Primary care patients with cardiovascular disease eligible for nurse-led internet-based cognitive behavioural therapy for insomnia: Characteristics and motives for participation.

AIM: To describe demographic, physical and psychological characteristics associated with insomnia in patients with cardiovascular disease (CVD) participating in nurse-led Internet-based cognitive behavioural therapy for insomnia (I-CBTI), and their motives and expectations regarding participation in I-CBTI. DESIGN: A mixed method design was applied, including primary care patients with angina pectoris, myocardial infarction, heart failure, atrial fibrillation and atrial flutter or arrhythmia in southern Sweden. METHODS: Data on demographics, insomnia severity and physical and psychological characteristics were collected through self-rated validated questionnaires (n = 126). Motives and expectations were collected through interviews (n = 19) and analysed using the 'personas' model. RESULTS: Physical symptoms and psychological characteristics were associated with insomnia. Three personas were identified: the pragmatist (a curious and optimistic persona), the philosopher (a problem-solving persona) and the philanthropist (an altruistic persona). Expectations were positive among the three personas, but comorbid conditions reduced the perceived ability to make necessary behavioural changes.

Effectiveness of a mobile app-based educational intervention to treat internet gaming disorder among Iranian adolescents: study protocol for a randomized controlled trial.

BACKGROUND: The use of video games, a hobby for many teenagers in their leisure time, has brought with it a new potential for concerns. Internet gaming disorder (IGD) is a mental condition classified as a disorder due to addictive behaviors. It may include use of video games, both online and offline. Consequences of IGD may include introversion, social anxiety, mood swings, loneliness, sleep problems, behavioral problems, depression, low self-esteem, and increased violence. In order to design an app-based intervention for adolescents, a transtheoretical model (TTM) has been used. This widely used model in the field of behavioral change is also practical for health education programs. In addition, cognitive-behavioral therapy (CBT) has been used to make people more aware of their behaviors, feelings and thoughts and how to achieve behavioral change. The present study seeks to determine the effectiveness of this app-based intervention in in the treatment of IGD among adolescents. METHOD: In this single-blinded, randomized, controlled trial, 206 high-school adolescents aged 13 to 18 years in Qazvin city will be recruited. Eligible adolescents will be randomly assigned into intervention and control groups. Eight consecutive sessions delivered over 2 months and based on the TTM and CBT will be delivered through the `app (named HAPPYTEEN) to the intervention group. The control group will receive a sleep hygiene intervention (8 consecutive sessions for 2 months) via the app. Data collection tools include the Internet Gaming Disorder Scale, Insomnia Severity Index, Depression, Anxiety, and Stress Scales, Stages of Change Questionnaire, Decision Balance, and Self-Efficacy. The study measures will be completed at baseline, post intervention, and 1 month and 3 months after the intervention. DISCUSSION: The results of this intervention could be used as adjunct therapy for adolescents with IGD. TRIAL REGISTRATION: Clinical Trial Registration Center of Iran (IRCT) IRCT20181226042140N1 . Registered on June 9, 2020.

Nursing Informatics Research Trends: Findings from an International Survey.

This follow-up survey on trends in Nursing Informatics (NI) was conducted by the International Medical Informatics Association (IMIA) Student and Emerging Professionals (SEP) group as a cross-sectional study in 2019. There were 455 responses from 24 countries. Based on the findings NI research is evolving rapidly. Current ten most common trends include: clinical quality measures, clinical decision support, big data, artificial intelligence, care coordination, education and competencies, patient safety, mobile health, description of nursing practices and evaluation of patient outcomes. The findings help support the efforts to efficiently use resources in the promotion of health care activities, to support the development of informatics education and to grow NI as a profession.

A Review of Usability Methods Used in the Evaluation of Mobile Health Applications for Diabetes.

