Implementation fidelity of patient-centered prescription label to promote opioid safe use.

PURPOSE: Patient-centered labels may improve safe medication use, but implementation challenges limit use. We assessed implementation of a patient-centered "PRN" (as needed) label entitled "Take-Wait-Stop" (TWS) with three deconstructed steps replacing traditional wording. METHODS: As part of a larger investigation, patients received TWS prescriptions (eg, Take: 1 pill if you have pain; Wait: at least 4 h before taking again; Stop: do not take more than 6 pills in 24 h). Prescriptions labels recorded at follow-up were classified into three categories: (1) one-step wording (Take 1 pill every 4 h [without daily limits]), (2) two-step wording (Take 1 pill every 4 h; do not exceed 6 pills/day), and (3) three-step wording. There were three subtypes of three-step wording: (3a) three-step, not TWS (three deconstructed steps, not necessarily TWS wording), (3b) TWS format, employing three steps with leading verbs, but "with additions or replacements" (eg, replaced "do not take" with "do not exceed"), and (3c) verbatim TWS. RESULTS: Two hundred eleven participants completed follow-up. Mean age was 44.3 years (SD 14.3); 44% were male. One-step bottles represented 12% (n = 25) of the sample, whereas 26% (n = 55) had two-step wording. The majority (44%, n = 93) had three-deconstructed steps, not TWS (3a); 16% (n = 34) retained TWS structure, but not verbatim (3b). Only 2% (n = 4) displayed verbatim TWS wording (3c). All category three labels (utilizing deconstructed instructions) were considered adequate implementation (62%). CONCLUSIONS: Exact intervention adherence was not achieved in the majority of cases, limiting impact. Nonetheless, community pharmacies were responsive to new instructions, but higher implementation reliability requires additional supports.

An experimental study on individual and group affect in multi-tasking teams.

Research has shown that affect can influence human performance in various settings. This study aimed to explore the effects of individual and group affect on task perceptions and performance under different stress conditions (task demand and technology reliability) and team training methods in multi-tasking environments. Seventy-two participants participated in the experiment in two-person teams. The participants' affect was measured using facial expression recognition technology. Affect aggregated mean and affect similarity were used as indicators of group affect. Self-reports of workload, teamwork satisfaction, trust in team, and trust in technology were collected. The results demonstrated that different stress conditions and training methods altered individual and group affect. Individual affect did not significantly correlate with the task perception measures, while group affect was related to performance in the team-oriented task but not the individual-oriented tasks. These findings suggested that group affect may have an important role in both multi-tasking and team coordination. Practitioner summary: Affect can influence human performance in various settings. This study explored how affect influences task perceptions and performance for teams in multi-tasking environments. The results demonstrated that individual affect was not correlated with self-reported task perceptions. Group affect was related to team performance in a team-oriented task.

Redesigning Transplant Organ Labeling to Prevent Patient Harm and Organ Loss.

BACKGROUND: In 2012, the Health Resources and Services Administration and the United Network for Organ Sharing launched the "Electronic Tracking and Transportation" (ETT) project, in response to "labeling and packaging issues" being a frequently reported safety incident. This article describes an improvement project conducted as part of this United Network for Organ Sharing project. METHODS: An interdisciplinary team conducted a Process Failure Modes and Effects Analysis, laboratory simulations of organ labeling during procurement, and a heuristic evaluation of a label software application to inform the design of TransNet, a system that uses barcode technology at the point of organ recovery. A total of 42 clinicians and staff from 10 organ procurement organizations and 2 transplant centers in the United States participated. Processes Addressed: Key features of the redesigned labeling system include independent, double entry of label information into the software application, a machine-readable barcode on each organ's label, and a handheld printer for at "point of use" label printing. OUTCOMES: The new labeling system, TransNet, has become mandatory since June 2017. A survey conducted on early adopters (N = 11), after 1 year of use, indicates the process is safer and more efficient. IMPLICATIONS FOR PRACTICE: The findings from this study suggest that the application of quality planning methods, common in other industries, when redesigning a health-care process, are valuable and revelatory and should be adopted more extensively. Future evaluation of TransNet effectiveness to reduce safety incidents is critical.

Developing a data element repository to support EHR-driven phenotype algorithm authoring and execution.

