Dataset Information

Radiological clinical trials: Proposal of a problem-finding questionnaire to improve study success.

ABSTRACT: AIM:To develop a survey to help define the main problems in radiological clinical trials. METHODS:Since 2006, we have managed seven different radiological clinical trials recruiting patients in academic and non-academic centres. We developed a preliminary questionnaire using a four-round Delphi approach to identify problems occurring in radiological clinical trials run at our centre. We investigated the recruitment experience, involvement of all multi-disciplinary team members and main obstacles to completing the projects. A final round of Delphi processes elucidated solutions to the identified problems. RESULTS:Among 19/20 (95%) respondents, 10 (53%) were young physicians (under 35 years old), and the respondents included non-faculty members, fellows, residents, and undergraduate students. Ninety-four percent (18/19) of respondents showed interest in conducting clinical trials. On a scale of 1 to 10, the problems with higher/worse scores (8-9) were related to technical or communication problems. The most frequent problems across all studies were technical problems related to clinical trial equipment, insufficient willingness to participate, obstacles to understanding the design of electronic-case report form and extra work. CONCLUSION:The developed questionnaire identified the main recurring problems in radiological clinical trials as perceived by end-users and helped define possible solutions that are mostly related to having dedicated clinical trial research staff.

SUBMITTER: Valdora F

PROVIDER: S-EPMC5183990 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Radiological clinical trials: Proposal of a problem-finding questionnaire to improve study success.

Valdora Francesca F Bignotti Bianca B Calabrese Massimo M Houssami Nehmat N Tagliafico Alberto A

World journal of methodology 20161226 4

<h4>Aim</h4>To develop a survey to help define the main problems in radiological clinical trials.<h4>Methods</h4>Since 2006, we have managed seven different radiological clinical trials recruiting patients in academic and non-academic centres. We developed a preliminary questionnaire using a four-round Delphi approach to identify problems occurring in radiological clinical trials run at our centre. We investigated the recruitment experience, involvement of all multi-disciplinary team members and ...[more]

PMID: 28074173

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Project description:ObjectiveInformation overload remains a challenge for patients seeking clinical trials. We present a novel system (DQueST) that reduces information overload for trial seekers using dynamic questionnaires.Materials and methodsDQueST first performs information extraction and criteria library curation. DQueST transforms criteria narratives in the ClinicalTrials.gov repository into a structured format, normalizes clinical entities using standard concepts, clusters related criteria, and stores the resulting curated library. DQueST then implements a real-time dynamic question generation algorithm. During user interaction, the initial search is similar to a standard search engine, and then DQueST performs real-time dynamic question generation to select criteria from the library 1 at a time by maximizing its relevance score that reflects its ability to rule out ineligible trials. DQueST dynamically updates the remaining trial set by removing ineligible trials based on user responses to corresponding questions. The process iterates until users decide to stop and begin manually reviewing the remaining trials.ResultsIn simulation experiments initiated by 10 diseases, DQueST reduced information overload by filtering out 60%-80% of initial trials after 50 questions. Reviewing the generated questions against previous answers, on average, 79.7% of the questions were relevant to the queried conditions. By examining the eligibility of random samples of trials ruled out by DQueST, we estimate the accuracy of the filtering procedure is 63.7%. In a study using 5 mock patient profiles, DQueST on average retrieved trials with a 1.465 times higher density of eligible trials than an existing search engine. In a patient-centered usability evaluation, patients found DQueST useful, easy to use, and returning relevant results.ConclusionDQueST contributes a novel framework for transforming free-text eligibility criteria to questions and filtering out clinical trials based on user answers to questions dynamically. It promises to augment keyword-based methods to improve clinical trial search.

Dataset Information

Radiological clinical trials: Proposal of a problem-finding questionnaire to improve study success.

Publications

Radiological clinical trials: Proposal of a problem-finding questionnaire to improve study success.

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