Calibration and XGBoost reweighting to reduce coverage and non-response biases in overlapping panel surveys: application to the Healthcare and Social Survey.

BACKGROUND: Surveys have been used worldwide to provide information on the COVID-19 pandemic impact so as to prepare and deliver an effective Public Health response. Overlapping panel surveys allow longitudinal estimates and more accurate cross-sectional estimates to be obtained thanks to the larger sample size. However, the problem of non-response is particularly aggravated in the case of panel surveys due to population fatigue with repeated surveys. OBJECTIVE: To develop a new reweighting method for overlapping panel surveys affected by non-response. METHODS: We chose the Healthcare and Social Survey which has an overlapping panel survey design with measurements throughout 2020 and 2021, and random samplings stratified by province and degree of urbanization. Each measurement comprises two samples: a longitudinal sample taken from previous measurements and a new sample taken at each measurement. RESULTS: Our reweighting methodological approach is the result of a two-step process: the original sampling design weights are corrected by modelling non-response with respect to the longitudinal sample obtained in a previous measurement using machine learning techniques, followed by calibration using the auxiliary information available at the population level. It is applied to the estimation of totals, proportions, ratios, and differences between measurements, and to gender gaps in the variable of self-perceived general health. CONCLUSION: The proposed method produces suitable estimators for both cross-sectional and longitudinal samples. For addressing future health crises such as COVID-19, it is therefore necessary to reduce potential coverage and non-response biases in surveys by means of utilizing reweighting techniques as proposed in this study.

Investigating sources of non-response bias in a population-based seroprevalence study of vaccine-preventable diseases in the Netherlands.

BACKGROUND: PIENTER 3 (P3), conducted in 2016/17, is the most recent of three nationwide serological surveys in the Netherlands. The surveys aim to monitor the effects of the National Immunisation Programme (NIP) by assessing population seroprevalence of included vaccine preventable diseases (VPDs). The response rate to the main sample was 15.7% (n = 4,983), following a decreasing trend in response compared to the previous two PIENTER studies (P1, 55.0%; 1995/1996 [n = 8,356] and P2, 33.0%; 2006/2007 [n = 5,834]). Non-responders to the main P3 survey were followed-up to complete a "non-response" questionnaire, an abridged 9-question version of the main survey covering demographics, health, and vaccination status. We assess P3 representativeness and potential sources of non-response bias, and trends in decreasing participation rates across all PIENTER studies. METHODS: P3 invitees were classified into survey response types: Full Participants (FP), Questionnaire Only (QO), Non-Response Questionnaire (NRQ) and Absolute Non-Responders (ANR). FP demographic and health indicator data were compared with Dutch national statistics, and then the response types were compared to each other. Random forest algorithms were used to predict response type. Finally, FPs from all three PIENTERs were compared to investigate the profile of survey participants through time. RESULTS: P3 FPs were in general healthier, younger and higher educated than the Dutch population. Random forest was not able to differentiate between FPs and ANRs, but when predicting FPs from NRQs we found evidence of healthy-responder bias. Participants of the three PIENTERs were found to be similar and are therefore comparable through time, but in line with national trends we found P3 participants were less inclined to vaccinate than previous cohorts. DISCUSSION: The PIENTER biobank is a powerful tool to monitor population-level protection against VPDs across 30 years in The Netherlands. However, future PIENTER studies should continue to focus on improving recruitment from under-represented groups, potentially by considering alternative and mixed survey modes to improve both overall and subgroup-specific response. Whilst non-responder bias is unlikely to affect seroprevalence estimates of high-coverage vaccines, the primary aim of the PIENTER biobank, other studies with varied vaccination/disease exposures should consider the influence of bias carefully.

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.

Impact of different cover letter content and incentives on non-response bias in a sample of Veterans applying for Department of Veterans Affairs disability benefits: a randomized, 3X2X2 factorial trial.