The Quality Data Model (QDM) is an information model developed by the National Quality Forum for representing electronic health record (EHR)-based electronic clinical quality measures (eCQMs). In conjunction with the HL7 Health Quality Measures Format (HQMF), QDM contains core elements that make it a promising model for representing EHR-driven phenotype algorithms for clinical research. However, the current QDM specification is available only as descriptive documents suitable for human readability and interpretation, but not for machine consumption. The objective of the present study is to develop and evaluate a data element repository (DER) for providing machine-readable QDM data element service APIs to support phenotype algorithm authoring and execution. We used the ISO/IEC 11179 metadata standard to capture the structure for each data element, and leverage Semantic Web technologies to facilitate semantic representation of these metadata. We observed there are a number of underspecified areas in the QDM, including the lack of model constraints and pre-defined value sets. We propose a harmonization with the models developed in HL7 Fast Healthcare Interoperability Resources (FHIR) and Clinical Information Modeling Initiatives (CIMI) to enhance the QDM specification and enable the extensibility and better coverage of the DER. We also compared the DER with the existing QDM implementation utilized within the Measure Authoring Tool (MAT) to demonstrate the scalability and extensibility of our DER-based approach.

Quantitative ethnographic study of physician workflow and interactions with electronic health record systems.

This study explores the relationship between primary care physicians' interactions with health information technology and primary care workflow. Clinical encounters were recorded with high-resolution video cameras to capture physicians' workflow and interaction with two objects of interest, the electronic health record (EHR) system, and their patient. To analyze the data, a coding scheme was developed based on a validated list of primary care tasks to define the presence or absence of a task, the time spent on each task, and the sequence of tasks. Results revealed divergent workflows and significant differences between physicians' EHR use surrounding common workflow tasks: gathering information, documenting information, and recommend/discuss treatment options. These differences suggest impacts of EHR use on primary care workflow, and capture types of workflows that can be used to inform future studies with larger sample sizes for more effective designs of EHR systems in primary care clinics. Future research on this topic and design strategies for effective health information technology in primary care are discussed.

Patient-physician racial/ethnic concordance and blood pressure control: the role of trust and medication adherence.

OBJECTIVES: To examine the associations between racial/ethnic concordance and blood pressure (BP) control, and to determine whether patient trust and medication adherence mediate these associations. DESIGN: Cross-sectional study of 723 hypertensive African-American and white patients receiving care from 205 white and African-American providers at 119 primary care clinics, from 2001 to 2005. Racial/ethnic concordance was characterized as dyads where both the patient and physician were of the same race/ethnicity; discordance occurred in dyads where the patient was African-American and the physician was white. Patient perceptions of trust and medication adherence were assessed with self-report measures. The BP readings were abstracted from patients' medical charts using standardized procedures. RESULTS: Six hundred thirty-seven patients were in race/ethnic-concordant relationships; 86 were in race/ethnic-discordant relationships. Concordance had no association with BP control. White patients in race/ethnic-concordant relationships were more likely to report better adherence than African-American patients in race/ethnic-discordant relationships (OR: 1.27, 95% CI: 1.01, 1.61, p = 0.04). Little difference in adherence was found for African-American patients in race/ethnic-concordant vs. discordant relationships. Increasing trust was associated with significantly better adherence (OR: 1.17, 95% CI: 1.04, 1.31, p < 0.01) and a trend toward better BP control among all patients (OR: 1.26, 95% CI: 0.97, 1.63, p = 0.07). CONCLUSIONS: Patient trust may influence medication adherence and BP control regardless of patient-physician racial/ethnic composition.

The behavioral intervention technology model: an integrated conceptual and technological framework for eHealth and mHealth interventions.

