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The demand for recreational access to wildlife management areas (WMAs) is relatively under-studied subject in human dimensions of wildlife. Management of public lands such as WMAs is challenging due to the diverse preferences of outdoor recreationists. By using mixed-mode survey data collected from sportspersons and other recreationists in Tennessee, this study analyzed the factors that influence the outdoor recreationists' intention to visit WMAs. Although the results indicate a high level of interest among sportspersons and other recreationists, visiting intentions were significantly influenced by site quality and recent experiences but not by perceptions of crowding. Similarly, the intention to visit WMAs was positively related to improvements in recreational services. These findings suggest that investment in recreational services, such as trails, hunting, fishing, and camping facilities, may help to increase public visits and generate significant benefits for visitors and wildlife agencies. [ABSTRACT FROM AUTHOR]

Abstract 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.

Abstract 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.

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. [ABSTRACT FROM AUTHOR]

Abstract 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

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. [ABSTRACT FROM AUTHOR]

Abstract 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.

Declining participation in voluntary establishment surveys poses a risk of increasing non‐response bias over time. In this paper, response rates and non‐response bias are examined for the 2010–2019 IAB Job Vacancy Survey. Using comprehensive administrative data, we formulate and test several theory‐driven hypotheses on survey participation and evaluate the potential of various machine learning algorithms for non‐response bias adjustment. The analysis revealed that while the response rate decreased during the decade, no concomitant increase in aggregate non‐response bias was observed. Several hypotheses of participation were at least partially supported. Lastly, the expanded use of administrative data reduced non‐response bias over the standard weighting variables, but only limited evidence was found for further non‐response bias reduction through the use of machine learning methods. [ABSTRACT FROM AUTHOR]

Abstract 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.

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. • Average loss of follow-up rate was 25 %. • Response rates of patients and of health professionals were similar. • The cohorts with completed and lost follow-up differed in maternal characteristics. • Risk of confounding due to high or low risk profiles appears unlikely. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract 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.

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. [ABSTRACT FROM AUTHOR]

Abstract 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.

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. [ABSTRACT FROM AUTHOR]

The participation rates in epidemiologic cohort studies have declined in recent decades. We aimed to evaluate the effect of home recruitment on participation rate and non-response bias within the individuals with psychosis in a follow-up study. The baseline (1999-2001) and follow-up (2008-2010) studies in the Northern Finland Birth Cohort 1966 consisted of magnetic resonance imaging of the brain, cognitive testing and psychiatric assessment. The participation rates were 67% (54/81) for baseline participants, 10% (5/49) for baseline non-participants and 35% (48/136) for those who were diagnosed with a psychosis after the baseline study. In order to increase participation of the individuals who had participated at the baseline (n=81), those who would not have participated otherwise were offered to be interviewed at home. Altogether 18 follow-up participants were home-recruited. Several illness-related variables were compared between the home-recruited participants, standard protocol participants and non-participants. The home-recruited participants had more symptoms, lower functioning, cognition and total grey matter volume, and higher use of antipsychotics measured at baseline (absolute values of effect sizes 0.60-1.05), compared to standard protocol participants and non-participants. The same differences occurred between the home-recruited and standard protocol participants in the follow-up. By using home recruitment we were able to increase the participation rate and to avoid problems of non-response bias. Effective recruitment may need special efforts in population-based studies for individuals with psychosis. Abbreviations: NFBC1966: The Northern Finland Birth Cohort 1966, CRHC: the Care Register for Health Care, PANSS: the Positive and Negative Syndrome Scale, CGI: the Clinical Global Impression, SOFAS: the Social and Occupational Functioning Assessment Scale, MRI: Magnetic Resonance Imaging, TGM: total grey matter volume, CVLT: the California Verbal Learning Test, VOLT: Visual Object Learning Test, AIM: Abstraction, Inhibition and Working Memory task.

Abstract 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.

Abstract 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.

