Substance use disorders among mentally ill patients in a General Hospital in Sri Lanka: prevalence and correlates

Hapangama, A.; Kuruppuarachchi, K. A. L. A.; Pathmeswaran, A.

doi:10.4038/cmj.v58i3.6103

Cited by 21 publications

(19 citation statements)

References 28 publications

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“…Low socio-economic strata and increased transport costs additionally contribute to medication non-adherence due to difficulties in the accessibility and affordability of mental health care (Oflaz et al, 2015). Additionally, various illness-related factors (Chopra et al, 2006;Hapangama et al, 2013;Moon et al, 2012;Oflaz et al, 2015;Yen et al, 2005), and patient-related factors such as ignorance about side effects (Bener et al, 2013) and…”

Section: Influence Of Adherencementioning

confidence: 94%

“…Male gender (Ahmadi et al, 2001;Hapangama et al, 2013) and low socio-economic status (Sedain, 2013) were independently associated with increased rates of substance use. Alcohol is the most commonly used substance in patients with BD (Chopra et al, 2006;Hapangama et al, 2013;Munoli et al, 2014;Tamam and Ozpoyraz, 2002;Tsai et al, 1997). Table 3 emphasizes the high negative influence exerted by SUD over the course and outcome of BD.…”

Section: Influence Of Substance Use Disorder (Sud)mentioning

confidence: 95%

“…Poor adherence was associated with multiple re-hospitalizations and consequently an increased economic burden in the form of lost working days (Hapangama et al, 2013;Khess et al, 1997;Tang et al, 2010). Low socio-economic strata and increased transport costs additionally contribute to medication non-adherence due to difficulties in the accessibility and affordability of mental health care (Oflaz et al, 2015).…”

Section: Influence Of Adherencementioning

confidence: 97%

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Bipolar disorder in Asia: Illness course and contributing factors

Subramanian

Sarkar

Kattimani

2017

Asian Journal of Psychiatry

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Section: Influence Of Adherencementioning

confidence: 94%

Section: Influence Of Substance Use Disorder (Sud)mentioning

confidence: 95%

Section: Influence Of Adherencementioning

confidence: 97%

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Bipolar disorder in Asia: Illness course and contributing factors

Subramanian

Sarkar

Kattimani

2017

Asian Journal of Psychiatry

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“…In recent times Sri Lanka has reported HRQoL studies on liver disease [21], spinal cord injuries [22], parasitic diseases [23], oral health [24], vision [25] and cancer [26]. These studies have provided better grounds for clinicians to understand the quality of life issues associated with their patients.…”

Section: Introductionmentioning

confidence: 99%

EQ-5D-3L Derived Population Norms for Health Related Quality of Life in Sri Lanka

et al. 2014

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BackgroundHealth Related Quality of Life (HRQoL) is an important outcome measure in health economic evaluation that guides health resource allocations. Population norms for HRQoL are an essential ingredient in health economics and in the evaluation of population health. The aim of this study was to produce EQ-5D-3L-derived population norms for Sri Lanka.MethodA population sample (n = 780) was selected from four districts of Sri Lanka. A stratified cluster sampling approach with probability proportionate to size was employed. Twenty six clusters of 30 participants each were selected; each participant completed the EQ-5D-3L in a face-to-face interview. Utility weights for their EQ-5D-3L health states were assigned using the Sri Lankan EQ-5D-3L algorithm. The population norms are reported by age and socio-economic variables.ResultsThe EQ-5D-3L was completed by 736 people, representing a 94% response rate. Sixty per cent of the sample reported being in full health. The percentage of people responding to any problems in the five EQ-5D-3L dimensions increased with age. The mean EQ-5D-3L weight was 0.85 (SD 0.008; 95%CI 0.84-0.87). The mean EQ-5D-3L weight was significantly associated with age, housing type, disease experience and religiosity. People above 70 years of age were 7.5 times more likely to report mobility problems and 3.7 times more likely to report pain/discomfort than those aged 18-29 years. Those with a tertiary education were five times less likely to report any HRQoL problems than those without a tertiary education. A person living in a shanty was 4.3 more likely to have problems in usual activities than a person living in a single house.ConclusionThe population norms in Sri Lanka vary with socio-demographic characteristics. The socioeconomically disadvantaged have a lower HRQoL. The trends of population norms observed in this lower middle income country were generally similar to those previously reported in high income countries.

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“…Some differences between SMI and SMI-SUD patients were not shared between the two 2-year periods. For instance, in the 2-year period 2013-2014, SMI-SUD patients were more likely than SMI ones to have a junior high school degree rather than a high school one or a university degree and to have no kids [92]. On the contrary, family problems and parents' divorce were reported as significantly more common by SMI-SUD patients in the years 2003-2004 than in SMI patients.…”

Section: Sociodemographic and Family Featuresmentioning

confidence: 94%

Dual Diagnosis Patients First Admitted to a Psychiatric Ward for Acute Psychiatric Patients: 2-Year Period 2003–2004 versus 2013–2014

Gramaglia¹,

Lombardi²,

Rossi³

et al. 2016

Recent Advances in Drug Addiction Research and Clinical Applications

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Dual diagnosis (DD) is the coexistence of severe mental illness (SMI) and substance use disorder (SUD). The increase of DD observed in recent years has important implications for mental health services organization. The aim of this study is to assess the prevalence and features of DD over a decade, comparing the periods 2003-2004 and 2013-2014. We performed a retrospective study retrieving sociodemographic and clinical data from the medical records of patients at their first admission to the Psychiatric Ward of University Hospital "Maggiore della Carità" in Novara, Italy. Patients with SMI and comorbid SUD (SMI-SUD) and patients with SMI without comorbidity (SMI) were compared in the two periods, 2003-2004 versus 2013-2014. SMI-SUD patients in both 2-year periods were more likely to be male, younger, unemployed, living with parents (or alone, for the 2013-2014 period) rather than with a family of their own, and single (or divorced, in 2003-2004). The 2003-2004 patients were more frequently diagnosed with a personality disorder, whereas the 2013-2014 patients had mixed diagnoses. We have found differences in the possible predictors of substance abuse in the two periods as well: in both periods, male gender was associated with an increased risk of DD, whereas age >61 years was associated with decreased risk. Only in the first period (2003)(2004) was having a university degree associated with a decreased risk of DD, whereas the diagnosis of a personality disorder was associated with an increased risk of DD; on the contrary, in the second period (2013)(2014), living in a protective environment was associated with a decreased risk of DD. The identification of changes in the prevalence of first admission DD patients and their clinical and sociodemographic features may help to highlight an evolving pattern of substance use and to identify possible risk factors that may be the target of prevention and treatment approaches.

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Substance use disorders among mentally ill patients in a General Hospital in Sri Lanka: prevalence and correlates

Abstract: A significant proportion of patients were found to have a comorbid substance use diagnosis and associated complications. These findings have important implications for service provision for mentally ill patients with a comorbid substance use disorder.

Cited by 21 publications

References 28 publications

Bipolar disorder in Asia: Illness course and contributing factors

Bipolar disorder in Asia: Illness course and contributing factors

EQ-5D-3L Derived Population Norms for Health Related Quality of Life in Sri Lanka

Dual Diagnosis Patients First Admitted to a Psychiatric Ward for Acute Psychiatric Patients: 2-Year Period 2003–2004 versus 2013–2014

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