Telehealth Research and Innovation for Veterans with Cancer: the THRIVE Center.

BACKGROUND: In recent years the US health-care system has witnessed a substantial increase in telehealth use. Telehealth enhances health-care access and quality and may reduce costs. However, there is a concern that the shift from in-person to telehealth care delivery may differentially improve cancer care access and quality in certain clinical settings and for specific patient populations while potentially exacerbating disparities in care for others. Our National Cancer Institute-funded center, called Telehealth Research and Innovation for Veterans with Cancer (THRIVE), is focused on health equity for telehealth-delivered cancer care. We seek to understand how social determinants of telehealth-particularly race and ethnicity, poverty, and rurality-affect the use of telehealth. METHODS: THRIVE draws from the Health Disparities Research Framework and the Consolidated Framework for Implementation Research. THRIVE consists of multiple cores that work synergistically to assess and understand health equity for telehealth-delivered cancer care. These include the Administrative Core, Research and Methods Core, Clinical Practice Network, and Pragmatic Trial. RESULTS: As of October 2023, we identified and trained 5 THRIVE scholars, who are junior faculty beginning a research career. We have reviewed 20 potential pilot studies, funding 6. Additionally, in communication with our funders and advisory boards, we have adjusted our study design and analytic approach, ensuring feasibility while addressing our operational partners' needs. CONCLUSIONS: THRIVE has several key strengths. First, the Veterans Health Administration's health-care system is large and diverse regarding health-care setting type and patient population. Second, we have access to longitudinal data, predating the COVID-19 pandemic, about telehealth use. Finally, equitable access to high-quality care for all veterans is a major tenet of the Veterans Health Administration health-care mission. As a result of these advantages, THRIVE can focus on isolating and evaluating the impact of social determinants of telehealth on equity in cancer care.

Sociotechnical feasibility of natural language processing-driven tools in clinical trial eligibility prescreening for Alzheimer's disease and related dementias.

BACKGROUND: Alzheimer's disease and related dementias (ADRD) affect over 55 million globally. Current clinical trials suffer from low recruitment rates, a challenge potentially addressable via natural language processing (NLP) technologies for researchers to effectively identify eligible clinical trial participants. OBJECTIVE: This study investigates the sociotechnical feasibility of NLP-driven tools for ADRD research prescreening and analyzes the tools' cognitive complexity's effect on usability to identify cognitive support strategies. METHODS: A randomized experiment was conducted with 60 clinical research staff using three prescreening tools (Criteria2Query, Informatics for Integrating Biology and the Bedside [i2b2], and Leaf). Cognitive task analysis was employed to analyze the usability of each tool using the Health Information Technology Usability Evaluation Scale. Data analysis involved calculating descriptive statistics, interrater agreement via intraclass correlation coefficient, cognitive complexity, and Generalized Estimating Equations models. RESULTS: Leaf scored highest for usability followed by Criteria2Query and i2b2. Cognitive complexity was found to be affected by age, computer literacy, and number of criteria, but was not significantly associated with usability. DISCUSSION: Adopting NLP for ADRD prescreening demands careful task delegation, comprehensive training, precise translation of eligibility criteria, and increased research accessibility. The study highlights the relevance of these factors in enhancing NLP-driven tools' usability and efficacy in clinical research prescreening. CONCLUSION: User-modifiable NLP-driven prescreening tools were favorably received, with system type, evaluation sequence, and user's computer literacy influencing usability more than cognitive complexity. The study emphasizes NLP's potential in improving recruitment for clinical trials, endorsing a mixed-methods approach for future system evaluation and enhancements.

Comparison of evaluation methods for improving the usability of a Spanish mHealth tool.

