WHODAS 2.0 is the standard measure of disability promoted by World Health Organization whereas Clinical Global Impression (CGI) is a widely used scale for determining severity of mental illness. Although a close relationship between these two scales would be expected, there are no relevant studies on the topic. In this study, we explore if WHODAS 2.0 can be used for identifying severity of illness measured by CGI using the Fisher Linear Discriminant Analysis (FLDA) and for identifying which individual items of WHODAS 2.0 best predict CGI scores given by clinicians. One hundred and twenty-two patients were assessed with WHODAS 2.0 and CGI during three months in outpatient mental health facilities of four hospitals of Madrid, Spain. Compared with the traditional correction of WHODAS 2.0, FLDA improves accuracy in near 15%, and so, with FLDA WHODAS 2.0 classifying correctly 59.0% of the patients. Furthermore, FLDA identifies item 6.6 (illness effect on personal finances) and item 4.5 (damaged sexual life) as the most important items for clinicians to score the severity of illness.
Having accurate indicators that measure the impact of illnesses on people’s live is a critical issue in several areas of medicine, including mental health. Disability is a useful construct for this. Disability refers to the difficulty of people suffering a disease to keep their premorbid or normal functionality. The World Health Organization (WHO) describes disability as a difficulty in functioning at the body, person, or societal levels, in one or more life domains, as experienced by an individual with a health condition in interaction with contextual factors [
The need to quantify disability first appears in 1962, with the publication of Health-Sickness Rating Scale (HSRS) [
In response to the need to have a tool to evaluate functionality with a cross-cultural perspective and at the same time be easy to apply, WHO developed the World Health Organization Disability Assessment Schedule (WHODAS), and its next version, with more domains, WHODAS 2.0 [
In routine clinical practice, clinicians generally classify patients’ illness severity according to their clinical experience and are supported by severity criteria used in measurement scales and classification manuals. Due to time restrictions in clinical practice, use of scales and questionnaires is limited. Simple scales such as the Global Clinical Impression Scale (CGI) allow the clinician to measure the severity and evolution of a patient without too much impact on the clinician’s care and clinical activity. CGI is an evaluation method for seriousness of symptoms in mental illnesses. The scale is composed by three global measures: severity of illness at the moment of evaluation (CGI-S); global improvement since last visit (CGI-I), and an efficacy index useful to compare the premorbid status and severity of treatment side effects (CGI-E). It is commonly used in clinical trials in depression or schizophrenia [
Although the relationship between illness severity and functionality or disability has been widely studied in mental disorders such as schizophrenia [
In the present study, we use Fisher Linear Discriminant Analysis (FLDA), a pattern recognition method [
From January to March 2017, a sample of 122 patients was evaluated in routine psychiatric or psychological visits at mental health facilities affiliated with the Fundación Jiménez Díaz Hospital in Madrid, Spain (Rey Juan Carlos Móstoles Hospital, Infanta Elena Valdemoro Hospital, General Hospital of Villalba, and University Hospital Fundación Jiménez Díaz).
All patients attended in the Psychiatry Department were candidates to participate in the study as long as they met the following inclusion criteria: outpatients, aged 18 or older, and who gave written informed consent. Exclusion criteria were illiteracy, refusal to participate, and situations in which the patient’s state of health did not allow for written informed consent.
All clinicians (psychiatrists, psychologists, and mental health nurses) were trained in the use of WHODAS 2.0 and ICG in December 2016 in a consensus meeting and after that, all of them were encouraged to use the instruments in their daily clinical practice. They were all asked to assess between 5 to 7 patients. Thirty-one clinicians participated actively in patient’s recruitment and they included a mean of
CGI and WHODAS 2.0 were used to assess all patients, in an electronical version integrated in MEmind (
WHODAS 2.0 [
CGI is an instrument to assess the severity of symptoms of mental disease according to the judgment of the clinician [
Furthermore, information on sociodemographics and ICD 10 diagnosis was collected.
This study was conducted in compliance with the Declaration of Helsinki and approved by the IRB at Fundación Jiménez Díaz Hospital. All patients who participated in the study signed an informed consent that was detailed by the clinician who did the assessment.
