Explanatory models and distress in primary caregivers of patients with acute psychotic presentations: A study from South India

Abstract

Background:

Emotional distress among caregivers of people with mental illness is common, changes overtime and requires appropriate coping strategies to prevent long-term disability. Explanatory models, which underpin understanding of disease and illness, are crucial to coping.

Aim:

To study the association of explanatory models and distress among caregivers of people with acute psychotic illness.

Method:

A total of 60 consecutive patients and their primary caregivers who presented to the Department of Psychiatry, Christian Medical College, Vellore, were recruited for the study. Positive and Negative Syndrome Scale (PANSS), Short Explanatory Model Interview (SEMI) and the General Health Questionnaire-12 (GHQ-12) were used to assess severity of psychosis, explanatory models of illness and emotional distress. Standard bivariate and multivariable statistics were employed.

Results:

Majority of the caregivers simultaneously held multiple models of illness, which included medical and non-medical perspectives. The GHQ-12 score were significantly lower in people who held multiple explanatory models of illness when compared to the caregivers who believed single explanations.

Conclusion:

Explanatory models affect coping in caregivers of patients with acute psychotic presentations. There is a need to have a broad-based approach to recovery and care.

Keywords

Mental disorders caregiver explanatory models emotional distress

Introduction

Clinical features, severity, variable response to treatment, adverse effects of medication and different courses and outcomes of psychotic illnesses have a significant impact on patients and their caregivers (Flyckt, Fatouros-Bergman, & Koernig, 2015). While many studies have examined diverse interventions to reduce caregiver burden (Yesufu-Udechuku et al., 2015), there is a death of studies on family and carer perspectives on beliefs about illness and coping strategies.

‘Explanatory Models (EMs) are the notions about an episode of sickness and its treatment that are employed by all those engaged in the clinical process’ (Kleinman, 1981). EMs are usually a conglomeration of emic and etic approaches involving ethnocultural, personal and idiosyncratic beliefs and components from both within and outside culture. People with chronic and debilitating conditions seek help from diverse sources; they visit centers, offering modern, traditional and alternative medicine and faith healers, simultaneously and sequentially, in search of cure and healing. Many reports, which have systematically elicited EMs, have documented the presence of multiple and contradictory beliefs about illness across cultures. Serial assessments of explanatory models and psychopathology document different progressions and support the contention that EMs are not fixed and immutable but tend to be idiosyncratic, changeable and heavily influenced by personality, cultural factors, response to interventions and clinical outcomes (Jacob, 2014, 2017; Johnson, Manoranjitham, Charles, Jeyaseelan, & Jacob, 2012).

However, the biomedical model compares patient, family and community perspectives against the biomedical standards of awareness, attribution and action related to mental illness (Saravanan, David, Bhugra, Prince, & Jacob, 2005). Non-medical explanations and diverse contexts, common across cultures and countries, ignored at best and dismissed at worst, are considered unscientific (Jacob, 2017). Mental health professionals often tend to claim exclusivity and superiority of biomedical beliefs, while rejecting non-medical perspectives, commonly employed coping strategies and impede healing.

Psychiatry, with its attempts at a universal understanding of mental disorders, dismisses the context of the illness and the personal narratives of patients and their families. The focus on objective behavioral and symptom criteria has reduced the importance of patient experience. Nevertheless, illness narratives contextualize the patient and their families, describe their reality and ways of coping and refocus the doctor–patient interaction. Consequently, explanatory models of illness, patient and family narratives which attempt to make sense of illness experiences, control them and improve quality of life should not be considered irrelevant to cure and healing.

The ability to construct accounts of personal and social reality will necessarily play a role in developing EMs of illness. The presence of residual symptoms, persistent deficits and incapacitating adverse effects of medication, despite good treatment compliance, demands the need to reconcile the simplistic biomedical model of disease and treatment with the patient’s reality. Patients and their families employ multiple EMs to cope with the unexplained reality of disabling mental illnesses.

Nevertheless, literature on the role of explanatory models of illness and their impact on caregiver burden is sparse. This study attempted to examine explanatory models in primary caregivers of patients with acute psychoses and their correlations with common mental disorders.

