A pilot study on a specific measure for sleep
disorders in Parkinson’s disease: SCOPA-Sleep
P. Martínez-Martín a, E. Cubo-Delgado a,b, M. Aguilar-Barberà c, A. Bergareche d, S. Escalante c,
A. Rojo c, J. Campdelacreu c, B. Frades-Payo a, S. Arroyo a, on behalf of the ELEP Group e
A PILOT STUDY ON A SPECIFIC MEASURE FOR SLEEP DISORDERS IN PARKINSON'S DISEASE: SCOPA-SLEEP
Introduction. There is a high prevalence of sleep disorders in Parkinson’s disease (PD).
Aims. To assess some basic
metric attributes of the SCOPA-Sleep scale, a measure for PD patients; secondary objective: to check the impact caused by the
sleep disorder on the health-related quality of life (HRQoL) of patients and their caregivers.
Subjects and methods. 68 PD
patients and their main caregivers; measures: Hoehn and Yahr staging, SCOPA-Motor, Clinical Impression of Severity Index
(CISI-PD), PDSS, Hospital Anxiety and Depression Scale, SCOPA-Psychosocial, and EuroQoL. Carers filled in a PDSS
questionnaire about patient sleep and HRQoL measures (SF-36, EuroQoL). SCOPA-Sleep acceptability, scaling assumptions,
internal consistency, construct validity and precision were determined.
Results. SCOPA-Sleep acceptability and scaling
assumptions resulted satisfactory, although the nocturnal sleep subescale (SC-Ns) showed a mild ceiling effect (22.1%) and a
defective convergent validity was found for daytime sleepiness (SC-Ds) item 6. Internal consistency also was satisfactory for
both scales (alpha = 0.84 and 0.75, respectively). The correlation between SC-Ns and PDSS was high (
r = –0.70), as it was
between SC-Ns and PDSS questionnaire by caregiver (
r = –0.53). The corresponding coefficients with the SC-Ds gained
lower values (
r = –0.41 y –0.50). Standard error of measurement was 1.45 for the SC-Ns and 1.76 for the SC-Ds. Both,
patient and caregiver HRQoL showed a loose association with the sleep measures.
Conclusion. SCOPA-Sleep is a feasible,
consistent, and useful scale for assessment of sleep disorder in PD patients. A weak association between sleep disorder and
HRQoL was found. [REV NEUROL 2006; 43: 577-83]
Key words. Assessment. CISI-PD. Health-related quality of life. Parkinson’s disease. Parkinson’s Disease Rating Scale. SCOPA-
Sleep. Sleep disorder.
such instruments would enable the magnitude of the alterations
While clinical manifestations of Parkinson’s disease (PD) typi-
and the effect of therapies to be quantified. The problem posed
cally include motor disorders, such as tremor, rigidity, hypo-
by this deficit will soon be resolved, however: specific scales
kinesia, and gait disturbances, there is also a wide variety of
for some of these dysfunctions are already available [4-7] and
‘non-motor’ symptoms, to which increasing attention is being
there are several initiatives under way aimed at designing a uni-
paid. Some noteworthy non-motor symptoms are neuropsychi-
fied scale for non-motor symptoms [1,8,9].
atric disturbances, sleep disorders, gastrointestinal and auto-
A very frequent problem in PD is upset sleep, which includes
nomic manifestations, sensory symptoms, and a miscellany
insomnia (difficulty falling or staying asleep at night), parasom-
that includes fatigue, visual troubles, seborrhea, and weight
nias –such as REM (rapid-eye movement) sleep behavior disor-
der–, daytime hypersomnia, and sleep attacks [10-12].
