Sitting balance as an early predictor of functional improvement in association with depressive symptoms in stroke patients


Seiji Hama, MD, Nishi-Hiroshima Rehabilitation Hospital, Miyake 6-265, Saeki-ku, Hiroshima 731-5143, Japan. Email:;


Abstract  The aim of the present study was to assess the relationship between sitting balance at an early stage and activities of daily living (ADL) function in 452 stroke patients. The effect of sitting balance on the two core elements of depression (apathy and depressive mood) was also examined. The ability to maintain a sitting position for 10 min (10-min sitting balance) was assessed, along with ADL using the Functional Independence Measurement, and psychological status using the Zung Self-rating Depression Scale (depressive mood), Apathy Scale (apathy) and Neuropsychiatric Inventory. Proportional-hazards analysis was used to determine the independent effect of post-stroke depression on functional outcome. Comparisons between sitting balance and psychological status were performed using logistic multiple regression analysis. Cox multiple regression analysis showed that significant differences were obtained for the sitting balance (P < 0.0002) and Mini-Mental State Examination scores (P < 0.02) in all six ADL subscales, and for age in four of the six ADL subscales (Dressing–Upper Body and Dressing–Lower Body, Toileting, Walking). Kaplan–Meier survival curves for reaching independence in ADL subscales showed highly significantly differences in achievement rate and time to reach goal for each subgroup on 10-min sitting balance (with or without assistance) and on age (young, <65; elderly, ≥65 years). Ten-minute sitting balance correlated with depressive mood and apathy. A rapid and simple screening method, 10-min sitting balance was related to scores for two core depressive symptoms, lowered mood and apathy, and was predictive of post-stroke ADL outcomes in the rehabilitation unit along with age.


Stroke is the most common cause of disability or dependence in activities of daily living (ADL) among the elderly.1 There is recent evidence that optimal management in stroke care results in reduced length of stay, reduced dependency, and earlier restoration of some aspects of physical function.2 However, care of stroke patients varies significantly between hospitals.3 A simple outcome measure that is sensitive to physical recovery profiles in stroke rehabilitation, is easy to use in various clinical environments, and which could be widely adopted, might provide an appropriate tool in the therapeutic setting for evaluating and optimizing physical outcome after stroke.

Sitting balance is not a functional activity, but the ability to maintain or attain sitting balance is believed to be necessary to perform functional activities such as dressing and transferring.4–6 Some studies have found that sitting balance at an early stage could predict activities of daily living (ADL) outcome at a late stage in patients after a stroke.5–8 To investigate a simple measurement to predict functional outcome after stroke, we estimated sitting balance using a modified mobility measurement: maintenance of a sitting position for 10 min (10-min sitting balance).2,9

Moreover, each stroke patient usually reaches a different level of functionality and does so at different times.2,10 Previous predictive ADL outcome studies did not estimate this tendency. Survival analysis allows the outcome data to be presented as a continuum that defines outcome status at any point in time along the curve, which facilitates comparison of the results of studies presenting data only at fixed time intervals.10 One of the aims of the present study was to generate a Cox regression model and Kaplan–Meier curves while the patients participated in an inpatient rehabilitation program. Patients were censored when they left the program if they had not yet reached their respective outcome goal. Then we examined the correlation between sitting balance and functional outcome to estimate the probability of obtaining independent functionality in ADL. In the prediction of functional recovery after stroke, depression is also an important factor.11 Depression has two core symptoms in the DSM-IV classification: “decline in mood” and “loss of interest (apathy)”.12 Physical disability among depressed persons is significantly higher than among non-depressed persons.13–15 Therefore, we also examined the correlation between sitting balance and these two core symptoms of depression, respectively.



The approval of the institutional ethics committee was obtained for this prospective study. Informed consent was obtained from all patients. Included in the present study were 452 patients with hemorrhagic or occlusive stroke and without subarachnoid hemorrhage who were diagnosed using computed tomography (CT), and who were admitted to the Nishi-Hiroshima Rehabilitation Hospital during the past 56 months, within 3months after suffering their stroke.

