Psychiatr Q DOI 10.1007/s11126-015-9357-3 ORIGINAL PAPER
Fatigue Experiences Among OCD Outpatients Massimo Pasquini1 • Daria Piacentino1 • Isabella Berardelli1 • Valentina Roselli1 • Annalisa Maraone1 • Lorenzo Tarsitani1 • Massimo Biondi1
Ó Springer Science+Business Media New York 2015
Abstract Patients with OCD are impaired in multiple domains of functioning and quality of life. While associated psychopathology complaints and neuropsychological deficits were reported, the subjective experience of general fatigue and mental fatigue was scarcely investigated. In this single-center case–control study we compared 50 non-depressed OCD outpatients consecutively recruited and 50 panic disorder (PD) outpatients, to determine whether they experienced fatigue differently. Assessment consisted of structured clinical interview for DSM-IV criteria by using the SCID-I and the SCID-II. Symptom severity was assessed using the Yale–Brown Obsessive–Compulsive Scale, the Hamilton Anxiety Rating Scale, the Hamilton Depression Rating Scale, the Clinical Global Impressions Scale, severity and the Global Assessment of Functioning Scale. Fatigue was assessed by using the Multidimensional Fatigue Inventory (MFI). Regarding MFI physical fatigue, an OR of 0.196 (95 % CI 0.080–0.478) was found, suggesting that its presence is associated with lower odds of OCD compared to PD. The same can be said for MFI mental fatigue, as an OR of 0.138 (95 % CI 0.049–0.326) was found, suggesting that its presence is associated with lower odds of OCD. Notably, OCD patients with OCDP co-morbidity reported higher scores of mental fatigue. In this study fatigue, including mental fatigue, seems not to be a prominent experience among adult nondepressed OCD patients. Keywords disorder
Obsessive–compulsive disorder OCD Fatigue Mental fatigue Panic
& Massimo Pasquini [email protected] 1
Department of Neurology and Psychiatry, Sapienza University of Rome, Viale dell’Universita` 30, 00185 Rome, Italy
123
Psychiatr Q
Introduction Obsessive–compulsive disorder (OCD) is a condition with a worldwide estimated prevalence of 1.5–3.0 % [1]. The main symptoms of OCD include intrusive thoughts, urges and images that cause marked anxiety or distress and repetitive mental acts or behavioral rituals which the person feels compelled to perform in order to reduce or prevent the distress provoked by the obsessive thoughts. The current neurobiological model of OCD suggest that intrusive thoughts are assumed to derive from hyperactivity within the orbitofrontal cortex (OFC) caused by deficient striatal function, while compulsions are considered to be the expression of compensatory striatal engagement [2]. The degree of severity of OCD and associated symptoms determine the overall functional impairment and quality of life [3]. Functional impairment may be produced by neuropsychological deficits too, including memory and concentration impairment. Although these deficits were largely studied a clear pattern of conclusions remains controversial [4]. Nevertheless the subjective experience of fatigue and particularly mental fatigue, such as concentration ability or distractibility, among OCD patients was scarcely explored [5], mostly using non-specific broad instruments including, among many others, items regarding fatigue. Fatigue is a symptom that characterizes several psychiatric and neurological disorders. High levels of fatigue were observed in patients with panic disorder (PD) [6]. Fatigue may impact on the overall disability and quality of life of the OCD patients [7]. The aim of this study was to test the hypothesis of an association between OCD and fatigue comparing non-depressed OCD outpatients with a similar group of patients affected by PD We expected OCD patients to experience higher levels of mental fatigue.
Methods Patients The study was conducted between November 2012 and January 2014 at a Psychopharmacology Outpatient Service of a large academic hospital. Fifty-first-visit outpatients with DSM-IV-TR [8] OCD and an equal number of first-visit outpatients with DSM-IV-TR PD were consecutively recruited, over the study period. We selected as a control group patients with PD since they report high levels of fatigue [6] and they generally share with OCD patients similar treatments, SSRIs even if at lower dosages, and psychotherapy. This may reduce the possible confounding effect of treatment on the association under study. Controls were recruited in the same outpatient clinic over the same study period. Inclusion criteria, besides the above-mentioned DSM-IV-TR diagnoses, included: both genders; age range 18–65 years; at least 1-year duration of illness; wish to participate in the study; written informed consent for taking part in the study. Exclusion criteria included: cognitive impairment (e.g., mental retardation, dementia); severe organic disease (e.g., cancer, autoimmune diseases, terminal renal failure); other concurrent psychiatric disorders (e.g., bipolar disorder, psychosis); alcohol or substance abuse except nicotine; non-optimal language knowledge. DSM-IV-TR diagnoses were established after structured interviews with all patients (Structured Clinical Interviews for DSM-IV Axis I and II Disorders; SCID-1 and SCID-2, respectively) [9, 10]. Patients were treated, in the past or currently, either with
123
Psychiatr Q
pharmacotherapy, consisting in SSRIs, or psychotherapy, or a combination of both. A minority of patients did not take any psychotropic medication, nor underwent psychotherapy. Approval from the Hospital Ethical Committee and written informed consent from participants were obtained.
Assessment Instruments A Socio-Demographic and Anamnestic Form to collect patients’ age, gender, nationality, marital status, offspring, level of education, working status, psychiatric familiarity, age of onset of current Axis I and, if any, Axis II psychopathological disorders, past and/or current psychopharmacological treatments. The Yale–Brown Obsessive–Compulsive Scale (Y-BOCS) [11, 12] is a clinician-administered, semi-structured interview designed to assess the type and severity of symptoms in individuals diagnosed with OCD. Responses are given on a 5-point Likert scale, ranging from 0 (‘‘no symptoms’’) to 4 (‘‘extreme symptoms’’), and are used to generate a total Y-BOCS score, ranging 0–40, as well as subscale scores for obsessions and compulsions, ranging 0–20 each. The Multidimensional Fatigue Inventory (MFI) [13] is a self-rated scale designed to measure fatigue. It consists of 20 statements, for which the individual has to indicate on a 5-point Likert scale, ranging from 1 (‘‘completely true’’) to 5 (‘‘completely false’’), to what extent the particular statement applies to him or her. The statements refer to aspects of fatigue experienced during the previous days and are worded in a positive and a negative direction to prevent tendencies towards the response set. Higher scores indicate a higher degree of fatigue, with a score of 20 indicating no fatigue and a score of 100 indicating maximum fatigue. The scale covers five dimensions, corresponding to five subscales, with an equal number of items for each, a score ranging 4–20 and a cut-off C13. The subscales have been postulated on the basis of the ways in which fatigue can be expressed: general fatigue (i.e., general remarks of an individual concerning his/her functioning, e.g., ‘‘I feel rested’’), physical fatigue (i.e., physical sensations, related to the feeling of tiredness), mental fatigue (i.e., cognitive symptoms, such as having difficulty concentrating), reduced motivation (i.e., a lack of motivation to start any activity), and reduced activity (i.e., a frequently occurring, although not necessary consequence of fatigue, namely a reduction in activity). The MFI has been tested for its psychometric properties in cancer patients receiving radiotherapy, patients with chronic fatigue syndrome, medical students, psychology students, army recruits, and junior physicians. The Hamilton Anxiety Rating Scale (HARS) [14] is a clinician-rated scale developed to measure the severity of anxiety symptoms. It consists of 14 items, each defined by a series of symptoms, and measures both psychic anxiety (i.e., mental agitation and psychological distress) and somatic anxiety (i.e., physical complaints related to anxiety). Each item is scored on a Likert scale ranging from 0 (‘‘not present’’) to 4 (‘‘severe’’), with a total score range of 0-56. The cut-off 12 for normality was chosen in accordance with Leentjens et al. [15]. The Hamilton Depression Rating Scale (HDRS) [16] is a clinician-rated scale designed to rate the severity of depression by probing mood, feelings of guilt, suicide ideation, insomnia, agitation or retardation, anxiety, weight loss, and somatic symptoms. Responses are used to generate a total score, ranging 0–40. The Clinical Global Impressions Scale, severity (CGIs) [17] is amongst the most widely used brief assessment tools in psychiatry. It asks the clinician to evaluate the patients’
123
Psychiatr Q
Table 1 Socio-demographic and anamnestic characteristics of OCD patients (N = 50) versus PD patients (N = 50) Variables
OCD patients (N = 50)
PD patients (N = 50)
Test (value)
p value
Age in years [median (Q1–Q3)]
29.5 (23.7–41.5)
33.5 (26.5–45.0)
Mann–Whitney U test (U = 2405.0)
0.409
Male
17 (34 %)
34 (68 %)
v2 test (v2 = 11.565)
0.001
Female
33 (66 %)
16 (32 %)
\8 years
6 (12 %)
1 (2 %)
v2 test (v2 = 3.843)
0.146
9–12 years
7 (14 %)
8 (16 %)
C13 years
37 (74 %)
41 (82 %)
Student
18 (36 %)
15 (30 %)
v2 test (v2 = 6.633)
0.157
Employee
11 (22 %)
17 (34 %)
v2 test (v2 = 2.775)
0.250
Gender [N (%)]
Years of education [N (%)]
Occupation [N (%)]
Self-employed
10 (20 %)
7 (14 %)
Retired
3 (6 %)
8 (16 %)
Unemployed
8 (16 %)
3 (6 %)
Single
30 (60 %)
29 (58 %)
Married/cohabitant
14 (28 %)
19 (38 %)
Marital status [N (%)]
Separated/divorced
6 (12 %)
2 (4 %)
0 (0–0)
0 (0–1)
Mann–Whitney U test (U = 2270.0)
0.079
Yes
21 (42 %)
10 (20 %)
v2 test (v2 = 5.657)
0.017
No
29 (58 %)
40 (80 %)
17 (13.0–20.0)
28 (20.7–35.0)
Mann–Whitney U test (U = 1666.0)
0.0001
v2 test (v2 = 16.333)
0.001
v2 test (v2 = 9.523)
0.023
v2 test (v2 = 12.222)
0.007
Offspring [median (Q1–Q3)] Psychiatric familiarity [N (%)]
Age of onset of axis I disorder [median (Q1–Q3)]
Co-morbid axis II disorder [N (%)] Yes
15 (30 %)
1 (2 %)
No
35 (70 %)
49 (98 %)
None
12 (24 %)
12 (24 %)
Pharmacotherapy (SSRIs)
17 (34 %)
30 (60 %)
Psychotherapy
4 (8 %)
2 (4 %)
Both
17 (34 %)
6 (12 %)
None
4 (8 %)
1 (2 %)
Pharmacotherapy (SSRIs)
25 (50 %)
40 (80 %)
Psychotherapy
5 (10 %)
1 (2 %)
Both
16 (32 %)
8 (16 %)
Past treatment [N (%)]
Current treatment [N (%)]
OCD obsessive–compulsive disorder, PD panic disorder
123
Psychiatr Q
illness severity at the time of assessment, relative to the clinician’s past experience with patients who have the same diagnosis, through a 7-point Likert scale, using a range of responses from 1 (‘‘not at all ill’’) to 7 (‘‘extremely ill’’). The Global Assessment of Functioning Scale (GAF) [18] is a numeric scale, ranging from 0 to 100, used by clinicians to rate subjectively the social, occupational, and psychological functioning of patients on a hypothetical continuum of mental health-illness. The pseudo-continuous scale is subdivided in ten 10-point content layers with higher scores indicating better psycho-socio-occupational functioning [8, p. 34]. The patients’ interviews have been carried-out by certified clinicians whose mean interrater reliability was 0.863 (Fleiss’ kappa).
Statistical Analysis Continuous variables were summarized as median, 1st quartile (Q1) and 3rd quartile (Q3); categorical variables were summarized as absolute and percentage values. Differences in
Table 2 Psychopathological characteristics of OCD patients (N = 50) versus PD patients (N = 50) Variables
OCD patients (N = 50)
PD patients (N = 50)
Y-BOCS total [median (Q1–Q3)]
28.6 (24.7–33.2)
0 (0–0)
Test (value)
p value
Y-BOCS obsessions
14.5 (13.0–19.0)
0 (0-0)
Y-BOCS compulsions
13.5 (11.7–16.0)
0 (0–0)
MFI total [median (Q1–Q3)]
62.0 (67.7–68.0)
63.0 (60.1–65.2)
Mann–Whitney U test (U = 2487.5)
0.798
MFI general fatigue
11.0 (8.0–12.2)
12.0 (7.7–14.0)
Mann–Whitney U test (U = 2339.0)
0.198
MFI physical fatigue
10.0 (9.0–12.0)
13.5 (9.0–14.2)
Mann–Whitney U test (U = 2078.0)
0.002
MFI mental fatigue
10.0 (9.0–11.2)
13.0 (8.0–16.0)
Mann–Whitney U test (U = 2071.0)
0.002
MFI reduced motivation
12.0 (11–0–13.0)
13.0 (11.0–14.0)
Mann–Whitney U test (U = 2341.5)
0.207
MFI reduced activity
11.0 (9.0–14.0)
12.0 (9.0–14– 0)
Mann–Whitney U test (U = 2414.5)
0.445
HARS [median (Q1–Q3)]
8.5 (6.7–12.0)
12.0 (10.0–15.0)
Mann–Whitney U test (U = 1942.5)
0.000
HDRS [median (Q1–Q3)]
7.0 (5.7–12.0)
9.0 (6.0–12.0)
Mann–Whitney U test (U = 2295.0)
0.112
CGIs [median (Q1–Q3)]
4.0 (4.0–5.0)
3.0 (2.0–3.0)
Mann–Whitney U test (U = 3437.5)
0.000
GAF [median (Q1–Q3)]
55.0 (45.0–60.0)
70.0 (70.0–75.0)
Mann–Whitney U test (U = 1552.5)
0.000
CGIs Clinical Global Impressions, severity, GAF Global Assessment of Functioning, HARS Hamilton Anxiety Rating Scale, HDRS Hamilton Depression Rating Scale, MFI Multidimensional Fatigue Inventory, OCD obsessive–compulsive disorder, PD panic disorder, Y-BOCS Yale–Brown Obsessive–Compulsive Scale
123
Psychiatr Q
socio-demographic, anamnestic, and psychopathological characteristics between the two groups of patients—OCD and PD—were determined by non-parametric tests, in particular Mann–Whitney U test for continuous variables and Pearson’s v2 test for categorical variables. Crude odds ratios (OR) were used to estimate the strength of the association between OCD and the main variables of interest, i.e., MFI physical or mental fatigue compared to PD. The 95 % confidence interval (CI) is used to estimate the precision of the estimate of the OR An OR = 1 means that the presence of fatigue is not associated with OCD, an OR [ 1 means that the presence of fatigue is associated with higher odds of OCD, an OR \ 1 means that the presence of fatigue is associated with lower odds of OCD. A large CI indicates a low level of precision of the OR, whereas a small CI indicates a higher precision of the OR When the unity is not included in the interval the estimated OR. Multivariate logistic regression analysis [19] was then used to calculate coefficients and standard errors (SE), in order to estimate the size of the association between OCD and selected study variables, after the confounding effect of covariates was adjusted for, to the extent allowed by the data. ‘‘Predictors’’ of fatigue were regarded as potential confounders and considered actual confounders if their distributions were substantially different in the two study groups, regardless of statistical significance. The cut-off for statistical significance was set at p B 0.05. When reporting results, p values lower or equal to 0.05 were considered as indicative of an association with OCD, whereas p values greater than 0.05 were considered as indicative of no association with OCD. Due consideration was given to associations at the edge of significance. All values were two-sided. Correlations between MFI and Y-BOCS scores on one hand and MFI scores and the type of treatment on the other hand were sought through Pearson’s r. The R statistical software release 2.15.3 [20] was used to perform analyses.
