Incorporating Cardiovascular Risk Assessment into Adolescent Reproductive Health and Primary Care Visits.

STUDY OBJECTIVE: This study aimed to evaluate the usability and feasibility of incorporating a cardiovascular risk assessment tool into adolescent reproductive health and primary care visits. METHODS: We recruited 60 young women ages 13-21 years to complete the HerHeart web-tool in two adolescent clinics in Atlanta, GA. Participants rated the tool's usability via the Website Analysis and Measurement Inventory (WAMMI, range 0-95) and their perceived 10-year and lifetime risk of cardiovascular disease (CVD) on a visual analog scale (range 0-10). Participants' perceived risk, blood pressure, and body mass index were measured at baseline and three months after enrollment. Healthcare providers (HCP, n=5) completed the WAMMI to determine the usability and feasibility of incorporating the HerHeart tool into clinical practice. RESULTS: Adolescent participants and HCPs rated the tool's usability highly on the WAMMI with a median of 79 (IQR 65, 84) and 76 (IQR 71, 84). At the baseline visit, participants' median perceived 10-year risk of a heart attack was 1 (IQR 0, 3), and perceived lifetime risk was 2 (IQR 0, 4). Immediately after engaging with the tool, participants' median perceived 10-year risk was 2 (IQR 1, 4.3), and perceived lifetime risk was 3 (IQR 1.8, 6). Thirty-one participants chose to set a behavior change goal, and 12 participants returned for follow-up. Clinical metrics were similar at the baseline and follow-up visits. CONCLUSION: HerHeart is acceptable to young women and demonstrates potential for changing risk perception and improving health habits to reduce risk of CVD. Future research should focus on improving retention in studies to promote cardiovascular health within reproductive health clinics.

What's in a Name? Experimental Evidence of Gender Bias in Recommendation Letters Generated by ChatGPT.

BACKGROUND: Artificial intelligence chatbots such as ChatGPT (OpenAI) have garnered excitement about their potential for delegating writing tasks ordinarily performed by humans. Many of these tasks (eg, writing recommendation letters) have social and professional ramifications, making the potential social biases in ChatGPT's underlying language model a serious concern. OBJECTIVE: Three preregistered studies used the text analysis program Linguistic Inquiry and Word Count to investigate gender bias in recommendation letters written by ChatGPT in human-use sessions (N=1400 total letters). METHODS: We conducted analyses using 22 existing Linguistic Inquiry and Word Count dictionaries, as well as 6 newly created dictionaries based on systematic reviews of gender bias in recommendation letters, to compare recommendation letters generated for the 200 most historically popular "male" and "female" names in the United States. Study 1 used 3 different letter-writing prompts intended to accentuate professional accomplishments associated with male stereotypes, female stereotypes, or neither. Study 2 examined whether lengthening each of the 3 prompts while holding the between-prompt word count constant modified the extent of bias. Study 3 examined the variability within letters generated for the same name and prompts. We hypothesized that when prompted with gender-stereotyped professional accomplishments, ChatGPT would evidence gender-based language differences replicating those found in systematic reviews of human-written recommendation letters (eg, more affiliative, social, and communal language for female names; more agentic and skill-based language for male names). RESULTS: Significant differences in language between letters generated for female versus male names were observed across all prompts, including the prompt hypothesized to be neutral, and across nearly all language categories tested. Historically female names received significantly more social referents (5/6, 83% of prompts), communal or doubt-raising language (4/6, 67% of prompts), personal pronouns (4/6, 67% of prompts), and clout language (5/6, 83% of prompts). Contradicting the study hypotheses, some gender differences (eg, achievement language and agentic language) were significant in both the hypothesized and nonhypothesized directions, depending on the prompt. Heteroscedasticity between male and female names was observed in multiple linguistic categories, with greater variance for historically female names than for historically male names. CONCLUSIONS: ChatGPT reproduces many gender-based language biases that have been reliably identified in investigations of human-written reference letters, although these differences vary across prompts and language categories. Caution should be taken when using ChatGPT for tasks that have social consequences, such as reference letter writing. The methods developed in this study may be useful for ongoing bias testing among progressive generations of chatbots across a range of real-world scenarios. TRIAL REGISTRATION: OSF Registries osf.io/ztv96; https://osf.io/ztv96.

