| Abstract|| |
Background: The burden of mental disorders has been increasingly recognized and 450 million people globally are suffering from mental illness. Mental–physical comorbidity has adverse effects on the overall outcome. Research is scarce with regard to mental health screening in the context of “preventive health care” in India. Thus, the study aimed to identify the prevalence of mental illness and the effect on quality of life (QOL) among participants attending preventive health-care unit (PHCU).
Settings and Design: This was a cross-sectional study conducted in PHCU of a tertiary hospital in Puducherry.
Materials and Methods: All consecutive participants (>18 years) attending PHCU were included in the study. The Standard for Clinicians' Interview in Psychiatry (SCIP) screening module, Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) Level 1 Cross-Cutting Symptom Measure, Mini-Cog, and Quality of Life Enjoyment and Satisfaction Questionnaire were administered. Relevant diagnostic modules of SCIP were applied to participants who screened positive on SCIP. Data analysis was performed using SPSS (version 17.0).
Results: The mean age of participants was 43.38 ± 13.99 years. Of 203 participants enrolled, 28.1% screened positive and 26.1% were confirmed to have psychiatric disorder. About 4% screened positive for cognitive impairment. Most commonly diagnosed disorders were alcohol use disorder and major depressive disorder. The prevalence of depressive disorder was higher in patients with physical disorder. Participants with psychiatric disorder alone or with both psychiatric and physical disorders had significantly poorer QOL (F = 27.13; P < 0.001).
Conclusion: One-fourth of the participants attending preventive health-care services were found to have psychiatric disorders. The presence of psychiatric disorder was associated with significantly poorer QOL. This highlights the importance of routine mental health screening in this setting.
Keywords: Preventive health care, psychiatric morbidity, quality of life
|How to cite this article:|
Raghuraman P, Balasundaram S, Sarkar S, Subramaniam E. A cross-sectional study of psychiatric morbidity and quality of life among participants utilizing the preventive health-care services of a tertiary hospital. Indian J Psychiatry 2019;61:192-7
|How to cite this URL:|
Raghuraman P, Balasundaram S, Sarkar S, Subramaniam E. A cross-sectional study of psychiatric morbidity and quality of life among participants utilizing the preventive health-care services of a tertiary hospital. Indian J Psychiatry [serial online] 2019 [cited 2019 Mar 24];61:192-7. Available from: http://www.indianjpsychiatry.org/text.asp?2019/61/2/192/253821
| Introduction|| |
The term “health” is defined as a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity. The World Health Organization defined “mental health” as a state of mental well-being where an individual can understand his/her own abilities and to cope with the stressors of life, also to work productively, so that he/she is able to contribute to the society.
Mental illness is known to be a significant public health problem. Mental disorders such as depression, anxiety disorders, and substance use disorders are often nondetected/underdetected among patients attending public health facilities.,, Globally, around 450 million people are suffering from mental disorders and account for 12% of the disease burden globally., The National Mental Health Survey done in India from 2015 to 2016 revealed that the prevalence of psychiatric disorders is 10.6% and lifetime prevalence is 13.7%.
Research has established that mental health has profound influence on physical health through several pathways: brain-body information transfer systems (hypothalamic-pituitary-adrenal axis, autonomic nervous system, and immune system) and health behavior pathway., Mental disorders are more commonly associated with increased incidence of chronic diseases such as diabetes, obesity, asthma, epilepsy, and cancer. It is found that one-third of people attending medical and surgical outpatient clinics have a psychiatric disorder. Mental illness is related with lower use of medical care, reduced adherence to treatment therapies, and higher risks of unfavorable health outcome. The burden of a mental disorder may also lower a person's potential to adapt to symptoms of noncommunicable diseases. Comorbidity of depression with chronic medical disorders can frequently result in increased utilization of health-care facilities, reduced efficacy, and higher disability. Depressive disorders often complicate other medical conditions and add to the cost of health care. If depression is detected and treated at early stages, it reduces the direct cost of medications, hospital care, and community-based care.
Quality of life (QOL) linked to health has become a vital outcome measure for psychiatric patients in recent years.,, The concept of QOL has steadily shifted from an objective and sociological perspective to a psychosocial perspective, wherein one's sense of well-being becomes an important dimension of QOL. Patients suffering from psychiatric disorders are likely to experience reduced enjoyment or satisfaction in many aspects of their life. Hence, QOL has become an integral part of psychiatric assessment. Moreover, the coexistence of physical and mental disorder in a person can further bring down the QOL.
