Indian Journal of PsychiatryIndian Journal of Psychiatry
Home | About us | Current Issue | Archives | Ahead of Print | Submission | Instructions | Subscribe | Advertise | Contact | Login 
    Users online: 530 Small font sizeDefault font sizeIncrease font size Print this article Email this article Bookmark this page
 


 

 
     
    Advanced search
 

 
 
  
    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Email Alert *
    Add to My List *
* Registration required (free)  


    Abstract
   Introduction
    Materials and Me...
   Results
   Discussion
   Conclusion
    References
    Article Tables

 Article Access Statistics
    Viewed298    
    Printed8    
    Emailed0    
    PDF Downloaded47    
    Comments [Add]    

Recommend this journal

 


 
 Table of Contents    
ORIGINAL ARTICLE  
Year : 2021  |  Volume : 63  |  Issue : 5  |  Page : 439-447
Concordance of assessment of insight by different measures in obsessive-compulsive disorder: An outpatient-based study from India


Department of Psychiatry, Postgraduate Institute of Medical Education and Research, Chandigarh, India

Click here for correspondence address and email

Date of Submission13-Dec-2020
Date of Decision05-Mar-2021
Date of Acceptance01-Jul-2021
Date of Web Publication12-Oct-2021
 

   Abstract 


Aims: This study aimed to examine the (a) prevalence of various levels of insight among patients with obsessive-compulsive disorder (OCD) and (b) correlation of insight specifier (Diagnostic and Statistical Manual [DSM]-5) and other established measures of insight in OCD.
Methods: One hundred and twenty-five outpatients with a diagnosis of OCD were assessed by Brown Assessment of Beliefs Scale (BABS) and DSM-IV's insight specifier. The insight specifier of DSM-5 was determined by item one (“conviction”) of BABS. Dimensional Yale-Brown Obsessive-Compulsive Severity Scale was used to assess the frequency and severity of dimensional obsessive-compulsive (OC) symptoms.
Results: The mean age of the participants was 31.2 (±11) years. Seventy-seven (61.6%) of the participants were men. There was a high correlation (r = 0.73) between the insight specifiers of DSM-5 and DSM-IV. Insight categories of DSM-5 had modest correlations with BABS total score and BABS-based insight categories. Significant associations were observed between the level of insight and comorbid psychotic illness, hoarding and symmetry dimensions of OC symptoms, severity of depressive, and OC symptoms. The first two associations were consistent across group comparisons (insight-groups based on DSM-IV and BABS) and correlation (with total BABS score).
Conclusions: Majority of the patients with OCD have good insight and application of different tools influence the assessment of insight in OCD. The DSM-5 insight specifier has strong and significant correlation with the DSM-IV's insight classification and categorization of insight by BABS.

Keywords: Correlation, insight, obsessive compulsive disorder

How to cite this article:
Grover S, Ghosh A, Kate N, Sarkar S, Chakrabarti S, Avasthi A. Concordance of assessment of insight by different measures in obsessive-compulsive disorder: An outpatient-based study from India. Indian J Psychiatry 2021;63:439-47

How to cite this URL:
Grover S, Ghosh A, Kate N, Sarkar S, Chakrabarti S, Avasthi A. Concordance of assessment of insight by different measures in obsessive-compulsive disorder: An outpatient-based study from India. Indian J Psychiatry [serial online] 2021 [cited 2021 Oct 22];63:439-47. Available from: https://www.indianjpsychiatry.org/text.asp?2021/63/5/439/328098





   Introduction Top


The Diagnostic and Statistical Manual (DSM), 4th edition (DSM-IV) and the International Classification of Diseases (ICDs), 10th revision (ICD-10) define insight in obsessive-compulsive disorder (OCD) as, “recognition that symptoms are excessive or unreasonable at some point during the course of the illness” as an essential requirement for the diagnosis of OCD.[1],[2] However, both DSM-5 and ICD-11 have done away with this requirement and recognize a degree of insight. As per ICD-11 insight in patients with OCD is rated as a dichotomous outcome, i.e., good to fair and poor to absent, whereas DSM-5 classifies insight as good/fair, poor, and absent.[3],[4] Although categorical classification of insight is clinically useful, there is evidence to support continuum or dimensional approach to understand insight in OCD.[5] The multi-faceted construct of insight, consisting of conviction, stability, and fixity, among others could be measured by the various instruments.[6] A study which evaluated the correlation between different instruments assessing insight and DSM-IV categories show modest to high correlations.[7] However, there is a need to study the concordance using DSM-5's insight categories in a larger sample and from a different country.