Method

Setting

The study was conducted in Department of Psychiatry, Christian Medical College, Vellore, India, a 122-bed tertiary care facility. It employs a multidisciplinary approach to treatment and manages a variety of mental and behavioral disorders in adults and children. It caters to about 500 outpatients a day and has a 24-hour emergency service with 12 beds. The hospital is a family-oriented facility with carers and patients living in cottages during the period of hospitalization.

Sample

Consecutive patients presenting with acute psychotic presentations to the hospital were recruited for the study. Patients with first episode and those with episodic psychosis were included. The inclusion criteria were as follows: caregivers between 18 and 70 years of age and those who spoke English or the local language Tamil. Carers who were first-degree relatives and who were staying in the hospital were recruited. The purpose of the study was explained and written informed consent obtained.

Assessment

The instruments used for assessment are as follows:

Short Explanatory Model of Interview (SEMI). The SEMI is a standard tool to elicit explanatory models of illness (Lloyd et al., 1998). It is based on Kleinman’s original concepts, which examine health and sickness from anthropological perspective. It explores the nature of illness, perceived causes and consequences, help seeking and impact of sickness (Kleinman, 1981). It employs open-ended questions and is semi-structured. The language is simple and does not include any medical or technical words or phrases. The subjects are encouraged to talk openly about their attitudes and experiences with the aim of eliciting concepts held and relationship to current situation and culture. Probes are also employed to confirm the concepts and explore areas. Tamil version of the instrument, previously employed in many studies (Saravanan et al., 2007; Shankar, Saravanan, & Jacob, 2006) was used.

General Health Questionnaire-12 (GHQ-12). The GHQ-12 is a reliable instrument to assess the psychological distress, depression, anxiety and common mental disorders (Goldberg & Williams, 1988). It has been employed in diverse contexts, and the Tamil version has been used in India (John, Vijayakumar, Jayaseelan, & Jacob, 2006; Kuruvilla et al., 1999; Pothen, Kuruvilla, Philip, Joseph, & Jacob, 2003) and has reasonable indices of efficacy. A threshold of 3/4 has been recommended to identify cases with significant depression, anxiety and common mental disorders in the local population (John et al., 2006).

Positive and Negative Syndrome Scale (PANSS). PANSS is a standard scale to assess psychopathology (Kay, Fiszbein, & Opler, 1987). It consists of subscales to evaluate positive and negative symptoms and general psychopathology in psychosis. It has been widely used and has been employed in India (Johnson et al., 2012).

Socio-demographic and clinical details were also recorded. Tamil versions of the instruments were employed.

Analysis

Descriptive statistics were used to describe continuous variables, while frequency distributions were obtained for categorical data. Student t test and chi-square test were used to assess the statistical significance of associations. Logistic regression was used to adjust for age.

Results

A total of 60 patients with acute psychotic presentations were seen in the hospital during the period of the study. The socio-demographic and clinical characteristics are documented in Table 1. The majority of primary givers were women, married, with at least primary education and were housewives from rural backgrounds and lived with the patient. The majority of patients were male, single, with at least primary education and unemployed. They presented with psychosis of less than a week’s duration and of moderate severity.

Table 1.

Socio-demographic and clinical characteristics of patients and their caregivers.

Characteristic	Patients		Caregivers
	Mean (SD)	Freq. (%)	Mean (SD)	Freq. (%)
Age (years)	32.12 (10.59)		44.55 (13.98)
Gender – male		35 (58.3)		26 (43.3)
Marital status – married		28 (46.7)		42 (70.0)
Literacy – illiterate		5 (8.3)		8 (13.3)
Income – nil		37 (61.7)		28 (46.7)
Residence – rural		48 (80.0)		48 (80.0)
Relationship to patient
• Spouse				14 (23.3)
• Parent				30 (50.0)
• Sibling				10 (16.7)
• Child				6 (10.0)
Type of family – nuclear		45 (75.0)		45 (75.0)
Employment – unemployed		37 (61.7)		27 (45.0)
Total duration of illness (months)		5.72 (3.47)
History of violence – present		21 (35.0)
History of previous hospitalization – present		18 (30.0)
Total PANSS score	81.05 (6.81)
GHQ-12 case				36 (60.0)
Total GHQ-12 score			4.13 (1.70)
Belief in karma as causal				2 ( 3.3)
Belief in evil spirit as causal				21 (35.0)
Belief in black magic as causal				19 (31.7)
Belief in punishment by God as causal				2 (3.3)
Belief in disease as causal				51 (85.0)
Temple rituals as treatment				22 (36.1)
Treatment by shaman (Mantravadi)				14 (23.3)
Treatment by traditional healer				9 (15.0)
Treatment by doctor				49 (81.7)
Number of causal models held simultaneously
1				39 (65.0)
2				11 (18.3)
3				10 (16.7)
Number of treatment options simultaneously held
0				11 (18.3)
1				27 (45.0)
2				8 (13.5)
3				5 (8.3)
4				9 (15.0)
Number of people with two or more casual models				21 (35.0)
Number of people with two or more treatment models				22 (36.7)