Yet, despite the huge impact these symptoms have on
Non-specific scales for assessment of nocturnal sleep, such
patients’ overall health and quality of life, they are frequently
as the Pittsburgh scale , or daytime sleepiness, such as the
overlooked. Indeed, this is so even in the specialized setting,
Epworth scale , have been used for evaluation of sleep dis-
where health professionals tend to be more attentive to the motor
turbances in PD. In 2002, Chaudhuri et al  published the first
ever specific scale for evaluation of nocturnal sleep quality in
One of the reasons for this situation has been the absence of
PD. Recently, this Parkinson’s Disease Sleep Scale (PDSS) has
simple, valid measurement instruments for systematic applica-
undergone independent validation and cross-cultural adaptation
tion in daily practice and clinical research. The availability of
to Spain . In 2003, Marinus et al  published another spe-
guez, F. Rodríguez-Sanz (Segovia), L.J. López del Val (Zaragoza), J. Chacón-
Peña, M. Carballo (Sevilla), J.M. Fernández-García (Bilbao), V. Campos-
Neuroepidemiology Unit. National Center for Epidemiology. Carlos III
Arillo (Málaga), A. Rojo-Sebastián (Terrassa, Barcelona), M. Álvarez-Saúco,
Institute of Public Health. Madrid. b Department of Neurology. Nuestra
C. Leiva (Alicante), A. Castro, A. Sesar (Santiago de Compostela, A Coru-
Señora del Rosario Clinic. Madrid. c Department of Neurology, Mútua de
ña), A. Ortega-Moreno (Granada), R. Luquin (Pamplona).
Terrassa Hospital. Terrassa, Barcelona, d Department of Neurology. BidasoaHospital. Hondarribia, Guipúzcoa. e
Head Researcher: P. Martínez-Martín
Corresponding author: Dr. P. Martínez Martín. National Center for Epidemi-
Steering Committee: P. Martínez-Martín (Madrid), G. Linazasoro
ology. Carlos III Institute of Public Health. Sinesio Delgado, 6. E-28029
(Guipúzcoa), J. Kulisevsky (Barcelona), M. Aguilar-Barberà (Terrassa, Bar-
Madrid. Fax: +34 913 877 815. E-mail: [email protected]
Technical Committee: J. de Pedro, E. Cubo, M.J. Forjaz, J.M. Fer-nández-Castrillo (Madrid), A. Bergareche (Hondarribia, Guipúzcoa), M.
This study was partially funded by the Carlos III Institute of Public Health,
Members: L. Menéndez-Guisasola, C. Salva-
namely: E. Cubo by the CIEN Network of Excellence (C03-06); B. Frades
dor-Aguiar, S. González-González (Oviedo), A. Bayes-Rusiñol, F. Vallde-
by the IRYSS Network of Excellence (G03-202); and S. Arroyo by the Intra-
oriola (Barcelona), B. Frades-Payo, L. Vela-Desojo, J. Benito-León, F. Vi-
mural Research Program (ELEP Project: EPY1271/05).
vancos-Matellano, M.J. Catalán-Alonso (Madrid), S. García-Muñozguren (Al-bacete), C. Durán-Herrera (Badajoz), J. Duarte-García, A. Mendoza-Rodrí-
cific scale for PD (SCOPA-Sleep), designed to evaluate noctur-
themselves or by their caregivers .The maximum total PDSS score is
150: the lower the score, the worse the quality of sleep.
The main aim of this study was to assess some basic metric
attributes of the Spanish-version SCOPA-Sleep scale applied to
This scale has two sections, Nocturnal Sleep (SC-NS) and Daytime Sleepi-
a series of PD patients. As a secondary objective, it sought to
ness (SC-DS), which evaluate problems in these respective domains during
analyze the association between sleep disorders and patients’
the ‘last month’. The SC-NS consists of five items addressing trouble
and their caregivers’ health-related quality of life (HRQL).
falling asleep, fragmentation and duration of sleep, early waking, and feel-ing of having had too little sleep. Score options for items range from 0 (noproblem) to 3 (a lot of problems), with the limits of the total score being 0
SUBJECTS AND METHODS
and 15. Following this section is a global evaluation of nighttime sleep with
This was the first independent study on the metric properties of the SCOPA-
seven response options (1, ‘very well’ to 7, ‘very bad’). The SC-DS scale
Sleep and a pilot study for the Spanish version. A multicenter, open, cross-
evaluates daytime hypersomnia in the preceding month. It includes 6 items
sectional, one point-in-time evaluation study.
dealing with the frequency of falling asleep in certain situations (e.g., unex-
Consecutive patients older than 40 years, both genders, with diagnosis of
pectedly, sitting down peacefully, watching television or reading, or speak-
PD as per modified United Kingdom PD Society Brain Bank Criteria .
ing to somebody). Each item can score from 0 (never) to 3 (frequently), thus
The modifications consisted of considering ‘clear beneficial response to
dopaminergic treatment’ (not only to levodopa) and ‘maintained responseto dopaminergic treatment’ (instead of response to levodopa treatment for
Hospital Anxiety and Depression Scale (HADS)
more than 5 years) as support criteria (Section 3).
