| Quantified-self data (via devices, self-reporting, or sensors) |
Engaged in the self-tracking of signs and/or behaviors as n=1 individual or in groups, where there is often a proactive stance toward acting on the information [13] Provides richer and more detailed data on potential risk factors (biological, physical, behavioral or environmental) [13] Allows data collection over potentially longer follow-up periods than is currently possible using standard questionnaires [13] |
Food consumption [20] Information diet [21] Smile triggered electromyogram (EMG) muscle to create unexpected moments of joy in human interaction [22] Coffee consumption, social interaction, and mood [23] Idea-tracking process [24] Use of rescue and controller asthma medications with an inhaler sensor (e.g. Asthmapolis) [25] Monitors blood glucose levels in diabetics (e.g. Glooko) [26] Psychological, mental and cognitive states and traits (e.g. MyCompass) [27] Physical activity (e.g. FitBit; Jawbone Up, RunKeeper) [28, 29, 30] Diet (e.g. My Meal Mate) [31] Sleep quality (e.g. Lark) [32] Medication adherence (e.g. MyMedSchedule) [33] |
| Location-based information |
Information derived from Global Positioning Systems (GPS), Geographic Information Systems (GIS), and other open source mapping and visualization projects Provides information on the environmental and social determinants of health Monitors for disease outbreaks near your location |
Weather patterns, pollution levels, allergens, traffic patterns, water quality, walkability of neighborhood, and access to fresh fruit and vegetables (such as supermarkets) [34, 35, 36] HealthMap [37] |
| Twitter (Note: a 2011 study has suggested that 8.5% of English-language tweets relate to illness, and 16.6% relate to health [46]) |
Assesses disease spread in real-time Assesses sentiments and moods Facilitates emergency services by allowing for the wide-scale broadcast of available resource, enabling people in need of medical assistance to locate help Facilitates crisis mapping (e.g. where eyewitness reports are plotted on interactive maps. These data can help target areas for emergency services and additional resources) Facilitates discourse on non-emergency healthcare (e.g. broadcasts of public health messages, quantify medical misconception) |
Quantify medical misconceptions (e.g. concussions) [38] The spread of poor medical compliance (e.g., antibiotic use) [39] Trends of cardiac arrest and resuscitation communication [40] Cervical and breast cancer screening [41] Postpartum depression [42] Influenza A H1N1 outbreak (disease activity and public concern) [43] 2010 Haitian cholera outbreak [44] Emergency situations from Boston marathon explosion [45] |
| Health-related social networking sites |
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PatientsLikeMe [47] Disease surveillance sites which collect participant-reported symptoms and utilize informal online data sources to analyze, map, and disseminate information about infectious disease outbreaks (e.g. Flu Near You, HealthMap, GermTracker, Sickweather) [37, 48, 49, 50] |
| Other social networking sites (e.g. online discussion board, Facebook) |
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| Search queries and Web logs |
Found to be highly predictive for a wide range of population-level health behaviors Search keyword selection has been found to be critical for arriving at reliable curated health content “Click” stream navigational data from web logs are found to be informative of individual characteristics such as mental health and dietary preferences [57] |
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