Studies have evaluated the various demographic and clinical correlates of insight, and the findings have been inconsistent.[6],[8],[9] There is some consistency with respect to the association of poor insight with poor treatment outcomes in the form of chronicity, severity, lower quality of life, suboptimal response to psychotropics, and cognitive behavior therapy.[6],[10],[11],[12],[13] Younger age has largely been linked with poorer insight. The association of sex, marital, and economic status was not consistent.[6]

In this background, the present study aimed to examine the

  1. Correlation of insight specifier (DSM-5) and other established measures of insight in OCD and
  2. To examine the relationships of insight to demographic and clinical variables using a comparative and exploratory approach.



   Materials and Methods Top


Setting and participants

This study was done at the outpatient services of a general hospital psychiatric unit. The hospital caters to the seven neighboring states and union territory of Northern India. Recruitment of participants was done by the convenience sampling. A written informed consent was obtained from all the participants. The research was approved by the Institute's Ethics Committee.

Patients with OCD as per DSM IV-TR criteria were recruited.[1] The diagnosis of OCD and comorbidities was made following a detailed evaluation by a qualified psychiatrist based on the DSM-IV-TR criteria. All assessments were completed in a single session of 1.5–2 h duration by a qualified psychiatrist. The assessor ensured completion of the data intake. Participants with comorbid substance dependence, chronic physical illnesses, organic brain syndrome, and intellectual disability were excluded. The sample was collected between July 2012 and June 2013, i.e., for a period of 1 year.

Instruments

Brown Assessment of Beliefs Scale

It is a clinician administered six-item instrument. Brown Assessment of Beliefs Scale (BABS) is a multidimensional, multifaceted scale comprising conviction, perception of others' views of beliefs, explanation of differing views, fixity, attempt to disapprove ideas, and insight. All these dimensions are rated on a 5-point Likert scale (0–4). The total score ranges from 0 to 24.[14] BABS has excellent internal consistency, test-retest reliability, and inter-rater reliability. It has been shown to have a good convergent and divergent validity as well.[14] The item 1 of BABS (i.e., conviction: “how convinced are you of these ideas/beliefs? Are you certain your ideas/beliefs are accurate?”), is similar to the DSM-5's insight specifier. The first three ratings (0–2) suggest complete, probability, or uncertainty of the falsity of belief-good to fair insight (DSM-5). A score of 3 (“fairly convinced that beliefs are true but an element of doubt exists”) represents “poor” insight, whereas Score 4 (“completely convinced about the reality of held beliefs”) is indicative of absent insight of DSM-5.[3] In addition to the DSM-5's insight categories, based on the total BABS score, we classified the insight as good and poor insight. Participants with a total BABS score “zero” were classified to have good insight and those with a score of “14 or more” were categorized as having poor insight.[9] We used the principle of phenotypic extremes to categorize the two insight groups so that there was adequate zone of rarity (participants with BABS scores between 50th percentile and 75th percentile).

Diagnostic and Statistical Manual-IV insight criteria

DSM-IV recognized insight as a dichotomous variable – “OCD”or “OCD with poor insight.” This last specifier is applied when “for most of the time during the current episode the person does not recognize that the obsessions and compulsions are excessive or unreasonable.”

Yale-Brown Obsessive Compulsive Scale (Y-BOCS)

It is a ten-item interviewer-administered, 5-point (0–4) Likert scale. The score ranges from 0 to 40. Y-BOCS has two subsections: obsession and compulsion. Each subsection has five items.[15]

Dimensional Yale-Brown Obsessive-Compulsive Severity Scale

It is a self-reported or family-reported instrument, which measures dimensional severity of OCD across six dimensions, according to the content of OC symptoms (1 aggression, violence, and natural disasters; 2 sexual and religious; 3 symmetry, order, counting, and arrangement; 4 contamination, cleaning, and washing; 5 accumulation; and 6 miscellaneous content). For the sake of brevity, the dimensions would be referred in the text as aggressive, sexual, symmetry, contamination, and hoarding. We have used the “principal” symptom for categorization and those who had fulfilled more than one (41.6%) were categorized as such. The severity and degree of impairment defined the “principal” symptoms. The severity ratings, a composite measure of time, distress, and interference with daily activities, are done for each of these dimensions. The ratings are on a 6-point Likert scale (0–5), in which higher scores indicate greater severity.[15],[16]For those participants with obsessive-compulsive (OC) symptoms in more than one dimensions, we considered the insight of those symptoms which had higher the dimensional scores.