Mobile health applications for diabetes are developed like never before and many patients use them for their personalized health needs. With increased use, an increased number of usability evaluations are performed to assure that the applications function as intended. In this review the goal was to determine what usability methods are currently used in the evaluation of mobile health applications for diabetes and how these are used. METHODS: A literature review was conducted to identify applicable studies in the databases ACM Digital Library, Cinahl and Pubmed between the years 2015 and 2020. After the inclusion and exclusion criteria were applied, 32 articles remained that were included in the final review. RESULTS: Most of the studies included one established usability engineering method such as an expert-based and/or user-based method or a validated questionnaire/instrument. Some also included a combination of these. Others used methods of their own design; commonly questionnaires and interviews either on their own or in combination. CONCLUSION: To achieve an adequate level of evidence and quality in the evaluation, it is important that at least one is an established usability engineering method or a validated instrument. This to assure and continue to build the evidence base in this area.

NASA RTLX as a Novel Assessment for Determining Cognitive Load and User Acceptance of Expert and User-Based Evaluation Methods Exemplified Through a mHealth Diabetes Self-Management Application Evaluation.

Many diabetes patients utilize mobile health applications for their personalized self-management needs, but a majority of these systems have deficient usability. To assess the usability, different evaluation methods can be used. Two such methods are the expert-based cognitive walkthrough (CW) and user-based think aloud (TA) which have different advantages and disadvantages and can lead to the detection of many types of usability problems. There is, however, a lack of research on how the evaluators experience performing these different methods; an important aspect to include due to its possible implications for the evaluation overall. In this paper the focus was on assessing the evaluators' cognitive load and method acceptance through an instrument novel for this particular purpose, the NASA RTLX, and through in-depth interviews. Six usability experts and 6 diabetes patients performed the evaluations where 18 usability problems were found with the CW and 20 with the TA and with system usability (SUS) scores of 23.75 and 59.58. Both methods had similarly high cognitive loads: the CW with a RTLX score of 56.11, and the TA of 53.47 and both were experienced as cognitively demanding. The results indicate the potential importance of these dimensions for decision-making purposes between different evaluation methods.

Employing a user-centered cognitive walkthrough to evaluate a mHealth diabetes self-management application: A case study and beginning method validation.

INTRODUCTION: Self-management of chronic diseases using mobile health (mHealth) systems and applications is becoming common. Current evaluation methods such as formal usability testing can be very costly and time-consuming; others may be more efficient but lack a user focus. We propose an enhanced cognitive walkthrough (CW) method, the user-centered CW (UC-CW), to address identified deficiencies in the original technique and perform a beginning validation with think aloud protocol (TA) to assess its effectiveness, efficiency and user acceptance in a case study with diabetes patient users on a mHealth self-management application. MATERIALS AND METHODS: A total of 12 diabetes patients at University of Utah Health, USA, were divided into UC-CW and think aloud (TA) groups. The UC-CW method included: making the user the main evaluator for detecting usability problems, having a dual domain facilitator, and using three other improved processes: validated task development, higher level tasks and a streamlined evaluation process. Users interacted with the same mHealth application for both methods. Post-evaluation assessments included the NASA RTLX instrument and a set of brief interview questions. RESULTS: Participants had similar demographic characteristics. A total of 26 usability problems were identified with the UC-CW and 20 with TA. Both methods produced similar ratings: severity across all views (UC-CW = 2.7 and TA = 2.6), numbers of problems in the same views (Main View [UC-CW = 11, TA = 10], Carbohydrate Entry View [UC-CW = 4, TA = 3] and List View [UC-CW = 3, TA = 3]) with similar heuristic violations (Match Between the System and Real World [UC-CW = 19, TA = 16], Consistency and Standards [UC-CW = 17, TA = 15], and Recognition Rather than Recall [UC-CW = 13, TA = 10]). Both methods converged on eight usability problems, but the UC-CW group detected five critical issues while the TA group identified two. The UC-CW group identified needed personalized features for patients' disease needs not identified with TA. UC-CW was more efficient on average time per identified usability problem and on the total evaluation process with patients. NASA RTLX scores indicated that participants experienced the UC-CW half as cognitively demanding. Common themes from interviews indicated the UC-CW as enjoyable and easy to perform while TA was considered somewhat awkward and more cognitively challenging. CONCLUSIONS: UC-CW was effective for finding severe, recurring usability problems and it highlighted the need for personalized user features. The method was also efficient and had high user acceptance. These results indicate UC-CW's utility and user acceptance in evaluating a mHealth self-management application. It provides an additional usability evaluation technique for researchers.

