This dissertation focuses on testing a new method of capturing the influences on health-related behaviours, called Health Behaviour Mapping. This technique identifies determinants of health behaviours, by combining motivations, experiences and environmental contexts that influence health-related behaviours and decisions. Similar patterns of influences are used to characterise groups in a population. The work demonstrates two applications of the method, one in a healthy population, the other in a chronic disease population. Reliability and validity tests on the data capture and analysis components of the methods were conducted. The determinants of health behaviours were explored in a sample of healthy respondents and a sample of breast cancer patients for three behaviour outcomes: optimising health, food choice and quality of life. For the sample of healthy respondents, a variety of strategies are used to optimise, their health outcomes (diet 66% vitamin/mineral supplementation 21%, lifestyle changes 83%, and psychosocial responses 34%). This sample was clustered based on unique combinations of decision-making influences for each behaviour outcome. Eight out of nine decision-making influences had similar patterns of occurrence for two of the behaviour outcomes. For the patterns that were not similar, these differences appear to reflect he broader context of health-related behaviours explored with the respondent. For the sample of breast cancer patients, a variety of strategies used to optimise their treatment outcomes were identified (diet 74%, vitamin/mineral supplementation 84%, non-mainstream therapies 68%, lifestyle changes 39%, and psychosocial responses 90%). This sample was also clustered based on the similarities of unique combinations of decision-making influences for each behaviour outcome. In this sample, different combinations of decision-making influences are unique to the behaviour outcome as only two of the five categories of influences shared similar patterns of occurrence (p < 0.05). Eight decision-making influences were not common. Comparing the two samples for the same behaviour outcome, food choice, identified many shared influences supporting the notion that the differences may be attributable to the health status of the individual. This new method identifies the diversity of reasons for behaviours in a sample and that the combination of patterns is useful in grouping respondents. Some of these patterns of influences are similar within and between populations and others are dependent on the health-related behaviour. Health Behaviour Mapping provides comprehensive and reliable information that is relevant for health services. The connections between reasons and contexts provide a new perspective that can be used to idea program or service strategies to optimise health for a specific population.