ABSTRACT
Background:
The greatest contributor to the economic impact of common mental disorders (CMDs) is said to be the loss of work productivity. There is a paucity of studies from India that looks at the impact of CMDs on the productivity of work, which costs both patient and society significantly.
Aim:
To assess and compare work productivity by evaluating both absolute and relative presenteeism and absenteeism, in persons with CMDs.
Materials and Methods:
This was a cross-sectional observational study on 220 subjects (110, 58, and 52 patients with depressive disorder, anxiety disorders, and somatoform disorders, respectively), recruited through purposive sampling. We evaluated work productivity using the World Health Organization Health and Work Performance Questionnaire.
Results:
Absolute absenteeism was significantly different before and after treatment for CMDs as a group but not for individual disorders. Relative absenteeism, absolute presenteeism, and relative presenteeism were all significantly different before and after treatment among both CMDs as a group and also among individual disorders. Both presenteeism and absenteeism (absolute as well as relative) did not differ significantly across the diagnostic groups. Work productivity has been linearly associated with illness severity and disability.
Conclusion:
CMDs are associated with a significant loss of work productivity. Presenteeism is costlier than absenteeism in affecting work productivity. Loss of work productivity appears to be transdiagnostic across all CMDs. Also, the severity of loss of work productivity is associated linearly with the severity of illness and disability.
Keywords: Absenteeism, anxiety disorders, common mental disorders, depression, presenteeism, somatoform disorder, work productivity
INTRODUCTION
The term common mental disorders (CMDs) was coined by Goldberg and Huxley in 1992 for mental health conditions that are commonly encountered at primary health care and community-level general hospitals.[1] It includes disorders such as depressive disorder (major depressive disorder and dysthymia), anxiety disorders (generalized anxiety disorder, panic disorder, phobias, social anxiety disorder, OCD, PTSD), and medically unexplained somatic symptom disorders (somatoform disorders).[2] The national prevalence estimate of CMDs from India’s National Mental Health Survey is 5.1%.[3] The current prevalence of CMDs in an outpatient psychiatry clinic of a specialty mental healthcare institute in India is 29.3%.[4] Studies in India identified that 17-46% of patients attending primary health centers suffer from CMDs. They impact all aspects of life, disabling a person from participating in work and social activities, resulting in a significant socioeconomic burden on the family and society.[5] The number of people suffering from these illnesses is going up globally, particularly in low and middle-income countries such as India.
The greatest contributor to the economic impact of depression and other mental disorders is said to be the loss of work productivity.[6] Fifty to sixty percent of the total economic burden of depression is due to the loss in work productivity from absenteeism (habitual pattern of absence from work) and presenteeism (poor performance at work due to illness).[7,8] Absolute absenteeism is calculated by counting the number of work-off days and represented in raw hours, and relative absenteeism is defined as the number of work-off days divided by the expected number of days at work when such absence happened, represented in percentage. Presenteeism seems to be a costlier problem than absenteeism. Absolute presenteeism is a measure of actual performance in relation to the possible performance during working hours. Relative presenteeism is measured as the ratio of the actual performance of the employee to the performance of most workers in the same job.[8,9] Studies showed that working people diagnosed with depression lose 20% of total work, of which 81% of work loss is due to presenteeism and 19% is due to absenteeism.[10] There is a paucity of studies in India that looks at the impact of CMDs on work productivity, which costs both patient and society significantly. In this study, we assessed and compared work productivity by evaluating both absolute and relative presenteeism and absenteeism, in persons with CMDs (depression, anxiety disorders, and somatoform disorders). Our other objective was to assess the association of work productivity with disability and the severity of illness.
