Methods to increase response to postal and electronic questionnaires.

BACKGROUND: Self-administered questionnaires are widely used to collect data in epidemiological research, but non-response reduces the effective sample size and can introduce bias. Finding ways to increase response to postal and electronic questionnaires would improve the quality of epidemiological research. OBJECTIVES: To identify effective strategies to increase response to postal and electronic questionnaires. SEARCH METHODS: We searched 14 electronic databases up to December 2021 and manually searched the reference lists of relevant trials and reviews. We contacted the authors of all trials or reviews to ask about unpublished trials; where necessary, we also contacted authors to confirm the methods of allocation used and to clarify results presented. SELECTION CRITERIA: Randomised trials of methods to increase response to postal or electronic questionnaires. We assessed the eligibility of each trial using pre-defined criteria. DATA COLLECTION AND ANALYSIS: We extracted data on the trial participants, the intervention, the number randomised to intervention and comparison groups and allocation concealment. For each strategy, we estimated pooled odds ratios (OR) and 95% confidence intervals (CI) in a random-effects model. We assessed evidence for selection bias using Egger's weighted regression method and Begg's rank correlation test and funnel plot. We assessed heterogeneity amongst trial odds ratios using a Chi2 test and quantified the degree of inconsistency between trial results using the I2 statistic. MAIN RESULTS: Postal We found 670 eligible trials that evaluated over 100 different strategies of increasing response to postal questionnaires. We found substantial heterogeneity amongst trial results in half of the strategies. The odds of response almost doubled when: using monetary incentives (odds ratio (OR) 1.86; 95% confidence interval (CI) 1.73 to 1.99; heterogeneity I2 = 85%); using a telephone reminder (OR 1.96; 95% CI 1.03 to 3.74); and when clinical outcome questions were placed last (OR 2.05; 95% CI 1.00 to 4.24). The odds of response increased by about half when: using a shorter questionnaire (OR 1.58; 95% CI 1.40 to 1.78); contacting participants before sending questionnaires (OR 1.36; 95% CI 1.23 to 1.51; I2 = 87%); incentives were given with questionnaires (i.e. unconditional) rather than when given only after participants had returned their questionnaire (i.e. conditional on response) (OR 1.53; 95% CI 1.35 to 1.74); using personalised SMS reminders (OR 1.53; 95% CI 0.97 to 2.42); using a special (recorded) delivery service (OR 1.68; 95% CI 1.36 to 2.08; I2 = 87%); using electronic reminders (OR 1.60; 95% CI 1.10 to 2.33); using intensive follow-up (OR 1.69; 95% CI 0.93 to 3.06); using a more interesting/salient questionnaire (OR 1.73; 95% CI 1.12 to 2.66); and when mentioning an obligation to respond (OR 1.61; 95% CI 1.16 to 2.22). The odds of response also increased with: non-monetary incentives (OR 1.16; 95% CI 1.11 to 1.21; I2 = 80%); a larger monetary incentive (OR 1.24; 95% CI 1.15 to 1.33); a larger non-monetary incentive (OR 1.15; 95% CI 1.00 to 1.33); when a pen was included (OR 1.44; 95% CI 1.38 to 1.50); using personalised materials (OR 1.15; 95% CI 1.09 to 1.21; I2 = 57%); using a single-sided rather than a double-sided questionnaire (OR 1.13; 95% CI 1.02 to 1.25); using stamped return envelopes rather than franked return envelopes (OR 1.23; 95% CI 1.13 to 1.33; I2 = 69%), assuring confidentiality (OR 1.33; 95% CI 1.24 to 1.42); using first-class outward mailing (OR 1.11; 95% CI 1.02 to 1.21); and when questionnaires originated from a university (OR 1.32; 95% CI 1.13 to 1.54). The odds of response were reduced when the questionnaire included questions of a sensitive nature (OR 0.94; 95% CI 0.88 to 1.00). Electronic We found 88 eligible trials that evaluated over 30 different ways of increasing response to electronic questionnaires. We found substantial heterogeneity amongst trial results in half of the strategies. The odds of response tripled when: using a brief letter rather than a detailed letter (OR 3.26; 95% CI 1.79 to 5.94); and when a picture was included in an email (OR 3.05; 95% CI 1.84 to 5.06; I2 = 19%). The odds of response almost doubled when: using monetary incentives (OR 1.88; 95% CI 1.31 to 2.71; I2 = 79%); and using a more interesting topic (OR 1.85; 95% CI 1.52 to 2.26). The odds of response increased by half when: using non-monetary incentives (OR 1.60; 95% CI 1.25 to 2.05); using shorter e-questionnaires (OR 1.51; 95% CI 1.06 to 2.16; I2 = 94%); and using a more interesting e-questionnaire (OR 1.85; 95% CI 1.52 to 2.26). The odds of response increased by a third when: offering survey results as an incentive (OR 1.36; 95% CI 1.16 to 1.59); using a white background (OR 1.31; 95% CI 1.10 to 1.56); and when stressing the benefits to society of response (OR 1.38; 95% CI 1.07 to 1.78; I2 = 41%). The odds of response also increased with: personalised e-questionnaires (OR 1.24; 95% CI 1.17 to 1.32; I2 = 41%); using a simple header (OR 1.23; 95% CI 1.03 to 1.48); giving a deadline (OR 1.18; 95% CI 1.03 to 1.34); and by giving a longer time estimate for completion (OR 1.25; 95% CI 0.96 to 1.64). The odds of response were reduced when: "Survey" was mentioned in the e-mail subject (OR 0.81; 95% CI 0.67 to 0.97); when the email or the e-questionnaire was from a male investigator, or it included a male signature (OR 0.55; 95% CI 0.38 to 0.80); and by using university sponsorship (OR 0.84; 95%CI 0.69 to 1.01). The odds of response using a postal questionnaire were over twice those using an e-questionnaire (OR 2.33; 95% CI 2.25 to 2.42; I2 = 98%). Response also increased when: providing a choice of response mode (electronic or postal) rather than electronic only (OR 1.76 95% CI 1.67 to 1.85; I2 = 97%); and when administering the e-questionnaire by computer rather than by smartphone (OR 1.62 95% CI 1.36 to 1.94). AUTHORS' CONCLUSIONS: Researchers using postal and electronic questionnaires can increase response using the strategies shown to be effective in this Cochrane review.

