Integrating statistical and visual analytic methods for bot identification of health-related survey data.

OBJECTIVE: In recent years, we have increasingly observed issues concerning quality of online information due to misinformation and disinformation. Aside from social media, there is growing awareness that questionnaire data collected using online recruitment methods may include suspect data provided by bots. Issues with data quality can be particularly problematic in health and/or biomedical contexts; thus, developing robust methods for suspect data identification and removal is of paramount importance in informatics. In this study, we describe an interactive visual analytics approach to suspect data identification and removal and demonstrate the application of this approach on questionnaire data pertaining to COVID-19 derived from different recruitment venues, including listservs and social media. METHODS: We developed a pipeline for data cleaning, pre-processing, analysis, and automated ranking of data to address data quality issues. We then employed the ranking in conjunction with manual review to identify suspect data and remove them from subsequent analyses. Last, we compared differences in the data before and after removal. RESULTS: We performed data cleaning, pre-processing, and exploratory analysis on a survey dataset (N = 4,163) collected using multiple recruitment mechanins using the Qualtrics survey platform. Based on these results, we identified suspect features and used these to generate a suspect feature indicator for each survey response. We excluded survey responses that did not fit the inclusion criteria for the study (n = 29) and then performed manual review of the remaining responses, triangulating with the suspect feature indicator. Based on this review, we excluded 2,921 responses. Additional responses were excluded based on a spam classification by Qualtrics (n=13), and the percentage of survey completion (n=328), resulting in a final sample size of 872. We performed additional analyses to demonstrate the extent to which the suspect feature indicator was congruent with eventual inclusion, as well as compared the characteristics of the included and excluded data. CONCLUSION: Our main contributions are: 1) a proposed framework for data quality assessment, including suspect data identification and removal; 2) the analysis of potential consequences in terms of representation bias in the dataset; and 3) recommendations for implementation of this approach in practice.

Examining Engagement and Usability in an Online Discussion Platform for Older Adults: Findings From Pilot Studies.

Social media may facilitate older adults' ability to engage socially and explore health information, but it can present difficulties for older adults. Therefore, it is important to explore older adults' experience of usability and user engagement. We conducted two rounds of pilot studies where we used Facebook to engage older adults. We performed a mixed-methods evaluation of user engagement and usability. A directed content analysis of qualitative data from the pilot studies was used to explore engagement and perceived usability, and the Mann-Whitney U test was used to examine differences in feature usage and engagement. We analyzed qualitative data from 13 participants. Qualitative data analysis yielded themes pertaining to three main domains: user engagement , usability , and usability related to aging-related changes . In terms of user engagement and usability, participants in both pilot studies reported positive feedback on felt involvement and endurability, and the second pilot group reported more positive comments regarding perceived usefulness compared with the first pilot group. There was no statistically significant difference in usage over the two studies. The findings of this study suggest opportunities to improve older adults' experience of online discussion platforms. Considering changes that improve perceived aesthetic appeal and focused attention will be helpful.

An algorithm for optimal testing in co-segregation analysis.

Clinical genetic sequencing tests often identify variants of uncertain significance. One source of data that can help classify the pathogenicity of variants is familial cosegregation analysis. Identifying and genotyping relatives for cosegregation analysis can be time consuming and costly. We propose an algorithm that describes a single measure of expected variant information gain from genotyping a single additional relative in a family. Then we explore the performance of this algorithm by comparing actual recruitment strategies used in 35 families who had pursued cosegregation analysis with synthetic pedigrees of possible testing outcomes if the families had pursued an optimized testing strategy instead. For each actual and synthetic pedigree, we calculated the likelihood ratio of pathogenicity as each successive test was added to the pedigree. We analyzed the differences in cosegregation likelihood ratio over time resulting from actual versus optimized testing approaches. Employing the testing strategy indicated by the algorithm would have led to maximal information more rapidly in 30 of the 35 pedigrees (86%). Many clinical and research laboratories are involved in targeted cosegregation analysis. The algorithm we present can facilitate a data driven approach to optimal relative recruitment and genotyping for cosegregation analysis and more efficient variant classification.