SD: standard deviation; PANSS: Positive and Negative Syndrome Scale; GHQ-12: General Health Questionnaire-12.

The factors associated with GHQ caseness were older age and female gender. Carer beliefs in evil spirits, black magic, with fewer total number of causal explanatory models and fewer total number of treatment explanatory models were associated with the absence of mental morbidity (Table 2).

Table 2.

Factors associated with higher GHQ 12 scores among care givers of people with acute psychosis.

Characteristic	Care givers with GHQ score ≥ 4n= 36n (%)mean (sd)	Care givers with GHQ score ≤ 3n=24n (%)mean (sd)	Bivariate StatisticsX²-value;df;p-valuet-value; df; p-value
Caregiver -female	36 (72.2)	8 (33.3)	8.87; 1; 0.003
Caregiver- age	47.41 (13.34)	36.69 (13.01)	2.77; 58; 0.007
Caregiver’s belief in evil spirits as causal	9 (25.0)	12 (50.0)	3.96; 1; 0.047
Caregiver’s belief in black magic as causal	7 (19.4)	12 (50.0)	6.21; 1; 0.013
Visit to shaman	5 (13.9)	9 (37.5)	4.49; 1; 0.034
No. of causal models	1.33 (0.63)	1.79 (0.88)	−2.19; 38.45; 0.034
No. of treatment models	1.28 (1.21)	2.0 (1.35)	−2.16; 58; 0.035

Non-significant associations between GHQ status and the following variables: Rural residence, nuclear family, patient’s age, gender, education, marital status, employment, monthly income, previous hospitalization, history of violence and duration and severity of illness; Care giver’s marital status, education, employment, relationship to patient, belief in disease model, punishment by God, visits to traditional healer, doctor.

The relationship between GHQ caseness and the following variables remained statistically significant after age-adjusted analysis using multivariable logistic regression: female gender (odds ratio (OR): 4.20; 95% confidence interval (CI): 1.32, 13.89; p = .015) and the total number of causal explanatory models (OR: 0.47; 95% CI: 0.23, 0.98; p = .043). Beliefs in evil spirit, black magic and the number of treatment models lost their statistical significance when adjusted for age.

Discussion

This study examined the relationship between explanatory models and distress among primary caregivers of people with acute psychotic presentations. The advantages of the study include systematic and standard elicitation of explanatory models, often underemphasized in routine clinical care. Its limitations include cross-sectional assessment and its relatively small sample size.

The study documented significant emotional distress in the majority of caregivers. It also recorded the fact that many people simultaneously held multiple explanatory models of illness. The fact women who are caregivers frequently bear a disproportionate amount of stress has been documented across studies (Sharma, Chakrabarti, & Grover, 2016). While studies on EMs among carers have documented the simultaneous use of multiple and often contradictory EMs (Das et al., 2006), the correlation with reduced stress score among those who multiple explanatory models of illness has not been previously demonstrated.