Using Activity Theory as a Framework for the Usability Evaluation Process and Task Determination in mHealth Self-Management Systems for Diabetes.

mHealth systems can be used for patients in their diabetes self-management, but usability evaluations are often needed to determine how to make them more useful for the diabetes patient user in the monitoring and managing of their disease. Activity Theory (AT) was developed within Russian psychology to define the work and activity process in an activity system. AT was here considered to also be a particularly suitable framework for inspiration in usability evaluation both for the whole evaluation process and also for the usability task determination in this process for diabetes patient users. In the following paper, examples are provided from four usability studies using both user-based and expert usability methods in evaluation showing how AT was applied to guide the thoughts in evaluating the usability of two mHealth self-management systems for diabetes. Experiences and insights are provided from this process.

Biomedical informatics advancing the national health agenda: the AMIA 2015 year-in-review in clinical and consumer informatics.

The field of biomedical informatics experienced a productive 2015 in terms of research. In order to highlight the accomplishments of that research, elicit trends, and identify shortcomings at a macro level, a 19-person team conducted an extensive review of the literature in clinical and consumer informatics. The result of this process included a year-in-review presentation at the American Medical Informatics Association Annual Symposium and a written report (see supplemental data). Key findings are detailed in the report and summarized here. This article organizes the clinical and consumer health informatics research from 2015 under 3 themes: the electronic health record (EHR), the learning health system (LHS), and consumer engagement. Key findings include the following: (1) There are significant advances in establishing policies for EHR feature implementation, but increased interoperability is necessary for these to gain traction. (2) Decision support systems improve practice behaviors, but evidence of their impact on clinical outcomes is still lacking. (3) Progress in natural language processing (NLP) suggests that we are approaching but have not yet achieved truly interactive NLP systems. (4) Prediction models are becoming more robust but remain hampered by the lack of interoperable clinical data records. (5) Consumers can and will use mobile applications for improved engagement, yet EHR integration remains elusive.

Patients' Perceptions and Experiences of a mHealth Diabetes Self-management System.

Chronic diseases, including diabetes, constitute a substantial disease burden around the world. Mobile self-management systems now play a significant and increasingly important role in patients' disease management. Yet, patients' perceptions of these systems after longer-term use are largely unexplored. A random sample of 10 diabetes patients was assessed immediately after they exited a larger, 6-month randomized controlled trial on the use of a mHealth system called Care4Life. This descriptive, exploratory study assessed patients' perceptions and experiences of mHealth using a questionnaire and semistructured interview whose development was guided by the Technology Acceptance Model. Results indicated that patients saw clear benefits in using the technology and had favorable behavioral disease outcomes after using Care4Life. Suggestions for improving the system were highly individual despite the apparent homogeneity of the patient group. The study begins to fill the gap about the longer-term use of mHealth systems in chronic disease management and reflects the significance of individual needs for mHealth systems.

A Practical Method for Data Handling in Multi-Method Usability Research Studies.

BACKGROUND: Analyses of large, complex data sets are common in health informatics and usability research. Researchers need feasible ways of streamlining data handling and analyses. We offer a useful approach across qualitative and digitalized data. METHODS: Illustrated by a usability evaluation study on a mHealth system, we present methods for managing a large set of usability data using qualitative data analysis software (QDAS). Three different data collection methods were used (usability testing, in-depth interviews, and open-ended questionnaire responses). RESULTS: The process began at initial transcription and all data were imported into the system. Content analysis was used throughout - from problem identification to assigning problem classifications and severity ratings to linkages with system views. CONCLUSION: This approach was practical and useful as it allowed the capture and synthesis of a large number of multifaceted usability problems. We recommend this approach to other researchers performing usability evaluations on large data sets.