Characterizing uncertainty in goals-of-care discussions among black and white patients: a qualitative study.

BACKGROUND: Uncertainty has been associated with distress and poorer quality of life in patients with advanced cancer. Prior studies have focused on prognostic uncertainty; little is known about other types of uncertainty that patients and family members experience when discussing goals of care. Understanding the types of uncertainty expressed and differences between Black and White patients can inform the development of uncertainty management interventions. METHODS: This study sought to characterize the types of uncertainty expressed by Black and White patients and family members within the context of information needs during inpatient goals-of-care discussions. We performed a secondary analysis of transcripts from 62 recorded goals-of-care discussions that occurred between 2012 and 2014 at an urban, academic medical center in the United States. We applied an adapted taxonomy of uncertainty to data coded as describing information needs and used an inductive qualitative analysis method to analyze the discussions. We report the types of uncertainty expressed in these discussions. RESULTS: Fifty discussions included patient or family expressions of information needs. Of these, 40 discussions (n=16 Black and n=24 White) included statements of uncertainty. Black and White patients and families most frequently expressed uncertainty related to processes and structures of care (system-centered uncertainty) and to treatment (scientific uncertainty). Statements of prognostic uncertainty focused on quantitative information among Whites and on qualitative information and expectations for the future among Blacks. CONCLUSIONS: Black and White patients and families frequently expressed system-centered uncertainty, suggesting this may be an important target for intervention. Addressing other sources of uncertainty, such as prognostic uncertainty, may need more tailored approaches.

Behavioral Change Factors and Retention in Web-Based Interventions for Informal Caregivers of People Living With Dementia: Scoping Review.

BACKGROUND: Web-based interventions aimed at supporting informal caregivers of people living with dementia have the potential to improve caregivers' well-being and psychological health. However, few interventions are widely implemented for this population, and none of the prior reviews have systematically examined the use of behavior change techniques (BCTs), theories, and agents in web-based interventions for informal caregivers of people living with dementia. To better understand this implementation gap, we reviewed the literature to map behavioral factors (BCTs, theories, and agents) deployed in the studies. Furthermore, because there is an emerging consensus that retention could be shaped by participant characteristics and behavioral factors, we explored relationships between these features and retention rates across studies. OBJECTIVE: We pursued 3 objectives: to map behavioral factors involved in the web-based interventions for informal caregivers of people living with dementia; to examine the relationship between behavioral change elements and retention in the studies; and to examine the relationship between participant characteristics (gender, age, and spouse or adult children caregiver proportion) and study retention. METHODS: We conducted a literature review using the following keywords and their corresponding Medical Subject Headings terms: dementia, caregivers, and web-based intervention. The time limits were January 1998 to March 2022. Using the BCTv1 taxonomy, which specifies active behavioral components in interventions, 2 coders collected, summarized, and analyzed the frequency distributions of BCTs. Similarly, they abstracted and analyzed participant characteristics, behavior change theories, behavior change agents, and retention rates in the studies. RESULTS: The average age was 61.5 (SD 7.4) years, and the average proportion of spousal informal caregivers, adult children informal caregivers, and retention rates were 51.2% (SD 24.8%), 44.8% (SD 22%), and 70.4% (SD 17%), respectively. Only 53% (17/32) of the studies used behavior change theories, but 81% (26/32) included behavior change agents. The most common BCTv1 clusters were shaping knowledge and social support. The median number of BCTv1 clusters was 5 (IQR 3). We observed a negative correlation between the proportion of spousal informal caregivers and the retention rate (r=-0.45; P=.02) and between the number of BCTv1 clusters and retention rates (r=-0.47; P=.01). We also found that the proportion of adult children informal caregivers in the study was significantly and positively correlated with the retention rate (r=0.5; P=.03). No other participant characteristics or behavioral factors were associated with retention rates. CONCLUSIONS: We found that almost half of the studies were not informed by behavior change theories. In addition, spousal involvement and a higher number of BCTs were each associated with lower retention rates, while the involvement of adult children caregivers in the study was associated with higher retention. In planning future studies, researchers should consider matching participant characteristics with their intended intervention as the alignment might improve their retention rates.

