Background:
Older adults with serious mental illness (OASMI) have to manage the twin challenges of old age and mental illness. Understanding their characteristics will help policymakers and ...researchers plan tailored interventions. The profile of OASMI is not described in any publication from India, and this paper addresses that gap. The information from this study will serve as a baseline for the planned periodic follow-up of the study participants.
Methods:
This study employed a cross- sectional design among a sample of OASMI identified through multistage cluster sampling from three districts in Kerala. We interviewed them in their households and collected sociodemographic data using a pretested tool.
Results:
Among the 917 OASMI participants, 66% were females, 18% were the ‘oldest-old’ (≥80 years), 94.1% were unemployed, 51.7% were socially backward, 68.5% were financially weak, 10.1% were living alone, 59.4% were living without partners, and 63.7% had caregivers.
Conclusion:
Compared to the general population of older adults in Kerala, the OASMI have poorer socioeconomic status and higher rates of social isolation, and males are dying earlier. The profile of the OASMI depicts their multiple vulnerabilities and the need to address those.
The National Mental Health Survey was borne out of the felt need for a comprehensive epidemiological survey on mental health to understand the magnitude of psychiatric morbidities in India to aid in ...mental health policymaking, service planning, and delivery. Kerala was one of the 12 surveyed states, representing southern India.
To estimate the prevalence and pattern of various mental illnesses and substance use disorders in a representative sample from Kerala state.
A household survey using a multi-stage, stratified, random cluster sampling technique, with selection based on probability proportionate to size at each stage.
The community-based survey was carried out by trained field staff on individuals from systematically selected households from three randomly selected districts of Kerala. The instruments used in the survey included M.I.N.I adult version 6.0, a modified version of the Fagerström Nicotine Dependence Scale and questionnaires to screen for epilepsy, intellectual disability, and autism spectrum disorders.
A total of 2479 respondents aged >18 years were interviewed. The lifetime and current prevalence of mental morbidity (excluding tobacco use disorders) was 14.14% and 11.36%, respectively. Neurotic/stress-related disorders and depressive disorders were 5.43% and 2.49%, respectively, while severe mental disorders were prevalent in 0.44% of the sample. The prevalence of high risk for suicide was 2.23%.
The survey revealed high rates of common mental illnesses and suicide risk in the state when compared to national estimates.
Background:
India has the second-largest population of elderly in the world. Serious mental illness (SMI) is a subset of the mental disorders that result in significant functional impairment and is ...usually long term. Persons with SMI face several challenges in their old age that are different from the issues faced by younger people with SMI. Understanding the problems faced by elderly individuals suffering from SMI is fundamental for planning programs to address them. The SENIOR (Support Systems Evaluation of Neuropsychiatric Illness in Old age) project is a study aimed at evaluating the problems faced in obtaining mental health care by elderly persons having SMI in the Kerala state of India.
Aim:
To describe the scientific methodology of the SENIOR project.
Methods:
This study employs mixed-methods cross-sectional design among a minimum sample of 768 SMI patients identified through cluster sampling from three districts, and Focus Group Discussion among mental health program officials.
Discussion:
This paper presents a methodological model to assist researchers in future field epidemiological studies on mental illness. Assessing service needs and barriers to access for the most vulnerable among the mentally ill will help the policymakers make evidence-based decisions to improve their quality of life.
Background:
Recognizing the need for good quality, scientific and reliable information for strengthening mental health policies and programmes, the National Mental Health Survey (NMHS) of India was ...implemented by National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, in the year 2015–2016.
Aim:
To estimate the prevalence, socio-demographic correlates and treatment gap of mental morbidity in a representative population of India.