MATERIALS AND METHODS
This was a cross-sectional observational study, conducted at a tertiary psychiatric hospital in South India, from April 2018 to January 2019. The study was approved by the institutional ethics committee vide No.NIMH/DO/IEC (BEH.Sc.DIV)/2017 dated 31/07/2017. We used the purposive sampling method to recruit subjects. Patients diagnosed with depression/anxiety disorders/somatoform disorders, either single or a combination of multiple CMDs diagnoses, attending the follow-up outpatient psychiatry clinic were recruited after obtaining written informed consent. The cost of illness for CMDs which was part of this study has been published elsewhere.[11]
Assuming a frequency of (P) 25% of CMDs in the hospital-based population with ±10% confidence limits, and a design effect of 1.5, the sample size at 95% CI is about 110 patients diagnosed with CMDs. Our sample size was 220, including 110 patients with depression, 58 patients with anxiety disorders, and 52 patients having somatoform disorders. Subjects in the age group of 18-65 years, fulfilling the ICD-10[12] criteria for primary diagnosis of depression/anxiety disorders/somatoform disorders were enrolled. Severe depression requiring inpatient care, presence of psychotic symptoms, other psychiatric co-morbidities, uncontrolled medical disorders, and substance dependence except for nicotine dependence, were excluded.
All assessments of every patient were completed on the same day. The socio-demographic data were obtained on the semi-structured socio-demographic proforma. The diagnosis was confirmed with Mini International Psychiatric Interview Plus version 5.0.0 (MINI Plus 5.0.0). It is a short and accurate structured psychiatric interview for research, intended as a tool to facilitate clinical data collection and processing of symptoms elicited by trained personnel.[13] The Clinical Global Impression- Severity (CGI-S)[14] is a clinician-administered tool used in psychiatric research for a global rating of illness severity on a 7-point scale, from normal to extremely ill. It was used to assess the severity of CMDs. The disability was assessed on Sheehan Disability Scale (SDS).[15] It is a brief, patient-rated measure of disability and impairment, used in other Indian studies,[11,16] but not validated. The purpose is to rate the extent of impairment in three interrelated domains, i.e., work, social life, and family life on a 10-point visual analog scale.
The World Health Organization Health and Work Performance Questionnaire (WHO HPQ)[17] was the key assessment tool used in the study to assess work productivity. It is a self-report instrument designed to estimate the workplace costs of health problems in terms of self-reported sickness absence (absenteeism) and reduced job performance (presenteeism). It is not validated in Indian studies. The scores can be calculated for seven days or for 28 days but assessed mainly for 28 days. The questionnaire also assesses work productivity before the treatment was initiated, as well as over the past one to two years. We have assessed the work productivity for the current 28 days as well before the initiation of treatment. For absenteeism, it assesses how many hours a subject worked during the said period and how many hours his/her employer expects him to work during the same period. It also assesses how many hours he/she would have worked in the absence of sickness. The questions on presenteeism are rated on a scale from 0 to 10, with 0 being the worst and 10 being the best performance. Thus, a higher score indicates better performance with respect to presenteeism. We assessed absolute absenteeism, relative absenteeism, absolute presenteeism, and relative presenteeism, with the calculation methods as described in the questionnaire.
Data obtained were analyzed using IBM SPSS Statistics for Windows Version 22. We used Pearson’s Chi-square test (or Fisher-Freeman-Halton exact test) and the Kruskal-Wallis test (with post hoc Mann-Whitney test) to compare the demographic and clinical variables among the three groups for categorical and continuous variables, respectively. Absenteeism and presenteeism across the three CMDs were compared using the Kruskal-Wallis test. Further, on MINI-based interviews, 85 (39%) were detected to have more than one CMD. The clinical diagnosis by the treating consultant based on the initial presentation/symptoms when the patient presented to the hospital was considered the primary CMD, which was also confirmed by MINI during the study assessments. The additional diagnoses detected through MINI at the time of inclusion in the study were considered the comorbid CMDs. Absenteeism and presenteeism between single vs multiple CMDs were compared using the Mann-Whitney U test. Wilcoxon signed-rank test was used to compare the work productivity before treatment and after treatment (current status). The association between work productivity and clinical parameters was analyzed using Spearman’s rho. All P values less than 0.05 (2-tailed) were considered significant.