Concerning data protection, access to the online user interface was restricted to participating clinicians (MEmind Study Group). The data provided by the clinician was encrypted by Secure Socket Layer/Transport Layer Security (SSL/TLS) between the investigator’s computer and the server. Data was stored in an external server created for research purposes. An external auditor guaranteed that security measures met the Organic Law for Data Protection standards at a high protection level.
In the pattern recognition community, Fisher Linear Discriminant Analysis (FLDA) [
Once the data has been transformed into a more suitable space, we use the
A
The sample contains 55 (45.1%) men and 67 (54.9%) women, with a mean age of
Table
Diagnoses of total sample.
Mental and behavioural diagnoses |
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Percent |
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Schizophrenia | 24 | 14 |
Delusional disorder | 7 | 4.09 |
Unspecified nonorganic psychosis | 4 | 2.33 |
Schizoaffective disorders | 5 | 2.92 |
Schizotypal disorder | 1 | 0.58 |
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Bipolar affective disorder | 12 | 7.01 |
Depressive episode | 8 | 4.67 |
Dysthymia | 8 | 4.67 |
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Adjustment disorders | 10 | 5.84 |
Mixed anxiety and depressive disorder | 13 | 7.60 |
Panic disorder | 1 | 0.58 |
Specific (isolated) phobias | 2 | 1.16 |
Agoraphobia | 1 | 0.58 |
Dissociative disorders | 1 | 0.58 |
Obsessive-compulsive disorder | 1 | 0.58 |
Hypochondriacal disorder | 1 | 0.58 |
Posttraumatic stress disorder | 1 | 0.58 |
Somatoform disorders | 2 | 1.16 |
Neurasthenia | 1 | 0.58 |
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Mental and behavioural disorders due to use of alcohol | 9 | 5.26 |
Mental and behavioural disorders due to use of cannabinoids | 7 | 4.09 |
Mental and behavioural disorders due to use of cocaine | 3 | 1.75 |
Mental and behavioural disorders due to use of opioid | 1 | 0.58 |
Mental and behavioural disorders due to use of sedatives or hypnotics | 1 | 0.58 |
Pathological gambling | 1 | 0.58 |
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Personality disorder | 15 | 8.77 |
Anorexia nervosa | 2 | 1.16 |
Disturbance of activity and attention | 8 | 4.67 |
Mild mental retardation | 1 | 0.58 |
Sexual dysfunction, not caused by organic disorder or disease | 2 | 1.16 |
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Other diseases |
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Percent |
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Essential (primary) hypertension | 3 | 1.75 |
Human immunodeficiency virus [HIV] disease | 2 | 1.16 |
Malignant neoplasm of breast | 2 | 1.16 |
Angina pectoris | 1 | 0.58 |
Diabetes Mellitus | 1 | 0.58 |
Generalized pain | 1 | 0.58 |
Hearing loss, unspecified | 1 | 0.58 |
Hypothyroidism | 2 | 1.16 |
Thalassaemia | 1 | 0.58 |
Chronic hepatitis | 1 | 0.58 |
Diabetes polyneuropathy | 1 | 0.58 |
Chronic prostatitis | 1 | 0.58 |
Dizziness | 1 | 0.58 |
ICG-S measured by the clinician.
Score |
|
Percentage |
---|---|---|
Normal, not at all ill (1) | 5 | 4.10 |
Borderline mentally ill (2) | 3 | 2.46 |
Mildly ill (3) | 4 | 3.28 |
Moderately ill (4) | 35 | 28.69 |
Markedly ill (5) | 57 | 46.72 |
Severely ill (6) | 14 | 11.48 |
Among the most extremely ill patients (7) | 4 | 3.28 |
When we performed Pearson test for study correlation, we found a low positive correlation between CGI-S and total WHODAS 2.0
We performed a Fisher Linear Discriminant Analysis and obtained the weights of individual items for each projection (Table
Weights assigned by FLDA algorithm to individual items in the two projections.