The use of visual methods to support communication with older adults with cognitive impairment: A scoping review.

Older adults with cognitive impairment often face difficulties with comprehension and communication, which can impact other cognitive processes such as decision-making. This scoping review investigates how visual methods can support older adults with cognitive impairment. The review involved querying four databases. From these databases, eleven articles fit inclusion criteria. This paper examines the purposes, use contexts, types, and effectiveness of the visual methods described in each study. The two major use contexts were elicitation of thoughts, feelings, and preferences in everyday life and health/healthcare related uses. Studies that used visual methods for eliciting preferences generally employed static visualizations. Health-related contexts employed more complex and interactive visualizations. Three studies used visual tools to support older adults in understanding; six, communication; and three, decision-making. None addressed all three outcomes of interest. This study provides recommendations and future directions for visual communication research with older adults with cognitive impairment.

Reactions to COVID-19, information and technology use, and social connectedness among older adults with pre-frailty and frailty.

The emergence of Coronavirus Disease 2019 (COVID-19) and social distancing measures has serious implications, particularly those age 65 and older. We performed a qualitative analysis of online discussion data generated by older adults with pre-frailty and frailty while subject to a state stay-at-home order. We provided participants with prompts relating to the public health emergency, collected 60 posts, and analyzed them using a general inductive analytic method. We report on: (1) the impact of the pandemic on daily life; (2) preparedness, perceptions, and behavior; (3) information and technology use; and (4) social impacts. Participants' lives of changed in many ways, including the adoption of precautionary measures and altered daily routines. Participants experienced negative emotional consequences including stress, worry, and anxiety. Information and technology use kept participants informed and connected. Participants reported varying degrees of preparedness. Our study findings provide insight into ways to support vulnerable older adults in pandemic circumstances.

Factors in the Building of Effective Patient-Provider Relationships in the Context of Fibromyalgia.

OBJECTIVE: Fibromyalgia patients face particular challenges in building relationships with health care providers. In this study, we examine, from patients' perspectives, factors that influence the formation of effective patient-provider relationships. DESIGN: This research employed a qualitative approach to analyze data collected from a study that employed semistructured interviews. METHODS: Multiple methods were used to recruit 23 fibromyalgia patients for interviews. Semistructured interviews were conducted to explore how participants' information behaviors, including their communication with and relationships to providers, changed over time. The interview data were analyzed using a qualitative analytic method based on interpretative phenomenological analysis and constructivist grounded theory. RESULTS: We identified three important factors that influenced the building of effective relationships: patients and providers' interactions involving information, identifying health care providers that fit patients' needs, and realizing shared responsibilities. With regard to information, we described three important themes: information gaps, providers as educators/facilitators, and collaborative information behavior. CONCLUSIONS: Understanding of the key elements of relationship development between patients and providers can be utilized in various ways to improve clinical care. First, the knowledge gained in this study can inform the design of patient education materials that assist patients to identify providers that fit their needs, prepare for consultations, and develop realistic expectations for providers. The findings of this study can also inform the design of resources and tools to enable clinicians to communicate and relate better with their patients.

Exploring relatives' perceptions of participation, ethics, and communication in a patient-driven study for hereditary cancer variant reclassification.