RESULTS
Socio-demographic and clinical characteristics of the whole sample as well as the different diagnostic groups are represented in Table 1. The demographic factors that significantly differed across the different diagnostic groups include age, gender, education, socio-economic class, duration of illness, and duration of treatment. Table 2 represents the work productivity (absenteeism and presenteeism) across the three CMDs. Both presenteeism and absenteeism (absolute as well as relative) did not differ significantly across the diagnostic groups. Thus, work productivity is significantly affected across all three CMDs. Among the patients, 85 (39%) were detected to have more than one CMD on the MINI interview. However, the total sample of 220 (110 with depression, 58 with anxiety disorders, and 52 with somatoform disorders) represents the primary CMD categories, diagnosed initially by the treating consultant. There was no difference in presenteeism and absenteeism (absolute as well as relative) between those with single CMD as compared to multiple CMDs.
Table 1.
Sample characteristics
| Total n=220 | Depressive disorder n=110 | Anxiety disorder n=58 | Somatoform disorder n=52 | P | |
|---|---|---|---|---|---|
| Age, M (SD)a | 41.4 (10.2) | 41.6 (9.7) | 36.5 (8.8) | 46.4 (10.4) | <0.001*b |
| Gender, n (%)† | 0.029* | ||||
| Male | 82 (37.3) | 36 (32.7) | 30 (51.7) | 16 (30.8) | |
| Female | 138 (62.7) | 74 (67.3) | 28 (48.3) | 36 (69.2) | |
| Education, n (%)‡ | <0.001* | ||||
| Illiterate | 65 (29.5) | 33 (30) | 6 (10.3) | 26 (50) | |
| Primary | 48 (21.8) | 27 (24.5) | 9 (15.5) | 12 (23.1) | |
| High school | 51 (23.2) | 21 (19.1) | 21 (36.2) | 9 (17.3) | |
| College | 14 (6.4) | 6 (5.5) | 5 (8.6) | 3 (5.8) | |
| Undergraduate | 35 (15.9) | 19 (17.3) | 15 (25.9) | 1 (1.9) | |
| Postgraduate | 7 (3.2) | 4 (3.6) | 2 (3.4) | 1 (1.9) | |
| Occupation, n (%)# | 0.13 | ||||
| Unemployed | 4 (1.8) | 3 (2.7) | 0 | 1 (1.9) | |
| Unskilled/semiskilled | 100 (45.5) | 51 (46.4) | 19 (32.8) | 30 (57.7) | |
| Skilled | 73 (33.2) | 33 (30) | 23 (39.7) | 17 (32.7) | |
| Business | 15 (6.8) | 9 (8.2) | 4 (6.9) | 2 (3.8) | |
| Clerical | 19 (8.6) | 8 (7.3) | 9 (15.5) | 2 (3.8) | |
| Professional | 9 (4.1) | 6 (5.5) | 3 (5.2) | 0 | |
| Marital status, n (%)# | 0.078 | ||||
| Single | 20 (9.1) | 7 (6.4) | 11 (19) | 2 (3.8) | |
| Married | 166 (75.5) | 84 (76.4) | 41 (70.7) | 41 (78.8) | |
| Divorced/Separated | 6 (2.7) | 5 (4.5) | 0 | 1 (1.9) | |
| Widow/Widower | 28 (12.7) | 14 (12.7) | 6 (10.3) | 8 (15.4) | |
| Family type, n (%)† | 0.14 | ||||
| Nuclear | 148 (67.6) | 76 (69.1) | 43 (74.1) | 29 (56.9) | |
