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(https://web.archive.org/web/20230424122515/https:/dhpir.mak.ac.ug/sites/default/files/2023-04/DHPI-R-Research-Brief (https://web.archive.org/web/20240315044440/https:/dhpir.mak.ac.ug/sites/default/files/2023-03/DHPI-R%
JMIR Med Inform 2025;13:e65325
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Data analysis was performed using R (version 4.3.1; R Foundation for Statistical Computing) and R Studio software (version 2023.6.0.421; R Foundation for Statistical Computing). Actigraphy data were processed using the open-source AX3/AX6 OMGUI application and analyzed in R using the GGIR package [54]. Where available, sleep timing was adjusted using participants’ sleep diaries; otherwise, GGIR uses the heuristic algorithm looking at distribution of change in z-angle [55] to estimate sleep timing.
JMIR Aging 2025;8:e72824
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Given the small sample size and nature of this study, scores across various measures were descriptively analyzed using R software (version 4.3.1; R Foundation for Statistical Computing). Meanwhile, exit interview transcripts were coded line by line and examined using reflexive thematic analysis [42,43]. Following separate qualitative and quantitative analyses, the results were integrated, along with observations, for interpretation and extrapolation of developmental priorities for the VR-GMI program.
JMIR Res Protoc 2025;14:e68008
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