Because Zung Self-rating Depression Scale (SDS) and Apathy Scale (AS) are patient-rated, it was necessary to exclude patients with (i) a history of major psychiatric illness including depression; (ii) medical illness, a speech impediment, or impaired cognitive function (Mini-Mental State Examination [MMSE] score <20) for whom a reliable psychological test result and/or informed consent could not be obtained; or (iii) physical disability sufficient to preclude cognitive testing. The remaining 190 patients were given the SDS and AS questionnaires. Among these patients, Neuropsychiatric Inventory (NPI) assessment could not be carried out for 18 patients, and psychological information could not be obtained from the caregiver in these cases, leaving 172 patients who were assessed using NPI.

Data were gathered from a subset of the subjects of a previous study, which was a research project on depression and lesion location, or depression/apathy and functional outcome among stroke rehabilitation patients.11,12 Patients were not selected on the basis of results of the previous study.

Computed tomography findings

The study had a prospective design using 452 CT scans. CT results were used because a larger sample was available than of magnetic resonance imaging (MRI) data. CT scanning was carried out in all patients on admission; a follow-up CT scan was performed every 1–3 months after admission to measure the infarction/hemorrhage site and volume (cubic centimeters) according to the formula 0.5 × A × B × C, where A and B represent the largest perpendicular diameters through the hypodense area on CT scan, and C is the thickness of the infarcted area.16

Stroke location was categorized into two groups: infratentorial and supratentorial according to the CT findings and/or clinical findings.

Functional measures

The Functional Independence Measurement (FIM; version 3.0) is an 18-item assessment tool that is an observer-rated multi-item summed rating scale used to evaluate disability in terms of dependency and which is widely used (the Japanese version of FIM is used for rehabilitation in Japan) as a measure of disability in stroke patients.11,17–19 All patients were examined for disability using the FIM within 1 week after admission and at 1–2-week intervals during hospitalization. For the purpose of the present study the FIM items pertaining to ADL (i.e. Dressing–Upper Body, Dressing–Lower Body, Toileting, Transfer, Locomotion: Wheelchair, Locomotion: Walking) were used to form an index of ADL functioning.

Ten-minute sitting balance was evaluated with or without assistance within 1 week after admission and at 1–2-week intervals during hospitalization as follows: a period of sitting on a bed or plinth without a backrest for longer than 10 min, with the hips, knees and ankles positioned at 90° and with both feet flat on the floor. Ten-minute sitting balance assessed by rehabilitation staff (PT, OT) and nurses, and analyzed statistically with Fisher's exact test, demonstrated a high level of significance between these two groups (P < 0.0001).

Motor impairment in hemiplegic stroke patients was measured by stage on the Brunnstrom Recovery Scale (BRS), in which movement patterns are evaluated and motor function is rated according to stages of motor recovery.20 The BRS defines recovery only in broad categories; these categories correlate with progressive functional recovery. The Japanese version of the BRS is widely used for rehabilitation in Japan.

Cognitive functions of stroke patients were measured using the Mini-Mental State Examination (MMSE). Scores range from 0 to 30.

Self-rating Depression Scale

We used the Japanese version of the SDS to examine the subjective severity of depressed mood, as previously described.12 SDS was administered within 1 month following stroke. We classified patients into two groups according to their score: a depressed-mood group (SDS score ≥45 points) and a maintained-mood group (SDS score <45 points). The cut-off point was determined on the basis of a previous report on Japanese stroke patients.21

Apathy Scale

To quantify loss of interest (state of apathy), we used a Japanese version of the apathy scale.11,12,22–24 AS was administered within 1 month following stroke. The AS consists of 14 questions concerning spontaneity, initiation, emotionality, activity level, and interest in hobbies. This scale was self-assessed. The answers were scored in four grades (0–3) and the total score was used for analysis. We classified the patients into two groups according to their score: an apathetic group (apathy score ≥16 points) and a non-apathetic group (apathy score <16 points). This cut-off point was determined on the basis of previous reports on Japanese stroke patients.22,24

Japanese version of the Neuropsychiatric Inventory

The self-report assessments (i.e. SDS, AS) resulted in a discrepancy between the observer and patient rating scale for diagnosis of depression, suggesting that either patients tended to minimize the severity of their mood disorders or observers were more sensitive to patient behavior than the patients themselves.11,25,26 Therefore, we also performed NPI as an observer-rating psychological examination. NPI is an informant-based interview with a caregiver familiar for evaluating behavioral changes following the onset of illness, and it was shown to be useful for better assessing neuropsychiatric symptoms also in stroke survivors.27–29 The Japanese version of NPI28 was given within 1 month following admission. The interviewer confirms whether the patient has any psychiatric symptoms (delusions, hallucinations, agitation, dysphoria, anxiety, euphoria, apathy, disinhibition, irritability, aberrant behavior) and determines the severity and frequency of each symptom according to defined criteria. Frequency is rated on a 5-point scale from 0 to 4 and severity is rated on a 4-point scale from 0 to 3: the higher the score, the greater the severity or frequency. The product of the severity score and the frequency score gives the score for each symptom.27,28

