208 research outputs found

    Estimating nonresponse bias and mode effects in a mixed mode survey

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    In mixed-mode surveys, it is difficult to separate sample selection differences from mode-effects that can occur when respondents respond in different interview settings. This paper provides a framework for separating mode-effects from selection effects by matching very similar respondents from different survey modes using propensity score matching. The answer patterns of the matched respondents are subsequently compared. We show that matching can explain differences in nonresponse and coverage in two Internet-samples. When we repeat this procedure for a telephone and Internet-sample however, differences persist between the samples after matching. This indicates the occurrence of mode-effects in telephone and Internet surveys. Mode-effects can be problematic; hence we conclude with a discussion of designs that can be used to explicitly study mode-effects

    Standard survey methods for estimating colony losses and explanatory risk factors in Apis mellifera

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    This chapter addresses survey methodology and questionnaire design for the collection of data pertaining to estimation of honey bee colony loss rates and identification of risk factors for colony loss. Sources of error in surveys are described. Advantages and disadvantages of different random and non-random sampling strategies and different modes of data collection are presented to enable the researcher to make an informed choice. We discuss survey and questionnaire methodology in some detail, for the purpose of raising awareness of issues to be considered during the survey design stage in order to minimise error and bias in the results. Aspects of survey design are illustrated using surveys in Scotland. Part of a standardized questionnaire is given as a further example, developed by the COLOSS working group for Monitoring and Diagnosis. Approaches to data analysis are described, focussing on estimation of loss rates. Dutch monitoring data from 2012 were used for an example of a statistical analysis with the public domain R software. We demonstrate the estimation of the overall proportion of losses and corresponding confidence interval using a quasi-binomial model to account for extra-binomial variation. We also illustrate generalized linear model fitting when incorporating a single risk factor, and derivation of relevant confidence intervals

    Ovarian cancer symptom awareness and anticipated delayed presentation in a population sample

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    Background: While ovarian cancer is recognised as having identifiable early symptoms, understanding of the key determinants of symptom awareness and early presentation is limited. A population-based survey of ovarian cancer awareness and anticipated delayed presentation with symptoms was conducted as part of the International Cancer Benchmarking Partnership (ICBP). Methods: Women aged over 50 years were recruited using random probability sampling (n = 1043). Computer-assisted telephone interviews were used to administer measures including ovarian cancer symptom recognition, anticipated time to presentation with ovarian symptoms, health beliefs (perceived risk, perceived benefits/barriers to early presentation, confidence in symptom detection, ovarian cancer worry), and demographic variables. Logistic regression analysis was used to identify the contribution of independent variables to anticipated presentation (categorised as < 3 weeks or ≥ 3 weeks). Results: The most well-recognised symptoms of ovarian cancer were post-menopausal bleeding (87.4%), and persistent pelvic (79.0%) and abdominal (85.0%) pain. Symptoms associated with eating difficulties and changes in bladder/bowel habits were recognised by less than half the sample. Lower symptom awareness was significantly associated with older age (p ≤ 0.001), being single (p ≤ 0.001), lower education (p ≤ 0.01), and lack of personal experience of ovarian cancer (p ≤ 0.01). The odds of anticipating a delay in time to presentation of ≥ 3 weeks were significantly increased in women educated to degree level (OR = 2.64, 95% CI 1.61 – 4.33, p ≤ 0.001), women who reported more practical barriers (OR = 1.60, 95% CI 1.34 – 1.91, p ≤ 0.001) and more emotional barriers (OR = 1.21, 95% CI 1.06 – 1.40, p ≤ 0.01), and those less confident in symptom detection (OR = 0.56, 95% CI 0.42 – 0.73, p ≤ 0.001), but not in those who reported lower symptom awareness (OR = 0.99, 95% CI 0.91 – 1.07, p = 0.74). Conclusions: Many symptoms of ovarian cancer are not well-recognised by women in the general population. Evidence-based interventions are needed not only to improve public awareness but also to overcome the barriers to recognising and acting on ovarian symptoms, if delays in presentation are to be minimised

    The prevalence of genital warts in the Baltic countries : Findings from national cross-sectional surveys in Estonia, Latvia and Lithuania

