Automated Fidelity Assessment for Strategy Training in Inpatient Rehabilitation using Natural Language Processing.

Strategy training is a multidisciplinary rehabilitation approach that teaches skills to reduce disability among those with cognitive impairments following a stroke. Strategy training has been shown in randomized, controlled clinical trials to be a more feasible and efficacious intervention for promoting independence than traditional rehabilitation approaches. A standardized fidelity assessment is used to measure adherence to treatment principles by examining guided and directed verbal cues in video recordings of rehabilitation sessions. Although the fidelity assessment for detecting guided and directed verbal cues is valid and feasible for single-site studies, it can become labor intensive, time consuming, and expensive in large, multi-site pragmatic trials. To address this challenge to widespread strategy training implementation, we leveraged natural language processing (NLP) techniques to automate the strategy training fidelity assessment, i.e., to automatically identify guided and directed verbal cues from video recordings of rehabilitation sessions. We developed a rule-based NLP algorithm, a long-short term memory (LSTM) model, and a bidirectional encoder representation from transformers (BERT) model for this task. The best performance was achieved by the BERT model with a 0.8075 F1-score. This BERT model was verified on an external validation dataset collected from a separate major regional health system and achieved an F1 score of 0.8259, which shows that the BERT model generalizes well. The findings from this study hold widespread promise in psychology and rehabilitation intervention research and practice.

Toward Improving Health Literacy in Patient Education Materials with Neural Machine Translation Models.

Health literacy is the central focus of Healthy People 2030, the fifth iteration of the U.S. national goals and objectives. People with low health literacy usually have trouble understanding health information, following post-visit instructions, and using prescriptions, which results in worse health outcomes and serious health disparities. In this study, we propose to leverage natural language processing techniques to improve health literacy in patient education materials by automatically translating illiterate languages in a given sentence. We scraped patient education materials from four online health information websites: MedlinePlus.gov, Drugs.com, Mayoclinic.org and Reddit.com. We trained and tested the state-of-the-art neural machine translation (NMT) models on a silver standard training dataset and a gold standard testing dataset, respectively. The experimental results showed that the Bidirectional Long Short-Term Memory (BiLSTM) NMT model outperformed Bidirectional Encoder Representations from Transformers (BERT)-based NMT models. We also verified the effectiveness of NMT models in translating health illiterate languages by comparing the ratio of health illiterate language in the sentence. The proposed NMT models were able to identify the correct complicated words and simplify into layman language while at the same time, the models suffer from sentence completeness, fluency, readability, and have difficulty in translating certain medical terms.

Changes in the Histology of Walnut (Juglans regia L.) Infected with Phomopsis capsici and Transcriptome and Metabolome Analysis.

Phomopsis capsici (P. capsici) causes branch blight of walnuts, which leads to significant economic loss. The molecular mechanism behind the response of walnuts remains unknown. Paraffin sectioning and transcriptome and metabolome analyses were performed to explore the changes in tissue structure, gene expression, and metabolic processes in walnut after infection with P. capsici. We found that P. capsici caused serious damage to xylem vessels during the infestation of walnut branches, destroying the structure and function of the vessels and creating obstacles to the transport of nutrients and water to the branches. The transcriptome results showed that differentially expressed genes (DEGs) were mainly annotated in carbon metabolism and ribosomes. Further metabolome analyses verified the specific induction of carbohydrate and amino acid biosynthesis by P. capsici. Finally, association analysis was performed for DEGs and differentially expressed metabolites (DEMs), which focused on the synthesis and metabolic pathways of amino acids, carbon metabolism, and secondary metabolites and cofactors. Three significant metabolites were identified: succinic semialdehyde acid, fumaric acid, and phosphoenolpyruvic acid. In conclusion, this study provides data reference on the pathogenesis of walnut branch blight and direction for breeding walnut to enhance its disease resistance.