BACKGROUND: Non-random non-response bias in surveys requires time-consuming, complicated, post-survey analyses. Our goal was to see if modifying cover letter information would prevent non-random non-response bias altogether. Our secondary goal tested whether larger incentives would reduce non-response bias. METHODS: A mailed, survey of 480 male and 480 female, nationally representative, Operations Enduring Freedom, Iraqi Freedom, or New Dawn (OEF/OIF/OND) Veterans applying for Department of Veterans Affairs (VA) disability benefits for posttraumatic stress disorder (PTSD). Cover letters conveyed different information about the survey's topics (combat, unwanted sexual attention, or lifetime and military experiences), how Veterans' names had been selected (list of OEF/OIF/OND Veterans or list of Veterans applying for disability benefits), and what incentive Veterans would receive ($20 or $40). The main outcome, non-response bias, measured differences between survey respondents' and sampling frame's characteristics on 8 administrative variables, including Veterans' receipt of VA disability benefits and exposure to combat or military sexual trauma. Analysis was intention to treat. We used ANOVA for factorial block-design, logistic, mixed-models to assess bias and multiple imputation and expectation-maximization algorithms to assess potential missing mechanisms (missing completely at random, missing at random, or not random) of two self-reported variables: combat and military sexual assault. RESULTS: Regardless of intervention, men with any VA disability benefits, women with PTSD disability benefits, and women with combat exposure were over-represented among respondents. Interventions explained 0.0 to 31.2% of men's variance and 0.6 to 30.5% of women's variance in combat non-response bias and 10.2 to 43.0% of men's variance and 0.4 to 31.9% of women's variance in military sexual trauma non-response bias. Non-random assumptions showed that men's self-reported combat exposure was overestimated by 19.0 to 28.8 percentage points and their self-reported military sexual assault exposure was underestimated by 14.2 to 28.4 percentage points compared to random missingness assumptions. Women's self-reported combat exposure was overestimated by 8.6 to 10.6 percentage points and military sexual assault exposure, by 1.2 to 6.9 percentage points. CONCLUSIONS: Our interventions reduced bias in some characteristics, leaving others unaffected or exacerbated. Regardless of topic, researchers are urged to present estimates that include all three assumptions of missingness.

Evaluating Non-response Bias in a Parent-Based College Alcohol Intervention.

Background: The purpose of this study was to address a dearth in the literature on non-response bias in parent-based interventions (PBIs) by investigating parenting constructs that might be associated with whether a parent volunteers to participate in a no-incentive college drinking PBI. Method: Incoming first-year students (N = 386) completed an online questionnaire that included items assessing plausible predictors of participation in a PBI (students' drinking, perceptions of parents' harm-reduction and zero-tolerance alcohol communication, whether parents allowed alcohol, and changes in parents' alcohol rules). Four months later, all parents of first-year students at the study university were invited to join the PBI, which was described as a resource guide to teach them how to help their student navigate the college transition and prepare them for life at their university. Results: Parents who signed up for the intervention used greater harm-reduction communication than those who did not sign up, were more likely to have allowed alcohol use, and signing up was significantly associated with student reports that fathers became less strict toward drinking after high school. Students' drinking and zero-tolerance communication did not significantly differ between the groups. Conclusion: Results indicate that non-response bias can be an issue when utilizing a real-world, non-RCT recruitment approach to invite parents into a PBI (i.e., non-incentivized, inviting all parents). Findings suggest that more comprehensive recruitment strategies may be required to increase parent diversity in PBIs.

A framework for exploring non-response patterns over time in health surveys.

