Positive mental health of young people: a policy framework

Abstract

The key concern of this study is to develop a tool to measure positive mental health among young people, explore its correlates and develop a model that can be used by the policy-makers to formulate supportive and evidence-based policy for mental health promotion.

Keywords::

• positive mental health
• young people
• Kerala
• India

The shift in emphasis of health from a curative model to an upstream approach that promotes health as well as the wide recognition to mental health in recent years in turn invites the introduction of necessary public health policies to improve the macro- and microenvironments to promote health. The vital contribution made by mental health to the overall well-being of a population is well recognised in public health.

This study tries to identify the determinants of positive mental health (PMH) in the young people aged 18–24 years, and by focusing on the malleable variables, identifies the possible public health policy interventions to promote PMH. PMH is an attribute, which helps individuals to respond to life positively and productively. It is much more than the mere absence of mental disease.

Objectives of the study

This study has the following objectives:

• To develop and validate a scale for measuring PMH in a sample of young people (age 18–24 years).

• To measure the PMH of young people in Kerala, India, using the scale developed and to identify the correlates of PMH among them.

• To create a model of the determinants of PMH in young people based on these data.

• To identify areas for possible effective policy interventions for promoting mental health in young people.

Methods used

Phase I

Qualitative (Key Informant Interviews) and quantitative methods (Cross Sectional Survey) were used in this phase to develop and validate the scale (Ganga & Kutty, 2012).

The steps used were as follows:

• Defining the construct: Starting with the WHO definition for mental health as a basis for the definition of PMH, five key informant interviews were conducted with experts in the field of mental health to get their inputs to modify the definition in the specific cultural context of India.

• Preliminary scale development: In order to create an item pool to select items to be included in the new scale, the available standardised scales measuring similar constructs were used. An initial pool of 116 items in four subscales was developed. The items were prioritised and a total of 45 items were selected in this preliminary round. For the response part, a five-point Likert format was adopted.

• Translation into the local language was done, which was back-translated.

• Pre-testing: The tool was pre-tested in 20 subjects and cognitive interviews were conducted. The length of the scale was the major problem sited by the respondents in the pre-test.

• Fine tuning: The tool was administered to 326 young people, in the age group of 18–24 years, after receiving consent. The response rate was 99.1%. A total of 3 subjects were excluded from analysis for incomplete responses.

• Scale Reliability analysis: Total scale reliability was analysed by estimating Cronbach's α. The logical importance of items in the scale was also considered to include items in the scale.

• Factor analysis: For further reduction of items in the scale without losing the valuable information in each of the items, factor analysis of the items was done. The factor analysis was followed by scale reliability analysis after the elimination of each item. At the end of this process a 20-item scale with four factors remained.

• Construct validity (separate sample of 55): In the absence of a comprehensive measure to test criterion validity, convergent validity was tested against a newly created five-item PMH inventory and divergent validity against the Mental Health Inventory-5 (MHI-5) (a subscale of the Short Form 36 [SF36]). This constituted the construct validity for the scale.

• Test–retest reliability of the 20-item scale was done in a separate sample of 40 with a gap of five days.

Phase II

All the young people in the age group of 18–24 years (both years inclusive) in the district of Kannur, Kerala, constituted the population from which the sample for this phase was drawn. Based on the Scottish health survey, 2008, the estimated sample size was 450. Sampling method was stratified cluster probability proportional to size (PPS) sampling. Separate PPS sampling was done for rural and urban strata to get representative clusters from each. The cluster size was 10; numbers of clusters were 45. The number of clusters selected from each rural/urban administrative unit is proportional to the population of the same.

The study scale described in Phase 1, along with a detailed interview schedule containing five domains – individual details, family background, details of social interaction, social capital and outlook towards life – was administered to the study subjects.

There were 456 response forms, including some extra subjects (3 urban and 3 rural) who were selected in anticipation of incomplete response in some clusters. Out of these, 453 forms were available for analysis. The response rate was 99.56%. The investigator personally interviewed all the subjects after receiving written informed consent.

Phase III

Using qualitative techniques – two focus group discussions (FGDs) and Delphi technique – to gather information about attitudes, perceptions or opinions of policy-makers and mental/public health experts, policy guidelines for promoting PMH in young people in Kerala were evolved. The sample size for the two FGDs was 18; consensus through Delphi technique was 8. Standard techniques of qualitative analysis were used.

