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BioMed Central, BMC Medical Informatics and Decision Making, 1(15), 2015

DOI: 10.1186/s12911-015-0168-0

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Exploring the relationship between patients’ information preference style and knowledge acquisition process in a computerized patient decision aid randomized controlled trial

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Postprint: archiving allowed
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Data provided by SHERPA/RoMEO

Abstract

Abstract Background We have shown in a randomized controlled trial that a computerized patient decision aid (P-DA) improves medical knowledge and reduces decisional conflict, in early stage papillary thyroid cancer patients considering adjuvant radioactive iodine treatment. Our objectives were to examine the relationship between participants’ baseline information preference style and the following: 1) quantity of detailed information obtained within the P-DA, and 2) medical knowledge. Methods We randomized participants to exposure to a one-time viewing of a computerized P-DA (with usual care) or usual care alone. In pre-planned secondary analyses, we examined the relationship between information preference style (Miller Behavioural Style Scale, including respective monitoring [information seeking preference] and blunting [information avoidance preference] subscale scores) and the following: 1) the quantity of detailed information obtained from the P-DA (number of supplemental information clicks), and 2) medical knowledge. Spearman correlation values were calculated to quantify relationships, in the entire study population and respective study arms. Results In the 37 P-DA users, high monitoring information preference was moderately positively correlated with higher frequency of detailed information acquisition in the P-DA ( r  = 0.414, p  = 0.011). The monitoring subscale score weakly correlated with increased medical knowledge in the entire study population ( r  = 0.268, p  = 0.021, N  = 74), but not in the respective study arms. There were no significant associations with the blunting subscale score. Conclusions Individual variability in information preferences may affect the process of information acquisition from computerized P-DA’s. More research is needed to understand how individual information preferences may impact medical knowledge acquisition and decision-making.