Statistical analysis

The construction of the survival curves was performed by means of the Kaplan–Meier method. Survival time was defined as the period from the date of onset of the stroke to the date of discharge (if subscale at discharge ≤4: need for some assistance), or the date when the subscale exceeded 5 (no need for any assistance). Patients were censored if they had not yet reached their independent outcome goal when they left the rehabilitation hospital (subscale at discharge ≤4). We divided the patients into two age groups (young, <65; elderly, ≥65 years), and the comparison of the survival curves was made using the log–rank test. To control the contribution of the variables to each functional state, a multivariate survival analysis was performed using Cox regression.

The comparison between sitting balance and SDS or AS was performed with the Mann–Whitney U-test. Logistic regression analysis was used to estimate the independent effects of predictor variables (age, sex, supra/infratentorial lesion site, MMSE, and sitting balance) on psychopathological status (depressed or non-depressed and apathetic or non-apathetic state).

Values were considered to be significant at P < 0.05. The statistical package StatView 5.0 (SAS Institute, Cary, NC, USA) was used for all analyses.


Baseline structures in all patients

Table 1 shows baseline data for all patients. The young age group (<65 years) consisted of 179 patients, and the elderly group (≥65 years) of 275 patients. A total of 155 patients (34.1%) needed some assistance in maintaining a 10-min sitting position. Among them, 38 patients were in the young group, and 31 of them (81.6%) were improved (without assistance) at discharge. However, of the 117 patients who were in the elderly group, 66 (56.4%) were improved at discharge.

Table 1.  Baseline characteristics on admission
 Baseline (n = 452)Age <65 (n = 178)Age ≥65 (n = 274)P
  • † 

    Twenty-six patients in whom hypodense area was not detected on CT were not included.

  • ‡ 

    Thirty-nine patients for whom MMSE examination was not carried out are not included.

  • To test the correlation between the two age groups (age <65 and Age ≥65), Fisher exact test was used to compared categorical variables and Mann–Whitney test was used to compare continuous variables.

  • Size of lesion was measured on CT.

  • BRS, Brunnstrom Recovery Scale; CT, computed tomography; FIM, Functional Independence Measurement; MMSE, Mini-Mental State Examination.

Age (years) 66.6 ± 12.3 54.2 ± 8.3 74.7 ± 6.5<0.0001
Sex (male; female)299; 153136; 42163; 1110.0002
Duration of hospitalization (days)150.6 ± 50.0143.2 ± 51.8155.4 ± 48.30.0394
Time interval between onset and admission (days) 44.3 ± 21.1 (7–91) 44.9 ± 21.4 (7–90) 43.9 ± 20.8 (10–91)0.6326
Type of stroke (hemorrhage; infarction)196; 25698; 8098; 176<0.0001
Past history of stroke67 (14.8%)18 (10.1%)49 (17.9%)0.0296
Size of lesion in CT (cm3) 39.2 ± 65.1 43.5 ± 75.4 36.4 ± 57.20.4114
BRS upper limb 3.3 ± 1.7 3.2 ± 1.6 3.3 ± 1.70.8867
BRS finger 3.3 ± 1.7 3.2 ± 1.7 3.3 ± 1.80.7672
BRS lower limb 3.5 ± 1.6 3.6 ± 1.5 3.5 ± 1.60.6601
MMSE 18.9 ± 10.3 21.3 ± 9.9 17.4 ± 10.2<0.0001
FIM on admission 67.9 ± 26.7 77.3 ± 25.6 61.8 ± 25.7<0.0001
10-min sitting balance/with assistance155 (34.3%)38 (21.3%)117 (42.7%)<0.0001

Cox multiple regression analysis

To determine which of the nine variables studied contributed significantly to prediction of ADL subscale independence, we used Cox multiple regression analysis.