Effective communication of genetic information within families depends on several factors. Few studies explore intra-familial communication of variant of uncertain significance (VUS) results or active collaboration between family members to classify VUS. Our qualitative study aimed to describe the experiences of individuals asked by family members to participate in the FindMyVariant study, a patient-driven family study which aimed to reclassify a clinically identified familial VUS in a hereditary cancer gene. We collected feedback from 56 individuals from 21 different families through phone interviews and written correspondence, transcribed the interviews, and performed thematic analysis on all text. We describe themes from three main topics: participation, ethical considerations, and study impacts. Participation in the FindMyVariant study, defined as returning a sample for targeted genotyping, was motivated by convenience and a desire to help the family, oneself, and science. Relatives were generally responsive to invitations to participate in FindMyVariant from another family member. Those who declined to participate did so due to concerns about research program confidentiality rather than family dynamics. No major ethical issues arose in response to the patient-driven study structure, and no major changes in stress and anxiety, medical care, or behavior occurred. Participation in patient-driven familial VUS classification studies has a neutral or positive impact on family health communication. While it is important to design studies to minimize familial coercion, intra-familial confidentiality breaches, and misinterpretation of genetic results, these were not major concerns among relatives in this study. Clinicians and laboratories may consider encouraging familial communication about genetic variants using family members as liaisons.

Correction: The Relationship Between Health Management and Information Behavior Over Time: A Study of the Illness Journeys of People Living With Fibromyalgia.

[This corrects the article DOI: 10.2196/jmir.5309.].

Challenges and Benefits of an Internet-Based Intervention With a Peer Support Component for Older Adults With Depression: Qualitative Analysis of Textual Data.

BACKGROUND: Technological interventions provide many opportunities for improving the health and quality of life of older adults. However, interaction with new technologies can also cause frustration. Although these themes have been explored in extant research, much remains to be learned with regard to how the challenges of aging and technology use and the experiences of participating in a social and learning environment are interrelated. OBJECTIVE: This study aimed to perform a qualitative analysis of data collected from MoodTech, a pilot study of an internet-based intervention with a peer support component for older adults with symptoms of depression, to better understand the participants' experience of using technological interventions, including the challenges and benefits that they experienced over the course of these interventions. METHODS: We employed an inductive qualitative analysis method based on grounded theory methodology and interpretative phenomenological analysis to analyze participant textual data. These textual data were of 3 main types: (1) assignments in which participants challenged their negative thoughts, (2) status updates, and (3) comments in the peer support component of the intervention. RESULTS: We have presented the results through 3 main themes: (1) the challenges of aging as seen through the participants' comments, (2) the difficulties experienced by the participants in using MoodTech, and (3) the benefits they derived from participating. CONCLUSIONS: This paper offers several contributions concerning study participants' experiences with internet-based cognitive behavioral therapy (iCBT) interventions with a peer support component and design considerations for developing complex technological interventions that support the challenges participants experience due to aging and cognitive difficulties. First, technical issues encountered by older adults within the context of the intervention can interact with and exacerbate the insecurities they experience in life, and it is important to consider how intervention components might be designed to mitigate these issues. Second, peer support can be employed as a mechanism to facilitate communication, support, and collaborative problem solving among participants in an intervention. The insights from this paper can inform the design of iCBT interventions for older adults.

Incorporating user feedback in the design of a genetics analysis tool: A two-part approach.

While general usability assessment models for websites have been developed for a wide variety of contexts, research literature on incorporating user feedback in the design of online scientific tools is lacking. In this article, we present an approach that we developed and illustrate how it was used to elicit user feedback of the AnalyzeMyVariant tool, which enables geneticists to use family pedigree data to calculate pathogenicity likelihood ratios for variants of unknown significance. We reviewed existing usability literature and developed a survey instrument emphasizing concepts of importance to online, data-driven, scientific tools. The items on the survey instrument were grouped in four categories: usability, quality, privacy and security, and satisfaction. We performed a two-part evaluation using the survey and a semi-structured interview protocol. The survey instrument was used to collect data about the use experience of AnalyzeMyVariant from 57 genetic experts and trainees who were recruited via email invitations. We also conducted semi-structured interviews with six genetics experts to explore work contexts in which users might use the tool and further delve into issues faced in tool use. Interviews were inductively coded and major themes identified using the constant comparative method. We found that the needs of genetics professionals vary for research- and clinically-focused work. These differences can inform the design of tools to serve their needs. The major contribution of this work is the description of a two-part method to elicit user feedback to inform the design of online, data-driven, scientific tools, which focuses on constructs of particular relevance to these tools such as usability, quality, privacy, security, and satisfaction. The survey instrument that we developed, coupled with contextual interviews, may serve as an example that can be used by others conducting usability studies of similar tools. In addition, our results emphasize the importance of considering contextual factors such as background knowledge, situational factors, and the intended application of results, in the usability evaluation of scientific software. It is our hope that this two-part approach might be adapted to assess the usability of other online scientific tools and facilitate the design of tools to meet the needs of their target audiences.