| Joint | 71 (32.4) | 34 (30.9) | 15 (25.9) | 22 (43.1) | |
| SES, n (%)† | 0.02* | ||||
| Lower | 154 (70) | 76 (69.1) | 33 (56.9) | 45 (86.5) | |
| Lower middle | 30 (13.6) | 15 (13.6) | 12 (20.7) | 3 (5.8) | |
| Middle and Upper | 36 (16.4) | 19 (17.3) | 13 (22.4) | 4 (7.7) | |
| Duration of illness (in years), M (SD)a | 6.27 (6.39) | 6.63 (6.52) | 4.64 (5.68) | 7.52 (6.67) | 0.009*c |
| Duration of treatment (in years), M (SD)a | 4.07 (5.39) | 4.69 (6.14) | 2.88 (4.99) | 4.27 (3.95) | 0.028*c |
| CGI-S, M (SD)a | 3.19 (1.01) | 3.12 (1.08) | 3.35 (0.97) | 3.15 (0.89) | 0.42 |
| SDS, M (SD)a | 9.88 (5.61) | 10.15 (6.16) | 10.10 (5.03) | 9.06 (5.00) | 0.55 |
CGI-S=Clinical global impression severity, SDS=Sheehan disability scale. *P<0.05 (2-tailed); †Pearson’s Chi square test; ‡Likelihood ratio; #Fisher-Freeman-Halton exact test; aKruskal-Wallis test; bPost hoc Mann-Whitney test (Somatoform > Depression > Anxiety); cPost hoc Mann-Whitney test (Somatoform=Depression > Anxiety)
Table 2.
Work productivity across the diagnostic groups
| Work productivity indicators | Total CMDs | Depressive disorder | Anxiety disorder | Somatoform disorder | P a |
|---|---|---|---|---|---|
| Absenteeism (hours in past month) | |||||
| Absolute absenteeism in hours |
n=219 49.4 (70.5) 0 (84), 0-360 |
n=109 52.4 (80.8) 0 (84), 0-360 |
n=58 45.0 (57.3) 4 (87), 0-192 |
n=52 48.0 (60.8) 28 (84), 0-224 |
0.87 |
| Relative absenteeism in % |
n=219 25.2 (32.8) 0 (50), 0-100 |
n=109 22.2 (33.3) 0 (46.4), 0-100 |
n=58 23.4 (30.4) 1.8 (50), 0-100 |
n=52 29.2 (34.8) 15.5 (50), 0-100 |
0.56 |
| Presenteeism (hours in past month)† | |||||
| Absolute presenteeism in % |
N=215 58.2 (22.1) 60 (40), 10-90 |
n=105 58.3 (22.6) 60 (40), 10-90 |
n=58 61 (19.9) 60(30), 10-90 |
n=52 55 (23.3) 60 (40), 10-90 |
0.42 |
| Relative presenteeism in % |
n=215 73.1 (26.1) 75 (50), 25-112.5 |
n=105 72.7 (26.7) 75 (50), 25-112.5 |
n=58 76.5 (24.6) 75 (44.4), 25-112.5 |
n=52 70.2 (26.7) 75 (50), 25-112.5 |
0.45 |
Mean (SD), Median (IQR), Range. aKruskal-Wallis test; †Restricted between 25-200%
Table 3 shows the comparison of absenteeism and presenteeism before treatment and at the time of study participation, i.e., while on treatment. It shows that absolute absenteeism was significantly differing before and after treatment for the total sample and somatoform disorders but not the individual disorders. However relative absenteeism, absolute presenteeism, and relative presenteeism were all significantly different before and after treatment both for individual disorders and for the whole study sample.
Table 3.