Historic air pollution exposure and long-term mortality risks in England and Wales: prospective longitudinal cohort study.

INTRODUCTION: Long-term air pollution exposure contributes to mortality but there are few studies examining effects of very long-term (>25 years) exposures. METHODS: This study investigated modelled air pollution concentrations at residence for 1971, 1981, 1991 (black smoke (BS) and SO2) and 2001 (PM10) in relation to mortality up to 2009 in 367,658 members of the longitudinal survey, a 1% sample of the English Census. Outcomes were all-cause (excluding accidents), cardiovascular (CV) and respiratory mortality. RESULTS: BS and SO2 exposures remained associated with mortality decades after exposure-BS exposure in 1971 was significantly associated with all-cause (OR 1.02 (95% CI 1.01 to 1.04)) and respiratory (OR 1.05 (95% CI 1.01 to 1.09)) mortality in 2002-2009 (ORs expressed per 10 µg/m(3)). Largest effect sizes were seen for more recent exposures and for respiratory disease. PM10 exposure in 2001 was associated with all outcomes in 2002-2009 with stronger associations for respiratory (OR 1.22 (95% CI 1.04 to 1.44)) than CV mortality (OR 1.12 (95% CI 1.01 to 1.25)). Adjusting PM10 for past BS and SO2 exposures in 1971, 1981 and 1991 reduced the all-cause OR to 1.16 (95% CI 1.07 to 1.26) while CV and respiratory associations lost significance, suggesting confounding by past air pollution exposure, but there was no evidence for effect modification. Limitations include limited information on confounding by smoking and exposure misclassification of historic exposures. CONCLUSIONS: This large national study suggests that air pollution exposure has long-term effects on mortality that persist decades after exposure, and that historic air pollution exposures influence current estimates of associations between air pollution and mortality.

