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Abstract
It has been proposed that it should be possible to identify patterns of daily occupations that promote health or cause illness. This study aimed to develop and to evaluate.a process for analysing and characterising subjectively perceived patterns of daily occupations, by describing patterns as consisting of main, hidden, and unexpected occupations. Yesterday diaries describing one day of 100 working married mothers were collected through interviews. The diaries were transformed into time‐and‐occupation graphs. An analysis based on visual interpretation of the patterns was performed. The graphs were grouped into the categories low, medium, or high complexity. In order to identify similarities the graphs were then compared both pair‐wise and group‐wise. Finally, the complexity and similarities perspectives were integrated, identifying the most typical patterns of daily occupations representing low, medium, and high complexity. Visual differences in complexity were evident. In order to validate the Recognition of Similarities (ROS) process developed, a measure expressing the probability of change was computed. This probability was found to differ statistically significantly between the three groups, supporting the validity of the ROS process.