Toward the Identification of Distinct Phenotypes: Research Protocol for the Low Back Pain Biological, Biomechanical, and Behavioral (LB3P) Cohort Study and the BACPAC Mechanistic Research Center at the University of Pittsburgh.

As a member of the Back Pain Consortium (BACPAC), the University of Pittsburgh Mechanistic Research Center's research goal is to phenotype chronic low back pain using biological, biomechanical, and behavioral domains using a prospective, observational cohort study. Data will be collected from 1,000 participants with chronic low back pain according to BACPAC-wide harmonized and study-specific protocols. Participation lasts 12 months with one required in person baseline visit, an optional second in person visit for advanced biomechanical assessment, and electronic follow ups at months 1, 2, 3, 4, 5, 6, 9, and 12 to assess low back pain status and response to prescribed treatments. Behavioral data analysis includes a battery of patient-reported outcomes, social determinants of health, quantitative sensory testing, and physical activity. Biological data analysis includes omics generated from blood, saliva, and spine tissue. Biomechanical data analysis includes a physical examination, lumbopelvic kinematics, and intervertebral kinematics. The statistical analysis includes traditional unsupervised machine learning approaches to categorize participants into groups and determine the variables that differentiate patients. Additional analysis includes the creation of a series of decision rules based on baseline measures and treatment pathways as inputs to predict clinical outcomes. The characteristics identified will contribute to future studies to assist clinicians in designing a personalized, optimal treatment approach for each patient.

Trading quality for quantity? Evidence from patient level data in China.

In China, overcrowding at hospitals increases the workload of medical staff, which may negatively impact the quality of medical services. This study empirically examined the impact of hospital admissions on the quality of healthcare services in Chinese hospitals. Specifically, we estimated the impact of the number of hospital admissions per day on a patient's length of stay (LOS) and hospital mortality rate using both ordinary least squares (OLS) and instrumental variable (IV) methods. To deal with potential endogeneity problems and accurately identify the impact of medical staff configuration on medical quality, the daily air quality index was selected as the IV. Furthermore, we examined the differential effects of hospital admissions on the quality of care across different hospital tiers. We used the data from a random sample of 10% of inpatients from a city in China, covering the period from January 2014 to June 2019. Our final regression analysis included a sample of 167 disease types (as per the ICD-10 classification list) and 862,722 patient cases from 517 hospitals. According to our results, the LOS decreased and hospital mortality rate increased with an increasing number of admissions. Using the IV method, for every additional hospital admission, there was a 6.22% (p < 0.01) decrease in LOS and a 1.86% (p < 0.01) increase in hospital mortality. The impact of healthcare staffing levels on the quality of care varied between different hospital tiers. The quality of care in secondary hospitals was most affected by the number of admissions, with the average decrease of 18.60% (p < 0.05) in LOS and the increase of 6.05% (p < 0.01) in hospital mortality for every additional hospital admission in our sample. The findings suggested that the supply of medical services in China should be increased and a hierarchical diagnosis and treatment system should be actively promoted.

Development of a Weighted Well-Being Assessment Mobile App for Trauma Affected Communities: A Usability Study.

A well-being mobile app was built and tested by performing a usability study in a trauma affected community (TAC). Seven usability tasks were given to social workers during Phase 1. Phase 2 of the usability study was a re-test of the same tasks with the same social workers after refinements were applied. The results showed that most users preferred darker foreground colors, lighter background colors, larger fonts, and larger sized UI components. Statistically significant improvements were found after changes were implemented to the app and included time for page navigation (Z = -2.366, p = 0.018), logout (Z = -1.997, p = 0.046), and item selection in a page (Z = -2.371, p = 0.018). UI positioning and size changes proved to be a significant determinant of user satisfaction based on the positive feedback received from the computer systems usability questionnaire (CSUQ). (User1: p = .000, User 2 withdrew; User3: p = .010, User4: p = .000, User5: p = .001, User6: p = .006, User7: p = .025). HIM professionals assisted in the design, development, and administration of the usability study. This is another area in which HIM professionals are needed when assessing health and wellness in communities affected by trauma.

