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Information on healthcare providers on the internet can be found in both public reports and/or anecdotal comments. Healthcare consumers rely more on the anecdotal comments than public reports as they are easier to understand, more engaging and convincing. However, the anecdotal comments can be misleading as they are based on a relatively smaller and less representative sample. Hence, it’s important to understand how users make sense of the anecdotal information and define the factors that influence their decisions. This study utilized the domain of dentistry, focusing on how the nature of the review and other decision aids affect the sensemaking process of healthcare seekers. We conducted a mixed-method study with twenty participants, finding the nature of the review (the text) to be the most influential factor and the wait time to be the least contributing factor in the decision.

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Visual inspection is used in many areas due to the potential high costs of inspection error such as injury, fatality, loss of expensive equipment, scrapped items, rework, or failure to procure repeat business. This study presents an application of hidden Markov models (HMM) to fixations' sequences analysis during visual inspection of front panels in a home appliance facility. The eye tracking data are gathered when quality control operators perform their tasks. The results support the difference between expert and novice operator. Moreover, the article demonstrates four HMMs with two and three hidden states both for novice and experienced operators and provides analysis and discussion of the outcomes. Keywords Human factors • Visual inspection • Human visual behavior • Hidden Markov models • Eye tracking technology B Rafał Michalski