Major findings of the study

In the first phase of the study, PMH was defined as a dynamic state of well-being in which the individual realizes his/her own potential, with the underlying belief in the dignity and worth of self and others, can cope well with the normal stresses of life, is able to work productively and can contribute to the community. A PMH measurement scale was developed, named Achutha Menon Centre Positive Mental Health Scale (AMCPMHS; Ganga & Kutty, 2012), which can be used in both clinical and community settings. The scale's Cronbach's α value was estimated as 0.756 and test–retest reliability as 0.838. The scale mean was 66.85 ( ± 9.39). Convergent validity with PMH inventory was 0.86; divergent validity with MHI-5 was 0.42. The factor analysis gave four underlying constructs:

• realisation of own potential and belief in the dignity and worth of self (six questions);

• belief in the dignity and worth of others (four questions);

• ability to cope with normal stresses (five questions); and

• productivity (five questions).

This scale was used in the second phase of the study – the survey of 453 subjects: 230 (50.8%) males and 223 (49.2%) females. Among the subjects, 382 (84.3%) lived in rural areas and 71 (15.7%) lived in urban areas. Of the respondents, 325 (71.7%) were Hindu, 62 (13.7%) were Christian and 66 (14.6%) were Muslim. There were 268 (59.2%) students and 129 (28.5%) employed young people in the sample.

The mean score for the AMCPMHS in this population is 60.37 ( ± 12.08) (median, 57.5) out of a maximum of 100. Males scored significantly higher than females (males, mean = 64.88 [ ± 10.70]; females, mean = 58.26 [ ± 13.80]; p <  0.01). Of the four domains of PMH, three showed significantly higher scores in males. Two-way ANOVA showed significant sex difference even after controlling for other relevant socio-demographic variables, with females showing lower scores.

A common regression model followed by separate regression models for explaining the score for men and women were created. For males, the significant predictors are religion, employment, years of education, parenting of father and family structure, explaining 12.7% of the variation. For females, the factors are religion, employment, whether studying, parental care and quality of home learning environment, able to explain a much larger proportion of the variation, 44.7%. Religion remains a significant predictor in the common regression model (Ganga & Kutty, 2013a). Young people from the Muslim community have low PMH score compared to those from Hindu and Christian communities; gender enhances the effect.

Path analysis shows that the females, Muslim religion, low social capital and less social interactions, perceived unfavourable parenting, unemployment and low education status, low financial status of the family, being married, poor skills, less adherence to innate values are the conditions which contribute to the low PMH score of young people. The input path model obtained out of a series of multiple regression analyses was tested using AMOS software and the model produced having absolute fit with the data obtained.

The next phase of the study, the FGDs and the Delphi identified areas for possible effective policy interventions for promoting mental health in young people (Ganga & Kutty, 2013b). The suggestions include (1) promoting PMH may find a place in health promotion efforts, separate from the preventive interventions, which requires different expertise and inputs; (2) to address the issue of gender in mental health, multifaceted intervention strategies, which require systematic planning and action including improvements in structural, social, legal and policy environment may be developed. There may be specific policies focusing on strategies to improve the PMH of the population. Tertiary support systems or community support systems such as community hubs may be developed. The policies may target on school-based programmes to improve the social skills of girls as well as adolescents in general on their parenting skills. The interests of women may be protected through grass-root-level interventions, through community-based support system and by implementing favourable laws. Empowerment of women through ensuring the civil political rights will naturally improve the situation of women. The structural determinants such as poverty, unemployment and violence against women are to be addressed through policy.

Significance and implications of the findings

It emerged from the study that in the age group of 18–24 years, young people of Kerala have low levels of PMH. There is a gender difference unfavourable to females even after controlling for other variables. This seems to be not attributable to any innate biological factor but rather to the restrictive environments in which girls are brought up.

Religion, parenting and social connectedness are the other important determinant factors in PMH. Though many of the above-mentioned factors are strongly culturally determined, some are amenable to effective intervention. The recognition of this fact should lead to inclusion of strategies to promote PMH in young people. The study could develop a model of the determinants of PMH of young people in the state of Kerala. This could be used as a framework for integrating the concept of PMH into health policy interventions in the state.

The study could develop and test a useful tool to measure PMH in young people, which seems to be robust in a variety of circumstances. This still needs further testing in different populations. It could be an effective measuring scale for PMH both in the population and individual settings.

Acknowledgement

The contributions made by the research guide, Dr V.R. Kutty is gratefully acknowledged. Also, I hereby thank all the study participants as well as the 28 experts who participated in the focus group discussions and Delphi process.

Additional information

Notes on contributors

Nima S. Ganga

Nima S. Ganga holds a PhD in positive mental health. She is currently a postdoctoral fellow at Achutha Menon Centre for Health Science Studies, the public health wing of Sree Chitra Tirunal Institute for Medical Sciences and Technology with SHARE (South Asian Hub for Advocacy Research and Training on Mental Health) fellowship for doing research in mental health policy. Her research interests include mental health promotion of young people.