Patients, their families and the community often employ multiple EMs to cope with the unexplained reality of disabling mental illnesses (Charles, Manoranjitham, & Jacob, 2007; Das et al., 2006; Joel et al., 2006; Saravanan et al., 2007, 2010; Shankar et al., 2006). EMs about mental illness are based on socio-cultural belief systems prevalent in the local culture and region and are combinations of etic and emic models of illness. Most societies are pluralistic and offer a wide range of beliefs including biomedical explanations (e.g. disease, degeneration and deficiency), on one hand, to supernatural ideas, on the other hand (e.g. consequence of sin, punishment by God, black magic, evil spirits and karma). These belief systems interact with the trajectory of the person’s illness to produce a unique set of EMs of illness for the particular individual and his or her family (Johnson et al., 2012). The choice of EMs is dependent on a complex interaction between the person’s persistent symptoms, current deficits, adverse medication effects, social relations, livelihood issues and response to treatment, on one hand, and available biomedical and cultural explanations, on the other hand. While medical EMs are popular for acute illness and curable disease, non-medical EMs are often employed by people with chronic illnesses (Jacob, 2016). Multiple EMs have also been documented among people who are partial responders to treatment and who are compliant with their psychotropic medication (Johnson et al., 2012).

People tend to choose EMs/perspectives, which are non-stigmatizing explanations and which seem to rationalize their individual concerns and contexts and are suited to their personality (Johnson et al., 2012). These perspectives seem to provide support and even offer worldviews. However, the frequent presence of multiple and contradictory EMs, often held simultaneously, suggests their pragmatic role in coping with the effects of mental illness. Pluralistic societies employ multiple approaches to health and illness and they embrace multiple EMs, all possibly valid. People with mental illness commonly combine modern medicine with complementary and alternative therapies for relief of symptoms and distress (Jacob, 1999). Patients and their families seem to be comfortable with compartmentalizing their contradictory EMs and seek diverse forms of cure and healing.

EMs and illness perspectives help construct personal and social reality and play a crucial role in cure and healing. They allow people with chronic and debilitating conditions to seek help from diverse sources. Patients and their relatives visit facilities that offer remedies employing modern, traditional and alternative medicine and faith-based therapies, simultaneously and sequentially, in search of cure and healing (Jacob, 2014, 2017; Johnson et al., 2012).

Psychiatry and mental health professionals should employ a broad-based approach to mental illness. They should elicit patient, family and community perspectives and examine illness awareness, their attribution and action (Saravanan et al., 2005). They should have a non-judgmental approach to non-medical explanations of suffering and should not claim exclusivity and superiority of biomedical beliefs nor reject non-medical perspectives as these are commonly employed coping strategies in diverse cultures and countries. Such strategies that attempt to make sense of illness experiences, control them and improve quality of life should not be considered irrelevant to cure and healing (Jacob, 2017).

Eliciting stress and the explanatory models of illness among carers of people with mental illness is crucial to sensitive clinical care. While antipsychotic medication has a significant impact on acute psychotic illness, the uncertainties of clinical outcomes (Thangadurai, Gopalakrishnan, Kurian, & Jacob, 2006) mean that other strategies are also crucial for coping among patients and families. It requires wisdom to realize that cultures and communities have overtime understood the complexity of mental health and illness. While the biomedical model should be presented, local explanatory models and personal methods of coping should not be dismissed (Das et al., 2006). Coping with mental illness for people and their families is a major challenge, and people should be encouraged to employ diverse strategies to relieve distress. Psychiatry needs to review the sole use of the biomedical model in the management of mental illness and revisit and re-examine the role of diverse approaches to mental health, illness and healing.

Footnotes

Funding

The author(s) received no financial support for the research, authorship and/or publication of this article.

References

Charles

Manoranjitham

S. D.

Jacob

K. S.

(2007). Stigma and explanatory models among people with schizophrenia and their relatives in Vellore, south India. International Journal of Social Psychiatry, 53, 325–332.

Das

Saravanan

Karunakaran

K. P.

Manoranjitham

Ezhilarasu

Jacob

K. S.

(2006). Effect of a structured educational intervention on explanatory models of relatives of patients with schizophrenia Randomised controlled trial. The British Journal of Psychiatry, 188, 286–287.

Flyckt

Fatouros-Bergman

Koernig

(2015). Determinants of subjective and objective burden of informal caregiving of patients with psychotic disorders. International Journal of Social Psychiatry, 61, 684–692.

Goldberg

Williams

(1988). A user’s guide to the General Health Questionnaire. Windsor, UK: National Foundation for Educational Research-Nelson.

