Mining online social network data for biomedical research: a comparison of clinicians' and patients' perceptions about amyotrophic lateral sclerosis treatments

Visual Analytics of Multidimensional Oral Health Surveys: Data Mining Study

BACKGROUND

Oral health surveys largely facilitate the prevention and treatment of oral diseases as well as the awareness of population health status. As oral health is always surveyed from a variety of perspectives, it is a difficult and complicated task to gain insights from multidimensional oral health surveys.

OBJECTIVE

We aimed to develop a visualization framework for the visual analytics and deep mining of multidimensional oral health surveys.

METHODS

First, diseases and groups were embedded into data portraits based on their multidimensional attributes. Subsequently, group classification and correlation pattern extraction were conducted to explore the correlation features among diseases, behaviors, symptoms, and cognitions. On the basis of the feature mining of diseases, groups, behaviors, and their attributes, a knowledge graph was constructed to reveal semantic information, integrate the graph query function, and describe the features of intrigue to users.

RESULTS

A visualization framework was implemented for the exploration of multidimensional oral health surveys. A series of user-friendly interactions were integrated to propose a visual analysis system that can help users further achieve the regulations of oral health conditions.

CONCLUSIONS

A visualization framework is provided in this paper with a set of meaningful user interactions integrated, enabling users to intuitively understand the oral health situation and conduct in-depth data exploration and analysis. Case studies based on real-world data sets demonstrate the effectiveness of our system in the exploration of oral diseases.

Developments in the assessment of non-motor disease progression in amyotrophic lateral sclerosis

INTRODUCTION

The burden of non-motor symptoms is a major determinant of quality of life and outcome in amyotrophic lateral sclerosis (ALS) and has profound negative effect also on caregivers.

AREAS COVERED

Non-motor symptoms in ALS include cognitive impairment, neurobehavioral symptoms, depression and anxiety, suicidal ideation, pain, disordered sleep, fatigue, weight loss and reduced appetite, and autonomic dysfunctions. This review summarizes the measures used for the assessment of non-motor symptoms and their properties and recaps the frequency and progression of these symptoms along the course of ALS.

EXPERT OPINION

Non-motor symptoms in ALS represent a major component of the disease and span over several domains. These symptoms require a high level of medical attention and should be checked at each visit using ad hoc questionnaires and proactively treated. Several instruments assessing non-motor symptoms have been used in ALS. Specific screening questionnaires for non-motor symptoms can be used for monitoring patients during telehealth visits and for remote surveillance through sensors and apps installed on smartphones. Novel trials for non-motor symptoms treatment specifically designed for ALS are necessary to increase and refine the therapeutic armamentarium. Finally, scales assessing the most frequent and burdensome non-motor symptoms should be included in clinical trials.

Bowel, bladder, and sudomotor symptoms in ALS patients

OBJECTIVES

To describe prevalence rates of bowel, bladder, and sudomotor symptoms in patients with amyotrophic lateral sclerosis (ALS) in relation to disease onset and progression. Treatment strategies and efficacies were also assessed.

METHODS

A pilot patient cohort revealed increased incidences of bowel/bladder and sudomotor symptoms. Questionnaires derived from formal bowel and bladder survey instruments were administered to a second cohort of patients during multidisciplinary ALS clinic visits.

RESULTS

The pilot cohort of 30 patients reported an increase in bowel symptoms from 17% prior to 70% after the diagnosis of ALS, and an increase in urinary symptoms from 24% to 76%. In the second cohort of 66 patients an increase in constipation from 33% prior to 64.7% after the diagnosis of ALS was reported. 25.4% of patients reported bowel urgency initially, which increased to 33.3% over time. Constipation was most commonly treated with docusate, dietary fiber supplementation, fluid/exercise, and polyethylene glycol. In the second cohort the prevalence of overactive bladder symptoms increased from 3.1% prior to 25.0% after the diagnosis of ALS. Urinary symptoms are most commonly treated with catheters and oxybutynin. A sudomotor survey found stinging eyes in 17.2% of patients, oily/greasy skin in 14.1% of patients, and flaking of the skin in 29.7% of patients.

CONCLUSIONS

Bowel and bladder symptoms are common in the ALS population and respond to treatment. Sudomotor symptoms are also common. Inquiring about these symptoms at clinic visits and initiating treatment can significantly improve the patients' quality of life.

