BACKGROUND: Postal and electronic questionnaires are widely used for data collection in epidemiological studies 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 health research. OBJECTIVES: To identify effective strategies to increase response to postal and electronic questionnaires. SEARCH STRATEGY: We searched 14 electronic databases to February 2008 and manually searched the reference lists of relevant trials and reviews, and all issues of two journals. We contacted the authors of all trials or reviews to ask about unpublished trials. Where necessary, we also contacted authors to confirm methods of allocation used and to clarify results presented. We assessed the eligibility of each trial using pre-defined criteria. SELECTION CRITERIA: Randomised controlled trials of methods to increase response to postal or electronic questionnaires. 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 among trial odds ratios using a Chi(2) test and the degree of inconsistency between trial results was quantified using the I(2) statistic. MAIN RESULTS: PostalWe found 481 eligible trials. The trials evaluated 110 different ways of increasing response to postal questionnaires. We found substantial heterogeneity among trial results in half of the strategies. The odds of response were at least doubled using monetary incentives (odds ratio 1.87; 95% CI 1.73 to 2.04; heterogeneity P < 0.00001, I(2) = 84%), recorded delivery (1.76; 95% CI 1.43 to 2.18; P = 0.0001, I(2) = 71%), a teaser on the envelope - e.g. a comment suggesting to participants that they may benefit if they open it (3.08; 95% CI 1.27 to 7.44) and a more interesting questionnaire topic (2.00; 95% CI 1.32 to 3.04; P = 0.06, I(2) = 80%). The odds of response were substantially higher with pre-notification (1.45; 95% CI 1.29 to 1.63; P < 0.00001, I(2) = 89%), follow-up contact (1.35; 95% CI 1.18 to 1.55; P < 0.00001, I(2) = 76%), unconditional incentives (1.61; 1.36 to 1.89; P < 0.00001, I(2) = 88%), shorter questionnaires (1.64; 95% CI 1.43 to 1.87; P < 0.00001, I(2) = 91%), providing a second copy of the questionnaire at follow up (1.46; 95% CI 1.13 to 1.90; P < 0.00001, I(2) = 82%), mentioning an obligation to respond (1.61; 95% CI 1.16 to 2.22; P = 0.98, I(2) = 0%) and university sponsorship (1.32; 95% CI 1.13 to 1.54; P < 0.00001, I(2) = 83%). The odds of response were also increased with non-monetary incentives (1.15; 95% CI 1.08 to 1.22; P < 0.00001, I(2) = 79%), personalised questionnaires (1.14; 95% CI 1.07 to 1.22; P < 0.00001, I(2) = 63%), use of hand-written addresses (1.25; 95% CI 1.08 to 1.45; P = 0.32, I(2) = 14%), use of stamped return envelopes as opposed to franked return envelopes (1.24; 95% CI 1.14 to 1.35; P < 0.00001, I(2) = 69%), an assurance of confidentiality (1.33; 95% CI 1.24 to 1.42) and first class outward mailing (1.11; 95% CI 1.02 to 1.21; P = 0.78, I(2) = 0%). The odds of response were reduced when the questionnaire included questions of a sensitive nature (0.94; 95% CI 0.88 to 1.00; P = 0.51, I(2) = 0%).ElectronicWe found 32 eligible trials. The trials evaluated 27 different ways of increasing response to electronic questionnaires. We found substantial heterogeneity among trial results in half of the strategies. The odds of response were increased by more than a half using non-monetary incentives (1.72; 95% CI 1.09 to 2.72; heterogeneity P < 0.00001, I(2) = 95%), shorter e-questionnaires (1.73; 1.40 to 2.13; P = 0.08, I(2) = 68%), including a statement that others had responded (1.52; 95% CI 1.36 to 1.70), and a more interesting topic (1.85; 95% CI 1.52 to 2.26). The odds of response increased by a third using a lottery with immediate notification of results (1.37; 95% CI 1.13 to 1.65), an offer of survey results (1.36; 95% CI 1.15 to 1.61), and using a white background (1.31; 95% CI 1.10 to 1.56). The odds of response were also increased with personalised e-questionnaires (1.24; 95% CI 1.17 to 1.32; P = 0.07, I(2) = 41%), using a simple header (1.23; 95% CI 1.03 to 1.48), using textual representation of response categories (1.19; 95% CI 1.05 to 1.36), and giving a deadline (1.18; 95% CI 1.03 to 1.34). The odds of response tripled when a picture was included in an e-mail (3.05; 95% CI 1.84 to 5.06; P = 0.27, I(2) = 19%). The odds of response were reduced when "Survey" was mentioned in the e-mail subject line (0.81; 95% CI 0.67 to 0.97; P = 0.33, I(2) = 0%), and when the e-mail included a male signature (0.55; 95% CI 0.38 to 0.80; P = 0.96, I(2) = 0%). AUTHORS' CONCLUSIONS: Health researchers using postal and electronic questionnaires can increase response using the strategies shown to be effective in this systematic review.

