Content area
Issue Title: Mental Health and Substance Use
The aims of this research were to study both direct and indirect path analyses of mental health, and to analyse a causal relationship of each variable. A cross-sectional study used stratified random sampling to select Thai immigrant employees in Pranakron Si Ayutthaya Province, Thailand. General data were analysed by number and percentage. The mental health variable was measured by THMHI-15. The latter was analysed by general statistic, and a path analysis. The results found that job conditions and distance travelled between house and workplace had a direct effect on mental health with a standardised regression weight of 0.581, and -0.443, respectively (p value <0.01). It was found that housing conditions had no effect on mental health. The income variable had a direct influence on mental health with a standardised regression weight of 0.68 (p value <0.01). This research indicated that job conditions were an important factor related to mental health.
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Web End = A Path Analysis of Mental Health Among Thai Immigrant Employees in Pranakron Si Ayutthaya Province
Chonticha Kaewanuchit1 Yothin Sawangdee2
Published online: 20 August 2015 Springer Science+Business Media New York 2015
Abstract The aims of this research were to study both direct and indirect path analyses of mental health, and to analyse a causal relationship of each variable. A cross-sectional study used stratied random sampling to select Thai immigrant employees in Pranakron Si Ayutthaya Province, Thailand. General data were analysed by number and percentage. The mental health variable was measured by THMHI-15. The latter was analysed by general statistic, and a path analysis. The results found that job conditions and distance travelled between house and workplace had a direct effect on mental health with a standardised regression weight of 0.581, and -0.443, respectively (p value \0.01). It was found that housing conditions had no effect on mental health. The income variable had a direct inuence on mental health with a standardised regression weight of 0.68 (p value\0.01). This research indicated that job conditions were an important factor related to mental health.
Keywords Thai immigrant employees Mental health
Path analysis Pranakron Si Ayutthaya Province
Introduction
The change in society, economics and environment because of globalisation has led to immigration of the Thai population, especially mental health problems from occupations. Their effects show poor mental health [1]. The denition of mental health by WHO is as a state of well-being in which every individual realizes his or her own potential, can cope with the normal stresses of life, can work productively and fruitfully, and is able to make a contribution to her or his community [2]. The mental health of immigrants is affected by different variables that are associated with the migratory process itself [3].
From the Annual Report 2012 of the National Statistic, Thailand, it was found that immigrants were 1.8 % of the total population. It showed that immigrants within a region gave rise to more immigrant movement than immigrants between regions in 2011. This report represented that the trend of immigration between provinces had increased in 2008 (16.9 %), 2009 (17.2 %), and 2011 (21 %) [4]. Several empirical research studies support the notion that cause and mental health problems among immigrant employees from other countries are inuenced by cultural background, social class inequalities, behavioral risk factors, and job conditions [58]. These have led to poor mental health and psychosocial factors [9] including distance travelled between workplace and house, job conditions, separation from family and friends, lack of social service and access to adequate health services and social exclusion and lack of social support [3, 10, 11]. This was similar to immigrant employees who came from developing countries and worked as famers in the U.S.A., in which situation it was found that poor mental health was caused by lack of access to health services, job conditions, job insecurity, occupation characteristics and distance from workplace to house
& Chonticha Kaewanuchit [email protected]
1 Department of Applied Sciences, Faculty of Science andTechnology, Phranakhon Si Ayutthaya Rajabhat University, Phranakhon Si Ayutthaya,Phranakhon Si Ayutthaya Province 13000, Thailand
2 Institute for Population and Social Research, Mahidol University, Phutthamonthon,Nakhon Pathom Province 73170, Thailand
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and in some cases was linked to stress, anxiety and depression [1215].
Immigrant employees who were housekeepers in the U.S.A. found that job characteristics, organisation, social support, social economic status, low education and occupation characteristics inuenced their job pleasure and mental health problems [1618]. This was similar to a study done in China, and Chinese immigrant employees who worked in Canada, which found that working hours, income, family support, housing conditions, age, job characteristics, income, and social support related to mental health [1921]. However, race and sex exclusion and job insecurity also resulted in poor mental health [17, 22].
This research used the public health and social determinants of the health perspective in this study [2327]. They related to job, and housing conditions all these linked to the immigrants mental health status [2831] within the segment of public health, especially occupational health [32, 33].
In the previous century, Thailand faced several severe problems such as economic crises, social conicts and natural disasters that affected Thai lifestyle and had a bearing on health. A survey of mental health among the Thai population in 2010, they suffered the highest number of mental health problems. The average of the mental health score for those over 15 years of age in Pranakron Si Ayutthaya Province was lower than the average of mental health in Bangkok and other regions [34]. Authors agreed to select this province for this study. This outstanding province is a semi-industrial, rural province where a lot of national immigrant employees work an important transitional phase when it is developing to become industrial area and a world heritage of Thailand. The main hypotheses were distance travelled between house and workplace, job conditions, housing conditions and income inuence mental health.
