PHVIT9510 Concept and Theory Development in Health Sciences Course description

This course covers research into key phenomena originating from human experience of health and illness. Such phenomena can be perceptions of quality of life, hope, coping, pain, body, dignity, and suffering, and serve as the basis for developing concepts and theories in the health sciences. The course covers different methods for concept and theory development; for example, the hybrid model of concept development, semantic concept analysis, Walker and Avant's model for theory development, and grounded theory. The methods are applied to selected phenomena, concepts, and theories.

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On completion of the course, the PhD candidate has achieved the following learning outcomes, defined in terms of knowledge, skills, and general competence:

Knowledge

The PhD candidate:

• is at the forefront of knowledge of methodologies related to the development of concepts and theories
• has an in-depth understanding of the relationship between human experience, concepts, and theories in a health science context

Skills

The PhD candidate can:

• develop a conceptual and/or theoretical framework related to his or her own research
• identify relevant clinical phenomena in order to develop concepts and theories
• analyse and interpret research findings related to concept and theory development
• address complex scientific issues and challenge established knowledge and practice in concept and theory development

General competence

The PhD candidate can:

• argue in favour of particular methodologies in concept and theory development on the basis of scientific theory
• participate in discussions on concept and theory development

Work and teaching methods consist of lectures, seminars, and self-study. The outcomes of the seminars are presented and discussed in plenary sessions.

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Candidates must write an essay based on a concept and/or theory of their choice and apply principles from the methods of concept and theory development presented in the course. The essay must consist of up to 5,000 words and must be submitted no more than 2 weeks after the end of the course.

All

This course will present complex systems (cellular automata, networks, and agent-based) modelling and programming through state-of-the-art artificial intelligence methods that take inspiration from biology (sub-symbolic and bio-inspired AI methods), such as evolutionary algorithms, neuro-evolution, artificial development, swarm intelligence, evolutionary and swarm robotics.

No formal requirements over and above the admission requirements.