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.

Cancer-related cognitive impairment in survivors of adolescent and young adult non-central nervous system cancer: A scoping review.

OBJECTIVES: Cancer-related cognitive impairments (CRCI) are common after treatment and can have important impacts on the lives of adolescent and young adult (AYA) cancer survivors-those cancer survivors diagnosed between ages 15 and 39. However, most research focuses on survivors diagnosed under age 15 or over age 39 so we know relatively little about CRCI among AYA survivors of non-central nervous system (CNS) cancers. Here we review the research on CRCI among AYA survivors of non-CNS cancers to determine prevalence, associated factors, and impact on survivors' lives as well as implications for future research. METHODS: In November 2021 we performed a systematic search of the literature in MEDLINE, Web of Science, PsycInfo, CINAHL, EMBASE, and Cochrane Central Register of Controlled Trials to identify peer-reviewed English language articles describing original research with at least one cognitive outcome and conducted with AYA survivors of non-CNS cancer diagnosed as AYAs. We screened 6003 articles and 21 met eligibility criteria. Guided by the PRISMA-ScR Checklist, we extracted study information to meet review objectives. RESULTS: Most studies employed cross-sectional surveys or interviews, though some employed longitudinal methods, neurocognitive assessments, or brain imaging. From the subset of articles that reported a prevalence we calculated a weighted mean prevalence of 25.75% and weighted median prevalence of 27.8%. The factors associated with CRCI included female gender, higher dose chemotherapy, and comorbidities. CRCI impacted the lives of AYA survivors through impaired role functioning, financial toxicity, and unmet needs. CONCLUSIONS: CRCI is highly prevalent among non-CNS cancer survivors diagnosed as AYAs and impacts quality of life and role functioning. This review suggests a need for further longitudinal, imaging, and mixed methods research and provision of resources to help achieve better quality of life and educational and occupational attainment during what is potentially a decades-long survivorship period. However, although interventions might improve cognition and functioning, the review identified only one pilot study. Digital interventions may be a practical and effective option for this age group, but they have yet to be adequately investigated.

Health information technology to support cancer survivorship care planning: A systematic review.

OBJECTIVE: The study sought to conduct a systematic review to explore the functions utilized by electronic cancer survivorship care planning interventions and assess their effects on patient and provider outcomes. MATERIALS AND METHODS: Based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines, studies published from January 2000 to January 2020 were identified in PubMed, CINAHL, EMBASE, PsychINFO, Scopus, Web of Science, and the ACM Digital Library . The search combined terms for cancer, survivorship, care planning, and health information technology (HIT). Eligible studies evaluated the effects of a HIT intervention on usability, knowledge, process, or health-related outcomes. A total of 578 abstracts were reviewed, resulting in 60 manuscripts describing 40 studies. Thematic analyses were used to define meta-themes of system functions, and Fisher's exact tests were used to examine associations between functions and outcomes. RESULTS: Patients were the target end users for 18 interventions, while 12 targeted providers and 10 targeted both groups. Interventions used patient-reported outcomes collection (60%), automated content generation (58%), electronic sharing (40%), persistent engagement (28%), and communication features (20%). Overall, interventions decreased the time to create survivorship care plans (SCPs) and supported care planning knowledge and abilities, but results were mixed for effects on healthcare utilization, SCP sharing, and provoking anxiety. Persistent engagement features were associated with improvements in health or quality-of-life outcomes (17 studies, P = .003). CONCLUSIONS: Features that engaged users persistently over time were associated with better health and quality-of-life outcomes. Most systems have not capitalized on the potential of HIT to share SCPs across a care team and support care coordination.

Information needs and perceptions of chatbots for hypertension medication self-management: a mixed methods study.

OBJECTIVE: Chatbots have potential to deliver interactive self-management interventions but have rarely been studied in the context of hypertension or medication adherence. The objective of this study was to better understand patient information needs and perceptions of chatbots to support hypertension medication self-management. MATERIALS AND METHODS: Mixed methods were used to assess self-management needs and preferences for using chatbots. We purposively sampled adults with hypertension who were prescribed at least one medication. Participants completed questionnaires on sociodemographics, health literacy, self-efficacy, and technology use. Semi-structured interviews were conducted, audio-recorded, and transcribed verbatim. Quantitative data were analyzed using descriptive statistics, and qualitative data were analyzed using applied thematic analysis. RESULTS: Thematic saturation was met after interviewing 15 participants. Analysis revealed curiosity toward chatbots, and most perceived them as humanlike. The majority were interested in using a chatbot to help manage medications, refills, communicate with care teams, and for accountability toward self-care tasks. Despite general enthusiasm, there were concerns with chatbots providing too much information, making demands for lifestyle changes, invading privacy, and usability issues with deployment on smartphones. Those with overall positive perceptions toward chatbots were younger and taking fewer medications. DISCUSSION: Chatbot-related informational needs were consistent with existing self-management research, and many felt chatbots would be valuable if customizable and compatible with patient portals, pharmacies, or health apps. CONCLUSION: Although most were not familiar with chatbots, patients were interested in interacting with them, but this varied. This research informs future design and functionalities of conversational interfaces to support hypertension self-management.

