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.

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.

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.

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.

Influence of Endogenous Bacteria on Behavioral Responses in Leptocybe invasa: An Analysis of mVOCs.

Microorganisms within insects play a vital role in maintaining the basal physiological functions of the insects, with olfactory signals as critical components of insect survival strategies. Leptocybe invasa (L. invasa), an invasive alien pest inflicting significant damage to eucalyptus trees, harbors a rich and varied bacterial community within its body. However, the impact of its endogenous bacteria and their microbial Volatile Organic Compounds (mVOCs) on the behavioral preferences of L. invasa remains unexplored to date. This study focused on nine cultivable and dominant endogenous bacterial strains within L. invasa. Using a Y-tube olfactometer, we investigated the behavioral responses of female L. invasa to the mVOCs emitted by these bacteria. Concurrently, gas chromatography-mass spectrometry (GC-MS) was employed to quantify the mVOCs produced by these endogenous bacteria. Our findings revealed that Staphylococcus sp. exhibited the highest attractiveness of L. invasa, whereas Microbacterium sp. and E. cloacae exerted the most significant avoidance effects. The analysis of the mVOCs further highlighted the significance of aldehyde compounds, notably 2,3,6-trichlorobenzaldehyde, and alkane compounds, such as eicosane, in mediating the repellency and attraction effects. These results contribute to a deeper understanding of the invasion mechanism of L. invasa and provide a scientific basis for developing novel biopesticides or elicitors.

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.

Mechanisms of intron gain and loss in Drosophila.

BACKGROUND: It is widely accepted that orthologous genes have lost or gained introns throughout evolution. However, the specific mechanisms that generate these changes have proved elusive. Introns are known to affect nearly every level of gene expression. Therefore, understanding their mechanism of evolution after their initial fixation in eukaryotes is pertinent to understanding the means by which organisms develop greater regulation and complexity. RESULTS: To investigate possible mechanisms of intron gain and loss, we identified 189 intron gain and 297 intron loss events among 11 Drosophila species. We then investigated these events for signatures of previously proposed mechanisms of intron gain and loss. This work constitutes the first comprehensive study into the specific mechanisms that may generate intron gains and losses in Drosophila. We report evidence of intron gain via transposon insertion; the first intron loss that may have occurred via non-homologous end joining; intron gains via the repair of a double strand break; evidence of intron sliding; and evidence that internal or 5' introns may not frequently be deleted via the self-priming of reverse transcription during mRNA-mediated intron loss. Our data also suggest that the transcription process may promote or result in intron gain. CONCLUSION: Our findings support the occurrence of intron gain via transposon insertion, repair of double strand breaks, as well as intron loss via non-homologous end joining. Furthermore, our data suggest that intron gain may be enabled by or due to transcription, and we shed further light on the exact mechanism of mRNA-mediated intron loss.

Sim4cc: a cross-species spliced alignment program.

Advances in sequencing technologies have accelerated the sequencing of new genomes, far outpacing the generation of gene and protein resources needed to annotate them. Direct comparison and alignment of existing cDNA sequences from a related species is an effective and readily available means to determine genes in the new genomes. Current spliced alignment programs are inadequate for comparing sequences between different species, owing to their low sensitivity and splice junction accuracy. A new spliced alignment tool, sim4cc, overcomes problems in the earlier tools by incorporating three new features: universal spaced seeds, to increase sensitivity and allow comparisons between species at various evolutionary distances, and powerful splice signal models and evolutionarily-aware alignment techniques, to improve the accuracy of gene models. When tested on vertebrate comparisons at diverse evolutionary distances, sim4cc had significantly higher sensitivity compared to existing alignment programs, more than 10% higher than the closest competitor for some comparisons, while being comparable in speed to its predecessor, sim4. Sim4cc can be used in one-to-one or one-to-many comparisons of genomic and cDNA sequences, and can also be effectively incorporated into a high-throughput annotation engine, as demonstrated by the mapping of 64,000 Fagus grandifolia 454 ESTs and unigenes to the poplar genome.

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.

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.

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.

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.

Effective cluster-based seed design for cross-species sequence comparisons.

SUMMARY: To annotate newly sequenced organisms, cross-species sequence comparison algorithms can be applied to align gene sequences to the genome of a related species. To improve the accuracy of alignment, spaced seeds must be optimized for each comparison. As the number and diversity of genomes increase, an efficient alternative is to cluster pairwise comparisons into groups and identify seeds for groups instead of individual comparisons. Here we investigate a measure of comparison closeness and identify classes of comparisons that show similar seed behavior and therefore can employ the same seed. AVAILABILITY: Source code is freely available at http://dna.cs.gwu.edu and from Bioinformatics online.

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.

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.

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.

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.