Hamilton Depression Rating Scale

Hamilton Depression Rating Scale was used to rate the severity of comorbid major depressive symptoms.[17] Positive and Negative Syndrome Scale (PANSS) was used only for the patients with psychotic illness.[18]

We assessed the socioeconomic status (SES) by the Modified Kuppuswamy socioeconomic scale.[19]

Statistical analysis

Correlation across various measurements of insight was the primary outcome of the study. We assumed a small correlation (0.3) between the measurements. A sample size of 125 was estimated to detect a small correlation (0.3) with 80% power and 1% chance of false positivity (alpha = 0.01).

The analysis was done by the Statistical Package for the Social Sciences (SPSS) software version 21 (IBM Corp, Armonk, NY, USA).

A comparison between the groups with good or fair versus poor or absent insight was done by an independent-sample t-test for the continuous variables, which are normally distributed and by the Mann–Whitney test for nonnormally distributed continuous variables. The categorical variables were compared by the Pearson's Chi-square test. However, for those variables with expected counts of <5 in any of the cells of contingency tables, Fisher's exact test (and exact significance) was used. For others, we used asymptotic 2-tailed significance value. A point biserial correlation was used for DMS-IV insight category (dichotomous variable) and BABS total score (continuous variable). The DSM-5 insight has three grades. The correlation between DSM-5 and BABS total score was done by Spearman analysis. The correlation analysis between DSM-IV, DSM-5, and BABS insight categories was done by Cramér's V-test. To address the problem of multiple comparisons, we applied false discovery rate (FDR) method using the Benjamini–Hochberg adjusted P value. We conducted a multiple linear regression analysis to examine the relationship between insight (as measured by the BABS total score) and other clinical and demographic variables.


   Results Top


A total of 125 participants were included in the analysis. The mean age of the participants was 31.2 (standard deviation: 11) years. Seventy-seven (61.6%) of the participants were men. The rest of the demographic variables are depicted in [Table 1]. There were four patients with anxiety disorders (generalized anxiety disorder = 1, social phobia = 2, and anxiety not otherwise specified = 1), two with bipolar disorder, and one participant with a past history of tic disorder. The PANSS positive, negative, and general psychopathology scale scores were 8.1 (±6.4), 9 (±8.1), and 13.6 (±10.7), respectively. Contamination (and cleaning) (62.4%) was the most common symptom dimension, followed by symmetry (32.8%) and sexual (30.4%) symptoms. Somatic obsession (2%) was least frequently encountered. Fifty-two (41.6%) of participants had more than one dimension of symptoms.
Table 1: Sociodemographic and clinical profile of the participants (n=125)

Click here to view


Correlations between various measures of insight in obsessive-compulsive disorder

Insight of participants was assessed using the DSM-IV and DSM-5 specifiers, BABS total score, and BABS-based insight categories. DSM-5 has high correlation (r = 0.74, P < 0.001) with the DSM-IV's insight specifier and has modest correlations with the BABS total score (r = 0.5, P < 0.001) and BABS-based insight categories (r = 0.56, P < 0.001). DSM-IV insight specifiers too had modest correlations (r = 0.5, P < 0.001) with the BABS insight category. All the correlations were significant even after Bonferroni correction for multiple comparisons [Table 2].
Table 2: Correlations of measures of insight