BACKGROUND: Most health surveys have experienced a decline in response rates. A structured approach to evaluate whether a decreasing - and potentially more selective - response over time biased estimated trends in health behaviours is lacking. We developed a framework to explore the role of differential non-response over time. This framework was applied to a repeated cross-sectional survey in which the response rate gradually declined. METHODS: We used data from a survey conducted biannually between 1995 and 2017 in the city of Rotterdam, The Netherlands. Information on the sociodemographic determinants of age, sex, and ethnicity was available for respondents and non-respondents. The main outcome measures of prevalence of sport participation and watching TV were only available for respondents. The framework consisted of four steps: 1) investigating the sociodemographic determinants of responding to the survey and the difference in response over time between sociodemographic groups; 2) estimating variation in health behaviour over time; 3) comparing weighted and unweighted prevalence estimates of health behaviour over time; and 4) comparing associations between sociodemographic determinants and health behaviour over time. RESULTS: The overall response rate per survey declined from 47% in 1995 to 15% in 2017. The probability of responding was higher among older people, females, and those with a Western background. The response rate declined in all subgroups, and a faster decline was observed among younger persons and those with a non-Western ethnicity as compared to older persons and those with a Western ethnicity. Variation in health behaviours remained constant. Prevalence estimates and associations did not follow the changes in response over time. On the contrary, the difference in probability of participating in sport gradually decreased between males and females, while no differential change in the response rate was observed. CONCLUSIONS: Providing insights on non-response patterns over time is essential to understand whether declines in response rates may have influenced estimated trends in health behaviours. The framework outlined in this study can be used for this purpose. In our example, in spite of a major decline in response rate, there was no evidence that the risk of non-response bias increased over time.

The effect of home visits as an additional recruitment step on the composition of the final sample: a cross-sectional analysis in two study centers of the German National Cohort (NAKO).

BACKGROUND: Participation in epidemiologic studies has been declining over the last decades. In addition to postal invitations and phone calls, home visits can be conducted to increase participation. The aim of this study was therefore to evaluate the effects of home visits in terms of response increase and composition of the additionally recruited and final sample. METHODS: In the framework of the German National Cohort (NAKO) recruitment process, two of 18 study centers, Halle (Saale) and Berlin-Center, performed home visits as additional recruitment step after postal invitation and reminders. Response increase was calculated and differences between participants recruited via home visits and standard recruitment were examined. Proportions are presented as percentages with 95%-confidence intervals. RESULTS: In the general population in Halle, 21.3-22.8% participated after postal invitation and two reminders in the five assessed recruitment waves. The increase of the overall response was 2.8 percentage points (95%confidence interval: 1.9-4.0) for home visits compared to 2.4 percentage points (95%CI: 1.7-3.3) for alternatively sent third postal reminder. Participants recruited via home visits had similar characteristics to those recruited via standard recruitment. Among persons of Turkish descent in Berlin-Center site of the NAKO, home visits conducted by native speakers increased the participation of women, persons living together with their partner, were born in Turkey, had lower German language skills, lower-income, lower education, were more often smokers and reported more often diabetes and depression to a degree which changed overall estimates for this subsample. CONCLUSIONS: As an additional recruitment measure in the general population, home visits increased response only marginally, and the through home visits recruited participants did not differ from those already recruited. Among persons with migration background, home visits by a native speaker increased participation of persons not reached by the standard recruitment, but the effects of using a native speaker approach could not be separated from the effect of home visits.

Increasing questionnaire response: evidence from a nested RCT within a longitudinal birth cohort study.

BACKGROUND: High response rates are essential when questionnaires are used within research, as representativeness can affect the validity of studies and the ability to generalise the findings to a wider population. The study aimed to measure the response rate to questionnaires from a large longitudinal epidemiological study and sought to determine if any changes made throughout data collection had a positive impact on the response to questionnaires and addressed any imbalance in response rates by participants' levels of deprivation. METHODS: Data were taken from a prospective, comparative study, designed to examine the effects of the reintroduction of water fluoridation on children's oral health over a five-year period. Response rates were analysed for the first year of data collection. During this year changes were made to the questionnaire layout and cover letter to attempt to increase response rates. Additionally a nested randomised control trial compared the effect on response rates of three different reminders to complete questionnaires. RESULTS: Data were available for 1824 individuals. Sending the complete questionnaire again to non-responders resulted in the highest level of response (25%). A telephone call to participants was the only method that appeared to address the imbalance in deprivation, with a mean difference in deprivation score of 2.65 (95% CI -15.50 to 10.20) between the responders and non-responders. CONCLUSIONS: Initially, low response rates were recorded within this large, longitudinal study giving rise to concerns about non-response bias. Resending the entire questionnaire again was the most effective way of reminding participants to complete the questionnaire. As this is a less labour intensive method than for example, calling participants, more time can then be spent targeting groups who are underrepresented. In order to address these biases, data can be weighted in order to draw conclusions about the population.