A Web-Based Intervention to Address Risk Factors for Maternal Morbidity and Mortality (MAMA LOVE): Development and Evaluation Study.

Background: Maternal mortality in the United States is a public health crisis and national emergency. Missed or delayed recognition of preventable life-threatening symptoms and untimely treatment of preventable high-risk medical conditions have been cited as key contributors to the nation's worsening mortality rates. Effective strategies are urgently needed to address this maternal health crisis, particularly for Black birthing populations. Morbidity and Mortality Assessment: Lifting Outcomes Via Education (MAMA LOVE) is a web-based platform that focuses on the identification of maternal morbidity and mortality risk factors. Objective: The purpose of this paper is to present the conceptualization, development, heuristics, and utility evaluation of the web-based maternal mortality risk assessment and educational tool MAMA LOVE. Methods: A user-centered design approach was used to gain feedback from clinical experts and potential end users to ensure that the tool would be effective among groups most at risk for maternal morbidity and mortality. A heuristic evaluation was conducted to evaluate usability and need within the current market. Algorithms describing key clinical, mental health, and social conditions were designed using digital canvas software (Miro) and incorporated into the final wireframes of the revised prototype. The completed version of MAMA LOVE was designed in Figma and built with the SurveyJS platform. Results: The creation of the MAMA LOVE tool followed three distinct phases: (1) the content development and creation of an initial prototype; (2) the feedback gathering and usability assessment of the prototype; and (3) the design, development, and testing of the final tool. The tool determines the corresponding course of action using the algorithm developed by the authors. A total of 38 issues were found in the heuristic evaluation of the web tool's initial prototype. Conclusions: Maternal morbidity and mortality is a public health crisis needing immediate effective interventions. In the current market, there are few digital resources available that focus specifically on the identification of dangerous symptoms and risk factors. MAMA LOVE is a tool that can address that need by increasing knowledge and providing resources and information that can be shared with health care professionals.

Navigating the complexities of mobile medical app development from idea to launch, a guide for clinicians and biomedical researchers.

With today's pace of rapid technological advancement, many patient issues in modern medicine are increasingly solvable by mobile app solutions, which also have the potential to transform how clinical research is conducted. However, many critical challenges in the app development process impede bringing these translational technologies to patients, caused in large part by the lack of knowledge among clinicians and biomedical researchers of "what it takes" to design, develop, and maintain a successful medical app. Indeed, problems requiring mobile app solutions are often nuanced, requiring more than just clinical expertise, and issues such as the cost and effort required to develop and maintain a well-designed, sustainable, and scalable mobile app are frequently underestimated. To bridge this skill set gap, we established an academic unit of designers, software engineers, and scientists that leverage human-centered design methodologies and multi-disciplinary collaboration to develop clinically viable smartphone apps. In this report, we discuss major misconceptions clinicians and biomedical researchers often hold regarding medical app development, the steps we took to establish this unit to address these issues and the best practices and lessons learned from successfully ideating, developing, and launching medical apps. Overall, this report will serve as a blueprint for clinicians and biomedical researchers looking to better benefit their patients or colleagues via medical mobile apps.

