Losses in electrical power systems

Chen, Mo-Shing; Ohba, Yasuo; Reynolds, Lindian; Dickson, W.Donald

doi:10.1016/0378-7796(77)90004-9

Cited by 8 publications

(1 citation statement)

References 12 publications

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“…G*Power 3.1 was used to determine the most appropriate sample size based on F-test linear multiple regression modeling [ 33 ]. To estimate sample size for the R² deviation from zero, we used the following settings: effect size f 2 = 0.15, α err prob = 0.05, power (1 − β err prob) = 0.95, and number of measures = 5.…”

Section: Methodsmentioning

confidence: 99%

Relation of environmental factors with activity limitations and participation restrictions in older adults with diabetes mellitus over time: an international classification of functioning framework perspective

Tsai

Chiu

2023

BMC Geriatr

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Background Activity limitations and participation restrictions were observed in patients with diabetes, which may impact their quality of life. Environmental factors such as seasonal effects, resources and perceived stress may play important role in activity limitations and participation restrictions. In this study, a variant of International Classification of Functioning (ICF) model was used to clarify the associations of function/structure factors, personal factors and environmental factors with activity limitations and participation restrictions. Methods This was a longitudinal design with 1 year follow-up. The Mini-Mental State Examination (MMSE), Geriatric Depression Scale- short form, Perceived Stress Scale, and Instrumental Activities of Daily Living assessments were measured at 3-month intervals for long-term follow-up in 110 patients with diabetes aged ≥ 65 years. Results Hierarchical linear regression models revealed that age (p = 0.001), perceived health status, MMSE scores (p < 0.01), and positive perceived stress (p < 0.001) were predictors of activity limitations (adjusted R2 = 53%). GDS-S (p < 0.05) and positive perceived stress (p < 0.01) were predictors of participation restrictions (adjusted R2 = 30%). Generalized estimating equation analysis indicated that seasonal effects, age, perceived health status, MMSE predicted the changes of slopes in activity limitations. Seasonal effects and GDS-S were predictors of the changes of slopes for participation restrictions (all p < 0.001). Conclusions The ICF can be used to identify the risk factors for activity limitations and participation restrictions in older adults with diabetes. Practitioners should provide individualized interventions with consideration of these risk factors.

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Section: Methodsmentioning

confidence: 99%