Heidi Scharf Donovan

Introduction: Financial toxicity and poor mental health are common among lesbian, gay, bisexual, transgender, queer, and other non‐cisgender heterosexual (LGBTQ+) cancer caregivers. This study aimed to assess the relationship between financial toxicity and mental health among LGBTQ+cancer caregivers. Methods: We conducted a sequential explanatory mixed‐methods study (national survey and semi‐structured interviews with a subset of survey participants). Data were collected from April 2024 through December 2024. Bivariate and multivariable regression models were used to examine the association between financial toxicity (modified COmprehensive Score for financial Toxicity [mCOST]) and mental health outcomes (Mental Health Continuum‐SF [MHC‐SF] and Patient‐Reported Outcomes Measurement Information System [PROMIS] domains of anxiety, depression, sleep disturbance, and fatigue). Results: A total of N = 316 LGBTQ+cancer caregivers participated in the survey, and N = 14 participated in an interview. Among caregivers, 34.5% reported high financial toxicity (mCOST< 22). The average MHC‐SF score was 38.4 (SD: 16.9, range: 0–70). Mean PROMIS domain T‐scores were: anxiety 59.7 (SD: 10.0, range: 40.3–81.6), depression 56.2 (SD: 10.6, range: 41.0–79.4), sleep disturbance 54.2 (SD: 9.2, range: 32–73.3), and fatigue 54.8 (SD: 11.9, range: 33.7–75.8). In controlled multivariable models, high financial toxicity was significantly associated with poorer mental health (lower MHC‐SF scores [beta = −10.56, 95% CI: −14.47 to −6.65], and higher PROMIS anxiety [beta = 8.54, 95% CI: 6.33–10.74], depression [beta = 7.49, 95% CI: 5.07–9.91], sleep disturbance [beta = 6.33, 95% CI: 4.16–8.50], and fatigue [beta = 8.94, 95% CI: 6.26–11.63]. Qualitative analysis yielded two themes: (1) Financial Stress and Frustration and (2) Negative impacts of financial toxicity on health. Conclusion: LGBTQ+cancer caregivers experience high financial toxicity that is associated with poor mental health outcomes. Financial toxicity should be addressed in addition to general caregiving‐related stress in this at‐risk population.

User-centered design is a commonly accepted approach in designing interactive systems; however, its application to the design of interactive recommender systems is still limited. This paper reviews the design of H ELPeR, a patient-focused interactive recommender system for ovarian cancer ( O vCa) patients and caregivers. It has a dual goal: to present an example of an interactive recommender system in a health domain and to demonstrate a case of user-centered design of a recommender system in this challenging domain. The design of H ELPeR was informed by foundational studies of patients and caregivers and collaboration with health experts to understand the user base and their needs. Foundational studies revealed how users transition from seeking information to sharing advice, leading to a dual-mode system that provides recommendations for novice users and search functionality for experienced users. Health experts provided insights into challenges such as trajectory misalignment, multi-topic complexity, and contextual mismatches, guiding refinements to both interaction design and recommendation algorithms. The iterative design process resulted in a system that dynamically adapts to user trajectories and supports diverse user preferences through a multi-topic carousel and search interface. The evaluation demonstrated H ELPeR’s positive usability and performance outcomes, highlighting its ability to address the evolving needs of O vCa patients and caregivers.

