ArticleJournal of cancer survivorship : research and practice2025
Effectiveness of a mobile-based return to work program for decent return to work, fatigue, stress, and quality of working life among cancer survivors.
Article in Journal of cancer survivorship : research and practice, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Navigating work after prostate cancer treatment: a systematic review of qualitative research.Journal of cancer survivorship : research and practice · 2026Review
- Returning to work in the digital age: why smartphone interventions must go further.NPJ digital medicine · 2025Article
- Research hotspots and trends in cancer rehabilitation: a bibliometric analysis (2013-2023).Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
purposeThis study aimed to develop a smartphone mobile application-based supportive return to work (RTW) program for cancer survivors and evaluate its effects on their RTW, fatigue, stress, and quality of working life. This program was developed through a comprehensive process involving literature review, interviews with cancer survivors, and consultations with experts.
methodsA non-equivalent control group pre- and post-test design was used, with 41 participants assigned to the experimental (n = 18) and control (n = 23) groups based on recruitment timing. The experimental group received a 6-week smartphone mobile application-based supportive RTW program comprising "Counseling and Education" and "Self-Management." Participants completed assessments of decent RTW, fatigue, stress, and quality of working life at baseline and 6 months later. The experimental group completed an additional post-program completion survey.
resultsDuring the 6-week program, no experimental group participants dropped out. The program's impact on decent RTW remains unclear. Fatigue (F = 2.52, p = 0.095) and quality of working life (F = 0.86, p = 0.434) did not show statistically significant differences. However, there was a significant reduction in stress (F = 4.59, p = 0.017).
conclusionThe smartphone application-based RTW program, focusing on self-management and counseling, effectively reduced participants' stress levels. To further evaluate the effectiveness of the program, a more diverse range of interventions and ongoing programs should be implemented. IMPLICATIONS FOR CANCER SURVIVORS: This study underscores the importance of tailored digital interventions to support the RTW of cancer survivors. The use of mobile smartphone applications allows temporal and spatial flexibility in program participation. Interventions involving various activities should be implemented to ensure ongoing participation.
Indexed as
Identifiers
38769245What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.