Background: Quantity, quality, and impact of scientific publications are used to assess national, institutional, and individual levels of research productivity. While the importance of quality research is stressed among the medical research community, minimal research has been conducted on analyzing which factors affect research productivity. Current literature assesses the quality of research institutions rather than that of individual researchers; there is also no research on the difference between high-impact researchers and other researchers. This study, conducted in 2015, sought to investigate the underlying reason for high-throughput authors' success by understanding their similar habits and motivations leading to high productivity. Methods: The authors conducted a qualitative study via interviews of high-throughput researchers from around the world. Semi-structured interview scripts guided the interviews in accordance to the grounded theory method for qualitative studies. Broad themes from preliminary interviews were identified and explored in subsequent interviews. Results: Qualitative analysis of participant interviews identified eight major themes: “Writing habits,” “Writing strategy,” “Previous training and writing experience,” “Major driver,” “Balancing volume and impact of publications,” “Ideal and non-ideal conditions,” “Timelines,” and “Role of networking on high-throughput productivity.” These themes are not exclusive nor required qualities of high-throughput researchers but highlight similarities and broadly unifying characteristics of these researchers. Conclusion:This study identified the common qualities and attitudes of high-throughput researchers. We found common factors in most individuals that can be considered markers of high productivity.
-Dep ar tm en t o f S u r g er y , D i vi s io n o f Or th op aed i cs. Du ke Un i ver s i ty . Du r h am /NC , U S A 5-As s is tan t Pr o fes so r . D e p ar tm en t o f Su r g er y , D i v is ion o f Ur o lo g y . Du ke Un i ver s it y. Du r h am /N C , US A 6-D iv i s ion o f Em er g en c y M ed ic in e , Dep ar tm en t of Su r g er y . Du k e Un i ver s it y M ed ic al Cen te r ,Du r h a m /NC , U S A. ABSTRACTBackgro und: In cost-effectiveness analyses, Quality -Adjusted Life Years (QALY) remains one of the most widely used health effect measure. Among the various methods of estimating utility values, time trade -off (TTO) has traditionally been one of the dominant methods for eliciting utilities, however it has been presenting several practical impediments to provide a high and fast collecting process. Objective: To test a method of collecting TTO -derived utilities using a plat form called Amazon's Mechanical Turk (MTurk) that provides reliable, fast and inexpensive data. Methods: A pre -programmed interactive questionnaire was design to simulate a live TTO interview using Qualtrics. To validate the results members of the Research on Research (RoR) Group not aware of the research agreed to answer the same questions on a videoco nference live interview. We determined feasibility through assessment quality and cost/benefit relation indicators. In addition, this paper followed the fram ework for reproducible research reports proposed by our group. Results: Results: Our results showed that the MTurk populatio n is representative of the US population (based on 2012 census) and there were no differences on the willingness to live when compar ing the MTurk sample and the live interview sample, and also no differences of the WTL when comparing the different questionnaire designs developed. Preference results showed differences only for race (between others and African -Americans, and other and wh ite), and overall median values of 0.83 (Q1=0.83; Q3=0.90). Conclusions: MTurk is a reliable web place to collect large sample using the TTO method, and should be used to collect utility data for CEA.Keywords: cost -effectivenes s, Quality -Adjusted Life Years , time trade -off. Rev i sta El etr ôn ic a Ge st ão & Soc ied ad ev. 12 , n . 31 , p . 2 17 3 -2 DATA C O L L EC T I O N M E C H A N I S M SMTurk is a web platform that allows PAYMENTIn previo us research using MTurk, the amount of participation is directly related to financial incentives18. The amount paid for each TTO session varied throughout the data collection phase. Initially we paid 20 cents for the Jumping questions; however we noticed a low rate of adherence with this amount. We therefore decided to increase the payment to 40 cents in the Slider questionnaire. TECHNICAL FEATURESWe a priori determined that the jumping questions questionnaire required approximately 7.5 minutes to be answered ELIGIBILIT Y CRITERIAFor the MTurk population the inclusio n criteria were age greater than 18 years old (MTurk workers are r equired to be 18 years of age or old...
Objective: The objective of this study was to perform a qualitative study to identify commonalities and differences in reasoning processes between these groups.Methods: A phenomenological qualitative study based on transcriptions of physicians and statisticians conceptualizing clinical cases and clinical research questions. Interviews were carried out with nine statisticians and sixteen physicians contacted virtually. The main outcome measures were emerging themes that were common to both expert groups.Results: Both groups used conceptual models -although different models- during their reasoning processes, but their concepts were not common between the groups complicating the exchange of information. Both groups were unaware that their specialty language was frequently inaccessible to non-specialists or specialists from other fields, which leads to communication difficulties. These difficulties were broadly classified into translational problems of field-specific terms and concepts. Field-specific terms would sometimes lead to misinterpretations while the translation of field-specific concepts often leads to content loss.Conclusions: The use of field-specific terms and concepts can lead to confusion and misinterpretation. Teams would benefit from taxonomies containing terms that can be understood by specialists from both disciplines
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