Abstract
The data was obtained from a field survey aimed at measuring the patterns of utilization of mental healthcare services among people living with mental illness. The data was collected using a standardized and structured questionnaire from People Living with Mental Illness (PLMI) receiving treatment and the care-givers of People Living with Mental Illness. Three psychiatric hospitals in Ogun state, Nigeria were the population from which the samples were taken. Chi-square test of independence and correspondence analysis were used to present the data in analyzed form.
Keywords: Survey, Utilization questionnaire, Survey analytics, Statistics, Mental health, Psychiatry
Specification Table
| Subject Area | Psychology |
|---|---|
| More Specific subject area | Quantitative Psychology and Mental Health |
| Type of data | Table and text file |
| How data was acquired | Field survey |
| Data format | Raw, partial analyzed |
| Experimental factors | Pattern of utilization of mental healthcare services |
| Experimental features | Only those receiving treatments and the care-givers (in the case of very unstable patients) were considered. Also only those residents in the study areas were considered. Adults younger than 18 years were also excluded. |
| Data Source location | Covenant University Sociology Laboratory, Ota, Nigeria |
| Data accessibility | All the data are in this data article |
Significance of the data
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The central theme is the study of utilization of mental healthcare facilities among people living with mental illness.
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The data could be useful in monitoring the extent to which the mental health services are available and utilized.
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The study can be replicated to other countries with similar demographic factors.
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The data can be used in the overall study of mental health.
1. Data
The data is a summary of responses from a field survey. Structured questionnaires were administered to People Living with Mental Illness (PLWMI) and their caregivers and the aim is to measure the patterns of utilization of mental healthcare services among PLWMI.
Only those receiving treatments and the care-givers (in the case of very unstable patients) were considered. Also, those residents in the study areas that are of Yoruba origin were considered. Adults younger than 18 years were excluded from the study.
The pattern of utilization mental healthcare services in this context was determined by the perceived use of the mental healthcare services by the respondents, frequency of use, frequency of taking prescribed medications and the perceived obstacle of using the available mental healthcare services. These are shown in Fig. 1, Fig. 2, Fig. 3, Fig. 4. The raw data can be assessed as Supplementary data 1 and the questionnaire can be assessed as Supplementary data 2.
Fig. 1.
Perceived use of the mental healthcare services by the respondents.
Fig. 2.
Perceived frequency of use of the mental healthcare services by the respondents.
Fig. 3.
Frequency of taking prescribed medications.
Fig. 4.
Perceived obstacle of using the available mental healthcare services.
2. Experimental design, materials and methods
Mental illness has been believed by numerous experts to be caused amongst others by depression, alcohol and substance abuse, stress, violence against women or minors, post-traumatic stress disorder, women׳s infertility and biological factors. Mental health in particular requires special help, care and management. The treatment may come as psychotherapy and medications which are available in mental healthcare services. The availability of mental health services determines their patterns of usage or utilization [1], [2], [3], [4], [5].
Utilization is connected with ease of use, excellence service, good customer relations, affordable fees charge, management and socio-economic factors.
Questionnaire was used in this article to measure the pattern of utilization of mental healthcare services in Psychiatric hospitals located in three local Government areas of Ogun state, Nigeria. The utilization of the mental healthcare services in the demographics of the study area in particular and Nigeria in general are historically low due to long distance, unavailability of medications, stigmatization, epileptic or skeletal services, poor road networks, poverty and dearth of skilled psychiatrics [6], [7], [8], [9], [10], [11], [12], [13], [14], [15]. Generally, the following statistical analysis and survey methods in these articles can be useful [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30].
2.1. Contingency analysis
Chi-square test of independence was used to determine the association between the measure of utilization of mental healthcare services and the socio-demographics of the respondents and is presented in Table 1, Table 2.
Table 1.
Contingency analysis between the usage of mental services and the soocio-demographic variables.
| Socio-demographic factors | Chi-square | P value |
|---|---|---|
| Gender | 0.153316 | 0.695387 |
| Age | 5.595044 | 0.347636 |
| Marital status | 12.941725 | 0.023931 |
| Religion | 2.046284 | 0.562856 |
| Level of education | 7.503471 | 0.483409 |
| Occupation/ Profession | 12.302178 | 0.138222 |
| Income | 3.307660 | 0.507719 |
| Duration of residency in the studied area | 5.069540 | 0.407453 |
| Family type | 2.222229 | 0.329192 |
| Form of marriage | 1.108207 | 0.574587 |
Table 2.
Contingency analysis between the perceived hindrance of mental services and the soocio-demographic variables.
| Socio-demographic factors | Chi-square | P value |
|---|---|---|
| Gender | 2.667740 | 0.445737 |
| Age | 40.262166 | 0.000414 |
| Marital status | 20.179331 | 0.165161 |
| Religion | 6.378052 | 0.701566 |
| Level of education | 32.969706 | 0.104714 |
| Occupation/ Profession | 31.410814 | 0.142287 |
| Income | 7.675522 | 0.809946 |
| Duration of residency in the studied area | 20.965525 | 0.137934 |
| Family type | 7.046988 | 0.316524 |
| Form of marriage | 4.321635 | 0.633238 |
Remarks: P-value less than 0.05 imply association.
