Abstract

Obsessive-Compulsive Disorder (OCD) is a chronic and heterogeneous psychiatric condition with significant disability and a lifetime prevalence of 2-3%. Recent research has focused on the relationship between neurological dysfunction and OCD, specifically investigating Soft Neurological Signs (SNS). This systematic review and meta-analysis, based on 21 studies and 2024 participants, explored the severity of SNS in OCD patients compared to healthy controls. The results confirmed that OCD patients exhibit higher levels of SNSs, with no significant influence from demographic factors, age of onset, illness severity and duration, assessment tools or pharmacological treatment. High heterogeneity and potential publication bias were noted, particularly in the “SNS total score”. Limitations included the lack of blinded assessments in most studies and the cross-sectional nature of the research, which prevents establishing the potential prognostic value of SNS. Longitudinal studies and standardized assessments are needed to better understand the role of SNSs in OCD progression.

INTRODUCTION

Obsessive Compulsive Disorder (OCD) is a clinically heterogeneous and chronic condition, with potentially severe outcomes despite adequate treatment1. With an estimated lifetime prevalence of 2-3%2,3, and a remarkable burden of associated disability4, OCD constitutes a challenge both at an epidemiological and clinical level. Despite extensive characterization attempts5, diagnosis and assessment of this condition are mostly guided by clinical evaluation, and by the use of psychometric indexes such as the Yale-Brown Obsessive Compulsive Scale (Y-BOCS)6. In recent years the bidirectional relationship between obsessive-compulsive symptoms and neurological dysfunction has been increasingly acknowledged7,8 thus leading to a more in depth investigation of soft neurological signs (SNS) in this psychiatric condition.

The term “SNSs” was first used to identify a wide array of clinical information obtained from neurological examination9, but their use in psychiatry mostly emerged as imaging techniques became increasingly available – together with a growing interest in the neurological underpinnings of major psychiatric disorders10,11. SNSs can be defined as neurological alterations which are mainly expressed as a defective functioning in sensory integration (SI), motor coordination (MC), complex motor sequencing (CMS), or primitive reflexes12,13.

The neurobiological foundations of SNSs still have to be clearly defined: while there is evidence of alterations at a neuroanatomical level in schizophrenic patients presenting with SNSs14, no similar studies have been conducted for any other disease presenting with this phenomenon. Implicated areas seem to be basal ganglia and cerebellum, which would account for deficits in visual processing and spatial orientation, as well as frontoparietal and cerebellar networks; other theories attribute to white matter lack of integrity or neurometabolic alterations a possible etiopathogenetic role15. However, no clear hypotheses concerning a pathogenetic mechanism have been established.

In psychiatry, SNSs assessment primarily involved schizophrenia spectrum disorders12-16. In fact, subjects suffering from the latter conditions were used in the validation of the most used SNSs assessment instruments, e.g. the Neurological Evaluation Scale (NES)17, the Cambridge Neurological Inventory (CNI)18, and the Heidelberg Soft Neurological Signs Scale (HSNSS)19. Notably, some of the few studies addressing SNSs in OCD use patients with schizophrenia as a comparator group20-22 on the basis of the so-called “schizo-obsessive spectrum” construct23, and the abovementioned attention devoted to schizophrenia as primary field of interest for SNSs.

As for other psychiatric conditions like post-traumatic stress disorder24, bipolar disorder25, and substance misuse26, the investigation of SNSs in OCD per se remains uncommon. However, differently from the other disorders, OCD holds strong neurological underpinnings: functional neuroimaging allowed to identify orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), and caudate nucleus resting state hyperactivity, a finding which supports the hypothesis of “structural modifications” related to OCD but does not allow to determine whether this occurs before or after the disease develops27. Nevertheless, these areas were affected in patients with PANDAs28 and traumatic brain injury29 who later developed OCD, and are successfully targeted in patients with severe OCD who undergo neurosurgery or Deep Brain Stimulation30; this represents a stronger causal correlation as for a neurological etiopathogenesis. If such a correlation was confirmed and SNSs turned out to be an early marker for its detection, this would hold great potential in both prognostic31 and therapeutic terms32.

Conversely, as for other psychiatric conditions33,34, the investigation of SNSs in OCD per se, remains uncommon, even if the neurological underpinnings of this disorder are possibly stronger than for other psychiatric diagnoses35 – with potential prognostic31 and therapeutic implications32.

