Search Results Heading

MBRLSearchResults

mbrl.module.common.modules.added.book.to.shelf
Title added to your shelf!
View what I already have on My Shelf.
Oops! Something went wrong.
Oops! Something went wrong.
While trying to add the title to your shelf something went wrong :( Kindly try again later!
Are you sure you want to remove the book from the shelf?
Oops! Something went wrong.
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
    Done
    Filters
    Reset
  • Discipline
      Discipline
      Clear All
      Discipline
  • Is Peer Reviewed
      Is Peer Reviewed
      Clear All
      Is Peer Reviewed
  • Item Type
      Item Type
      Clear All
      Item Type
  • Subject
      Subject
      Clear All
      Subject
  • Year
      Year
      Clear All
      From:
      -
      To:
  • More Filters
2 result(s) for "Kassianos, A.P."
Sort by:
Resource use during systematic review production varies widely: a scoping review
•Evidence on resource use is limited to studies reporting mostly on the resource “time” and not always under real life conditions.•Administration and project management, study selection, data extraction, and critical appraisal seem to be very resource intensive, varying with the number of included studies, while protocol development, literature search, and study retrieval take less time.•Lack of experience and domain knowledge, lack of collaborative and supportive software, as well as lack of good communication and management can increase resource use during the systematic review process. We aimed to map the resource use during systematic review (SR) production and reasons why steps of the SR production are resource intensive to discover where the largest gain in improving efficiency might be possible. We conducted a scoping review. An information specialist searched multiple databases (e.g., Ovid MEDLINE, Scopus) and implemented citation-based and grey literature searching. We employed dual and independent screenings of records at the title/abstract and full-text levels and data extraction. We included 34 studies. Thirty-two reported on the resource use—mostly time; four described reasons why steps of the review process are resource intensive. Study selection, data extraction, and critical appraisal seem to be very resource intensive, while protocol development, literature search, or study retrieval take less time. Project management and administration required a large proportion of SR production time. Lack of experience, domain knowledge, use of collaborative and SR-tailored software, and good communication and management can be reasons why SR steps are resource intensive. Resource use during SR production varies widely. Areas with the largest resource use are administration and project management, study selection, data extraction, and critical appraisal of studies.
Educators’ perspectives of adopting virtual patient online learning tools to teach clinical reasoning in medical schools: a qualitative study
Background Learning tools using virtual patients can be used to teach clinical reasoning (CR) skills and overcome limitations of using face-to-face methods. However, the adoption of new tools is often challenging. The aim of this study was to explore UK medical educators’ perspectives of what influences the adoption of virtual patient learning tools to teach CR. Methods A qualitative research study using semi-structured telephone interviews with medical educators in the UK with control over teaching materials of CR was conducted. The Consolidated Framework for Implementation Research (CFIR), commonly used in healthcare services implementation research was adapted to inform the analysis. Thematic analysis was used to analyse the data. Results Thirteen medical educators participated in the study. Three themes were identified from the data that influenced adoption: the wider context (outer setting); perceptions about the innovation; and the medical school (inner context). Participants’ recognition of situations as opportunities or barriers related to their prior experiences of implementing online learning tools. For example, participants with experience of teaching using online tools viewed limited face-to-face placements as opportunities to introduce innovations using virtual patients. Beliefs that virtual patients may not mirror real-life consultations and perceptions of a lack of evidence for them could be barriers to adoption. Adoption was also influenced by the implementation climate of the setting, including positioning of CR in curricula; relationships between faculty, particularly where faculty were dispersed. Conclusions By adapting an implementation framework for health services, we were able to identify features of educators, teaching processes and medical schools that may determine the adoption of teaching innovations using virtual patients. These include access to face-to-face teaching opportunities, positioning of clinical reasoning in the curriculum, relationship between educators and institutions and decision-making processes. Framing virtual patient learning tools as additional rather than as a replacement for face-to-face teaching could reduce resistance. Our adapted framework from healthcare implementation science may be useful in future studies of implementation in medical education.