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. [ABSTRACT FROM AUTHOR]

Surveys of a general population have been a mainstay of leisure and recreation research methods. This study assesses the impact of two different pre-incentives on eliciting a survey response. Two counties with large federal prairie restoration projects and active municipal and county park districts were the study sites. Results show that residents whose pre-incentive was two $1 bills had a significantly higher response rate than residents with a pre-incentive of one $2 bill. With park operations being responsive to needs and preferences of residents, the most accurate representation of the general population of constituents is an important goal in any research effort. Given that pre-incentives have become a standard and sizeable portion of a survey's budget, maximizing the effectiveness of the pre-incentive investment is a small, yet critical, part of connecting research to practice. [ABSTRACT FROM AUTHOR]

Many agricultural researchers are now turning away from the traditional postal surveys to email surveys of farmers – an option that is increasingly viable as digitalisation continues to permeate rural areas. However, email surveys often result in considerably lower response rates. This raises questions about the potential of email surveys to experience non-response bias, where the survey methodology excludes particular sectors of the general population and thus results in responses that do not represent the wider population. In this paper we address the issue of whether agricultural researchers should move from postal surveys to email surveys by comparing the results of two applications of the Norwegian national Trends survey – one to 3000 farmers via email and one to 3000 farmers via standard mail. The postal survey achieved a response rate of 41.1% – almost double that of the email survey at 21.4%. However, analysis of the returns suggested this had not led to greater non-response bias in the email survey. While respondents to the email survey were younger, better educated and more likely to be part-time farmers, comparing the entire survey revealed very few significant differences between the two samples. Where the difference was significant (in particular, attitudes towards technology), the scalar difference was so small that using different survey methods would not have led to different conclusions. Although there was no evidence that the low response rate compromised the email survey, we conclude that postal surveys may still be preferable because (a) there is less scope for non-response bias, and (b) having to double the gross survey size to achieve a sufficient sample size may create additional survey fatigue in the long term. We discuss the applicability of the findings to farm surveys in other countries. • The postal survey had twice as high response rate as the email survey. • Low response rate in the email survey did not compromised the overall quality. • Postal surveys may still be preferable because of higher response rate. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract 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.

Objectives: To provide a methodological reference paper for the inception cohort of the Swiss Spinal Cord Injury Cohort Study (SwiSCI), by detailing its methodological features and reporting on participant characteristics, response rates and non-response bias. Design: Prospective cohort study starting in 2013 in all 4 specialized rehabilitation centres in Switzerland. Subjects: Included are 655 newly diagnosed first rehabilitation patients aged ≥16 years with traumatic or non-traumatic spinal cord injury (TSCI, NTSCI). Methods: Descriptive statistics were used to depict participant characteristics and to compare characteristics of responders and non-responders. Logistic regressions were conducted to estimate non-response bias. Results: The sample consisted of 69% males, with mean age 53.5 years, 57.9% TSCI, 60.7% paraplegia and 78.8% incomplete SCI. Males and younger persons more often sustained TSCI and more severe SCI, resulting in longer duration of rehabilitation. Complete lesions were more prevalent in TSCI compared to NTSCI. The response rate was 47.5% and study participation was less likely in females, older persons, persons with lower functional independence and those with NTSCI. Conclusion: SwiSCI inception cohort data enable the estimation of epidemiological figures of SCI in Switzerland, and prognostic and trajectory modelling of outcomes after SCI to guide policy, service provision and clinical practice.