In recent years, different investigations explored the presence of SNSs in OCD, with heterogeneous and sometimes inconsistent findings. Most studies found that OCD patients had more SNSs as compared to controls in SNS total scores 15,20,36-50, or in at least one of the most extensively assessed domains – i.e, SI20,37,43,44,49,50, MC20,37,39,40,43,44,46,47,50, CMS37,50, or primitive reflexes20. On the contrary, a minimum body of evidence found no differences regarding total SNSs levels or related sub-domains21,22,51,52.

When evaluating the above mentioned studies, common observations are carried out on small samples sizes and with high grades of heterogeneity – e.g., selective evaluation of clinical subtypes, and the fact that some studies involve patients receiving pharmacological treatments, whereas others only involve drug-naïve subjects53. Moreover, some studies simply describe SNS as part of neurological examinations, rather than using validated, standardized scales.

In 2013, a meta-analysis from Jaafari and colleagues (2013) systematically investigated the presence and severity of SNSs in individuals with OCD by evaluating the available evidence from 15 selected studies (498 patients and 520 controls). Authors concluded that patients had higher levels of SNSs as compared to healthy controls in total scale scores (Hedges’ g = 1.27), and in the domains of SI, MC, and primitive reflexes; moreover, SNSs did not prove to be associated with socio-demographic data, clinical severity of OCD, chosen instruments for SNSs assessment, or presence of a pharmacological treatment53.

The primary aim of the present work was to update the evidence in this field to explore the frequency, severity, and type of SNSs in OCD patients versus healthy controls. The secondary aim was to use a meta-regression analysis to evaluate the role of possible confounding variables (i.e., socio-demographic characteristics, type of SNS rating scale used, and OCD clinical-therapeutic features) on the association between SNSs and OCD.

METHODS

This systematic review and meta-analysis follow the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) guidelines54. The identification of relevant abstracts, the selection of studies and the subsequent data extraction were performed independently by four of the authors (A.F., F.D.M, O.B.B. and G.D.) and conflicts were resolved by a third investigator (F.F.). This review was registered in PROSPERO (PROSPERO ID: CRD42022322161).

A Medline, Embase, Scopus and Google Scholar search for eligible studies published up to April 21, 2024 was conducted using the following terms: (“neurological soft signs” OR “neurological signs” OR “soft signs” OR “neurological abnormalit*” OR “motor coordination” OR “sensory integration” OR “complex motor sequencing” OR “Luria task” OR “fist-edge-palm”) AND (“OCD” OR “obsessive compulsive disorder”). Furthermore, we manually searched relevant articles in reference lists of the previous review and included studies. The exclusion criteria were non-original study, non-human population, missing OCD group, missing control group, missing SNS assessment. For each of the selected studies, four authors (F.D.M, G.D.A, O.B.B. and A.F.) independently extracted the following data: publication year, sample size, mean age, female percentage, mean education (years), SNS measurement tool, total SNS, motor coordination and sensory integration scores of cases and controls. Moreover, only from the OCD group mean age of illness onset, mean duration of illness, Y-BOCS total score and percentage of individuals under antidepressants or antipsychotics therapy were extracted. Corresponding authors of included studies were contacted to obtain missing data.

Primary outcomes were the total SNS score, the motor coordination score and the sensory integration score. Whenever possible, the gold data entry format, i.e. “mean - standard deviation - sample size”, was used for data entry and calculation of the standardized mean difference. Alternatively, the format “mean - p value - sample size” were used. Heterogeneity was computed by using I2 statistics55. Meta-regression analyses were performed to assess the influence of demographic characteristics, mean age of OCD onset, duration and severity of illness, pharmacotherapy (defined as the percentage of cases that are undergoing antidepressants or antipsychotics treatment) and SNS assessment instrument in the analysis. All analyses were conducted by applying a random effects model and a 95% confidence interval. To assess publication bias, funnel plot interpretation and Egger’s regression intercept56 were used. To assess the risk of bias in the included studies, we used the Newcastle-Ottawa Quality Assessment Scale, version for case-control studies (NOS)57, and we provided a graphical representation of our analysis using RevMan tool (Review Manager, Version 5.3)58, which illustrates the assessment of risk of bias of included studies for each item with ratings of “low risk” (green light), “uncertain risk” (yellow light) or “high risk”(red light). Based on the risk of bias assessment, a sensitivity analysis was conducted by including only the best quality studies for each outcome. A “one study removed” sensitivity analysis was conducted to detect outlier studies and to assess the influence of each study on the analysis. All analyses were performed using the software programs Review Manager (RevMan) [Computer program], Version 5.358, and Comprehensive Meta Analysis, version 3.3.07059.