Advancing Nursing Informatics in the Next Decade: Recommendations from an International Survey.

In the summer of 2015, the International Medical Informatics Association Nursing Informatics Special Interest Group (IMIA NISIG) Student Working Group developed and distributed an international survey of current and future trends in nursing informatics. The survey was developed based on current literature on nursing informatics trends and translated into six languages. Respondents were from 31 different countries in Asia, Africa, North and Central America, South America, Europe, and Australia. This paper presents the results of responses to the survey question: "What should be done (at a country or organizational level) to advance nursing informatics in the next 5-10 years?" (n responders = 272). Using thematic qualitative analysis, responses were grouped into five key themes: 1) Education and training; 2) Research; 3) Practice; 4) Visibility; and 5) Collaboration and integration. We also provide actionable recommendations for advancing nursing informatics in the next decade.

Nursing Informatics Research Priorities for the Future: Recommendations from an International Survey.

We present one part of the results of an international survey exploring current and future nursing informatics (NI) research trends. The study was conducted by the International Medical Informatics Association Nursing Informatics Special Interest Group (IMIA-NISIG) Student Working Group. Based on findings from this cross-sectional study, we identified future NI research priorities. We used snowball sampling technique to reach respondents from academia and practice. Data were collected between August and September 2015. Altogether, 373 responses from 44 countries were analyzed. The identified top ten NI trends were big data science, standardized terminologies (clinical evaluation/implementation), education and competencies, clinical decision support, mobile health, usability, patient safety, data exchange and interoperability, patient engagement, and clinical quality measures. Acknowledging these research priorities can enhance successful future development of NI to better support clinicians and promote health internationally.

Heuristic Evaluation of a mHealth Diabetes Self-Management System Using Disease Specific Patient Profiles.

Patient-centeredness is an important concept in diabetes treatment. We modified Nielsen's expert heuristic evaluation method addressing common gaps: a patient perspective and variability in findings. Two expert, dual-domain evaluators referred to validated patient profiles (mild, moderate, severe diabetes) when conducting uniform evaluation processes on a diabetes mHealth system. Evaluators found 103 usability problems and 224 heuristic violations. For 69% of the problems, the profiles had an effect on severity ratings. "Consistency and Standards" (n = 57) and "Match between the System and Real World" (n = 55) violations dominated at 50%. The overall system severity rating was major. Severity was highest for a severe diabetic profile due to likely visual issues (crowded elements), cognitive concerns (remembering many steps) and for insufficient medication information. Interrater reliability was respectable at Kappa = 0.67. Our novel evaluation method represents one way of improving on a usability expert technique making it more patient-centered with less individual evaluator variability.

Current Trends in Nursing Informatics: Results of an International Survey.

Nursing informatics (NI) can help provide effective and safe healthcare. This study aimed to describe current research trends in NI. In the summer 2015, the IMIA-NI Students Working Group created and distributed an online international survey of the current NI trends. A total of 402 responses were submitted from 44 countries. We identified a top five NI research areas: standardized terminologies, mobile health, clinical decision support, patient safety and big data research. NI research funding was considered to be difficult to acquire by the respondents. Overall, current NI research on education, clinical practice, administration and theory is still scarce, with theory being the least common. Further research is needed to explain the impact of these trends and the needs from clinical practice.

Mediating the Cognitive Walkthrough with Patient Groups to achieve Personalized Health in Chronic Disease Self-Management System Evaluation.