Patient satisfaction and survey response in 717 hospital surveys in Switzerland: a cross-sectional study.

BACKGROUND: The association between patient satisfaction and survey response is only partly understood. In this study, we describe the association between average satisfaction and survey response rate across hospital surveys, and model the association between satisfaction and propensity to respond for individual patients. METHODS: Secondary analysis of patient responses (166'014 respondents) and of average satisfaction scores and response rates obtained in 717 annual patient satisfaction surveys conducted between 2011 and 2015 at 164 Swiss hospitals. The satisfaction score was the average of 5 items scored between 0 and 10. The association between satisfaction and response propensity in individuals was modeled as the function that predicted best the observed response rates across surveys. RESULTS: Among the 717 surveys, response rates ranged from 16.1 to 80.0% (pooled average 49.8%), and average satisfaction scores ranged from 8.36 to 9.79 (pooled mean 9.15). At the survey level, the mean satisfaction score and response rate were correlated (r = 0.61). This correlation held for all subgroups of surveys, except for the 5 large university hospitals. The estimated individual response propensity function was "J-shaped": the probability of responding was lowest (around 20%) for satisfaction scores between 3 and 7, increased sharply to about 70% for those maximally satisfied, and increased slightly for the least satisfied. Average satisfaction scores projected for 100% participation were lower than observed average scores. CONCLUSIONS: The most satisfied patients were the most likely to participate in a post-hospitalization satisfaction survey. This tendency produces an upward bias in observed satisfaction scores, and a positive correlation between average satisfaction and response rate across surveys.

The impact of survey mode on the response rate in a survey of the factors that influence Minnesota physicians' disclosure practices.

BACKGROUND: There is evidence that the physician response rate is declining. In response to this, methods for increasing the physician response rate are currently being explored. This paper examines the response rate and extent of non-response bias in a mixed-mode study of Minnesota physicians. METHODS: This mode experiment was embedded in a survey study on the factors that influence physicians' willingness to disclose medical errors and adverse events to patients and their families. Physicians were randomly selected from a list of licensed physicians obtained from the Minnesota Board of Medical Practice. Afterwards, they were randomly assigned to either a single-mode (mail-only or web-only) or mixed-mode (web-mail or mail-web) design. Differences in response rate and nonresponse bias were assessed using Fischer's Exact Test. RESULTS: The overall response rate was 18.60%. There were no statistically significant differences in the response rate across modes (p - value = 0.410). The non-response analysis indicates that responders and non-responders did not differ with respect to speciality or practice location. CONCLUSIONS: The mode of administration did not affect the physician response rate.

Cancer survivors not participating in observational patient-reported outcome studies have a lower survival compared to participants: the population-based PROFILES registry.

