A novel approach to assessing disparity in representativeness of clinical trial participants within a large midwestern healthcare system

Background

Representativeness in clinical trials (CT) serves as a metric of access to healthcare and reflects differences that may determine differential efficacy of medical interventions; thus, quantifying representativeness in CT participation is critical.

Methods

This retrospective, descriptive study utilized patient demographic data extracted from the largest Midwestern non-profit healthcare system. Using data between January 1, 2019 and December 31, 2021, a CT Participant Sample of 4,537 system patients who were active CT participants was compared to a CT Patient Population of 195,726 system patients receiving care by the PI of active CTs, which represented the target population. Chi-square goodness-of-fit tests were used to test differences in distributions of demographic variables between groups, indicating disparity in CT participation. Two metrics adapted from literature - participation incidence disparity (PID) and participation incidence ratio (PIR) - were calculated to quantify absolute and relative disparity in representativeness proportions, respectively. Descriptive approaches to assessing representativeness are also provided.

Results

Results showed significant differences by race/ethnicity (χ2 = 50.64; p < 0.0001), age categories (χ2 = 56.64; p < 0.0001), and insurance (χ2 = 41.29; p < 0.0001). PID and PIR metrics revealed reduced CT participation among non-White racial/ethnic groups and increased CT participation among White Non-Hispanic patients. Further, CT participants ≥80 or Worker's Compensation were underrepresented while those with Self-Pay insurance were overrepresented as CT participants.

Conclusions

Despite progress, continued efforts to not only enroll participants into CTs that are representative of the healthcare system and region, but also to better assess representativeness quantitatively are still needed.

How representative are participants in geriatric oncology clinical trials? The case of the 5C RCT in geriatric oncology: A cross-sectional comparison to a geriatric oncology clinic

INTRODUCTION

Frail older adults make up a substantial portion of the older adult population. However, frail patients are often excluded from randomized controlled trials. This underrepresentation restricts the extent to which trial findings can be generalized to this population. We compared a sample from the Canadian 5C Randomized Controlled Trial investigating comprehensive geriatric assessment (CGA) in the geriatric oncology setting in terms of frailty to patients referred to the Older Adults with Cancer Clinic (OACC) to determine if the trial sample was representative of the normal geriatric oncology practice.

MATERIALS AND METHODS

Baseline CGA data of 5C Trial participants seen at the Princess Margaret Cancer Centre (PM), were compared to data from OACC patients that were seen during the duration of the 5C trial (between April 2018 and April 2020) and that satisfied the 5C inclusion criteria. To assess the frailty of samples, sex, age, disease site, comorbidity level, medical optimization, social supports, functional status, falls risk, nutrition, cognition, and mood were compared between 5C participants and OACC patients using Fisher's exact and independent samples t-test.

RESULTS

A sample of 115 5C participants and 205 OACC patients were included. The mean age of 5C participants and OACC patients was 75.4 and 81.6 years, respectively (p < 0.001). The distribution of disease sites was significantly different between the samples (p < 0.001) and OACC patients were also significantly more impaired compared to 5C participants in comorbidity (23.4% versus 10.4% high comorbidity) (p = 0.001), IADL dependence (55.1% versus 42.6%) (p = 0.036), impaired physical function (70.6% versus 31.3%) (p < 0.001), falls risk (67.8% versus 27%) (p < 0.001), impaired nutrition (55.6% versus 40.9%) (p = 0.014), and cognition (47.2% versus 10%) (p < 0.001). There were no differences in sex, medication optimization, poor social supports, and impaired mood between the samples.

DISCUSSION

The 5C sample was less frail and younger than patients seen in the geriatric oncology clinic. Finding strategies to address barriers to the inclusion of frailer older adults is important to increase their representation in future trials to allow findings to be generalized to this vulnerable population.

TRIAL REGISTRATION

Clinicaltrials.gov # NCT03154671.

Screening of representative rainfall event series for long-term hydrological performance evaluation of grassed swales

Evaluation of the hydrological performance of grassed swales usually needs long-term monitoring data. At present, suitable techniques for simulating the hydrological performance using limited monitoring data are not available. Therefore, current study aims to investigate the relationship between saturated hydraulic conductivity (Ks) fitting results and rainfall characteristics of various events series length. Data from a full-scale grassed swale (Enschede, the Netherlands) were utilized as long-term rainfall event series length (95 rainfall events) on the fitting outcomes. Short-term rainfall event series were extracted from these long-term series and used as input in fitting into a multivariate nonlinear model between Ks and its influencing rainfall indicators (antecedent dry days, temperature, rainfall, rainfall duration, total rainfall, and seasonal factor (spring, summer, autumn, and winter, herein refer as 1, 2, 3, and 4). Comparison of short-term and long-term rainfall event series fitting results allowed to obtain a representative short-term series that leads to similar results with those using long-term series. A cluster analysis was conducted based on the fitting results of the representative rainfall event series with their rainfall event characteristics using average values of influencing rainfall indicators. The seasonal index (average value of seasonal factors) was found to be the most representative short rainfall event series indicator. Furthermore, a Bayesian network was proposed in the current study to predict if a given short-term rainfall event series is representative. It was validated by a data series (58 rainfall events) from another full-scale grassed swale located in Utrecht, the Netherlands. Results revealed that it is quite promising and useful to evaluate the representativeness of short-term rainfall event series used for long-term hydrological performance evaluation of grassed swales.

Comparing clinical trial population representativeness to real-world users of 17 biologics approved for immune-mediated inflammatory diseases: An external validity analysis of 66,639 biologic users from the Italian VALORE project

To date, no population-based studies have specifically explored the external validity of pivotal randomized clinical trials (RCTs) of biologics simultaneously for a broad spectrum of immuno-mediated inflammatory diseases (IMIDs). The aims of this study were, firstly, to compare the patients' characteristics and median treatment duration of biologics approved for IMIDs between RCTs' and real-world setting (RW); secondly, to assess the extent of biologic users treated for IMIDs in the real-world setting that would not have been eligible for inclusion into pivotal RCT for each indication of use. Using the Italian VALORE distributed database (66,639 incident biologic users), adult patients with IMIDs treated with biologics in the Italian real-world setting were substantially older (mean age ± SD: 50 ± 15 years) compared to those enrolled in pivotal RCTs (45 ± 15 years). In the real-world setting, certolizumab pegol was more commonly used by adult women with psoriasis/ankylosing spondylitis (F/M ratio: 1.8-1.9) compared to RCTs (F/M ratio: 0.5-0.6). The median treatment duration (weeks) of incident biologic users in RW was significantly higher than the duration of pivotal RCTs in almost all indications for use and most biologics (4-100 vs. 6-167). Furthermore, almost half (46.4%) of biologic users from RW settings would have been ineligible for inclusion in the respective indication-specific pivotal RCTs. The main reasons were: advanced age, recent history of cancer and presence of other concomitant IMIDs. These findings suggest that post-marketing surveillance of biologics should be prioritized for those patients.

Assessing real-world representativeness of prospective registry cohorts in oncology: insights from patients with esophagogastric cancer

OBJECTIVES

This study aimed to explore the real-world representativeness of a prospective registry cohort with active accrual in oncology, applying a representativeness metric that is novel to health care.

STUDY DESIGN AND SETTING

We used data from the Prospective Observational Cohort Study of Esophageal-Gastric Cancer Patients (POCOP) registry and from the population-based Netherlands Cancer Registry (NCR). We used Representativeness-indicators (R-indicators) and overall survival to investigate the degree to which the POCOP cohort and clinically relevant subgroups were a representative sample compared to the NCR database. Calibration using inverse propensity score weighting was applied to correct differences between POCOP and NCR.

RESULTS

The R-indicator of the entire POCOP registry was 0.72 95% confidence interval [0.71, 0.73]. Representativeness of palliative patients was higher than that of potentially curable patients (R-indicator 0.88 [0.85, 0.90] and 0.70 [0.68, 0.71], respectively). Stratification to clinically relevant subgroups based on treatment resulted in higher R-indicators of the respective subgroups. Both after stratification and calibration weighting survival estimates in the POCOP registry were more similar to that in the NCR population.

CONCLUSION

This study demonstrated the assessment of real-world representativeness of patients who participated in a prospective registry cohort and showed that real-world representativeness improved when the variability in treatment was accounted for.

Representativeness in health research studies: an audit of Greater Manchester Clinical Research Network studies between 2016 and 2021

BACKGROUND

There are increasing concerns that participants in health research in the UK are not representative of the UK population, risking widening health inequities. However, detailed information on the magnitude of the problem is limited. Therefore, we evaluated if the health research conducted in the Greater Manchester region was broadly representative of its diverse population.

METHODS

We conducted an audit of all health  research studies conducted exclusively in Greater Manchester, using data from a national research network. Two researchers selected studies that were (1) an interventional or observational study of a health outcome; (2) 'closed' for recruitment between May 2016 and May 2021 and (3) human research. They extracted study information (dates, contacts, sample recruited, clinical speciality). Participant characteristics were sourced from published and unpublished manuscripts and requested directly from principal investigators and named study contacts. Data were extracted, summarised and compared to the Greater Manchester population for the following metrics: ethnicity, sex, age, deprivation and smoking status. A weighted mean age estimate was calculated to account for variation in age reporting. Too few studies provided patient-level deprivation data so, using the area code of the recruitment site, the area level multiple deprivation, health deprivation and disability index and decile was derived. These data were geo-mapped using QGIS 3.26.

