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BACKGROUND Depression and other mental health disorders are prevalent among people living with chronic health conditions. Although digital cognitive behavioral therapy (CBT) is considered an effective treatment, African American individuals are less likely to engage in and adhere to digital therapies for mental health disorders compared with White individuals. OBJECTIVE The aim of this study was to understand digital CBT mental health treatment perceptions and preferences of African American individuals with sickle cell disease (SCD). METHODS African American individuals with SCD from various US locations were invited to participate in a series of focus groups. Participants were introduced to a health coach–supported mental health app and then asked a series of questions about the usability and appeal of the program as well as, more generally, what would make a digital mental health program effective for them. The authors reviewed the focus group transcripts and conducted a qualitative analysis of the results. RESULTS A total of 25 people participated in 5 focus groups. Overall, 5 primary themes emerged regarding how app content and related coaching could be modified to enhance digital CBT engagement. These themes included connection with others living with SCD, the personalization of app content and coaching, characteristics of coaches, journaling and pain tracking, and considerations for optimal engagement. CONCLUSIONS Enhancing the user experience by making digital CBT tools relevant to patient populations is critical for optimizing program engagement and its uptake. Our findings highlight potential strategies to modify and design digital CBT tools for users with SCD and may also be applicable to patients with other chronic conditions. CLINICALTRIAL ClinicalTrials.gov NCT04587661; https://clinicaltrials.gov/ct2/show/NCT04587661

BACKGROUND Patients with chronic pain face several challenges in using clinical tools to help them monitor, understand, and make meaningful decisions about their pain conditions. Our group previously presented data on Painimation, a novel electronic tool for communicating and assessing pain. OBJECTIVE This paper describes the human-centered design and development approach (inspiration, ideation, and implementation) that led to the creation of Painimation. METHODS We planned an iterative and cyclical development process that included stakeholder engagement and feedback from users. Stakeholders included patients with acute and chronic pain, health care providers, and design students. Target users were adults with acute or chronic pain who needed clinical assessment and tracking of the course of their pain over time. Phase I (inspiration) consisted of empathizing with users, understanding how patients experience pain, and identifying the barriers to accurately expressing and assessing pain. This phase involved understanding how patients communicate pain symptoms to providers, as well as defining limitations of current models of clinical pain assessment tools. In Phase II (ideate) we conceptualized and evaluated different approaches to expressing and assessing pain. The most promising concept was developed through an iterative process that involved end users and stakeholders. In Phase III (implementation), based on stakeholder feedback from initial designs and prototypes of abstract pain animations (painimations), we incorporated all concepts to test a minimally viable product, a fully functioning pain assessment app. We then gathered feedback through an agile development process and applied this feedback to finalizing a testable version of the app that could ultimately be used in a pain clinic. RESULTS Engaging intended users and stakeholders in an iterative, human-centered design process identified 5 criteria that a pain assessment tool would need to meet to be effective in the medical setting. These criteria were used as guiding design principles to generate a series of pain assessment concept ideas. This human-centered approach generated 8 highly visual painimations that were found to be acceptable and useable for communicating pain with medical providers, by both patients with general pain and patients with sickle cell disease (SCD). While these initial steps continued refinement of the tool, further data are needed. Agile development will allow us to continue to incorporate precision medicine tools that are validated in the clinical research arena. CONCLUSIONS A multiphase, human-centered design approach successfully resulted in the development of an innovation that has potential to improve the quality of medical care, particularly for underserved populations. The use of Painimation may especially benefit the medical care of minority populations with chronic and difficult-to-treat pain, such as adults with SCD. The insights generated from this study can be applied to the development of patient-reported outcomes tools that are more patient-centered, engaging, and effective.

Background Patients with chronic pain face several challenges in using clinical tools to help them monitor, understand, and make meaningful decisions about their pain conditions. Our group previously presented data on Painimation, a novel electronic tool for communicating and assessing pain. Objective This paper describes the human-centered design and development approach (inspiration, ideation, and implementation) that led to the creation of Painimation. Methods We planned an iterative and cyclical development process that included stakeholder engagement and feedback from users. Stakeholders included patients with acute and chronic pain, health care providers, and design students. Target users were adults with acute or chronic pain who needed clinical assessment and tracking of the course of their pain over time. Phase I (inspiration) consisted of empathizing with users, understanding how patients experience pain, and identifying the barriers to accurately expressing and assessing pain. This phase involved understanding how patients communicate pain symptoms to providers, as well as defining limitations of current models of clinical pain assessment tools. In Phase II (ideate) we conceptualized and evaluated different approaches to expressing and assessing pain. The most promising concept was developed through an iterative process that involved end users and stakeholders. In Phase III (implementation), based on stakeholder feedback from initial designs and prototypes of abstract pain animations (painimations), we incorporated all concepts to test a minimally viable product, a fully functioning pain assessment app. We then gathered feedback through an agile development process and applied this feedback to finalizing a testable version of the app that could ultimately be used in a pain clinic. Results Engaging intended users and stakeholders in an iterative, human-centered design process identified 5 criteria that a pain assessment tool would need to meet to be effective in the medical setting. These criteria were used as guiding design principles to generate a series of pain assessment concept ideas. This human-centered approach generated 8 highly visual painimations that were found to be acceptable and useable for communicating pain with medical providers, by both patients with general pain and patients with sickle cell disease (SCD). While these initial steps continued refinement of the tool, further data are needed. Agile development will allow us to continue to incorporate precision medicine tools that are validated in the clinical research arena. Conclusions A multiphase, human-centered design approach successfully resulted in the development of an innovation that has potential to improve the quality of medical care, particularly for underserved populations. The use of Painimation may especially benefit the medical care of minority populations with chronic and difficult-to-treat pain, such as adults with SCD. The insights generated from this study can be applied to the development of patient-reported outcomes tools that are more patient-centered, engaging, and effective.