This is composed of 14 items, seven identifying anxiety and seven for depres-
As an additional inclusion criterion, patients were required to have a sta-
sion. Each item scores from 0 (no problem) to 3 (extreme problem). Scores
ble caregiver, and both patients and carers were required to be ‘able to read,
higher than 10 on each subscale are indicative of anxiety or depression,
to understand and to answer questionnaires’ in the participant neurologist’s
respectively. Marinus et al.  report that the HADS’ metric properties
mean that it can be applied to PD patients.
Exclusion criteria were defined as the absence of one or more inclusion
criteria and the presence of any comorbidity that could interfere with or sig-
nificantly modify evaluation of the effects caused by PD (e.g., blindness,
This scale was designed to evaluate the psychosocial impact of PD. It con-
serious systemic illness, residual hemiplegia, etc.).
sists of 11 items, each of which assesses the severity of a particular problem
Informed consent was obtained from all participant patients and care-
during the preceding month, using a score ranging from 0 (not at all) to 3
givers. This study forms part of the Longitudinal PD Patient Study –Estudio
(very much). It includes information on psychosocial functioning and diffi-
Longitudinal de pacientes con Enfermedad de Parkinson (ELEP)–, approved
culties vis-à-vis daily living and recreational activities, relationships with
by the Clinical Research Ethics Committees of the Princesa Hospital
family and friends, dependence, isolation and concern about the future.
(Madrid) and the Carlos III Institute of Public Health .
Intended for use in econometrics, this is an instrument designed to measure
HRQL on the basis of preferences. It contains a descriptive part, comprising
In the present study, we applied the version included in the Unified Parkin-
five items with three answer levels (1 = there are no problems or symptoms,
to 3 = problems or severe symptoms). The descriptive system can thus gen-erate 243 different health profiles. To each of these profiles, a preference
Mini-Mental State Examination (MMSE)
index or social tariff can be assigned, ranging from 1.0 (perfect health state)
This test was applied to ascertain the cognitive state of patients included in
to 0.0 (death). Such an index is obtained by means of techniques such as time
trade-off (the indices used in the present study) or the analogue visual scale.
SCOPA-Motor (SC-M) . The SCOPA-Motor scale was designed
The EuroQoL also includes a question on the course of respondents’ gen-
within a program to develop specific PD measures –Scales for Outcomes
eral state of health in the previous 12 months and a visual analogue scale for
in Parkinson’s disease (SCOPA)–. It is made up of the following 3 sec-
evaluation of their current (‘today’) health state (from 0 = worst imaginable
tions: 1) Motor evaluation (‘clinical examination’ subscale, 8 items, and
health state, to 100 = best imaginable health state).
‘historical information’ subscale, 2 items); 2) Activities of daily living(ADL) (7 items); and 3) Motor complications (4 items). Each item is scored
from 0 (normal) to 3 (severe). The average time spent on administering this
scale is 8.1 ± 1.9 minutes . A cross-culturally validated Spanish version
A questionnaire containing the same items as the PDSS was purpose-designed
to obtain an evaluation by caregivers (evaluation by proxy) of sleep distur-bances that might go unnoticed by patients.
Clinical Impression of Severity Index (CISI-PD)
This is a clinimetric index comprising four items (motor signs, disability,
Hospital Anxiety & Depression Scale (HADS)
motor complications, and cognitive state) that are scored by the neurologist
Administered to assess caregivers’ mood.
after the interview and examination. Each item is scored from 0 (normal)to 6 (severe). An index is obtained from the sum of these scores (range, 0 to
24), which reflects the neurologist’s impression as regards the severity of
Administered to assess caregivers’ own perceived health state.
