Incentives for recruiting trainee participants in medical education research

Stovel, Rebecca; Ginsburg, Shiphra; Stroud, Lynfa; Cavalcanti, Rodrigo B.; Devine, Luke

doi:10.1080/0142159x.2017.1395402

Cited by 6 publications

(15 citation statements)

References 41 publications

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“…We discover 59 papers (39%) from the set of ACM DEV papers (which were selected for our review regardless of title) that have some amount of human subject work 21% mentioned incentive systems and only 6% thoroughly described incentive systems. These are lower percentages than the nearest related work, which found 8% of work directly describing incentive systems [52].…”

Section: Incentive Systems In the Wildcontrasting

confidence: 63%

“…We evaluate incentive systems in the wild by performing a literature review of 175 papers across three development-related ACM communities. We also consider work containing descriptions of incentive systems discovered from an examination of 215 publications from medical journals [52]. We evaluate the performance of OINK under an ongoing deployment managed by the authors where participants are incentivized for nine different types of activities.…”

Section: Discussionmentioning

confidence: 99%

“…Stovel et al examine 251 articles in five medical education journals to extract the incentives used [52]. They find 8% of papers directly describe the incentive system employed.…”

Section: Incentive Systems In the Literaturementioning

confidence: 99%

“…We review prior CHI and ICTD proceedings based on titles that seem likely to have human factors research. Finally, we review papers identified by Stovel et al that contain incentive system descriptions from the medical community [52]. Because of the intuition that a survey might have a simpler incentive system that would be less likely to be reported in the literature, we then classify each paper's incentive system as either triggered by a survey or by a deployment.…”

Section: Incentive Systems In the Wildmentioning

confidence: 99%

“…These experiments often encourage user participation by providing incentives to participants [14,30,50,60]. It is known that incentive system design choices can have significant effects on the results of a study [5,14,22,52], yet incentive systems receive relatively little discussion in the literature and, even when they do, there is no standard vocabulary to describe them [25,52].…”

Section: Introductionmentioning

confidence: 99%

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The open incentive kit (OINK)

Klugman

Correa

Pannuto

et al. 2019

Proceedings of the Tenth International Conference on Information and Communication Technologies and Development

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Incentives are a key facet of human studies research, yet the stateof-the-art often designs and implements incentive systems in an ad-hoc, on-demand manner. We introduce the first vocabulary for formally describing incentive systems and develop a software infrastructure that enables UI-based graphical generation of complex, auditable, reliable, and reproducible incentive systems. We call this infrastructure the Open INcentive Kit (OINK). A review of recent literature from several communities finds that of the one hundred and twenty-one publications that incorporate incentives, only thirty-one describe their incentive system in detail, and all of these could be implemented using OINK. We evaluate OINK in practice by using it for an active energy monitoring deployment in Ghana and find that OINK successfully facilitates thousands of individual incentive payments. Finally, we describe our efforts to generalize OINK for different research communities, specifically focusing on architectural decisions around extensibility to support unanticipated use cases. OINK is free and open-source software. CCS CONCEPTS • Human-centered computing Field studies; • Information systems Incentive schemes.

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Section: Incentive Systems In the Wildcontrasting

confidence: 63%

Section: Discussionmentioning

confidence: 99%

“…Stovel et al examine 251 articles in five medical education journals to extract the incentives used [52]. They find 8% of papers directly describe the incentive system employed.…”

Section: Incentive Systems In the Literaturementioning

confidence: 99%

Section: Incentive Systems In the Wildmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

The open incentive kit (OINK)

Klugman

Correa

Pannuto

et al. 2019

Proceedings of the Tenth International Conference on Information and Communication Technologies and Development

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Features of the learner, task, and instructional environment that predict cognitive load types during patient handoffs: Implications for instruction

Young

Thakker

John

et al. 2021

Applied Cognitive Psychology

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Summary We used the cognitive load inventory for handoffs (CLIH) to identify predictors of cognitive load types during patient handoffs in order to identify opportunities to improve instruction. In 2019, out of a total of 1,807 residents and fellows within a 24‐hospital health system, 693 (38.4%) completed the CLIH after a patient handoff. Multivariable regression yielded predictors for each cognitive load type. Intrinsic load associated with features of the learner (fatigue positively associated) and task (higher complexity clinical setting, number of patients, and handoff length positively associated). Extraneous load associated with learner (fatigue positively associated, and number of times trained in the verbal protocol negatively associated) and task design (number of sources of written information positively associated). Germane load associated with learner (level of training negatively associated, and fatigue positively associated) and instructional environment (interruptions negatively associated and formal feedback positively associated). Implications for instructional design are explored.

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