Changes in work productivity with treatment
| Work productivity indicators | Total n=103 | Depressive disorder n=50 | Anxiety disorder n=27 | Somatoform disorder n=26 |
|---|---|---|---|---|
| Absolute absenteeism (hours per month) | ||||
| Before treatment | 26.1 (18.4) | 28.5 (19.5) | 30 (17.7) | 17.6 (14.5) |
| 27 (28) | 28 (28) | 28 (31) | 17.5 (28) | |
| 0-105 | 0-105 | 0-56 | 0-48 | |
| Current | 41.0 (58.5) | 39.7 (64.1) | 46.5 (60.3) | 37.8 (45.9) |
| 0 (80) | 0 (81) | 24 (96) | 14 (63) | |
| 0-280 | 0-280 | 0-192 | 0-168 | |
| Pa | 0.028 | 0.381 | 0.360 | 0.029 |
| Relative absenteeism (hours per month) | ||||
| Before treatment | 57.4 (33.5) | 62.8 (31.2) | 59.5 (32.9) | 44.8 (36.3) |
| 66.7 (50) | 66.7 (44) | 60 (66.7) | 41.4 (71.9) | |
| 0-100 | 0-100 | 0-100 | 0-100 | |
| Current | 22.4 (29.9) | 19.9 (28.6) | 23.8 (31.6) | 25.6 (31.4) |
| 0 (50) | 0 (44.6) | 12.5 (50) | 10 (50) | |
| 0-100 | 0-100 | 0-100 | 0-100 | |
| Pa | <0.001 | <0.001 | <0.001 | 0.021 |
|
| ||||
| n=107 | n=51 | n=27 | n=29 | |
|
| ||||
| Absolute presenteeism in % (in past month) | ||||
| Before treatment | 36.45 (22.7) | 30.4 (19.7) | 39.3 (26.3) | 44.5 (21.6) |
| 40 (30) | 30 (30) | 40 (50) | 40 (35) | |
| 0-90 | 10-80 | 0-90 | 10-80 | |
| Current | 60.6 (20) | 60.39 (19.6) | 63.7 (19) | 58.3 (21.9) |
| 60 (30) | 60 (30) | 70 (30) | 60 (40) | |
| 10-90 | 10-90 | 20-90 | 10-90 | |
| Pa | <0.001 | <0.001 | <0.001 | 0.005 |
| Relative presenteeism in % (Restricted between 25-200%) | ||||
| Before treatment | 48.5 (23.9) | 41.2 (21.7) | 53.7 (27) | 56.6 (24.8) |
| 50 (37.5) | 37.5 (25) | 50 (50) | 50 (39.6) | |
| 25-112.5 | 25-100 | 25-112.5 | 25-100 | |
| Current | 76.3 (23.9) | 75.7 (23.9) | 79.6 (23.8) | 74.1 (24.6) |
| 75 (37.5) | 75 (37.5) | 87.5 (37.5) | 75 (38.2) | |
| 25-112.5 | 25-112.5 | 25-112.5 | 25-112.5 | |
| Pa | <0.001 | <0.001 | <0.001 | 0.005 |
Mean (SD), Median (IQR), Range current means - on treatment. aWilcoxon signed rank test
Work productivity was significantly associated with CGI-S scores and the total scores on SDS, but not with duration of illness and duration of treatment [Table 4]. Overall, the results show that work productivity is significantly affected in patients with CMDs, despite being under treatment. Work productivity was also associated negatively with the severity of illness as well as the disability, associated with CMDs.
Table 4.
