Table 1.
Study design and aim of the studies included in the review (N=32).
| Author, date | Study design | Aim |
| Attfield et al, 2006 [6] | Qualitative interview study; cross-sectional | Explore information seeking of patients before and after consultations, its situational influences, and its impact on patient-provider relationships |
| Briet et al, 2014 [19] | Quantitative; cross-sectional analysis of website queries | Explore the nature and content of questions and answers on a health website, and to examine the situations of patients asking questions |
| Cartrightet et al, 2011 [20] | Longitudinal log-based study | Analyze the search activity of users researching health information online and identify goals and patterns of search behavior |
| Chin, 2009 [21] | Experimental between subjects design: 2×2 (ill–well-defined tasks, younger-older users) | Compare older and younger adults in their performance and search behavior in ill and well-defined tasks |
| Chin & Fu, 2010 [22] | Experimental between subjects design: 2×2×2 (older-younger adults, parts-systems interface, parts-system task) | Examine differences between older and younger adults in interacting with different online search tasks and interfaces |
| Cooper et al, 2013 [23] | Qualitative study (focus groups) | Explore how women would evaluate symptoms associated with gynecologic cancers |
| Cumming et al, 2010 [24] | Cross-sectional Web-based survey study | Evaluate digital storytelling videos (videos of people talking about their own experiences) about help seeking for menopausal symptoms |
| De Choudhury et al, 2014 [25] | Cross-sectional survey study (quantitative + qualitative data) + longitudinal log-based study | Research the prevalence of health activities on social media and search engines; characterize health activities on the different platforms and describe how people evaluate information obtained from these |
| Fiksdal et al, 2014 [26] | Qualitative focus group study | To gain a deeper understanding of online health-searching behavior to inform future developments of personalizing information searching and content delivery. |
| Fox & Duggan, 2013 [1] | Nationwide cross-sectional survey | The Pew Internet & American Life Project is an initiative of the Pew Research Center, a nonprofit “fact tank” that provides information on the issues, attitudes and trends shaping America and the world |
| Hay et al, 2008 [27] | Mixed-methods survey and interview study | Understand the extent and reasons for online research prior to first appointments for patients in a rheumatology clinic |
| Keselman et al, 2008 [28] | Cross-sectional qualitative interview and Think Aloud study. | Explore users’ information-seeking difficulties by conceptualizing information seeking as a form of hypothesis testing, and to examine the role of users’ competencies in online information seeking |
| Lauckner & Hsieh, 2013 [29] | Experimental 2×2 design (position: top-bottom; frequency: high-low) | Does the position and frequency of serious conditions in search results affect perceived severity and susceptibility, and are they related to negative emotional outcomes? Do health literacy and experience with online health seeking moderate these relationships? |
| Luger, 2014 [30] | Experimental 2×2 design: two different symptom vignettes (mononucleosis or scarlet fever), either Google or WebMD | Explore older adults’ online health seeking to determine the cognitive and diagnostic processes involved |
| Medlock et al, 2015 [31] | Cross-sectional online survey | To determine which information resources seniors who use the Internet use and trust for health information, which sources are preferred, and which sources are used by seniors for different information needs |
| Morgan et al, 2014 [32] | Analysis of inquiries posted to a health website | Describe what information people seek from a US website about genetic and rare diseases, and why |
| Mueller et al, 2016 [33] | Experimental (randomized trial) | To assess the feasibility of testing a symptom appraisal tool for lung cancer symptoms in an online randomized trial |
| Norr et al, 2014 [34] | Experimental within-subjects design | Investigate whether viewing medical websites adversely affects anxiety sensitivity |
| North et al, 2011 [35] | Cross-sectional analysis of clicks on a health website and calls to a telephone triage system | Establish what symptoms Internet users tend to look up online and whether telephone triage algorithms could be applied to these |
| Perez et al, 2015 [36] | Experimental study with Think Aloud | Describe Internet search processes and identify demographic and personal characteristics associated with use of system 1 (does not include hypothesis testing and evidence gathering) and system 2 (includes hypothesis testing and evidence gathering) processing |
| Powell et al, 2011 [37] | Cross-sectional survey with embedded qualitative semistructured interviews | Identify the characteristics and motivations of online health information seekers accessing the NHS Direct website |
| Powley et al, 2016 [38] | Cross-sectional survey and observational study | Evaluate whether patients with inflammatory arthritis and inflammatory arthralgia use the Internet for symptom appraisal and to assess the advice given and diagnoses suggested by the NHS and WebMD symptom checkers |
| Rice, 2006 [39] | Cross-sectional survey study; secondary analysis of existing dataset | Understand what influences online health seeking, what the reported benefits of online health seeking are, and to identify similarities among online activities |
| Teriaky et al, 2015 [40] | Cross-sectional survey | Understand how outpatients awaiting initial gastroenterology consultation seek medical information on the Internet and how wait times affect Internet usage |
| Thomson et al, 2012 [41] | Cross-sectional survey study | Explore characteristics of colorectal cancer patients who used the Web to appraise symptoms prior to diagnosis |
| White & Horvitz, 2009 [5] | Longitudinal log-based study and cross-sectional survey | (1) Describe escalations that occur when users search for common symptoms and how this escalates to queries about serious conditions, and (2) examine how this persists over several sessions |
| White & Horvitz, 2009 [42] | Cross-sectional survey study | Explore how lay individuals use the Web to find explanations for symptoms, what activities they pursue, and what their experiences are |
| White & Horvitz, 2010 [43] | Longitudinal log study using logs from Windows Live toolbar | Predict escalations in searches based on characteristics of websites visited |
| White & Horvitz, 2010 [44] | Longitudinal log-based study | Establish predictors of when searches for common symptoms lead to health care utilization |
| White & Horvitz, 2012 [45] | Longitudinal log-based study | Explore how users search for medical concerns and particularly how these concerns impact on future behavior (eg how this influences focus and attention of future searches) |
| White & Horvitz, 2013 [46] | Longitudinal log-based study | (1) Whether snippets in search results are biased toward serious conditions when symptoms are entered into search engines and 2) how these snippets influence user behavior |
| Ybarra & Suman, 2006 [47] | National, longitudinal telephone survey | Examine which factors predict whether a Web user is likely to contact a health professional |