Results Socio-demographic and anamnestic characteristics of the sample are summarized in Table 1. Differently from our expectations, OCD patients showed lower levels of physical [10.0 (9.0–12.0) vs. 13.5 (9.0–14.2)] and mental fatigue [10.0 (9.0–11.2) vs. 13.0 (8.0–16.0)] as compared with patients with PD (Table 2). Table 3 shows the 2 9 2 contingency tables used to calculate the ORs for the association between OCD and MFI physical fatigue and MFI mental fatigue, respectively. Table 3 2 9 2 contingency tables to calculate the odds ratios for the association between OCD and MFI physical fatigue and MFI mental fatigue, respectively OCD
PD
Total
Presence of MFI physical fatigue (C13)
10
28
38
Absence of MFI physical fatigue (\13)
40
22
62
Total
50
50
100
OCD
PD
Total
Presence of MFI mental fatigue (C13)
8
29
37
Absence of MFI mental fatigue (\13)
42
21
63
Total
50
50
100
MFI multidimensional fatigue inventory, OCD obsessive compulsive disorder, PD panic disorder
123
Psychiatr Q
Regarding MFI physical fatigue, an OR of 0.196 (95 % CI 0.080–0.478) was found, suggesting that its presence is associated with lower odds of OCD. The same can be said for MFI mental fatigue, as an OR of 0.138 (95 % CI 0.049–0.326) was found, suggesting that its presence is associated with lower odds of OCD. Table 4 shows the results of univariate and multivariate analysis for determining the association between OCD diagnosis and patients’ gender, psychiatric familiarity, age of onset (1 year increase), co-morbid Axis II disorders, MFI physical fatigue score (\13 vs. C13), MFI mental fatigue score (\13 vs. C13), HARS score (B 12 vs. [12). Coefficients of the multivariate analysis show for any single variable its estimated independent effect after controlling for the confounding effect of all other variables in the model. For the age of onset, the estimated coefficients express the difference between a patient with an onset at x years and another with an onset at x ? 1 year (e.g., between a patient with an age of onset of 20 years and another with an age of onset of 21 years). In the univariate analysis, associations between female gender, positive psychiatric familiarity, presence of comorbid Axis II disorders, lower levels of physical and mental fatigue, as indicated by MFI scores, and OCD were observed. A lower age of onset and lower levels of anxiety, as shown by HARS scores, were associated with OCD, both at the univariate and multivariate analysis (p = 0.001 and p = 0.003 at the latter, respectively). The estimated strengths of the crude associations between OCD and the main study variables (physical and mental fatigue), as expected, were essentially the same whether they were calculated as the crossproduct of the 2 9 2 tables (respectively .20 and .14) or they were estimated from the coefficients of the univariate logistic model (respectively .20 and .15). When the latter method for estimating ORs from the multivariate logistic model was used, the negative association between OCD and physical fatigue was not significant anymore, while the negative association OCD and mental fatigue was at the edge of significance (p value = 0.066). Pearson’s coefficient showed no correlation between MFI and Y-BOCS scale and subscale scores, respectively. Moreover, it showed no correlation between MFI scale
Table 4 Association between obsessive–compulsive disorder, socio-demographic, anamnestic, and psychopathological characteristics Variables
Obsessive–compulsive disorder Univariate analysis Coeff. (SE)
Multivariate analysis p value
Coeff. (SE)
p value 0.057
Gender (male vs. female)
-1.417 (0.425)
0.001***
-1.394 (0.632)
Psychiatric familiarity (yes vs. no)
1.063 (0.455)
0.019*
1.301 (0.705)
0.065
Age of onset of OCD (1 year increase)
-2.357 (0.550)
0.000***
-2.612 (0.779)
0.001***
OCDP (yes vs. no)
3.044 (1.056)
0.004**
1.471 (1.307)
0.260
MFI physical fatigue (\13 vs. C13)
-1.627 (0.454)
0.000***
-1.028 (0.692)
0.137
MFI mental fatigue (\13 vs. C13)
-1.839 (0.466)
0.000***
-1.323 (0.719)
0.066
HARS (B12 vs. [12)
-1.356 (0.464)
0.004**
-2.246 (0.750)
0.003**
Level of significance: * B0.05; ** B0.01; *** B0.001 CGIs Clinical Global Impressions, severity, coeff. coefficient, GAF Global Assessment of Functioning, HARS Hamilton Anxiety Rating Scale, MFI Multidimensional Fatigue Inventory, OCD obsessive–compulsive disorder, OCDP Obsessive Compulsive Personality Disorder, SE standard error
123
Psychiatr Q
and subscale scores and the type of treatment, i.e., no current treatment, current pharmacotherapy, current psychotherapy, current pharmacotherapy plus psychotherapy.
Discussion In this single-center study conducted on a sample of adult non-depressed OCD patients compared with patients with PD, we were unable to find a positive association between OCD and fatigue, as we expected, but rather a negative one. In fact, OCD patients reported low to moderate scores on all the dimension of fatigue investigated with the MFI. In addition, according to our results, the severity of OCD did not affect perception of fatigue. In the multivariate analysis, the negative association between OCD and anxiety remains highly significant (p value = 0.003), the PD subjects having a 9.3 higher probability of being affected by anxiety as compared to OCD cases. A possible explanation for this remarkable difference is the fact that most OCD patients were: treated with SSRI at higher dosage as compared to PD subjects and for a longer period of time since PD cases have a more recent onset of illness (median = 5.5 years) as compared to OCD cases (median = 12.5 years). Differently from our expectations, impairment in mental fatigue was not found, given that the subscale mental fatigue of the MFI investigates concentration ability or distractibility. Deficits in memory and attention and their subdomains were largely ascertained in OCD [4], while the self-perception of concentration impairment was not observed in our study. Of some interest is the finding that OCD patients with OCDP co-morbidity reported high scores of mental fatigue. This because non-depressive ruminative thoughts may have a huge role in concentration impairment. Several explanations might underlie these negative findings. Firstly, OCD patients were not depressed; secondly, more than 80 % of them were treated with SSRIs and 10 % of them with psychotherapy alone. We could assume that depression determines a higher perception of mental fatigue than obsessions and compulsions do. Thirdly, MFI scores general fatigue, physical fatigue, and reduced activity were significantly higher in PD patients compared to healthy controls in a Japanese study [6]. Last, we may speculate that MFI alone, being a self-report instrument, is not so accurate in determining mental fatigue among these patients. In any case, we found higher subscales scores in PD patients, including mental fatigue ones. We did our best, in the study design and in the way patients were recruited, to minimize the presence of selection bias, but we recognize that bias, in particular Berkson’s bias, can never be ruled out completely. We acknowledge that this can be regarded as a study limitation. As far as information bias is concerned, we assume that its probability has been maintained low by the fact that cases and controls were recruited from the same trained study associates using identical instruments for collecting information, in the same clinic, over the same study period. Misclassification of cases and controls is also very unlikely, given type and number of ad hoc diagnostic instruments adopted. Confounding has been controlled for, to the extent possible, by multivariate logistic analysis. In any case it cannot possibly be an explanation for the observed association, given its size. The other limitation is represented by the less than ideal statistical power, which, however is less of a problem if, in drawing inferences, one is not too obstinate with testing, which makes a lot of sense
123
Psychiatr Q
before data collection, and consider estimating, which seems to us more appropriate and commonsensical in front of the data. In summary, fatigue, including mental fatigue, seems not to be a prominent experience among adult non-depressed OCD patients. Differently, patients with OCD plus OCDP experience a high degree of mental fatigue intended as distractibility and poor concentration. Conflict of interest Pasquini M, Tarsitani L, Berardelli I, Roselli V, Maraone A, Piacentino D, and Biondi M declare that they have no conflict of interest.