OBJECTIVE: Mobile health (mHealth) technology is now widely used across health conditions and populations. The rigorous development of these tools has yielded improved health outcomes, yet the ideal approach for developing mHealth tools continues to evolve, indicating the need for rigorous usability evaluation methods. This study compares two usability evaluation methods - cognitive interviews and usability assessments employing a think-aloud approach - for adapting an evidence-based mHealth tool from English into Spanish. METHODS: We conducted cognitive interviews and usability assessments using a think-aloud protocol to evaluate the usability of an HIV mHealth application among 40 Spanish-speaking adults with HIV in New York City, NY, and La Romana, Dominican Republic. The Health IT Usability Evaluation Model (Health-ITUEM) was used to guide the analysis of qualitative data collected from each method. RESULTS: Participants (N = 40) averaged 43 years old (SD = 12.26; range 20-79), identified primarily Hispanic/Latino (92.5 %), and resided in La Romana (50 %) or New York City (50 %). Both usability evaluation methods yielded similar findings, highlighting learnability and information needs as crucial components of participant feedback for the mHealth application. Cognitive interviews captured participants' perspectives on the app's interface and design. On the other hand, results from usability assessments offered insights into participants' competency while interacting with the mHealth tool. CONCLUSION: Findings from this study highlight the contributions and limitations of including cognitive interviews and task-based usability assessments using a think-aloud approach in mHealth usability testing. Future research should employ a multi-method approach, incorporating complementary usability evaluation methods and engaging participants in multiple assessments. Using complementary usability evaluation methods may provide a more comprehensive understanding of the usability and participant experience aspects of a mHealth tool compared to using a single usability evaluation method.

Associations between Self-Rated Health and Perinatal Depressive and Anxiety Symptoms among Latina Women.

PURPOSE: The objective of this study was to determine whether decreases in or consistently low preconception to pregnancy self-rated health (SRH) were associated with perinatal depressive and anxiety symptoms among Latinas. METHODS: This is a secondary data analysis of 153 perinatal Latinas. Three groups were created to capture SRH from preconception to pregnancy: a decline in ratings, consistently low, and good+ (i.e., good, very good, or excellent). SRH was measured using two questions about their perceived physical health before and during pregnancy. Depressive symptoms and anxiety symptoms were assessed in the third trimester and six weeks postpartum using the Edinburgh Postnatal Depression Scale and State-Trait Anxiety Inventory, respectively. Life stressors were assessed in pregnancy using a modified version of the Life Experiences Survey. Linear regressions tested the associations. RESULTS: Women with consistently low (i.e., fair or poor) SRH reported significantly more prenatal depressive symptoms than women who reported consistently good+ SRH. Women who reported a decline in SRH to fair or poor reported more prenatal anxiety symptoms but decreased postpartum anxiety symptoms than women who reported consistently good+ ratings. Life stressors were positively associated with prenatal depressive and anxiety symptoms. CONCLUSIONS: Healthcare practitioners should assess changes in SRH ratings to identify risks for prenatal depressive and anxiety symptoms among Latinas, who have elevated rates of depressive and anxiety symptoms compared to non-Hispanic White women. Policymakers should provide healthcare providers with mental health resources to support at-risk Latinas during the prenatal period.

Perinatal Anxiety Symptoms: Rates and Risk Factors in Mexican Women.

Anxiety during pregnancy and after childbirth can have negative consequences for a woman and her baby. Despite growing interest in the perinatal mental health of Mexican women living in the U.S., perinatal anxiety symptom (PAS) rates and risk factors have yet to be established for women in Mexico. We sought to determine PAS rates and identify risk factors, including the traditional female role (TFR) in a sample of Mexican women. This secondary data analysis is based on 234 Mexican women who participated in a longitudinal study on perinatal depression in Mexico. Anxiety symptoms were assessed in pregnancy and at six weeks postpartum. Rates were determined through frequencies, and multiple logistics regressions were conducted to identify risk factors in the sample. The PAS rate was 21% in pregnancy and 18% postpartum. Stressful life events and depressive symptoms were associated with a higher probability of PAS. Adherence to TFR increased the probability of prenatal anxiety; lower educational attainment and low social support during pregnancy increased the probability of postpartum anxiety. The PAS rates were within the range reported in the literature. The TFR was only associated with anxiety in gestation, highlighting the role of this culturally relevant risk factor. Culturally responsive early interventions are therefore required.