This is a generic measure of health-related quality of life, which includes
Parkinson’s Disease Sleep Scale (PDSS)
eight dimensions of health state focusing on:
This scale is composed of fifteen items, fourteen of which explore seven
– Functional aspects, such as physical functioning (10 items), social func-
aspects relating to nocturnal sleep, such as global quality of nighttime sleep,
tioning (2 items), and role limitations due to physical (4 items) and emo-
difficulty falling sleep, presence of hallucinations, nocturia, etc. One item
(item 15) evaluates the presence of unexpectedly falling asleep during the
– Well-being, which integrates the domains of mental health (5 items),
day. The time span explored is the preceding week. On a visual analogue
vitality (4 items) and bodily pain (2 items).
scale that runs from ‘always’ (0) to ‘never’ (10), patients indicate their level
of disability for each aspect assessed. The scale can be completed by patients
– Change in health status over time (1 item).
Store distribution of the applied measures.
data and their location have been considered. The maximum acceptable lim-it for missing and non-analyzable data is 5% .
The acceptability of the measure indicates to what extent the distribution
of the scores represents the true distribution of health state in the assessed
sample. To determine this property, parameters such as the distance betweenthe mean and the median, floor and ceiling effects (ideally less than 15%)
 and skewness (acceptable limits: –1 to +1)  are taken into account.
Scaling assumptions refer to the correct grouping of items in the corre-
sponding scales or dimensions, and to what extent it is appropriate for the
respective scores to be directly added to produce a total score representativeof the construct to be measured. To this end, item-total correlation, duly
corrected for overlap, was analyzed. A value of 0.40  was taken as theminimum standard limit. Items should demonstrate higher correlations (+ 2
× standard error of the correlation coefficient) with their own scale than
with the other in the multitrait analysis .
Internal consistency is one of the attributes of a measure’s reliability.
This property is based on the homogeneity (intercorrelation) of the itemsthat comprise the scale. The most appropriate statistic for exploring this
property is Cronbach’s α coefficient. A value of 0.70 was taken as the low-er limit for
α . Other techniques for ascertaining this attribute are item
homogeneity coefficient (the mean of the inter-item correlation coefficients;
acceptable lower limit = 0.30)  and factor analysis.
Validity assessment tests whether an instrument really measures what it
purports to measure. Construct validity refers to the evidence that enablesscores to be interpreted according to the theoretical implications associated
with the construct that is being measured; convergent validity refers to the
correlation with other accepted measures for the same or related constructs(in which case the coefficients should be high); and divergent or discriminant
validity refers to the relationships with variables that measure other unrelatedconstructs (in this case correlation coefficients should be low). We hypothe-
sized that there would be: a high correlation between the SC-NS and PDSS(r
≥ 0.60) and a moderate correlation between the SC-DS and PDSS (r
0.30-0.59); a weak association between SC-Sleep subscales and patients’
age, duration of PD, HY, and MMSE (r
= 0.10-0.29); a moderate relationshipbetween SC-Sleep and SC-M, CISI-PD, HADS, SC-PS and EuroQoL (r
0.30-0.59) [15, 37]; and a high correlation between the SC-NS and the PDSS-based questionnaire completed by caregivers. Since the data did not fit a nor-
mal distribution, the Spearman rank correlation coefficient was used.
The ability of a measure to detect differences at a point in time among
patients who are ranked according to different levels of severity, is known as
discriminative validity. This was assessed using the Mann-Whitney andKruskal-Wallis tests, with differences being deemed statistically significant
The precision (sensitivity) of a measure is its ability to detect small dif-
ferences. The statistic recommended for this purpose is standard error of
measurement (SEM = SD × √1 – r
, where SD is the standard deviation and
the coefficient of reliability) [38,39].
The association between sleep dysfunction and deterioration in patients’
HRQL was determined by the correlation between PDSS and SC-Sleep
scores and EuroQoL and SC-PS parameters. To analyze the impact of patients’
sleep dysfunction on caregiver’s HRQL, sleep scales scores were correlatedwith caregivers’ EuroQoL and SF-36 indices.
MMSE: Mini-Mental State Examination; CISI-PD: Clinical Impression of Seve-
rity; Index for Parkinson’s disease; HADS: Hospital Anxiety and Depression
A total of sixty-eight PD patients, 61.8% males, were included (Table I).
