2024
Content Analysis in Health Sciences
Name: Content Analysis in Health Sciences
Code: CMS13715D
6 ECTS
Duration: 15 weeks/156 hours
Scientific Area:
Health Sciences
Teaching languages: Portuguese
Languages of tutoring support: Portuguese
Presentation
The UC provides, learn specialized knowledge to the autonomous development of content analysis in diverse contexts of research and intervention, deepen methodological skills for critical, holistic and ethically sustained reflection with a view to understanding social reality.
Sustainable Development Goals
Learning Goals
The main objective is to develop specialized knowledge that provides content analysis (CA) skills in diverse contexts of research and intervention in SC.
Students should be able to: a) present and critically discuss the theoretical-epistemological assumptions behind the CA in HS, with an emphasis on its potential and challenges in broad and multidisciplinary contexts; b) distinguish and operationalize methodological approaches adjusted to different contexts, showing mastery in the use of different languages and techniques of CA; c) design effective plans for implementing CA, with sampling criteria, constitution of the corpus, manual and computer-assisted analytical strategies; d) construct interpretive categories and discuss the limits of inference in the analysis of small and big data; e) choose reasonably between different visualization techniques and write output products aiming the presentation and multi-format dissemination of scientific results.
Students should be able to: a) present and critically discuss the theoretical-epistemological assumptions behind the CA in HS, with an emphasis on its potential and challenges in broad and multidisciplinary contexts; b) distinguish and operationalize methodological approaches adjusted to different contexts, showing mastery in the use of different languages and techniques of CA; c) design effective plans for implementing CA, with sampling criteria, constitution of the corpus, manual and computer-assisted analytical strategies; d) construct interpretive categories and discuss the limits of inference in the analysis of small and big data; e) choose reasonably between different visualization techniques and write output products aiming the presentation and multi-format dissemination of scientific results.
Contents
I. Theoretical-epistemological assumptions of content analysis in health sciences: outline, potentialities and challenges.
II. Methodological approaches: contexts, languages and techniques of content analysis.
III. Sampling, corpus, manual and computer-assisted analytical strategies.
IV. Categorization and inference: reliability and validity in the analysis of small and big data.
V. Visualization techniques, scientific writing and findings dissemination.
II. Methodological approaches: contexts, languages and techniques of content analysis.
III. Sampling, corpus, manual and computer-assisted analytical strategies.
IV. Categorization and inference: reliability and validity in the analysis of small and big data.
V. Visualization techniques, scientific writing and findings dissemination.
Teaching Methods
Lectures and practical lessons, tutorial follow-up and e-learning solutions. According to internal regulation, students may choose between a continuous assessment process or a final examination. Continuous assessment: written essay with oral presentation and discussion in (100%). Final examination: written examination (100%).
Certificações