RESULTS

Overall, 145/153 (95%) studies met inclusion criteria and participant information was sourced for 85/145 (59%) studies, representing 21,797 participants. Participant information was incomplete for all metrics. Where ethnicity (N = 10,259) data were available and compared to Greater Manchester estimates there was evidence that ethnic minorities were under-represented (6% versus 16%). Most of the recruitment occurred in central Manchester (50%) and with NHS hospital settings (74%).

CONCLUSIONS

Greater Manchester health research in 2016-2021 was centralised and under-represented ethnic minorities. We could not report which ethnic minority group was least represented because sourcing detailed participant information was challenging. Recommendations to improve the reporting of key participant characteristics with which to monitor representativeness in health research are discussed.

Using linked administrative data to aid the handling of non-response and restore sample representativeness in cohort studies: the 1958 national child development study and hospital episode statistics data

BACKGROUND

There is growing interest in whether linked administrative data have the potential to aid analyses subject to missing data in cohort studies.

METHODS

Using linked 1958 National Child Development Study (NCDS; British cohort born in 1958, n = 18,558) and Hospital Episode Statistics (HES) data, we applied a LASSO variable selection approach to identify HES variables which are predictive of non-response at the age 55 sweep of NCDS. We then included these variables as auxiliary variables in multiple imputation (MI) analyses to explore the extent to which they helped restore sample representativeness of the respondents together with the imputed non-respondents in terms of early life variables (father's social class at birth, cognitive ability at age 7) and relative to external population benchmarks (educational qualifications and marital status at age 55).

RESULTS

We identified 10 HES variables that were predictive of non-response at age 55 in NCDS. For example, cohort members who had been treated for adult mental illness had more than 70% greater odds of bring non-respondents (odds ratio 1.73; 95% confidence interval 1.17, 2.51). Inclusion of these HES variables in MI analyses only helped to restore sample representativeness to a limited extent. Furthermore, there was essentially no additional gain in sample representativeness relative to analyses using only previously identified survey predictors of non-response (i.e. NCDS rather than HES variables).

CONCLUSIONS

Inclusion of HES variables only aided missing data handling in NCDS to a limited extent. However, these findings may not generalise to other analyses, cohorts or linked administrative datasets. This work provides a demonstration of the use of linked administrative data for the handling of missing cohort data which we hope will act as template for others.

A new methodology to extrapolate disease freedom to an area using surveillance results from selected aquatic populations

According to Chapter 1.4 of the World Organisation for Animal Health (WOAH) Aquatic Animal Health Code, an entire country or zone can be classified as free of a disease only if there is compelling evidence that all susceptible populations within the country or zone are free. However, the methods for achieving freedom are not prescribed in the WOAH standards and guidelines. Within this context, this paper describes a novel methodology to determine if surveillance results can be extrapolated from a study population to a target population. A framework of six criteria was developed to standardize a method for extrapolating surveillance results to other susceptible populations that have not been sampled. Criteria 1 assesses the internal validity for the freedom claim on the source population. Criteria 2 assesses which other susceptible populations have a non-negligible probability of exposure. Criteria 3 assesses whether the risk of infection upon exposure of the source population is the same or greater than each of the other susceptible populations. Finally, Criteria 4, 5 and 6 assess if the other susceptible populations would transmit the infection to the source population or if they have the same exposure pathways as the source population. We illustrate the use of this novel methodology using two hypothetical case scenarios. The presented methodology has the advantage of being applicable either retrospectively or prospectively. When applied retrospectively, it can be used to assess if the surveillance results of the source population can be extrapolated to the target population. When applied prospectively it can be used to design a more efficient surveillance system by selecting source populations from which it is easier to extrapolate surveillance results to the rest of the target population. Conclusions drawn using this methodology depend on the validity of the assumptions made when working through the methodology. We therefore recommend cautious application of the criteria and thorough review of all assumptions.

Quantitative Representativeness and Constituency of the Long-Term Agroecosystem Research Network and Analysis of Complementarity with Existing Ecological Networks

Studies conducted at sites across ecological research networks usually strive to scale their results to larger areas, trying to reach conclusions that are valid throughout larger enclosing regions. Network representativeness and constituency can show how well conditions at sampling locations represent conditions also found elsewhere and can be used to help scale-up results over larger regions. Multivariate statistical methods have been used to design networks and select sites that optimize regional representation, thereby maximizing the value of datasets and research. However, in networks created from already established sites, an immediate challenge is to understand how well existing sites represent the range of environments in the whole area of interest. We performed an analysis to show how well sites in the USDA Long-Term Agroecosystem Research (LTAR) Network represent all agricultural working lands within the conterminous United States (CONUS). Our analysis of 18 LTAR sites, based on 15 climatic and edaphic characteristics, produced maps of representativeness and constituency. Representativeness of the LTAR sites was quantified through an exhaustive pairwise Euclidean distance calculation in multivariate space, between the locations of experiments within each LTAR site and every 1 km cell across the CONUS. Network representativeness is from the perspective of all CONUS locations, but we also considered the perspective from each LTAR site. For every LTAR site, we identified the region that is best represented by that particular site-its constituency-as the set of 1 km grid locations best represented by the environmental drivers at that particular LTAR site. Representativeness shows how well the combination of characteristics at each CONUS location was represented by the LTAR sites' environments, while constituency shows which LTAR site was the closest match for each location. LTAR representativeness was good across most of the CONUS. Representativeness for croplands was higher than for grazinglands, probably because croplands have more specific environmental criteria. Constituencies resemble ecoregions but have their environmental conditions "centered" on those at particular existing LTAR sites. Constituency of LTAR sites can be used to prioritize the locations of experimental research at or even within particular sites, or to identify the extents that can likely be included when generalizing knowledge across larger regions of the CONUS. Sites with a large constituency have generalist environments, while those with smaller constituency areas have more specialized environmental combinations. These "specialist" sites are the best representatives for smaller, more unusual areas. The potential of sharing complementary sites from the Long-Term Ecological Research (LTER) Network and the National Ecological Observatory Network (NEON) to boost representativeness was also explored. LTAR network representativeness would benefit from borrowing several NEON sites and the Sevilleta LTER site. Later network additions must include such specialist sites that are targeted to represent unique missing environments. While this analysis exhaustively considered principal environmental characteristics related to production on working lands, we did not consider the focal agronomic systems under study, or their socio-economic context.

Learning about unprecedented events: Agent-based modelling and the stock market impact of COVID-19

We model the learning process of market traders during the unprecedented COVID-19 event. We introduce a behavioural heterogeneous agents' model with bounded rationality by including a correction mechanism through representativeness (Gennaioli et al., 2015). To inspect the market crash induced by the pandemic, we calibrate the STOXX Europe 600 Index, when stock markets suffered from the greatest single-day percentage drop ever. Once the extreme event materializes, agents tend to be more sensitive to all positive and negative news, subsequently moving on to close-to-rational. We find that the deflation mechanism of less representative news seems to disappear after the extreme event.

Prevalence of lameness in dairy cows: A literature review

Lameness in dairy cows has major negative impacts on animal welfare and production economy. While previous studies have evaluated the prevalence of lameness in single countries, the present literature review is the first overview of the prevalence of lameness in dairy cows globally. This literature review identified 53 studies reporting prevalence of lameness among representative samples of dairy cows and fulfilling a number of specified inclusion criteria (e.g., at least 10 herds and 200 cows, and locomotion scoring by trained observers). A total of 414,950 cows from 3945 herds were included in these 53 studies, which spanned a 30-year period (1989-2020) and included herds from six continents, with the majority from Europe and North America. Across the studies, the mean prevalence of lameness (typically defined as score 3-5 on a 1-5 scale) was 22.8% with a median of 22.0% and a range between studies from 5.1% to 45%, and a within herd range from 0% to 88%. The mean prevalence of severely lame cows (typically defined as score 4-5 on a 1-5 scale) was 7.0% with a median of 6.5% and a range between studies from 1.8% to 21.2%, and a within herd range from 0% to 65%. Over time, it appears that the prevalence of lameness has changed very little. Several different locomotion scoring systems and definitions of (severe) lameness were used across the 53 studies, and this may have affected the reported lameness prevalence. Sampling of herds and cows, inclusion criteria and representativeness also differed between studies. This review offers recommendations for the future capture of information on lameness in dairy cows and identifies potential knowledge gaps.

