FoRSHE-X digital health intervention to improve the quality of life during chemotherapy among gynecological cancer survivors in Indonesia: A protocol for a pilot and feasibility study
Afiyanti, Y.; Juliastuti, D.; So, W. K. W.; Milanti, A.; Nasution, L. A.; Prawesti, A. D.
Show abstract
Most Indonesian gynecological cancer survivors have unmet supportive care needs during chemotherapy, which may lower their quality of life and discontinue the treatment. Digital health intervention can address this issue. This pilot investigation aims to (1) examine the feasibility and acceptability of a Fighting on distRess, Self-efficacy, Health Effects, and seXual issues (FoRSHE-X) intervention and (2) evaluate prospectively the impact of the study implementation on the level of distress, self-efficacy, side effects knowledge and management, and sexual quality of life using the RE-AIM (Reach Effectiveness, Adoption, Implementation, and Maintenance) framework. This is a non-randomized pilot and feasibility study. We will recruit women diagnosed with gynecological cancer undergoing chemotherapy to participate in the FoRSHE-X intervention consisting of ten weeks of social media-based education and telecoaching. We will evaluate the primary outcomes of study feasibility and acceptability, and the secondary outcomes of study impacts at three time points with quantitative and qualitative inquiries. We anticipate a minimum of 30 participants to enroll in the study and complete the assessment. We will disseminate results through conferences and peer-reviewed scientific journals. This study will imply whether a definitive trial to evaluate the potential benefits of the FoRSHE-X is viable and how it should proceed. The protocol can aid researchers or nurses in implementing this approach in their study or practice.
Matching journals
The top 1 journal accounts for 50% of the predicted probability mass.
Similar papers in this journal
- Evaluating the effectiveness of mindfulness alone compared to exercise and mindfulness on fatigue in women with gynaecology cancer (GEMS): Protocol for a randomised feasibility trial 96%
- Experiences of cervical cancer survivors in Chitwan, Nepal: a qualitative study 96%
- Effectiveness of integrating cervical cancer prevention strategies into HIV care programmes: A mixed-methods systematic review protocol 96%
Similar papers in this journal
- Palliative care in the treatment of women with breast cancer: a scoping review protocol 95%
- Family physicians supporting patients with palliative care needs within the Patient Medical Home in the community: An Appreciative Inquiry qualitative study 94%
- Challenges and facilitators in pathways to cancer diagnosis in Southern Africa: A qualitative study 94%
Similar papers in this journal
- The Impact of Fasting the Holy Month of Ramadan on Colorectal Cancer Patients and Two Tumor Biomarkers: A Tertiary-Care Hospital Experience 94%
- Impact of mHealth interventions on antenatal and postnatal care utilization in low and middle-income countries: A Systematic Review and Meta-Analysis 94%
- Evaluation of Self-Directed Learning Activities at King Abdulaziz University: A Qualitative Study of Faculty Perceptions 93%
Similar papers in this journal
- The Impact for implementing Balanced Scorecard in Health Care Organizations: A Systematic Review 93%
- Assessing Language Difficulties in Health Facilities in Malawi 93%
- A Systematic Review: The Dimensions and Indicators utilized in the Performance Evaluation of Health Care Organizations- An Implication during COVID-19 Pandemic 93%
Similar papers in this journal
- Effectiveness of educational intervention on breast cancer knowledge and breast self-examination among female university students in Bangladesh: a pre-post quasi-experimental one group study 95%
- Risk-Reducing Salpingectomy: Considerations from an OBGYN Perspective 93%
- Assessing awareness of blood cancer symptoms and barriers to symptomatic presentation: Measure development and results from a population survey in the UK 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.