A growing number of investigators have commented on the lack of models to inform the design of behavioral intervention technologies (BITs). BITs, which include a subset of mHealth and eHealth interventions, employ a broad range of technologies, such as mobile phones, the Web, and sensors, to support users in changing behaviors and cognitions related to health, mental health, and wellness. We propose a model that conceptually defines BITs, from the clinical aim to the technological delivery framework. The BIT model defines both the conceptual and technological architecture of a BIT. Conceptually, a BIT model should answer the questions why, what, how (conceptual and technical), and when. While BITs generally have a larger treatment goal, such goals generally consist of smaller intervention aims (the "why") such as promotion or reduction of specific behaviors, and behavior change strategies (the conceptual "how"), such as education, goal setting, and monitoring. Behavior change strategies are instantiated with specific intervention components or "elements" (the "what"). The characteristics of intervention elements may be further defined or modified (the technical "how") to meet the needs, capabilities, and preferences of a user. Finally, many BITs require specification of a workflow that defines when an intervention component will be delivered. The BIT model includes a technological framework (BIT-Tech) that can integrate and implement the intervention elements, characteristics, and workflow to deliver the entire BIT to users over time. This implementation may be either predefined or include adaptive systems that can tailor the intervention based on data from the user and the user's environment. The BIT model provides a step towards formalizing the translation of developer aims into intervention components, larger treatments, and methods of delivery in a manner that supports research and communication between investigators on how to design, develop, and deploy BITs.

Initial design of culturally informed behavioral intervention technologies: developing an mHealth intervention for young sexual minority men with generalized anxiety disorder and major depression.

BACKGROUND: To our knowledge, there is no well-articulated process for the design of culturally informed behavioral intervention technologies. OBJECTIVE: This paper describes the early stages of such a process, illustrated by the methodology for the ongoing development of a behavioral intervention technology targeting generalized anxiety disorder and major depression among young sexual minority men. METHODS: We integrated instructional design for Internet behavioral intervention technologies with greater detail on information sources that can identify user needs in understudied populations, as well as advances in the understanding of technology-specific behavioral intervention technology dimensions that may need to be culturally tailored. RESULTS: General psychological theory describing how to effect change in the clinical target is first integrated with theory describing potentially malleable factors that help explain the clinical problem within the population. Additional information sources are then used to (1) evaluate the theory, (2) identify population-specific factors that may affect users' ability to relate to and benefit from the behavioral intervention technology, and (3) establish specific skills, attitudes, knowledge, etc, required to change malleable factors posited in the theory. User needs result from synthesis of this information. Product requirements are then generated through application of the user needs to specific behavioral intervention technology dimensions (eg, technology platform). We provide examples of considerations relevant to each stage of this process and how they were applied. CONCLUSIONS: This process can guide the initial design of other culturally informed behavioral intervention technologies. This first attempt to create a systematic design process can spur development of guidelines for design of behavioral intervention technologies aimed to reduce health disparities.

Organizational and technological correlates of nurses' trust in a smart intravenous pump.

The aim of this study was to understand technology and system characteristics that contribute to nurses' ratings of trust in a smart intravenous pump. Nurses' trust in new technologies can influence how technologies are used. Trust in technology is defined as a person's belief that a technology will not fail them. Potential outcomes of trust in technology are appropriate trust, overtrust, distrust, and mistrust. Trust in technology is also related to several use-specific outcomes, including appropriate use and inappropriate use such as overreliance, disuse or rejection, or misuse. Understanding trust in relation to outcomes can contribute to designs that facilitate appropriate trust in new technologies. A survey was completed by 391 nurses a year after the implementation of a new smart intravenous pump. The survey assessed trust in the intravenous pump and other elements of the sociotechnical system, individual characteristics, technology characteristics, and organizational characteristics. Results show that perceptions of usefulness, safety, ease of use, and usability are related to ratings of trust in smart intravenous pumps. Other work systemfactors such as perception of work environment, age, experience, quality of work, and perception of work performance are also related to ratings of trust. Nurses' trust in smart intravenous pumps is influenced by both characteristics of the technology and the sociotechnical system. Findings from this research have implications for the design of future smart intravenous pumps and health systems. Recommendations for appropriately trustworthy smart intravenous pumps are discussed. Findings also have implications for how trust in health technologies can be measured and conceptualized in complex sociotechnical systems.

The Impact of Feedback Modalities and the Influence of Cognitive Load on Interpersonal Communication in Nonclinical Settings: Experimental Study Design.

