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Abstract：
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.
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.
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).
The Untire app can be an effective mHealth solution for cancer patients and survivors with moderate to severe CRF.
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.
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).
The Untire app can be an effective mHealth solution for cancer patients and survivors with moderate to severe CRF.
摘要：
这项等待名单的随机对照试验研究了自我管理的mHealth应用程序在改善癌症患者和幸存者的疲劳和生活质量（QoL）方面的有效性。
癌症相关性疲劳（CRF）患者被招募到四个英语国家，通过社交媒体,并随机分为干预组(n=519)和对照组(n=280)。而干预组立即获得了对Untire应用程序的访问权限，对照组仅在12周后接受访问.主要结果疲劳严重程度和干扰，和次要结局QoL在基线评估，4、8和12周。我们对所有结果运行广义线性混合模型，以确定应用程序访问的效果(是/否)，超过12周,遵循意向治疗原则。
与对照组相比，干预组显着改善了疲劳严重程度（d=0.40），疲劳干涉(d=0.35)，和总体生活质量平均(d=0.32)(P's<0.01)，但不是过去一周的整体QoL（P=.07）。敏感性分析表明，与非使用者和对照参与者相比，中等或高应用使用率的参与者受益最大（P's≤.02）。年轻参与者对疲劳干扰的干预效果稍强(≤56vs.>56)。效果并不取决于教育和癌症状况。可靠的变化分析表明，干预组与对照组相比，有更多的人表现出完全恢复的疲劳（Ps=.02）。
Untire应用程序可以成为癌症患者和患有中度至重度CRF的幸存者的有效mHealth解决方案。
癌症相关性疲劳（CRF）患者被招募到四个英语国家，通过社交媒体,并随机分为干预组(n=519)和对照组(n=280)。而干预组立即获得了对Untire应用程序的访问权限，对照组仅在12周后接受访问.主要结果疲劳严重程度和干扰，和次要结局QoL在基线评估，4、8和12周。我们对所有结果运行广义线性混合模型，以确定应用程序访问的效果(是/否)，超过12周,遵循意向治疗原则。
与对照组相比，干预组显着改善了疲劳严重程度（d=0.40），疲劳干涉(d=0.35)，和总体生活质量平均(d=0.32)(P's<0.01)，但不是过去一周的整体QoL（P=.07）。敏感性分析表明，与非使用者和对照参与者相比，中等或高应用使用率的参与者受益最大（P's≤.02）。年轻参与者对疲劳干扰的干预效果稍强(≤56vs.>56)。效果并不取决于教育和癌症状况。可靠的变化分析表明，干预组与对照组相比，有更多的人表现出完全恢复的疲劳（Ps=.02）。
Untire应用程序可以成为癌症患者和患有中度至重度CRF的幸存者的有效mHealth解决方案。
