the qualitative experiences of gender discrimination in healthcare during the COVID-19 pandemic. Results: Among women, increased gender discrimination was associated with heightened symptoms of posttraumatic stress, depression, anxiety, and burnout after adjusting for demographics and pandemic-related stressors; however, among men, increased gender discrimination was only associated with heightened symptoms of depression. Using thematic analysis, we identified five themes that describe experiences of gender discrimination faced by women in healthcare, including differential valuing of work and contributions, gendered roles and assumptions about roles, maternal discrimination, objectification, and "old boys club." We also identified two themes describing how men perceived gender discrimination, including instances of symbolic discrimination and woman provider preference. Conclusion: These findings suggest that experiences of gender discrimination persist during times of health system strain and negatively impact women HCWs' mental health.

Gender discrimination among women healthcare workers during the COVID-19 pandemic: Findings from a mixed methods study.

BACKGROUND: Gender discrimination among women healthcare workers (HCWs) negatively impacts job satisfaction, mental health, and career development; however, few studies have explored how experiences of gender discrimination change during times of health system strain. Thus, we conducted a survey study to characterize gender discrimination during a time of significant health system strain, i.e., the COVID-19 pandemic. METHODS: We used a convenience sampling approach by inviting department chairs of academic medical centers in the United States to forward our online survey to their staff in January 2021. The survey included one item assessing frequency of gender discrimination, and an open-ended question asking respondents to detail experiences of discrimination. The survey also included questions about social and work stressors, such as needing additional childcare support. We used ordinal logistic regression models to identify predictors of gender discrimination, and grounded theory to characterize themes that emerged from open-ended responses. RESULTS: Among our sample of 716 women (mean age = 37.63 years, SD = 10.97), 521 (72.80%) were White, 102 (14.20%) Asian, 69 (9.60%) Black, 53 (7.4%) Latina, and 11 (1.50%) identified as another race. In an adjusted model that included demographic characteristics and social and work stressors as covariates, significant predictors of higher gender discrimination included younger age (OR = 0.98, 95%CI = 0.96, 0.99); greater support needs (OR = 1.26, 95%CI = 1.09,1.47); lower team cohesion (OR = 0.94, 95%CI = 0.91, 0.97); greater racial discrimination (OR = 1.07, 95%CI = 1.05,1.09); identifying as a physician (OR = 6.59, 95%CI = 3.95, 11.01), physician-in-training (i.e., residents and fellows; OR = 3.85, 95%CI = 2.27,6.52), or non-clinical worker (e.g., administrative assistants; OR = 3.08, 95%CI = 1.60,5.90), compared with nurses; and reporting the need for a lot more childcare support (OR = 1.84, 95%CI = 1.15, 2.97), compared with reporting no childcare support need. In their open-ended responses, women HCWs described seven themes: 1) belittlement by colleagues, 2) gendered workload distributions, 3) unequal opportunities for professional advancement, 4) expectations for communication, 5) objectification, 6) expectations of motherhood, and 7) mistreatment by patients. CONCLUSIONS: Our study underscores the severity of gender discrimination among women HCWs. Hospital systems should prioritize gender equity programs that improve workplace climate during and outside of times of health system strain.

Psychosocial family-level mediators in the intergenerational transmission of trauma: Protocol for a systematic review and meta-analysis.

INTRODUCTION: Family-level psychosocial factors appear to play a critical role in mediating the intergenerational transmission of trauma; however, no review article has quantitatively synthesized causal mechanisms across a diversity of trauma types. This study aims to systematically consolidate the epidemiological research on family-level psychosocial mediators and moderators to ultimately produce causal diagram(s) of the intergenerational transmission of trauma. METHODS: We will identify epidemiological peer-reviewed publications, dissertations, and conference abstracts that measure the impact of at least one psychosocial family-level factor mediating or moderating the relationship between parental trauma exposure and a child mental health outcome. English, French, Kinyarwanda, and Spanish articles will be eligible. We will search MEDLINE, PsycINFO, PTSDpubs, Scopus, and ProQuest Dissertations and Theses and will conduct forward citation chaining of included documents. Two reviewers will perform screening independently. We will extract reported mediators, moderators, and relevant study characteristics for included studies. Findings will be presented using narrative syntheses, descriptive analyses, mediation meta-analyses, moderating meta-analyses, and causal diagram(s), where possible. We will perform a risk of bias assessment and will assess for publication bias. DISCUSSION: The development of evidence-based causal diagram(s) would provide more detailed understanding of the paths by which the psychological impacts of trauma can be transmitted intergenerationally at the family-level. This review could provide evidence to better support interventions that interrupt the cycle of intergenerational trauma. TRIAL REGISTRATION: Systematic review registration: PROSPERO registration ID #CRD42021251053.