Click here to view


Comparison of participants with good versus poor insight

For this, first, the sample of 125 was divided into two groups based on the DSM-IV specifier of insight. There were 111 (88.8%) with good or fair insight and 14 (11.2%) participants with poor insight. Poor insight was associated with male sex (P = 0.05), lower SES (P = 0.004), comorbid psychotic illness (P < 0.0001), and “hoarding (and collection)” dimension (P = 0.006) of OCD. The association between the total BABS score and insight specifiers too was highly significant (P < 0.0001). Nevertheless, after correcting for multiple comparisons, SES, comorbid psychotic illness, and hoarding retained statistical significance [Table 3].
Table 3: Comparison of groups with good versus poor insight (diagnostic and statistical manual-IV)

Click here to view


Comparison of participants with good/fair versus poor/absent insight

Second, the total sample was divided based on the BABS total score. “Good insight” was defined by a total BABS score of zero and 29 participants had “good insight” as per this definition. We defined “poor insight” by a BABS cutoff score of ≥14. Sixteen participants had “poor insight.” The categorization was based on the article by de Avila et al.[9] Poor insight was associated with comorbid psychotic illness (P = 0.02), higher frequency of “hoarding (and collection)” (P = 0.004) and symmetry (P = 0.04) dimensions of OCD, and higher frequency of OCD symptomatology in more than one dimension (P = 0.02). However, after significant test using FDR at 0.05, only the frequency of hoarding symptoms and comorbid psychotic illness remained significant [Table 4].
Table 4: Comparison of groups with good/fair versus poor insight (Brown Assessment of Beliefs Scale-category)

Click here to view


Correlations of clinical and demographic parameters with brown assessment of beliefs scale total score

Significant but small correlations of BABS score was observed with the presence of psychotic illness (r = 0.19; P = 0.04), hoarding (r = 0.30; P = 0.001), symmetry (r = 0.20; P = 0.02), and more than one dimensions (r = 0.21; P = 0.02) of OCD symptomatology, and Y-BOCS total score (r = 0.18; P = 0.05). Spearman rank correlation was done for all the analyses except the correlation between BABS and Y-BOCS total scores analyzed by Pearson test. After correction for FDR, only the association between hoarding and BABS total score remained significance.

Multivariate analysis of the association between Brown Assessment of Beliefs Scale total score and other clinical and demographic parameters

The BABS total score was the dependent variable. Clinical and demographic characteristics, which retained significance after the corrections for multiple comparisons in the univariate analyses, were chosen as independent variables. The variance inflation factor ranged from 1.06 to 1.19, suggesting minimal collinearity. The adjusted variance was 0.18. The goodness of fit of the regression model was statistically significant.

Hoarding (standardized coefficient = 0.23; t = 2.32; P = 0.02) and comorbid psychotic illness (standardized coefficient = 0.29; t = 3.02; P = 0.003) were significantly associated with higher BABS score (suggesting poorer insight). Symmetry (standardized coefficient = 0.17; t = 1.7; P = 0.08) and SES (standardized coefficient = −0.06; t = 0.72; P = 0.45) did not reach statistical significance.


   Discussion Top


There is no published literature either from the Indian sub-continent or elsewhere on the correspondence of DSM-5's degree of insight in OCD with that of DSM-IV's insight specifiers and another well-validated instrument, BABS.[14] A review on the Indian research in OCD has highlighted the paucity of literature in insight.[20] Our study was adequately powered to test these correlations. We decided to use the DSM-5's insight specifier as a reference because it is the latest classificatory system.

A strong and significant correlation was observed between the DSM-5 and DSM-IV's degree of insight. Because of the overlap between the grades of insight, a high correlation between the former and existing classificatory system was not surprising.[1],[3] Concurrence between the previous and the present system should ensure continuity. Moreover, an objectively anchored insight determination in our study could have improved the credibility and eased the assessors' difficulty. This is supported by the World Health Organization's Global Clinical Practice Network's survey report.[21]

As per DSM-IV and DSM-5, 11.2% and 12% of our sample had a poor insight. The DSM-IV field trial conducted across seven outpatient clinics of the United States showed nearly 30% of patients would qualify for poor or absent insight.[22] However, another study, done in an Italian sample, had 15% of patients with poor insight.[23] Therefore, our sample had a lesser proportion of patients with poor insight. Different study populations and varying scales to assess insight might explain this difference. According to the DSM-5, 12% of our study sample had poor or absent insight. Despite acknowledging the insight spectrum, DSM-5 did not bring about a major change to the insight specifier of DSM-IV. Nevertheless, recognition of “absent insight” as a specifier should reduce the probability of misdiagnosis of OCD as a psychotic illness.[24] ICD-11 too has “good to fair” and “poor to absent insight”-dichotomous classification like DSM-IV.[25]