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Methods to increase response to postal and electronic questionnaires

This article reports the results of a meta-analysis of experimental studies which have examined ten different factors felt to influence response rates to mail surveys. The form of meta- analysis used clearly defines the individual impact of each of the factors examined. Results indicate that prenotification and follow-ups increase the response rate, as does the type of outgo- ing postage used. Furthermore, studies sponsored by a university receive greater returns. Increases in the size of the monetary incentive used appear to have decreasing marginal gains. Finally, some evidence exists to suggest that the color of the question- naire influences response rate. The extensive use of mail surveys coupled with the low response rates typically encountered has made the issue of mail survey response rate improvement an intriguing topic. High response rates have the obvi- ous benefits of increased sample size, reduced costs associated with follow-up contacts, and reduced concern over nonresponse bias. Many experiments have been conducted to measure the effectiveness of one or more of the factors expected to influence response rates. The purpose of this paper is to apply a form of meta-analysis to reported experimental findings to isolate and estimate the individual impact of several typical response rate enhancement techniques. The meta-analysis technique used avoids the problems associated with past similar efforts but is more restrictive in the factors which can be exam-

https://www.jstor.org/stable/pdfplus/2749256.pdf

Mail survey response rate a meta-analysis of selected techniques for inducing response

Background: Postal questionnaires are widely used for data collection in epidemiological studies but non-response reduces the effective sample size and can introduce bias. Finding ways to increase response rates to postal questionnaires would improve the quality of health research. Objectives: To identify effective strategies to increase response rates to postal questionnaires. Search strategy: We aimed to find all randomised controlled trials of strategies to increase response rates to postal questionnaires. We searched 14 electronic databases to February 2003 and manually searched the reference lists of relevant trials and reviews, and all issues of two journals. We contacted the authors of all trials or reviews to ask about unpublished trials. Where necessary, authors were also contacted to confirm methods of allocation used and to clarify results presented. We assessed the eligibility of each trial using pre-defined criteria. Selection criteria: Randomised controlled trials of methods to increase response rates to postal questionnaires. 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 and 95% confidence intervals in a random effects model. Evidence for selection bias was assessed using Egger's weighted regression method and Begg's rank correlation test and funnel plot. Heterogeneity among trial odds ratios was assessed using a chi-square test at a 5% significance level and the degree of inconsistency between trial results was quantified using I2. Main results: We found 372 eligible trials. The trials evaluated 98 different ways of increasing response rates to postal questionnaires and for 62 of these the combined trials included over 1,000 participants. We found substantial heterogeneity among trial results in half of the strategies. The odds of response were at least doubled using monetary incentives (odds ratio 1.99, 95% CI 1.81 to 2.18; heterogeneity p < 0.00001, I 2 =78%), recorded delivery (2.04, 1.60 to 2.61; p=0.0004, I 2 =69%), a teaser on the envelope - e.g. a comment suggesting to participants that they may benefit if they open it (3.08, 1.27 to 7.44) and a more interesting questionnaire topic (2.44, 1.99 to 3.01; p=0.74, I 2 =0%). The odds of response were substantially higher with pre-notification (1.50, 1.29 to 1.74; p < 0.00001, I 2 =90%), follow-up contact (1.44, 1.25 to 1.65; p < 0.0001, I 2 =68%), unconditional incentives (1.61, 1.27 to 2.04; p < 0.00001, I 2 =91%), shorter questionnaires (1.73, 1.47 to 2.03; p < 0.00001, I 2 =93%), providing a second copy of the questionnaire at follow-up (1.51, 1.13 to 2.00; p < 0.00001, I 2 =83%), mentioning an obligation to respond (1.61, 1.16 to 2.22; p=0.98, I 2 =0%) and university sponsorship (1.32, 1.13 to 1.54; p < 0.00001, I 2 =83%). The odds of response were also increased with non-monetary incentives (1.13, 1.07 to 1.21; p < 0.00001, I 2 =71%), personalised questionnaires (1.16, 1.07 to 1.26; p < 0.00001, I 2 =67%), use of coloured as opposed to blue or black ink (1.39, 1.16 to 1.67), use of stamped return envelopes as opposed to franked return envelopes (1.29, 1.18 to 1.42; p < 0.00001, I 2 =72%), an assurance of confidentiality (1.33, 1.24 to 1.42) and first class outward mailing (1.12, 1.02 to 1.23). The odds of response were reduced when the questionnaire included questions of a sensitive nature (0.94, 0.88 to 1.00; p=0.51, I 2 =0%), when questionnaires began with the most general questions (0.80, 0.67 to 0.96), or when participants were offered the opportunity to opt out of the study (0.76, 0.65 to 0.89; p=0.46, I 2 =0%). Authors' conclusions: Health researchers using postal questionnaires can increase response rates using the strategies shown to be effective in this systematic review. Copyright © 2008 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd.

Methods to increase response rates to postal questionnaires

It is important to remain creative when conducting segmentation research, as many different ways to segment a market can exist. Five main bases are discussed: geographic, demographic, psychographic, behaviouristic and image. This is followed by an overview of the main techniques used to establish and verify segments, including automatic interaction detector, conjoint analysis, multidimensional scaling and canonical analysis.

Market Segmentation: A Review

Since being recognized as a separate field of inquiry over 75 years ago, marketing has made enormous strides in terms of becoming a scholarly discipline. Marketing scholars have used scientific approaches to discover and document a number of regularities pertaining to consumer behavior and marketing exchages. Many regularities that have been empirically validated have achieved the status of “lawlike generalizations.” In this article, the authors first classify these generalizations into four categories: location centric, time centric, market centric, and competition centric. They then argue that each category is now being affected by at least one major contextual discontinuity that is likely to challenge the relevance, if not validity, of these well-accepted lawlike generalizations. The authors also identify important questions stemming from these discontinuities and issue a call for further research to discover new insights and paradigms.

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Revisiting Marketing’s Lawlike Generalizations:

MARKET segmentation has been accepted as a strategic marketing tool to define markets and thereby allocate resources. The concept as originally defined by Wendell Smith requires an "adjustment of product and marketing effort to (differences in) consumer or user requirements."'1 Marketers frequently cite segmentation studies for this purpose, and the term has become something of a buzzword in the literature. A debate has developed between research practitioners as to whether markets can be segmented in a valid and reliable manner. However, a growing number of researchers feel that such studies characteristi-

A. Marvin Roscoe

Papers

Approaches to Market Segmentation Analysis

Follow-Up Methods, Questionnaire Length, and Market Differences in Mail Surveys

Intertechnique cross-validation in cluster analysis / 175

Intertechnique cross-validation in cluster analysis / 208