A multi-faceted approach to characterizing user behavior and experience in a digital mental health intervention.

Digital interventions offer great promise for supporting health-related behavior change. However, there is much that we have yet to learn about how people respond to them. In this study, we present a novel mixed-methods approach to analysis of the complex and rich data that digital interventions collect. We perform secondary analysis of IntelliCare, an intervention in which participants are able to try 14 different mental health apps over the course of eight weeks. The goal of our analysis is to characterize users' app use behavior and experiences, and is rooted in theoretical conceptualizations of engagement as both usage and user experience. In the first aim, we employ cluster analysis to identify subgroups of participants that share similarities in terms of the frequency of their usage of particular apps, and then employ other engagement measures to compare the clusters. We identified four clusters with different app usage patterns: Low Usage, High Usage, Daily Feats Users, and Day to Day users. Each cluster was distinguished by its overall frequency of app use, or the main app that participants used. In the second aim, we developed a computer-assisted text analysis and visualization method - message highlighting - to facilitate comparison of the clusters. Last, we performed a qualitative analysis using participant messages to better understand the mechanisms of change and usability of salient apps from the cluster analysis. Our novel approach, integrating text and visual analytics with more traditional qualitative analysis techniques, can be used to generate insights concerning the behavior and experience of users in digital health contexts, for subsequent personalization and to identify areas for improvement of intervention technologies.

Understanding User Experience: Exploring Participants' Messages With a Web-Based Behavioral Health Intervention for Adolescents With Chronic Pain.

BACKGROUND: Delivery of behavioral health interventions on the internet offers many benefits, including accessibility, cost-effectiveness, convenience, and anonymity. In recent years, an increased number of internet interventions have been developed, targeting a range of conditions and behaviors, including depression, pain, anxiety, sleep disturbance, and eating disorders. Human support (coaching) is a common component of internet interventions that is intended to boost engagement; however, little is known about how participants interact with coaches and how this may relate to their experience with the intervention. By examining the data that participants produce during an intervention, we can characterize their interaction patterns and refine treatments to address different needs. OBJECTIVE: In this study, we employed text mining and visual analytics techniques to analyze messages exchanged between coaches and participants in an internet-delivered pain management intervention for adolescents with chronic pain and their parents. METHODS: We explored the main themes in coaches' and participants' messages using an automated textual analysis method, topic modeling. We then clustered participants' messages to identify subgroups of participants with similar engagement patterns. RESULTS: First, we performed topic modeling on coaches' messages. The themes in coaches' messages fell into 3 categories: Treatment Content, Administrative and Technical, and Rapport Building. Next, we employed topic modeling to identify topics from participants' message histories. Similar to the coaches' topics, these were subsumed under 3 high-level categories: Health Management and Treatment Content, Questions and Concerns, and Activities and Interests. Finally, the cluster analysis identified 4 clusters, each with a distinguishing characteristic: Assignment-Focused, Short Message Histories, Pain-Focused, and Activity-Focused. The name of each cluster exemplifies the main engagement patterns of that cluster. CONCLUSIONS: In this secondary data analysis, we demonstrated how automated text analysis techniques could be used to identify messages of interest, such as questions and concerns from users. In addition, we demonstrated how cluster analysis could be used to identify subgroups of individuals who share communication and engagement patterns, and in turn facilitate personalization of interventions for different subgroups of patients. This work makes 2 key methodological contributions. First, this study is innovative in its use of topic modeling to provide a rich characterization of the textual content produced by coaches and participants in an internet-delivered behavioral health intervention. Second, to our knowledge, this is the first example of the use of a visual analysis method to cluster participants and identify similar patterns of behavior based on intervention message content.