Analysis of influencing factors of economic burden and medical service utilization of diabetic patients in China.

BACKGROUND: This study analyzed factors that affect the financial burden and utilization of medical services of patients with diabetes in a city of China. METHODS: We randomly sampled 10% of the information on the front page of diabetic inpatient medical records in the city from January 2014 to September 2019. Total cost of hospitalization, length of hospitalization and the number of hospitalization were analyzed. Descriptive statistical analysis and multiple linear regression analysis were adopted. RESULTS: Understanding the current financial burden of diabetic patients and the use of medical services, the results show that the direct economic burden of diabetic patients per hospitalization was approximately 8,000 Yuan, and the indirect economic burden was approximately 2,000 Yuan. Age, medical payment methods, admission channels, and medical institution grades are all important factors affecting medical expenses and medical service utilization of diabetic patients. In addition, the inequality of medical service utilization of patients is increased due to different types of medical insurance. CONCLUSIONS: To reduce the economic burden on patients and society, governments should strengthen supervision, the advancement of diagnosis and treatment systems, the service conditions of primary medical institutions, the management of medical services, and the use of medical resources. To create a more impartial medical and health environment where the value of medical staff are truly reflected, financial investments should be attained to improve medical technologies and labor costs.

Development and Validation of a Comprehensive Well-Being Scale for People in the University Environment (Pitt Wellness Scale) Using a Crowdsourcing Approach: Cross-Sectional Study.

BACKGROUND: Well-being has multiple domains, and these domains are unique to the population being examined. Therefore, to precisely assess the well-being of a population, a scale specifically designed for that population is needed. OBJECTIVE: The goal of this study was to design and validate a comprehensive well-being scale for people in a university environment, including students, faculty, and staff. METHODS: A crowdsourcing approach was used to determine relevant domains for the comprehensive well-being scale in this population and identify specific questions to include in each domain. A web-based questionnaire (Q1) was used to collect opinions from a group of university students, faculty, and staff about the domains and subdomains of the scale. A draft of a new well-being scale (Q2) was created in response to the information collected via Q1, and a second group of study participants was invited to evaluate the relevance and clarity of each statement. A newly created well-being scale (Q3) was then used by a third group of university students, faculty, and staff. A psychometric analysis was performed on the data collected via Q3 to determine the validity and reliability of the well-being scale. RESULTS: In the first step, a group of 518 university community members (students, faculty, and staff) indicated the domains and subdomains that they desired to have in a comprehensive well-being scale. In the second step, a second group of 167 students, faculty, and staff evaluated the relevance and clarity of the proposed statements in each domain. In the third step, a third group of 546 students, faculty, and staff provided their responses to the new well-being scale (Pitt Wellness Scale). The psychometric analysis indicated that the reliability of the well-being scale was high. CONCLUSIONS: Using a crowdsourcing approach, we successfully created a comprehensive and highly reliable well-being scale for people in the university environment. Our new Pitt Wellness Scale may be used to measure the well-being of people in the university environment.

Making Self-Management Mobile Health Apps Accessible to People With Disabilities: Qualitative Single-Subject Study.