Methods:
NMHS was conducted across 12 Indian states where trained field investigators completed 34,802 interviews using tablet-assisted personal interviews. Eligible study subjects (18+ years) in households were selected by a multi-stage, stratified, random cluster sampling technique. Mental morbidity was assessed using MINI 6. Three-tier data monitoring system was adopted for quality assurance. Weighted and specific prevalence estimates were derived (current and lifetime) for different mental disorders. Mental morbidity was defined as those disorders as per the International Statistical Classification of Diseases, Tenth Revision Diagnostic Criteria for Research (ICD-10 DCR). Multivariate logistic regression was conducted to examine risk for mental morbidity by different socio-demographic factors. Survey was approved by central and state-level institutional ethical committees.
Results:
The weighted lifetime prevalence of ‘any mental morbidity’ was estimated at 13.67% (95% confidence interval (CI) = 13.61, 13.73) and current prevalence was 10.56% (95% CI = 10.51, 10.61). Mental and behavioural problems due to psychoactive substance use (F10–F19; 22.44%), mood disorders (F30–F39; 5.61%) and neurotic and stress-related disorders (F40–F48; 3.70%) were the most commonly prevalent mental morbidity in India. The overall prevalence was estimated to be higher among males, middle-aged individuals, in urban-metros, among less educated and in households with lower income. Treatment gap for overall mental morbidity was 84.5%.
Conclusion:
NMHS is the largest reported survey of mental morbidity in India. Survey estimated that nearly 150 million individuals suffer from one or the other mental morbidity in India. This information is to be used for planning, delivery and evaluating mental health programming in the country.
Understanding the burden and pattern of mental disorders as well as mapping the existing resources for delivery of mental health services in India, has been a felt need over decades. Recognizing this ...necessity, the Ministry of Health and Family Welfare, Government of India, commissioned the National Mental Health Survey (NMHS) in the year 2014-15. The NMHS aimed to estimate the prevalence and burden of mental health disorders in India and identify current treatment gaps, existing patterns of health-care seeking, service utilization patterns, along with an understanding of the impact and disability due to these disorders. This paper describes the design, steps and the methodology adopted for phase 1 of the NMHS conducted in India. The NMHS phase 1 covered a representative population of 39,532 from 12 states across 6 regions of India, namely, the states of Punjab and Uttar Pradesh (North); Tamil Nadu and Kerala (South); Jharkhand and West Bengal (East); Rajasthan and Gujarat (West); Madhya Pradesh and Chhattisgarh (Central) and Assam and Manipur (North East). The NMHS of India (2015-16) is a unique representative survey which adopted a uniform and standardized methodology which sought to overcome limitations of previous surveys. It employed a multi-stage, stratified, random cluster sampling technique, with random selection of clusters based on Probability Proportionate to Size. It was expected that the findings from the NMHS 2015-16 would reveal the burden of mental disorders, the magnitude of the treatment gap, existing challenges and prevailing barriers in the mental-health delivery systems in the country at a single point in time. It is hoped that the results of NMHS will provide the evidence to strengthen and implement mental health policies and programs in the near future and provide the rationale to enhance investment in mental health care in India. It is also hoped that the NMHS will provide a framework for conducting similar population based surveys on mental health and other public health problems in low and middle-income countries.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Background: Adherence to therapy is central to the success of anti-retroviral treatment (ART) and one of the most important factors influencing long term prognosis of HIV infection. In order to ...achieve this, patients are required to maintain more than 95% adherence to achieve lasting suppression of viral replication. The objective of the study was to assess the adherence to highly active antiretroviral therapy among people living with HIV (PLHIV) and the factors associated with adherence.Methods: This was a cross-sectional study conducted among PLHIV patients attending ART clinic, government medical college, Kozhikode from June 2015 to 2016. Adherence was estimated using modified Morisky 8 items questionnaire. Pretested semi-structured questionnaire was used to study various associated factors by interview method.Results: Of the 265 patients, the majority 246 (92.8%) were found to be treatment adherent and 19 (7.2%) were non-adherent. Most of the study population were in the age group 31-45 years and majority of the PLHIV were taking first line fixed dose regimens. Factors such as the early stage of the disease, using a method to remember, disclosure status, involvement in social activities, regular visit to ART clinic, financial and emotional support, involvement in social activities and HIV in the family were found be positively associated with adherence.Conclusions: Our study had found that a cordial environment in the ART centre will improve adherence and factors such as strong patient-provider relationship, including trust and engagement with the provider, which helps in improving ART adherence.