Limited co-benefits of protected areas in southwest China under current climate change and human modification

An ambitious new Post-2020 Global Biodiversity Framework "Kunming-Montreal Global Biodiversity Framework" has been developed. However, the combined effects of climate change and human modification can undermine the potential benefits of the global post-2020 conservation efforts. The co-benefits of stabilizing the climate, conserving biodiversity, and maintaining intact wilderness areas may help to persuade the general public of the need to quickly expand existing protected areas (PAs). To maximize the co-benefits after 2020, the careful optimization of existing (PAs) network and scientific identification of conservation targets are both essential. Here, we mapped hotspots of biodiversity, climate vulnerability, and wilderness in Southwest China (SWC). By analyzing the representativeness and gaps of the existing PAs network in SWC, we devised post-2020 conservation targets and highlighted their implications for decision-makers. Our results showed that the incongruence between hotspots of different species exists, indicating that habitats suitable for one taxon may not fully harbor other taxa. According to our assessment, the five jurisdictions of SWC have warmed on average by 0.4°C-1.1 °C over the past 60 years alone. In particular, biodiversity hotspots in SWC are undergoing stark climatic changes. We uncovered prominent conservation gaps in SWC's network of PAs, especially in terms of climate vulnerability and biodiversity. Due to their insufficient number and unreasonable spatial distribution, the PAs network in SWC may be not capable of meeting its biodiversity, climate vulnerability, and wilderness conservation objectives. To rectify this, we proposed a 3-step mission: milestone 2025, milestone 2030, and goal 2050, which aims to protect 23%, 28%, and 60% of the terrestrial area in SWC, respectively. Taken together, our study derived conservation priority areas with relatively clear spatial boundaries and importance levels, thus providing detailed, timely information for decision-makers to expand the PAs network and implement conservation measures varying in strictness in post-2020 conservation practice.

REPRESENT: REPresentativeness of RESearch data obtained through the 'General Informed ConsENT'

BACKGROUND

We assessed potential consent bias in a cohort of > 40,000 adult patients asked by mail after hospitalization to consent to the use of past, present and future clinical and biological data in an ongoing 'general consent' program at a large tertiary hospital in Switzerland.

METHODS

In this retrospective cohort study, all adult patients hospitalized between April 2019 and March 2020 were invited to participate to the general consent program. Demographic and clinical characteristics were extracted from patients' electronic health records (EHR). Data of those who provided written consent (signatories) and non-responders were compared and analyzed with R studio.

RESULTS

Of 44,819 patients approached, 10,299 (23%) signed the form. Signatories were older (median age 54 [IQR 38-72] vs. 44 years [IQR 32-60], p < .0001), more comorbid (2614/10,299 [25.4%] vs. 4912/28,676 [17.1%] with Charlson comorbidity index ≤ 4, p < .0001), and more often of Swiss nationality (6592/10,299 [64%] vs. 13,813/28,676 [48.2%], p < .0001).

CONCLUSIONS

Our results suggest that actively seeking consent creates a bias and compromises the external validity of data obtained via 'general consent' programs. Other options, such as opt-out consent procedures, should be further assessed.

Leveraging Every Door Direct Mail for remote recruitment of a rural Appalachian study Sample: Response rate and representativeness

Every Door Direct Mail (EDDM) is a service of the United States Postal Service (USPS) that delivers non-addressed mail to all postal customers on designated mailing routes. Primarily used for marketing, we describe EDDM's efficacy as a research tool for remotely recruiting a representative convenience sample of rural Appalachian households for a longitudinal survey-based health study. In June 2020, recruitment postcards were sent via EDDM to all residential addresses (n = 31,201) within an 18 ZIP code region of Southeastern Ohio. Adults were invited to complete a survey online via QR code or to call for a mailed survey. Respondent demographic characteristics were generated using SPSS and compared with the region's 2019 U.S. Census Bureau statistics. A total of 841 households responded to the invitation, reflecting a response rate higher than marketing estimates (2.7 % vs 2 %). Compared to Census data, a greater proportion of respondents were female (74 % vs 51 %), and highly educated (64 % vs 36 % college graduates); a comparable proportion were non-Hispanic (99 % vs 98 %), white (90 % vs 91 %), and had ≥ 1 adult in the household (1.7 ± 0.9); and a lower proportion had a household income < $50 k (47 % vs 54 %). The median age was higher (56 vs 30 years), and 29 % were retirees. EDDM was a viable method for remote recruitment of a rural geographically-based sample. Further work is needed to explore its efficacy in recruiting representative samples in other contexts and to inform best practices for its use.

Impact of sampling and data collection methods on maternity survey response: a randomised controlled trial of paper and push-to-web surveys and a concurrent social media survey

BACKGROUND

Novel survey methods are needed to tackle declining response rates. The 2020 National Maternity Survey included a randomised controlled trial (RCT) and social media survey to compare different combinations of sampling and data collection methods with respect to: response rate, respondent representativeness, prevalence estimates of maternity indicators and cost.

METHODS

A two-armed parallel RCT and concurrent social media survey were conducted. Women in the RCT were sampled from ONS birth registrations and randomised to either a paper or push-to-web survey. Women in the social media survey self-selected through online adverts. The primary outcome was response rate in the paper and push-to-web surveys. In all surveys, respondent representativeness was assessed by comparing distributions of sociodemographic characteristics in respondents with those of the target population. External validity of prevalence estimates of maternity indicators was assessed by comparing weighted survey estimates with estimates from national routine data. Cost was also compared across surveys.

RESULTS

The response rate was higher in the paper survey (n = 2,446) compared to the push-to-web survey (n = 2,165)(30.6% versus 27.1%, difference = 3.5%, 95%CI = 2.1-4.9, p < 0.0001). Compared to the target population, respondents in all surveys were less likely to be aged < 25 years, of Black or Minority ethnicity, born outside the UK, living in disadvantaged areas, living without a partner and primiparous. Women in the social media survey (n = 1,316) were less representative of the target population compared to women in the paper and push-to-web surveys. For some maternity indicators, weighted survey estimates were close to estimates from routine data, for other indicators there were discrepancies; no survey demonstrated consistently higher external validity than the other two surveys. Compared to the paper survey, the cost saving per respondent was £5.45 for the push-to-web survey and £22.42 for the social media survey.

CONCLUSIONS

Push-to-web surveys may cost less than paper surveys but do not necessarily result in higher response rates. Social media surveys cost significantly less than paper and push-to-web surveys, but sample size may be limited by eligibility criteria and recruitment window and respondents may be less representative of the target population. However, reduced representativeness does not necessarily introduce more bias in weighted survey estimates.

Is it a judgment of representativeness? Re-examining the birth sequence problem

Although all birth orders in the "birth sequence problem" are equiprobable, most participants judge the less representative order as less likely than the more representative order. But this well-known problem confounds representativeness with the direction in which birth orders are compared. We hypothesized and corroborated in three experiments (total N = 1,136) that participants pragmatically infer the birth orders' relative prevalence from the direction of comparison. Experiment 1 found that participants judged the less representative sequence as more common when we reversed the comparison. Experiment 2 reproduced these results despite removing representativeness as a cue. In Experiment 3, participants preferred to place the relatively common sequence as the referent in an inverted "speaker" problem. Our results turn the iconic problem's interpretation on its head: Rather than indicating flawed human cognition, the birth sequence problem illustrates people's ability to adaptively extract subtle linguistic meaning beyond the literal content.

Exploring ethnic representativeness in diabetes clinical trial enrolment from 2000 to 2020: a chronological survey

AIMS/HYPOTHESIS

Ethnic representativeness of participant enrolment in diabetes RCTs involving multiple ethnicities remains unknown. The aims of this study were to evaluate the status and temporal trend of ethnic representativeness in enrolment to diabetes RCTs, and to assess under-enrolment of non-white ethnic groups and explore trial characteristics associated with under-enrolment.

METHODS

We conducted a chronological survey by systematically searching the literature to include eligible RCTs published between January 2000 and December 2020. We assessed temporal trends in enrolment of ethnic groups in the included trials. Univariable logistic regression was used to explore the association between trial characteristics and under-enrolment of non-white groups, using a participant to prevalence ratio of <0.8 to define under-enrolment. This study was registered in PROSPERO (CRD42021229100).

RESULTS

We included 405 RCTs for analysis (327 multi-country trials, 69 conducted in the USA and nine conducted in the UK). The median enrolment rate of all non-white groups was 24.0% in the overall RCTs. Trials conducted in the USA and the UK had median enrolment rates of 29.0% and 12.0% for all non-white groups, respectively. There was a temporal trend towards increased participation of non-white ethnic groups in the overall RCTs; however, no significant improvement over time was found in the US or UK trials. Non-white groups were under-enrolled in most included trials: 62.3% (43/69) in US trials and 77.8% (7/9) in UK trials. The US trials with a high female proportion were associated with lower odds of under-enrolment of all non-white groups (OR 0.22; 95% CI 0.07, 0.65), while trials receiving funding from industry showed increased odds of under-enrolment (OR 4.64; 95% CI 1.50, 14.35). Outpatient enrolment and intervention duration were significantly associated with under-enrolment of Black participants. Only a small proportion of trials reported subgroup results or explored the effect modification by ethnicity.

CONCLUSIONS/INTERPRETATION

A temporal trend towards increased non-white ethnic enrolment was found in diabetes RCTs globally, but not in the USA or the UK. Non-white ethnic groups were under-represented in the majority of diabetes trials conducted in the USA and the UK. Some trial characteristics may be associated with non-white under-enrolment in diabetes trials. These findings provide some evidence for non-white ethnic representativeness in diabetes trials over the past two decades, and highlight the need for more effective strategies and endeavours to alleviate under-enrolment of non-white ethnic groups.