Association (rs) between work productivity and clinical parameters
| Absolute absenteeism (hours per month) | Relative absenteeism (hours per month) | Absolute presenteeism in % (in past month) | Relative presenteeism in % (Restricted between 25-200%) | |
|---|---|---|---|---|
| Duration of illness | 0.169 | 0.160 | −0.262* | −0.258* |
| Duration of treatment | 0.022 | 0.020 | −0.075 | −0.063 |
| CGI-S | 0.549* | 0.563* | −0.648* | −0.649* |
| SDS total score | 0.664* | 0.681* | −0.703* | −0.704* |
CGI-S=Clinical global impression severity, IDEAS=Indian disability evaluation and assessment scale, SDS=Sheehan disability scale. *P<0.05 (2-tailed); Spearman’s rho (rs)
DISCUSSION
We studied the role of CMDs in work productivity and the associated disability. This is the first study that assessed both absenteeism and presenteeism, absolute as well as relative, i.e., the four different types of impaired work productivity. The average absolute absenteeism scores of all study subjects range from 45 to 52 hours per 4 weeks lost due to absence from work. This would mean a loss of productivity for about a week during the approximate period of one month. Relative absenteeism scores range from 22 to 29%, which indicates that a quarter of the productivity of a month is lost, while the person is actually at work. In other words, each patient with CMDs is absent one-fourth of the time from their work. Similarly, the average absolute presenteeism scores range from 55 to 61% across different CMDs. So, work productivity translates to less than 50% of what can be expected for a healthy person. We found that relative presenteeism scores ranged from 70 to 76% per month, i.e., equal to about ¾ of a normal person’s work productivity per month. The absenteeism and presenteeism scores did not differ across the diagnoses, thus indicating that irrespective of the diagnosis, all CMDs have a significant impact on work productivity. This also supports the transdiagnostic approach of CMDs in view of public health and primary care perspective. In this study, presenteeism seems to have affected more than absenteeism in our study subjects, which is in accordance with the existing research.[9]
The previous studies have been conclusive of the negative linear relationship between work productivity and the severity of disorders such as depression and anxiety disorders.[10,17] Some of them have reported that more than one CMD in the same patient is associated with more disability and work impairment.[18] They also support the findings that presenteeism is a stronger correlate of depression/anxiety than absenteeism.[9,19-22] One of the Indian studies also reports a similar rate of absenteeism of 54% and much higher presenteeism of 90% in CMDs. However, all subjects in that study had the cardiovascular disease as a co-morbidity along with CMDs, and the study has not assessed the absolute and relative aspects separately like in our study.[19] One study compared the work productivity of paid workers having unexplained physical symptoms (UPS) (which included undifferentiated somatoform disorder and pain disorder) with the general population, healthy workforce, and workforce with chronic medical illness. Patients with UPS had the largest percentage of absenteeism compared with that the other reference populations. Also, the mean work-related cost due to presenteeism in UPS was higher than that of patients with other psychiatric disorders but lower than that of patients with rheumatic arthritis. However, the study has not shared the details of the comorbid psychiatric disorders in their study population (41% of axis I and 29% of axis II comorbid disorders according to DSM IV, have been reported) associated with UPS, thus making it difficult to attribute absenteeism and presenteeism to UPS alone.[21]
The duration of illness significantly differed across the three diagnostic groups, with somatoform disorders having more chronic courses than depression and anxiety. Though there is no consistent research knowledge on the course of somatoform disorders, a proportion of these disorders is said to run into chronicity.[22] Also, the duration of treatment differed across the groups with patients having depression receiving a longer duration of treatment than the other groups, at the time of study participation. However, all three CMDs had mild severity of illness as rated on CGI-S and did not differ significantly. The disability scores on SDS indicated a mild level of disability. This may be possibly due to the fact that all patients were on regular medication and so were on the path to recovery. Furthermore, our study showed that the severity of illness and disability had a positive association with both absenteeism (absolute and relative) and presenteeism (absolute and relative), thus indicating that the higher the scores on CGI-S and SDS, severe is the loss of work productivity. Though we did not come across similar studies, a study that compared disability in depression/anxiety disorders with somatic illnesses, as well as somatic illnesses comorbid with depression/anxiety disorders, found that both somatic illnesses and depression/anxiety caused substantial disability individually, but it was highest when they were comorbid.[18] Some studies have estimated loss of productivity in terms of currency,[19,21] however we did not infer it in terms of money. Also, we did not consider unpaid work like some of the other studies that showed unpaid work suffered more than paid work due to absenteeism and presenteeism.