Scale; PDSS: Parkinson’s Disease Sleep Scale; SC-NS: SCOPA-Nocturnal sleep;SC-DS: SCOPA-Daytime sleepiness; SD: standard deviation
According to HY, the patients distribution was as follows: stage 1, 10.6%;stage 1.5, 6.1%; stage 2, 59.1%; stage 2.5, 9.1%; stage 3, 7.6%; stage 4, 4.5%;and stage 5, 3.0%. Patients were receiving treatment with: levodopa, 82.35%;dopamine agonists, 63.24%; selegiline, 13.24%; amantadine, 2.94%; and apo-
For each dimension, scores are standardized, ranging from 0 (worst health
morphine, 1.47%. Their level of education was: university or equivalent, 13.4%;
state) to 100 (best health state). Finally, the individual dimension scores are
high school, 20.9%; primary, 53.7%; and no formal education, 11.9%.
combined to provide a physical and mental component index .
The mean age of caregivers, 77.3%, women, was 62.9 ± 12.3 years. Their
level of education was: university, 21.5%; high school, 21.5%; primary,
The following metric attributes of the SC-Sleep were analyzed: acceptability;
The descriptive statistics of the scales applied to or used by the patients
scaling assumptions; internal consistency; construct validity; and precision.
are shown in table I. A total of 39 caregivers were requested to complete the
Data quality refers to the instrument’s fitness for use in a clinical context
PDSS-based questionnaire on patients’ sleep (mean score: 96.1 ± 31.5; range:
and is determined by the proportion of fully computable data, after missing
One patient failed to answer SC-DS items 5 and 6 (missing data, 1.5%;
SCOPA-Sleep scaling assumptions (n = 67).
computable, 98.5%). All SC-NS data were available (100%). Accordingly,data quality was satisfactory.
The scores registered for all SC-Sleep items covered the complete theo-
retical range. In contrast, the total score of both subscales failed to reach the
higher theoretical score limit (Table I). The distance of the mean to the
median was 0.63/15 (4.2%) for the SC-NS and 0.55/18 (3.05%) for the SC-DS. Although the SC-NS displayed no floor effect (5.90%), it nevertheless
showed a mild ceiling effect (22.1%), with the corresponding values for theSC-DS being 3.0% and 10.45%, respectively. Skewness proved to be 0.47
for the SC-NS and 1.20 for the SC-DS. To sum up, a slight ceiling effect forthe SC-NS and skewness for the SC-DS were observed.
Item-total correlations were higher than the standard, 0.40 , except
for item 6 of the SC-DS (r
= 0.21), which registered substandard convergentvalidity (Table II). Hence, with single exception of SC-DS item 6, all items
on both subscales were deemed to fit the scaling assumptions (Table II).
Cronbach α coefficient values were 0.84 for the SC-NS and 0.75 for the
SC-DS, with item homogeneity coefficient values of 0.52 and 0.36, respec-tively. All these coefficients proved higher than the established minimum
limit. The exploratory factor analysis (principal components, orthogonal rota-
tion) showed one factor explaining 62% of the variance in the SC-NS, andtwo factors explaining 68% of the variance in the SC-DS. The first of these
latter two factors comprised the first three items of the SC-DS (falling asleepunexpectedly, falling asleep while sitting peacefully, falling asleep while
watching television or reading), and the second comprised the last three items(falling asleep while talking to someone, problems staying awake during
day, and experiencing falling asleep during the day as a problem).
Correlation coefficients between the SCOPA-Sleep subscales and the
other measures applied in the study are shown in the table III. In line with
a Spearman rank correlation coefficients (rs standard error = 0.12). SC-NS: SCOPA-
our working hypothesis, the correlation between the SC-NS and PDSS
Nocturnal sleep; SC-DS: SCOPA-Daytime sleepiness.
(which also measures quality of the nocturnal sleep) was high (r
and the relationship between the SC-DS and PDSS was moderate (r
–0.41). The SC-NS registered moderate associations (r
= 0.30-0.59) with
Correlation a between SCOPA-Sleep and the other measures
the HADS (anxiety and depression sections) and Motor complications of
the SC-M. The SC-DS displayed moderate coefficient values with HY and theCISI-PD (Table III). The remaining correlations were weak. No significant
association was observed between sleep scales scores (including the PDSS)and patients’ age or disease duration.