Very low percentages (40%) of people suffering from mental illness seek professional help. Recognition of mental health problems can facilitate treatment-seeking behavior. In one study, majority of the participants had waited 3–5 years before looking for expert help for common mental disorders. Mental health literacy enhancement programs for the general population can aid in early recognition, management, and prevention of mental disorders, thereby reducing treatment gap. The WHO Mental Health Gap Action Programme states that with proper care, psychosocial aid, and medication, millions of people could be treated for mental disorders (depression, schizophrenia, prevention from suicide, etc.) and begin to lead normal lives even where resources are scanty.
In India, majority of the preventive health checkup services focus mainly on physical health. Standard international guidelines recommend routine screening for common mental disorders in primary and preventive care.,, The importance of early detection has also been emphasized in the literature. Screening increases the possibility of identifying those who are in need of treatment and treating them appropriately. However, research is scarce with regard to mental health screening in the context of “preventive health care.” It would be enlightening to gain a deeper and wider understanding of psychiatric morbidity and QOL among participants utilizing the preventive health-care services of a tertiary hospital. In addition, it would also be pertinent to explore the feasibility of conducting mental health screening among this population. Hence, this study was undertaken.
This study aimed to document the prevalence of psychiatric disorders among participants attending the preventive health-care unit (PHCU) of a tertiary hospital. The concordance between mental health screening and diagnostic interview was also studied. An attempt was also made to study the correlation between presence of psychiatric diagnosis, other medical diagnosis, and QOL.
| Materials and Methods|| |
This observational cross-sectional study was conducted in the Department of Psychiatry and the PHCU in a tertiary care center in Puducherry, India. PHCU also called as master health checkup (in some institutions) is a separate unit in this hospital where participants come voluntarily for screening of physical illness as well as for routine annual physical checkup. Both healthy people as well as people with medical morbidities utilize the services of this unit. Thus, this unit serves the purpose of both primary and secondary prevention of diseases. The study has been cleared by the Institutional Human Ethics Committee. Using convenience sampling, all consecutive patients aged 18 years and above attending PHCU on a specified day of the week, providing consent, were included in the study.
A semi-structured pro forma was used to collect information pertaining to sociodemographic details. The “Standard for Clinicians' Interview in Psychiatry (SCIP)” tool was used to screen the participants for mental disorders and later for confirmation of diagnosis. SCIP helps in assessing the psychopathology and can be administered by psychiatrists/clinicians with experience and knowledge about mental health and diagnostic criteria for mental disorders. It has 29 screening questions and corresponding diagnostic modules for each disorder. The SCIP follows BFTT (Bottom First Then Top approach) which avoids biases toward preconceived diagnoses by starting with comprehensive symptom assessment.
The “Quality of Life Enjoyment and Satisfaction Questionnaire – Short Form” was used to assess the QOL among the participants. It helps assess the degree of enjoyment and satisfaction experienced during the past week. It is based on a Likert scale wherein the responses range from very poor to very good. Higher the score better is the QOL.
The “Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) Level 1 Cross-Cutting Symptom Measure (DSM-5 L1 CCSM) Question Number 15” and “Mini-Cog” were used to screen for cognitive impairment., The DSM-5 L1 CCSM is a self/informant-rated measure that assesses mental health domains that are important across psychiatric diagnoses. For this study, we utilized question number 15, which screens for cognitive impairment. A score of 2 or more is considered to be positive for cognitive impairment.
Mini-Cog is a brief instrument used for the detection of cognitive impairment in older adults. Two or less recalled words and abnormal clock drawing test are indicative of cognitive impairment. Permission for the use of these questionnaires was obtained from the authors before the study. Details with regard to other medical diagnoses were recorded after completion of the checkup.