BACKGROUND: Over the past decade, a large number of mobile health (mHealth) apps have been created to help individuals to better manage their own health. However, very few of these mHealth apps were specifically designed for people with disabilities, and only a few of them have been assessed for accessibility for people with disabilities. As a result, people with disabilities have difficulties using many of these mHealth apps. OBJECTIVE: The objective of this study was to identify an approach that can be generally applied to improve the accessibility of mHealth apps. METHODS: We recruited 5 study participants with a primary diagnosis of cerebral palsy or spinal cord injury. All the participants had fine motor impairment or lack of dexterity, and hence, they had difficulties using some mHealth apps. These 5 study participants were first asked to use multiple modules in the client app of a novel mHealth system (iMHere 2.0), during which their performance was observed. Interviews were conducted post use to collect study participants' desired accessibility features. These accessibility features were then implemented into the iMHere 2.0 client app as customizable options. The 5 participants were asked to use the same modules in the app again, and their performance was compared with that in the first round. A brief interview and a questionnaire were then performed at the end of the study to collect the 5 participants' comments and impression of the iMHere 2.0 app in general and of the customizable accessibility features. RESULTS: Study results indicate that the study participants on their first use of the iMHere 2.0 client app experienced various levels of difficulty consistent with the severity of their lack of dexterity. Their performance was improved after their desired accessibility features were added into the app, and they liked the customizable accessibility features. These participants also expressed an interest in using this mHealth system for their health self-management tasks. CONCLUSIONS: The accessibility features identified in this study improved the accessibility of the mHealth app for people with dexterity issues. Our approach for improving mHealth app accessibility may also be applied to other mHealth apps to make those apps accessible to people with disabilities.

User Preferences for Privacy Protection Methods in Mobile Health Apps: A Mixed-Methods Study.

BACKGROUND: Mobile health (mHealth) apps have the potential to facilitate convenient health care delivery and self-management of health. However, many users have concerns about their privacy when they use mHealth apps. Different apps provide different solutions for protecting users' privacy. OBJECTIVE: The purpose of this study was to determine user preferences among the several privacy protection methods used in current mHealth apps and the reasons behind their preferences. METHODS: Five privacy protection methods currently used in mHealth apps were presented to a group of study participants who had mild or moderate depression and expressed concerns about privacy of information when they used mental health apps. After a demonstration of the methods, study participants were asked to fill out a questionnaire and indicate their perceived privacy protection level (PPPL) of each method, their preference rating for each method, and the privacy protection methods they had used in the past. A brief interview was then conducted to collect study participants' comments on these methods and elicit the reasons for their preference ratings. Statistical analysis was performed to determine the statistical significance of differences in participants' preference ratings and in the PPPLs obtained for the five methods. Study participants' comments on the privacy protection methods and suggestions were noted and summarized. RESULTS: Forty (40) study participants were selected from a large candidate pool using the IRB approved selection criteria. All study participants viewed the app demonstration and understood the five privacy protection methods properly, which was indicated by their correct sorting of the PPPL of the five methods in their answers to the questionnaire. All study participants specified their preferences with respect to these methods and provided the rationale behind their selections on the questionnaire and during the brief interview. The results indicate that the users preferred privacy protection methods with customizable modules in multi-purpose apps because of their convenience and strong privacy protection, where the customization can be done either in the app or via a Web portal. CONCLUSIONS: This study identified user preferred privacy protection methods. These identified privacy protection methods may be used in many types of apps that perform sensitive health information management to better protect users' privacy and encourage more users to adopt these mHealth apps.

Determinants of efficiency growth of county-level public hospitals-evidence from Chongqing, China.

BACKGROUND: The reform of county-level public hospitals is a breakthrough in the new era of healthcare reform in China and has attracted considerable attention since 2012. Continuous and efficient operations of hospital are primary concerns of this reform. To ensure the effectiveness of county-based intervention reform measures in Chongqing, it is significant to understand how hospital and county characteristics are associated with county-level public hospital efficiency due to significant development differences between counties. This study identifies the trajectory of hospital efficiency over time and determinants. It will also provide preliminary references for advancing reform. METHODS: This study employs data from the Chongqing Regional Health Information Platform, Chongqing Health and Family Planning Statistical Yearbook, and Chongqing Statistical Yearbook for 2012-2016. A three-level growth model is used to estimate the efficiency growth trajectories within the contexts of hospitals and counties. RESULTS: The intra-hospital level factors that affect the initial efficiency include government financial assistance, daily charge per bed, total assets turnover, number of hospital healthcare technicians, and medical costs per 100-yuan medical income. Inter-hospital variance is explained by hospital type. Inter-county level factors affecting the growth rate include the number of healthcare technicians per 1000 people and population density of the county. The interaction effect of the number of hospital healthcare technicians, hospital type, and number of healthcare technicians per 1000 people on hospital efficiency growth is significant. CONCLUSIONS: This study identifies determinants that contribute to efficiency changes in public county-hospitals over time by using a three-level growth model. The differences in efficiency are associated with intra-hospital, inter-hospital, and inter-county characteristics in Chongqing, which provides useful insight into government decision-making and the progress of reform. The stability and reasonable increase in the number of healthcare technicians in a county are the key factors that improve the efficiency. Further reform should focus on maternal and child healthcare hospitals for increasing investment and implementing government compensation.

