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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/23976

Title: The Value of E-Learning for the Prevention of Healthcare-Associated Infections
Authors: Labeau, Sonia O.
Rello, Jordi
Dimopoulos, George
Lipman, Jeffrey
Sarikaya, Aklime
Ozturk, Candan
Vandijck, Dominique M.
Vogelaers, Dirk
Vandewoude, Koenraad
Blot, Stijn I.
Issue Date: 2016
Abstract: Healthcare workers (HCWs) lack familiarity with evidence-based guidelines for the prevention of healthcare-associated infections (HAIs). There is good evidence that effective educational interventions help to facilitate guideline implementation, so we investigated whether e-learning could enhance HCW knowledge of HAI prevention guidelines. We developed an electronic course (e-course) and tested its usability and content validity. An international sample of voluntary learners submitted to a pretest (T0) that determined their baseline knowledge of guidelines, and they subsequently studied the e-course. Immediately after studying the course, posttest 1 (T1) assessed the immediate learning effect. After 3 months, during which participants had no access to the course, a second posttest (T2) evaluated the residual learning effect. A total of 3,587 HCWs representing 79 nationalities enrolled: 2,590 HCWs (72%) completed T0; 1,410 HCWs (39%) completed T1; and 1,011 HCWs (28%) completed T2. The median study time was 193 minutes (interquartile range [IQR], 96–306 minutes) The median scores were 52% (IQR, 44%–62%) for T0, 80% (IQR, 68%–88%) for T1, and 74% (IQR, 64%–84%) for T2. The immediate learning effect (T0 vs T1) was +24% (IQR, 12%–34%; P<.001), and a residual effect (T0 vs T2) of +18% (IQR 8–28) remained (P<.001). A 200-minute study time was associated with a maximum immediate learning effect (28%). A study time >300 minutes yielded the greatest residual effect (24%). Moderate time invested in e-learning yielded significant immediate and residual learning effects. Decision makers could consider promoting e-learning as a supporting tool in HAI prevention.
URI: http://hdl.handle.net/1942/23976
DOI: 10.1017/ice.2016.107
ISI #: 000382896800007
ISSN: 0899-823X
Category: A1
Type: Journal Contribution
Validation: ecoom, 2017
Appears in Collections: Research publications

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