RESULTS

The study flow summary is reported in Figure 1. Four hundred ninety-two records were identified through database searching. Of these, 174 studies were excluded through abstract and title screening; 296 studies were excluded due to the presence of exclusion criteria reported in Figure 1. Twenty-two full texts were assessed for eligibility to quantitative synthesis. Only 1 study was excluded due to the use of median as effect size measure60. Formulas are suggested to compute means from medians and, occasionally, medians can be used directly in meta-analyses when the distribution of the data is normally distributed, but this is not valid when the data distribution of the included study is skewed55. Thus, since medians are often used when data are skewed, and since it is not possible to check the data distribution in this study, authors decided to exclude the study from quantitative synthesis. Twenty-one studies were included in the meta-analysis. From these, the effect size estimates computed were 18 for the outcome “SNS total score”, 17 for “motor coordination” and 17 for “sensory integration”.

Characteristics of included studies are summarized in Table I. The total sample included 2024 participants (1098 OCD patients and 926 healthy controls). In the OCD group the mean age of participants was 31.48 years, the mean of education years was 12.06 and females were 41.94 % of the total sample. The mean OCD age of onset was 21.59 and the mean duration of illness was 9.62 years. YBOCS mean total score was 23.19 and patients receiving standard treatment were 83.27%. In the healthy controls group the mean age and education years were 32.1 and 12.95 respectively, and females were the 39.98% of the total sample. Six studies lack an OCD symptoms severity assessment. In 1 study61 the use of Y-BOCS is declared but the scores are not reported. In all the other studies included Y-BOCS was used to assess symptoms severity. The tools used to assess soft neurological signs were the Cambridge Neurological Inventory (CNI, n=8;18), the Neurological Evaluation Scale (NES, n=8;17), the Krebs standardized neurological examination (n=1,62), the Physical and Neurological Examination for Soft Signs (PANESS, n=1;63), and the Heidelberg Neurological soft signs Scale (HSNSS, n=1;19). Two studies36,39 employed a non-validated clinical exam. 16 out of 21 studies reported the proportion of OCD patients under psychopharmacological treatment.

For 17 out of 21 studies it was possible to use the gold data entry “mean - DS - sample size”, for the others the format “mean - p value - sample size” was used. The meta-analysis showed large effect sizes for all the outcomes examined. Standardized mean differences were 2.08 (CI 1.45, 2.71; p<.001), 1.15 (CI .79, 1.50; p <.001) and .98 (CI .62, 1.34; p<.001) respectively for the outcomes SNS total score, motor coordination and sensory integration. I2 statistics showed a high level of heterogeneity (>90%) for all the analyses (Figs. 2, 3 and 4).

Meta regression analyses were conducted to investigate the role of covariates in the formation of heterogeneity. The results showed that none of the covariates significantly influence the effect sizes (Supplemental Material, Tables I-VIII).

The interpretation of funnel plot and Egger’s Test results (p = .034) are not suggestive of publication bias for the “SNS total score” outcome (Fig. 5) or for the other outcomes (p = .25 for “motor coordination”, p = .26 for “sensory integration”).

The risk of bias assessment (Fig. 6) conducted using the Newcastle-Ottawa Quality Assessment Scale revealed that the risk of bias in the items “definition of the cases”, “representativeness of the cases”, “definition of controls”, “selection of controls”, “comparability” of cases and controls, and “data loss management” were low or uncertain. However, only 3 out of 21 studies implemented blinded ascertainment of SNS and/or OCD symptoms. Given the potential for observer bias to affect the accuracy of assessments, the absence of blinding was considered a potential source of bias. Consequently, we conducted a sensitivity analysis, excluding all studies that employed non-blinded assessment methods. While the “motor coordination” and “sensory integration” subgroups exhibited all three effect sizes, the “SNS total score” outcome lacked one of the effect sizes. The results of the sensitivity analysis for the “motor coordination” and “sensory integration” subgroups confirmed the findings with lower effect sizes (SMDs = .66 and .55, p = .001 and .036, respectively), while no analysis was conducted for the “SNS total score” group due to the paucity of effect sizes.

“One study removed” sensitivity analysis showed that none of the included studies influences the analyses with significance.

DISCUSSION

The results from the present study almost entirely confirm and strengthen the findings of the meta-analysis by Jaafari et al.53, i.e. the large effect sizes confirming the greater rates of SNSs in OCD patients compared to the healthy controls, and the absence of influence by demographic variables, mean age of illness onset, mean duration of illness, Y-BOCS total score and rates of individuals under antidepressants or antipsychotics.