Using an Innovative Discussion Platform to Give Voice to Aging-Related Experiences: A Pilot Study.

Exchanging information with peers may support older adults' management of aging-related health changes, including frailty. The current pilot study used a mixed-methods approach to develop and evaluate an online virtual community for older adults to discuss aging-related health issues and management strategies. Eight older adults (mean age = 84) were enrolled at the start of the study. During a 10-week moderated discussion, participants contributed a total of 133 responses. Common themes included (a) symptoms (e.g., pain, weakness/tiredness, sleep difficulties) and (b) management strategies (e.g., health behavior changes, psychosocial support). A positive trend of change was noted in participants' average self-reported health and chronic disease management self-efficacy scores. This platform could facilitate information exchange among older adults, empowering them to leverage their own knowledge to improve their health management strategies. Future research should expand on this study to include older adults of diverse racial, educational, and cultural backgrounds. [Journal of Gerontological Nursing, 45(12), 33-40.].

The User Knows What to Call It: Incorporating Patient Voice Through User-Contributed Tags on a Participatory Platform About Health Management.

BACKGROUND: Body listening, described as the act of paying attention to the body's signals and cues, can be an important component of long-term health management. OBJECTIVE: The aim of this study was to introduce and evaluate the Body Listening Project, an innovative effort to engage the public in the creation of a public resource-to leverage collective wisdom in the health domain. This project involved a website where people could contribute their experiences of and dialogue with others concerning body listening and self-management. This article presents an analysis of the tags contributed, with a focus on the value of these tags for knowledge organization and incorporation into consumer-friendly health information retrieval systems. METHODS: First, we performed content analysis of the tags contributed, identifying a set of categories and refining the relational structure of the categories to develop a preliminary classification scheme, the Body Listening and Self-Management Taxonomy. Second, we compared the concepts in the Body Listening and Self-Management Taxonomy with concepts that were automatically identified from an extant health knowledge resource, the Unified Medical Language System (UMLS), to better characterize the information that participants contributed. Third, we employed visualization techniques to explore the concept space of the tags. A correlation matrix, based on the extent to which categories tended to be assigned to the same tags, was used to study the interrelatedness of the taxonomy categories. Then a network visualization was used to investigate structural relationships among the categories in the taxonomy. RESULTS: First, we proposed a taxonomy called the Body Listening and Self-Management Taxonomy, with four meta-level categories: (1) health management strategies, (2) concepts and states, (3) influencers, and (4) health-related information behavior. This taxonomy could inform future efforts to organize knowledge and content of this subject matter. Second, we compared the categories from this taxonomy with the UMLS concepts that were identified. Though the UMLS offers benefits such as speed and breadth of coverage, the Body Listening and Self-Management Taxonomy is more consumer-centric. Third, the correlation matrix and network visualization demonstrated that there are natural areas of ambiguity and semantic relatedness in the meanings of the concepts in the Body Listening and Self-Management Taxonomy. Use of these visualizations can be helpful in practice settings, to help library and information science practitioners understand and resolve potential challenges in classification; in research, to characterize the structure of the conceptual space of health management; and in the development of consumer-centric health information retrieval systems. CONCLUSIONS: A participatory platform can be employed to collect data concerning patient experiences of health management, which can in turn be used to develop new health knowledge resources or augment existing ones, as well as be incorporated into consumer-centric health information systems.

Conflicting health information: a critical research need.

Conflicting health information is increasing in amount and visibility, as evidenced most recently by the controversy surrounding the risks and benefits of childhood vaccinations. The mechanisms through which conflicting information affects individuals are poorly understood; thus, we are unprepared to help people process conflicting information when making important health decisions. In this viewpoint article, we describe this problem, summarize insights from the existing literature on the prevalence and effects of conflicting health information, and identify important knowledge gaps. We propose a working definition of conflicting health information and describe a conceptual typology to guide future research in this area. The typology classifies conflicting information according to four fundamental dimensions: the substantive issue under conflict, the number of conflicting sources (multiplicity), the degree of evidence heterogeneity and the degree of temporal inconsistency.

