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41128-01 - Vorlesung mit Übungen: Implementation Science 4 KP

Semester Herbstsemester 2019
Angebotsmuster Jahreskurs
Dozierende Sabina M. De Geest (sabina.degeest@unibas.ch, BeurteilerIn)
Olivia Yip (olivia.yip@unibas.ch)
Inhalt Autumn semester
-Introduction to Implementation Science
-Implementation Research Designs and Implementation Outcomes
-Contextual Analysis
-Implementation Strategies
Spring semester
-Evaluation of High Quality Evidence / Meta-analysis
-Intervention Development
-Methods for Patient and Public Involvement
-Reporting of Implementation Science Studies and implementation science research infrastructure
Lernziele Learning Objectives:
1. Position implementation science in the research pipeline and identify different terminology used to describe implementation science internationally.
2. Recognize and critically evaluate common implementation science study designs and methods for addressing implementation research aims.
3. Distinguish implementation outcomes from efficacy, service, and summative outcomes.
4. Apply key implementation science constructs and theories in developing an implementation science project.
5. Argue the need for contextual analysis in implementation science and describe how to perform a contextual analysis methodologically.
6. Understand the evidence base of implementation strategies and discuss their difference with evidence-based interventions.
7. Participate in discussion on ongoing implementation science projects and apply learned theoretical knowledge in the discussions.
Learning Objectives FS 2020:
8. Understand the role of meta-analysis in evaluating the strength of evidence of interventions and assessing the quality of evidence.
9. Argue the need for a multi-phase approach in intervention development and provide an example of intervention development in implementation science.
10. Discuss patient and public involvement (PPI) in the whole research cycle and argue the role of PPI in implementation science.
12. Apply the reporting guidelines for implementation science research studies in reviewing an implementation science paper.
13. Provide examples of elements that need to be put into place to develop an implementation science research infrastructure.
Literatur Required and optional readings on implementation science research papers are assigned in preparation for each lecture.
Weblink ADAM

 

Teilnahmebedingungen Studierende im Studiengang Pflegewissenschaft Vertiefung Research; PhD students involved in Implementation Science projects
Anmeldung zur Lehrveranstaltung Belegen
Unterrichtssprache Englisch
Einsatz digitaler Medien Online-Angebot fakultativ

 

Intervall wöchentlich
Datum 25.09.2019 – 17.12.2019
Zeit Dienstag, 09.00-11.00 Bernoullistrasse 28, Seminarraum 7

Termine und Zeiten siehe "Termine und Räume" im VV sowie Semesterkalender auf ADAM.

Datum Zeit Raum
Mittwoch 25.09.2019 09.00-11.00 Uhr Bernoullistrasse 28, Seminarraum 7
Dienstag 01.10.2019 09.00-11.00 Uhr Bernoullistrasse 28, Seminarraum 7
Dienstag 12.11.2019 14.00-16.00 Uhr Bernoullistrasse 28, Seminarraum 7
Dienstag 10.12.2019 13.00-15.00 Uhr Bernoullistrasse 28, Seminarraum 7
Dienstag 17.12.2019 14.30-16.00 Uhr Kollegienhaus, Hörsaal 119
Module Modul Vertiefung Research (Masterstudium: Pflegewissenschaft)
Leistungsüberprüfung Lehrveranst.-begleitend
Hinweise zur Leistungsüberprüfung Written exam 60%
The content of the course will be tested in two written exams (at the end of both semesters) where students have to apply the learned content. This will be primarily using examples from the implementation science literature.
Active participation and presence in course 40%
Students need to be present in at least 80% of the lectures – participation in whole day session is optional for Master’s students and obliged for PhD students.
An-/Abmeldung zur Leistungsüberprüfung Anmelden: Belegen; Abmelden: Institut
Wiederholungsprüfung keine Wiederholungsprüfung
Skala 1-6 0,1
Wiederholtes Belegen einmal wiederholbar
Zuständige Fakultät Medizinische Fakultät
Anbietende Organisationseinheit Institut für Pflegewissenschaft

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