BACKGROUND: The escalating demands of modern health care systems, combined with the emotional toll of patient care, have led to an alarming increase in physician burnout rates. This burnout, characterized by emotional exhaustion, depersonalization, and reduced personal accomplishment, can hinder doctors' ability to connect with patients effectively. Moreover, the cognitive load arising from information overload and the need for multitasking can further hinder doctors' ability to connect with patients effectively. Understanding the complex relationship between physician burnout and cognitive load is crucial for devising targeted interventions that enhance physician well-being and promote effective physician-patient interactions. Implementing strategies to alleviate burnout and cognitive load can lead to improved health care experiences and patient outcomes. OBJECTIVE: Our study explores the interplay between physician burnout and its potential impact on interpersonal communication, particularly focusing on the role of cognitive load using a pilot study in a nonclinical setting involving nonclinical participants. METHODS: This study uses an experimental design to evaluate 3 feedback tools (haptic, visual, and postvisit summary) and measure the cognitive load they impose on nonclinical participants in a nonclinical environment. The NASA Task Load Index, a widely accepted measure of cognitive load, was used to quantify the cognitive load associated with the feedback tools. The study used a within-subject design, meaning participants experienced all 3 feedback methods. A sample of 18 nonclinical participants was selected using counterbalancing techniques. RESULTS: Postsession feedback not only enhancing performance but also mitigating the influence of cognitive load as compared with real-time feedback (haptic+visual). Participants with interview experience showed lower cognitive load levels when exposed to real-time feedback as compared with novice users. In contrast, postsession feedback was more effective for novice users. In addition, cognitive workload emerged as a moderating factor in the relationship between feedback tools and their impact on performance, particularly in terms of speaking balance and pace. This moderating effect suggests that the correlation between feedback tool efficacy and performance varies based on an individual's cognitive load while using the feedback tool. The comparison of postfeedback with haptic feedback yielded a Z score of -3.245 and a P value of .001, while the comparison with visual feedback resulted in a Z score of -2.940 and a P value of .003. These outcomes underscore a significant disparity in the means between postsession feedback and real-time feedback (haptic+visual), with postsession feedback indicating the lowest mean score. CONCLUSIONS: Through the examination of various feedback tools, this study yields significant and insightful comparisons regarding their usability and appropriateness in nonclinical settings. To enhance the applicability of these findings to clinical environments, further research encompassing diverse participant cohorts and clinical scenarios is warranted.

Evaluation of Eye Gaze Dynamics During Physician-Patient-Computer Interaction in Federally Qualified Health Centers: Systematic Analysis.

BACKGROUND: Understanding the communication between physicians and patients can identify areas where they can improve and build stronger relationships. This led to better patient outcomes including increased engagement, enhanced adherence to treatment plan, and a boost in trust. OBJECTIVE: This study investigates eye gaze directions of physicians, patients, and computers in naturalistic medical encounters at Federally Qualified Health Centers to understand communication patterns given different patients' diverse backgrounds. The aim is to support the building and designing of health information technologies, which will facilitate the improvement of patient outcomes. METHODS: Data were obtained from 77 videotaped medical encounters in 2014 from 3 Federally Qualified Health Centers in Chicago, Illinois, that included 11 physicians and 77 patients. Self-reported surveys were collected from physicians and patients. A systematic analysis approach was used to thoroughly examine and analyze the data. The dynamics of eye gazes during interactions between physicians, patients, and computers were evaluated using the lag sequential analysis method. The objective of the study was to identify significant behavior patterns from the 6 predefined patterns initiated by both physicians and patients. The association between eye gaze patterns was examined using the Pearson chi-square test and the Yule Q test. RESULTS: The results of the lag sequential method showed that 3 out of 6 doctor-initiated gaze patterns were followed by patient-response gaze patterns. Moreover, 4 out of 6 patient-initiated patterns were significantly followed by doctor-response gaze patterns. Unlike the findings in previous studies, doctor-initiated eye gaze behavior patterns were not leading patients' eye gaze. Moreover, patient-initiated eye gaze behavior patterns were significant in certain circumstances, particularly when interacting with physicians. CONCLUSIONS: This study examined several physician-patient-computer interaction patterns in naturalistic settings using lag sequential analysis. The data indicated a significant influence of the patients' gazes on physicians. The findings revealed that physicians demonstrated a higher tendency to engage with patients by reciprocating the patient's eye gaze when the patient looked at them. However, the reverse pattern was not observed, suggesting a lack of reciprocal gaze from patients toward physicians and a tendency to not direct their gaze toward a specific object. Furthermore, patients exhibited a preference for the computer when physicians directed their eye gaze toward it.