References 1. Ruscio AM, Stein DJ, Chiu WT, Kessler RC. The epidemiology of obsessive-compulsive disorder in the National Comorbidity Survey Replication. Molecular Psychiatry 15:53–63, 2010. 2. Deckersbach T, Dougherty DD, Rauch SL. Functional imaging of mood and anxiety disorders. Journal of Neuroimaging 16:1–10, 2006. 3. Jacoby RJ, Leonard RC, Riemann BC, Abramowitz JS. Predictors of quality of life and functional impairment in Obsessive-Compulsive Disorder. Comprehensive Psychiatry 55:1195–1202, 2014. 4. Abramovitch A, Abramowitz JS, Mittelman A. The neuropsychology of adult obsessive–compulsive disorder: A meta-analysis. Clinical Psychology Review 33:1163–1171, 2013. 5. Gros DF, Magruder KM, Frueh BC. Obsessive compulsive disorder in veterans in primary care: prevalence and impairment. General Hospital Psychiatry 35:71–73, 2013. 6. Kaiya H, Sugaya N, Iwasa R, Tochigi M. Characteristics of fatigue in panic disorder patients. Psychiatry and Clinical Neuroscience 62:234–237, 2008. 7. Subramaniam M, Soh P, Vaingankar JA, Picco L, Chong SA. Quality of life in obsessive-compulsive disorder: impact of the disorder and of treatment. CNS Drugs 27:367–383, 2013. 8. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Text Revision. Washington, American Psychiatric Press, 2000. 9. First MB, Spitzer RL, Gibbon M, Williams JBW. Structured Clinical Interview for DSM-IV Axis I Disorders (SCID I), Research Version, Patient Edition. New York, Biometric Research, New York State Psychiatric Institute, A1–A46, 2002. 10. First MB, Gibbon M, Spitzer RL, Williams JBW, Benjamin LS. Structured Clinical Interview for DSMIV Axis II Personality Disorders (SCID-II). Washington, American Psychiatric Press, Inc., 1997. 11. Goodman WK, Price LH, Rasmussen SA, Mazure C, Fleischmann RL, Hill CL et al. The Yale–Brown Obsessive Compulsive Scale: I. Development, use, and reliability. Archives of General Psychiatry 46:1006–1011, 1989. 12. Goodman WK, Price LH, Rasmussen SA, Mazure C, Delgado P, Heninger GR et al. The Yale–Brown Obsessive Compulsive Scale: II. Validity. Archives of General Psychiatry 46:1012–1016, 1989. 13. Smets EMA, Garssen B, Bonke B, De Haes JCJM. The Multidimensional Fatigue Inventory (MFI). Psychometric qualities of an instrument to assess fatigue. Journal of Psychosomatic Research 39:315–325, 1995. 14. Hamilton M. The assessment of anxiety states by rating. British Journal of Medical Psychology 32:50–55, 1959. 15. Leentjens AFG, Dujardin K, Marsh L, Richard IH, Starkstein SE, Martinez-Martin P. Anxiety rating scales in Parkinson’s disease: a validation study of the Hamilton Anxiety Scale, the Beck Anxiety Inventory and the Hospital Anxiety and Depression Scale. Movement Disorders 26:407–415, 2011. 16. Hamilton M. A rating scale for depression. Journal of Neurology, Neurosurgery, and Psychiatry 23: 56–62, 1960. 17. Guy W. ECDEU Assessment Manual of Psychopharmacology—Revised (DHEW Publ No ADM 76-338). Rockville, MD: Department of Health, Education, and Welfare, Public Health Service, Alcohol, Drug Abuse, and Mental Health Administration, NIMH Psychopharmacology Research Branch, Division of Extramural Research Programs, pp. 218–22, 1976. 18. Endicott J, Spitzer RL, Fleiss JL. The global assessment scale. A procedure for measuring overall severity of psychiatric disturbance. Archives of General Psychiatry 33:766–71, 1976. 19. Hosmer DW, Lemeshow S. Applied Logistic Regression. New York, Wiley, 1989.
123
Psychiatr Q 20. R Development Core Team: R. A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2013.
Massimo Pasquini, MD born in Rome, Italy, on July 20 1973. Psychiatrist at the Academic Hospital Umberto I Policlinico di Roma, Sapienza University of Rome. Adjunct Professor of Psychiatry, Sapienza University of Rome. Coordinator of the Outpatient Service for Psycho-Oncology, Policlinico Umberto I, Rome. He has authored and coauthored around 54 papers in international peer reviewed journals (H index 14, Scopus 2014), book chapters and many presentations and posters at national and international congresses. Daria Piacentino, MD born in Rome, Italy, on May 22 1981. Doctor at the Psychiatric Care Unit of Sant’Andrea Hospital, Rome, Italy. Research fellow at NESMOS (Neuroscience, Mental Health and Sensory Organs) Department, Sapienza University of Rome, Rome, Italy. PhD student in Clinical-Experimental Neurosciences and Psychiatry, Sapienza University of Rome, Rome, Italy. She has authored and coauthored around 10 papers in international peer reviewed journals (H index 2, Scopus 2014), book chapters and many presentations and posters at national and international congresses. Isabella Berardelli, MD born in Rome, Italy, on October 20-1982. Psychiatrist at the Academic Hospital Umberto I Policlinico di Roma, Sapienza University of Rome. Phd trainig student in Neuroscience, Sapienza University of Rome. Clinical fellow of the Outpatient Service for Psycho-Oncology, Policlinico Umberto I, Rome. She has authored and coauthored around 20 papers national and international peer reviewed journals, book chapters and many presentations and posters at national and international congresses. Valentina Roselli, MD born in Civitavecchia, Italy, on April 24 1984. Psychiatrist fellow at Sapienza University of Rome, Policlinic Umberto I, Rome, Italy, on going. Involved in clinical and research activities concerning psychiatric disorder in Academic Hospital Umberto I Policlinico di Roma. She has coauthored around 7 papers in international peer reviewed journals. Annalisa Maraone, MD born in Cassino (Frosinone), Italy, on June 05 1983. Psychiatrist fellow at Sapienza University of Rome, Policlinic Umberto I, Rome, Italy, on going. Reviewer for the Journal ‘‘Rivista di Psichiatria’’, untill 2013. Coauthored for around 6 papers in national and international journals and for some posters at national and international congresses. Lorenzo Tarsitani, MD born in Rome, Italy, on May 11 1974. Psychiatrist at the Academic Hospital Umberto I Policlinico di Roma, Sapienza University of Rome. Adjunct Professor of Psychiatry, Sapienza University of Rome. Coordinator of the Outpatient Service for Migration Psychiatry, Policlinico Umberto I, Rome. He has authored and coauthored around 48 papers in international peer reviewed journals (H index 9, Scopus 2014), book chapters and many presentations and posters at national and international congresses. Massimo Biondi, MD Full Professor of Psychiatry and Head of the Psychiatry and Psychopharmacology Unit; since 2007 Director of the Postgraduate School in Psychiatry, same University. Chief of the Psychiatry and Mental Health Area, Policlinico Umberto I, 1200 beds; Head of the Psychiatric Intensive Care Unit. Author of four and editor of 14 books, of 350 scientific publications, about 90 in English in international journals; H index 21; IF 180 last ten years. Chief Editor of Rivista di Psichiatria, a leader journal in Italy, listed in MEDLINE/PubMed, Current Contents, Excertpta Medica/EMBASE, PsychInfo; Chief Editor of the journal Medicina Psicosomatica, official journal of the Italian Society of Psychosomatic Medicine, listed in Excerpta Medica/EMBASE and PsycINfo; Assistant Editor of The American Psychiatric Publishing; Member of the Editorial Board of the journal Psychotherapy and Psychosomatics (Karger, Basel); Memberships. International Member of the American Psychiatric Association.