The aims of this research were (1) to determine a path analysis of both direct and indirect effects of mental health, and (2) to analyse causal relationship of each variable, all of which had an effect on mental health.
Methods
Sample
A cross-sectional survey was conducted from November 22th, 2014 to February 4th, 2015 to reply questionnaire. Participants in this study were 800 Thai immigrant employees living in Pranakron Si Ayutthaya Province, Thailand. The eligibility criteria included Thai immigrant employees who could communicate in the Thai language.
Sample size was calculated as 800 for general statistics. For the path analysis, 800 participants were calculated according to the rule of 5 subjects per parameter.
Instruments
The instruments of this research were divided into 3 parts. Firstly, general geographic data examined previous home address, sex, education, married status, age, and occupation. Mostly, the general geographic data used nominal and interval scales. Secondly, a questionnaire about the path analysis of mental health was distributed among the participants. It consisted of 4 predictor variables (e.g. distance travelled between house and workplace, income, job conditions and housing conditions).The level of measurement was the interval scale. The scale of distance travelled between house and workplace was 1 (3364 km), 2 (65 98 km), 3 (99132 km), 4 (133166 km), 5 (167200 km), 6 (201233 km), 7 (234267 km), 8 (268301 km), 9 (302 335 km), 10 (336369 km), 11 (370403 km), 12 (404 437 km), 13 (438471 km), 14 (472505 km) and 15 (over 506 km). The scale of income consisted of 1 (B5000 baht), 2 (500110,000 baht), 3 (10,00115,000 baht), 4 (15,001 20,000 baht), 5 (20,00125,000 baht), 6 (25,00130,000 baht), 7 (30,00135,000 baht), 8 (35,00140,000 baht), 9 (40,00145,000 baht), 10 (45,00150,000 baht), and 11 ([50,000 baht). The scales of job conditions and housing conditions consisted of 8 and 5 items, respectively, and each item was rated on a 4-point scale ranging from 1 (none) to 4 (the most). All scores were summed up. Job conditions were taken to be factors such as exploitation by employers, job characteristics and job environment on the mental health. Housing conditions were taken to be perception of welfare of the condition of accommodation, house renting and compensation. Finally, mental health was assessed using THMHI-15 [34]. It was divided into 4 domains (e.g. mental state, mental capacity, mental quality and supporting factors) and 15 items. Each item was rated on a 4-point Likert scale ranging from none (1) to the most (4). The scores of all items were averaged, with higher scores indicating a greater level of mental health. The scores were divided into 3 groups: good (5160 points), fair (4450 points) and poor mental health (43 points or below). The Cronbachs alphas for distance travelled between house and workplace, job conditions, housing conditions, income, and mental health scales were 0.79, 0.80, 0.80, 0.81, and 0.89, respectively.
Data Collection
Before data collection, this research was accepted by the Human Ethics Committees (Social Sciences) from Mahidol University, Thailand; the code was COA. No. 2014/202.2907 while the Thai Clinical Trial Registry code
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was TCTR20141122001. Data were collected by the researchers and assistance researchers. The principal investigator explained the entire questionnaire to data collectors. If participants had difculty understanding the questions, data collectors provided further explanations by face-to-face surveys.
Data Analysis
Descriptive statistics were used to analyse the characteristics of participants. Pearsons correlation analyses were used to examine bivariate relationships between predictor variables and mental health. Path analysis was conducted to determine the strength related to the predictor variables and mental health using M-plus (version 5.2). Model t of the path analysis was evaluated.
Results
The demographic characteristics are shown (Table 1). The mean, SD, minimum, maximum, skewness, and kurtosis of each variable are represented (Table 2). The model t of the path analysis was acceptable (Table 3). The path analysis showed between variables and mental health (Fig. 1).
Discussion
This research found that the occupation of 62.30 % of the participants was temporary immigrant employee, while the education level of 47.50 % of the participants was Bachelors degree. The participants age was 4049 years old and their previous home address was located in Northeast Thailand (Table 1) while their mean income was 15,00120,000 baht/month (Table 2). It was found that mental health among Thai immigrant employees was almost poor mental health (Table 2). This nding is not so different from that related to immigrants of Thai population [4, 34]. The changes faced by immigrant employees were the result of the psychosocial condition of occupational stress including job conditions, especially occupational health [32] and social determinants of health perspective that showed up in immigrant employees as psycho-physical symptoms including mental health [25, 35].
Table 3 shows that the measure of goodness of t can vary from 0 to 1. The closer the value approaches 1, the better the path model ts the data. Based on goodness of t indices, the comparative t index of 0.9083 indicated a very close t (CFI,1.000 and an SRMR, 0.000 represent an excellent t.). Furthermore, all the variables could explain mental health change by 73.5 % (R square = 0.735, p \ 0.01).