BABS insight measurement showed modest (and significant) correlations with the DSM-IV and DSM-5's insight specifiers. The strength of the correlation between BABS total score and DSM-IV's grades of insight was similar to the study done among Israeli clinical samples.[7] Perhaps, ours was the first study to correlate the insight measurements of DSM-5 and BABS. Nevertheless, finding a modest correlation was not startling. BABS insight scale is a multidimensional instrument, which generates a composite score, while the degrees of insight in classificatory systems are categorical and largely based on a single domain (conviction on the obsessive beliefs). Thus, classificatory systems and BABS although measure the similar construct of insight, conceptualization differs.

Another aim of our study was to examine the relationships of insight with the demographic and clinical variables using a comparative and exploratory approach. The group comparisons between good and poor insight were done from two different perspectives

  1. Insight specifiers of DSM-IV, and
  2. Two subgroups created from multi-dimensional BABS.


The exploratory approach consisted of correlating BABS total score with relevant clinical variables. In both comparative and exploratory analyses, the presence of comorbid psychotic illness was consistently associated with OCD with poor insight. The significance of the association between poor insight and comorbid psychosis survived the corrections for multiple comparisons and regression analysis. Sixty percent of the participants with comorbid psychosis had poor insight into their OC symptoms and this constituted nearly 43% participants with poor insight. We retained the comorbid group in our analysis because a substantial minority (8%−26%) of individuals with schizophrenia also suffer from OCD and the prevalence of OCD in patients with schizophrenia is significantly more than the general population. We did not want to exclude this sizeable population. Moreover, the study participants with psychosis were in remission. Hence, the psychopathology did not confound the assessment of insights into OC symptoms.[26] Others have reported similar finding of the association between OCD with poor insight and comorbid schizophrenia. A study from Japan, comparing patients with OCD, with or without comorbid schizophrenia showed a significantly higher prevalence of poor insight into OC symptoms among patients with comorbid schizophrenia.[13] Researchers observed similar findings among patients with schizotypy and schizotypal disorder.[27] These results suggest a possibility of a common biological substrate for developing delusional convictions about the reasonableness of obsessions and beliefs related to psychotic symptoms. The concept of the schizo-obsessive spectrum is based on this common link, where OCD with schizophrenia lies proximal to pure schizophrenia.[28]

The second consistent relationship shown in our study was between hoarding symptoms and poor insight. This association, too, survived the correction of FDR. Besides, the association of hoarding and poor insight remained significant even after controlling for other factors (e.g., comorbid psychosis, symptoms of symmetry, and SES) in the regression analysis. Similar findings were also demonstrated in previous studies.[12],[29],[30],[31]

Higher occurrence of symmetry or exactness-related symptoms was shown among OCD with poor insight and those with comorbid psychotic disorders.[13] Although a common dopamine dysregulation hypothesis is posited to explain the association, any conclusive understanding is yet to be reached.[32] In our study, too, the link between symmetry-related symptoms and poor insight lost statistical significance after controlling for the comorbid psychotic illness. The relationship between insight and OCD severity has been inconclusive. Some investigations showed significant relationships between insight and the severity of obsessions,[13],[29] compulsions,[13],[29],[30] and both obsessions and compulsions.[12],[31] On the other hand, another line of research did not find a significant relationship between insight and symptom severity in OCD.[7],[19],[32],[33],[34] Despite the mixed evidence, the association between symptom severity and poor insight is clinically relevant because it is to a large extent driven by poor resistance and control over the symptoms.[35] While performing cognitive behavior therapy, clinicians should pay added attention to emphasize the importance of resisting obsessions and preventing compulsions in patients with poor insight. Sub-optimal treatment response in OCD among patients with poor insight might also be contributed by these factors.[10],[11],[12] Our study showed greater severity of depressive symptoms in patients with poor insight. However, the difference between the poor and good insight groups did not reach statistical significance. There has been some evidence to suggest a higher prevalence of depressive symptoms and disorders in patients with lower levels of insight.[13],[30],[36] Evidence is not always consistent.[7],[37] The inconsistency is attributed to varying levels of depressive symptoms across the study samples. Similar to our study, research in childhood OCD[38] found a significant association between the severity of depressive symptoms and level of insight, but the relationship was rendered nonsignificant, when the depressive disorder was considered a comorbid diagnosis.