Health and wellness technology use by historically underserved health consumers: systematic review.

BACKGROUND: The implementation of health technology is a national priority in the United States and widely discussed in the literature. However, literature about the use of this technology by historically underserved populations is limited. Information on culturally informed health and wellness technology and the use of these technologies to reduce health disparities facing historically underserved populations in the United States is sparse in the literature. OBJECTIVE: To examine ways in which technology is being used by historically underserved populations to decrease health disparities through facilitating or improving health care access and health and wellness outcomes. METHODS: We conducted a systematic review in four library databases (PubMed, PsycINFO, Web of Science, and Engineering Village) to investigate the use of technology by historically underserved populations. Search strings consisted of three topics (eg, technology, historically underserved populations, and health). RESULTS: A total of 424 search phrases applied in the four databases returned 16,108 papers. After review, 125 papers met the selection criteria. Within the selected papers, 30 types of technology, 19 historically underserved groups, and 23 health issues were discussed. Further, almost half of the papers (62 papers) examined the use of technology to create effective and culturally informed interventions or educational tools. Finally, 12 evaluation techniques were used to assess the technology. CONCLUSIONS: While the reviewed studies show how technology can be used to positively affect the health of historically underserved populations, the technology must be tailored toward the intended population, as personally relevant and contextually situated health technology is more likely than broader technology to create behavior changes. Social media, cell phones, and videotapes are types of technology that should be used more often in the future. Further, culturally informed health information technology should be used more for chronic diseases and disease management, as it is an innovative way to provide holistic care and reminders to otherwise underserved populations. Additionally, design processes should be stated regularly so that best practices can be created. Finally, the evaluation process should be standardized to create a benchmark for culturally informed health information technology.

Trust in technology-mediated collaborative health encounters: constructing trust in passive user interactions with technologies.

The present study investigated factors that explain patient trust in health technology and the relationship between patient trust in technology and trust in their care provider. Sociotechnical systems theory states that changes in one part of the system are likely related to other parts of the system. Therefore, attitudes about technologies, like trust, are likely related to other aspects of the system. Contributing to appropriate trust at the technological, interpersonal, and system levels can potentially lead to positive health outcomes. The study described in this manuscript used data collected from 101 patients with a Trust in Medical Technology instrument. The instrument measured patients' trust in (1) their providers, (2) the technology, and (3) how their providers used the technology. Measure 3 was positively associated with measures 1 and 2, while measures 1 and 2 were not positively or negatively associated with one another. These results may indicate that patient assessments of the trustworthiness of care providers and technologies are based on their observations of how providers use technologies. PRACTITIONER SUMMARY: Though patients are not active users of technologies in health care, the results of this study show that their perceptions of how providers use technology are related to their trust in both technology and the care provider. Study findings have implications for how trust is conceptualised and measured in interpersonal relationships and in technologies.

A Call to Action: Using and Extending Human-Centered Design Methodologies to Improve Mental and Behavioral Health Equity.

Mental health disparities directly tie to structural racism. Digital mental health (DMH), the use of technologies to deliver services, have been touted as a way to expand access to care and reduce disparities. However, many DMH fail to mitigate the persistent disparities associated with structural racism that impact delivery (e.g., costs, dependable internet access)-and may even exacerbate them. Human-centered design (HCD) may be uniquely poised to design and test interventions alongside, rather than "for," marginalized individuals. In employing HCD methodologies, developers may proceed with a vested interest in understanding and establishing empathy with users and their needs, behaviors, environments, and constraints. As such, HCD used to mindfully address structural racism in behavioral health care may address shortcomings of prior interventions that have neglected to elevate the voices of marginalized individuals. We argue that a paradigm shift in behavioral health services research is critically needed-one that embraces HCD as a key methodological framework for developing and evaluating interventions with marginalized communities, to ultimately promote more accessible, useful, and equitable care. The current commentary illustrates practical examples of the use of HCD methodologies to develop and evaluate DMH designed with marginalized populations, while also highlighting its limitations and need for even greater inclusivity. Following this, calls to action to learn from and improve upon HCD methodologies will be detailed. Acknowledging potential limitations of current design practices, methodologies must ultimately engage representative voices beyond research participation and invest in their active role as compensated and true collaborators to intervention design.