OpenSAFELY: Representativeness of electronic health record platform OpenSAFELY-TPP data compared to the population of England

Background: Since its inception in March 2020, data from the OpenSAFELY-TPP electronic health record platform has been used for more than 20 studies relating to the global COVID-19 emergency. OpenSAFELY-TPP data is derived from practices in England using SystmOne software, and has been used for the majority of these studies. We set out to investigate the representativeness of OpenSAFELY-TPP data by comparing it to national population estimates.    Methods: With the approval of NHS England, we describe the age, sex, Index of Multiple Deprivation and ethnicity of the OpenSAFELY-TPP population compared to national estimates from the Office for National Statistics. The five leading causes of death occurring between the 1st January 2020 and the 31st December 2020 were also compared to deaths registered in England during the same period.  Results: Despite regional variations, TPP is largely representative of the general population of England in terms of IMD (all within 1.1 percentage points), age, sex (within 0.1 percentage points), ethnicity and causes of death. The proportion of the five leading causes of death is broadly similar to those reported by ONS (all within 1 percentage point).  Conclusions: Data made available via OpenSAFELY-TPP is broadly representative of the English population. Users of OpenSAFELY must consider the issues of representativeness, generalisability and external validity associated with using TPP data for health research. Although the coverage of TPP practices varies regionally across England, TPP registered patients are generally representative of the English population as a whole in terms of key demographic characteristics.

Assessment of the impact of sensor error on the representativeness of population exposure to urban air pollutants

For the monitoring of urban air pollution, smart sensors are often seen as a welcome addition to fixed-site monitoring (FSM) networks. Due to price and simple installation, increases in spatial representation are thought to be achieved by large numbers of these sensors, however, a number of sensor errors have been identified. Based on a high-resolution modelling system, up to 400 pseudo smart sensors were perturbated with the aim of simulating common sensor errors and added to the existing FSM network in Hong Kong, resulting in 1200 pseudo networks for PM_2.5 and 1040 pseudo networks for NO₂. For each pseudo network, population-weighted area representativeness (PWAR) was calculated based on similarity frequency. For PM_2.5, improvements (up to 16%) to the high baseline representativeness (PWAR = 0.74) were achievable only by the addition of high-quality sensors and favourable environmental conditions. The baseline FSM network represents NO₂ less well (PWAR = 0.52), as local emissions in the study domain resulted in high spatial pollution variation. Due to higher levels of pollution (population-weighted average 37.3 ppb) in comparison to sensor error ranges, smart sensors of a wider quality range were able to improve network representativeness (up to 42%). Marginal representativeness increases were found to exponentially decrease with existing sensor number. The quality and maintenance of added sensors had a stronger effect on overall network representativeness than the number of sensors added. Often, a small number of added sensors of a higher quality class led to larger improvements than hundreds of lower-class sensors. Whereas smart sensor performance and maintenance are important prerequisites particularly for developed cities where pollutant concentration is low and there is an existing FSM network, our study shows that for places with high pollutant variability and concentration such as encountered in some developing countries, smart sensors will provide benefits for understanding population exposure.

Raking of data from a large Australian cohort study improves generalisability of estimates of prevalence of health and behaviour characteristics and cancer incidence

Background

Health surveys are commonly somewhat non-representative of their target population, potentially limiting the generalisability of prevalence estimates for health/behaviour characteristics and disease to the population. To reduce bias, weighting methods have been developed, though few studies have validated weighted survey estimates against generally accepted high-quality independent population benchmark estimates.

Methods

We applied post-stratification and raking methods to the Australian 45 and Up Study using Census data and compared the resulting prevalence of characteristics to accepted population benchmark estimates and separately, the incidence rates of lung, colorectal, breast and prostate cancer to whole-of-population estimates using Standardised Incidence Ratios (SIRs).

Results

The differences between 45 and Up Study and population benchmark estimates narrowed following sufficiently-informed raking, e.g. 13.6% unweighted prevalence of self-reported fair/poor overall health, compared to 17.0% after raking and 17.9% from a population benchmark estimate. Raking also improved generalisability of cancer incidence estimates. For example, unweighted 45 and Up Study versus whole-of-population SIRs were 0.700 (95%CI:0.574–0.848) for male lung cancer and 1.098 (95%CI:1.002–1.204) for prostate cancer, while estimated SIRs after sufficiently-informed raking were 0.828 (95%CI:0.684–0.998) and 1.019 (95%CI:0.926–1.121), respectively.

Conclusion

Raking may be a useful tool for improving the generalisability of exposure prevalence and disease incidence from surveys to the population.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01626-5.

Aging of tire and road wear particles in terrestrial and freshwater environments - A review on processes, testing, analysis and impact

The environmental fate of tire and road wear particles (TRWPs) receives increasing attention due to the per capita emission volumes of 0.2-5.5 kg/(cap year) and recent reports on the environmental hazard of TRWP constituents. It is expected that aging impacts TRWPs fate in the environment but detailed knowledge is quite limited, yet. Making use of information on tire aging, the available knowledge on environmental aging processes such as thermooxidation, photooxidation, ozonolysis, shear stress, biodegradation and leaching is reviewed here. Experimental techniques to simulate aging are addressed as are analytical techniques to determine aging induced changes of TRWPs, covering physical and chemical properties. The suitability of various tire wear test materials is discussed. Findings and methods from tire aging can be partially applied to study aging of TRWPs in the environment. There is a complex interplay between aging processes in the environment that needs to be considered in future aging studies. In addition to existing basic qualitative understanding of the aging processes, quantitative understanding of TRWP aging is largely lacking. Aging in the environment needs to consider the TRWPs as well as chemicals released. Next steps for filling the gaps in knowledge on aging of TRWPs in the environment are elaborated.

Generalizability of Randomized Controlled Trials in Rectal Cancer

BACKGROUND

The generalizability of outcomes from randomized controlled trials (RCTs) in oncology is a frequent concern. Given the prevalence and multidisciplinary management of rectal cancer, understanding the generalizability of rectal cancer RCTs is critical to surgical oncologists.

METHODS

An exhaustive literature review identified 100 non-metastatic rectal cancer RCTs published in English over the past 10 years investigating surgery, chemotherapy, or radiotherapy. In order to evaluate the representativeness of these RCTs compared to the USA and each continent's rectal cancer populations, demographic characteristics were stratified by surgical versus chemoradiotherapy (CRT) trial and by continent then compared with the National Cancer Database and CANCER TODAY using chi-squared and Welch's t-tests.

RESULTS

Of the 100 trials identified, 65% enrolled significantly younger patients, and 38% enrolled a significantly greater proportion of males than the US rectal cancer population. These demographic differences were more prominent among CRT trials than surgical trials. Half of all trials enrolled patients who were on average more than 7 years younger and enrolled a 5% greater proportion of males than their respective continental rectal cancer populations. Patients enrolled in trials had more advanced cancers than their corresponding continental populations. Sociodemographic data was rarely reported.

CONCLUSION

Patients enrolled in trials were younger, predominantly male, and had advanced stage cancer when compared to the rectal cancer population. Sociodemographic variables are underreported, further limiting equal participation in clinical trials. Future rectal cancer RCTs should strive to recruit representative samples. To enhance recruitment of women and underrepresented minorities, tailored recruitment strategies must be implemented.

Cohort profile and representativeness of participants in the Diet, Cancer and Health-Next Generations cohort study

The Diet, Cancer and Health-Next Generations (DCH-NG) study is a large population-based cohort study that was established as a resource for transgenerational research. The cohort is an extension of the Diet, Cancer and Health (DCH) cohort. The aim of this paper was to describe the study design and methods and to investigate the representativeness of participants by comparing participants with non-participants with emphasis on socioeconomic determinants. In 2015-2019, children (G1), their spouses (G1P) and grandchildren (G2) of DCH cohort members were invited to participate. Participants completed questionnaires, a physical examination and collection of biological material. Information on general and sociodemographic variables was obtained by linkage to administrative registries in Denmark. The cohort includes 39,554 adult participants with complete data collection. Participants are represented in different family structures including 2- and 3-generation relationships, offspring-parents trios and siblings. The odds ratio for participation was highest among G1, females, middle-aged and married individuals and individuals with the highest education, highest income, occupations requiring high-level skills and residency near a study centre. The different family structures allow a range of studies with cohort and transgenerational designs. The pattern of more likelihood of participation in higher socioeconomic groups was similar to the pattern of participation in the DCH cohort and the general patterns in population-based studies. Accordingly, the study population has some limitations as to being representative of the general population. Yet, the DCH-NG cohort will provide valuable insight on the association between risk factor-disease relationships and the role of heredity on these associations.

To what extent do citizens support the disinvestment of healthcare interventions? An exploration of the support for four viewpoints on active disinvestment in the Netherlands

BACKGROUND

Active disinvestment of healthcare interventions (i.e. discontinuing reimbursement by means of a policy decision) has received limited public support in the past. Previous research has identified four viewpoints on active disinvestment among citizens in the Netherlands. However, it remained unclear how strong these viewpoints are supported by society, and by whom. Therefore, the current study aimed to 1) measure the support for these four viewpoints and 2) assess whether support is associated with background characteristics of citizens.