The SC-NS showed a significant correlation with the question on global
evaluation of nocturnal sleep (r = 0.81) and with item 1 (global quality of
night sleep) of the PDSS (r
= –0.65, p
<0.0001). The correlation between
SC-DS and PDSS item 15 (unexpectedly falling asleep during the day) wasmoderate (r
= –0.52, p
<0.0001), as was the correlation between SCOPA-
Sleep and the PDSS-based questionnaire completed by caregivers (r
–0.50 with the SC-NS; r
= –0.53 with the SC-DS) (Table III).
There were no significant gender-related differences in the SCOPA-Sleep
scores. The SC-NS score displayed a non-statistically significant rising trend
as HY stage increased. The SC-DS registered a non-linear trend, with highest
values in stage 3 (7.75 points) and inferior values in the lower and higherstages (e.g., 2.4 in stage 1 and 5.5 in stage 5) (Kruskal-Wallis, p
Mean SC-NS scores increased significantly with global evaluation of
night sleep (Table IV) (Kruskal-Wallis, p
<0.0001). The SEM was 1.45 for
The correlation coefficients between patients’ HRQL measures and sleep
rating scales (both SC-Sleep and PDSS) were weak overall (r
= –0.06 at
–0.27). The SC-NS and PDSS showed a moderate association with the SC-PS (r
= 0.37 and –0.36; p
= 0.002 and 0.004, respectively).
With respect to the impact of patients’ sleep dysfunction on caregivers’
HRQL, the correlation between patients’ sleep rating scales and caregivers’
HRQL measures ranged from –0.01 (SC-DS and the physical component of
the SF-36) to –0.23 (SC-DS and the EuroQoL tariff). The PDSS-based ques-
Spearman rank correlation coefficient. CISI-PD: Clinical Impression of Severity
Index for Parkinson's Disease; HADS: Hospital Anxiety and Depression Scale;
tionnaire completed by caregivers correlated moderately with the EuroQoL
PDSS: Parkinson's Disease Sleep Scale; SC-NS: SCOPA-Nocturnal sleep; SC-DS:
= 0.34, p
<0.05) and weakly with the other caregiver HRQL parame-
= 0.03-0.29; p
has led to the design of numerous evaluation methods over the
Valid, specific measures are required to assess the diversity of
last five decades . Recent years have witnessed increasing
manifestations that may be present in PD patients. This need
recognition of the importance of a complete evaluation that
SCOPA-Nocturnal sleep score distribution by the anchor question.
As hypothesized, a close association was found between
each SC-Sleep subscale and the respective PDSS parameters
for nocturnal sleep and daytime hypersomnia. The correlation
between SC-NS and the question on global evaluation of
night sleep proved similar to that of the original study (0.81vs. 0.85) . The convergent validity of the SC-Sleep scale is
therefore viewed as satisfactory. As for the other measures,
the SC-NS showed moderate correlations with mood distur-bances and motor complications. In addition, a moderate asso-
ciation was found between the SC-DS and PD severity meas-
ures, suggesting that nocturnal and daytime sleep dysfunctionshave different relationships with the range of aspects evaluated
As in the original study , the SC-Sleep failed to identify
significant differences among patients with different levels of
Test de Kruskal-Wallis, p < 0.0001.
severity or disease duration. Similarly, these differences werenot observed when the PDSS was used, either in this or in otherprevious studies . This suggests that: 1) relationships between
encompasses the great variety of non-motor manifestations that
sleep dysfunction and disease severity, motor or cognitive status
can affect patients’ quality of life [1-3,41].
tend to be loose; 2) the type of sleep disturbance could change
Practically all PD patients suffer night sleep disturbances
over time without significantly modifying total scale scores;
and/or day hypersomnia [4,41]. Useful instruments, capable
or 3) sleep disturbances are present from the beginning of the
of reflecting the type and severity of these dysfunctions and
disease and do not increase despite the progression of the dis-
their response to therapeutic strategies, are therefore regarded
The SC-NS displayed excellent discriminative validity vis-
The first specific scale for assessing sleep disorders in PD
à-vis global evaluation of night sleep. The lack of a similar anchor
(PDSS) was published by Chaudhuri et al in 2002 . Subse-
question in the SC-DS means that this particular attribute can-
quently, the validation of the PDSS was completed in an inde-
not be explored in the same way for this subscale.