Using a sociotechnical systems analysis to evaluate an intervention to improve opioid prescribing in emergency medicine.

The United States is facing an unprecedented epidemic of opioid addiction and death due to opioid overdose. In an effort to improve patient knowledge and safe use about opioids, an Electronic Medication Complete Communication (EMC2) opioid strategy was developed targeting opioid naïve patients in the Emergency Department (ED). We conducted pre and post sociotechnical systems analyses to evaluate the variance between the process before the intervention and whether or not the process changed as expected with the new intervention. Results were analyzed using thematic qualitative analysis. Sociotechnical systems modeling illustrates the complexity of designing interventions for emergency medicine that affect multiple patients, providers, work systems, technologies, and processes. The post work systems model illustrates that several elements in the external ED environment can affect the effectiveness of the intervention. Sociotechnical systems analysis is an effective tool to illustrate the opportunities for designing health system interventions and evaluating the fidelity of such interventions.

Patient source of learning about health technologies and ratings of trust in technologies used in their care.

In order to design effective health technologies and systems, it is important to understand how patients learn and make decisions about health technologies used in their care. The objective of this study was to examine patients' source of learning about technologies used in their care and how the source related to their trust in the technology was used. Individual face-to-face and telephone interviews were conducted with 24 patients. Altogether, 13 unique sources of information about technology were identified and three major themes emerged: outside of the work system vs. inside the work system; when the health information was provided; the medium used. Patients used multiple sources outside of the healthcare work system to learn about technologies that will be used in their care. Results showed a relationship between learning about technologies from web sources and trust in technologies but no relationship between learning about technologies from healthcare providers and trust in technologies. STATEMENT OF RELEVANCE: The value of considering human attitudes about elements in health systems has been illustrated. This research shows a relationship between patient attitudes about medical technologies used in their care and healthcare work system design. Results show that patient attitudes are formed about technologies used in their care by sources within and outside of the sociotechnical work system.

Behavioral and cognitive intervention strategies delivered via coached apps for depression: Pilot trial.

Depression is common in primary care settings, but barriers prevent many primary care patients from initiating treatment. Smartphone apps stand as a possible means to overcome such barriers. However, there is limited evidence to understand the use and efficacy of these apps. The purpose of the current study was to pilot an evaluation of the usage and efficacy of apps for depression based upon behavioral or cognitive intervention skills, compared to a wait-list control. Thirty adults with depression were randomized to the use of either a behavioral app (Boost Me) or a cognitive app (Thought Challenger) or to a wait-list control. Boost Me and Thought Challenger participants received 6 weeks of the respective intervention along with weekly coaching sessions, with a 4-week follow-up period; wait-list control participants received no interventions for 10 weeks. A repeated-measures analysis of variance was conducted to examine depression over time and across treatment groups; t tests compared app usage across groups. Depression scores changed significantly over time (p < .001), with group differences occurring between Thought Challenger and wait-list control participants (p = .03). Boost Me was used significantly more than was Thought Challenger (p = .02); however, there was no evidence to suggest correlations between usage and changes in depression (ps > .05). The present study provides initial support that intervention strategies for depression delivered via apps with human support can impact symptoms and may promote continued use over 6 weeks. This pilot also demonstrates the feasibility of future research regarding the delivery of behavioral and cognitive intervention strategies via apps. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

A Multifaceted Intervention to Improve Patient Knowledge and Safe Use of Opioids: Results of the ED EMC2 Randomized Controlled Trial.