METHOD

In an online survey, a representative sample of adult citizens in the Netherlands (n = 1794) was asked to rate their agreement with short narratives of the four viewpoints on a 7-point Likert scale. The survey also included questions on sociodemographic characteristics, health status, healthcare utilization, and opinions about responsibility and costs in the healthcare context. Logistic regression models were estimated for each viewpoint to assess the association between viewpoint support and these characteristics.

RESULTS

The support for the different viewpoints varied between 46.8% and 57.7% of the sample. Viewpoint support was associated with participants' age, gender, educational level, financial situation, healthcare utilization, opinion on the responsibility of the government for the health of citizens, and opinion on whether the increase in healthcare expenditure and health insurance premiums is considered a problem.

CONCLUSION

Resistance to active disinvestment may partially be explained by the consequences of disinvestment citizens anticipate experiencing themselves. Citizens considering the increase in healthcare expenditure a larger problem were more supportive of disinvestment than those considering it less of a problem.

Sensitivity and representativeness of one-health surveillance for diseases of zoonotic potential at health facilities relative to household visits in rural Guatemala

Most human and animal disease notification systems are unintegrated and passive, resulting in underreporting. Active surveillance can complement passive efforts, but because they are resource-intensive, their attributes must be evaluated. We assessed the sensitivity and representativeness of One-Health surveillance conducted at health facilities compared to health facilities plus monthly household visits in three rural communities of Guatemala. From September 2017 to November 2018, we screened humans for acute diarrheal, febrile and respiratory infectious syndromes and canines, swine, equines and bovines for syndromic events or deaths. We estimated the relative sensitivity as the incidence rate ratio of detecting an event in health facility surveillance compared to household surveillance from Poisson models. We used interaction terms between the surveillance method and sociodemographic factors or time trends to assess effect modification as a measure of relative representativeness. We used generalized additive models with smoothing splines to model incidence over time by surveillance method. We randomized 216 households to health facility surveillance and 198 to health facility surveillance plus monthly household visits. Health facility surveillance alone was less sensitive than when combined with household surveillance by 0.42 (95% CI: 0.34, 0.53), 0.56 (95% CI: 0.39, 0.79), 0.02 (95% CI: 0.00, 0.10), 0.28 (95% CI: 0.15, 0.50) and 0.22 (95% CI: 0.03, 0.92) times for human acute infections, human severe acute infections, and deaths in canines, swine and equines, respectively. Health facility surveillance alone underrepresented Spanish speakers (interaction p-value = 0.0003) and persons in higher economic assets (interaction p-values = 0.0008). The trend in incidence over time was different between the two study groups, with a larger decrease in the group with household surveillance (all interaction p-values <0.10). Surveillance at health facilities under ascertains syndromes in humans and animals which leads to underestimation of the burden of zoonotic disease. The magnitude of under ascertainment was differentially by sociodemographic factors, yielding an unrepresentative sample of health events. However, it is less time-intensive, thus might be sustained over time longer than household surveillance. The choice between methodologies should be evaluated against surveillance goals and available resources.

Using a population health management approach to enroll participants in a diabetes prevention trial: reach outcomes from the PREDICTS randomized clinical trial

Population health management (PHM) strategies to address diabetes prevention have the potential to engage large numbers of at-risk individuals in a short duration. We examined a PHM approach to recruit participants to a diabetes prevention clinical trial in a metropolitan health system. We examined reach and representativeness and assessed differences from active and passive respondents to recruitment outreach, and participants enrolled through two clinical screening protocols. The PHM approach included an electronic health record (EHR) query, physician review of identified patients, letter invitation, and telephone follow-up. Data describe the reach and representativeness of potential participants at multiple stages during the recruitment process. Subgroup analyses examined proportional reach, participant differences based on passive versus active recruitment response, and clinical screening method used to determine diabetes risk status. The PHM approach identified 10,177 potential participants to receive a physician letter invitation, 60% were contacted by telephone, 2,796 (46%) completed telephone screening, 1,961 were eligible from telephone screen, and 599 were enrolled in 15 months. Accrual was unaffected by shifting clinical screening protocols despite the increase in participant burden. Relative to census data, study participants were more likely to be obese, female, older, and Caucasian. Relative to the patient population, enrolled participants were less likely to be Black and were older. Active respondents were more likely to have a higher income than passive responders. PHM strategies have the potential to reach a large number of participants in a relatively short period, though concerted efforts are needed to increase participant diversity.

The German Environmental Survey for Children and Adolescents 2014-2017 (GerES V) - Study population, response rates and representativeness

The German Environmental Survey (GerES) is a population-representative, cross-sectional study on environmental exposures of the general population of Germany. GerES has repeatedly been conducted since 1985 by the German Environment Agency (UBA) in close collaboration with the Health Interview and Examination Surveys of the Robert Koch Institute (RKI). In the German Environmental Survey for Children and adolescents 2014-2017 (GerES V) pollutants and other environmental stressors were measured in human samples as well as in the homes of 3- to 17-year-old children and adolescents. Interviews were conducted about health-related behaviors and living conditions. The GerES V basic program encompassed examinations of whole blood, blood plasma, morning urine and drinking water samples, measurements of ultrafine particles and noise levels, comprehensive standardized interviews, and self-administrated questionnaires. Additional modules on volatile organic compounds and aldehydes, particulate matter (PM_2.5) in indoor air, organic compounds in drinking water and pollutants in house dust were conducted in subsamples. Potential GerES V participants were identified and attained by the RKI from those participants who were examined and interviewed for the cross-sectional component of the second follow-up to the German Health Interview and Examination Survey for Children and Adolescents (KiGGS Wave 2). The gross sample of GerES V comprised 3031 children and adolescents of which 2294 finally took part in the survey. This equals a total response rate of 75.7 %. Response rates varied, depending on region, type of municipality, age and sex, from 66.0 % to 78.3 %. By calculating individual case weights, discrepancies due to sample design and non-response between the GerES V sample and the whole population could be considered in statistical analysis. Therefore, the representativeness of the GerES V results with regard to age, sex, community size and region was assured.

What characterizes schools and students participating in health promoting school-based intervention studies? Findings from the healthy high school study

The Healthy High School (HHS) intervention was developed to promote well-being among first-year high school students (~16 years of age) in Denmark by targeting stress, physical activity, meal habits, sleep, and sense of community. Thirty-one schools were randomly allocated to intervention (16 schools) or control (15 schools) groups in a cluster-randomized controlled trial. The purpose of this short communication was to compare characteristics of students and schools between 1) schools accepting to participate in the HHS study and non-participating schools using national survey data and 2) intervention and control schools using HHS baseline data. We included cross-sectional data from the Danish National Youth Study 2014 on 119 schools and 22,935 first-year students to characterize participating schools and students. At baseline (August 2016), students (n = 4577; 88.0%) and principals (n = 29; 96.7%) completed online questionnaires. Compared to non-participating schools, fewer HHS schools perceived their school as being popular and offered weekly sport activities outside school hours. More HHS schools had teachers engaged in health promotion activities and focused on stress prevention. The characteristics of HHS students did not differ markedly from non-participating high school students. There were no socio-demographic, outcome or contextual differences between the study arms. To ensure successful recruitment of schools it is important that the intervention meets the need of the schools and that the advantages of participation are explicit. This underlines the need for a thorough needs assessment prior to intervention development, co-creation of intervention activities with school staff, and a well-planned recruitment strategy.

Regular and random judgements are not two sides of the same coin: Both representativeness and encoding play a role in randomness perception

The overalternating bias is that people rate sequences with an excess of alternation as more random than prescribed by information theory. There are two main explanations: the representativeness heuristic (Kahneman & Tversky Cognitive Psychology, 3, 430-454, 1972) and the implicit encoding hypothesis (Falk & Konold Psychological Review, 104, 301-318, 1997). These hypotheses are associated with different reaction times predictions. According to the encoding hypothesis, reaction times should increase as the complexity of the sequence increases, whereas the representativeness heuristic predicts fast reaction times only for more complex sequences that appear more random. We asked participants to guess the generating source of pairs of sequences of dichotomous elements in two different conditions: selecting the string generated by a random source or selecting the string generated by a nonrandom source. Results suggest that both the encoding strategy and the representativeness heuristic have a role in randomness perception and that the two criteria may have a different weight when determining the randomness versus the regularity of a string.

Replications, Comparisons, Sampling and the Problem of Representativeness in Animal Cognition Research

Animal cognition research often involves small and idiosyncratic samples. This can constrain the generalizability and replicability of a study's results and prevent meaningful comparisons between samples. However, there is little consensus about what makes a strong replication or comparison in animal research. We apply a resampling definition of replication to answer these questions in Part 1 of this article, and, in Part 2, we focus on the problem of representativeness in animal research. Through a case study and a simulation study, we highlight how and when representativeness may be an issue in animal behavior and cognition research and show how the representativeness problems can be viewed through the lenses of, i) replicability, ii) generalizability and external validity, iii) pseudoreplication and, iv) theory testing. Next, we discuss when and how researchers can improve their ability to learn from small sample research through, i) increasing heterogeneity in experimental design, ii) increasing homogeneity in experimental design, and, iii) statistically modeling variation. Finally, we describe how the strongest solutions will vary depending on the goals and resources of individual research programs and discuss some barriers towards implementing them.