Table 2 shows the results of the Cox multiple regression analysis. A highly significant difference was obtained from the cognitive variable (MMSE score; P < 0.02) and from sitting balance (P < 0.0002) with regard to the percentage of patients achieving the defined functional goal and the time taken to achieve it on all six ADL subscales. Age also made a significant difference in four of the six ADL subscales (Dressing–Upper Body, Dressing–Lower Body, Toileting, Walking), while other factors made little or no significant difference in any of the six ADL subscales. Therefore, age, cognitive function (MMSE) and sitting balance were significant predictors of functional outcome after stroke.

Table 2.  Variables with functional prognosis values during hospitalization after stroke
VariablesDressing–upper bodyDressing–lower bodyToileting
βPRR (95%CI)βPRR (95%CI)βPRR (95%CI)
Age−0.0290.0030.972 (0.954–0.990)−0.0310.00090.970 (0.952–0.987)−0.0250.00540.975 (0.958–0.993)
Sex/Female0.0160.94021.017 (0.663–1.559)−0.2170.33510.805 (0.517–1.252)−0.5060.01690.603 (0.398–0.913)
The presence of history of stroke/recurrence0.0590.84321.060 (0.593–1.895)0.2990.28281.348 (0.782–2.326)0.1300.61781.139 (0.682–1.902)
Size of lesion (CT)0.0000.02471.000 (1.000–1.000)0.0000.11461.000 (1.000–1.000)0.0000.08461.000 (1.000–1.000)
BRS up−0.0340.84960.967 (0.682–1.370)0.0690.70571.072 (0.748–1.535)0.1740.40591.190 (0.790–1.793)
BRS finger0.0250.87111.025 (0.759–1.385)−0.0880.58110.915 (0.669–1.253)−0.1630.31720.850 (0.618–1.169)
BRS low0.1110.3521.117 (0.883–1.413)0.1180.34561.126 (0.880–1.439)0.0360.78101.036 (0.807–1.331)
MMSE0.0270.01461.027 (1.005–1.050)0.0310.00551.031 (1.009–1.054)0.0370.00061.038 (1.016–1.060)
Sitting/Assistance−1.337<0.00010.263 (0.164–0.419)−1.478<0.00010.228 (0.137–0.379)−1.550<0.00010.212 (0.132–0.341)
VariablesTransfer: Bed, Chair, WheelchairLocomotion: WheelchairLocomotion: Walking
βPRR (95%CI)βPRR (95%CI)βPRR (95%CI)
  1. Bold, P < 0.05.

  2. Multivariate analysis by means of Cox regression.

  3. Size of lesion was measured on CT. BRS, Brunnstrom Recovery Scale; CI, confidence interval; CT, computed tomography; MMSE, Mini-Mental State Examination; RR, relative risk.

Age−0.0150.09360.985 (0.967–1.003)−0.0060.49390.994 (0.977–1.011)−0.0250.00210.975 (0.959–0.991)
Sex/Female−0.2250.26470.798 (0.538–1.186)−0.5740.00350.563 (0.380–0.829)−0.5440.00800.580 (0.388–0.868)
The presence of history of stroke/recurrence−0.3630.20290.695 (0.397–1.217)−0.6920.01600.501 (0.285–0.879)−0.1140.65750.892 (0.539–1.477)
Size of lesion (CT)0.0000.33651.000 (1.000–1.000)0.0000.38371.000 (1.000–1.000)0.0000.30201.000 (1.000–1.000)
BRS up0.4120.04121.510 (1.017–2.244)0.1010.58891.106 (0.767–1.595)0.2450.08101.278 (0.970–1.683)
BRS finger−0.2290.14810.795 (0.583–1.085)−0.0470.72780.954 (0.733–1.242)−0.1720.16600.842 (0.660–1.074)
BRS low0.0250.83991.025 (0.808–1.300)−0.1570.21270.854 (0.667–1.094)0.4000.00011.492 (1.217–1.830)
MMSE0.0290.00491.029 (1.009–1.050)0.040<0.00011.041 (1.022–1.061)0.051<0.00011.052 (1.027–1.077)
Sitting/Assistance−1.209<0.00010.298 (0.191–0.465)−0.7980.00020.450 (0.296–0.686)−1.328<0.00010.265 (0.151–0.465)

Kaplan–Meier survival analysis of 10-min sitting with or without assistance in two age groups

Figure 1 presents Kaplan–Meier survival curves for reaching independence in transfer and toileting functions, indicating that the requirement for assistance to maintain sitting balance for 10 min had a highly significantly effect on the overall probability of reaching this goal in each age group (walking and toileting, both P < 0.0001). Other FIM subscales (Eating, Dressing–Upper Body, Dressing–Lower Body, Transfer, Locomotion: Wheelchair) showed the same trend (data not shown). Therefore, the Kaplan–Meier method, using sitting balance and age, was a useful tool to define ADL functional goals and the time taken to achieve them during rehabilitation after stroke.

