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Background <p>The integrated screening action model (I-SAM) posits sources of automatic motivation (e.g., affect-based feeling states like worry, distress) are important predictors of cancer screening engagement. Yet no prior studies demonstrate how these feeling states change across survivorship and relate to screening behavior. This study tested the feasibility and acceptability of collecting longitudinal data on affect-based feeling states among rural breast cancer survivors using a smartphone-based ecological momentary assessment (EMA) platform.</p> Methods <p>The study recruited survivors of stage 0–3 breast cancer who recently completed breast cancer treatment at a large, rural academic cancer center. Participants received each of three, 30-day EMA assessment schedules of varied intensity in a randomly assigned order via smartphone app. Participants received 12–18 notification-contingent EMAs each month and were asked to complete an event-contingent EMA each day they attended a medical appointment. Feasibility measures included study recruitment, enrollment, and retention rates. We assessed EMA completion rates and acceptability scores for each schedule and concordance of event-contingent EMAs with verified medical encounters.</p> Results <p>Mean age of the 65 enrolled participants was 59&#xa0;years (range: 36–77). Participants were majority white, non-Hispanic, and 65% lived in a rural area. Fifty-two participants were retained at 3-months. Mean EMA completion rates were 73.7%, 71.7%, 71.7% for the low, medium, and high intensity EMA schedules, respectively. Event-contingent EMA concordance was 53.2%. All schedules achieved a priori benchmarks for acceptability.</p> Conclusions <p>It was feasible to recruit and retain rural breast cancer survivors for this research and acceptability ratings were strong for the three EMA sampling intensities evaluated.</p>

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Use of Ecological Momentary Assessment to Measure Affect-Based Feeling States Among Rural Breast Cancer Survivors: A Feasibility Study Guided by the Integrated Screening Action Model

  • 期刊论文

  • 发表日期：

    2025年10月27日

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  • Mia St. Angelo,
  • Courtney J. Stevens,
  • Laura B. Beidler,
  • Jennifer A. Emond,
  • Anna N. A. Tosteson,
  • Christine M. Gunn

摘要

Background

The integrated screening action model (I-SAM) posits sources of automatic motivation (e.g., affect-based feeling states like worry, distress) are important predictors of cancer screening engagement. Yet no prior studies demonstrate how these feeling states change across survivorship and relate to screening behavior. This study tested the feasibility and acceptability of collecting longitudinal data on affect-based feeling states among rural breast cancer survivors using a smartphone-based ecological momentary assessment (EMA) platform.

Methods

The study recruited survivors of stage 0–3 breast cancer who recently completed breast cancer treatment at a large, rural academic cancer center. Participants received each of three, 30-day EMA assessment schedules of varied intensity in a randomly assigned order via smartphone app. Participants received 12–18 notification-contingent EMAs each month and were asked to complete an event-contingent EMA each day they attended a medical appointment. Feasibility measures included study recruitment, enrollment, and retention rates. We assessed EMA completion rates and acceptability scores for each schedule and concordance of event-contingent EMAs with verified medical encounters.

Results

Mean age of the 65 enrolled participants was 59 years (range: 36–77). Participants were majority white, non-Hispanic, and 65% lived in a rural area. Fifty-two participants were retained at 3-months. Mean EMA completion rates were 73.7%, 71.7%, 71.7% for the low, medium, and high intensity EMA schedules, respectively. Event-contingent EMA concordance was 53.2%. All schedules achieved a priori benchmarks for acceptability.

Conclusions

It was feasible to recruit and retain rural breast cancer survivors for this research and acceptability ratings were strong for the three EMA sampling intensities evaluated.