Bmc Med Res Methodol
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Bmc Med Res Methodol · Mar 2017
Randomized Controlled Trial Multicenter StudyThe effect of postal questionnaire burden on response rate and answer patterns following admission to intensive care: a randomised controlled trial.
The effects of postal questionnaire burden on return rates and answers given are unclear following treatment on an intensive care unit (ICU). We aimed to establish the effects of different postal questionnaire burdens on return rates and answers given. ⋯ In survivors of intensive care, questionnaire burden had no effect on return rates. However, questionnaire burden affected answers to the same questionnaire (EQ-5D-3 L).
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Bmc Med Res Methodol · Jan 2015
Randomized Controlled TrialPersonalized contact strategies and predictors of time to survey completion: analysis of two sequential randomized trials.
Effective strategies for contacting and recruiting study participants are critical in conducting clinical research. In this study, we conducted two sequential randomized controlled trials of mail- and telephone-based strategies for contacting and recruiting participants, and evaluated participant-related variables' association with time to survey completion and survey completion rates. Subjects eligible for this study were survivors of acute lung injury who had been previously enrolled in a 12-month observational follow-up study evaluating their physical, cognitive and mental health outcomes, with their last study visit completed at a median of 34 months previously. ⋯ We found that age ≤40 years and minority race were associated with a longer time to survey completion, but personalized versus generic approaches to mail- and telephone-based contact strategies had no significant effect. Repeating both mail and telephone contact attempts was important for increasing survey completion rate.
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Bmc Med Res Methodol · Oct 2012
Randomized Controlled TrialAn exploration of the missing data mechanism in an Internet based smoking cessation trial.
Missing outcome data are very common in smoking cessation trials. It is often assumed that all such missing data are from participants who have been unsuccessful in giving up smoking ("missing=smoking"). Here we use data from a recent Internet based smoking cessation trial in order to investigate which of a set of a priori chosen baseline variables are predictive of missingness, and the evidence for and against the "missing=smoking" assumption. ⋯ Those conducting smoking cessation trials, and wishing to perform an analysis that assumes the data are MAR, should collect and incorporate baseline variables into their models that are thought to be good predictors of missing data in order to make this assumption more plausible. However they should also consider the possibility of Missing Not at Random (MNAR) models that make or allow for less extreme assumptions than "missing=smoking".
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Bmc Med Res Methodol · Jan 2012
Randomized Controlled Trial Comparative StudyTelephone follow-up to a mail survey: when to offer an interview compared to a reminder call.
Using a different mode of contact on the final follow-up to survey non-respondents is an identified strategy to increase response rates. This study was designed to determine if a reminder phone call or a phone interview as a final mode of contact to a mailed survey works better to increase response rates and which strategy is more cost effective. ⋯ The additional cost of completing an interview is worth it when an additional signed form is not required of the respondent. However, when such a signed form is required, offering an interview instead of a reminder phone call as a follow up to non-respondents does not increase response rates enough to outweigh the additional costs.
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Bmc Med Res Methodol · Jan 2012
Randomized Controlled TrialAlternative analyses for handling incomplete follow-up in the intention-to-treat analysis: the randomized controlled trial of balloon kyphoplasty versus non-surgical care for vertebral compression fracture (FREE).
Clinical trial participants may be temporarily absent or withdraw from trials, leading to missing data. In intention-to-treat (ITT) analyses, several approaches are used for handling the missing information - complete case (CC) analysis, mixed-effects model (MM) analysis, last observation carried forward (LOCF) and multiple imputation (MI). This report discusses the consequences of applying the CC, LOCF and MI for the ITT analysis of published data (analysed using the MM method) from the Fracture Reduction Evaluation (FREE) trial. ⋯ The FREE trial results are robust as the alternative methods used for substituting missing data produced similar results. The MM method showed the highest statistical precision suggesting it is the most appropriate method to use for analysing the FREE trial data.