The study has some limitations. This was a cross-sectional study. A longitudinal study with symptomatic patients before the onset of treatment would have inferred the course of improvement of work productivity with the recovery of illness. As the subjects were asked to recall and complete the WHO HPQ before the initiation of treatment, which can be several years before the current assessment, recall bias cannot be ruled out. Further, there was no normative comparative group of working people to set a baseline of work productivity and compare the patients with them. We did not include an arm of patients with physical disorders, and we did not match the sample for comorbid physical problems. Also, we did not compare differential work productivity based on the subjects’ professions, which could have provided information on differences in challenges with different jobs, if any. We did not represent work productivity with currency as mentioned above, which could have provided another perspective of quantifying the loss of productivity.
Nevertheless, the strengths of our study include an extensive assessment of work productivity including all aspects such as absolute and relative absenteeism, and absolute and relative presenteeism; an adequate sample size; and the use of standardized study tools for assessment (though SDS and WHOHPQ are not validated for Indian studies). Though it is a study of one of its kind in terms of methodology, as far as the main findings are concerned, it agrees with the previous studies that CMDs are associated with significant loss of work productivity and presenteeism is a costlier problem than absenteeism, among Indian subjects.
CONCLUSIONS
All CMDs are associated with a significant loss of work productivity. Presenteeism affects work productivity more than absenteeism. Loss of work productivity is transdiagnostic, not significantly different across different CMDs. Also, the severity of loss of work productivity is associated linearly with the severity of illness and disability. Thus we suggest it is essential to implement mechanisms for early diagnosis and management of CMDs across the country, to overcome the economic losses due to deficits in work productivity.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
Acknowledgement
We are grateful to the faculty and scholars of the Department of Biostatistics at NIMHANS, Bengaluru, for their role in guiding the study tools.
REFERENCES
- 1.Goldberg D. A bio-social model for common mental disorders. Acta Psychiatr Scand Suppl. 1994;385:66–70. doi: 10.1111/j.1600-0447.1994.tb05916.x. [DOI] [PubMed] [Google Scholar]
- 2.Patel V, Pereira J, Coutinho L, Fernandes R. Is the labelling of common mental disorders as psychiatric illness clinically useful in primary care? Indian J Psychiatry. 1997;39:239–46. [PMC free article] [PubMed] [Google Scholar]
- 3.Jayasankar P, Manjunatha N, Rao GN, Gururaj G, Varghese M, Benegal V NMHS India National Collaborator Group. Epidemiology of common mental disorders: Results from “National Mental Health Survey”of India, 2016. Indian J Psychiatry. 2022;64:13–9. doi: 10.4103/indianjpsychiatry.indianjpsychiatry_865_21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Chander R. Prevalence and socio-clinical correlates of patients with common mental disorders attending specialty mental health care. Thesis submitted to NIMHANS Bengaluru for partial fulfillment of MD Psychiatry, 2018 [Google Scholar]
- 5.Insel TR, Collins PY, Hyman SE. Darkness Invisible: The Hidden Global Costs of Mental Illness. Foreign Affairs. [[Last accessed on 2022 Nov 02]]. 2015 January/February. Available from: https://www.foreignaffairs.com/articles/africa/darkness-invisible .