123
Fatigue Experiences Among OCD Outpatients Massimo Pasquini1 • Daria Piacentino1 • Isabella Berardelli1 • Valentina Roselli1 • Annalisa Maraone1 • Lorenzo Tarsitani1 • Massimo Biondi1
Ó Springer Science+Business Media New York 2015
Abstract Patients with OCD are impaired in multiple domains of functioning and quality of life. While associated psychopathology complaints and neuropsychological deficits were reported, the subjective experience of general fatigue and mental fatigue was scarcely investigated. In this single-center case–control study we compared 50 non-depressed OCD outpatients consecutively recruited and 50 panic disorder (PD) outpatients, to determine whether they experienced fatigue differently. Assessment consisted of structured clinical interview for DSM-IV criteria by using the SCID-I and the SCID-II. Symptom severity was assessed using the Yale–Brown Obsessive–Compulsive Scale, the Hamilton Anxiety Rating Scale, the Hamilton Depression Rating Scale, the Clinical Global Impressions Scale, severity and the Global Assessment of Functioning Scale. Fatigue was assessed by using the Multidimensional Fatigue Inventory (MFI). Regarding MFI physical fatigue, an OR of 0.196 (95 % CI 0.080–0.478) was found, suggesting that its presence is associated with lower odds of OCD compared to PD. The same can be said for MFI mental fatigue, as an OR of 0.138 (95 % CI 0.049–0.326) was found, suggesting that its presence is associated with lower odds of OCD. Notably, OCD patients with OCDP co-morbidity reported higher scores of mental fatigue. In this study fatigue, including mental fatigue, seems not to be a prominent experience among adult nondepressed OCD patients. Keywords disorder
Obsessive–compulsive disorder OCD Fatigue Mental fatigue Panic
& Massimo Pasquini [email protected] 1
Department of Neurology and Psychiatry, Sapienza University of Rome, Viale dell’Universita` 30, 00185 Rome, Italy
123
Psychiatr Q
Introduction Obsessive–compulsive disorder (OCD) is a condition with a worldwide estimated prevalence of 1.5–3.0 % [1]. The main symptoms of OCD include intrusive thoughts, urges and images that cause marked anxiety or distress and repetitive mental acts or behavioral rituals which the person feels compelled to perform in order to reduce or prevent the distress provoked by the obsessive thoughts. The current neurobiological model of OCD suggest that intrusive thoughts are assumed to derive from hyperactivity within the orbitofrontal cortex (OFC) caused by deficient striatal function, while compulsions are considered to be the expression of compensatory striatal engagement [2]. The degree of severity of OCD and associated symptoms determine the overall functional impairment and quality of life [3]. Functional impairment may be produced by neuropsychological deficits too, including memory and concentration impairment. Although these deficits were largely studied a clear pattern of conclusions remains controversial [4]. Nevertheless the subjective experience of fatigue and particularly mental fatigue, such as concentration ability or distractibility, among OCD patients was scarcely explored [5], mostly using non-specific broad instruments including, among many others, items regarding fatigue. Fatigue is a symptom that characterizes several psychiatric and neurological disorders. High levels of fatigue were observed in patients with panic disorder (PD) [6]. Fatigue may impact on the overall disability and quality of life of the OCD patients [7]. The aim of this study was to test the hypothesis of an association between OCD and fatigue comparing non-depressed OCD outpatients with a similar group of patients affected by PD We expected OCD patients to experience higher levels of mental fatigue.
Methods Patients The study was conducted between November 2012 and January 2014 at a Psychopharmacology Outpatient Service of a large academic hospital. Fifty-first-visit outpatients with DSM-IV-TR [8] OCD and an equal number of first-visit outpatients with DSM-IV-TR PD were consecutively recruited, over the study period. We selected as a control group patients with PD since they report high levels of fatigue [6] and they generally share with OCD patients similar treatments, SSRIs even if at lower dosages, and psychotherapy. This may reduce the possible confounding effect of treatment on the association under study. Controls were recruited in the same outpatient clinic over the same study period. Inclusion criteria, besides the above-mentioned DSM-IV-TR diagnoses, included: both genders; age range 18–65 years; at least 1-year duration of illness; wish to participate in the study; written informed consent for taking part in the study. Exclusion criteria included: cognitive impairment (e.g., mental retardation, dementia); severe organic disease (e.g., cancer, autoimmune diseases, terminal renal failure); other concurrent psychiatric disorders (e.g., bipolar disorder, psychosis); alcohol or substance abuse except nicotine; non-optimal language knowledge. DSM-IV-TR diagnoses were established after structured interviews with all patients (Structured Clinical Interviews for DSM-IV Axis I and II Disorders; SCID-1 and SCID-2, respectively) [9, 10]. Patients were treated, in the past or currently, either with
123
Psychiatr Q
pharmacotherapy, consisting in SSRIs, or psychotherapy, or a combination of both. A minority of patients did not take any psychotropic medication, nor underwent psychotherapy. Approval from the Hospital Ethical Committee and written informed consent from participants were obtained.
Assessment Instruments A Socio-Demographic and Anamnestic Form to collect patients’ age, gender, nationality, marital status, offspring, level of education, working status, psychiatric familiarity, age of onset of current Axis I and, if any, Axis II psychopathological disorders, past and/or current psychopharmacological treatments. The Yale–Brown Obsessive–Compulsive Scale (Y-BOCS) [11, 12] is a clinician-administered, semi-structured interview designed to assess the type and severity of symptoms in individuals diagnosed with OCD. Responses are given on a 5-point Likert scale, ranging from 0 (‘‘no symptoms’’) to 4 (‘‘extreme symptoms’’), and are used to generate a total Y-BOCS score, ranging 0–40, as well as subscale scores for obsessions and compulsions, ranging 0–20 each. The Multidimensional Fatigue Inventory (MFI) [13] is a self-rated scale designed to measure fatigue. It consists of 20 statements, for which the individual has to indicate on a 5-point Likert scale, ranging from 1 (‘‘completely true’’) to 5 (‘‘completely false’’), to what extent the particular statement applies to him or her. The statements refer to aspects of fatigue experienced during the previous days and are worded in a positive and a negative direction to prevent tendencies towards the response set. Higher scores indicate a higher degree of fatigue, with a score of 20 indicating no fatigue and a score of 100 indicating maximum fatigue. The scale covers five dimensions, corresponding to five subscales, with an equal number of items for each, a score ranging 4–20 and a cut-off C13. The subscales have been postulated on the basis of the ways in which fatigue can be expressed: general fatigue (i.e., general remarks of an individual concerning his/her functioning, e.g., ‘‘I feel rested’’), physical fatigue (i.e., physical sensations, related to the feeling of tiredness), mental fatigue (i.e., cognitive symptoms, such as having difficulty concentrating), reduced motivation (i.e., a lack of motivation to start any activity), and reduced activity (i.e., a frequently