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This study aims to reveal the distribution of topics, and the associations among them, in information behavior research from 2009 to 2018. Working with a collection of 6744 publications from the Web of Science database, co-word analysis is used to investigate the overall topic structure, the associations among the topics, and their evolution in different years, which is supplemented by visualization with science maps. The results uncovered an unbalanced distribution of topics, and that the topics cluster into six communities representing subdivisions of this field: information behavior in patient-centered studies; information interaction in the digital environment; information literacy in health and academic contexts; health literacy on the Internet; information behavior in child-centered studies; and information behavior in medical informatics. The findings supplement and provide refinements to work on the state of this field, and help researchers obtain an overview of the past decade to guide their future work.

PurposeDrawing on the Health Belief Model (HBM), this study aims to investigate the roles of health beliefs (i.e. perceived susceptibility, perceived severity, perceived benefits, perceived barriers, health self-efficacy and cues to action) in promoting college students’ smartphone avoidance intention.Design/methodology/approachEmpirical data were collected through a cross-sectional survey questionnaire administered to 4,670 student smartphone users at a large university located in Central China. Further, a two-step Structural Equation Modeling was conducted using AMOS 22.0 software to test the hypothesized relationships in the research model.FindingsAnalytical results indicate that (1) perceived susceptibility, perceived severity, perceived benefits and health self-efficacy positively influence users’ smartphone avoidance intention; (2) perceived barriers negatively influence smartphone avoidance intention, while (3) cues to action reinforce the relationships between perceived susceptibility/perceived benefits and smartphone avoidance intention, but attenuate the relationships between perceived barriers/health self-efficacy and smartphone avoidance intention.Research limitations/implicationsThis study demonstrates that HBM is invaluable in explaining and promoting users’ smartphone avoidance intention, thereby extending extant literature on both HBM and smartphone avoidance.Originality/valueResearch on smartphone avoidance is still in a nascent stage. This study contributes to the field by offering a fresh theoretical lens for pursuing this line of inquiry together with robust empirical evidence.

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Extant literature on measuring the performance of physicians’ knowledge contribution in an online health community (OHC) is limited. To address this gap, this article aims to (1) develop a measurement model for physicians’ knowledge contribution performance; (2) use BP neural network to assign reasonable weight to each indicator of the model; and (3) explore the status and differences of knowledge contribution performance among a group of physicians. Based on the sample of 5407 infectious disease physicians in a Chinese OHC, we propose the measurement model by integrating physicians’ active knowledge contribution (AKC) and responsive knowledge contribution (RKC), covering 11 dimensions of contribution quantity and quality. We employ the BP neural network to optimise the model weights using the initial weight of the model obtained by the entropy method. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is used to evaluate the performance of physicians’ knowledge contribution in the OHC. The results show that it is feasible to use BP neural network to assign model weights. The distribution of physicians’ knowledge contribution performance is uneven; only a few have a high-level knowledge contribution performance. Meanwhile, a significant positive correlation exists between a physician’s title and respective knowledge contribution performance. Our research may contribute to related literature and practices by offering a fine-grained understanding of the performance of physicians’ knowledge contribution.