Domain | Items: in the last 30 days, how much difficulty did you have in: | Weight for 1st FLDA | Weight for 2nd FLDA |
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(1) Cognition | (1.1) Concentrating on doing something for 10 minutes |
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(1.2) Remembering to do important things |
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(1.3) Analysing and finding solutions to problems in day to day life |
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(1.4) Learning a new task, for example, learning how to get to a new place |
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(1.5) Generally understanding what people say |
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(1.6) Starting and maintaining a conversation |
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(2) Mobility | (2.1) Standing for long periods such as 30 minutes |
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(2.2) Standing up from sitting down |
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(2.3) Moving around inside your home |
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(2.4) Getting out of your home |
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(2.5) Walking a long distance such as a kilometre |
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(3) Self-care | (3.1) Washing your whole body |
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(3.2) Getting dressed |
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(3.3) Eating |
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(3.4) Staying by yourself for a few days |
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(4) Getting along | (4.1) Dealing with people you do not know |
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(4.2) Maintaining a friendship |
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(4.3 Getting along with people who are close to you |
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(4.4) Making new friends |
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(4.5) Sexual activities |
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(5) Life activities | (5.1) Taking care of your household responsibilities |
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(5.2) Doing most important household tasks well |
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(5.3) Getting all the household work done that you needed to do |
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(5.4) Getting your household work done as quickly as needed |
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(5.5) Your day-to-day work/school |
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(5.6) Doing your most important work/school tasks well |
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(5.7) Getting done all the work that you needed to do |
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(5.8) Getting your work done as quickly as needed |
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(6) Participation | (6.1) Joining in community activities |
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(6.2) Because of barriers or hindrances in the world |
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(6.3) Living with dignity |
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(6.4) From time spent on health condition |
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(6.5) Feeling emotionally affected |
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(6.6) Because health is a drain on your financial resources |
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(6.7) With your family facing difficulties due to your health |
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(6.8) Doing things for relaxation or pleasure by yourself |
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Scatter plot of the FLDA scores. Green dots represent ICG-S from 1 to 4 (low severity). Blue dots represent ICG-S of 5 (medium severity). Red dots represent ICG-S of 6 or 7 (high severity).
In Table
In order to determine the accuracy attained by our FLDA/
Classification accuracy of FLDA and clinical approaches.
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1 | 3 | 5 | 7 |
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FLDA | 45.9 | 59.0 | 53.3 | 45.9 |
Clinical approach | 45.9 | 40.1 | 42.6 | 36.9 |
Finally, we make a classification map for the best result
Classification map.
We found that WHODAS 2.0 is a useful scale for measuring severity of illness scored by clinicians with ICG, and so WHODAS 2.0 correctly classifies 59.0% of the patients. Compared with the traditional correction of WHODAS 2.0, FLDA improves accuracy in near 15% with respect to the traditional method. However, as it is shown in the classification map figure, the classification is far from being perfect and there are overlapped areas and some patients can be catalogued by WHODAS 2.0 with a low level of illness severity whereas clinicians classified them with higher scores and vice versa. Finally, FLDA shows that there are certain items of WHODAS more important for clinicians when considering severity of illness, specifically items regarding economic repercussion of illness and regarding a detriment of sexual life.
In contrast with previous studies, our sample is composed of patients obtained in a real clinical environment with a range variety of diagnoses which represent one strength of our study. To develop studies in real clinical settings is important as this gives us a useful insight for a daily practice. Furthermore, we do not just study correlations between CGI and WHODAS 2.0 but use a more sophisticated statistical method and demonstrated that FLDA is useful for better classification of illness severity of patients using a disability measure, in a similar way that we previously did in the field of suicide [
However, our study also has certain limitations. First, our sample size was relatively small, which in part is influenced by data collection method as MEmind web platform is time consuming for a clinician. Moreover, while the range variety of diagnoses composing our sample is a strength, this heterogeneity can also be considered a limitation. As the impact on the disease in the functionality is very different in every mental disorder, a further analysis differentiating by diagnosis would be necessary, but unfortunately our sample size does not allow us to do that. This point should be taken into account as a future perspective of our work.
In conclusion, in this study we demonstrated an association between WHODAS 2.0 and ICG in a group of patients heterogeneously diagnosed. Future works focusing on this relationship in particular diagnoses are warranted.
The authors declare that they have no conflicts of interest.
This work was partially supported by Instituto de Salud Carlos III Fondos FEDER (ISCIII PI16/01852), Delegación del Gobierno para el Plan Nacional de Drogas (20151073), and American Foundation for Suicide Prevention (AFSP) (LSRG-1-005-16). The authors want to acknowledge the collaboration of the clinicians (MEmind Study Group) involved in the collection of data and the development of MEmind.