"They Wanted to Talk to a 'Real Doctor'": Predictors, Perpetrators, and Experiences of Racial and Ethnic Discrimination Among Healthcare Workers.

BACKGROUND: Racial and ethnic diversity of healthcare workers have benefits on team functioning and patient care. However, a significant barrier to retaining diverse providers is discrimination. OBJECTIVE: To assess the predictors, perpetrators, and narratives of racial discrimination among healthcare workers. DESIGN: Survey study. PARTICIPANTS: Healthcare workers employed at academic hospitals. MAIN MEASURES: We assessed prevalence and perpetrators of racial and ethnic discrimination using the General Ethnic Discrimination Scale. We included an open-ended question asking respondents to recount experiences of discrimination and analyzed responses using grounded theory. KEY RESULTS: Of the 997 participants, 12.2% were females from backgrounds underrepresented in medicine (URM), 4.0% URM males, 10.1% Asian females, 4.7% Asian males, 49.1% non-Hispanic White females, and 19.8% non-Hispanic White males. Among healthcare workers of color, 85.2% reported discrimination. Over half of URM females (51.4%), URM males (52.6%), and Asian females (62.5%) reported discrimination by patients. About 20-25% of URM females, URM males, and Asian females reported discrimination by teachers, supervisors, co-workers, and institutions. In adjusted binary logistic models, URM females had 10.14 odds (95% confidence interval [95%CI]: 5.13, 20.02, p<.001), URM males 6.23 odds (95%CI: 2.59, 14.98, p<.001), Asian females 7.90 odds (95%CI: 4.07, 15.33, p<.001), and Asian males 2.96 odds (95% CI: 1.47, 5.97, p=.002) of reporting discrimination compared with non-Hispanic White males. Needing more support was associated with 2.51 odds (95%CI: 1.54, 4.08, p<.001) of reporting discrimination. Our qualitative findings identified that the murder of George Floyd intensified URM healthcare workers' experiences of discrimination through increased fear of violence and requests for unpaid diversity work. Asian healthcare workers reported that pandemic-related anti-Asian violence shaped their experiences of discrimination through increased fear of violence and care refusal from patients. CONCLUSIONS: Our findings provide insights into experienced discrimination among healthcare workers and opportunities for hospitals to create programs that improve inclusivity.

Comparing the measurement equivalence of EQ-5D-5L across different modes of administration.

BACKGROUND: Interest in collecting Patient Reported Outcomes using electronic methods such as mobile phones has increased in recent years. However there is debate about the level of measurement equivalence between the traditional paper and newer electronic modes. Information about the acceptability of the electronic versions to respondents is also required. The aim of this study is to compare the equivalence of delivering a widely used generic measure of health status (EQ-5D-5L) across two administration modes (paper and mobile phone). METHODS: Respondents from a research cohort of people in South Yorkshire were identified, and randomly allocated to one of two administration modes (paper vs. mobile phone) based on stratifications for age and gender (and across a range of self-reported health conditions). A parallel group design was used where each respondent only completed EQ-5D-5L using one of the modes. In total, 70 respondents completed the measure in the mobile phone arm, and 66 completed the standard paper version. Follow up usability questions were also included to assess the acceptability of the mobile version of EQ-5D-5L. Measurement equivalence was compared at the dimension, utility score and visual analogue scale level using chi square analysis and ANOVA, and by comparing mean differences to an estimated minimally important difference value. RESULTS: Response rates were higher in the mobile arm. The mean EQ-5D-5L utility and VAS scores, and the frequency of respondents endorsing individual EQ-5D-5L dimension response levels did not significantly differ across the administration modes. The majority of the mobile arm agreed that the mobile version of EQ-5D-5L was easy to complete, and that the phone was easy to use, and that they would complete mobile health measures again. CONCLUSIONS: Completing health status measures such as EQ-5D using mobile phones produces equivalent results to more traditional methods, but with added benefits (for example lessening the burden of data entry). Respondents are positive towards completing questionnaires using these methods. The results provide evidence that electronic measures are valid for use to collect data in a range of settings including clinical trials, routine care, and in health diary settings.