Figure 1.

Survival analysis of time to achieve (a) independent walking and (b) toileting. Age groups: young, <65; elderly, ≥65. (a) (—) Young, sitting without assistance (n = 99); (–·–·) elderly, sitting without assistance (n = 146); (- - -) young, sitting with assistance (n = 28); (· · ·) elderly, sitting with assistance (n = 83). (b) (—) Young, sitting without assistance (n = 62); (–·–·) elderly, sitting without assistance (n = 107); (- - -) young, sitting with assistance (n = 27); (· · ·) elderly, sitting with assistance (n = 83). Sitting with vs without assistant: log–rank P < 0.0001.

Association between sitting balance and core depressive symptoms (mood disorder and apathy)

We examined the association between sitting balance on admission and the two core depressive symptoms separately using the Mann–Whitney U-test. Significant differences were demonstrated between the 10-min sitting balance on admission and the SDS or AS score (Fig. 2), suggesting that depressed mood and apathetic state were associated with physical dysfunction after stroke.

Figure 2.

Box plots showing differences in (a) Zung Self-rating Depression Scale (SDS) and (b) Apathy Scale (AS) scores between maintaining 10-min sitting with and without assistance. Box plots show median, quartiles, and 10th and 90th percentiles.

Other factors, such as age, lesion location and cognitive function, were also thought to affect psychological status (depression and apathy) as described previously.12,15,26 Therefore we performed logistic regression analysis to identify predictors of psychological status (depression or apathy; Table 3). The results from the self-report scales (SDS and AS) showed that there was a statistically significant increase in SDS score when sitting balance was more severely impaired (P = 0.0078, RR [relative risk] = 2.835). There was no statistically significant difference between AS score and sitting balance, while the same tendency was evident for SDS score (P = 0.0592, RR = 2.087). The observer-rating results also showed the same trend (depression vs sitting balance/with assistance: P = 0.006, RR = 3.195; apathy vs sitting balance/with assistance: P = 0.0289, RR = 3.256), suggesting that depressed mood and apathetic state were associated with sitting balance after stroke.

Table 3.  Multivariate analysis by means of logistic regression
VariablesDepression vs no-depressionApathy vs no-apathy
βPRR (95%CI)βPRR (95%CI)
  1. SDS score: ≥45, depression; <45, no depression; AS score: ≥16, apathy; <16, no apathy.

  2. Depression subscore of NPI: ≥1, depression; 0, no depression; Apathy subscore of NPI: ≥1, apathy; 0, no apathy.

  3. AS, Apathy scale; CI, confidence interval; MMSE, Mini-Mental State Examination; NPI, Neuropsychiatric Inventory; RR, relative risk; SDS, Zung Self-rating Depression Scale.

SDS and AS
 Age−0.0260.07640.974 (0.947–1.003)0.0320.03281.033 (1.033–1.064)
 Sex: Male0.1480.6831.159 (0.571–2.355)−0.4590.17470.632 (0.326–1.226)
 Supra- or infratentorial lesion0.0450.92831.046 (0.396–2.762)0.8430.12022.323 (0.802–6.726)
 MMSE−0.0770.16670.925 (0.829–1.033)−0.0710.18540.931 (0.838–1.035)
 Sitting balance: with assist1.0420.00782.835 (1.316–6.107)0.7360.05922.087 (0.972–4.482)
 Age0.0180.26561.018 (0.986–1.051)0.1030.00051.109 (1.046–1.175)
 Sex: Male0.2430.50011.275 (0.629–2.586)1.3170.0320 3.732 (1.120–12.438)
 Supra- or infratentorial lesion1.9630.01127.123 (1.563–32.457)0.3730.65951.452 (0.276–7.643)
 MMSE−0.0020.96750.998 (0.893–1.115)−0.1250.11930.882 (0.754–1.033)
 Sitting balance: with assist1.1610.0063.195 (1.396–7.313)1.1810.02893.256 (1.129–9.387)


