Patterns of non-response to a mail survey

Macera, Caroline A.; Jackson, Ken; Davis, Dorothy R.; Kronenfeld, Jennie Jacobs; Blair, Steven N.

doi:10.1016/0895-4356(90)90112-3

Cited by 140 publications

(89 citation statements)

References 6 publications

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“…The factors associated with not returning the survey were younger age, male sex, and more pain. Our finding that older patients are more likely to return the survey is in line with previous studies [7,21,26]. Smoking, marital status, and working status were not associated with returning surveys in our study, in contrast to earlier studies that did find differences in these demographic factors [8,13,21].…”

Section: Discussionsupporting

confidence: 91%

“…Our finding that older patients are more likely to return the survey is in line with previous studies [7,21,26]. Smoking, marital status, and working status were not associated with returning surveys in our study, in contrast to earlier studies that did find differences in these demographic factors [8,13,21]. Hardie et al [9] reported that men were more likely to return postal surveys in a population older than 70 years in contrast to our finding that men were more likely to be nonresponders.…”

Section: Discussionsupporting

confidence: 89%

“…[1,15,17,21,[25][26][27]. Previous studies suggest that nonresponders to mailed surveys might differ in important ways from responders [7,8,13,21].…”

Section: Discussionmentioning

confidence: 99%

“…Previous studies suggest that nonresponders to mailed surveys might be different than responders with respect to age, smoking habit, working status, marital status, and sex [7,8,13,21].…”

Section: Introductionmentioning

confidence: 99%

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Factors Associated With Survey Response in Hand Surgery Research

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Anderson

Neuhaus

et al. 2013

Clinical Orthopaedics &Amp; Related Research

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Background A low response rate is believed to decrease the validity of survey studies. Factors associated with nonresponse to surveys are poorly characterized in orthopaedic research. Questions/purposes This study addressed whether (1) psychologic factors; (2) demographics; (3) illness-related factors; and (4) pain are predictors of a lower likelihood of a patient returning a mailed survey. Methods One hundred four adult, new or return patients completed questionnaires including the Pain Catastrophizing Scale, Patient Health Questionnaire-9 depression scale, Short Health Anxiety Index, demographics, and a pain scale (0-10) during a routine visit to a hand and upper extremity surgeon. Of these patients, 38% had undergone surgery and the remainder was seen for various other conditions. Six months after their visit, patients were mailed the DASH questionnaire and a scale to rate their satisfaction with the visit (0-10). Bivariate analysis and logistic regression were used to determine risk factors for being a nonresponder to the followup of this study. The cohort consisted of 57 women and 47 men with a mean age of 51 years with various diagnoses. Thirty-five patients (34%) returned the questionnaire. Responders were satisfied with their visit (mean satisfaction, 8.7) and had a DASH score of 9.6.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionsupporting

confidence: 89%

“…[1,15,17,21,[25][26][27]. Previous studies suggest that nonresponders to mailed surveys might differ in important ways from responders [7,8,13,21].…”

Section: Discussionmentioning

confidence: 99%

“…Previous studies suggest that nonresponders to mailed surveys might be different than responders with respect to age, smoking habit, working status, marital status, and sex [7,8,13,21].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Factors Associated With Survey Response in Hand Surgery Research

Bot

Anderson

Neuhaus

et al. 2013

Clinical Orthopaedics &Amp; Related Research

View full text Add to dashboard Cite

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“…Most of those studies have found small or no differences between respondents and nonrespondents [7][8][9][10]. Subjects who repeatedly returned a questionnaire tended to be married, non-smokers and more physically active than those who returned it only once.…”

Section: Introductionmentioning

confidence: 99%

Estimating Non-Response Bias in Family Studies: Application to Mental Health and Lifestyle

et al. 2003

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Abstract. Non-response to mailed surveys reduces the effective sample size and may introduce bias. Nonresponse has been studied by (1) comparison to available data in population based registers, (2) directly contacting non-respondents by telephone or single-item reply cards, and (3) longitudinal repetition of the survey. The goal of this paper was to propose an additional method to study non-response bias: when the variable of interest has a familial component, data from respondents can be used as proxy for the data from their non-responding family members. This approach was used with data on smoking, alcohol consumption, physical activity, coffee-and tea-use, education, body mass index, religion, burnout, life events, personality and mental health in large number of siblings and DZ twins registered with the Netherlands Twin Register. In addition, for smoking behavior, we also used the second strategy by sending a reply card. Results show that scores of members from less cooperative families or incomplete twin pairs tended to be more unfavorable than the scores from highly cooperative families or complete twin pairs. For example, family members from less cooperative families cycled less often and scored higher on anxious depression and neuroticism. For smoking, both the results of the reply card and the results of the additional method suggested a higher percentage smokers among the non-respondents but this was only significant with reply card method. In general, differences between highly/less cooperative families and complete/incomplete DZ twins were small. Results suggest that, even for studies with moderate response rates, data collected on health, personality and lifestyle are relatively unbiased.

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