Two demographic variables, namely male gender and lower SES were linked with DSM-IV's specifier of poor insight. Although the statistical significance was lost for the gender, SES retained significance even after corrections for multiple comparisons. However, the significant relationship between SES and insight was lost in the regression analysis. Existing literature did not show a consistent association of levels of insight with either gender. Evidence is also limited for an association with SES.[39] Although the good and poor insight groups did not differ significantly in the duration of untreated OCD, the good insight group had a higher mean duration of untreated illness than the group with poor insight. This observation was counterintuitive. We believe treatment seeking in OCD, especially in the Indian context may not be entirely driven by individual's insight. In our collectivistic society, possibly family plays an important role in bringing the patients to the treatment. Patients with poor insight, although would feel lesser urge for treatment, they might cause a greater family level distress or dysfunction. On the other hand, patients with good insight may actually try to control and resist their symptoms, making these less apparent to the family. Nevertheless, this is a hypothesis and will need further research for confirmation.

The present study had several limitations. The sample size of patients with poor insight (at least for the DSM-IV specifier) was relatively small, resulting in potential false-negative associations. Moreover, regression analysis could not be carried out because of a small number of patients with poor insight. In the absence of multivariate analysis, the confounding effects of some clinical and demographic characteristics (e.g., confounding effect of psychosis in the association between male sex and poor insight) could not be tested. We did not use structured instruments for the diagnosis of OCD or comorbidities. This could be considered as a major limitation of the study. However, all diagnoses were made following a detailed evaluation and discussion with a consultant psychiatrist. Although we have assessed several demographic and clinical variables, we did not assess the response to treatment. The cross-sectional design of our study was an impediment to get reliable data on the treatment and prognosis. We hope future studies will look into this. Finally, the results of single-center-based study from a tertiary care institute setting can not be generalized. Convenience sampling may further affect the generalizability of our study results.


   Conclusion Top


In sum, the new DSM-5's insight specifier for OCD seemed to have high correspondence with DSM-IV's insight specifier and modest correlation with a multi-dimensional construct of insight. Patients with lower levels of insight had a significantly higher prevalence of psychosis and hoarding behavior. This relationship remained significant after corrections for multiple comparisons and controlling for other confounding variables. The application of different tools seems to influence the assessment of insight in OCD. Nevertheless, various assessment methods showed modest and correlations.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
   References Top

1.
American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Washington, DC: Author; 2000.  Back to cited text no. 1
    
2.
World Health Organization. The ICD-10 Classification of Mental and Behavioural Disorders. Clinical Descriptions and Diagnostic Guidelines. Geneva: WHO; 1992.  Back to cited text no. 2
    
3.
American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (DSM-5). 5th ed. Arlington: American Psychiatric Publishing; 2013.  Back to cited text no. 3
    
4.
World Health Organization. ICD-11 for Mortality and Morbidity Statistics. Geneva: World Health Organization; 2018.  Back to cited text no. 4
    
5.
Kozak MJ, Foa EB. Obsessions, overvalued ideas, and delusions in obsessive-compulsive disorder. Behav Res Ther 1994;32:343-53.  Back to cited text no. 5
    
6.
Wu MS, Lewin AB. Insight in Obsessive–Compulsive Disorder. The Wiley Handbook of Obsessive Compulsive Disorders. Hoboken, NJ: Wiley-Blackwell; 2017. p. 492-510.  Back to cited text no. 6
    
7.
Shimshoni Y, Reuven O, Dar R, Hermesh H. Insight in obsessive-compulsive disorder: A comparative study of insight measures in an Israeli clinical sample. J Behav Ther Exp Psychiatry 2011;42:389-96.  Back to cited text no. 7
    
8.
Hamblin RJ, Park JM, Wu MS, Storch EA. Variable insight in OCD. In: Obsessive-compulsive Disorder: Phenomenology, Pathophysiology, and Treatment. Oxfordshire: Oxford University Press; 2017. p. 129-37.  Back to cited text no. 8
    