How patient-generated health data and patient-reported outcomes affect patient-clinician relationships: A systematic review.

INTRODUCTION: Many patients use mobile devices to track health conditions by recording patient-generated health data. However, patients and clinicians may disagree how to use these data. OBJECTIVE: To systematically review the literature to identify how patient-generated health data and patient-reported outcomes collected outside of clinical settings can affect patient-clinician relationships within surgery and primary care. METHODS: Six research databases were queried for publications documenting the effect of patient-generated health data or patient-reported outcomes on patient-clinician relationships. We conducted thematic synthesis of the results of the included publications. RESULTS: Thirteen of the 3204 identified publications were included for synthesis. Three main themes were identified: patient-generated health data supported patient-clinician communication and health awareness, patients desired for their clinicians to be involved with their patient-generated health data, which clinicians had difficulty accommodating, and patient-generated health data platform features may support or hinder patient-clinician collaboration. CONCLUSION: Patient-generated health data and patient-reported outcomes may improve patient health awareness and communication with clinicians but may negatively affect patient-clinician relationships.

Why Should I Trust You? Supporting the Sharing of Health Data in the Interprofessional Space of Child Development.

Many stakeholders can be involved in supporting a child's development, including parents, pediatricians, and educators. These stakeholders struggle to collaborate, and experts suggest that health information technology could improve their communication. Trust, based on perceptions of competence, benevolence, and integrity is fundamental to supporting information sharing, so information technologies should address trust between stakeholders. We engaged 75 parents and 60 healthcare workers with two surveys to explore this topic. We first elicited the types of information parents and healthcare workers use to form perceptions of competence, benevolence, and integrity. We then designed and tested user profile prototypes listing the elicited information to see if it builds trust in previously unknown professionals. We discovered that providing information related to personal characteristics, relationships, professional experience, and workplace practices can support trust and the sharing of information. This work has implications for designing informative electronic user interfaces to support interprofessional trust.

Implementing patient-reported outcome measures in clinical practice: a companion guide to the ISOQOL user's guide.

PURPOSE: The use of patient-reported outcome (PRO) measures in clinical practice is increasing. Following the creation of a 'User's Guide to Implementing PRO Assessment in Clinical Practice' by the International Society for Quality of Life Research (ISOQOL), volunteers from ISOQOL sought to create a Companion Guide to assist health care providers with the scientific and practical considerations involved in implementing and using PRO measures in clinical care by using information from real-world case studies. This paper summarizes the key issues presented in the Companion Guide. METHODS: Ten respondents, who were members of the ISOQOL's CP-SIG and worked in various clinical areas, participated in a survey or telephone interview. Participants were from Canada (n = 2), Denmark (n = 1), England (n = 2), Holland (n = 1), and the United States (n = 4). RESULTS: Based on the information provided by respondents, a Companion Guide was produced, organized according to the nine questions presented in the User's Guide. An additional section for key take-home messages was also provided. This guide provides examples of issues and considerations related to the implementation of PRO measures in clinical practice. CONCLUSIONS: Respondents provided insight into their experiences and emphasized that PRO initiatives were likely to be more successful if there is purposeful, designed integration into clinical practice, meaningful substantive engagement with all stakeholders and access to necessary organizational resources. The ability to leverage existing technology as well as realistic and stakeholder consensus-driven expectations for planning and timing were also key to the successful implementation of PRO measures.

The use of model constructs to design collaborative health information technologies: A case study to support child development.