PURPOSE: The 'Patient Reported Outcomes Following Initial treatment and Long-term Evaluation of Survivorship' (PROFILES) registry collects patient-reported outcomes (PROs) from short- and long-term cancer survivors in the Netherlands, in a population-based setting. The aim of this analysis is to assess the generalizability of observational PRO research among cancer survivors by comparing socio-demographic and clinical characteristics, and survival of participants and non-participants in cancer survivors invited for questionnaire research through the PROFILES registry. METHODS: Between 2008 and 2015, cancer survivors with different cancer diagnoses (N = 14,011) were invited to participate in PROFILES registry studies, of whom 69% (N = 9684) participated. Socio-demographic and clinical characteristics and survival data, collected through the Netherlands Cancer Registry, were associated with participation versus non-participation in multivariable logistic regression analyses and cox proportional hazard regression models, respectively. RESULTS: Participants had a significantly better survival compared to non-participants (HR = 1.47, P < .01). Participation was associated with male gender, being 60-70 years old, high socio-economic status, receiving any treatment, receiving radiotherapy, having no comorbidities, and a cancer diagnosis 2-3 years before invitation. Sensitivity analysis demonstrates that the health-related quality of life (HRQoL) might be up to 1.3 points lower (scale 0-100) using hot deck imputation compared to non-imputed participant data. CONCLUSIONS: Cancer survivors not participating in observational PROs research significantly differ from participants, with respect to socio-demographic and clinical characteristics, and survival. Their HRQoL scores may be systematically lower compared to participants. Therefore, even in PRO studies with relatively high participation rates, observed outcomes may represent the healthier patient with better outcomes.

Non-response bias in estimates of prevalence of club-based sport participation from an Australian national physical activity, recreation and sport survey.

BACKGROUND: An estimate of the prevalence of an activity derived from a sample survey is potentially subject to non-response bias, whereby people not involved in the activity are less likely to respond than those involved. Quantifying the extent of non-response bias is generally difficult, since it involves estimating differences between respondents for whom data is directly available from the survey, and non-respondents, for whom data is generally not directly or readily available. However, in the case of the Australian Exercise Recreation and Sport Survey (ERASS), comparative "gold standard" benchmarks exist for some aspects of the survey, in the form of state sporting association (SSA) registration databases, each of which purports to constitute a complete enumeration of club-based players of a particular sport. METHODS: ERASS estimates of the prevalence of participation in four major club-based team sports in the Australian state of Victoria in the year 2010 were compared with prevalences based on numbers of registered participants in the corresponding SSA databases. Comparisons were made for the adult population as a whole (ERASS scope being 15+ years of age), and for strata defined by age and geographical region. Because three of the four sports investigated are strongly sex-specific, no sex breakdowns were conducted. In each case the proportion of ERASS respondents reporting participation, with associated confidence limits, was compared with the corresponding SSA count expressed as a proportion of the population, to form an ERASS/SSA prevalence ratio with associated confidence limits. RESULTS: The 24 ERASS/SSA ratios ranged from 1.72 to 7.80. Most ratios lay in the range 2 to 3. The lower 95% confidence bound for the ratio was greater than 1.0 in 23 out of 24 cases. CONCLUSIONS: ERASS estimates of prevalence of these particular aspects of sport participation were higher than SSA estimates, to statistically significant degrees. The effect sizes (i.e. the discrepancies represented by the ratios) were large enough to be of great practical importance. It is conjectured that non-response bias is the most likely explanation for the discrepancies.

The effectiveness of a monetary incentive offer on survey response rates and response completeness in a longitudinal study.

BACKGROUND: Achieving adequate response rates is an ongoing challenge for longitudinal studies. The World Trade Center Health Registry is a longitudinal health study that periodically surveys a cohort of ~71,000 people exposed to the 9/11 terrorist attacks in New York City. Since Wave 1, the Registry has conducted three follow-up surveys (Waves 2-4) every 3-4 years and utilized various strategies to increase survey participation. A promised monetary incentive was offered for the first time to survey non-respondents in the recent Wave 4 survey, conducted 13-14 years after 9/11. METHODS: We evaluated the effectiveness of a monetary incentive in improving the response rate five months after survey launch, and assessed whether or not response completeness was compromised due to incentive use. The study compared the likelihood of returning a survey for those who received an incentive offer to those who did not, using logistic regression models. Among those who returned surveys, we also examined whether those receiving an incentive notification had higher rate of response completeness than those who did not, using negative binomial regression models and logistic regression models. RESULTS: We found that a $10 monetary incentive offer was effective in increasing Wave 4 response rates. Specifically, the $10 incentive offer was useful in encouraging initially reluctant participants to respond to the survey. The likelihood of returning a survey increased by 30% for those who received an incentive offer (AOR = 1.3, 95% CI: 1.1, 1.4), and the incentive increased the number of returned surveys by 18%. Moreover, our results did not reveal any significant differences on response completeness between those who received an incentive offer and those who did not. CONCLUSIONS: In the face of the growing challenge of maintaining a high response rate for the World Trade Center Health Registry follow-up surveys, this study showed the value of offering a monetary incentive as an additional refusal conversion strategy. Our findings also suggest that an incentive offer could be particularly useful near the end of data collection period when an immediate boost in response rate is needed.