The main update to the 2012 review was that the population it examined almost doubled (2024 against 1018), although not all studies from the previous review were included in our work; in fact, the studies by Stein et al.52 and Salama et al.48 were excluded from this study. The first was considered not eligible because it shares part of the sample with the study by Hollander et al.39, (the study by Hollander et al. was chosen because it had the largest sample size). The second was excluded due to the impossibility of finding the manuscript in any database.

Similarly to the previous meta-analysis, it is not possible to draw conclusions on the prognostic value of SNSs in OCD: while Jaafari et al. suggested that the the co-occurrence of the two in absence of an apparent proportional relationship might indicate that we are dealing with a a stable characteristic rather than a state one64 this could only be inferred from longitudinal observation.

However, this does not entirely deprive our findings of clinical significance: as previously noted by Jaafari et al.53 SNSs might prove to be early, aspecific markers of an ongoing psychopathological process. The fact that their increased incidence in OCD was demonstrated might prove valuable once their role in determining general psychopathology is established.

The handling and presentation of data on pharmacotherapy of patients recruited in the included studies are highly heterogeneous i.e., in some studies data are not reported38,39, in others, only the number of patients under treatment are reported43,50, while in a few studies class of psychotropic drugs is specified, etc.46,47. In this context, the only way to study the possible role of pharmacotherapy as a predictive value in a meta-analytic approach is to use the percentage of patients under treatment. However, this is a highly nonspecific value, which does not consider drug class, dosage, and polypharmacotherapy. In addition, the cross-sectional design does not allow attributing causal value to pharmacotherapy on the measured outcome.

The unblinded assessment, which was performed in 17 out of the 21 included studies, is a major limitation of the results emerging from this meta-analysis, although sensitivity analyses for “motor coordination” and “sensory integration” subgroups, conducted by including only those studies using a blinded assessment, confirmed the results with smaller effect sizes. The authors did not consider it appropriate to conduct a sensitivity analysis for the outcome “SNS total score” because of the presence of only studies with blinded assessment. This bias could lead to overestimating the presence of SNSs in OCD patients.

LIMITATIONS AND FUTURE PERSPECTIVES

Meta-regression analysis doesn’t explain the high heterogeneity observed in our meta-analysis. One possible explanation is that given the limited number of effects conducting a multivariate meta-regression is not feasible. This approach would allow for the identification of potential interrelationships between covariates, thereby enhancing the precision of the results compared to conventional univariate analyses.

The lack of longitudinal studies does not allow to draw inferences on the prognostic value of SNSs; a shift in study design - which was already suggested in original meta-analysis53 could allow for a better understanding of the causal relationship between SNSs and OCD development. Follow-up measurements would also allow us to assess whether SNSs fluctuate over time in patients with OCD; this hypothesis, drawing from the schizo-obsessive model, would be consistent with phase-specificity. On the other hand, a lack of fluctuations would identify SNSs as a trait feature of OCD, as more recent studies have suggested.

An alternative to longitudinally-designed studies would be running correlations between presence and intensity of SNSs with disease duration; this could prove as an efficient method to respond to some of the questions raised by this research.

CONCLUSIONS

OCD patients are more affected by neurological signs than healthy controls; however, SNSs do not seem to correlate with disease severity. A shift in research design with more longitudinal studies and blinding assessment are needed to reinforce the evidence.

Conflicts of interest statement

None of the authors have financial involvement or affiliation with any organization whose interests may be affected by material in the manuscript.

Funding

None of the authors or institutions at any time received payment from a third party for any aspect of the submitted work.

Authors’ contributions

Andrea Falone, Ottone Baccaredda Boy, Francesco Del Monaco, Giulio D’Anna, Fabio Fierini participated in the study selection and data extraction phase. Andrea Falone also oversaw the data analysis phase and manuscript writing phase. Valdo Ricca and Francesco Rotella played supervisory and conflict resolution roles.

Figures and tables

FIGURE 1. Flow-diagram.

FIGURE 2. “SNSs Total Score” forest plot.

FIGURE 3. “Motor coordination” forest plot

FIGURE 4. “Sensory integration” forest plot..

FIGURE 5. Funnel plot for “SNS total score”.

FIGURE 6. Risk of bias assessment (green: Low risk of bias; yellow: unclear risk of bias; red: high risk of bias).