Combining network topology and information theory to construct representative brain networks

Network neuroscience employs graph theory to investigate the human brain as a complex network, and derive generalizable insights about the brain's network properties. However, graph-theoretical results obtained from network construction pipelines that produce idiosyncratic networks may not generalize when alternative pipelines are employed. This issue is especially pressing because a wide variety of network construction pipelines have been employed in the human network neuroscience literature, making comparisons between studies problematic. Here, we investigate how to produce networks that are maximally representative of the broader set of brain networks obtained from the same neuroimaging data. We do so by minimizing an information-theoretic measure of divergence between network topologies, known as the portrait divergence. Based on functional and diffusion MRI data from the Human Connectome Project, we consider anatomical, functional, and multimodal parcellations at three different scales, and 48 distinct ways of defining network edges. We show that the highest representativeness can be obtained by using parcellations in the order of 200 regions and filtering functional networks based on efficiency-cost optimization-though suitable alternatives are also highlighted. Overall, we identify specific node definition and thresholding procedures that neuroscientists can follow in order to derive representative networks from their human neuroimaging data.

Can the validity of a cohort be improved by reweighting based on register data? Evidence from the Swedish MDC study

Background

In any study with voluntary participation, self-selection risks leading to invalid conclusions. If the determinants of selection are observed, it is however possible to restore the parameters of interest by reweighting the sample to match the population, but this approach has seldom been applied in epidemiological research.

Methods

We reweighted the Malmö Diet and Cancer (MDC) study based on population register data on background variables, including socio-demographics and hospital admissions for both participants and the background population. Following individuals from baseline in 1991–1996 and at most until 2016, we studied mortality (all-cause, cancer, and CVD), incidences (cancer and CVD), and associations between these outcomes and background variables. Results from the unweighted and reweighted participant sample were compared with those from the background population.

Results

Mortality was substantially lower in participants than in the background population, but reweighting the sample helped only little to make the numbers similar to those in the background population. For incidences and associations, numbers were generally similar between participants and the background population already without reweighting, rendering reweighting unnecessary.

Conclusion

Reweighting samples based on an extensive range of sociodemographic characteristics and previous hospitalizations does not necessarily yield results that are valid for the population as a whole. In the case of MDC, there appear to be important factors related to both mortality and selection into the study that are not observable in registry data, making it difficult to obtain accurate numbers on population mortality based on cohort participants. These issues seem less relevant for incidences and associations, however. Overall, our results suggest that representativeness must be judged on a case-by-case basis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-020-10004-z.

[Patient and public involvement in health-related research: How is the selection of participants reported?]

BACKGROUND AND OBJECTIVES

In recent years, the reporting on patient and public involvement (PPI) in health-related research has gained significantly in importance. However, little attention is being paid to the selection of target groups or participating citizens and patients. Individual contributions already point out that the selection is often described in a complex but ambiguous way; for example, individual groups are often not sufficiently differentiated from each other. The aim of our study is to provide an overview of the main topics, questions and challenges that are specific to the selection of participants in PPI by means of an explorative sample of different PPI documents (studies with PPI, studies on PPI, PPI guidelines, PPI websites, PPI journals). Based on this overview, we will make recommendations to help authors of studies and other relevant stakeholders in the planning, implementation and reporting of participant selection.

METHODS

First, the explorative sample of the above-mentioned PPI documents was identified by conducting a systematic database and online search. A total of 46 documents were taken into account, including 11 studies with PPI, 12 studies on PPI, 12 guidelines, 6 websites and 5 journals. Relevant text passages were extracted from each of them and evaluated using deductively and inductively developed topic-specific categories.

RESULTS

Overall, the selected PPI documents significantly vary a) in the use of terms, b) in the detailing of the individual aspects of participant selection, and c) in the description of the planning and implementation of participant selection. For the latter, there is usually a lack of systematic, comprehensive explanations, e. g., on how to weigh up a relevant number of participants, on objectives and methods in the selection process and on how to prepare participants.

DISCUSSION

The various documents about and contributions to the topic of PPI should, in future, report more transparently and systematically on the selection of participants, especially to create practical added value for authors of studies. This includes, in particular, the description of the selection (studies with PPI), a complete overview of all relevant steps of the selection process (PPI guidelines), recommendations on how to deal with representativeness (studies on PPI), notes on reporting PPI (journals) as well as overviews of individual steps of the implementation process (PPI websites).

Representativeness of personality and involvement preferences in a web-based survey on healthcare decision-making

Background

Obtaining a sample that is representative of the group of interest is of utmost importance in questionnaire studies. In a survey using a state authorized web-portal for citizen communication with authorities, we wanted to investigate the view of adult men on patient involvement in health care decision-making regarding Prostate-Specific Antigen test for prostatic cancer. In this paper, we report on sample characteristics and representativeness of our sample in terms of personality and baseline involvement preferences.

Methods

We compared personality profiles (BFI-10) and baseline healthcare decision-making preferences (CPS) in our sample (n = 6756) to internationally available datasets. Pooled data from a) US, UK, Canada, Australia, and New Zealand (n = 1512), b) Germany, Netherlands, Switzerland, and Belgium (n = 1136), and c) Norway, Sweden, Finland, and Denmark (n = 1313) were used for BFI-10 comparisons. Regarding CPS, we compared our sample with three previous datasets relating to decision-making in cancer (n = 425, 387, and 199).

Results

Although statistically significant differences particularly appeared in large dataset comparisons, sample BFI-10 and CPS profiles mostly were within the range of those previously reported. Similarity was greatest in BFI-10 comparisons with group a) where no statistically significant difference could be established in factors ‘agreeableness’ and ‘neuroticism’ (p = .095 and .578, respectively).

Conclusion

Despite some variation, our sample displays personality and baseline preference profiles that are generally similar to those described in previous international studies. For example, this was the case with the BFI-10 ‘agreeableness’ measure (incl. trust and fault-finding items), an important factor in healthcare decision-making.

Validation of a semi-automated surveillance system for surgical site infections: Improving exhaustiveness, representativeness, and efficiency

OBJECTIVES

To assess whether electronic records data could improve the efficiency, exhaustiveness, and representativeness of SSI surveillance by selecting a group of high-risk patients for manual review.

METHODS

Colorectal surgeries (2016-2018) and cholecystectomies (2017-2018) were selected. Post-surgical antibiotic use, positive culture, C-reactive protein (CRP) values, body temperature, leukocyte count, surgical re-intervention, admission to the emergency room, and hospital readmission were retrieved. For representativeness, procedures registered in HAI-Net were compared with non-included procedures, and the validity of each variable (or combination) was tested considering the presence of SSI as the gold standard. The proportion of procedures flagged for manual review by each criterion was estimated.

RESULTS

Little more than 50% of procedures were included in HAI-Net (SSI risk: 10.6% for colorectal and 2.9% for cholecystectomies). Non-included procedures showed higher proportions of infection markers. Antibiotic use and CRP >100 mg/dl presented the highest sensitivity for both surgical groups, while antibiotic use achieved the highest positive predictive value in both groups (22% and 21%, respectively) and flagged fewer colorectal procedures (47.7%).

CONCLUSIONS

Current SSI surveillance has major limitations. Thus, the reported incidence seems unreliable and underestimated. Antibiotic use appears to be the best criterion to select a sub-sample of procedures for manual review, improving the exhaustiveness and efficiency of the system.

Practice of reporting social characteristics when describing representativeness of epidemiological cohort studies - A rationale for an intersectional perspective

Representativeness has been defined as the degree of similarity of a study population compared to an external population. To characterize a study population, both health-related and social or demographic features should be considered according to current guidelines. However, little guidance is given on how to describe social complexity of study populations when aiming to conclude on representativeness. We argue that sociological concepts should inform characterizations of study populations in order to increase credibility of conclusions on representativeness. The concept of intersectionality suggests to conceptualize social location as a combination of characteristics such as sex/gender and ethnicity instead of focusing on each feature independently. To contextualize advantages of integrating the concept of intersectionality when investigating representativeness, we reviewed publications that described the baseline population of selected epidemiological cohort studies. Information on the applied methods to characterize the study population was extracted, as well as reported social characteristics. Nearly all reviewed studies reported descriptive statistics of the baseline population and response proportions. In most publications, study populations were characterized according to place of residence, age and sex/gender while other social characteristics were reported irregularly. Differential patterns of representativeness were revealed in analyses that stratified social characteristics by sex/gender or age. Furthermore, the included studies did not explicitly state the theoretical approach that underlay their description of the study population. Intersectionality might be particularly fruitful when applied to descriptions of representativeness, because this concept provides an understanding of social location that has been developed based on situated experiences of people at the intersection of multiple axes of social power relations. An intersectional perspective, hence, contributes to approximate social complexity of study populations and might contribute to increase validity of conclusions on representativeness of population-based studies.