The healthy worker effect: Do health problems predict participation rates in, and the results of, a follow-up survey?

PURPOSE: To determine the impact of the healthy worker effect (HWE) as a bias for the external and internal validity of the follow-up assessment in prospective survey research. Specifically, the study examined (1) whether the health status of respondents at the baseline measurement influenced response at the follow-up survey (external validity) and (2) whether HWE is a threat to internal validity by differential attrition, i.e., whether associations between work and health at baseline differ between stayers and dropouts. METHODS: In a two-wave questionnaire survey with a 2-year time lag comprising 6283 persons, 4392 responded at both time points (response rate 70%). Mental distress and somatic symptoms served as indicators of health. Role conflict and role clarity were indicators of work factors. RESULTS: There were few differences in response rate at follow-up between persons with and without health complaints at the baseline measurement. As response rate increased incrementally with educational level, there seems to be a socio-educational bias, rather than a HWE bias on survey participation. Baseline relationships between work factors and health indicators were equal in magnitude among stayers and dropouts. CONCLUSION: The health status of participants at baseline seems to have little impact on the external and internal validity of the follow-up assessment in prospective survey research. Hence, the findings provide little support to the HWE as a potential bias in prospective studies within occupational health research. A limitation of the study is that the findings do not inform about the impact of the HWE on participation in the baseline assessment.

Does response propensity bias stress audits?

BACKGROUND: Non-response bias in surveys occurs when non-respondents differ from respondents. Methods of dealing with this include measuring 'response propensity'. We propose that response propensity has a trait-like component, measurable within the survey. Covariance of this component with survey items could indicate non-response bias. AIMS: To measure and validate trait-like response propensity, to test whether it co-varied with survey items during a routine stress audit and to test whether a prior staff attitude survey may have been biased. METHODS: Stress survey sent to government employees during a routine audit. We designed two new items to measure trait-like response propensity and completion of a prior staff survey. We calculated an odds ratio, correlations and Mann-Whitney U-tests to assess relationships between trait response propensity, completion of the prior staff survey and current stress survey scores. RESULTS: There were 71 respondents; response rate 68%. The trait response propensity item predicted completion of a prior staff survey (odds ratio 8.75, 95% confidence interval 2.32-33.08). Trait response propensity significantly correlated with two of the 40 survey items and did not significantly correlate with any of the eight 'stressor' sub-scales. Non-respondents to the prior staff survey had a significantly lower risk of stress on two of the eight stressor scales. CONCLUSIONS: Trait response propensity seems to be a valid construct. The weight of evidence does not provide an indication of non-response bias (yet neither does it assure freedom from non-response bias). The prior staff survey may have been affected by non-response bias.

Exploring the role of gut microbiota in advancing personalized medicine.