ID N OCD GROUP N HCs GROUP YBOCS TOTAL SCORE Age of OCD onset (mean) Duration of illness (mean) Age of OCD grup (mean) Age of HCs (mean) Female % in OCD group (mean) Female % in HCs group (mean) Education in OCD group (mean years of schooling) Education in HCs group (mean years of schooling) Patients under treatment SNSs assessment tool Severity of OCD symptoms assessment tool Year of publication
Bersani G et al. 14 15 22,73 28,93 37,71 32,14 31,36 \ \ 12,57 12,93 64,28 NES YBOCS 2023
Bihari K et al. 39 43 \ \ \ \ \ \ \ \ \ 64,1 Clin Exam \ 1991
Bolton D et al. 51 67 \ \ \ 36,9 38,2 58,8 17,9 \ \ 100 CNI \ 1998
Dhuri CV, Parkar SR. 50 50 \ 21,76 \ 30,62 \ 36 \ 14 \ \ HSNSS \ 2016
Ekinci O, Erkan Ekinci A. 126 84 20,28 23,42 6,3 27,53 29,65 64,2 67,9 11,17 11,33 100 NES YBOCS 2019
Guz H, Aygun D 30 30 \ \ 0,68 36,3 36,3 36,67 36,67 \ \ \ PANESS \ 2004
Hollander E et al. 41 20 25,3 \ 12,9 33,9 32,4 39 40 \ \ \ Clin Exam YBOCS 1990
Jaafari N et al. 49 54 22,7 17,7 12,5 29,9 29,6 55,1 57,41 13,1 13,7 \ NSS YBOCS 2011
Jaafari N et al. 2012 spanish sample 50 49 20,54 \ 13,9 33,9 34 38 38,8 12,3 12,7 98 CNI YBOCS 2012
Jaafari N et al. 2012 UK sample 35 39 24,51 \ 21,2 36,7 33,8 42,9 48,7 13,3 14,6 75,7 CNI YBOCS 2012
Kader MAE et al. 40 40 \ \ \ 32,75 37,78 45 45 \ \ \ CNI YBOCS 2012
Karadag F et al. 64 32 27,98 26,28 9,87 36,37 32,25 62,5 56,25 9,95 11,84 79,68 NES YBOCS 2011
Malhotra DS et al. 180 90 \ 21,16 5,95 30,64 32,22 14,4 12,3 11,84 \ 100 CNI \ 2016
Mataix-Cols et al. 30 30 17,93 18,96 \ 33,53 32,33 43,3 43,3 17,7 18,43 90 CNI YBOCS 2003
Nickoloff SE et al. 8 12 21,6 \ \ 36,5 38,2 37,5 50 \ \ 87,5 NES YBOCS 1991
Ozcan H et al. 33 21 22,1 22,5 12,7 35,3 32,4 69,69 42,9 9,3 11,3 72,7 NES YBOCS 2016
Peng ZW et al. 138 101 25,91 21,06 9,48 26,72 27,16 32,6 31,68 13,05 14,36 100 CNI YBOCS 2012
Poyurovsky M et al. 20 51 22,5 16,7 14,2 29,7 31,9 45 41,18 12,2 13,8 \ NES YBOCS 2007
Sevincok L et al. 25 23 28,5 \ 9,4 33,2 33 80 47,83 8,2 9,3 \ NES YBOCS 2005
Tapanci Z et al. 30 30 \ 19,33 \ 31,07 30,7 50 50 13,7 14,23 100 NES \ 2017
Tripathi R et al. 45 45 21,6 21,7 \ 29,96 28,96 24,4 35,56 10,22 8,93 57,8 CNI YBOCS 2015
OCD: Obessive Compulsive Disorder; HCs: Healty Controls; YBOCS: Yale-Brown Obsessive Compulsive Scale; SNSs: Soft Neurological Signs
TABLE I. Characteristics of included studies

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Andrea Falone - Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, FI, Italy

Ottone Baccaredda Boy - Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, FI, Italy

Francesco Del Monaco - Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, FI, Italy

Giulio D'Anna - Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, FI, Italy

Fabio Fierini - Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, FI, Italy

Valdo Ricca - Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, FI, Italy

Francesco Rotella - Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, FI, Italy

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Falone, A., Baccaredda Boy, O., Del Monaco, F., D’Anna, G., Fierini, F., Ricca, V., & Rotella, F. (2025). Soft neurological signs in patients with obsessive compulsive disorder: a systematic review and meta-analysis. Italian Journal of Psychiatry, 11(1). https://doi.org/10.36180/2421-4469-2025-885
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