OBJECTIVE: Health information technology could provide valuable support for inter-professional collaboration to address complex health issues, but current HIT systems do not adequately support such collaboration. Existing theoretical research on supporting collaborative work can help inform the design of collaborative HIT systems. Using the example of supporting collaboration between child development service providers, we describe a deductive approach that leverages concepts from the literature and analyzes qualitative user-needs data to aid in collaborative system design. MATERIALS AND METHODS: We use the Collaboration Space Model to guide the deductive qualitative analysis of interviews focused on the use of information technology to support child development. We deductively analyzed 44 interviews from two separate research initiatives and included data from a wide range of stakeholder groups including parents and various service providers. We summarized the deductively coded interview excerpts using quantitative and qualitative methods. RESULTS: The deductive analysis method provided a rich set of design data, highlighting heterogeneity in work processes, barriers to adequate communication, and gaps in stakeholder knowledge in supporting child development work. DISCUSSION: Deductive qualitative analysis considering constructs from a literature-based model provided useful, actionable data to aid in design. Design implications underscore functions needed to adequately share data across many stakeholders. More work is needed to validate our design implications and to better understand the situations where specific system features would be most useful. CONCLUSIONS: Deductive analysis considering model constructs provides a useful approach to designing collaborative HIT systems, allowing designers to consider both empirical user data and existing knowledge from the literature. This method has the potential to improve designs for collaborative HIT systems.

Trust and Sharing in an Interprofessional Environment: A Thematic Analysis From Child Development Support Work in the Community.

Health information technology (HIT) could aid collaboration in the complex, interprofessional space of child development. Trust between stakeholders is necessary to support collaboration, but extant research provides little guidance on designing HIT that promotes trust within interprofessional collaborations. We analyzed interview data obtained from a heterogeneous group of stakeholders (n = 46) including parents and various service providers to explore trust relationships in the child development space. Our thematic analysis revealed that stakeholders assess the trustworthiness of others based on perceived competence, benevolence, integrity, relevance to work, and source of the data. Stakeholders also based trust on the type of data shared, electronic system features or functions, perceived risks and benefits of sharing information, and made trust calculations based on multiple factors. Our research identifies multiple aspects of trust that should be considered in designs for collaborative HIT systems.

Utilizing Standard Data Transactions and Public-Private Partnerships to Support Healthy Weight Within the Community.

CONTEXT: Obesity is a significant health issue in the United States that both clinical and public health systems struggle to address. Electronic health record data could help support multi-sectoral interventions to address obesity. Standards have been identified and created to support the electronic exchange of weight-related data across many stakeholder groups. CASE DESCRIPTION: The Centers for Disease Control and Prevention initiated a public-private partnership including government, industry, and academic technology partners to develop workflow scenarios and supporting systems to exchange weight-related data through standard transactions. This partnership tested the transmission of data using this newly-defined Healthy Weight (HW) profile at multiple health data interoperability demonstration events. FINDINGS: Five transaction types were tested by 12 partners who demonstrated how the standards and related systems support end-to-end workflows around managing weight-related issues in the community. The standard transactions were successfully tested at two Integrating the Healthcare Enterprise (IHE) Connectathon events through 86 validated tests encompassing 38 multi-partner transactions. DISCUSSION: We have successfully demonstrated the transactions defined in the HW profile with a public-private partnership. These tested IT products and HW standards could be used to support a continuum of care around health related issues encompassing both health care and public health functions. CONCLUSION: The use of the HW profile, including a set of transactions and identified standards to implement those transactions, in IT products is a helpful first step in leveraging health information technology to address weight-related issues in the United States. Future work is needed to expand the use of these standards and to assess their use in real world settings.

Design and feasibility of integrating personalized PRO dashboards into prostate cancer care.

OBJECTIVE: Patient-reported outcomes (PROs) are a valued source of health information, but prior work focuses largely on data capture without guidance on visual displays that promote effective PRO use in patient-centered care. We engaged patients, providers, and design experts in human-centered design of "PRO dashboards" that illustrate trends in health-related quality of life (HRQOL) reported by patients following prostate cancer treatment. MATERIALS AND METHODS: We designed and assessed the feasibility of integrating dashboards into care in 3 steps: (1) capture PRO needs of patients and providers through focus groups and interviews; (2) iteratively build and refine a prototype dashboard; and (3) pilot test dashboards with patients and their provider during follow-up care. RESULTS: Focus groups (n = 60 patients) prioritized needs for dashboards that compared longitudinal trends in patients' HRQOL with "men like me." Of the candidate dashboard designs, 50 patients and 50 providers rated pictographs less helpful than bar charts, line graphs, or tables (P < .001) and preferred bar charts and line graphs most. Given these needs and the design recommendations from our Patient Advisory Board (n = 7) and design experts (n = 7), we built and refined a prototype that charts patients' HRQOL compared with age- and treatment-matched patients in personalized dashboards. Pilot testing dashboard use (n = 12 patients) improved compliance with quality indicators for prostate cancer care (P < .01). CONCLUSION: PRO dashboards are a promising approach for integrating patient-generated data into prostate cancer care. Informed by human-centered design principles, this work establishes guidance on dashboard content, tailoring, and clinical use that patients and providers find meaningful.