occurring, although not necessary consequence of fatigue, namely a reduction in activity). The MFI has been tested for its psychometric properties in cancer patients receiving radiotherapy, patients with chronic fatigue syndrome, medical students, psychology students, army recruits, and junior physicians. The Hamilton Anxiety Rating Scale (HARS) [14] is a clinician-rated scale developed to measure the severity of anxiety symptoms. It consists of 14 items, each defined by a series of symptoms, and measures both psychic anxiety (i.e., mental agitation and psychological distress) and somatic anxiety (i.e., physical complaints related to anxiety). Each item is scored on a Likert scale ranging from 0 (‘‘not present’’) to 4 (‘‘severe’’), with a total score range of 0-56. The cut-off 12 for normality was chosen in accordance with Leentjens et al. [15]. The Hamilton Depression Rating Scale (HDRS) [16] is a clinician-rated scale designed to rate the severity of depression by probing mood, feelings of guilt, suicide ideation, insomnia, agitation or retardation, anxiety, weight loss, and somatic symptoms. Responses are used to generate a total score, ranging 0–40. The Clinical Global Impressions Scale, severity (CGIs) [17] is amongst the most widely used brief assessment tools in psychiatry. It asks the clinician to evaluate the patients’
123
Psychiatr Q
Table 1 Socio-demographic and anamnestic characteristics of OCD patients (N = 50) versus PD patients (N = 50) Variables
OCD patients (N = 50)
PD patients (N = 50)
Test (value)
p value
Age in years [median (Q1–Q3)]
29.5 (23.7–41.5)
33.5 (26.5–45.0)
Mann–Whitney U test (U = 2405.0)
0.409
Male
17 (34 %)
34 (68 %)
v2 test (v2 = 11.565)
0.001
Female
33 (66 %)
16 (32 %)
\8 years
6 (12 %)
1 (2 %)
v2 test (v2 = 3.843)
0.146
9–12 years
7 (14 %)
8 (16 %)
C13 years
37 (74 %)
41 (82 %)
Student
18 (36 %)
15 (30 %)
v2 test (v2 = 6.633)
0.157
Employee
11 (22 %)
17 (34 %)
v2 test (v2 = 2.775)
0.250
Gender [N (%)]
Years of education [N (%)]
Occupation [N (%)]
Self-employed
10 (20 %)
7 (14 %)
Retired
3 (6 %)
8 (16 %)
Unemployed
8 (16 %)
3 (6 %)
Single
30 (60 %)
29 (58 %)
Married/cohabitant
14 (28 %)
19 (38 %)
Marital status [N (%)]
Separated/divorced
6 (12 %)
2 (4 %)
0 (0–0)
0 (0–1)
Mann–Whitney U test (U = 2270.0)
0.079
Yes
21 (42 %)
10 (20 %)
v2 test (v2 = 5.657)
0.017
No
29 (58 %)
40 (80 %)
17 (13.0–20.0)
28 (20.7–35.0)
Mann–Whitney U test (U = 1666.0)
0.0001
v2 test (v2 = 16.333)
0.001
v2 test (v2 = 9.523)
0.023
v2 test (v2 = 12.222)
0.007
Offspring [median (Q1–Q3)] Psychiatric familiarity [N (%)]
Age of onset of axis I disorder [median (Q1–Q3)]
Co-morbid axis II disorder [N (%)] Yes
15 (30 %)
1 (2 %)
No
35 (70 %)
49 (98 %)
None
12 (24 %)
12 (24 %)
Pharmacotherapy (SSRIs)
17 (34 %)
30 (60 %)
Psychotherapy
4 (8 %)
2 (4 %)
Both
17 (34 %)
6 (12 %)
None
4 (8 %)
1 (2 %)
Pharmacotherapy (SSRIs)
25 (50 %)
40 (80 %)
Psychotherapy
5 (10 %)
1 (2 %)
Both
16 (32 %)
8 (16 %)
Past treatment [N (%)]
Current treatment [N (%)]
OCD obsessive–compulsive disorder, PD panic disorder
123
Psychiatr Q
illness severity at the time of assessment, relative to the clinician’s past experience with patients who have the same diagnosis, through a 7-point Likert scale, using a range of responses from 1 (‘‘not at all ill’’) to 7 (‘‘extremely ill’’). The Global Assessment of Functioning Scale (GAF) [18] is a numeric scale, ranging from 0 to 100, used by clinicians to rate subjectively the social, occupational, and psychological functioning of patients on a hypothetical continuum of mental health-illness. The pseudo-continuous scale is subdivided in ten 10-point content layers with higher scores indicating better psycho-socio-occupational functioning [8, p. 34]. The patients’ interviews have been carried-out by certified clinicians whose mean interrater reliability was 0.863 (Fleiss’ kappa).
Statistical Analysis Continuous variables were summarized as median, 1st quartile (Q1) and 3rd quartile (Q3); categorical variables were summarized as absolute and percentage values. Differences in
Table 2 Psychopathological characteristics of OCD patients (N = 50) versus PD patients (N = 50) Variables
OCD patients (N = 50)
PD patients (N = 50)
Y-BOCS total [median (Q1–Q3)]
28.6 (24.7–33.2)
0 (0–0)
Test (value)
p value
Y-BOCS obsessions
14.5 (13.0–19.0)
0 (0-0)
Y-BOCS compulsions
13.5 (11.7–16.0)
0 (0–0)
MFI total [median (Q1–Q3)]
62.0 (67.7–68.0)
63.0 (60.1–65.2)
Mann–Whitney U test (U = 2487.5)
0.798
MFI general fatigue
11.0 (8.0–12.2)
12.0 (7.7–14.0)
Mann–Whitney U test (U = 2339.0)
0.198
MFI physical fatigue
10.0 (9.0–12.0)
13.5 (9.0–14.2)
Mann–Whitney U test (U = 2078.0)
0.002
MFI mental fatigue
10.0 (9.0–11.2)
13.0 (8.0–16.0)
Mann–Whitney U test (U = 2071.0)
0.002
MFI reduced motivation
12.0 (11–0–13.0)
13.0 (11.0–14.0)
Mann–Whitney U test (U = 2341.5)
0.207
MFI reduced activity
11.0 (9.0–14.0)
12.0 (9.0–14– 0)
Mann–Whitney U test (U = 2414.5)
0.445
HARS [median (Q1–Q3)]
8.5 (6.7–12.0)
12.0 (10.0–15.0)
Mann–Whitney U test (U = 1942.5)
0.000
HDRS [median (Q1–Q3)]
7.0 (5.7–12.0)
9.0 (6.0–12.0)
Mann–Whitney U test (U = 2295.0)
0.112
CGIs [median (Q1–Q3)]
4.0 (4.0–5.0)
3.0 (2.0–3.0)
Mann–Whitney U test (U = 3437.5)
0.000
GAF [median (Q1–Q3)]
55.0 (45.0–60.0)
70.0 (70.0–75.0)
Mann–Whitney U test (U = 1552.5)
0.000
CGIs Clinical Global Impressions, severity, GAF Global Assessment of Functioning, HARS Hamilton Anxiety Rating Scale, HDRS Hamilton Depression Rating Scale, MFI Multidimensional Fatigue Inventory, OCD obsessive–compulsive disorder, PD panic disorder, Y-BOCS Yale–Brown Obsessive–Compulsive Scale
123
Psychiatr Q
socio-demographic, anamnestic, and psychopathological characteristics between the two groups of patients—OCD and PD—were determined by non-parametric tests, in particular Mann–Whitney U test for continuous variables and Pearson’s v2 test for categorical variables. Crude odds ratios (OR) were used to estimate the strength of the association between OCD and the main variables of interest, i.e., MFI physical or mental fatigue compared to PD. The 95 % confidence interval (CI) is used to estimate the precision of the estimate of the OR An OR = 1 means that the presence of fatigue is not associated with OCD, an OR [ 1 means that the presence of fatigue is associated with higher odds of OCD, an OR \ 1 means that the presence of fatigue is associated with lower odds of OCD. A large CI indicates a low level of precision of the OR, whereas a small CI indicates a higher precision of the OR When the unity is not included in the interval the estimated OR. Multivariate logistic regression analysis [19] was then used to calculate coefficients and standard errors (SE), in order to estimate the size of the association between OCD and selected study variables, after the confounding effect of covariates was adjusted for, to the extent allowed by the data. ‘‘Predictors’’ of fatigue were regarded as potential confounders and considered actual confounders if their distributions were substantially different in the two study groups, regardless of statistical significance. The cut-off for statistical significance was set at p B 0.05. When reporting results, p values lower or equal to 0.05 were considered as indicative of an association with OCD, whereas p values greater than 0.05 were considered as indicative of no association with OCD. Due consideration was given to associations at the edge of significance. All values were two-sided. Correlations between MFI and Y-BOCS scores on one hand and MFI scores and the type of treatment on the other hand were sought through Pearson’s r. The R statistical software release 2.15.3 [20] was used to perform analyses.