Descriptive statistics was used to describe the sample in terms of frequency and percentage. Independent samples t-test was used to study the association between QOL and psychiatric disorders. The participants were divided into four groups based on the presence/absence of psychiatric/physical disorder or a combination of both. The groups were compared with respect to QOL using one-way ANOVA. Statistical significance was set at P < 0.05. All data analysis was performed using Microsoft Excel software and the Statistical Package for the Social Sciences (SPSS for Windows, version 17.0. SPSS Inc., Chicago, IL, USA).
| Results|| |
A total of 203 individuals participated in the study. The mean age of the participants was 44 years (43.38 ± 13.99 years). Of these, 125 (61.6%) were males and 78 (38.4%) were females. Majority of the participants belonged to lower middle class (135 [66.5%]) and hailed from urban areas (107 [52.7%]). Three-fourth of the participants were married (160 [78.8%]) [Table 1].
|Table 1: Sociodemographic profile of participants attending preventive health-care services (n=203)|
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Based on the screening module of SCIP, 57 (28.1%) screened positive for psychiatric disorders. Of these, 53 (92.9%) were confirmed to have psychiatric disorder, using diagnostic module of SCIP. Among them, 8 (3.9%) participants had more than one psychiatric disorder. Thus, the prevalence of psychiatric disorders was 26.1%. Although eight participants (3.9%) screened positive for cognitive impairment, clinical interview did not establish the diagnosis of dementia.
The psychiatric disorders most prevalent were alcohol use disorder (AUD, 20 [9.9%]), major depressive disorder (MDD, 13 [6.4%]), persistent depressive disorder (11 [5.4%]) and tobacco use disorder (11 [5.4%]). Most of the participants had a single psychiatric diagnosis [Table 2].
|Table 2: Distribution of psychiatric disorders in participants attending preventive health-care services (n=203)|
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The most prevalent physical disorders were diabetes (44 [1.7%]), hypertension (39 [19.2%]), and hyperlipidemia (22 [10.8%]). Majority of the participants had a single physical diagnosis.
The prevalence of psychiatric disorders among participants with and without physical disorders was 31% and 21%, respectively. The prevalence of depressive disorders among participants with and without physical disorders was 13.1% and 10.5%, respectively. The prevalence of MDD was 38.5% among diabetic participants and 30.8% among hypertensive patients.
The mean score of QOL among the participants was 65.00 ± 10.179. QOL was significantly poorer among the following psychiatric disorders: AUD, MDD, persistent depressive disorder, and generalized anxiety disorder [Table 3].
|Table 3: Association between quality of life and presence of psychiatric disorder using independent samples t-test|
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The participants were divided into four groups based on the presence/absence of physical/psychiatric disorder. Group 1 (psychiatric + physical disorder) had 31 (15.3%) participants, Group 2 (only psychiatric disorder) had 22 (10.8%) participants, Group 3 (only physical disorder) had 68 (33.5%) participants, and Group 4 had (no psychiatric/physical disorder) 82 (40.4%) participants. Group 1 and Group 2 both had significantly poorer QOL as compared to the other groups [Table 4].
|Table 4: Comparison of four groups with regard to quality of life using one-way ANOVA|
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| Discussion|| |
In this study, we attempt to study the psychiatric morbidity and QOL among participants attending the preventive health-care services of a tertiary hospital. Many studies have focused on screening for psychiatric disorders alone; however, we have screened both for psychiatric disorders as well as for cognitive impairment.,,, We have used SCIP – a structured diagnostic interview (SDI) which includes both screening module and diagnostic module in it. Not many studies have used this tool for assessing psychopathology. Most of the SDIs are based on DSM diagnostic system. Since the DSM-5 was published in 2013, all of these SDIs will require major revisions. However, SCIP which was published in 2014 provides diagnoses according to both DSM and ICD criteria. The complexity of few SDIs restricts its use only in research purposes. Others are lengthy and require extensive training for administering it. On the other hand, SCIP is a comprehensive tool and can be administered by psychiatrists/clinicians with knowledge about mental health and diagnostic criteria for mental disorders. The SCIP has also been validated in an international multisite study (in three countries) using a large sample (1004 participants). Out of 57 participants who screened positive for psychiatric disorders on using SCIP, 53 participants received a psychiatric diagnosis. This implies that the SCIP tool has high sensitivity. Hence, screening for psychiatric disorders using SCIP can be incorporated into preventive health checkup packages.