The Relationship Between Health Management and Information Behavior Over Time: A Study of the Illness Journeys of People Living With Fibromyalgia.

BACKGROUND: Over the course of a chronic illness, patients face many challenges, including understanding what is happening to them and developing an effective strategy for managing illness. While there is existing literature concerning how people seek health-related information and cope with chronic illnesses, there is a need for additional research on how information affects patients' understandings of their illness, and how changes in this understanding affect their health management strategies over time. OBJECTIVE: This study examined how health management, information seeking, and information consumption and use processes are related throughout an illness. METHODS: A diversified recruitment strategy involving multiple media channels was used to recruit participants for an interview study. During the interviews, participants were asked to draw an "illness journey" timeline. The data were analyzed using a qualitative approach drawn from Interpretative Phenomenological Analysis and Grounded Theory. RESULTS: The study identified four main health management features of illness journeys: onset, progression toward diagnosis, acceptance, and development of an effective management strategy. The study then focused on how information seeking changes over illness journeys, particularly in terms of a transition from active information seeking to monitoring with intermittent focused searching. Last, the paper describes the information consumption and use processes that patients engaged in throughout their journey. CONCLUSIONS: This study makes three important contributions to the field. First, it presents an integrated conceptualization of how health management and information behaviors are related on illness journeys. Second, it adds to our existing knowledge on health literacy and self-management of chronic illness. Third, the study has implications for health interface design.

What Online Communities Can Tell Us About Electronic Cigarettes and Hookah Use: A Study Using Text Mining and Visualization Techniques.

BACKGROUND: The rise in popularity of electronic cigarettes (e-cigarettes) and hookah over recent years has been accompanied by some confusion and uncertainty regarding the development of an appropriate regulatory response towards these emerging products. Mining online discussion content can lead to insights into people's experiences, which can in turn further our knowledge of how to address potential health implications. In this work, we take a novel approach to understanding the use and appeal of these emerging products by applying text mining techniques to compare consumer experiences across discussion forums. OBJECTIVE: This study examined content from the websites Vapor Talk, Hookah Forum, and Reddit to understand people's experiences with different tobacco products. Our investigation involves three parts. First, we identified contextual factors that inform our understanding of tobacco use behaviors, such as setting, time, social relationships, and sensory experience, and compared the forums to identify the ones where content on these factors is most common. Second, we compared how the tobacco use experience differs with combustible cigarettes and e-cigarettes. Third, we investigated differences between e-cigarette and hookah use. METHODS: In the first part of our study, we employed a lexicon-based extraction approach to estimate prevalence of contextual factors, and then we generated a heat map based on these estimates to compare the forums. In the second and third parts of the study, we employed a text mining technique called topic modeling to identify important topics and then developed a visualization, Topic Bars, to compare topic coverage across forums. RESULTS: In the first part of the study, we identified two forums, Vapor Talk Health & Safety and the Stopsmoking subreddit, where discussion concerning contextual factors was particularly common. The second part showed that the discussion in Vapor Talk Health & Safety focused on symptoms and comparisons of combustible cigarettes and e-cigarettes, and the Stopsmoking subreddit focused on psychological aspects of quitting. Last, we examined the discussion content on Vapor Talk and Hookah Forum. Prominent topics included equipment, technique, experiential elements of use, and the buying and selling of equipment. CONCLUSIONS: This study has three main contributions. Discussion forums differ in the extent to which their content may help us understand behaviors with potential health implications. Identifying dimensions of interest and using a heat map visualization to compare across forums can be helpful for identifying forums with the greatest density of health information. Additionally, our work has shown that the quitting experience can potentially be very different depending on whether or not e-cigarettes are used. Finally, e-cigarette and hookah forums are similar in that members represent a "hobbyist culture" that actively engages in information exchange. These differences have important implications for both tobacco regulation and smoking cessation intervention design.