"How do online and offline sampling compare in a multinational study of drug use and nightlife behaviour?"

BACKGROUND

Online sampling is widely used to recruit hard to reach samples such as drug users at nightlife events. We conducted the first study comparing differences in demographics, drug use and nightlife behaviour between an online sample of young adults engaging with the European nightlife scene, and an offline sample recruited at nightclubs and festivals in Europe.

METHODS

Online participants who attended at least six nightlife events in the past 12 months were recruited using social media advertising (May-November 2017). Offline participants were recruited at nightclubs and festivals using a random intercept method (May-November 2017). Samples were compared with respect to age, gender, past year use of alcohol, cannabis, cocaine, ecstasy/MDMA and amphetamines, and past year attendance at nightclubs, licensed festivals, illegal festivals, pubs and house-parties.

RESULTS

6153 online and 3529 offline participants were recruited. When adjusting for differences in age and gender, online participants were less likely to have used each drug and to have attended illegal festivals, pubs and house-parties in the past 12 months. The online sample also used each drug and attended each venue, with the exception of nightclubs, less frequently on average than offline participants. Adjusted odds ratios (range 0.37 to 1.39) and regression coefficients (range -0.84 to 0.07) indicate that the majority of observed differences between the samples were of a small effect size.

CONCLUSIONS

Estimates of drug use and nightlife engagement are more conservative when using online sampling compared to venue based sampling. Observed differences were generally small in effect, indicating good overall representativeness when using online sampling in the European nightlife scene.

Evaluation of the representativeness and generalizability of Japanese clinical trials for localized rectal/colon cancer: Comparing participants in the Japan Clinical Oncology Group study with patients in Japanese registries

INTRODUCTION

It is unclear if clinical trial results including patients who meet trial eligibility criteria, are applicable to actual patients in daily practice (generalizability). Moreover, the extent to which are trial participants different from patients seen in daily practice (representativeness) is also unclear. The aim of this study was to evaluate the representativeness of the patients registered in randomized clinical trials to patients in daily practice and examine the generalizability of trial results to daily practice.

METHODS

We compared the results of surgical trials conducted by the Japan Clinical Oncology Group with data from two Japanese cancer registries, representing patients seen in daily practice. We compared overall survival (OS) between trial participants and registry patients to evaluate representativeness of trial participants. We then compared the OS of registry patients who received open surgery (OP) and laparoscopic surgery (LAP) to evaluate the generalizability of trial results.

RESULTS

We analyzed 3051 patients (701 in JCOG0212, 2350 registry patients) with rectal cancer and 3116 patients (1057 in JCOG0404, 2059 registry patients) with colon cancer. Trial participants tended to possess lower clinical stages. Multivariable analyses revealed registry patients with significantly worse survival compared with trial participants. The hazard ratio of LAP to OP among registry patients was 0.305 (95% CI; 0.048-2.188), which did not meet the prespecified generalizability criteria of 0.9.

CONCLUSIONS

Our results failed to ensure either the representativeness or generalizability of clinical trial results, compared to daily practice. Careful considerations are required when applying trial results to patients in daily practice.

Representativeness of an air quality monitoring station for PM2.5 and source apportionment over a small urban domain

In this study, PM_2.5 concentrations together with the water-soluble ionic compounds and total elements were simultaneously measured at 16 sites in the city of Varese located in Northern Italy within a domain of 2 × 2 km². The center point of this domain consisted of an existing urban air quality monitoring station. The representativeness of the monitoring station for PM_2.5 mass and chemical composition was estimated using a methodology relying on statistical/geostatistical analyses. Source apportionment by means of the Chemical Mass Balance (CMB) receptor model was also performed to evaluate the spatial distribution of source contribution throughout the domain. Very high soluble fraction was found for Cd, Sb, K and V, indicating the anthropogenic origin of those elements. The geostatistical analysis/mapping showed that the monitoring station captured the spatial variation of PM_2.5 and most of the anthropogenic originated elements, e.g., As, Cd and V, whereas it did not captured the spatial patterns of the ones originated from both natural and anthropogenic sources, e.g., Na, Ni, Pb, K, Zn, Fe, Cr, and Ti. The CMB source contribution estimations in the monitoring station were at least 25% different from many sites of the domain for PM_2.5. The significant spatial variation in concentrations and source contribution estimates showed that the monitoring station could not be considered representative for the air quality monitoring studies with exposure assessment and source apportionment purposes in Varese.

Neurocognitive processes underlying heuristic and normative probability judgments

Judging two events in combination (A&B) as more probable than one of the events (A) is known as a conjunction fallacy. According to dual-process explanations of human judgment and decision making, the fallacy is due to the application of a heuristic, associative cognitive process. Avoiding the fallacy has been suggested to require the recruitment of a separate process that can apply normative rules. We investigated these assumptions using functional magnetic resonance imaging (fMRI) during conjunction tasks. Judgments, whether correct or not, engaged a network of brain regions identical to that engaged during similarity judgments. Avoidance of the conjunction fallacy additionally, and uniquely, involved a fronto-parietal network previously linked to supervisory, analytic control processes. The results lend credibility to the idea that incorrect probability judgments are the result of a representativeness heuristic that requires additional neurocognitive resources to avoid.

The European gonococcal antimicrobial surveillance programme (Euro-GASP) appropriately reflects the antimicrobial resistance situation for Neisseria gonorrhoeae in the European Union/European Economic Area

Background

European Gonococcal Antimicrobial Surveillance Programme (Euro-GASP) antimicrobial resistance (AMR) data are used to inform gonorrhoea treatment guidelines; therefore the data need to be robust and representative. We assessed the extent to which Euro-GASP reflects national measures of the AMR situation for Neisseria gonorrhoeae across the European Union/European Economic Area (EU/EEA).

Methods

We compared data from Euro-GASP with published national gonococcal AMR data from 15 countries for azithromycin, cefixime and ciprofloxacin for the period 2009 to 2013 and performed Poisson regression to identify differences (p < 0.05) between the proportions of resistant isolates. The 2014 Euro-GASP AMR data for each country (n = 19) were weighted to account for differences in the distribution of patient characteristics between Euro-GASP and EU/EEA epidemiological gonorrhoea surveillance data. Data were compared to determine whether estimates of resistance levels differed with regards to the 5% threshold used to assess the clinical utility of first-line gonorrhoea treatments. We assessed the quality of decentralised testing by comparing AMR data for isolates tested both centrally and in the participating laboratories, and by evaluating external quality assessment (EQA) performance.

Results

There was no significant difference for azithromycin, cefixime and ciprofloxacin resistance when Euro-GASP country data were compared with data from national reports. Weighting slightly altered the Euro-GASP AMR estimates (by between − 4.7 and 4.7% from the unweighted estimates). Weighting resulted in greater changes in estimates of resistance to azithromycin (from − 9.5 to 2.7%) and ciprofloxacin (from − 14.8 to 17.9%) in countries with low isolate numbers and low completeness of reporting (n = 3). Weighting caused AMR levels to fall below or above the 5% threshold for cefixime or azithromycin, respectively in only two countries. Susceptibility category data submitted from the decentralised Euro-GASP laboratories were concordant with the Euro-GASP data (> 90%). EQA performance was also good; < 5% of the minimum inhibitory concentration (MIC) results differed by > 4-fold from the modal MIC of the EQA isolate.

Conclusions

The overall prevalence of AMR reported by Euro-GASP reflects closely the AMR situation for N. gonorrhoeae in the EU/EEA. Euro-GASP data can be used to provide robust AMR estimates to inform the European guideline for the management of gonorrhoea.

Early intervention in psychiatry: scotomas, representativeness, and the lens of clinical populations

Evidence supporting early intervention in mental health has gained prominence in recent years, with services for first episode psychosis having led the way. Despite this momentum, however, the extent to which rapidly accumulating data has been collected in samples resembling real-world clinical populations remains unclear. Kline et al. compare and contrast two groups experiencing a first episode of psychosis: research participants, and a clinical sample receiving early intervention services at the same health centre. They find key differences-including the underrepresentation of vulnerable groups and surprisingly little overlap between the two samples-that should prompt reflection about blind spots, filters between research and clinical care, and how to tie the generation of evidence to practice-based research.

Non-response and external validity in a school-based quasi-experimental study 'The Healthy Primary School of the Future': A cross-sectional assessment

Limited evidence is available about (non)-representativeness of participants in health-promoting interventions. The Dutch Healthy Primary School of the Future (HPSF)-study is a school-based study aiming to improve health through altering physical activity and dietary behaviour, that started in 2015 (registered in ClinicalTrials.gov on 14-06-2016, NCT02800616). The study has a response rate of 60%. A comprehensive non-responder analysis was carried out, and responders were compared with schoolchildren from the region and the Netherlands using a cross-sectional design. External sources were consulted to collect non-responder, regional, and national data regarding relevant characteristics including sex, demographics, health, and lifestyle. The Chi-square test, Mann-Whitney U test, or Student's t-test were used to analyse differences. The analyses showed that responders (n = 494) were comparable with non-responders (n = 348) and regional data (n = 6172) with regard to sex and health. Responders did not significantly differ from regional data with regard to lifestyle. Responders had significantly higher educated parents compared to non-responders and were more often of autochthonous ethnicity compared to regional data. Major differences were observed between responders and schoolchildren in the Netherlands, regarding, among others sex, ethnicity, and parental employment rates. We conclude that a potential healthy-volunteer effect in the HPSF-sample is limited. External validity is high when compared to the regional population but low when compared to the national sample. For future intervention studies, we advise to evaluate outcome measures according to regional/national standards and to cooperate with external parties in early stages of research to be able to assess and enhance generalisability.