Reaching People With Disabilities in Underserved Areas Through Digital Interventions: Systematic Review.

BACKGROUND: People with disabilities need rehabilitation interventions to improve their physical functioning, mental status, and quality of life. Many rehabilitation interventions can be delivered electronically ("digitally") via telehealth systems. For people with disabilities in underserved areas, electronically delivered rehabilitation interventions may be the only feasible service available for them. OBJECTIVE: The objective of this study was to evaluate the current status of digital interventions for people with disabilities in remote and underserved areas. METHODS: A systematic review was conducted on this topic. Keyword searches in multiple databases (PubMed, CINAHL, and Inspec) were performed to collect articles published in this field. The obtained articles were selected based on our selection criteria. Of the 198 identified articles, 16 duplicates were removed. After a review of the titles and abstracts of the remaining articles, 165 were determined to be irrelevant to this study and were therefore removed. The full texts of the remaining 17 articles were reviewed, and 6 of these articles were removed as being irrelevant to this study. The 11 articles remaining were discussed and summarized by 2 reviewers. RESULTS: These 11 studies cover a few types of disabilities, such as developmental disabilities and mobility impairments as well as several types of disability-causing disorders such as stroke, multiple sclerosis, traumatic brain injury, and facio-scapulo-humeral muscular dystrophy. Most of these studies were small-scale case studies and relatively larger-scale cohort studies; the project evaluation methods were mainly pre-post comparison, questionnaires, and interviews. A few studies also performed objective assessment of functional improvement. The intervention technology was mainly videoconferencing. Moreover, 10 of these studies were for people with disabilities in rural areas and 1 was for people in urban communities. CONCLUSIONS: A small number of small-scale studies have been conducted on digital interventions for people with disabilities in underserved areas. Although the results reported in these studies were mostly positive, they are not sufficient to prove the effectiveness of telehealth-based digital intervention in improving the situation among people with disabilities because of the small sample sizes and lack of randomized controlled trials.

A Telehealth Privacy and Security Self-Assessment Questionnaire for Telehealth Providers: Development and Validation.

BACKGROUND: Telehealth is a great approach for providing high quality health care services to people who cannot easily access these services in person. However, because of frequently reported health data breaches, many people may hesitate to use telehealth-based health care services. It is necessary for telehealth care providers to demonstrate that they have taken sufficient actions to protect their patients' data security and privacy. The government provided a HIPAA audit protocol that is highly useful for internal security and privacy auditing on health care systems, however, this protocol includes extensive details that are not always specific to telehealth and therefore is difficult to be used by telehealth practitioners. OBJECTIVE: The goal of this study was to develop and validate a telehealth privacy and security self-assessment questionnaire for telehealth providers. METHODS: In our previous work, we performed a systematic review on the security and privacy protection offered in various telehealth systems. The results from this systematic review and the HIPAA audit protocol were used to guide the development of the self-assessment questionnaire. The draft of the questionnaire was created by the research team and distributed to a group of telehealth providers for evaluating the relevance and clarity of each statement in the draft. The questionnaire was adjusted and finalized according to the collected feedback and face-to-face discussions by the research team. A website was created to distribute the questionnaire and manage the answers from study participants. A psychometric analysis was performed to evaluate the reliability of the questionnaire. RESULTS: There were 84 statements in the draft questionnaire. Five telehealth providers provided their feedback to the statements in this draft. They indicated that a number of these statements were either redundant or beyond the capacity of telehealth care practitioners, who typically do not have formal training in information security. They also pointed out that the wording of some statements needed to be adjusted. The final released version of the questionnaire had 49 statements. In total, 31 telehealth providers across the nation participated in the study by answering all the statements in this questionnaire. The psychometric analysis indicated that the reliability of this questionnaire was high. CONCLUSION: With the availability of this self-assessment questionnaire, telehealth providers can perform a quick self-assessment on their telehealth systems. The assessment results may be used to identify possible vulnerabilities in telehealth systems and practice or demonstrate to patients the sufficient security and privacy protection to patients' data.