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    Objectives: To assess the prevalence and correlates of self-reported genital warts (GWs) among women and men aged 18-45 years in the Baltic countries. Methods: In 2011-2013 we performed a cross-sectional survey using a self-administered questionnaire to collect information on the history of clinically diagnosed GWs, sociodemographic characteristics and sexual behaviour. Probability sampling methods were used to invite 16 959 individuals representing the general population, of whom 7760 (45.8%) participated (Estonia: 1967 women, 1221 men; Latvia: 1525 women, 1525 men; Lithuania: 1522 women). Results: The estimated lifetime prevalence of clinically diagnosed GWs in women was 4.6% (95% CI 3.8 to 5.5) in Estonia, 2.9% (95% CI 2.0 to 3.6) in Latvia and 1.5% (95% CI 1.2 to 2.0) in Lithuania. Among men, the corresponding values were 2.8% (95% CI 1.9 to 4.0) in Estonia and 1.9% (95% CI 1.3 to 2.6) in Latvia. The mean age at first episode of clinically diagnosed GW was 24.6 years (95% CI 23.6 to 25.5) for women and 24.5 years (95% CI 22.9 to 26.0) for men. A lifetime history of clinically diagnosed GW was associated with a history of sexually transmitted infections other than GW (adjusted OR (AOR) 3.0, 95% CI 2.1 to 4.3 for women; AOR 5.3, 95% CI 3.0 to 9.2 for men), and a higher number (5+) of lifetime sexual partners (AOR 2.9, 95% CI 1.9 to 4.2 for women; AOR 2.1, 95% CI 1.2 to 3.9 for men). Men living comfortably within their household income had higher odds for GW (AOR 1.9, 95% CI 1.1 to 3.2). Conclusions: Our estimated prevalence of clinically diagnosed GWs was lower than estimates from the general population of other European countries.publishersversionPeer reviewe

    Treatment decision-making and the form of risk communication: results of a factorial survey

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    BACKGROUND: Prospective users of preventive therapies often must evaluate complex information about therapeutic risks and benefits. The purpose of this study was to evaluate the effect of relative and absolute risk information on patient decision-making in scenarios typical of health information for patients. METHODS: Factorial experiments within a telephone survey of the Michigan adult, non-institutionalized, English-speaking population. Average interview lasted 23 minutes. Subjects and sample design: 952 randomly selected adults within a random-digit dial sample of Michigan households. Completion rate was 54.3%. RESULTS: When presented hypothetical information regarding additional risks of breast cancer from a medication to prevent a bone disease, respondents reduced their willingness to recommend a female friend take the medication compared to the baseline rate (66.8% = yes). The decrease was significantly greater with relative risk information. Additional benefit information regarding preventing heart disease from the medication increased willingness to recommend the medication to a female friend relative to the baseline scenario, but did not differ between absolute and relative risk formats. When information about both increased risk of breast cancer and reduced risk of heart disease were provided, typical respondents appeared to make rational decisions consistent with Expected Utility Theory, but the information presentation format affected choices. Those 11% – 33% making decisions contrary to the medical indications were more likely to be Hispanic, older, more educated, smokers, and to have children in the home. CONCLUSIONS: In scenarios typical of health risk information, relative risk information led respondents to make non-normative decisions that were "corrected" when the frame used absolute risk information. This population sample made generally rational decisions when presented with absolute risk information, even in the context of a telephone interview requiring remembering rates given. The lack of effect of gender and race suggests that a standard strategy of presenting absolute risk information may improve patient decision-making

    Recruitment using mobile telephones in an Irish general population sexual health survey: challenges and practical solutions

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    BACKGROUND: Non-coverage of households without a landline telephone is a major concern of telephone survey researchers. Sampling mobile telephone users in national surveys is vital in order to gain access to the growing proportion of households that use mobile telephones extensively or exclusively. The complex logistics of conducting surveys with mobile telephones have been discussed in the literature. This paper outlines the actual challenges encountered during a recent national sexual health survey in Ireland, which utilized a mobile telephone sampling frame to recruit approximately half of the sample. METHOD: The 2010 Irish Contraception and Crisis Pregnancy Survey (ICCP-2010) is a nationally representative sample of adults aged 18-45 years living in Ireland (n = 3002; 1416 recruited by landline telephone and 1586 recruited by mobile telephone). The overall response rate for the survey was 69% (79% for the landline telephone strand; 61% for the mobile telephone strand). All interviews were conducted using computer-assisting telephone interviewing. RESULTS: During the 18-week fieldwork period, five main challenges relating to the use of mobile telephones were encountered: (1) explaining to respondents how random digit dialling works in relation to mobile telephones; (2) establishing the respondent\u27s eligibility; (3) calling the respondent with the Caller ID blocked or withheld; (4) calling the respondent when they are in any number of locations or situations; and (5) explaining to respondents the importance of refusal conversion calls for the response rate calculation. Details of how the survey protocols and procedures were monitored and adapted throughout the study to ensure a high response rate are outlined. CONCLUSION: It is undeniably more challenging to recruit respondents using mobile telephones as opposed to landline telephones. Respondents are generally not familiar with being contacted on their personal mobile telephone for the purposes of being recruited for a research study. The main challenge for survey methodologists and interviewers is to devise simple protocols to explain to respondents why they are being contacted on a mobile telephone. Recommendations for survey researchers interested in using this methodological approach in the future are discussed
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