This study was undertaken to evaluate the relationship between sitting balance on admission and FIM improvement during rehabilitation in patients hospitalized after stroke. We found that poor sitting balance and advanced age was associated with poor functional improvement after stroke. Sitting balance is not a functional activity, but the ability to maintain or attain sitting balance is believed to be necessary to perform functional activities such as dressing, transferring, and eating in a seated position.4–6 The ability to balance is maintained by a delicate interplay among the sensory, motor and cognitive systems, and changes in the ability to balance, particularly in complex situations, can occur as a result of stroke.5,30 Impairment or disruption of the mechanisms responsible for postural control can lead to unsteadiness and a tendency toward instability, and preclude effective rehabilitation.30 Sandin and Smith found that weekly sitting balance assessments correlated strongly with weekly Barthel Index scores (another measure of function) throughout the rehabilitation stay for patients with hemiparesis secondary to stroke.8 Other studies have also demonstrated that at hospital admission, a trunk control test could predict ADL outcome at a late stage in patients with stroke.5–8 Therefore, these results and the present data support the value of early assessment of trunk control in predicting ADL function in stroke patients.

We also found age to be a significant predictor of ADL function. Aging is associated with higher incidence of physical impairment (i.e. disorders of postural control, proprioception and gait) and functional disability. Elderly stroke patients have poorer functional outcomes than younger patients after stroke and require longer hospitalization to achieve the same functional gains as younger patients.31,32 These observations are consistent with the present data that the improvement in sitting balance of elderly patients (56%) during hospitalization was less than that of younger patients (82%) and imply that aging is a poor prognostic factor for functional disability.

The identification of simple clinical predictors (i.e. age and sitting balance) for stroke outcome is of practical value in clinical settings. Some researchers have argued that multivariable models were not only difficult to use in practice but also had little advantage over simple clinical predictors.33 The more complex these models are, the less likely they are to be widely used.34 In the present study we also found cognitive function (MMSE) to be a significant predictor of ADL function. However, MMSE could not be done for patients with severe comprehension deficits. Therefore, the predictive outcome model using MMSE may not be applicable to all stroke patients. Age and 10-min sitting balance were easy to determine and are applicable to all stroke patients in various hospitals. The combination of these simple factors (i.e. age and sitting balance) with the Kaplan–Meier method can predict the level of functional recovery and the time required to achieve it. Use of this technique could reduce variations in stroke care and provide an appropriate tool in the therapeutic setting after stroke. Therefore the present findings extend the simple prognostic value of age and sitting balance in predicting ADL function after stroke.

Post-stroke depression, frequently observed, consists of two separate core symptoms (depressive mood and apathy) with different underlying neuroanatomical mechanisms.12,26 Several studies have shown that both depressive mood and apathy have a negative impact on the capacity of stroke patients to recover ADL.11,20,23,25,26 Somatic symptoms, including psychomotor retardation, weakness, and lethargy, are important features of depression.13–15 This observation is consistent with the results of the present multiple regression analysis, in which reduced mood and apathetic state was associated with sitting balance after stroke. Depressive symptoms were influenced by several factors, such as age15 and lesion location,12,26 while the present results also suggest that trunk control, that is, sitting balance, might be an important predictive factor. The findings from the present study do not suggest that poor sitting balance causes depressive symptoms; rather they indicate that poor sitting balance is associated with depressive symptoms, especially depressive mood after stroke.

Several methodological limitations should be acknowledged. It is possible that some variables not included in the present study, such as perceptual and motivational variables, could have increased the predictive value of the model. Additionally, patients enrolled in the present study underwent CT scanning only (not MRI). Modern imaging techniques could provide valuable information for improving the early prediction of stroke outcome.35 These technologies are, however, unlikely to become accessible for routine clinical use soon. We excluded patients with cognitive deficits based on the results of a psychopathological study; the results may therefore not be applicable to all stroke patients. Finally, because the sample size of the psychopathological study was small, the results require replication with a larger sample.


A rapid and simple screening method, 10-min sitting balance, was associated with two core depressive symptoms, reduced mood and apathy. Along with age, it was effective in the prediction of ADL outcomes after stroke in a rehabilitation unit.


This study was supported by Research on Psychiatric and Neurological Disease and Mental Health, Ministry of Health, Labour and Welfare, Japan (H15-kokoro-005).