9.
de Avila RC, do Nascimento LG, Porto RL, Fontenelle L, Filho EC, Brakoulias V, et al. Level of insight in patients with obsessive-compulsive disorder: An exploratory comparative study between patients with “Good Insight” and “Poor Insight”. Front Psychiatry 2019;10:413.  Back to cited text no. 9
    
10.
Visser H, van Megen H, van Oppen P, Hoogendoorn A, Glas G, Neziroglu F, et al. The impact of poor insight on the course of obsessive-compulsive disorder in patients receiving naturalistic treatment. J Obsessive Compuls Relat Disord 2017;13:42-8.  Back to cited text no. 10
    
11.
Catapano F, Sperandeo R, Perris F, Lanzaro M, Maj M. Insight and resistance in patients with obsessive-compulsive disorder. Psychopathology 2001;34:62-8.  Back to cited text no. 11
    
12.
Ravi Kishore V, Samar R, Janardhan Reddy YC, Chandrasekhar CR, Thennarasu K. Clinical characteristics and treatment response in poor and good insight obsessive-compulsive disorder. Eur Psychiatry 2004;19:202-8.  Back to cited text no. 12
    
13.
Matsunaga H, Kiriike N, Matsui T, Oya K, Iwasaki Y, Koshimune K, et al. Obsessive-compulsive disorder with poor insight. Compr Psychiatry 2002;43:150-7.  Back to cited text no. 13
    
14.
Eisen JL, Phillips KA, Baer L, Beer DA, Atala KD, Rasmussen SA. The brown assessment of beliefs scale: Reliability and validity. Am J Psychiatry 1998;155:102-8.  Back to cited text no. 14
    
15.
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. Arch Gen Psychiatry 1989;46:1006-11.  Back to cited text no. 15
    
16.
Leckman JF, Grice DE, Boardman J, Zhang H, Vitale A, Bondi C, et al. Symptoms of obsessive-compulsive disorder. Am J Psychiatry 1997;154:911-7.  Back to cited text no. 16
    
17.
Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry 1960;23:56.  Back to cited text no. 17
    
18.
Kay SR, Fiszbein A, Opler LA. The positive and negative syndrome scale (PANSS) for schizophrenia. Schizophr Bull 1987;13:261-76.  Back to cited text no. 18
    
19.
Bairwa M, Rajput M, Sachdeva S. Modified Kuppuswamy's Socioeconomic Scale: Social researcher should include updated income criteria, 2012. Indian J Community Med 2013;38:185-6.  Back to cited text no. 19
[PUBMED]  [Full text]  
20.
Reddy YC, Rao NP, Khanna S. An overview of Indian research in obsessive compulsive disorder. Indian J Psychiatry 2010;52:S200-9.  Back to cited text no. 20
    
21.
Kogan CS, Stein DJ, Rebello TJ, Keeley JW, Chan KJ, Fineberg NA, et al. Accuracy of diagnostic judgments using ICD-11 vs. ICD-10 diagnostic guidelines for obsessive-compulsive and related disorders. J Affect Disord 2020;273:328-40.  Back to cited text no. 21
    
22.
Foa EB, Kozak MJ, Goodman WK, Hollander E, Jenike MA, Rasmussen SA. DSM-IV field trial: Obsessive-compulsive disorder. Am J Psychiatry 1995;152:90-6.  Back to cited text no. 22
    
23.
Marazziti D, Dell'Osso L, Di Nasso E, Pfanner C, Presta S, Mungai F, et al. Insight in obsessive-compulsive disorder: A study of an Italian sample. Eur Psychiatry 2002;17:407-10.  Back to cited text no. 23
    
24.
Simpson HB, Reddy YC. Obsessive-compulsive disorder for ICD-11: Proposed changes to the diagnostic guidelines and specifiers. Braz J Psychiatry 2014;36 Suppl 1:3-13.  Back to cited text no. 24
    