pendent study conducted in Spain, after the necessary cross-
The influence of sleep disturbances on PD patients’ HRQL
cultural adaptation . Marinus et al published another spe-
has been highlighted [43-45], but this relationship has yielded
cific scale for evaluation of sleep disturbances in PD, known as
low-to-moderate correlation coefficients between specific
the SC-Sleep . To our knowledge, this scale has, as yet, nei-
measures that evaluated both aspects (PDQ-39 and PDSS) in
ther been subjected to independent validation nor been adapted
previous studies (|r
| = 0.26-0.39) [15,46]. In the present study,
for use in a Spanish setting. The main objective of this study,
while a moderate correlation was observed between the sleep
albeit preliminary, was to assess some basic metric attributes of
scales (SC-NS and PDSS) and the SC-PS, the correlation between
both scales and the EuroQoL was low or nonexistent. Further
Analysis of data quality and acceptability shows that the
studies are called for, in order to apply the data furnished by the
SC-Sleep is a viable scale, with a mild ceiling effect in the SC-
new specific measures and thereby enhance our knowledge of
NS domain (22.1%), in line with the data reported in the origi-
Although patients’ sleep disorders influence caregivers’ sleep
In our study, item 6 of the SC-DS was shown by the scaling
and quality of life , the present study failed to find a signif-
assumptions analysis to be substandard. In contrast, the study
icant association between patients’ sleep disorders and care-
by Marinus et al  showed that all the item-total correlation
givers’ HRQL. However, a PDSS questionnaire adapted for
coefficients exceeded the standard criterion of 0.40. Neverthe-
proxy assessment showed that there was a moderate relation-
less, in view of the differences in size and characteristic of the
ship between the EuroQoL index and caregiver evaluation of
two samples, no conclusion can be drawn on this point.
Both the SC-NS and SC-DS obtained α and item-homo-
The limitations of this study are linked to the characteristics
geneity coefficients higher than the established limit, demon-
of the sample, with scant representation of patients in the most
strating that their internal consistency is satisfactory. However,
advanced stages of the disease and those with the most severe
there was a qualitative difference with respect to the findings by
sleep disturbances. These facts limit the generalizability of the
Marinus et al , according to which α was almost equivalent for
results. Yet the quality of the relevant SC-Sleep metric attrib-
the two subscales (difference = 0.03), with it being slightly high-
utes, assessment of which constituted the main objective of this
er for the SC-DS. Yet, in our study, not only was the difference
pilot study, was nevertheless confirmed. Stability of the meas-
between the subscales greater (0.09), but it was also in favour of
the SC-NS. At all events, both studies coincide in substantiating
The SC-Sleep is a viable scale, with appropriate scaling
the reliability of the two subscales. While the exploratory factor
assumptions, internal consistency, and construct validity. On the
analysis confirmed the unidimensionality of the SC-NS, the fol-
whole, the impact of sleep dysfunctions on patients’ and care-
lowing two factors were identified in the SC-DS: the first
givers’ HRQL proved to be low, yet these relationships should
included items 1 to 3 and could be defined as ‘drowsiness in
be explored by means of specific studies, which have a design
inactivity’; and the second contained items 4 to 6 and was relat-
different to ours and implement newly-developed specific meas-
ed to ‘inappropriate daytime sleepiness’.
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ESPECÍFICA PARA LOS TRASTORNOS DEL SUEÑO
ESPECÍFICA PARA AS PERTURBAÇÕES DO SONO
DE LA ENFERMEDAD DE PARKINSON: SCOPA-SUEÑO
ASSOCIADAS À DOENÇA DE PARKINSON: SCOPA-SONO
Introducción. En la enfermedad de Parkinson (EP) exis-
Introdução. A doença de Parkinson (DP) associa-se a uma
te una alta prevalencia de trastornos del sueño.
elevada prevalência de perturbações do sono.
bar los atributos métricos básicos de la escala SCOPA-sueño para
os atributos métricos básicos da escala SCOPA-sono para doentes
pacientes con EP; objetivo secundario: analizar el impacto del tras-
com DP; objectivo secundário: analisar o impacto das perturbaçõ-
torno del sueño en la calidad de vida relacionada con la salud
es do sono na qualidade de vida relacionada com a saúde (QVRS)
(CVRS) del paciente y de su cuidador principal.
Sujetos y métodos.
do doente e do seu principal cuidador.