OBJECTIVES: Despite increased focus on opioid prescribing, little is known about the influence of prescription opioid medication information given to patients in the emergency department (ED). The study objective was to evaluate the effect of an Electronic Medication Complete Communication (EMC2 ) Opioid Strategy on patients' safe use of opioids and knowledge about opioids. METHODS: This was a three-arm prospective, randomized controlled pragmatic trial with randomization occurring at the physician level. Consecutive discharged patients at an urban academic ED (>88,000 visits) with new hydrocodone-acetaminophen prescriptions received one of three care pathways: 1) usual care, 2) EMC2 intervention, or 3) EMC2  + short message service (SMS) text messaging. The ED EMC2 intervention triggered two patient-facing educational tools (MedSheet, literacy-appropriate prescription wording [Take-Wait-Stop]) and three provider-facing reminders to counsel (directed to ED physician, dispensing pharmacist, follow-up physician). Patients in the EMC2  + SMS arm additionally received one text message/day for 1 week. Follow-up at 1 to 2 weeks assessed "demonstrated safe use" (primary outcome). Secondary outcomes including patient knowledge and actual safe use (via medication diaries) were assessed 2 to 4 days and 1 month following enrollment. RESULTS: Among the 652 enrolled, 343 completed follow-up (57% women; mean ± SD age = 42 ± 14.0 years). Demonstrated safe opioid use occurred more often in the EMC2 group (adjusted odds ratio [aOR] = 2.46, 95% confidence interval [CI] = 1.19 to 5.06), but not the EMC2  + SMS group (aOR = 1.87, 95% CI = 0.90 to 3.90) compared with usual care. Neither intervention arm improved medication safe use as measured by medication diary data. Medication knowledge, measured by a 10-point composite knowledge score, was greater in the EMC2  + SMS group (ß = 0.57, 95% CI = 0.09 to 1.06) than usual care. CONCLUSIONS: The study found that the EMC2 tools improved demonstrated safe dosing, but these benefits did not translate into actual use based on medication dairies. The text-messaging intervention did result in improved patient knowledge.

Exploring User Learnability and Learning Performance in an App for Depression: Usability Study.

BACKGROUND: Mental health apps tend to be narrow in their functioning, with their focus mostly being on tracking, management, or psychoeducation. It is unclear what capability such apps have to facilitate a change in users, particularly in terms of learning key constructs relating to behavioral interventions. Thought Challenger (CBITs, Chicago) is a skill-building app that engages users in cognitive restructuring, a core component of cognitive therapy (CT) for depression. OBJECTIVE: The purpose of this study was to evaluate the learnability and learning performance of users following initial use of Thought Challenger. METHODS: Twenty adults completed in-lab usability testing of Thought Challenger, which comprised two interactions with the app. Learnability was measured via completion times, error rates, and psychologist ratings of user entries in the app; learning performance was measured via a test of CT knowledge and skills. Nonparametric tests were conducted to evaluate the difference between individuals with no or mild depression to those with moderate to severe depression, as well as differences in completion times and pre- and posttests. RESULTS: Across the two interactions, the majority of completion times were found to be acceptable (5 min or less), with minimal errors (1.2%, 10/840) and successful completion of CT thought records. Furthermore, CT knowledge and skills significantly improved after the initial use of Thought Challenger (P=.009). CONCLUSIONS: The learning objectives for Thought Challenger during initial uses were successfully met in an evaluation with likely end users. The findings therefore suggest that apps are capable of providing users with opportunities for learning of intervention skills.

What might get in the way: Barriers to the use of apps for depression.

OBJECTIVE: Smartphones are being used with increasing frequency to deliver behavioral interventions for depression via apps. However, barriers specific to using an app for depression are poorly defined. The purpose of the current study is to identify barriers to the use of a mobile app to deliver treatment for depression. Secondarily, design implications will be provided based upon identified barriers. METHOD: A card sorting task that ranked and grouped barriers to the use of apps for depression was completed. Participants first completed a card sorting task identifying barriers to face-to-face treatment, as a primer to identification of treatment barriers. The sample consisted of those above (n = 9) and below (n = 11) the threshold for a referral to psychotherapy, to capture anticipated barriers for likely end users. Cluster analyses were conducted to analyze the card sorting data. Multiple analyses were conducted to identify: 1) the most important barriers, and 2) how consistently barriers were ranked as important. RESULT: The card sorting task identified a number of primary barriers to the use of apps for depression treatment, including concerns over intervention efficacy, app functioning, privacy, cost, and lack of guidance and tailored feedback. The top face-to-face treatment barrier was cost, overlapping with mobile barriers. CONCLUSION: This study identified perceived barriers to the use of mobile treatment apps. Identification of barriers implicates design recommendations for apps for depression.