25.
Reddy YJ, Simpson HB, Stein DJ. Obsessive-compulsive and related disorders in International Classification of Diseases-11 and its relation to International Classification of Diseases-10 and Diagnostic and Statistical Manual of Mental Disorders-5. Indian J Soc Psychiatry 2018;34:34-8.  Back to cited text no. 25
  [Full text]  
26.
Schirmbeck F, Zink M. Comorbid obsessive-compulsive symptoms in schizophrenia: Contributions of pharmacological and genetic factors. Front Pharmacol 2013;4:99.  Back to cited text no. 26
    
27.
Poyurovsky M, Faragian S, Pashinian A, Heidrach L, Fuchs C, Weizman R, et al. Clinical characteristics of schizotypal-related obsessive-compulsive disorder. Psychiatry Res 2008;159:254-8.  Back to cited text no. 27
    
28.
Poyurovsky M, Koran LM. Obsessive-compulsive disorder (OCD) with schizotypy vs. schizophrenia with OCD: Diagnostic dilemmas and therapeutic implications. J Psychiatr Res 2005;39:399-408.  Back to cited text no. 28
    
29.
Fontenelle JM, Harrison BJ, Santana L, Rosario MC, Versiani M, Fontenelle LF. Correlates of insight into different symptom dimensions in obsessive-compulsive disorder. Ann Clin Psychiatry 2013;25:11-6.  Back to cited text no. 29
    
30.
Cherian AV, Narayanaswamy JC, Srinivasaraju R, Viswanath B, Math SB, Kandavel T, et al. Does insight have specific correlation with symptom dimensions in OCD? J Affect Disord 2012;138:352-9.  Back to cited text no. 30
    
31.
Chakraborty V, Cherian AV, Math SB, Venkatasubramanian G, Thennarasu K, Mataix-Cols D, et al. Clinically significant hoarding in obsessive-compulsive disorder: Results from an Indian study. Compr Psychiatry 2012;53:1153-60.  Back to cited text no. 31
    
32.
Catapano F, Perris F, Fabrazzo M, Cioffi V, Giacco D, De Santis V, et al. Obsessive-compulsive disorder with poor insight: A three-year prospective study. Prog Neuropsychopharmacol Biol Psychiatry 2010;34:323-30.  Back to cited text no. 32
    
33.
Rauch SL, Jenike MA. Neurobiological models of obsessive-compulsive disorder. Psychosomatics 1993;34:20-32.  Back to cited text no. 33
    
34.
Türksoy N, Tükel R, Ozdemir O, Karali A. Comparison of clinical characteristics in good and poor insight obsessive-compulsive disorder. J Anxiety Disord 2002;16:413-23.  Back to cited text no. 34
    
35.
Storch EA, De Nadai AS, Jacob ML, Lewin AB, Muroff J, Eisen J, et al. Phenomenology and correlates of insight in pediatric obsessive-compulsive disorder. Compr Psychiatry 2014;55:613-20.  Back to cited text no. 35
    
36.
Tumkaya S, Karadag F, Oguzhanoglu NK, Tekkanat C, Varma G, Ozdel O, et al. Schizophrenia with obsessive-compulsive disorder and obsessive-compulsive disorder with poor insight: A neuropsychological comparison. Psychiatry Res 2009;165:38-46.  Back to cited text no. 36
    
37.
Alonso P, Menchón JM, Segalàs C, Jaurrieta N, Jiménez-Murcia S, Cardoner N, et al. Clinical implications of insight assessment in obsessive-compulsive disorder. Compr Psychiatry 2008;49:305-12.  Back to cited text no. 37
    
38.
Lewin AB, Bergman RL, Peris TS, Chang S, McCracken JT, Piacentini J. Correlates of insight among youth with obsessive-compulsive disorder. J Child Psychol Psychiatry 2010;51:603-11.  Back to cited text no. 38
    
39.
Jakubovski E, Pittenger C, Torres AR, Fontenelle LF, do Rosario MC, Ferrão YA, et al. Correlates of insight level in obsessive-compulsive disorder with dimensions of symptomology. Prog Neuropsychopharmacol Biol Psychiatry 2011;35:1677-81.  Back to cited text no. 39
    

Top
Correspondence Address:
Sandeep Grover
Department of Psychiatry, Postgraduate Institute of Medical Education and Research, Chandigarh - 160 012
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/indianjpsychiatry.indianjpsychiatry_1380_2

Rights and Permissions



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

Top