Sujeitos e métodos. Foram
68 pacientes con EP y sus cuidadores principales. Se aplicaron:
estudados 68 doentes com DP e respectivos cuidadores. Aplicaram-
Hoehn y Yahr, SCOPA-motor, impresión clínica de gravedad (CISI-
se as escalas: Hoehn e Yahr, SCOPA-motor,
Clinical Impression of
PD), escala PDSS,
Hospital Anxiety and Depression Scale, SCO-
Severity Index for Parkinson’s Disease (CISI-PD), escala PDSS,
PA-psicosocial y EuroQoL. El cuidador cumplimentó un cuestiona-
Hospital Anxiety and Depression Scale, SCOPA-psicosocial e Euro-
rio PDSS sobre el sueño del paciente y las medidas de la CVRS
QoL. O cuidador preencheu um questionário PDSS sobre o sono do
(SF-36, EuroQoL). Se analizaron la aceptabilidad, las asunciones
doente e as medidas da QVRS (SF-36, EuroQoL). Foram analisadas
escalares, la consistencia interna, la validez de constructo y la pre-
a aceitabilidade, as assunções escalares a consistência interna, a
cisión de la SCOPA-sueño.
Resultados. La SCOPA-sueño mostró
validade de construção e a precisão da SCOPA-sono.
aceptabilidad satisfactoria y asunciones escalares. La subescala
SCOPA-sono revelou aceitabilidade satisfatória e assunções das es-
sueño nocturno (SC-Sn) presentó leve efecto techo (22,1%), y la
calas. A subescala sono nocturno (SC-Sn) apresentou um discreto
subescala somnolencia diurna (SC-Sd), defectuosa validez conver-
efeito tecto (22,1%) e a subescala sonolência diurna (SC-Sd) uma
gente del ítem 6; la consistencia interna de ambas resultó satisfac-
validade convergente imperfeita do item 6; a consistência interna de
toria (alfa = 0,84 y 0,75, respectivamente). SC-Sn correlacionó sig-
ambas resultou satisfatória (alfa = 0,84 e 0,75, respectivamente).
nificativamente con la PDSS (
–0,70) y con el cuestionario PDSS
SC-Sn correlacionou-se significativamente com a PDSS (
r = –0,70)
cumplimentado por el cuidador (
–0,53), y fueron menores los
e com o questionário PDSS preenchido pelo cuidador (
r = –0,53), e
valores respectivos para la SC-Sd (
–0,41 y –0,50). Error están-
foram menores os valores respectivos para a SC-Sd (
r = –0,41
dar de la medida: SC-Sn, 1,45; SC-Sd, 1,76. La CVRS del paciente
e –0,50). O erro standard das medidas foi: SC-Sn, 1,45; SC-Sd,
y la del cuidador mostraron una escasa correlación con las me-
1,76. A QVRS do doente e do cuidador revelou uma ténue correla-
didas de sueño.
Conclusiones. La escala SCOPA-sueño es viable,
ção com as medidas do sono.
Conclusões. A escala SCOPA-sono é
consistente y útil para evaluar el trastorno del sueño en pacientes
viável, consistente e útil para avaliar a perturbação do sono em
con EP. La relación entre la CVRS y la alteración del sueño fue
doentes com DP. Detectou-se uma ténue relação entre a QVRS e a
débil. [REV NEUROL 2006; 43: 577-83]
alteração do sono. [REV NEUROL 2006; 43: 577-83]
Palabras clave. Calidad de vida relacionada con la salud. CISI-PD.
Palavras chave. Avaliação. CISI-PD. Doença de Parkinson. Esca-
Enfermedad de Parkinson. Evaluación.
Parkinson’s Disease Rating
la para avaliação da doença de Parkinson. Perturbação do sono.
Scale. SCOPA-sueño. Trastorno del sueño.
Qualidade de vida relacionada com a saúde. SCOPA-sono.
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2ème cycle – MID – item 69 – Symptômes digestifs SYMPTOMES DIGESTIFS : I -Nausées, vomissements 40 % en phase terminale considérés comme * Étirement de la capsule hépatique* Irritation de la muqueuse intestinalemédiastinale (compression du défilé du X)STIMULATION DE LA ZONE GACHETTE DES CHEMOREC(Opiacés, Toxiques, Hypercalcémie, …) 2ème cycle