Assessing and Promoting Cardiovascular Health for Adolescent Women: User-Centered Design Approach.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death among women in the United States. A considerable number of young women already have risk factors for CVD. Awareness of CVD and its risk factors is critical to preventing CVD, yet younger women are less aware of CVD prevalence, its risk factors, and preventative behaviors compared to older women. OBJECTIVE: The purpose of this study is to assess CVD awareness among adolescent and young adult women and develop a lifestyle-based cardiovascular risk assessment tool for the promotion of CVD awareness among this population. METHODS: This study used a 3-phase iterative design process with young women and health care practitioners from primary care and reproductive care clinics in Atlanta, Georgia. In phase 1, we administered a modified version of the American Heart Association Women's Health Survey to young women, aged 15-24 years (n=67), to assess their general CVD awareness. In phase 2, we interviewed young women, aged 13-21 years (n=10), and their health care practitioners (n=10), to solicit suggestions for adapting the Healthy Heart Score, an existing adult cardiovascular risk assessment tool, for use with this age group. We also aimed to learn more about the barriers and challenges to health behavior change within this population and the clinical practices that serve them. In phase 3, we used the findings from the first 2 phases to create a prototype of a new online cardiovascular risk assessment tool designed specifically for young women. We then used an iterative user-centered design process to collect feedback from approximately 105 young women, aged 13-21 years, as we adapted the tool. RESULTS: Only 10.5% (7/67) of the young women surveyed correctly identified CVD as the leading cause of death among women in the United States. Few respondents reported having discussed their personal risk (4/67, 6%) or family history of CVD (8/67, 11.9%) with a health care provider. During the interviews, young women reported better CVD awareness and knowledge after completing the adult risk assessment tool and suggested making the tool more teen-friendly by incorporating relevant foods and activity options. Health care practitioners emphasized shortening the assessment for easier use within practice and discussed other barriers adolescents may face in adopting heart-healthy behaviors. The result of the iterative design process was a youth-friendly prototype of a cardiovascular risk assessment tool. CONCLUSIONS: Adolescent and young adult women demonstrate low awareness of CVD. This study illustrates the potential value of a cardiovascular risk assessment tool adapted for use with young women and showcases the importance of user-centered design when creating digital health interventions.

The development and characterization of a novel yet simple 3D printed tool to facilitate phantom imaging of photoacoustic contrast agents.

We report a new approach to preparing phantoms using 3D printing. This device supports plastic tubing containing the contrast agent and is immersed in a solution with absorption or scattering properties that mimic tissue. Up to 12 tubing samples could be placed in the device with sample-to-sample spacing as low as 0.3 mm and at a constant distance from the transducer (±0.16 mm), which is critical in validating photoacoustic contrast agents. We also studied different types of tubing and found that tubing with a larger outside diameter has more inherent signal. Both 40% India Ink and lipids in the immersion media modulated the signal. Finally, we created a depth phantom and found that signal decayed following a linear relationship (R2 = 0.997) with respect to distance from the focal point. We include computer-assisted drafting code the community can use to print this phantom or customized versions of this phantom.

A Nanoscale Tool for Photoacoustic-Based Measurements of Clotting Time and Therapeutic Drug Monitoring of Heparin.

Heparin anticoagulation therapy is an indispensable feature of clinical care yet has a narrow therapeutic window and is the second most common intensive care unit (ICU) medication error. The active partial thromboplastin time (aPTT) monitors heparin but suffers from long turnaround times, a variable reference range, limited utility with low molecular weight heparin, and poor correlation to dose. Here, we describe a photoacoustic imaging technique to monitor heparin concentration using methylene blue as a simple and Federal Drug Administration-approved contrast agent. We found a strong correlation between heparin concentration and photoacoustic signal measured in phosphate buffered saline (PBS) and blood. Clinically relevant heparin concentrations were detected in blood in 32 s with a detection limit of 0.28 U/mL. We validated this imaging approach by correlation to the aPTT (Pearson's r = 0.86; p < 0.05) as well as with protamine sulfate treatment. This technique also has good utility with low molecular weight heparin (enoxaparin) including a blood detection limit of 72 µg/mL. We then used these findings to create a nanoparticle-based hybrid material that can immobilize methylene blue for potential applications as a wearable/implantable heparin sensor to maintain drug levels in the therapeutic window. To the best of our knowledge, this is the first use of photoacoustics to image anticoagulation therapy with significant potential implications to the cardiovascular and surgical community.