Comparing Physician and Patient Perspectives on Prophylactic Treatment with BAY 94-9027 for Severe Haemophilia A: A Post Hoc Analysis

Introduction

BAY 94-9027 is a newly developed extended half-life product to treat haemophilia, allowing for fewer injections than with standard products. This post hoc analysis aimed to compare physicians’ and patients’ opinions on BAY 94-9027 prophylaxis, and explore how qualitative interview data is aligned with the data from the Haemophilia-specific Quality of Life questionnaire for Adults (Haemo-QoL-A).

Methods

Exploratory qualitative interviews were conducted with physicians and patients by phone upon the exit of patients from the PROTECT VIII extension phase following a semi-directed guide. In this post hoc analysis, all transcripts were reviewed and reported concepts were compared to assess the level of concordance between physicians and patients. These qualitative data were compared with the Haemo-QoL-A mean global and subscale scores at baseline and end of main phase (36 weeks later).

Results

Ten physicians and 16 patients (mean age 47 years) from Israel, the Netherlands and the USA were interviewed. Significant improvements were reported by all physicians from baseline [e.g. lower frequency of bleeds (80%), improvement in emotional functioning (90%)], which is in concordance with patients’ reports. The improved confidence reported by physicians cascaded to greater participation in various activities, resulting in a better perceived emotional state and a significant improvement on the Haemo-QoL-A emotional impact subscale score (p = 0.04) between baseline and end of main phase. Most physicians (80%) reported improvement in bleed frequency, as patients did (88%). Improvement in physical functioning or mobility was not consistently reported in this 8-month study.

Conclusion

Interviewed physicians and patients generally agreed on the beneficial impact of BAY 94-9027, specifically regarding the increased level of self-confidence in patients and its subsequent positive impact on patients’ lives. These findings supported the observed improvement on the Haemo-QoL-A emotional impact subscale. Overall, this study highlights the concordance between physician and patient perspective on the positive experience with BAY 94-9027.

Cataloguing Treatments Discussed and Used in Online Autism Communities

A large number of patients discuss treatments in online health communities (OHCs). One research question of interest to health researchers is whether treatments being discussed in OHCs are eventually used by community members in their real lives. In this paper, we rely on machine learning methods to automatically identify attributions of mentions of treatments from an online autism community. The context of our work is online autism communities, where parents exchange support for the care of their children with autism spectrum disorder. Our methods are able to distinguish discussions of treatments that are associated with patients, caregivers, and others, as well as identify whether a treatment is actually taken. We investigate treatments that are not just discussed but also used by patients according to two types of content analysis, cross-sectional and longitudinal. The treatments identified through our content analysis help create a catalogue of real-world treatments. This study results lay the foundation for future research to compare real-world drug usage with established clinical guidelines.

Innovations in health information technologies for chronic pulmonary diseases

Asthma and chronic obstructive pulmonary disease (COPD) are common chronic obstructive lung disorders in the US that affect over 49 million people. There is no cure for asthma or COPD, but clinical guidelines exist for controlling symptoms that are successful in most patients that adhere to their treatment plan. Health information technologies (HITs) are revolutionizing healthcare by becoming mainstream tools to assist patients in self-monitoring and decision-making, and subsequently, driving a shift toward a care model increasingly centered on personal adoption and use of digital and web-based tools. While the number of chronic pulmonary disease HITs is rapidly increasing, most have not been validated as clinically effective tools for the management of disease. Online communities for asthma and COPD patients are becoming sources of empowerment and support, as well as facilitators of patient-centered research efforts. In addition to empowering patients and facilitating disease self-management, HITs offer promise to aid researchers in identifying chronic pulmonary disease endotypes and personalized treatments based on patient-specific profiles that integrate symptom occurrence and medication usage with environmental and genomic data.

Leveraging cues from person-generated health data for peer matching in online communities

OBJECTIVE

Online health communities offer a diverse peer support base, yet users can struggle to identify suitable peer mentors as these communities grow. To facilitate mentoring connections, we designed a peer-matching system that automatically profiles and recommends peer mentors to mentees based on person-generated health data (PGHD). This study examined the profile characteristics that mentees value when choosing a peer mentor.