Kozhikode district of North Kerala, India witnessed an outbreak of Nipah virus (NiV) in the month of May 2018. Two adjacent districts were affected leaving 17 patients dead out of the 19 confirmed. ...United Nations and WHO lauded the expeditious response of the state’s health system in the diagnosis and containment of the outbreak which was unprecedented. The authors being in the contact tracing and surveillance operation district team, had kept a record of timeline of events and actions at the state level, compiled the news clippings and tracked events. In the absence of an end‑of‑epidemic report for reference, these records served as a valuable tool for the present review. We used the Management science for health frame work tool (MSH framework) to evaluate the district and state coordinated actions which helped in curbing the outbreak. Though NiV outbreak in South India (2018) had similar epidemiological features to previous disease outbreaks, it stands out as the one to be detected and contained in a short span of time. As health personnel working in the government medical college of an affected district and directly involved in contact tracing operations and containment measures, exploring and sharing, what worked and how, in the context of multidisciplinary response and recovery attempts of the outbreak in the state may be beneficial to public health personnel and policy makers. This management framework may be replicated in the national and international context, particularly in South East Asian region under threat of emerging viral infections like COVID-19, lacking specific epidemic management frameworks for outbreak response and containment.
Background Diphtheria cases continue to occur in India despite a national vaccination program targeting the disease. Outbreaks of diphtheria have been known to occur in areas of low immunization ...coverage. An age shift has been noted to older children and adults in recent outbreaks from the Indian states of Andhra Pradesh, Karnataka, Delhi and Assam. Kerala witnessed its largest outbreak of Diphtheria in recent times from 2015 to 2017.Methods: Surveillance data from the Regional PEID Cell during the outbreak period was analysed and epidemiological data generated.Results: A total of 734 cases of diphtheria were reported during this period with eight deaths (Case fatality rate=1.08%). The mean age of the cases was 17.4 years (±13.9). More than 72% of the cases occurred in children above 10 year of age and 68% of the cases were either unimmunized or partially immunized. 32% of the cases were immunized for age. Of these, immunized children, 88% were above 10 years of age, indicating waning immunity with age. The existence of a sizeable unimmunized cohort in the adolescent age group and waning immunity among immunized were two major factors contributing to the outbreak.Conclusions: An age shift has been observed in the occurrence of Diphtheria cases during the outbreak in Kerala. Booster doses with Td vaccine during adolescence in addition to maintaining a high immunization coverage in the routine immunization program, with special emphasis on pockets of low coverage is essential for preventing the reemergence of diphtheria.
Background: With increase in prevalence of stroke and life expectancy the quality of life of stroke survivors assumes importance. Despite advances in diagnosis and treatment of cerebrovascular ...accidents the survivors continue to experience low Quality of life (QoL) especially in developing countries. The objective of this study was to assess the quality of life among stroke survivors and the prevalence of depression among them. Methods: Cross-sectional population based study was conducted in a rural area of North Kerala. Stoke survivors were interviewed at home to assess the quality of life and depression status. QOL was assessed using the Medical Outcomes 36-Item Short-Form Health Survey (SF-36), functional status using the modified barthel index (MBI), and mood using the Beck’s Depression Inventory (BDI).Results: A total of 40 patients (65.5% men, mean age 70.58±10.7 years) were interviewed. The mean MBI was 55.25±2.79, and the prevalence of unrecognized depression was 90%. 95 percent of patients needed varying degrees of care for their activities of daily living. The SF-36 scores of the patients were considerably lower than that to that of the general population especially in the areas of role limitation and physical functioning. Depression was more among older subjects and Depressed patients had lower MBI scoresConclusions: A significant proportion of stroke survivors continue to face limitations in their physical activities. In addition, majority have unrecognised depression that affects their QOL adversely.
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