Applying a User-Centered Approach to Building a Mobile Personal Health Record App: Development and Usability Study.

BACKGROUND: A personal health record (PHR) system encourages patients to engage with their own health care by giving them the ability to manage and keep track of their own health data. Of the numerous PHR systems available in the market, many are Web-based patient portals and a few are mobile apps. They have mainly been created by hospitals and electronic health record (EHR) vendors. One major limitation of these hospital-created PHR systems is that patients can only view specific health data extracted from their EHR. Patients do not have the freedom to add important personal health data they collect in their daily lives into their PHR. Therefore, there is an information gap between clinical visits. OBJECTIVE: The aim of this study was to develop and evaluate a new mobile PHR app that can be easily used to manage various types of personal health data to fill the information gap. METHODS: A user-centered approach was used to guide the development and evaluation of the new mobile PHR app. There were three steps in this study: needs assessment, app design and development, and conducting a usability study. First, a large-scale questionnaire study was conducted with the general population to gain an understanding of their needs and expectations with regard to a mobile PHR app. A mobile PHR app for personal medical data tracking and management was then created based on the results of the questionnaire study. End users were actively involved in all stages of the app development. Finally, a usability study was performed with participants to evaluate the usability of the mobile PHR app, which involved asking participants to finish a set of tasks and to respond to a usability questionnaire. RESULTS: In the questionnaire study for needs assessment, there were 609 participants in total. The answers from these participants revealed that they wanted to manage various types of personal health data in a mobile PHR app. Participants also reported some features they desired to have in the app. On the basis of the needs assessment findings, a new mobile PHR app (PittPHR) was created with 6 major modules: health records, history, trackers, contacts, appointments, and resources. This app allows users to customize the trackers according to their needs. In the usability study, there were 15 participants. The usability study participants expressed satisfaction with the app and provided comments and suggestions for further development. CONCLUSIONS: This new mobile PHR app provides options for users to manage a wide range of personal health data conveniently in one place. The app fills the information gap between clinical visits. The study results indicated that this new mobile PHR app meets the need of users and that users welcome this app.

The mHealth App Usability Questionnaire (MAUQ): Development and Validation Study.

BACKGROUND: After a mobile health (mHealth) app is created, an important step is to evaluate the usability of the app before it is released to the public. There are multiple ways of conducting a usability study, one of which is collecting target users' feedback with a usability questionnaire. Different groups have used different questionnaires for mHealth app usability evaluation: The commonly used questionnaires are the System Usability Scale (SUS) and Post-Study System Usability Questionnaire (PSSUQ). However, the SUS and PSSUQ were not designed to evaluate the usability of mHealth apps. Self-written questionnaires are also commonly used for evaluation of mHealth app usability but they have not been validated. OBJECTIVE: The goal of this project was to develop and validate a new mHealth app usability questionnaire. METHODS: An mHealth app usability questionnaire (MAUQ) was designed by the research team based on a number of existing questionnaires used in previous mobile app usability studies, especially the well-validated questionnaires. MAUQ, SUS, and PSSUQ were then used to evaluate the usability of two mHealth apps: an interactive mHealth app and a standalone mHealth app. The reliability and validity of the new questionnaire were evaluated. The correlation coefficients among MAUQ, SUS, and PSSUQ were calculated. RESULTS: In this study, 128 study participants provided responses to the questionnaire statements. Psychometric analysis indicated that the MAUQ has three subscales and their internal consistency reliability is high. The relevant subscales correlated well with the subscales of the PSSUQ. The overall scale also strongly correlated with the PSSUQ and SUS. Four versions of the MAUQ were created in relation to the type of app (interactive or standalone) and target user of the app (patient or provider). A website has been created to make it convenient for mHealth app developers to use this new questionnaire in order to assess the usability of their mHealth apps. CONCLUSIONS: The newly created mHealth app usability questionnaire-MAUQ-has the reliability and validity required to assess mHealth app usability.