The main hypotheses of this research was that distance travelled between house and workplace, job conditions, housing conditions and income inuenced mental health. The results found that their variables had a causal relationship with mental health (Fig. 1).
The aims of this research were (1) to determine a path analysis of both direct and indirect effects of mental health, and (2) to analyse causal relationship of distance travelled between house and workplace, job conditions, housing conditions, income, all of which had an effect on mental health among Thai immigrant employees in Pranakron Si Ayutthaya Province. Both aims of this research indicated that after adjustment the path model had both direct and
Table 1 General geographic data among Thai immigrant employees (N = 800)
Data Number Percentage
Previous home address
Northern region 120 15.00
North-eastern region 180 22.50
Central region 300 37.50
Eastern region 100 12.50
Southern region 100 12.50
SexFemale 400 50.00
Male 400 50.00
Age (years)
2029 100 12.50
3039 150 18.70
4049 300 37.50
5059 200 25.00
6069 50 6.30
Education
Primary school 80 10.00
High school 120 15.00
Bachelor degree 380 47.50
Master degree 200 25.00
Doctoral degree 20 2.50
OccupationCivil servants 50 6.30
University employees 50 6.30
Permanent employees 201 25.10
Temporary employees 499 62.30
Income (baht/month)
B5000 10 1.30
500010,000 70 8.70
10,00115,000 150 18.70
15,00120,000 300 37.50
20,00125,000 200 25.00
25,00130,000 50 6.30
30,00135,000 20 2.50
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Table 2 Statistic data among Thai immigrant employees (N = 800)
Variable Mean Minimum Maximum SD Skewness Kurtosis
Distance travelled between house and workplace
320.945 km (code as 9 = 302335 km) 33 km [506 km 2.590 -1.014 0.913
Income 17,750.487 baht/month (code as 4 = 15,00120,000 baht/month)
B5000 baht/month
[50,000 baht/month
1.172 -0.004 0.117
Housing conditions 3.062 (more) 2 (less) 4 (most) 0.658 -0.067 -0.699 Job conditions 2.375 (less) 1 (none) 4 (most) 0.857 0.392 -0.462
Mental health status 1.50 (almost poor) 1 (poor) 3 (good) 0.612 0.818 -0.328
Table 3 Overall test among Thai immigrant employees (N = 800)
Criteria Value
Chi square 0.013 (p value = 0.9083)
CFI 1.000
TLI 1.002
RMSEA 0.000
SRMR 0.000
R square (mental health) 0.735**
** p value \0.01
indirect effects on mental health. Job conditions were exogenous variables that had the greatest direct effect on mental health and showed a positive relationship on mental health. According to the questionnaire used in this research, the persistence of mental health problems among Thai immigrant employees in this province resulted from
the exploitation of employers, shiftwork, bad environment, overtime with payment, working hours of more than 8 job h/day, lack of equipment and not enough rest. This was consistent with the social determinants of health that explained that job conditions were an important variable that had direct inuence on mental health. At the same times, job conditions showed positive relationship on income. It meant that poor job conditions had effect on low income. Distance travelled between house and workplace was the second exogenous variable of this research. It is possible that travelling in a globalised world is easier than in the past. It should be noted that this province is located not far from civil society and Bangkok. This fact represents that distance travelled between house and workplace had negative direction of association on mental health. It was possible that distance travelled between house and work-place among Thai immigrant employees in this province were not so far distance because average of this variable
Fig. 1 A path analysis of mental health among Thai immigrant employees
Distance travelled between house and workplace
-0.443 (p-value < 0.01)
0.389(p-value < 0.01)
0.572 (p-value < 0.01)
Income
(R2 = 0.915, p-value < 0.01)
0.427 (p-value < 0.01)
0.680 (p-value < 0.01)
Mental Health
(R2 = 0.735 p-value < 0.01)
Job
conditions
0.581 (p-value < 0.01)
0.290 (p-value < 0.01)
Housing conditions
0.009
= Direct effect = Indirect effect
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was 320.945 kilometres. Some participants went back their houses in every 12 weeks or month. However, this variable was not dominant, showing its direct effect on mental health. The literature regarding this type of research indicates that distance travelled from house and workplace is an important variable related to mental health [1214]. It should be proofed this variable in the future. By opposite, this variable had positive effect to income. It indicated that far distance travelled between house and workplace associated with high income because this province is an important economics region at the central region of Thailand. Its effect increased income among Thai immigrant employees.
With regards to the rst aim of this research, the results indicated that most of the components of mental health among Thai immigrant employees in this province had a direct and indirect effect on mental health (p \ 0.01). The income variable was a mediator of this research and had a direct effect on mental health (p \ 0.01). In addition, it displayed a positive effect on mental health. It implied that it was a type of direct proportion on mental health. It meant that Thai immigrant employees who had low income. Their mental health were poor. At the same times, Thai immigrant employees who had high income more. Their mental health were better. Conversely, however, housing conditions did not have either a direct or indirect effect on mental health.