PURPOSE: Chemotherapy can cause symptoms that impair quality of life and lead to unplanned health care encounters (UHEs) such as emergency department visits and inpatient admissions. Collecting patient-reported symptom data between clinic visits can enable timely identification of symptoms. This observational study aimed to identify how daily individual symptoms are associated with UHE. METHODS: We recruited patients (n = 183) receiving cytotoxic chemotherapy for solid tumors into our 90-day study. Participants completed a modified version of the patient-reported outcome-Common Terminology Criteria for Adverse Events questionnaire assessing common chemotherapy symptoms daily, and UHE information was extracted from medical records. We fit a series of logistic generalized estimating equations to evaluate day-level associations between moderate-to-severe daily symptoms and the occurrence of UHE within 7 days. RESULTS: On days with moderate-to-severe symptom levels, the odds of having one or more UHE within 7 days were 4.53 times higher for vomiting (95% CI, 1.77 to 11.58; P = .002), 2.84 times higher for decreased appetite (95% CI, 1.94 to 4.17; P < .001), 2.5 times higher for shortness of breath (95% CI, 1.44 to 4.34; P = .001), 1.76 times higher for diarrhea (95% CI, 1.11 to 2.79; P = .02), 1.65 times higher for fatigue (95% CI, 1.20 to 2.26; P = .002), and 1.58 times higher for pain (95% CI, 1.01 to 2.48; P = .04) relative to days with no-to-mild levels of that symptom. After adjusting for days since study enrollment, the odds of UHE were 2.17 times higher on days with moderate-to-severe pain in the abdomen (95% CI, 1.31 to 3.58; P = .003). The odds of UHE within 7 days also increased significantly as the number of moderate-to-severe symptoms increased ( P < .001). CONCLUSION: Specific daily symptoms were associated with increased risk of subsequent UHE during chemotherapy. Interventional studies are needed to better understand whether daily remote monitoring of these symptoms can reduce UHE.

Background: Wearable devices are becoming more ubiquitous and are capable of capturing health-relevant information that patients may be interested in sharing with their providers. However, limited research has been conducted on oncology provider perspectives on how these data could be used to inform cancer care. Objective: The goal of this study was to understand oncology clinicians’ preferences about which data would be most clinically valuable and in what clinical scenarios, the benefits and barriers to integrating wearable device data into cancer care, and perspectives on how wearable device data could impact decision-making using 3 clinical vignettes. Methods: A total of 13 oncology care clinicians completed an online questionnaire to assess the perceived value of different types of wearable device data in different clinical scenarios and participated in semistructured interviews to gather preferences around integrating these data into clinical workflows. During the interviews, providers were also presented with 3 clinical vignettes and asked for clinical recommendations both before and after seeing the patient’s wearable device data. Descriptive statistics were calculated to summarize quantitative data from questionnaires and structured interview questions, and interviews were transcribed and coded using an iterative thematic analysis approach. Results: Survey responses indicated that providers were most interested in tracking vital sign metrics, followed by data related to falls and functioning, and then by data on sleep and activity. Clinicians thought that wearable device data might be especially useful for remotely monitoring patients at high-risk moments in their care trajectory, such as after an acute hospitalization or after starting a new outpatient treatment. Four main themes were discussed by providers in the interviews: (1) corroborating reports, (2) identifying new issues, (3) coordinating care, and (4) patient-provider communication. Although there were no statistically significant differences in clinical recommendations before and after viewing wearable device data for any vignette (all P >.25), all clinicians reported that the wearable device data impacted their decision-making confidence, and most rated the wearable device data as helpful. Conclusions: Oncology providers highlighted the potential clinical value of vital sign and physical functioning data from wearable devices, particularly when outpatients might be at risk for readmissions or other acute deteriorations between clinic visits. Providers noted that the objective data captured by consumer wearable devices can be helpful complements to patient and caregiver subjective reports and that this information could improve patient-provider communication and care coordination. During the interviews, most providers found wearable device data to be helpful when making decisions. While there are challenges to address on how to integrate this information into the clinical workflow and communicate alerts with patients, there is cautious enthusiasm among clinicians about how these data could inform and improve cancer care.

