ArticleBMC research notes2015
Mail merge can be used to create personalized questionnaires in complex surveys.
Article in BMC research notes, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Article
- Using Digital Technologies in Clinical HIV Research: Real-World Applications and Considerations for Future Work.Journal of medical Internet research · 2017Article
- Integration of Specialized Pain Control Services in Palliative Care: A Nationwide Web-based Survey.Indian journal of palliative careArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
backgroundLow response rates and inadequate question comprehension threaten the validity of survey results. We describe a simple procedure to implement personalized-as opposed to generically worded-questionnaires in the context of a complex web-based survey of corresponding authors of a random sample of 300 published cluster randomized trials. The purpose of the survey was to gather more detailed information about informed consent procedures used in the trial, over and above basic information provided in the trial report. We describe our approach-which allowed extensive personalization without the need for specialized computer technology-and discuss its potential application in similar settings.
resultsThe mail merge feature of standard word processing software was used to generate unique, personalized questionnaires for each author by incorporating specific information from the article, including naming the randomization unit (e.g., family practice, school, worksite), and identifying specific individuals who may have been considered research participants at the cluster level (family doctors, teachers, employers) and individual level (patients, students, employees) in questions regarding informed consent procedures in the trial. The response rate was relatively high (64%, 182/285) and did not vary significantly by author, publication, or study characteristics. The refusal rate was low (7%).
conclusionWhile controlled studies are required to examine the specific effects of our approach on comprehension, quality of responses, and response rates, we showed how mail merge can be used as a simple but useful tool to add personalized fields to complex survey questionnaires, or to request additional information required from study authors. One potential application is in eliciting specific information about published articles from study authors when conducting systematic reviews and meta-analyses.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.