METHODS: in this study, a fixed retrospective cohort design has been conducted by using data from the Indonesia Family Life Survey (IFLS) in 2007 and 2014. A total of 6,863 respondents who were not diagnosed with NCD by medical personnel in 2007 were successfully traced. After being controlled for covariates, the association between NCD type and poor physical function was measured by using the Adjusted Risk Ratio (ARR) and Population Attributable Risk (PAR).
RESULTS: respondents with poor physical function were at a significantly increased of being diagnosed with stroke (ARR: 6.9, 95%CI: 4.3-10.9), diabetes (ARR: 3.1, 95%CI: 2.4-4.1), or heart disease (ARR: 3.2, 95%CI: 2.4-4.5). The PAR score of respondents with diabetes was 0.006, meaning 0.6% of diabetes cases are attributed to poor physical function and can therefore be prevented if people maintain good physical function.
CONCLUSION: poor physical function can be assessed to identify risk of diabetes, heart disease, and stroke. Healthcare personnel should provide education programs that inform patients on the importance of maintaining a healthy physical ability.
METHODS: In a graph, to obtain the exact location of a required vertex, which is unique from all the vertices, several vertices are selected; this is called resolving set, and its generalization is called resolving partition, where selected vertices are in the form of subsets. A minimum number of partitions of the vertices into sets is called partition dimension.
RESULTS: It was proved that determining the partition dimension of a graph is a nondeterministic polynomial time (NP) problem. In this article, we find the partition dimension of convex polytopes and provide their bounds.
CONCLUSION: The major contribution of this article is that due to the complexity of computing the exact partition dimension, we provide the bounds and show that all the graphs discussed in the results have partition dimensions either less or equals to 4, but not greater than 4.
OBJECTIVE: Our main objective is to study the pre-effects and posteffects of the Personalized Mobile Mental Health Intervention (PMMH-I) for workplace cyberbullying in public and private hospitals in Malaysia.
METHODS: A hospital-based multimethod multi-analytic evidential approach is proposed, involving social and psychological health informatics. The project has been subdivided into 3 stages, starting with Phase 1, a prevalence study, followed by exploratory studies. Phase 2 consists of a quasi-experimental design, whereas the development of a prototype and their testing will be proposed in Phase 3. Each stage includes the use of quantitative and qualitative methods (mixed-method program), using SPSS (version 26.0; IBM Corp) and Stata (version 16.1; StataCorp) as tools for quantitative research, and NVivo (version 1.0; QSR International) and Atlas.ti (version 9.0.16; ATLAS.ti Scientific Software Development GmbH) for qualitative research.
RESULTS: The results of this study will determine the pre- and posteffectiveness of an integrated PMMH-I for health care professionals. The prototype system platform will be developed and implemented in a public and private hospital. Results from Phase 1 will be published in 2021, followed by the implementation of Phase 2 in subsequent years.
CONCLUSIONS: This study will provide evidence and guidance regarding the implementation of a personalized mobile mental health intervention for health care professionals into routine public and private hospitals to enhance communication and resolve conflicts.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/23112.