Genetic Variations and Precision Medicine.

The time and costs associated with the sequencing of a human genome have decreased significantly in recent years. Many people have chosen to have their genomes sequenced to receive genomics-based personalized healthcare services. To reach the goal of genomics-based precision medicine, health information management (HIM) professionals need to manage and analyze patients' genomic data. Two important pieces of information from the genome sequence are the risk of genetic diseases and the specific medication or pharmacogenomic results for the individual patient, both of which are linked to a patient's genetic variations. In this review article, we introduce genetic variations, including their data types, relevant databases, and some currently available analysis methods and systems. HIM professionals can choose to use these databases, methods, and systems in the management and analysis of patients' genomic data.

An Adaptive Mobile Health System to Support Self-Management for Persons With Chronic Conditions and Disabilities: Usability and Feasibility Studies.

BACKGROUND: Persons with chronic conditions and disabilities (PwCCDs) are vulnerable to secondary complications. Many of these secondary complications are preventable with proactive self-management and proper support. To enhance PwCCDs' self-management skills and conveniently receive desired support, we have developed a mobile health (mHealth) system called iMHere. In 2 previous clinical trials, iMHere was successfully used to improve health outcomes of adult participants with spina bifida and spinal cord injury. To further expand use of iMHere among people with various types of disabilities and chronic diseases, the system needs to be more adaptive to address 3 unique challenges: 1) PwCCDs have very diverse needs with regards to self-management support, 2) PwCCDs' self-management needs may change over time, and 3) it is a challenge to keep PwCCDs engaged and interested in long-term self-management. OBJECTIVE: The aim of this study was to develop an adaptive mHealth system capable of supporting long-term self-management and adapting to the various needs and conditions of PwCCDs. METHODS: A scalable and adaptive architecture was designed and implemented for the new version, iMHere 2.0. In this scalable architecture, a set of mobile app modules was created to provide various types of self-management support to PwCCDs with the ability to add more as needed. The adaptive architecture empowers PwCCDs with personally relevant app modules and allows clinicians to adapt these modules in response to PwCCDs' evolving needs and conditions over time. Persuasive technologies, social support, and personalization features were integrated into iMHere 2.0 to engage and motivate PwCCDs and support long-term usage. Two initial studies were performed to evaluate the usability and feasibility of the iMHere 2.0 system. RESULTS: The iMHere 2.0 system consists of cross-platform client and caregiver apps, a Web-based clinician portal, and a secure 2-way communication protocol for providing interactions among these 3 front-end components, all supported by a back-end server. The client and caregiver apps have 12 adaptive app modules to support various types of self-management tasks. The adaptive architecture makes it possible for PwCCDs to receive personalized app modules relevant to their conditions with or without support from various types of caregivers. The personalization and persuasive technologies in the architecture can be used to engage PwCCDs for long-term usage of the iMHere 2.0 system. Participants of the usability study were satisfied with the iMHere 2.0 client app. The feasibility evaluation revealed several practical issues to consider when implementing the system on a large scale. CONCLUSIONS: We developed an adaptive mHealth system as a novel method to support diverse needs in self-management for PwCCDs that can dynamically change over time. The usability of the client app is high, and it was feasible for PwCCDs to use in supporting personalized and evolving self-care needs.