BACKGROUND Providing care to a family member or friend with a serious illness like cancer increases risk for poor physical, psychological, and functional health outcomes. Despite their critical role, family caregivers (FCGs) are rarely screened in clinical settings for the wide range of factors that may put them and the person they care for at risk for poor outcomes. Mobile health (mHealth) applications can efficiently facilitate access to high-quality health information for FCGs; however, few are clinically integrated. OBJECTIVE This study aimed to evaluate the usability of CareCheck, an mHealth-based digital risk screening tool designed to enable family caregivers' self-awareness of potential caregiving-related risks for adverse health and psychosocial outcomes and to support health care professionals in personalizing interventions that address FCGs' specific risk factors. METHODS We conducted a usability testing study of CareCheck using two evaluation methods: quantitative measurement with a modified 5-item Mobile Health App Usability Questionnaire (MAUQ) and exploratory qualitative thematic analysis based on feedback from FCGs and trained staff. FCGs of individuals with gynecologic cancer were recruited through the inpatient unit and the outpatient gynecologic oncology clinic of a Comprehensive Cancer Center. Participants completed CareCheck and the usability questionnaire via the mHealth app installed on tablets. Staff observed the assessment process and provided feedback. RESULTS A total of 56 CGs and 2 trained staff participated in the usability study. The mean MAUQ score was 6.49 (SD = 1.06) out of 7, indicating high usability. Qualitative analysis identified recommendations in three categories: 1) Improvements to CareCheck ; 2) Perceptions of CareCheck’s Usability and Functionality, and 3) Clinical Implementation Considerations for CareCheck. CONCLUSIONS FCGs and staff found CareCheck to be user-friendly and easy to navigate. While further iterations are needed to refine content and optimize integration with clinical workflows, CareCheck demonstrated potential as a clinically integrated tool for identifying and addressing FCG risk for poor social, psychological, or health outcomes in gynecologic oncology care settings.

Introduction: Family caregivers frequently experience sleep challenges that impact their own health and ability to provide care for a care recipient (i.e., the person a caregiver supports). Cognitive-behavioral therapy for insomnia (CBT-I) effectively treats insomnia, but there is limited evidence regarding caregivers’ perceived impacts of this intervention. The current study evaluated caregivers’ experiences using Sleep Healthy Using The Internet (SHUTi), an Internet-delivered CBT-I intervention. Method: The sample comprised caregivers with insomnia who supported care recipients requiring medium- or high-intensity care for any condition, including Alzheimer’s disease/dementia (21%), cancer (11%), or a mobility problem (11%). Participating caregivers who used SHUTi ( n = 82; age M = 53.20, 85% female, 59% lived with the care recipient) provided open-ended feedback about their experience. Responses were analyzed using a rapid content analysis approach. Results: Responses revealed that caregivers perceived benefits of SHUTi to their functioning and their understanding of sleep . Caregivers described how the intervention improved their overall daytime abilities, mood, and caregiving capacity. They also shared how the intervention helped them prioritize sleep and self-care, gave them insight into their sleep, and increased their knowledge of healthy sleep. Discussion: Caregivers reported wide-ranging benefits from CBT-I beyond improved sleep. Despite the untailored nature of this intervention, several caregivers described positive impacts on their caregiving capabilities and outlook, resulting from the program helping them to improve their sleep and self-care more broadly. These results suggest that framing caregiver-focused health interventions as important to both caregivers and care recipients may increase caregivers’ uptake of such resources.

BACKGROUND Wearable devices are becoming more ubiquitous and are capable of capturing health-relevant information that patients may be interested in sharing with their providers. However, limited research has been conducted on oncology provider perspectives on how this data could be used to inform cancer care. OBJECTIVE The goal of this study was to understand oncology clinicians’ preferences about which data would be most clinically valuable and in what clinical scenarios, benefits and barriers to integrating wearable device data into cancer care, and perspectives about how wearable device data could impact decision-making using three clinical vignettes. METHODS A total of 13 oncology care clinicians completed an online questionnaire to assess the perceived value of different types of wearable device data in different clinical scenarios and participated in semi-structured interviews to gather preferences around integrating these data into clinical workflows. During the interviews, providers were also presented with three clinical vignettes and asked for clinical recommendations before and after seeing the patient’s wearable device data. Descriptive statistics were calculated to summarize quantitative data from questionnaires and structured interview questions, and interviews were transcribed and coded using an iterative thematic analysis approach. RESULTS Survey responses indicated providers were most interested in tracking vital sign metrics, followed by data related to falls and functioning and then by data on sleep and activity. Clinicians thought that wearable device data might be especially useful for remotely monitoring patients at high-risk moments in their care trajectory, such as after an acute hospitalization or after starting a new outpatient treatment. Four main themes were discussed by providers in the interviews: (1) corroborating reports, (2) identifying new issues, (3) coordinating care, and (4) patient-provider communication. Although there were no statistically significant differences in clinical recommendations before and after viewing wearable device data for any vignette (all p > 0.25), most clinicians reported that the wearable device data impacted their decision-making confidence and rated the wearable device data as helpful. CONCLUSIONS Oncology providers highlighted the potential clinical value of vital sign and physical functioning data from wearable devices, particularly when outpatients might be at risk for readmissions or other acute deteriorations between clinic visits. Providers noted that the objective data captured by consumer wearable devices can be helpful complements to patient and caregiver subjective reports and that this information could improve patient-provider communication and care coordination. During the interviews, most providers found wearable device data to be helpful when making decisions. While there are challenges to address on how to integrate this information in the clinical workflow and communicate alerts with patients, there is cautious enthusiasm among clinicians about how these data could inform and improve cancer care.