With regards to the second aim of this research, the results indicated that distance travelled between house and workplace, job conditions and income had a causal relationship that was either an exogenous or endogenous variable related to mental health (p \ 0.01). Nevertheless, housing conditions did not have a causal relationship with mental health among Thai immigrant employees (no signicance) and could not specify a result. Some literature related to this type of research describe this variable as having a causal relationship with mental health among immigrant employees [19, 20].
The results indicated that there was consistency with ndings of occupational research conducted in various other countries. For example, job conditions [7, 9, 36] had a negative effect on mental health, especially in terms of the psychosocial factor. In addition, distance travelled between house and workplace, job conditions and lack of social support [3, 10, 11] had an inuence on mental health problems. It is consistent of immigrant agricultural employees who came from developing countries to work in the U.S.A., who found that job conditions, job insecurity, occupational characteristics, distance travelled between house and workplace, and inconvenient transportation were risk factors for poor mental health and in some cases led to mental health problems (e.g. stress, anxiety and depression) [1215]. Job characteristics, social support, socioeconomic
status and education factors [16, 18, 19] among immigrant employees in the U.S.A. were linked to mental health problems (e.g. depression) and poor mental health. In China, period of year, income, family support, housing conditions, age, and occupational characteristics had an inuence on mental health (e.g. stress among immigrant employees) [20]. Income and social support among China immigrant employees in Canada as well as race, sex and occupational characteristics [17, 21, 22] had an inuence on mental health. A previous research study found that job conditions among university employees were an important variable linked to occupational stress in Thailand [37]. Moreover, Brazilian immigrant employees were exposed to psychosocial job hazards and had experienced a variety of health symptoms that may be associated with these work environment exposures [38].
The major strengths of this research are the focus on a path analysis of how job conditions, housing conditions and income factors are linked to mental health. It links to both concepts of public health, occupational health and social determinants of health. The concept of public health in terms of occupational health that focused on psychosocial dimension was at the micro level. But the concept of social determinants of health that focused on job and housing conditions was at the macro level. This research explores the main variables related to mental health to clearly explain the path analysis between the variables in terms of psychosocial hazards in the area of public health under occupational health in Thailand. The results indicated that well-validated measures were used to drive rapid changes in Thai society in the globalised world. The other strengths of this research are that the questionnaire contained only a few longer and short questions and there were all easy to understand. In addition, the results of this research can be applied to create mental health policy in Thailand to improve a measurement index of happiness of Thailand and good mental health.
There were several limitations to the present research. First, using THMHI-15 in Thailand, to measure mental health among the Thai immigrant employees showed that the level of poor mental health among the participants was remarkably high. In this research, the authors did not use other mental health tests to compare results; they only used THMHI-15 test. This was because the other Thai stress tests did not have unity of psychosocial dimensions. This test was not used to measure mental health symptoms. This is a measure with high sensitivity, but lower specicity in terms of occupational health and psychosocial hazard because it could not specify mental diseases. The authors suggest that for future studies a way to measure mental health in Thailand should be selected where other measurements to determine mental health symptoms or disease are also used.
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A second limitation was that this research did not have an independent variable, specically, individual variables. Mental health in this research was a dependent variable in the path analysis. The authors did not try to link individual factors in the path model because the focus was just on the psychosocial dimension in the area of public health. The authors suggest that future studies in this area include several individual factors such as e.g. sex and education.
Furthermore, a third limitation of this research was that budget management from National Research Council of Thailand to university was fast, but budget management from university to the researchers was delayed. This limitation suggests that university could do with better budget management.
A suggestion for future research is to add either some individual factors (i.e. age, education, income) linked to mental health or to study specic job conditions and occupational stress by using the path analysis or SEM under the ASIAN community. In addition, the ndings suggest that a path analysis in this research highlights the importance of the development of Thai immigrant employees mental health policies. Decision makers should give more attention to all facets of Thai immigrant employees and other employees under future ASIAN communities as Thailand changes.
Conclusion
This research demonstrated that job conditions were an important factor related to mental health among Thai immigrant employees. In line with this research, a signi-cant relationship between job conditions and mental health was observed, and the mediating effect of the income factor was also supported. However, in contradiction, housing conditions were not a signicant relationship of mental health. The results of this research have implications for public health, especially occupational health research and practice as they can bring awareness to occupational professionals of the importance of a comprehensive approach to poor mental health prevention in this vulnerable Thai population.
Acknowledgments This project was funded by the National Research Council of Thailand (NRCT), Thailand.
Compliance with Ethical Standards
Conict of interest The authors declare no conicts of interest.
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