Barriers to and Facilitators of the Use of Mobile Health Apps From a Security Perspective: Mixed-Methods Study.

BACKGROUND: A large number of mobile health (mHealth) apps have been created to help users to manage their health or receive health care services. Many of these mHealth apps have proven to be helpful for maintaining or improving their users' health. However, many people still choose not to use mHealth apps or only use them for a short period. One of the reasons behind this lack of use is the concern for their health information security and privacy. OBJECTIVE: The goal of this study was to determine the relationship between users' characteristics and their security and privacy concerns and to identify desired security features in mHealth apps, which could reduce these concerns. METHODS: A questionnaire was designed and validated by the research team. This questionnaire was then used to determine mobile app users' security and privacy concerns regarding personal health data in mHealth apps as well as the security features most users' desire. A semistructured interview was used to identify barriers to and facilitators of adopting mHealth apps. RESULTS: In total, 117 randomly selected study participants from a large pool took part in this study and provided responses to the validated questionnaire and the semistructured interview questions. The results indicate that most study participants did have concerns about their privacy when using mHealth apps. They also expressed their preferences regarding several security features in mHealth apps, such as regular password updates, remote wipe, user consent, and access control. An association between their demographic characteristics and their concerns and preferences in security and privacy was identified; however, in most cases, the differences among the different demographic groups were not statistically significant, except for a few very specific aspects. These study participants also indicated that the cost of apps and lack of security features in mHealth apps were barriers for adoption, whereas having free apps, strong but easy-to-use security features, and clear user protection privacy policies might encourage them to use mHealth apps in their health management. CONCLUSIONS: This questionnaire and interview study verified the security and privacy concerns of mHealth app users, identified the desired security and privacy features, and determined specific barriers to and facilitators of users adopting mHealth apps. The results can be used to guide mHealth app developers to create apps that would be welcomed by users.

A Comprehensive Review of Quality of Life Surveys for Trauma-Affected Communities.

Research shows that exposure to community and domestic violence leads to psychological trauma from childhood through adulthood, which can lead to poor health and early death. A team of health information management (HIM) professionals reviewed existing surveys to determine their suitability for assessing the quality of life (QoL) of people in trauma-affected communities (TACs). Keywords were used to search for papers describing validated QoL surveys. The obtained papers were screened, reviewed, and summarized to determine if they include the aspects needed for assessing QoL in TACs. Survey items from 20 surveys were identified as relevant to this study. Most of these 20 surveys cover one or two domains of QoL, and none of them were specifically designed for people in TACs. Therefore, it is necessary to develop a psychometrically sound assessment tool to quantify the levels of trauma, resilience, and well-being in TACs. HIM professionals have the required skills for this task.

Development and Evaluation of a New Security and Privacy Track in a Health Informatics Graduate Program: Multidisciplinary Collaboration in Education.

BACKGROUND: The widespread application of technologies such as electronic health record systems, mobile health apps, and telemedicine platforms, has made it easy for health care providers to collect relevant data and deliver health care regimens. While efficacious, these new technologies also pose serious security and privacy challenges. OBJECTIVE: The training program described here aims at preparing well-informed health information security and privacy professionals with enhanced course materials and various approaches. METHODS: A new educational track has been built within a health informatics graduate program. Several existing graduate courses have been enhanced with new security and privacy modules. New labs and seminars have been created, and students are being encouraged to participate in research projects and obtain real-world experience from industry partners. Students in this track receive both theoretical education and hands-on practice. Evaluations have been performed on this new track by conducting multiple surveys on a sample of students. RESULTS: We have succeeded in creating a new security track and developing a pertinent curriculum. The newly created security materials have been implemented in multiple courses. Our evaluation indicated that students (N=72) believed that receiving security and privacy training was important for health professionals, the provided security contents were interesting, and having the enhanced security and privacy training in this program was beneficial for their future career. CONCLUSIONS: The security and privacy education for health information professionals in this new security track has been significantly enhanced.