Journal SINTA 1
Causal Modeling Between Factors on Quality of Life in Cancer Patients Using S3C-Latent Algorithm
Journal of Information Systems Engineering and Business Intelligence · Vol. 7 No. 1 (2021) · pp. 74–83
- ISSN
- 2443-2555, 2598-6333
- Published
- 2021-04-27
- Publisher
- Universitas Airlangga
- Language
- eng
Abstract
Background: Cancer patients can experience both physical and non-physical problems such as psychosocial, spiritual, and emotional problems, which impact the quality of life. Previous studies on quality of life mostly have employed multivariate analyses. To our knowledge, no studies have focused yet on the underlying causal relationship between factors representing the quality of life of cancer patients, which is very important when attempting to improve the quality of life. Objective: The study aims to model the causal relationships between the factors that represent cancer and quality of life.Methods: This study uses the S3C-Latent method to estimate the causal model relationships between the factors. The S3C-Latent method combines Structural Equation Model (SEM), a multi objective optimization method, and the stability selection approach, to estimate a stable and parsimonious causal model.Results: There are nine causal relations that have been found, i.e., from physical to global health with a reliability score of 0.73, to performance status with a reliability score of 1, from emotional to global health with a reliability score of 0.71, to performance status with a reliability score of 0.82, from nausea, loss of appetite, dyspnea, insomnia, loss of appetite and from constipation to performance status with reliability scores of 0.76; 1; 0.61; 0.76; 0.72; 0.70, respectively. Moreover, this study found that 15 associations (strong relation where the causal direction cannot be determined from the data alone) between factors with reliability scores range from 0.65 to 1.Conclusion: The estimated model is consistent with the results shown in previous studies. The model is expected to provide evidence-based recommendation for health care providers in designing strategies to increase cancer patients' life quality. For future research, we suggest studies to include more variables in the model to capture a broader view to the problem.
Collaboration network of the authors
17 authors · 32 co-authorship links · 12 across different organisations
Hover or tap a name to highlight its co-authors. Double-click to open the author's page.
- Institut Teknologi Telkom Purwokerto
- Islamic University of Indonesia
- Universitas Gadjah Mada
- Hasanuddin University
- University of Nigeria
- Affiliation unknown
- Different organisations
- Same organisation
- Affiliation unknown
- Thicker line = more joint articles · bigger circle = more articles
Show as table
| Co-author | Organisation | Joint articles |
|---|---|---|
| Nur Chayati | Affiliation unknown | 2 |
| Ismail Setyopranoto | Affiliation unknown | 2 |
| Yuan Sa'adati | Islamic University of Indonesia | 2 |
| Rizki Surtiyan Surya | Islamic University of Indonesia | 2 |
| Siti Khomsah | Institut Teknologi Telkom Purwokerto | 1 |
| Mohammad Teddy Syamkalla | Institut Teknologi Telkom Purwokerto | 1 |
| Andina Setyawati | Hasanuddin University | 1 |
| Mae Sri Hartati Wahyuningsih | Universitas Gadjah Mada | 1 |
| Dwi Aris Agung Nugrahaningsih | Universitas Gadjah Mada | 1 |
| Sam Chidi Ibeneme | University of Nigeria | 1 |
| Nyoman Sri Subawa | Affiliation unknown | 1 |
| Marselus Yansen | Affiliation unknown | 1 |
| Anak Agung Made Wirajaya | Affiliation unknown | 1 |
| AKICHIKA MIKAMI | Affiliation unknown | 1 |
Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.