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31st Dec, 2025 12:00 AM
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What’s the Time Burden of Women’s Cancers-Related Tasks?

TOPLINE:

A smartphone app-based study found that patients with advanced ovarian or metastatic breast cancer spent approximately 7 hours weekly on cancer-related tasks and averaged 4.2 out-of-home cancer-related care episodes over 28 days. At-home tasks accounted for a median of 209 minutes (3.5 hours) per week, and the median travel time per out-of-home episode was 35 minutes, with time spent traveling and waiting for care often exceeding time spent receiving care.

METHODOLOGY:

  • Patients with cancer often face nonmedical time burdens (including travel, waiting, scheduling, and home care) that are poorly captured in medical records. This study used a validated smartphone app to determine daily time demands among patients with advanced cancer who are at a high risk for substantial time burdens.
  • This longitudinal cohort study included 60 adults (median age, 59 years) with metastatic breast or advanced-stage ovarian cancer who received systemic therapy and were recruited at the University of Minnesota and University of Alabama at Birmingham between December 2023 and September 2024.
  • Participants used a mobile app called Daynamica to track time use for 28 days, with the app using Global Positioning System and phone sensor data to automatically infer location and activity type.
  • Researchers included participants with sufficient app engagement (7 or more days) who completed baseline and follow-up surveys while tracking facility-based cancer care episodes and nonfacility-based cancer care activities via daily app-based surveys.
  • Overall, 28% received initial treatment, 15% received maintenance treatment, and 57% received therapy for recurrence or progression.

TAKEAWAY:

  • Overall, patients spent a median of 400 minutes (6.7 hours) per week on cancer-related tasks. Participants reported a mean of 4.2 out-of-home cancer-related care episodes over 28 days, with treatment (36%), clinic visits (30%), and laboratories (31%) being the most common episode types.
  • Regarding facility visits, 44% had wait times under 15 minutes, 19% had no wait time, and 14% experienced waits exceeding 60 minutes, with a median travel time of 35 minutes per episode.
  • At-home cancer-related tasks accounted for a median of 209 minutes (3.5 hours) per week, with participants engaging in at least one task on 80% of study days. Activities included taking medication, scheduling appointments, handling medical bills, managing symptoms, monitoring health status, seeking information about cancer, and arranging help or transportation.
  • More than one third of participants (35%) reported that cancer-related tasks disrupted their daily activities, including self-care, chores, work, or socializing on more than half of their days.

IN PRACTICE:

“Future work should refine time burden measures by understanding how participants report each care component,” the authors write. “Next steps include examining demographic and clinical factors linked to time burdens and quantifying their impact on patient and caregiver quality of life, employment, and financial outcomes, with the end goal of reducing time burden through patient-centered interventions.”

SOURCE:

The study, led by Rachel I. Vogel, PhD, University of Minnesota in Minneapolis, was published online December 16 in JAMA Network Open.

LIMITATIONS:

The study had several limitations, including its pilot design. The exclusion of non-English speakers and a sample restricted to women with advanced ovarian or metastatic breast cancer limited generalizability of the study findings. The 28-day monitoring window prevented assessment of time burden near diagnosis or over longer treatment periods. 

DISCLOSURES:

The study was supported by a National Cancer Institute grant from the National Institutes of Health. Some authors reported receiving grants from various sources. Two authors reported being cofounders of Daynamica, Inc. Full disclosures are noted in the original article.

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This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.


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