Effects of Sequential Prepaid Incentives on Response Rates, Data Quality, Sample Representativeness, and Costs in a Mail Survey of Physicians

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 We contacted the authors of all trials or reviews to ask about unpublished trials; where necessary, we also contacted authors to confirm the methods of allocation used and to clarify results presented.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.

[Quality assurance follow-up survey of the ELISA cohort study on the prevalence of COVID-19: The view of study participants - What is well received?]

INTRODUCTION

With the outbreak of the Corona pandemic, the LübEcker longitudinal study on infections with SARS-CoV-2 (ELISA study) was conducted in the Lübeck area to provide information on the prevalence, unreported cases and symptoms of COVID-19. The aim of the present study is to evaluate defined structure and process indictors of the study conduct of the ELISA study by subjects.

METHODS

After defining and operationalizing participant-oriented quality indicators, 3,710 participants were surveyed online via LimeSurvey. Indicators defined were access to the study, time requirements, reporting of findings, ratings of the study apps used, communication, study center, tolerability of sample collection, and willingness to re-participate. In addition, comments on push and pull factors of study participation could be made. The evaluation was both quantitative and qualitative.

RESULTS

45% of the follow-up respondents (n=1,684) answered the questions on the defined structural and process indicators. In the quantitative part of the survey, tolerability of venous blood sampling was rated as significantly better than that of nasopharyngeal smears. 91% of the follow-up respondents welcomed the offer to view their findings in the personal results portal. Overall, the indicators were mostly rated positively. According to the qualitative data, the study participants found the win-win situation of the test opportunity to contribute to research, the local relevance of the study, the small incentives, and the low-threshold nature of the study registration to be positive aspects of the study. According to the quantitative data, participants suggested improving the usability of the digital applications in terms of more user-friendly identification solutions, reminder functions, announcements of software updates and avoidance of double entries.

DISCUSSION

The defined structure and process indicators appear to be suitable for assessing the quality of study implementation from the subjects' point of view and indicate a good quality of study implementation under pandemic conditions. The lowest participation rate (75%) was measured at the fifth test time of strongly declining COVID-19 infections during the summer holidays in Schleswig-Holstein. Obviously, the benefit and meaningfulness of further study participation as well as competing factors were weighted differently by the subjects at this point. The follow-up survey suggests a variety of options for motivating participants to maintain a high level of participation. Possible limitations are that a non-response bias cannot be excluded for the follow-up survey and that no suitable standardised questionnaire was available.

CONCLUSION

The present study provides recommendations for the planning of future cohort studies. It makes sense to continuously evaluate the motives for participation or non-participation and to explicitly consider them in the course of the study. Therefore, the definition of general quality indicators for the practical implementation of studies seems desirable. Positive experiences of the participants in connection with study participation are important, such as good time management, short response times, technical support offers and additional services such as a study homepage with frequently asked questions (FAQs), timely individual notifications of results and transparent, generally understandable information about study results during the study. Digital solutions are well received, but can still be improved for specific studies.