Red light camera interventions for reducing traffic violations and traffic crashes: A systematic review.

Background: Road traffic crashes are a major and increasing cause of injury and death around the world. In 2015, there were almost 6.3 million motor vehicle traffic crashes in the United States. Of these, approximately 1.7 million (27%) involved some form of injury and 32,166 (0.5%) resulted in one or more fatalities (National Highway Traffic Safety Administration, 2016, Traffic Safety Facts 2013: A Compilation of Motor Vehicle Crash Data from the Fatality Analysis Reporting System and the General Estimates System). The most common cause of urban crashes appears to be drivers running red lights or ignoring other traffic controls and injuries occur in 39% of all of these types of crashes (Insurance Institute for Highway Safety, IIHS, 2018, Red light running). While many drivers obey traffic signals, the possibility for violations exists due to issues such as driver distraction, aggressive driving behaviors, or a deliberate decision to ignore the traffic signal. One researcher suggests that eliminating traffic violations could reduce road injury crashes by up to 40% (Zaal, 1994, Traffic law enforcement: A review of the literature). Red light cameras (RLCs) are an enforcement mechanism that permit police to remotely enforce traffic signals; they may serve as a deterrent to drivers who intentionally engage in red light running (RLR). The one previous systematic review of RLCs found that they were effective in reducing total casualty crashes but also found that evidence on the effectiveness of cameras on red light violations, total crashes, or specific types of casualty crashes was inconclusive. However, this review searched only a small number of electronic databases and was limited to a handful of studies published in 2002 or earlier. Objectives: This report updates and expands upon the previous Cochrane systematic review of RLCs. The aim of this review is to systematically review and synthesize the available evidence on the effectiveness of RLCs on the incidence of red light violations and the incidence and severity of various types of traffic crashes. Search Methods: This study uses a four-part search strategy that involves: (a) searching 27 online electronic bibliographic databases for published and unpublished evaluations of RLCs; (b) searching the websites of 46 international institutes and research agencies focusing on transportation issues for reports and other gray literature; (c) searching the reference lists of published studies to identify additional published and unpublished works; and (d) conducting a keyword search using Google and Google Scholar to search for additional gray literature. Selection Criteria: The criteria for inclusion were determined before the search process began. To be eligible, studies must have assessed the impact of RLCs on red light violations and/or traffic crashes. Studies must have employed a quantitative research design that involved randomized controlled trials, quasi-random controlled trials, a controlled before-after design, or a controlled interrupted time series. Research that incorporated additional interventions, such as speed cameras or enhanced police enforcement, were excluded, although normal routine traffic enforcement in the nonintervention control condition was not excluded. Both published and unpublished reports were included. Studies were eligible regardless of the country in which they were conducted or the date of publication. Qualitative, observational, or descriptive studies that did not include formal comparisons of treatment and control groups were excluded from this research. Data Collection and Analysis: Initial searches produced a total of 5,708 references after duplicates were removed. After title and abstract screening, a total of 121 references remained. Full-text review of these works identified 28 primary studies meeting the inclusion criteria, in addition to the 10 studies identified in the prior Cochrane review. Because several of the primary studies reported on multiple independent study areas, this report evaluates 41 separate analyses. At least two review authors independently assessed all records for eligibility, assessed methodological risk of bias, and extracted data from the full-text reports; disagreements were resolved by discussion with a third review author. To facilitate comparisons between studies, a standardized summary measure based on relative effects, rather than differences in effects, was defined for each outcome. Summary measures were calculated for all studies when possible. When at least three studies reported the same outcome, the results were pooled in a meta-analysis. Pooled meta-analyses were carried out when at least three studies reported the same outcome; otherwise, the results of individual studies were described in a narrative. Heterogeneity among effect estimates was assessed using χ 2 tests at a 5% level of significance and quantified using the I 2 statistic. EMMIE framework data were coded using the EPPIE Reviewer database. Results: The results of this systematic review suggest that RLCs are associated with a statistically significant reduction in crash outcomes, although this varies by type of crash, and suggest a reduction in red light violations. RLCs are associated with a a 20% decrease in total injury crashes, a 24% decrease in right angle crashes and a 29% decrease in right angle injury crashes. Conversely, however, RLCs are also associated with a statistically significant increase in rear end crashes of 19%. There was also some evidence that RLCs were associated with a large reduction in crashes due to red light violations. There is no evidence to suggest that study heterogeneity is consistently explained by either country or risk of bias, nor did the presence or absence of warning signs appear to impact the effectiveness of RLCs. Studies accounting for regression to the mean tend to report more moderate decreases for right angle crashes resulting in injury than studies not accounting for regression to the mean. Studies with better control for confounders reported a nonsignificant decrease in right angle crashes, compared with a significant decrease for all studies. Authors' Conclusions: The evidence suggests that RLCs may be effective in reducing red light violations and are likely to be effective in reducing some types of traffic crashes, although they also appear linked to an increase in rear end crashes. Several implications for policymakers and practitioners have emerged from this research. The costs and benefits of RLCs must be considered when implementing RLC programs. The potential benefits of a reduction in traffic violations and in some types of injury crashes must be weighed against the increased risk of other crash types. The economic implications of operating an RLC program also must be considered, including the costs of installation and operation as well as the economic impact of RLC effects.