BACKGROUND Sickle cell disease (SCD) is an inherited red blood cell disorder affecting millions worldwide that results in many potential medical complications throughout the lifecourse. The hallmark of SCD is pain. Many patients experience daily chronic pain, as well as intermittent, unpredictable acute vaso-occlusive painful episodes called pain crises. These pain crises often require acute medical care and can lead to a day hospital or emergency department (ED) visit, or even a hospitalization [1]. Over one in four patients seen for acute pain in the ED or day hospital are admitted, with efforts focused on palliative pain control and hydration for management [2]. However, mitigating pain crises is challenging for both the patients and their providers, given the perceived unpredictability and subjective nature of pain. OBJECTIVE We aim to use physiologic changes during an acute pain crisis to objectively measure and predict pain scores. METHODS For this pilot study, we enrolled 20 adult patients presenting to the Adult Day Hospital with acute pain. Before beginning pain treatment, each participant was given a wearable device (Microsoft Band 2) that collected physiologic measurements, and pain scores were recorded from our mobile app Technology Recordings to Understand Pain (TRU-Pain). We used this data to describe changes in pain scores and physiologic measures. Then, we constructed regression and classification machine-learning models to predict pain scores collected from mobile applications with features extracted from wearable signals. RESULTS Patients were monitored for an average of 3.79 hours (SD: +/- 2.23 hours) with an average of 5,826 (SD: +/- 2,667) objective data values per patient. As expected, we found that pain scores and heart rate decreased for most patients during the course of hospitalization. Using the wearable data, we were able to create a regression model to predict subjective pain scores with a root mean error of 1.430 and correlation between observations and predictions of 0.706. Furthermore, we verified the hypothesis that the regression model outperformed the classification model by comparing the performances of the Support Vector Machines and the Support Vector Machines for Regression. CONCLUSIONS The combination of the TRU-Pain app and wearable device provided an efficient and cost-effective method for collecting objective, physiological markers of an acute pain crisis and change in pain intensity for adult patients with SCD. Applying machine learning in this small and highly imbalanced dataset, demonstrated the potential for objectively measuring pain in SCD.

BACKGROUND Pain is the most common medical symptom requiring care, yet the current methods for assessing pain are sorely inadequate. Pain assessment tools either take too long to complete for point of care use or are too simplistic to capture the dynamic pain experience. OBJECTIVE To address this, we developed Painimation, a novel tool that uses graphic visualizations and animations instead of words or numeric scales to assess pain quality, intensity, and course. This study examines the utility of abstract animations as a measure of pain. METHODS Painimation was evaluated in a chronic pain medicine clinic. Eligible patients were receiving treatment for pain and reported pain more days than not for at least 3 months. Using a tablet computer, participating patients completed the Painimation instrument, the McGill Pain Questionnaire (MPQ), and the PainDETECT questionnaire for neuropathic symptoms. RESULTS Participants (N = 207), completed Painimation and indicated it was useful for describing their pain (mean=4.04/5 on a usefulness scale), and 154 out of 196 participants (79%) agreed or strongly agreed that they would use Painimation to communicate with their providers. Animations selected corresponded with pain adjectives endorsed on the MPQ. Further, selection of the electrifying animation was associated with self-reported neuropathic pain (r=.16, P=.03), similar to the association between neuropathic pain and PainDETECT (r=.17, P=.03). Painimation was associated with PainDETECT (r=.35, P CONCLUSIONS Using animations may be a faster and more patient-centered method for assessing pain and is not limited by age, literacy level, or language; however, more data are needed to assess the validity of this approach. Painimation needs testing in a more homogenous pain population to validate animations as a pain assessment method.

Few studies have examined traits or behaviors that may predispose some African Americans to poor cardiovascular health outcomes. While several models of personality exist, the 5-factor model (FFM) is arguably the best representation of personality and provides a useful framework for the study of personality and health. Among personality characteristics associated with health risks among African Americans, a high-effort coping style called John Henryism is among the most thoroughly examined. It is not clear if personality coping and health are connected in a meaningful way. The present study utilized data from the Baltimore Study of Black Aging (BSBA) to examine whether personality was linked to John Henryism, how personality might be linked to cardiovascular health, and how John Henryism might mediate the relationship between personality and cardiovascular health. The sample consisted of 234 older African Americans (mean age, 67 years), 28% of which were men. Regressions were used to examine the questions. The results indicated that those who are more neurotic report more cardiovascular health problems, and that openness and conscientiousness were significant predictors of active coping. The mediation analysis results suggest that coping style did not mediate the relationship between personality and reports of cardiovascular health problems. These findings highlight the importance of personality in accounting for cardiovascular health in African Americans.