Optimizing Electronic Capture of Clinical Outcome Assessment Data in Clinical Trials: The Case of Patient-Reported Endpoints.

For a number of compelling scientific, operational, and regulatory reasons, the use of electronic data capture is becoming the preferred means of collecting clinical outcome assessment (eg, patient-reported outcome [PRO]) data in clinical trials. Electronic PRO (ePRO) data collection leverages screen-based technologies (eg, handheld devices, tablet computers, and web-based systems) and telephone-based (eg, interactive voice response) systems. Data collection is routinely either site based (ie, clinical study site) or field based (eg, subject's home, school, or workplace). While tablet computers are often used for site-based PRO data collection, handheld devices have become the mainstay for ePRO data capture in field-based settings. The data collection devices are usually provisioned to the sites or subjects by an ePRO system provider contracted by the clinical trial sponsor. With site-based data collection, study staff are responsible for ensuring subject compliance with the protocol-driven data collection procedures, whereas with field-based data collection, the subject is responsible for compliance with the data entry requirements and sites are accountable for remotely monitoring the data for compliance. In addition to site and subject compliance issues, technology-related factors must be anticipated in order to adhere to the electronic PRO data collection plan. The objective of this paper is to describe study site-, subject-, and technology-related factors that may lead to deviations from the planned electronic collection of PRO data (eg, defaulting to paper-based data collection) and to provide recommendations aimed at preventing potential problems or quickly resolving problems once they occur.

"Bring Your Own Device" (BYOD): The Future of Field-Based Patient-Reported Outcome Data Collection in Clinical Trials?

Field-based patient-reported outcome (PRO) assessments, including measures of signs, symptoms, and events that are administered outside of the research clinic, can be critical in evaluating the efficacy and safety of new medical treatments. Collection of this type of data commonly involves providing subjects with stand-alone electronic devices, such as smartphones, that they can use to respond to assessments in their home or work environment. Although this approach has proven useful, it is also limited in several ways: For example, provisioning stand-alone devices can be costly for sponsors, and requiring subjects to carry a device that is exclusively dedicated to the study can be burdensome. The "Bring Your Own Device" (BYOD) approach, in which subjects use their own smartphone or Internet-enabled device to complete field-based PRO assessments, addresses many of these concerns. However, the BYOD model has its own limitations that should be considered. In this article, representatives of the ePRO Consortium review operational, privacy/security, and scientific/regulatory considerations regarding BYOD. We hope that this review will allow researchers to make informed decisions when choosing methods to collect field-based PRO data in future clinical trials. Additionally, we hope that the discussion in this article will establish a research agenda for further examination of BYOD approaches.

Capturing Patient-Reported Outcome (PRO) Data Electronically: The Past, Present, and Promise of ePRO Measurement in Clinical Trials.

Patient-reported outcomes (PROs) are an important means of evaluating the treatment benefit of new medical products. It is recognized that PRO measures should be used when assessing concepts best known by the patient or best measured from the patient's perspective. As a result, there is growing emphasis on well defined and reliable PRO measures. In addition, advances in technology have significantly increased electronic PRO (ePRO) data collection capabilities and options in clinical trials. The movement from paper-based to ePRO data capture has enhanced the integrity and accuracy of clinical trial data and is encouraged by regulators. A primary distinction in the types of ePRO platforms is between telephone-based interactive voice response systems and screen-based systems. Handheld touchscreen-based devices have become the mainstay for remote (i.e., off-site, unsupervised) PRO data collection in clinical trials. The conventional approach is to provide study subjects with a handheld device with a device-based proprietary software program. However, an emerging alternative for clinical trials is called bring your own device (BYOD). Leveraging study subjects' own Internet-enabled mobile devices for remote PRO data collection (via a downloadable app or a Web-based data collection portal) has become possible due to the widespread use of personal smartphones and tablets. However, there are a number of scientific and operational issues that must be addressed before BYOD can be routinely considered as a practical alternative to conventional ePRO data collection methods. Nevertheless, the future for ePRO data collection is bright and the promise of BYOD opens a new chapter in its evolution.