Reduced street lighting at night and health: A rapid appraisal of public views in England and Wales.

Financial and carbon reduction incentives have prompted many local authorities to reduce street lighting at night. Debate on the public health implications has centred on road accidents, fear of crime and putative health gains from reduced exposure to artificial light. However, little is known about public views of the relationship between reduced street lighting and health. We undertook a rapid appraisal in eight areas of England and Wales using ethnographic data, a household survey and documentary sources. Public concern focused on road safety, fear of crime, mobility and seeing the night sky but, for the majority in areas with interventions, reductions went unnoticed. However, more private concerns tapped into deep-seated anxieties about darkness, modernity 'going backwards', and local governance. Pathways linking lighting reductions and health are mediated by place, expectations of how localities should be lit, and trust in local authorities to act in the best interests of local communities.

The effect of reduced street lighting on road casualties and crime in England and Wales: controlled interrupted time series analysis.

BACKGROUND: Many local authorities in England and Wales have reduced street lighting at night to save money and reduce carbon emissions. There is no evidence to date on whether these reductions impact on public health. We quantified the effect of 4 street lighting adaptation strategies (switch off, part-night lighting, dimming and white light) on casualties and crime in England and Wales. METHODS: Observational study based on analysis of geographically coded police data on road traffic collisions and crime in 62 local authorities. Conditional Poisson models were used to analyse longitudinal changes in the counts of night-time collisions occurring on affected roads during 2000-2013, and crime within census Middle Super Output Areas during 2010-2013. Effect estimates were adjusted for regional temporal trends in casualties and crime. RESULTS: There was no evidence that any street lighting adaptation strategy was associated with a change in collisions at night. There was significant statistical heterogeneity in the effects on crime estimated at police force level. Overall, there was no evidence for an association between the aggregate count of crime and switch off (RR 0.11; 95% CI 0.01 to 2.75) or part-night lighting (RR 0.96; 95% CI 0.86 to 1.06). There was weak evidence for a reduction in the aggregate count of crime and dimming (RR 0.84; 95% CI 0.70 to 1.02) and white light (RR 0.89; 95% CI 0.77 to 1.03). CONCLUSIONS: This study found little evidence of harmful effects of switch off, part-night lighting, dimming, or changes to white light/LEDs on road collisions or crime in England and Wales.