The cognitive walkthrough (CW) is a task-based, expert inspection usability evaluation method involving benefits such as cost effectiveness and efficiency. A drawback of the method is that it doesn't involve the user perspective from real users but instead is based on experts' predictions about the usability of the system and how users interact. In this paper, we propose a way of involving the user in an expert evaluation method by modifying the CW with patient groups as mediators. This along with other modifications include a dual domain session facilitator, specific patient groups and three different phases: 1) a preparation phase where suitable tasks are developed by a panel of experts and patients, validated through the content validity index 2) a patient user evaluation phase including an individual and collaborative process part 3) an analysis and coding phase where all data is digitalized and synthesized making use of Qualitative Data Analysis Software (QDAS) to determine usability deficiencies. We predict that this way of evaluating will utilize the benefits of the expert methods, also providing a way of including the patient user of these self-management systems. Results from this prospective study should provide evidence of the usefulness of this method modification.

An evaluation of patients' experienced usability of a diabetes mHealth system using a multi-method approach.

OBJECTIVE: mHealth systems are becoming more common to aid patients in their diabetes self-management, but recent studies indicate a need for thorough evaluation of patients' experienced usability. Current evaluations lack a multi-method design for data collection and structured methods for data analyses. The purpose of this study was to provide a feasibility test of a multi-method approach for both data collection and data analyses for patients' experienced usability of a mHealth system for diabetes type 2 self-management. MATERIALS AND METHODS: A random sample of 10 users was selected from a larger clinical trial. Data collection methods included user testing with eight representative tasks and Think Aloud protocol, a semi-structured interview and a questionnaire on patients' experiences using the system. The Framework Analysis (FA) method and Usability Problem Taxonomy (UPT) were used to structure, code and analyze the results. A usability severity rating was assigned after classification. RESULTS: The combined methods resulted in a total of 117 problems condensed into 19 usability issues with an average severity rating of 2.47 or serious. The usability test detected 50% of the initial usability problems, followed by the post-interview at 29%. The usability test found 18 of 19 consolidated usability problems while the questionnaire uncovered one unique issue. Patients experienced most usability problems (8) in the Glucose Readings View when performing complex tasks such as adding, deleting, and exporting glucose measurements. The severity ratings were the highest for the Glucose Diary View, Glucose Readings View, and Blood Pressure View with an average severity rating of 3 (serious). Most of the issues were classified under the artifact component of the UPT and primary categories of Visualness (7) and Manipulation (6). In the UPT task component, most issues were in the primary category Task-mapping (12). CONCLUSIONS: Multiple data collection methods yielded a more comprehensive set of usability issues. Usability testing uncovered the largest volume of usability issues, followed by interviewing and then the questionnaire. The interview did not surface any unique consolidated usability issues while the questionnaire surfaced one. The FA and UPT were valuable in structuring and classifying problems. The resulting descriptions serve as a communication tool in problem solving and programming. We recommend the usage of multiple methods in data collection and employing the FA and UPT in data analyses for future usability testing.

A Modified User-Oriented Heuristic Evaluation of a Mobile Health System for Diabetes Self-management Support.

Mobile health platforms offer significant opportunities for improving diabetic self-care, but only if adequate usability exists. Expert evaluations such as heuristic evaluation can provide distinct usability information about systems. The purpose of this study was to complete a usability evaluation of a mobile health system for diabetes patients using a modified heuristic evaluation technique of (1) dual-domain experts (healthcare professionals, usability experts), (2) validated scenarios and user tasks related to patients' self-care, and (3) in-depth severity factor ratings. Experts identified 129 usability problems with 274 heuristic violations for the system. The categories Consistency and Standards dominated at 24.1% (n = 66), followed by Match Between System and Real World at 22.3% (n = 61). Average severity ratings across system views were 2.8 (of 4), with 9.3% (n = 12) rated as catastrophic and 53.5% (n = 69) as major. The large volume of violations with severe ratings indicated clear priorities for redesign. The modified heuristic approach allowed evaluators to identify unique and important issues, including ones related to self-management and patient safety. This article provides a template for one type of expert evaluation adding to the informaticists' toolbox when needing to conduct a fast, resource-efficient and user-oriented heuristic evaluation.

Quantifying usability: an evaluation of a diabetes mHealth system on effectiveness, efficiency, and satisfaction metrics with associated user characteristics.