Ongoing extensive research in the field of gut microbiota (GM) has highlighted the crucial role of gut-dwelling microbes in human health. These microbes possess 100 times more genes than the human genome and offer significant biochemical advantages to the host in nutrient and drug absorption, metabolism, and excretion. It is increasingly clear that GM modulates the efficacy and toxicity of drugs, especially those taken orally. In addition, intra-individual variability of GM has been shown to contribute to drug response biases for certain therapeutics. For instance, the efficacy of cyclophosphamide depends on the presence of Enterococcus hirae and Barnesiella intestinihominis in the host intestine. Conversely, the presence of inappropriate or unwanted gut bacteria can inactivate a drug. For example, dehydroxylase of Enterococcus faecalis and Eggerthella lenta A2 can metabolize L-dopa before it converts into the active form (dopamine) and crosses the blood-brain barrier to treat Parkinson's disease patients. Moreover, GM is emerging as a new player in personalized medicine, and various methods are being developed to treat diseases by remodeling patients' GM composition, such as prebiotic and probiotic interventions, microbiota transplants, and the introduction of synthetic GM. This review aims to highlight how the host's GM can improve drug efficacy and discuss how an unwanted bug can cause the inactivation of medicine.

Later one knows better: the over-reporting of short-time work in firm surveys.

Short-time work (STW) in Germany allows for a lot of flexibility in actual usage. Ex ante, firms notify the Employment Agency about the total number of employees eligible, and, up to the total granted, firms can flexibly choose how many employees actually use STW. In firm-level surveys, which provide timely information on STW in Germany, over-reporting of the number of employees on STW is prevalent. This study explores reasons for STW over-reporting based on a high-frequency and low-cost survey initiated during the Covid-19-pandemic (BeCovid) and a low-frequency and high-cost long-running survey (BP). Merging administrative records on actual use of STW, firms that use STW prove more likely to participate in the BeCovid survey. Multi-establishment firms over-report STW because they tend to report STW for all subfirms. The BP uses more interview time and confirms the over-reporting of STW use in the survey month, while-crucially-the over-reporting drops sharply with a few months of retrospection.

Can non-responding mask or mimic drug effects on pregnancy outcome? Evaluation of case characteristics based on the national Embryotox cohort.

Women and their health care provider (HCP) often seek advice for drug safety in pregnancy at Teratology Information Services (TIS). In turn, TIS ask for details of drug exposure and pregnancy outcome. These data constitute a valuable basis for research on prenatal drug risks in many countries. Non-response to follow-up questionnaires, however, may cause biased study results. To assess the potential of non-response bias, this study based on the German Embryotox cohort compares maternal and HCP characteristics of responders and non-responders. Change in loss of follow-up rates over time is investigated using logistic regression. From 2010 until the end of 2020, 48,410 pregnant women and/or their HCP consented to participation in follow-up. Of these, 25.0 % did not return follow-up questionnaires. Loss rates were similar for patients and HCP but increased over time. Participants from semi-dense populated areas had a smaller loss rate (20.4 %) than those from rural (28.4 %) or urban areas (25.6 %). Responding women were older than non-responders, had a lower BMI, a more positive attitude towards pregnancy, a higher educational level, a lower number of previous pregnancies, smoked less, and indicated alcohol consumption more but social drugs less often. Non-response bias cannot be ruled out in studies based on observational data on drug use in pregnancy as those collected by TIS. However, differences between the complete and lost-to follow-up cohort do not suggest a particularly high or low risk profile for one of the cohorts that might substantially confound study results or even mask or mimic potential drug toxicity.

Combining patient reported outcomes and EHR data to understand population level treatment needs: correcting for selection bias in the migraine signature study.