Jacob

K. S.

(1999). Mental disorders across cultures: The common issues. International Review of Psychiatry, 11, 111–115.

Jacob

K. S.

(2014). Insight in psychosis: An independent predictor of outcome or an explanatory model of illness? Asian Journal of Psychiatry, 11, 65–71.

Jacob

K. S.

(2016). Insight in psychosis: An indicatory of severity of psychosis, an explanatory model of illness and a coping strategy. Indian Journal of Psychological Medicine, 38, 194–201.

Jacob

K. S.

(2017). Insight in psychosis: Standards, science, ethics and value judgment. International Journal of Social Psychiatry, 63, 345–351.

Joel

Sathyaseelan

Jayakaran

Vijayakumar

Muthuratnam

Jacob

K. S.

(2006). A biomedical educational intervention to change explanatory models of psychosis among community health workers in South India. Indian Journal of Psychiatry, 48, 138–142.

10.

John

Vijayakumar

Jayaseelan

Jacob

K. S.

(2006). The validation and usefulness of the Tamil version of the 12 item General Health Questionnaire in the community. British Journal of Community Nursing, 11, 382–386.

11.

Johnson

Manoranjitham

S. D.

Charles

Jeyaseelan

Jacob

K. S.

(2012). Insight, psychopathology, explanatory models and outcome of schizophrenia in India: A prospective 5-year cohort study. Biomedcentral Psychiatry, 12, 159.

12.

Kay

S. R.

Fiszbein

Opler

L. A.

(1987). The positive and negative syndrome scale (PANSS) for schizophrenia. Schizophrenia Bulletin, 13, 261–276.

13.

Kleinman

(1981). Patients and healers in the context of culture: An exploration of the borderland between anthropology, medicine, and psychiatry. Berkley, CA: University of California Press.

14.

Kuruvilla

Pothen

Philip

Braganza

Joseph

Jacob

K. S.

(1999). The validation of the Tamil version of the 12 item General Health Questionnaire. Indian Journal of Psychiatry, 41, 217–221.

15.

Lloyd

K. R.

Jacob

K. S.

Patel

St. Louis

Bhugra

Mann

A. H.

(1998). The development and use of the Short Explanatory Model Interview (SEMI) and its use among primary care attenders with common mental disorders: A preliminary report. Psychological Medicine, 28, 1231–1237.

16.

Pothen

Kuruvilla

Philip

Joseph

Jacob

K. S.

(2003). Common mental disorders among primary care attenders in Vellore, South India: Nature, prevalence and risk factors. International Journal of Social Psychiatry, 49, 119–125.

17.

Saravanan

David

Bhugra

Prince

Jacob

K. S.

(2005). Insight in people with psychosis: The influence of culture. International Review of Psychiatry, 17, 83–87.

18.

Saravanan

Jacob

K. S.

Johnson

Prince

Bhugra

David

A. S.

(2007). Belief models in first episode schizophrenia in South India. Social Psychiatry and Psychiatric Epidemiology, 42, 446–451.

19.

Saravanan

Jacob

K. S.

Johnson

Prince

Bhugra

… David

A. S.

(2010). Outcome of first-episode schizophrenia in India: Longitudinal study of effect of insight and psychopathology. The British Journal of Psychiatry, 196, 454–459.

20.

Shankar

B. R.

Saravanan

Jacob

K. S.

(2006). Explanatory models of common mental disorders among traditional healers and their patients in rural south India. International Journal of Social Psychiatry, 52, 221–233.

21.

Sharma

Chakrabarti

Grover

(2016). Gender differences in caregiving among family – caregivers of people with mental illnesses. World Journal of Psychiatry, 6, 7–17.

22.

Thangadurai

Gopalakrishnan

Kurian

Jacob

K. S.

(2006). Diagnostic stability and status of acute and transient psychotic disorders. The British Journal of Psychiatry, 188, 293–293.

23.

Yesufu-Udechuku

Harrison

Mayo-Wilson

Young

Woodhams

Shiers

… Kendall

(2015). Interventions to improve the experience of caring for people with severe mental illness: Systematic review and meta-analysis. The British Journal of Psychiatry, 206, 268–274.