Purpose:The purpose of this study was to compare motivation for rehabilitation, family support and adherence to rehabilitation and identify factors predicting adherence to rehabilitation between depressive and non-depressive stroke patients. Methods: Stroke patients admitted to rehabilitation hospitals (n=159) participated in the study. Data were collected through self-reported questionnaires including general characteristics, depression, motivation for rehabilitation, family support and adherence to rehabilitation. The data were analyzed by descriptive statistics, t-test, x 2 test, Pearson correlation coefficients and logistic regression using the SPSS/WIN 21.0 program. Results: 62.9% of the subjects were identified as depressive patients. Motivation for rehabilitation (F=48.18, p=.020) and adherence to rehabilitation (F=9.68, p=.002) in depressive stroke patients were significantly lower than non-depressive stroke patients. Family support also in depressive group was lower than non-depressive group but there was no statistical significance (F=2.35, p=.127). Motivation for rehabilitation (OR=11.46), family support (OR=1.05) and onset period (less than 2 year)(OR=3.61) predicted the good adherence to rehabilitation in depressive stroke patients. Conclusion: The results of this study indicate that health professionals need to identify factors affecting adherence to rehabilitation and provide a nursing intervention considering the depression especially when caring for stroke patients.

Purpose: The purpose of this study was to identify influencing factors on rehabilitation adherence in stroke patients. Methods: This study was a descriptive survey. A structured questionnaire was used for face-to-face interviews with a convenient sample of 192 subjects, who were admitted in 5 rehabilitation hospitals located in G metropolitan city. Results: The score of rehabilitation motivation in the subjects was a mean of 2.04± 0.35, self-efficacy 6.22± 2.32, family support 3.40± 0.82 and rehabilitation adherence 3.08± 0.41. The rehabilitation adherence was a statistically significant difference according to the education level (F= 3.40, p= .035), marital status (F= 4.04, p= .019), number of personal insurance policies (K= 9.80, p= .020), location of paresis (F= 2.72, p= .046), and status of current smoking (M = 657.00, p = .001). There was significant correlation among degree of rehabilitation adherence, rehabilitation motivation (r= .30, p< .001), self-efficacy (r= .14, p= .046) and family support (r= .18, p= .011). Rehabilitation motivation (β= 0.19, p= .007), self-efficacy (β= 0.14, p= .035), marital status (β= 0.14, p= .038), number of personal insurance policies (β= -0.15, p= .045) and location of paresis(β= -0.15, p= .028) were identified as significant predictors. This model explained 22.6% of variance in rehabilitation adherence (F= 5.92, p< .001). Conclusion: There is a need to develop an effective intervention for rehabilitation adherence improvement considering the identified variables in this study. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.