Results Socio-demographic and anamnestic characteristics of the sample are summarized in Table 1. Differently from our expectations, OCD patients showed lower levels of physical [10.0 (9.0–12.0) vs. 13.5 (9.0–14.2)] and mental fatigue [10.0 (9.0–11.2) vs. 13.0 (8.0–16.0)] as compared with patients with PD (Table 2). Table 3 shows the 2 9 2 contingency tables used to calculate the ORs for the association between OCD and MFI physical fatigue and MFI mental fatigue, respectively. Table 3 2 9 2 contingency tables to calculate the odds ratios for the association between OCD and MFI physical fatigue and MFI mental fatigue, respectively OCD
PD
Total
Presence of MFI physical fatigue (C13)
10
28
38
Absence of MFI physical fatigue (\13)
40
22
62
Total
50
50
100
OCD
PD
Total
Presence of MFI mental fatigue (C13)
8
29
37
Absence of MFI mental fatigue (\13)
42
21
63
Total
50
50
100
MFI multidimensional fatigue inventory, OCD obsessive compulsive disorder, PD panic disorder
123
Psychiatr Q
Regarding MFI physical fatigue, an OR of 0.196 (95 % CI 0.080–0.478) was found, suggesting that its presence is associated with lower odds of OCD. The same can be said for MFI mental fatigue, as an OR of 0.138 (95 % CI 0.049–0.326) was found, suggesting that its presence is associated with lower odds of OCD. Table 4 shows the results of univariate and multivariate analysis for determining the association between OCD diagnosis and patients’ gender, psychiatric familiarity, age of onset (1 year increase), co-morbid Axis II disorders, MFI physical fatigue score (\13 vs. C13), MFI mental fatigue score (\13 vs. C13), HARS score (B 12 vs. [12). Coefficients of the multivariate analysis show for any single variable its estimated independent effect after controlling for the confounding effect of all other variables in the model. For the age of onset, the estimated coefficients express the difference between a patient with an onset at x years and another with an onset at x ? 1 year (e.g., between a patient with an age of onset of 20 years and another with an age of onset of 21 years). In the univariate analysis, associations between female gender, positive psychiatric familiarity, presence of comorbid Axis II disorders, lower levels of physical and mental fatigue, as indicated by MFI scores, and OCD were observed. A lower age of onset and lower levels of anxiety, as shown by HARS scores, were associated with OCD, both at the univariate and multivariate analysis (p = 0.001 and p = 0.003 at the latter, respectively). The estimated strengths of the crude associations between OCD and the main study variables (physical and mental fatigue), as expected, were essentially the same whether they were calculated as the crossproduct of the 2 9 2 tables (respectively .20 and .14) or they were estimated from the coefficients of the univariate logistic model (respectively .20 and .15). When the latter method for estimating ORs from the multivariate logistic model was used, the negative association between OCD and physical fatigue was not significant anymore, while the negative association OCD and mental fatigue was at the edge of significance (p value = 0.066). Pearson’s coefficient showed no correlation between MFI and Y-BOCS scale and subscale scores, respectively. Moreover, it showed no correlation between MFI scale
Table 4 Association between obsessive–compulsive disorder, socio-demographic, anamnestic, and psychopathological characteristics Variables
Obsessive–compulsive disorder Univariate analysis Coeff. (SE)
Multivariate analysis p value
Coeff. (SE)
p value 0.057
Gender (male vs. female)
-1.417 (0.425)
0.001***
-1.394 (0.632)
Psychiatric familiarity (yes vs. no)
1.063 (0.455)
0.019*
1.301 (0.705)
0.065
Age of onset of OCD (1 year increase)
-2.357 (0.550)
0.000***
-2.612 (0.779)
0.001***
OCDP (yes vs. no)
3.044 (1.056)
0.004**
1.471 (1.307)
0.260
MFI physical fatigue (\13 vs. C13)
-1.627 (0.454)
0.000***
-1.028 (0.692)
0.137
MFI mental fatigue (\13 vs. C13)
-1.839 (0.466)
0.000***
-1.323 (0.719)
0.066
HARS (B12 vs. [12)
-1.356 (0.464)
0.004**
-2.246 (0.750)
0.003**
Level of significance: * B0.05; ** B0.01; *** B0.001 CGIs Clinical Global Impressions, severity, coeff. coefficient, GAF Global Assessment of Functioning, HARS Hamilton Anxiety Rating Scale, MFI Multidimensional Fatigue Inventory, OCD obsessive–compulsive disorder, OCDP Obsessive Compulsive Personality Disorder, SE standard error
123
Psychiatr Q
and subscale scores and the type of treatment, i.e., no current treatment, current pharmacotherapy, current psychotherapy, current pharmacotherapy plus psychotherapy.
Discussion In this single-center study conducted on a sample of adult non-depressed OCD patients compared with patients with PD, we were unable to find a positive association between OCD and fatigue, as we expected, but rather a negative one. In fact, OCD patients reported low to moderate scores on all the dimension of fatigue investigated with the MFI. In addition, according to our results, the severity of OCD did not affect perception of fatigue. In the multivariate analysis, the negative association between OCD and anxiety remains highly significant (p value = 0.003), the PD subjects having a 9.3 higher probability of being affected by anxiety as compared to OCD cases. A possible explanation for this remarkable difference is the fact that most OCD patients were: treated with SSRI at higher dosage as compared to PD subjects and for a longer period of time since PD cases have a more recent onset of illness (median = 5.5 years) as compared to OCD cases (median = 12.5 years). Differently from our expectations, impairment in mental fatigue was not found, given that the subscale mental fatigue of the MFI investigates concentration ability or distractibility. Deficits in memory and attention and their subdomains were largely ascertained in OCD [4], while the self-perception of concentration impairment was not observed in our study. Of some interest is the finding that OCD patients with OCDP co-morbidity reported high scores of mental fatigue. This because non-depressive ruminative thoughts may have a huge role in concentration impairment. Several explanations might underlie these negative findings. Firstly, OCD patients were not depressed; secondly, more than 80 % of them were treated with SSRIs and 10 % of them with psychotherapy alone. We could assume that depression determines a higher perception of mental fatigue than obsessions and compulsions do. Thirdly, MFI scores general fatigue, physical fatigue, and reduced activity were significantly higher in PD patients compared to healthy controls in a Japanese study [6]. Last, we may speculate that MFI alone, being a self-report instrument, is not so accurate in determining mental fatigue among these patients. In any case, we found higher subscales scores in PD patients, including mental fatigue ones. We did our best, in the study design and in the way patients were recruited, to minimize the presence of selection bias, but we recognize that bias, in particular Berkson’s bias, can never be ruled out completely. We acknowledge that this can be regarded as a study limitation. As far as information bias is concerned, we assume that its probability has been maintained low by the fact that cases and controls were recruited from the same trained study associates using identical instruments for collecting information, in the same clinic, over the same study period. Misclassification of cases and controls is also very unlikely, given type and number of ad hoc diagnostic instruments adopted. Confounding has been controlled for, to the extent possible, by multivariate logistic analysis. In any case it cannot possibly be an explanation for the observed association, given its size. The other limitation is represented by the less than ideal statistical power, which, however is less of a problem if, in drawing inferences, one is not too obstinate with testing, which makes a lot of sense
123
Psychiatr Q
before data collection, and consider estimating, which seems to us more appropriate and commonsensical in front of the data. In summary, fatigue, including mental fatigue, seems not to be a prominent experience among adult non-depressed OCD patients. Differently, patients with OCD plus OCDP experience a high degree of mental fatigue intended as distractibility and poor concentration. Conflict of interest Pasquini M, Tarsitani L, Berardelli I, Roselli V, Maraone A, Piacentino D, and Biondi M declare that they have no conflict of interest.
