ArticleThe journal of extra-corporeal technology2020
Perfusion Recruitment Strategies Using Choice-Based Conjoint Analysis.
Article in The journal of extra-corporeal technology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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
2 citing papers in PubMed, 1 synthesis or guideline pooled it, 1 citations in OpenAlex.
- The Evolving Landscape of Discrete Choice Experiments in Health Economics: A Systematic Review.PharmacoEconomics · 2025Pooled it
- Predictive factors for determining first-attempt success on the American Board of Cardiovascular Perfusion Certification Exams for graduates of a master's level perfusion education program.The journal of extra-corporeal technology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Perfusionists are leaving the workforce in higher rates as baby-boomers retire, yet the volume of cases involving perfusion continues to increase. This change has resulted in a high-demand market with organizations competing for the same candidates. The purpose of this study was to use a choice-based conjoint (CBC) analysis to determine what attributes of employment opportunities are most important to perfusionists so hiring organizations are better equipped to produce employment offers specific to each candidate. The Sawtooth Software Discover program was used to create a CBC survey that was distributed to perfusionists. After a series of demographic questions, respondents chose between three employment offers that comprised eight attributes, each with three varying options. Completed surveys were analyzed using the Discover software, producing importance scores. Two hundred forty surveys were completed, 154 (64%) male and 86 (36%) female. Extracorporeal membrane oxygenation (ECMO) impact to the perfusionist and hours worked per week ranked most important, at 19.4% and 17.5%, respectively. A significant difference exists between ECMO impact to perfusionists and all other attributes. The least important attributes were annual continuing education funds and sign-on bonus/relocation, at 6.8% and 4.7%, respectively. Respondents in their 20s and 30s find the importance of ECMO impact to be significantly less important than those in their 50s. Perfusionists with a master's degree believe salary to be significantly more important than perfusionists with other types of perfusion education. Based on the respondents who completed this survey, the impact ECMO has on the perfusionist was the most significant job attribute. Offering large sign-on bonuses and relocation packages to entice new employees is not indicated as a viable way to satisfy perfusionists. Appropriate management of hours worked, days on call, and how ECMO impacts the perfusionists will be most impactful in recruitment of new employees.
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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.