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

We evaluate the utility of coefficients of variation of response propensities (CVs) as measures of risks of survey variable non‐response biases when monitoring survey data collection. CVs quantify variation in sample response propensities estimated given a set of auxiliary attribute covariates observed for all subjects. If auxiliary covariates and survey variables are correlated, low levels of propensity variation imply low bias risk. CVs can also be decomposed to measure associations between auxiliary covariates and propensity variation, informing collection method modifications and post‐collection adjustments to improve dataset quality. Practitioners are interested in such approaches to managing bias risks, but risk indicator performance has received little attention. We describe relationships between CVs and expected biases and how they inform quality improvements during and post‐data collection, expanding on previous work. Next, given auxiliary information from the concurrent 2011 UK census and details of interview attempts, we use CVs to quantify the representativeness of the UK Labour Force Survey dataset during data collection. Following this, we use survey data to evaluate inference based on CVs concerning survey variables with analogues measuring the same quantities among the auxiliary covariate set. Given our findings, we then offer advice on using CVs to monitor survey data collection. [ABSTRACT FROM AUTHOR]

OBJECTIVES: The study aim was to examine (i) non-response bias between responders and non-responders, and (ii) whether the association between self-reported sickness absence (SA) and register-based SA differed by gender, age, sector, or physically demanding work. METHODS: The responses of 8110 participants to a question on self-reported SA in past 12 months in the Work Environment and Health in Denmark Survey (2014) was linked to 12 months of SA data from the Danish Register of Work Absence. We used logistic regression for the non-response analysis and Poisson regression to examine associations. RESULTS: Responders had on average 0.5 days less SA per year than non-responders. Public employees had a higher response rate than private employees (approximately five percentage points), women had a higher rate than men (approximately nine percentage points), and older employees a higher rate than younger employees (approximately nine percentage points in ten years). Self-reported SA correlated highly with register-based SA (Spearman’s rank correlation=0.76). In general, responders with few SA days (30) over-reported their SA. Women under-reported significantly more than men (average difference one day); older employees under-reported significantly more than younger employees (difference between age groups 18–29 and 60–64 was 1.7 days). Differences between sectors or levels of physically demanding work were non-significant. CONCLUSIONS: Self-reported SA data may be influenced by non-response bias, and different accuracy in different demographic groups. When available, the use of register-based SA data is recommended.

Low response rate has been considered as a matter in a survey. Even though researcher has applied techniques to enhance the response rate, they very often still experience low rate of response. This paper tries to share the challenging experience in dealing with low response rate in the context of international business research. This is a questionnaire survey of small firms in Indonesia that were doing business abroad. The results show that it is more important to select the most effective survey method rather than techniques to enhance response rate in order to deal with local condition. Survey by knocking the door is found to be the best suited alternative for maximizing the response rate.

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. [ABSTRACT FROM AUTHOR]

User-generated hotel ratings have been found to be an important element in customers' decision making. Nevertheless, most hotel ratings online show average ratings that are extremely positive. Thus, the question is raised of whether online ratings reflect objective evaluation of the reviewers. This study examines the distribution of online ratings and compares it the distribution of offline ratings. Online hotel score ratings reported on Booking.com were extracted and compared with offline rating scores from a field survey. Online and offline hotel ratings of eight hotels located in Seoul were collected. The ratings were compared using Welch's t-test. Overall, both online and offline ratings for all eight hotels show generally positive distribution curves. The distribution curves exhibit shapes analogous to those considered to contain self-selection bias. The randomized offline ratings did not produce more moderate ratings as predicted. Thus, no indication of non-response bias was found. Practically, this study supports the notion that hotels listed on online travel agencies such as Booking.com may already have passed certain quality criteria, thereby providing competitive marketplaces for customers searching for hotels online. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract 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.