References 1. Ruscio AM, Stein DJ, Chiu WT, Kessler RC. The epidemiology of obsessive-compulsive disorder in the National Comorbidity Survey Replication. Molecular Psychiatry 15:53–63, 2010. 2. Deckersbach T, Dougherty DD, Rauch SL. Functional imaging of mood and anxiety disorders. Journal of Neuroimaging 16:1–10, 2006. 3. Jacoby RJ, Leonard RC, Riemann BC, Abramowitz JS. Predictors of quality of life and functional impairment in Obsessive-Compulsive Disorder. Comprehensive Psychiatry 55:1195–1202, 2014. 4. Abramovitch A, Abramowitz JS, Mittelman A. The neuropsychology of adult obsessive–compulsive disorder: A meta-analysis. Clinical Psychology Review 33:1163–1171, 2013. 5. Gros DF, Magruder KM, Frueh BC. Obsessive compulsive disorder in veterans in primary care: prevalence and impairment. General Hospital Psychiatry 35:71–73, 2013. 6. Kaiya H, Sugaya N, Iwasa R, Tochigi M. Characteristics of fatigue in panic disorder patients. Psychiatry and Clinical Neuroscience 62:234–237, 2008. 7. Subramaniam M, Soh P, Vaingankar JA, Picco L, Chong SA. Quality of life in obsessive-compulsive disorder: impact of the disorder and of treatment. CNS Drugs 27:367–383, 2013. 8. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Text Revision. Washington, American Psychiatric Press, 2000. 9. First MB, Spitzer RL, Gibbon M, Williams JBW. Structured Clinical Interview for DSM-IV Axis I Disorders (SCID I), Research Version, Patient Edition. New York, Biometric Research, New York State Psychiatric Institute, A1–A46, 2002. 10. First MB, Gibbon M, Spitzer RL, Williams JBW, Benjamin LS. Structured Clinical Interview for DSMIV Axis II Personality Disorders (SCID-II). Washington, American Psychiatric Press, Inc., 1997. 11. Goodman WK, Price LH, Rasmussen SA, Mazure C, Fleischmann RL, Hill CL et al. The Yale–Brown Obsessive Compulsive Scale: I. Development, use, and reliability. Archives of General Psychiatry 46:1006–1011, 1989. 12. Goodman WK, Price LH, Rasmussen SA, Mazure C, Delgado P, Heninger GR et al. The Yale–Brown Obsessive Compulsive Scale: II. Validity. Archives of General Psychiatry 46:1012–1016, 1989. 13. Smets EMA, Garssen B, Bonke B, De Haes JCJM. The Multidimensional Fatigue Inventory (MFI). Psychometric qualities of an instrument to assess fatigue. Journal of Psychosomatic Research 39:315–325, 1995. 14. Hamilton M. The assessment of anxiety states by rating. British Journal of Medical Psychology 32:50–55, 1959. 15. Leentjens AFG, Dujardin K, Marsh L, Richard IH, Starkstein SE, Martinez-Martin P. Anxiety rating scales in Parkinson’s disease: a validation study of the Hamilton Anxiety Scale, the Beck Anxiety Inventory and the Hospital Anxiety and Depression Scale. Movement Disorders 26:407–415, 2011. 16. Hamilton M. A rating scale for depression. Journal of Neurology, Neurosurgery, and Psychiatry 23: 56–62, 1960. 17. Guy W. ECDEU Assessment Manual of Psychopharmacology—Revised (DHEW Publ No ADM 76-338). Rockville, MD: Department of Health, Education, and Welfare, Public Health Service, Alcohol, Drug Abuse, and Mental Health Administration, NIMH Psychopharmacology Research Branch, Division of Extramural Research Programs, pp. 218–22, 1976. 18. Endicott J, Spitzer RL, Fleiss JL. The global assessment scale. A procedure for measuring overall severity of psychiatric disturbance. Archives of General Psychiatry 33:766–71, 1976. 19. Hosmer DW, Lemeshow S. Applied Logistic Regression. New York, Wiley, 1989.
123
Psychiatr Q 20. R Development Core Team: R. A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2013.
Massimo Pasquini, MD born in Rome, Italy, on July 20 1973. Psychiatrist at the Academic Hospital Umberto I Policlinico di Roma, Sapienza University of Rome. Adjunct Professor of Psychiatry, Sapienza University of Rome. Coordinator of the Outpatient Service for Psycho-Oncology, Policlinico Umberto I, Rome. He has authored and coauthored around 54 papers in international peer reviewed journals (H index 14, Scopus 2014), book chapters and many presentations and posters at national and international congresses. Daria Piacentino, MD born in Rome, Italy, on May 22 1981. Doctor at the Psychiatric Care Unit of Sant’Andrea Hospital, Rome, Italy. Research fellow at NESMOS (Neuroscience, Mental Health and Sensory Organs) Department, Sapienza University of Rome, Rome, Italy. PhD student in Clinical-Experimental Neurosciences and Psychiatry, Sapienza University of Rome, Rome, Italy. She has authored and coauthored around 10 papers in international peer reviewed journals (H index 2, Scopus 2014), book chapters and many presentations and posters at national and international congresses. Isabella Berardelli, MD born in Rome, Italy, on October 20-1982. Psychiatrist at the Academic Hospital Umberto I Policlinico di Roma, Sapienza University of Rome. Phd trainig student in Neuroscience, Sapienza University of Rome. Clinical fellow of the Outpatient Service for Psycho-Oncology, Policlinico Umberto I, Rome. She has authored and coauthored around 20 papers national and international peer reviewed journals, book chapters and many presentations and posters at national and international congresses. Valentina Roselli, MD born in Civitavecchia, Italy, on April 24 1984. Psychiatrist fellow at Sapienza University of Rome, Policlinic Umberto I, Rome, Italy, on going. Involved in clinical and research activities concerning psychiatric disorder in Academic Hospital Umberto I Policlinico di Roma. She has coauthored around 7 papers in international peer reviewed journals. Annalisa Maraone, MD born in Cassino (Frosinone), Italy, on June 05 1983. Psychiatrist fellow at Sapienza University of Rome, Policlinic Umberto I, Rome, Italy, on going. Reviewer for the Journal ‘‘Rivista di Psichiatria’’, untill 2013. Coauthored for around 6 papers in national and international journals and for some posters at national and international congresses. Lorenzo Tarsitani, MD born in Rome, Italy, on May 11 1974. Psychiatrist at the Academic Hospital Umberto I Policlinico di Roma, Sapienza University of Rome. Adjunct Professor of Psychiatry, Sapienza University of Rome. Coordinator of the Outpatient Service for Migration Psychiatry, Policlinico Umberto I, Rome. He has authored and coauthored around 48 papers in international peer reviewed journals (H index 9, Scopus 2014), book chapters and many presentations and posters at national and international congresses. Massimo Biondi, MD Full Professor of Psychiatry and Head of the Psychiatry and Psychopharmacology Unit; since 2007 Director of the Postgraduate School in Psychiatry, same University. Chief of the Psychiatry and Mental Health Area, Policlinico Umberto I, 1200 beds; Head of the Psychiatric Intensive Care Unit. Author of four and editor of 14 books, of 350 scientific publications, about 90 in English in international journals; H index 21; IF 180 last ten years. Chief Editor of Rivista di Psichiatria, a leader journal in Italy, listed in MEDLINE/PubMed, Current Contents, Excertpta Medica/EMBASE, PsychInfo; Chief Editor of the journal Medicina Psicosomatica, official journal of the Italian Society of Psychosomatic Medicine, listed in Excerpta Medica/EMBASE and PsycINfo; Assistant Editor of The American Psychiatric Publishing; Member of the Editorial Board of the journal Psychotherapy and Psychosomatics (Karger, Basel); Memberships. International Member of the American Psychiatric Association.
123