Standard guidelines generally recommend that screening should always be followed by appropriate action such as referral for necessary treatment. As the study was conducted in a tertiary hospital, the participants who were diagnosed to have a psychiatric disorder were also offered appropriate treatment. Frequency of various mental disorders reported in our study was among participants attending preventive health-care services. Since comparable studies are very few, we can only use prevalence reports among general population, patients with physical illness, or patients attending primary care as reference points.,
In our study, we have found that the prevalence of psychiatric disorders among the participants attending PHCU was 26.1%. This result is in line with a paper by Gururaj et al. which states that the prevalence of mental illness in India is around 20–30 per 1000 population. The National Mental Health Survey done in India from 2015 to 2016 revealed that the prevalence of psychiatric disorders is 10.6%. However, research is meagre with regard to mental health screening in “preventive health care.” There is scarcity of studies in this context in both Indian and international literature.
The prevalence of depressive disorder observed in our study was similar to the results of a study conducted in primary care settings among the adult population. Out of the 13 participants who received a diagnosis of depression in our study, most were found to be females. It is well known that depression is more common among female population as compared to the male population., This increased prevalence of depressive disorder among females is attributed to factors such as fluctuations in hormones, higher rates of illness, and a more severe mental burden with regard to female's cultural role and relationships.
Our study showed that the prevalence of depressive disorder was comparatively higher among participants with physical disorders (13.1%) than those who did not have any physical disorder (10.5%). Egede reported that the 12-month prevalence of depression in individuals with chronic medical conditions was 8.8%, which is in close proximity to our observation. In the World Health Survey 2007, the prevalence of depression among people with one or more physical disorders ranged from 9.3% to 23.0%, which is also similar to our results. We observed that the prevalence of MDD was higher among diabetic and hypertensive patients. The probable reasons for this high prevalence of depression among hypertensive and diabetic patients could be the possible mental impact of being aware of having such a lifelong condition, the economic burden of health-care costs in low socioeconomic groups, the resulting stresses, and further disability.,
The prevalence of AUD was estimated to be 9.9%. According to the National Mental Health Survey in India (2015–2016), the prevalence of AUD was 4.6%. However, a study by Premarajan et al. conducted in Puducherry, India, showed that the prevalence of AUD was 34.1 per 1000 general population. The prevalence of AUD in Puducherry, India, is found to be high probably because of the widespread consumption of alcohol in this region. Once again, this highlights the importance of screening for AUD among participants attending preventive health-care services.
Patients with AUD, generalized anxiety disorder, and depressive disorder had significantly poorer QOL. Similar to our study, Rapaport et al. also found that people with mood disorder or anxiety disorder had significant impairment in their QOL. It was also found that groups having only psychiatric disorder or having psychiatric disorder along with physical disorder had significantly poorer QOL as compared to the groups having only physical disorder or not having psychiatric/physical disorder. This observation highlights the adverse impact of mental illness on QOL. It is well known that productivity and general functioning have a profound relationship with QOL. Hence, screening for mental illness, early detection, and simultaneous treatment with physical disorder can improve the overall QOL of the individual.
However, certain limitations of the study need to be borne in mind. In this study, participants were selected based on convenience sampling which was done once a week. However, consecutive or randomized sampling would have yielded in a larger and more representative sample. In SCIP, the modules pertaining to memory disorders and personality disorders have not yet been validated.
| Conclusion|| |
Our study showed that one-fourth of the participants attending preventive health-care services of a tertiary care hospital were suffering from various mental disorders including major depression. The study also highlights that the presence of mental disorder was associated with poor QOL. It can be inferred from the study that it is practically feasible to incorporate mental health screening within the framework of a physical health checkup program in a tertiary care hospital. This is important considering the impact of mental illness on QOL and the well-documented adverse implications of mental–physical comorbidity. This is also in concordance with recommendations that mental health care needs to be integrated with physical health care to achieve holistic care and improve health outcomes.
I would like to thank Dr. Abu Backer for providing me help in translating the forms in Tamil and in the completion of the study. I would also like to thank Dr. Govindharaj, Medical Officer, Preventive Health Care Unit, MGMCRI, for his help in interviewing the participants and Dr. G. Ezhumalai, Senior Statistician and Research Consultant, MGMCRI, with regard to statistical analysis.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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Dr. Preethy Raghuraman
No. 30, Subramaniar Kovil Street, Old Saram, Puducherry - 605 013
Source of Support: None, Conflict of Interest: None
[Table 1], [Table 2], [Table 3], [Table 4]