Impact of Survey Administration Mode on the Results of a Health-Related Discrete Choice Experiment: Online and Paper Comparison

Determann, Domino; Lambooij, Mattijs; Steyerberg, Ewout W.; Bekker‐Grob, Esther W. de; Wit, G. Ardine de

doi:10.1016/j.jval.2017.02.007

Cited by 75 publications

(54 citation statements)

References 30 publications

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“…Researchers must, however, be aware that using different modes (e.g. mail, Internet, interviews) to collect data can lead to variations in representativeness, convergent validity and data quality . The choice of survey mode will depend on the research question and population of interest and findings should be interpreted with mode effects in mind.…”

Section: Design and Analysis Of The Dcementioning

confidence: 99%

What can discrete choice experiments do for you?

2018

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Context In everyday life, the choices we make are influenced by our preferences for the alternatives available to us. The same is true when choosing medical education, training and jobs. More often than not, those alternatives comprise multiple attributes and our ultimate choice will be guided by the value we place on each attribute relative to the others. In education, for example, choice of university is likely to be influenced by preferences for institutional reputation, location, cost and course content; but which of these attributes is the most influential? An understanding of what is valued by applicants, students, trainees and colleagues is of increasing importance in the higher education and medical job marketplaces because it will help us to develop options that meet their needs and preferences. Methods In this article, we describe the discrete choice experiment (DCE), a survey method borrowed from economics that allows us to quantify the values respondents place on the attributes of goods and services, and to explore whether and to what extent they are willing to trade less of one attribute for more of another. Conclusions To date, DCEs have been used to look at medical workforce issues but relatively little in the field of medical education. However, many outstanding questions within medical education could be usefully addressed using DCEs. A better understanding of which attributes have most influence on, for example, staff or student satisfaction, choice of university and choice of career, and the extent to which stakeholders are prepared to trade one attribute against another is required. Such knowledge will allow us to tailor the way medical education is provided to better meet the needs of key stakeholders within the available resources.

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Section: Design and Analysis Of The Dcementioning

confidence: 99%

What can discrete choice experiments do for you?

2018

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“…Internet-based surveys also make it possible to record response time accurately and target groups of respondents faster at lower cost [1]. However, with internet surveys it is difficult to achieve sample representativeness (of the general population), and data quality may be poor due to low engagement of the respondents or limited understanding of the questions [1, 3]. These advantages and disadvantages of the different methods may be a source of variation in the results, even if the questions are identical [5, 6].…”

Section: Introductionmentioning

confidence: 99%

Comparing internet and face-to-face surveys as methods for eliciting preferences for social care-related quality of life: evidence from England using the ASCOT service user measure

Saloniki,

Malley,

Burge

et al. 2019

Qual Life Res

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Purpose Traditionally, researchers have relied on eliciting preferences through face-to-face interviews. Recently, there has been a shift towards using internet-based methods. Different methods of data collection may be a source of variation in the results. In this study, we compare the preferences for the Adult Social Care Outcomes Toolkit (ASCOT) service user measure elicited using best–worst scaling (BWS) via a face-to-face interview and an online survey. Methods Data were collected from a representative sample of the general population in England. The respondents (face-to-face: n = 500; online: n = 1001) completed a survey, which included the BWS experiment involving the ASCOT measure. Each respondent received eight best–worst scenarios and made four choices (best, second best, worst, second worst) in each scenario. Multinomial logit regressions were undertaken to analyse the data taking into account differences in the characteristics of the two samples and the repeated nature of the data. Results We initially found a number of small significant differences in preferences between the two methods across all ASCOT domains. These differences were substantially reduced—from 15 to 5 out of 30 coefficients being different at the 5% level—and remained small in value after controlling for differences in observable and unobservable characteristics of the two samples. Conclusions This comparison demonstrates that face-to-face and internet surveys may lead to fairly similar preferences for social care-related quality of life when differences in sample characteristics are controlled for. With or without a constant sampling frame, studies should carefully design the BWS exercise and provide similar levels of clarification to participants in each survey to minimise the amount of error variance in the choice process.

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“…The mean of ASC is statistically significant indicating the presence of left-to-right biases in our data, a result common to many other DCEs in the health domain (see e.g. Determann et al, 2017).…”

Section: Resultsmentioning

confidence: 50%

The Role of Heterogeneity of Patients’ Preferences in Kidney Transplantation

2019

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We elicit time and risk preferences for kidney transplantation from the entire population of patients of the largest Italian transplant centre using a discrete choice experiment (DCE). We measure patients' willingness-to-wait (WTW), expressed in months, for receiving a kidney with one-year longer expected graft survival, or low risk of complication. Using a mixed logit in WTW-space model, we find heterogeneity in patients' preferences. Our model allows WTW to vary with the patient's age and duration of dialysis. The results suggest that WTW correlates with age and duration of dialysis. The implication for transplant practice is that including individual preferences in kidney allocation protocols that assign "non-ideal" (expanded donor criteria) organs may not only increase the expected survival rates of patients with transplanted organs but also improve patients' satisfaction.

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Impact of Survey Administration Mode on the Results of a Health-Related Discrete Choice Experiment: Online and Paper Comparison

Cited by 75 publications

References 30 publications

What can discrete choice experiments do for you?

What can discrete choice experiments do for you?

Comparing internet and face-to-face surveys as methods for eliciting preferences for social care-related quality of life: evidence from England using the ASCOT service user measure

The Role of Heterogeneity of Patients’ Preferences in Kidney Transplantation

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