- 6.Sagar R, Pattanayak RD. Depression in India: Let's talk to physicians too. J Mental Health Hum Behav. 2017;22:4–6. [Google Scholar]
- 7.Evans-Lacko S, Knapp M. Global patterns of workplace productivity for people with depression: Absenteeism and presenteeism costs across eight diverse countries. Soc Psychiatry Psychiatr Epidemiol. 2016;51:1525–37. doi: 10.1007/s00127-016-1278-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Despiégel N, Danchenko N, François C, Lensberg B, Drummond MF. The use and performance of productivity scales to evaluate presenteeism in mood disorders. Value Health. 2012;15:1148–61. doi: 10.1016/j.jval.2012.08.2206. [DOI] [PubMed] [Google Scholar]
- 9.Uribe JM, Pinto DM, Vecino-Ortiz AI, Gómez-Restrepo C, Rondón M. Presenteeism, absenteeism, and lost work productivity among depressive patients from five cities of Colombia. Value Health Reg Issues. 2017;14:15–9. doi: 10.1016/j.vhri.2017.03.001. [DOI] [PubMed] [Google Scholar]
- 10.World Health Organization. The ICD 10 Classification of Mental and Behavioural Disorders. World Health Organization. Oxford: Oxford University Press; 1992. [Google Scholar]
- 11.Kondapura MB, Manjunatha N, Nagaraj AKM, Praharaj SK, Kumar CN, Math SB, et al. Cost of illness analysis of common mental disorders: A study from an Indian academic tertiary care hospital. Indian J Psychol Med (in press) doi: 10.1177/02537176221108867. doi:10.1177/02537176221108867. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Sheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E, et al. The Mini-International Neuropsychiatric Interview (M. I. N. I.): The development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry. 1998;59((Suppl 20)):22–33. [PubMed] [Google Scholar]
- 13.Busner J, Targum SD. The clinical global impressions scale: Applying a research tool in clinical practice. Psychiatry (Edgmont) 2007;4:28–37. [PMC free article] [PubMed] [Google Scholar]
- 14.Sheehan DV, Harnett-Sheehan K, Raj BA. The measurement of disability. Int Clin Psychopharmacol. 1996;11((Suppl 3)):89–95. doi: 10.1097/00004850-199606003-00015. [DOI] [PubMed] [Google Scholar]
- 15.Kessler RC, Barber C, Beck A, Berglund P, Cleary PD, McKenas D, et al. The World Health Organization Health and Work Performance Questionnaire (HPQ) J Occup Environ Med. 2003;45:156–74. doi: 10.1097/01.jom.0000052967.43131.51. [DOI] [PubMed] [Google Scholar]
- 16.Nemani A, Kampalli SVRNPK, Nadukuru NR. Disability associated with premenstrual dysphoric disorder: A prospective study. Arch Ment Health. 2022;23:118–22. [Google Scholar]
- 17.Johnston DA, Harvey SB, Glozier N, Calvo RA, Christensen H, Deady M. The relationship between depression symptoms, absenteeism and presenteeism. J Affect Disord. 2019;256:536–40. doi: 10.1016/j.jad.2019.06.041. [DOI] [PubMed] [Google Scholar]
- 18.Bokma WA, Batelaan NM, van Balcom AJLM, Pinninx BWJH. Impact of anxiety and/or depressive disorders and chronic somatic diseases on disability and work impairment. J Psychosom Res. 2017;94:10–6. doi: 10.1016/j.jpsychores.2017.01.004. [DOI] [PubMed] [Google Scholar]
- 19.Fathima FN, Kahn JG, Krishnamachari S, Ekstrand M. Productivity losses among individuals with common mental illness and comorbid cardiovascular disease in rural Karnataka, India. Int J Noncommun Dis. 2019;4:86–92. doi: 10.4103/jncd.jncd_17_19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Rost KM, Meng H, Xu S. Work productivity loss from depression: Evidence from an employer survey. BMC Health Serv Res. 2014;14:597. doi: 10.1186/s12913-014-0597-y. doi:10.1186/s12913-014-0597-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Zonneveld LNL, Sprangers MAG, Kooiman CG, van’t Spijker A, Busschbach JJV. Patients with unexplained physical symptoms have poorer quality of life and higher costs than other patient groups: A cross-sectional study on burden. BMC Health Serv Res. 2013;13:520. doi: 10.1186/1472-6963-13-520. doi:10.1186/1472-6963-13-520. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.olde Hartman TC, Borghuis MS, Lucassan PLBJ, van de Laar FA, Speckens AE, van Weel C. Medically unexplained symptoms, somatisation disorder and hypochondriasis: Course and prognosis. A systematic review. J Psychosom Res. 2009;66:363–77. doi: 10.1016/j.jpsychores.2008.09.018. [DOI] [PubMed] [Google Scholar]