Purpose: Declining response rates threaten the generalizability of health surveys. We investigate (1) the effect of item order on response rate; (2) characteristics of early , late and non-responders; and (3) potential non-response bias in a population-based health survey of childhood, adolescent and young adult cancer survivors (CAYACS).Methods: We mailed a questionnaire survey to 5361 eligible CAYACS identified by the Cancer Registry of Norway (CRN), representing a range of cancer diagnoses. The 302-item questionnaire included a range of survivorship-related questions and validated patient-reported outcome measures. To investigate item-order effects on response rates, we constructed two versions of the questionnaire presenting cancer-related or socio-demographic items first. The CRN provided demographic and clinical information for the total population. Risk of non-response bias was estimated by (1) comparing outcomes between early and late responders (answered after a reminder), and (2) by applying inverse probability of participation weights to construct a total population (with 100% response) and then compare 21 a priori selected outcomes between early responders, all responders (early + late) and the total population (all eligible).Results: Survey item order did not affect response rates (cancer first 49.8% vs socio-demographic first 50.2%). Shorter time since diagnosis, male gender and a malignant melanoma diagnosis remained significant predictors of non-response in a multivariable multinomial regression model. There were no significant differences on 16/21 survey outcomes between early and late responders, and 18/21 survey outcomes between early responders, all responders and the total population.Conclusion: Despite a modest response rate, we found little evidence for a response bias in our study.Implications For Cancer Survivors: Surveys of survivor-reported outcomes with low response rates may still be valuable and generalizable to the total survivor population. [ABSTRACT FROM AUTHOR]

A continuing decline in an institution's response rates for student evaluations of teaching (SET) raised faculty concerns about non-response bias in summary statistics. In response, this institution's SET stakeholders partnered with a Marketing Methods class section to create strategies for increasing response rates. The project was also an exercise in organisational citizenship behaviour (OCB) training because students in that class section received intensive training on how SET feedback is valued by instructors and its role in improving their academic organisation. Within the context of OCB theory, this article finds student exposure to OCB training increases SET response rates because knowing how SET benefits their organisation increases unit-level response propensity for member surveys intended to improve their institution. In the year of the OCB training, SET response rates increased by 26%, though the increases did not persist into later academic years. The response rate increases are realised across all demographic groups with disproportionate increases among low response rate groups, including low performing students, men and ethnic minorities. [ABSTRACT FROM AUTHOR]

Abstract Background: The Australian population that relies on mobile phones exclusively has increased from 5% in 2005 to 29% in 2014. Failing to include this mobile‐only population leads to a potential bias in estimates from landline‐based telephone surveys. This paper considers the impacts on selected health prevalence estimates with and without the mobile‐only population. Methods: Using data from the Australian Health Survey – which, for the first time, included a question on telephone status – we examined demographic, geographic and health differences between the landline‐accessible and mobile‐only population. These groups were also compared to the full population, controlling for the sampling design and differential non‐response patterns in the observed sample through weighting and benchmarking. Results: The landline‐accessible population differs from the mobile‐only population for selected health measures resulting in biased prevalence estimates for smoking, alcohol risk and private health insurance coverage in the full population. The differences remain even after adjusting for age and gender. Conclusions: Using landline telephones only for conducting population health surveys will have an impact on prevalence rate estimates of health risk factors due to the differing profiles of the mobile‐only population from the landline‐accessible population.

Conducting survey interviews on the internet has become an attractive method for lowering data collection costs and increasing the frequency of interviewing, especially in longitudinal studies. However, the advantages of the web mode for studies with frequent re-interviews can be offset by the serious disadvantage of low response rates and the potential for nonresponse bias to mislead investigators. Important life events, such as changes in employment status, relationship changes, or moving can cause attrition from longitudinal studies, producing the possibility of attrition bias. The potential extent of such bias in longitudinal web surveys is not well understood. We use data from the Relationship Dynamics and Social Life (RDSL) study to examine the potential for a mixed-device approach with active mode switching to reduce attrition bias. The RDSL design allows panel members to switch modes by integrating telephone interviewing into a longitudinal web survey with the objective of collecting weekly reports. We found that in this design allowing panel members to switch modes kept more participants in the study compared to a web only approach. The characteristics of persons who ever switched modes are different than those who did not – including not only demographic characteristics, but also baseline characteristics related to pregnancy and time-varying characteristics that were collected after the baseline interview. This was true in multivariate models that control for multiple of these dimensions simultaneously. We conclude that mode options and mode switching is important for the success of longitudinal web surveys to maximize participation and minimize attrition.

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Huang, Khan, Zheng, Lee, Li and Khan.)