MATERIALS AND METHODS

Through a mixed-methods user study, in which cancer patients and caregivers evaluated peer mentor recommendations, we examined the relative importance of four possible profile elements: health interests, language style, demographics, and sample posts. Playing the role of mentees, the study participants ranked mentors, then rated both the likelihood that they would hypothetically contact each mentor and the helpfulness of each profile element in helping the make that decision. We analyzed the participants' ratings with linear regression and qualitatively analyzed participants' feedback for emerging themes about choosing mentors and improving profile design.

RESULTS

Of the four profile elements, only sample posts were a significant predictor for the likelihood of a mentee contacting a mentor. Communication cues embedded in posts were critical for helping the participants choose a compatible mentor. Qualitative themes offer insight into the interpersonal characteristics that mentees sought in peer mentors, including being knowledgeable, sociable, and articulate. Additionally, the participants emphasized the need for streamlined profiles that minimize the time required to choose a mentor.

CONCLUSION

Peer-matching systems in online health communities offer a promising approach for leveraging PGHD to connect patients. Our findings point to interpersonal communication cues embedded in PGHD that could prove critical for building mentoring relationships among the growing membership of online health communities.

An Innovative Approach to Informing Research: Gathering Perspectives on Diabetes Care Challenges From an Online Patient Community

Background

Funding agencies and researchers increasingly recognize the importance of patient stakeholder engagement in research. Despite calls for greater patient engagement, few studies have engaged a broad-based online community of patient stakeholders in the early stages of the research development process.

Objective

The objective of our study was to inform a research priority-setting agenda by using a Web-based survey to gather perceptions of important and difficult aspects of diabetes care from patient members of a social networking site-based community.

Methods

Invitations to participate in a Web-based survey were sent by email to members of the PatientsLikeMe online diabetes community. The survey asked both quantitative and qualitative questions addressing individuals’ level of difficulty with diabetes care, provider communication, medication management, diet and exercise, and relationships with others. Qualitative responses were analyzed using content analysis.

Results

Of 6219 PatientsLikeMe members with diabetes who were sent survey invitations, 1044 (16.79%) opened the invitation and 320 (5.15% of 6219; 30.65% of 1044) completed the survey within 23 days. Of the 320 respondents, 33 (10.3%) reported having Type 1 diabetes; 107 (33.4%), Type 2 diabetes and taking insulin; and 180 (56.3%), Type 2 diabetes and taking oral agents or controlling their diabetes with lifestyle modifications. Compared to 2005-2010 National Health and Nutrition Examination Survey data for individuals with diabetes, our respondents were younger (mean age 55.8 years, SD 9.9 vs 59.4 years, SE 0.5); less likely to be male (111/320, 34.6% vs 48.4%); and less likely to be a racial or ethnic minority (40/312, 12.8% vs 37.5%). Of 29 potential challenges in diabetes care, 19 were categorized as difficult by 20% or more of respondents. Both quantitative and qualitative results indicated that top patient challenges were lifestyle concerns (diet, physical activity, weight, and stress) and interpersonal concerns (trying not to be a burden to others, getting support from family/friends). In our quantitative analysis, similar concerns were expressed across patient subgroups.

Conclusions

Lifestyle and interpersonal factors were particularly challenging for our online sample of adults with Type 1 or Type 2 diabetes. Our study demonstrates the innovative use of social networking sites and online communities to gather rapid, meaningful, and relevant patient perspectives that can be used to inform the development of research agendas.

Innovative research methods for studying treatments for rare diseases: methodological review

OBJECTIVE

To examine methods for generating evidence on health outcomes in patients with rare diseases.

DESIGN

Methodological review of existing literature.

SETTING

PubMed, Embase, and Academic Search Premier searched for articles describing innovative approaches to randomized trial design and analysis methods and methods for conducting observational research in patients with rare diseases.

MAIN OUTCOME MEASURES

We assessed information related to the proposed methods, the specific rare disease being studied, and outcomes from the application of the methods. We summarize methods with respect to their advantages in studying health outcomes in rare diseases and provide examples of their application.

RESULTS

We identified 46 articles that proposed or described methods for studying patient health outcomes in rare diseases. Articles covered a wide range of rare diseases and most (72%) were published in 2008 or later. We identified 16 research strategies for studying rare disease. Innovative clinical trial methods minimize sample size requirements (n=4) and maximize the proportion of patients who receive active treatment (n=2), strategies crucial to studying small populations of patients with limited treatment choices. No studies describing unique methods for conducting observational studies in patients with rare diseases were identified.