OBJECTIVE: Mobile health (mHealth) systems are becoming more common for chronic disease management, but usability studies are still needed on patients' perspectives and mHealth interaction performance. This deficiency is addressed by our quantitative usability study of a mHealth diabetes system evaluating patients' task performance, satisfaction, and the relationship of these measures to user characteristics. MATERIALS AND METHODS: We used metrics in the International Organization for Standardization (ISO) 9241-11 standard. After standardized training, 10 patients performed representative tasks and were assessed on individual task success, errors, efficiency (time on task), satisfaction (System Usability Scale [SUS]) and user characteristics. RESULTS: Tasks of exporting and correcting values proved the most difficult, had the most errors, the lowest task success rates, and consumed the longest times on task. The average SUS satisfaction score was 80.5, indicating good but not excellent system usability. Data trends showed males were more successful in task completion, and younger participants had higher performance scores. Educational level did not influence performance, but a more recent diabetes diagnosis did. Patients with more experience in information technology (IT) also had higher performance rates. DISCUSSION: Difficult task performance indicated areas for redesign. Our methods can assist others in identifying areas in need of improvement. Data about user background and IT skills also showed how user characteristics influence performance and can provide future considerations for targeted mHealth designs. CONCLUSION: Using the ISO 9241-11 usability standard, the SUS instrument for satisfaction and measuring user characteristics provided objective measures of patients' experienced usability. These could serve as an exemplar for standardized, quantitative methods for usability studies on mHealth systems.

Nurse Informaticians Report Low Satisfaction and Multi-level Concerns with Electronic Health Records: Results from an International Survey.

This study presents a qualitative content analysis of nurses' satisfaction and issues with current electronic health record (EHR) systems, as reflected in one of the largest international surveys of nursing informatics. Study participants from 45 countries (n=469) ranked their satisfaction with the current state of nursing functionality in EHRs as relatively low. Two-thirds of the participants (n=283) provided disconcerting comments when explaining their low satisfaction rankings. More than one half of the comments identified issues at the system level (e.g., poor system usability; non-integrated systems and poor interoperability; lack of standards; and limited functionality/missing components), followed by user-task issues (e.g., failure of systems to meet nursing clinical needs; non nursing-specific systems) and environment issues (e.g., low prevalence of EHRs; lack of user training). The study results call for the attention of international stakeholders (educators, managers, policy makers) to improve the current issues with EHRs from a nursing perspective.

Going mobile with diabetes support: a randomized study of a text message-based personalized behavioral intervention for type 2 diabetes self-care.

Objective. Patients with type 2 diabetes often fail to achieve self-management goals. This study tested the impact on glycemic control of a two-way text messaging program that provided behavioral coaching, education, and testing reminders to enrolled individuals with type 2 diabetes in the context of a clinic-based quality improvement initiative. The secondary aim examined patient interaction and satisfaction with the program. Methods. Ninety-three adult patients with poorly controlled type 2 diabetes (A1C >8%) were recruited from 18 primary care clinics in three counties for a 6-month study. Patients were randomized by a computer to one of two arms. Patients in both groups continued with their usual care; patients assigned to the intervention arm also received from one to seven diabetes-related text messages per day depending on the choices they made at enrollment. At 90 and 180 days, A1C data were obtained from the electronic health record and analyzed to determine changes from baseline for both groups. An exit survey was used to assess satisfaction. Enrollment behavior and interaction data were pulled from a Web-based administrative portal maintained by the technology vendor. Results. Patients used the program in a variety of ways. Twenty-nine percent of program users demonstrated frequent engagement (texting responses at least three times per week) for a period of ≥90 days. Survey results indicate very high satisfaction with the program. Both groups' average A1C decreased from baseline, possibly reflecting a broader quality improvement effort underway in participating clinics. At 90 and 180 days, there was no statistically significant difference between the intervention and control groups in terms of change in A1C (P >0.05). Conclusions. This study demonstrated a practical approach to implementing and monitoring a mobile health intervention for self-management support across a wide range of independent clinic practices.