PURPOSE: Consumer wearable devices provide new opportunities for measuring patterns of objective daily physical activity throughout cancer treatment. In addition to capturing step counts, these devices can also measure gait cadence and activity fragmentation, two metrics that may reflect functional capacity. The goal of the current study was to examine whether step count, gait cadence, and activity fragmentation predicted overall survival in patients with solid tumors. METHODS: We enrolled patients (N = 213) receiving outpatient chemotherapy for any solid tumor into an observational cohort study. Patients wore a consumer wearable device to measure continuous physical activity patterns for up to 90 days and were followed for a median of 2.53 years, during which 42% of the sample died. Univariable and multivariable Cox proportional hazards regression analyses were used to evaluate associations between wearable device physical function metrics and survival. RESULTS: In univariable analyses, higher step count (hazard ratio (HR), 0.87; P = .007), less activity fragmentation (HR, 1.03; P < .001), and faster peak gait cadence (HR, 0.81; P < .001) were significantly associated with lower mortality risk. Associations with activity fragmentation and gait cadence persisted after adjustment for age and cancer type and stage and after additional adjustment for clinician-rated performance status and patient-reported physical function. CONCLUSION: Activity fragmentation and gait cadence metrics derived from consumer wearable devices were associated with overall survival in patients receiving chemotherapy for any solid tumor. These associations remained statistically significant after adjustment for covariates, including clinician-rated performance status and patient-reported physical function. These findings suggest that wearable devices may capture important prognostic information about physical function independent of what clinicians and patients perceive.

PURPOSE: Family caregivers (CGs) of individuals with cancer are increasingly relied upon to provide long-term, sometimes intense care, although their integration into clinical cancer care remains minimal. The Caregiver Advocacy, Research, and Education (CARE) Center is a novel nurse-led academic-clinical partnership to support family CGs of individuals with gynecologic cancer. This study aims to describe the implementation of the Center protocols and report metrics of CG needs and Center support. MATERIALS AND METHODS: The Center's goals are to identify, assess, and provide tailored support to CGs. Initially, Center protocols included assessment of CGs' self-identified distress (distress thermometer, 0 = no distress to 10 = extreme distress) and needs (yes or no). Tailored support on the basis of CG distress was provided by in-person and remote staff who provided complementary, concurrent support based on CG need: evidence-based self-management guides, self-management support, referral to specialty services. Center documentation was analyzed to describe Center reach and CG distress. RESULTS: From November 2019 to June 2023, CGs (N = 1,250) were identified through referrals, new patient outreach, and inpatient visits. Seven hundred and six CGs (56.5%) were assessed through a needs-based assessment, and 515 (41.2%) CGs received tailored support. CGs were mostly men (53.0%) and the mean distress was 4.4/10 (standard deviation, 3.1). CG distress was moderately associated with CG needs including maintaining emotional (ρ = 0.40; P < .001) and physical (ρ = 0.31; P < .001) health and managing patient symptoms (ρ = 0.33; P < .001). CONCLUSION: Center protocols facilitate identification of high-need CGs within a cancer clinic. Future research will longitudinally evaluate the impact of Center protocols on CG and patient outcomes, incorporating updated assessment tools.