BACKGROUND: Electronic health records (EHR) data can be used to understand population level quality of care especially when supplemented with patient reported data. However, survey non-response can result in biased population estimates. As a case study, we demonstrate that EHR and survey data can be combined to estimate primary care population prescription treatment status for migraine stratified by migraine disability, without and with adjustment for survey non-response bias. We selected disability as it is associated with survey participation and patterns of prescribing for migraine. METHODS: A stratified random sample of Sutter Health adult primary care (PC) patients completed a digital survey about headache, migraine, and migraine related disability. The survey data from respondents with migraine were combined with their EHR data to estimate the proportion who had prescription orders for acute or preventive migraine treatments. Separate proportions were also estimated for those with mild disability (denoted "mild migraine") versus moderate to severe disability (denoted mod-severe migraine) without and with correction, using the inverse propensity weighting method, for non-response bias. We hypothesized that correction for non-response bias would result in smaller differences in proportions who had a treatment order by migraine disability status. RESULTS: The response rate among 28,268 patients was 8.2%. Among survey respondents, 37.2% had an acute treatment order and 16.8% had a preventive treatment order. The response bias corrected proportions were 26.2% and 11.6%, respectively, and these estimates did not differ from the total source population estimates (i.e., 26.4% for acute treatments, 12.0% for preventive treatments), validating the correction method. Acute treatment orders proportions were 32.3% for mild migraine versus 37.3% for mod-severe migraine and preventive treatment order proportions were 12.0% for mild migraine and 17.7% for mod-severe migraine. The response bias corrected proportions for acute treatments were 24.8% for mild migraine and 26.6% for mod-severe migraine and the proportions for preventive treatment were 8.1% for mild migraine and 12.0% for mod-severe migraine. CONCLUSIONS: In this study, we combined survey data with EHR data to better understand treatment needs among patients diagnosed with migraine. Migraine-related disability is directly related to preventive treatment orders but less so for acute treatments. Estimates of treatment status by self-reported disability status were substantially over-estimated among those with moderate to severe migraine-related disability without correction for non-response bias.

Uncovering survivorship bias in longitudinal mental health surveys during the COVID-19 pandemic.

AIMS: Markedly elevated adverse mental health symptoms were widely observed early in the coronavirus disease-2019 (COVID-19) pandemic. Unlike the U.S., where cross-sectional data indicate anxiety and depression symptoms have remained elevated, such symptoms reportedly declined in the U.K., according to analysis of repeated measures from a large-scale longitudinal study. However, nearly 40% of U.K. respondents (those who did not complete multiple follow-up surveys) were excluded from analysis, suggesting that survivorship bias might partially explain this discrepancy. We therefore sought to assess survivorship bias among participants in our longitudinal survey study as part of The COVID-19 Outbreak Public Evaluation (COPE) Initiative. METHODS: Survivorship bias was assessed in 4039 U.S. respondents who completed surveys including the assessment of mental health as part of The COPE Initiative in April 2020 and were invited to complete follow-up surveys. Participants completed validated screening instruments for symptoms of anxiety, depression and insomnia. Survivorship bias was assessed for (1) demographic differences in follow-up survey participation, (2) differences in initial adverse mental health symptom prevalence adjusted for demographic factors and (3) differences in follow-up survey participation based on mental health experiences adjusted for demographic factors. RESULTS: Adjusting for demographics, individuals who completed only one or two out of four surveys had significantly higher prevalence of anxiety and depression symptoms in April 2020 (e.g. one-survey v. four-survey, anxiety symptoms, adjusted prevalence ratio [aPR]: 1.30, 95% confidence interval [CI]: 1.08-1.55, p = 0.0045; depression symptoms, aPR: 1.43, 95% CI: 1.17-1.75, p = 0.00052). Moreover, individuals who experienced incident anxiety or depression symptoms had significantly higher adjusted odds of not completing follow-up surveys (adjusted odds ratio [aOR]: 1.68, 95% CI: 1.22-2.31, p = 0.0015, aOR: 1.56, 95% CI: 1.15-2.12, p = 0.0046, respectively). CONCLUSIONS: Our findings reveal significant survivorship bias among longitudinal survey respondents, indicating that restricting analytic samples to only respondents who provide repeated assessments in longitudinal survey studies could lead to overly optimistic interpretations of mental health trends over time. Cross-sectional or planned missing data designs may provide more accurate estimates of population-level adverse mental health symptom prevalence than longitudinal surveys.