CONCLUSIONS

Though numerous studies apply unique clinical trial designs and considerations to assess patient health outcomes in rare diseases, less attention has been paid to innovative methods for studying rare diseases using observational data.

Evaluating health interest profiles extracted from patient-generated data

Patient-generated health data (PGHD) offers a promising resource for shaping patient care, self-management, population health, and health policy. Although emerging technologies bolster opportunities to extract PGHD and profile the needs and experiences of patients, few efforts examine the validity and use of such profiles from the patient's perspective. To address this gap, we explore health interest profiles built automatically from online community posts. Through a user evaluation with community members, we found that extracted profiles not only align with members' stated health interests, but also expand upon those manually entered interests with little user effort. Community members express positive attitudes toward the use and expansion of profiles to connect with peers for support. Despite this promising approach, findings also point to improvements required of biomedical text processing tools to effectively process PGHD. Findings demonstrate opportunities to leverage the wealth of unstructured PGHD available in emerging technologies that patients regularly use.

Patient-centeredness in the design of clinical trials

Evidence from clinical trials should contribute to informed decision making and a learning health care system. People frequently, however, find participating in clinical trials meaningless or disempowering. Moreover, people often do not incorporate trial results directly into their decision making. The lack of patient centeredness in clinical trials may be partially addressed through trial design. For example, Bayesian adaptive trials designed to adjust in a prespecified manner to changes in clinical practice could motivate people and their health care providers to view clinical trials as more applicable to real-world clinical decisions. The way in which clinical trials are designed can transform the evidence generation process to be more patient centered, providing people with an incentive to participate or continue participating in clinical trials. To achieve the transformation to patient-centeredness in clinical trial decisions, however, there is a need for transparent and reliable methods and education of trial investigators and site personnel.

Mind the gap: social media engagement by public health researchers

Background

The traditional vertical system of sharing information from sources of scientific authority passed down to the public through local health authorities and clinicians risks being made obsolete by emerging technologies that facilitate rapid horizontal information sharing. The rise of Public Health 2.0 requires professional acknowledgment that a new and substantive forum of public discourse about public health exists on social media, such as forums, blogs, Facebook, and Twitter.

Objective

Some public health professionals have used social media in innovative ways: to surveil populations, gauge public opinion, disseminate health information, and promote mutually beneficial interactions between public health professionals and the lay public. Although innovation is on the rise, most in the public health establishment remain skeptical of this rapidly evolving landscape or are unclear about how it could be used. We sought to evaluate the extent to which public health professionals are engaged in these spaces.

Methods

We conducted a survey of professorial- and scientist-track faculty at the Johns Hopkins Bloomberg School of Public Health in Baltimore, Maryland, USA. We asked all available faculty via email to complete a 30-question survey about respondent characteristics, beliefs about social media, and usage of specific technologies, including blogs, Facebook, Twitter, and YouTube.

Results

A total of 181 (19.8%) of 912 professor- and scientist-track faculty provided usable responses. The majority of respondents rarely used major social media platforms. Of these 181 respondents, 97 (53.6%) had used YouTube, 84 (46.4%) had used Facebook, 55 (30.4%) had read blogs, and 12 (6.6%) had used Twitter in the prior month. More recent degree completion was the best predictor of higher usage of social media. In all, 122 (67.4%) agreed that social media is important for disseminating information, whereas only 55 (30.4%) agreed that social media is useful for their research. In all, 43 (23.8%) said social media was helpful for professional career advancement, whereas 72 (39.8%) said it was not. Only 43 (23.8%) faculty said they would employ a full- or part-time social media consultant, and 30 (16.6%) currently employed one.

Conclusions

Despite near-universal appreciation of the potential for social media to serve as a component of public health strategy, a small minority are actually engaged in this space professionally, whereas most are either disinterested or actively opposed to professional engagement. Social media is seen by most as more useful for spreading information than obtaining it. As public discourse on a number of critical health topics continues to be influenced and sometimes shaped by discussions online from Twitter to Facebook, it would seem that greater discourse is needed about when and how public health professionals should engage in these media, and also how personal, institutional, and professional barriers to greater use of social media may be overcome.