Beating cancer-related fatigue with the Untire mobile app: Results from a waiting-list randomized controlled trial

Abstract

Objective: This waiting-list randomized controlled trial examined the effectiveness of a self-management mHealth app in improving fatigue and quality of life (QoL) in cancer patients and survivors.

Methods: Persons with cancer-related fatigue (CRF) were recruited across four English speaking countries, via social media, and randomized into intervention (n = 519) and control (n = 280) groups. Whereas the intervention group received immediate access to the Untire app, the control group received access only after 12-weeks. Primary outcomes fatigue severity and interference, and secondary outcome QoL were assessed at baseline, 4, 8, and 12-weeks. We ran generalized linear mixed models for all outcomes to determine the effects of app access (yes/no), over 12-weeks, following the intention-to-treat principle.

Results: Compared with the control group, the intervention group showed significantly larger improvements in fatigue severity (d = 0.40), fatigue interference (d = 0.35), and overall QoL on average (d = 0.32) (P's < .01), but not for overall QoL in the past week (P = .07). Sensitivity analyses indicated that participants with medium or high app use benefited most when compared with nonusers and control participants (P's ≤ .02). The intervention effect on fatigue interference was slightly stronger in younger participants (≤56 vs. >56). Effects did not depend on education and cancer status. Reliable change analyses indicated that significantly more people showed full recovery for fatigue in the intervention vs the control group (P's = .02).

Conclusions: The Untire app can be an effective mHealth solution for cancer patients and survivors with moderate to severe CRF.

Keywords: RCT; app; cancer; cancer survivors; fatigue; mHealth; oncology; palliative care; psycho‐oncology; quality of life; self‐management.

FIGURE 1

Participant flow (CONSORT diagram) in the Untire app study. The figure presents the FSI at T0 and at T12, the number of completed assessments, and the number of participants who underwent the intervention (i.e., activated the app)

FIGURE 2

Change in levels of fatigue severity, A and in fatigue interference, B, over time and between conditions. Sensitivity analyses for fatigue severity, C and fatigue interference, D, based on four groups of app use (high, medium, low, nonusers' participants) and waiting‐list control participants. Change in overall QoL during the past week, E, and change in overall QoL on average over time and between conditions, F. Error bars present the 95% confidence interval. QoL, quality of life