Does the use of reference organisms in radiological impact assessments provide adequate protection of all the species within an environment?

Non-human biota in radiological risk assessment is typically evaluated using Reference Organisms (ROs) or Reference Animals and Plants (RAPs), for all exposure situations. However, it still remains open whether the use of an increased number of species would improve the ability to demonstrate protectiveness of the environment. In this paper, the representativeness of a broader list of fauna is tested in terms of the geometrical characteristics and habits for radiological risk assessments in the case of routine discharges from a nuclear installation: the Cadarache centre. A list of terrestrial animal species, compiled from ecological inventories carried out around it was evaluated. A first survey around the centre inventoried >400 terrestrial fauna species, which were then filtered to reduce the number to 28 species for which dose assessments were carried out. Despite the differences between geometries for those site-specific species and the ROs (including RAPs), the absorbed dose rates calculated for both were very close (within a factor of two). Regardless of the studied organism, the absorbed dose rates calculated for the discharge scenario were mainly related to internal exposure, particularly for tritium (³H) and carbon 14 (¹⁴C), showing that there would be an acceptable dose rates difference between species from the same organism group. Additionally, sensitivity analyses were conducted to determine if the use of generic, predefined ROs was enough to assure an adequate protection of endangered species. It was observed that for every radionuclide the difference between assessments for site-specific species and ROs are unlikely to exceed a factor of 3. Hence, the result of this evaluation indicates that the use of generic ROs for non-human biota radiological risk assessment covers sufficiently other species, including endangered ones.

A tool to guide the selection of impact categories for LCA studies by using the representativeness index

Understanding the environmental profile of a product computed from the Life Cycle Assessment (LCA) framework is sometimes challenging due to the high number of environmental indicators involved. The objective here, in guiding interpretation of LCA results, is to highlight the importance of each impact category for each product alternative studied. For a given product, the proposed methodology identifies the impact categories that are worth focusing on, relatively to a whole set of products from the same cumulated database. The approach extends the analysis of Representativeness Indices (RI) developed by Esnouf et al. (2018). It proposes a new operational tool for calculating RIs at the level of impact categories for a Life Cycle Inventory (LCI) result. Impact categories and LCI results are defined as vectors within a standardized vector space and a procedure is proposed to treat issues coming from the correlation of impact category vectors belonging to the same Life Cycle Impact Assessment (LCIA) method. From the cumulated ecoinvent database, LCI results of the Chinese and the German electricity mixes illustrate the method. Relevant impact categories of the EU-standardized ILCD method are then identified. RI results from all products of a cumulated LCI database were therefore analysed to assess the main tendencies of the impact categories of the ILCD method. This operational approach can then significantly contribute to the interpretation of the LCA results by pointing to the specificities of the inventories analysed and for identifying the main representative impact categories.

Representativeness of variation benchmark datasets

Background

Benchmark datasets are essential for both method development and performance assessment. These datasets have numerous requirements, representativeness being one. In the case of variant tolerance/pathogenicity prediction, representativeness means that the dataset covers the space of variations and their effects.

Results

We performed the first analysis of the representativeness of variation benchmark datasets. We used statistical approaches to investigate how proteins in the benchmark datasets were representative for the entire human protein universe. We investigated the distributions of variants in chromosomes, protein structures, CATH domains and classes, Pfam protein families, Enzyme Commission (EC) classifications and Gene Ontology annotations in 24 datasets that have been used for training and testing variant tolerance prediction methods. All the datasets were available in VariBench or VariSNP databases. We tested also whether the pathogenic variant datasets contained neutral variants defined as those that have high minor allele frequency in the ExAC database. The distributions of variants over the chromosomes and proteins varied greatly between the datasets.

Conclusions

None of the datasets was found to be well representative. Many of the tested datasets had quite good coverage of the different protein characteristics. Dataset size correlates to representativeness but only weakly to the performance of methods trained on them. The results imply that dataset representativeness is an important factor and should be taken into account in predictor development and testing.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2478-6) contains supplementary material, which is available to authorized users.

Study design and characteristics of the Luxembourg European Health Examination Survey (EHES-LUX)

Background

The European Health Examination Survey in Luxembourg (EHES-LUX) is a population based survey performed from 2013 to 2015 with the aim to establish baseline information on the general health status of the Luxembourg population aged 25 to 64 years. The paper introduces the study design, recruitment method and representativeness of the sample, and summarizes the sociodemographic characteristics of participants and the prevalence of major health outcomes.

Methods

EHES-LUX is based on a random sample representative of the population of Luxembourg based on gender, age and district of residence. The sample size of the study was determined to provide accurate prevalence estimates for major chronic conditions. During two visits, data were collected from participants through a questionnaire (personal data, health status and health care), medical examinations (anthropometric measures, electrocardiogram and spirometry) and biological analysis (blood, urine and hair). Means and frequencies were used to describe the general characteristics of the population and a one-way ANOVA to test the representativeness of the sample and the comparability of participants and non-participants.

Results

A total of 1529 individuals participated in this study (participation rate of 24.1%). Differences between participants and non-participants based on gender, age and district of residence were corrected by sampling weights. The mean age (±SD) of participants was 44.9 (±10.1) years, of which 52.8% were women. Based on clinical measurements, nearly 20% of participants were obese and more than one in three participants were overweight. From measurements (respectively from self-report), 22.0% (respectively 12.2%) were hypertensive, 49.3% (respectively 22.5%) had hypercholesterolemia, 3.5% (respectively 3.7%) had diabetes and 7.6% (respectively 6.0%) had depressive symptoms.

Conclusions

This nationwide epidemiological study on the general health status of Luxembourg residents provides updated prevalence estimates on a range of major health conditions. This information can be used by health authorities to evaluate policies and public health initiatives. At European level, prevalence data obtained by this study following the EHES-Reference Committee (EHES-RC) recommendations, will be comparable between European countries participating in this program.

Electronic supplementary material

The online version of this article (10.1186/s12889-018-6087-0) contains supplementary material, which is available to authorized users.

[Is the school entrance examination a door opener for health sciences research? : Analyzing study participation of hard-to-reach groups]

BACKGROUND

Additional scientific surveys within the compulsory school entrance examination (SEE) have become increasingly popular, partly because the SEE potentially reaches all socioeconomic groups. However, it has not been sufficiently explored whether selective participation in voluntary supplementary surveys actually results in no selection bias along socioeconomic characteristics. Therefore, the aim of this study is to analyze the participation of potentially hard-to-reach families in a parent survey at the SEE.

MATERIALS AND METHODS

The parent survey on the utilization of community prevention has been linked to the SEE in a community in North Rhine-Westphalia. We compared families with low and higher education (CASMIN classification), families with and without migration background (at least one parent was not born in Germany), as well as single-parent and two-parent families. Using logistic regression we analyzed whether survey participation (n = 3410) and non-participation (n = 346) was different along all three indicators.

RESULTS

Families with low education were slightly more often among the group of participants compared to non-participants (11.2 vs. 8.8%; odds ratio (OR) 1.29; 95% confidence interval (CI) 0.85-1.95) and single-parent families slightly less often (14.1 vs. 17.7%; OR 0.75; 95% CI 0.55-1.02). Families with migration background participated significantly more often (52.9 vs. 46.1%; OR 1.27; 95% CI 1.01-1.60).

CONCLUSIONS

Hard-to-reach families could be recruited for a voluntary parent survey in the SEE to a satisfying degree. This illustrates the potential of the SEE for population-based basic and evaluation research.

Assessing exposure factors in the smartphone generation: Design and evaluation of a smartphone app that collects use patterns of cosmetics and household chemicals

Exposure factors form the basis of reliable exposure estimates. The growing demand for population-specific exposure factors for complex exposure models is challenged by continuously declining response rates in surveys: Current survey methods clearly need a boost by user-friendly and efficient technologies. We compared the performance of a smartphone app to a paper questionnaire based on a survey on exposure factors that offered the choice between both methods and based on an observational study that investigated the performance of both methods. The development costs for smartphone app and paper questionnaire were comparable with 15'000 and 13'500 US-$, respectively. The cost efficiency for the paper questionnaire was much better than for the app, but model calculations show that the cost efficiency of the app improves considerably with adequate promotion and for larger surveys, especially for those with regular repetitions. Barcode scanning of consumer products by app saved time and effort of the participants and enhanced reliability. The app was able to attract the attention of younger adults between 20 and 40 years old: Thus, the limited representativity for younger age groups that sometimes is observed for paper-based surveys may be enhanced by including the option to use an app in a mixed-mode survey.