Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Defining Effective Engagement For Enhancing Cancer Patients' Well-being with Mobile Digital Behavior Change Interventions

Aneta Lisowska, Szymon Wilk, Laura Locati, Mimma Rizzo, Lucia Sacchi, Silvana Quaglini, Matteo Terzaghi, Valentina Tibollo, Mor Peleg

TL;DR

This paper addresses how to define and measure effective engagement with digital behavior change interventions (DBCIs) for cancer patients, focusing on small-scale, ethical studies. It builds a framework using micro- and macro-level engagement metrics, anchored by the CAPABLE mHealth platform and its capsule-based interventions. Empirical findings show that clinician prescriptions significantly boost engagement, and while weekly engagement supports well-being, shifting motivation from extrinsic to intrinsic may require higher engagement to sustain behavior change. The study provides methodological insights and predictive modeling results (via AutoML) that highlight baseline functioning and motivation as key predictors of QoL improvement, offering practical guidance for designing and evaluating DBCIs in similar contexts.

Abstract

Digital Behavior Change Interventions (DBCIs) are supporting development of new health behaviors. Evaluating their effectiveness is crucial for their improvement and understanding of success factors. However, comprehensive guidance for developers, particularly in small-scale studies with ethical constraints, is limited. Building on the CAPABLE project, this study aims to define effective engagement with DBCIs for supporting cancer patients in enhancing their quality of life. We identify metrics for measuring engagement, explore the interest of both patients and clinicians in DBCIs, and propose hypotheses for assessing the impact of DBCIs in such contexts. Our findings suggest that clinician prescriptions significantly increase sustained engagement with mobile DBCIs. In addition, while one weekly engagement with a DBCI is sufficient to maintain well-being, transitioning from extrinsic to intrinsic motivation may require a higher level of engagement.

Defining Effective Engagement For Enhancing Cancer Patients' Well-being with Mobile Digital Behavior Change Interventions

TL;DR

This paper addresses how to define and measure effective engagement with digital behavior change interventions (DBCIs) for cancer patients, focusing on small-scale, ethical studies. It builds a framework using micro- and macro-level engagement metrics, anchored by the CAPABLE mHealth platform and its capsule-based interventions. Empirical findings show that clinician prescriptions significantly boost engagement, and while weekly engagement supports well-being, shifting motivation from extrinsic to intrinsic may require higher engagement to sustain behavior change. The study provides methodological insights and predictive modeling results (via AutoML) that highlight baseline functioning and motivation as key predictors of QoL improvement, offering practical guidance for designing and evaluating DBCIs in similar contexts.

Abstract

Digital Behavior Change Interventions (DBCIs) are supporting development of new health behaviors. Evaluating their effectiveness is crucial for their improvement and understanding of success factors. However, comprehensive guidance for developers, particularly in small-scale studies with ethical constraints, is limited. Building on the CAPABLE project, this study aims to define effective engagement with DBCIs for supporting cancer patients in enhancing their quality of life. We identify metrics for measuring engagement, explore the interest of both patients and clinicians in DBCIs, and propose hypotheses for assessing the impact of DBCIs in such contexts. Our findings suggest that clinician prescriptions significantly increase sustained engagement with mobile DBCIs. In addition, while one weekly engagement with a DBCI is sufficient to maintain well-being, transitioning from extrinsic to intrinsic motivation may require a higher level of engagement.
Paper Structure (17 sections, 3 equations, 7 figures, 3 tables)

This paper contains 17 sections, 3 equations, 7 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Related Work
  3. The CAPABLE DBCI study
  4. Population
  5. Available DBCIs
  6. Engagement Measures
  7. Outcome Measures
  8. Data Collection and Storage
  9. A Methodology for Assessing the Effectiveness of DBCIs for a Small Study Population
  10. Capsule Prescription vs Autonomous Engagement
  11. Engagement with Capsules: the Impact of Prescription
  12. Association Between Capsule Engagement and Quality of Life Outcomes
  13. Micro- vs Macro-level engagement
  14. Predicting Intervention Outcome
  15. Discussion
  16. ...and 2 more sections

Figures (7)

  • Figure 1: Patient Demographic and Cancer Distribution
  • Figure 2: Enrolment QoL scores
  • Figure 3: Goals and capsules (general goals are located on the left, and specific goals are the right, PA = physical activity)
  • Figure 4: Capsules Statistic
  • Figure 5: Engagement with Walking Capsule. Patients prescribed the capsule are represented in red, while those who engaged with the capsule without a specific prescription from clinicians are shown in blue. For those prescribed the capsule, the recommended weekly dosage is indicated by a green dashed line.
  • ...and 2 more figures