2.2. Correlational analysis
The correlational studies are important to reveal the strength and nature of the observed linear relationship that exist between the measure of utilization and the socio-demographic variables. These are presented in Table 3, Table 4.
Table 3.
Correlational analysis between the usage of mental services and the soocio-demographic variables.
| Socio-demographic factors | Pearson׳s R | P value |
|---|---|---|
| Gender | -0.012084 | 0.695721 |
| Age | 0.026051 | 0.399072 |
| Marital status | -0.088972 | 0.003910 |
| Religion | -0.017942 | 0.561412 |
| Level of education | -0.037189 | 0.228575 |
| Occupation/ Profession | -0.030210 | 0.328092 |
| Income | -0.036221 | 0.240918 |
| Duration of residency in the studied area | 0.015793 | 0.609235 |
| Family type | -0.009194 | 0.766027 |
| Form of marriage | -0.006283 | 0.838854 |
Table 4.
Correlational analysis between the perceived hindrance of mental services and the soocio-demographic variables.
| Socio-demographic factors | Pearson׳s R | P value |
|---|---|---|
| Gender | -0.001236 | 0.968093 |
| Age | 0.078624 | 0.010815 |
| Marital status | -0.032353 | 0.294916 |
| Religion | 0.002405 | 0.937959 |
| Level of education | -0.025976 | 0.400421 |
| Occupation/ Profession | -0.038578 | 0.211642 |
| Income | 0.018045 | 0.559159 |
| Duration of residency in the studied area | 0.028956 | 0.348574 |
| Family type | 0.037799 | 0.221030 |
| Form of marriage | -0.032385 | 0.294450 |
2.3. Correspondence analysis
Correspondence analysis is performed to visually display the contributions of the income of the respondents to the hindrance from using mental health services. Details on correspondence analysis can be found in [31], [32], [33], [34], [35].
The results are presented as follows: Correspondence table (Table 5), model summary (Table 6), overview row points (Table 7), overview column points (Table 8) and biplot (Fig. 5).
Table 5.
Correspondence table of patterns of utilization of mental healthcare services among people living with mental illness.
| What hinders people from using mental health services? | Approximately how much is your monthly income (Naira) from all sources? |
|||||
|---|---|---|---|---|---|---|
| Less than N10,000 | N10,000–24,000 | N25,000–39,000 | N40,000-N54,000 | N55,000 and above | Active Margin | |
| Finance | 68 | 346 | 100 | 107 | 163 | 784 |
| Distance | 2 | 27 | 8 | 10 | 9 | 56 |
| Stigma | 14 | 50 | 18 | 25 | 29 | 136 |
| Other (please specify) | 6 | 34 | 8 | 9 | 17 | 74 |
| Active Margin | 90 | 457 | 134 | 151 | 218 | 1050 |
Table 6.
model summary of patterns of utilization of mental healthcare services among people living with mental illness.
| Dimension | Singular Value | Inertia | Chi Square | Sig. | Proportion of Inertia |
Confidence Singular Value |
||
|---|---|---|---|---|---|---|---|---|
| Accounted for | Cumulative | Standard Deviation | Correlation | |||||
| 2 | ||||||||
| 1 | 0.064 | 0.004 | 0.557 | 0.557 | 0.031 | -0.098 | ||
| 2 | 0.055 | 0.003 | 0.411 | 0.968 | 0.029 | |||
| 3 | 0.015 | 0.000 | 0.032 | 1.000 | ||||
| Total | 0.007 | 7.676 | 0.810a | 1.000 | 1.000 | |||
The p value indicates that the income of the respondents is not associated with the hindrance they encountered in the utilization of mental healthcare services.
12 degrees of freedom
Table 7.
Overview row points table of patterns of utilization of mental healthcare services among people living with mental illness.
| What hinders people from using mental health services? | Mass | Score in Dimension |
Inertia | Contribution |
|||||
|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | Of Point to Inertia of Dimension |
Of Dimension to Inertia of Point |
||||||
| 1 | 2 | 1 | 2 | Total | |||||
| Finance | .747 | -.055 | .065 | .000 | .035 | .057 | .409 | .484 | .893 |
| Distance | .053 | -.415 | -.896 | .003 | .144 | .780 | .199 | .799 | .998 |
| Stigma | .130 | .613 | -.158 | .003 | .762 | .059 | .943 | .054 | .997 |
| Other (please specify) | .070 | -.230 | .285 | .001 | .059 | .104 | .326 | .428 | .755 |
| Active Total | 1.000 | .007 | 1.000 | 1.000 | |||||
Table 8.
Overview column points table of patterns of utilization of mental healthcare services among people living with mental illness.
| Approximately how much is your monthly income (Naira) from all sources? | Mass | Score in Dimension |
Inertia | Contribution |
|||||
|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | Of Point to Inertia of Dimension |
Of Dimension to Inertia of Point |
||||||
| 1 | 2 | 1 | 2 | Total | |||||
| Less than N10,000 | .086 | .458 | .424 | .002 | .282 | .281 | .566 | .416 | .981 |
| N10,000–24,000 | .435 | -.254 | -.003 | .002 | .439 | .000 | 1.000 | .000 | 1.000 |
| N25,000–39,000 | .128 | .044 | -.174 | .000 | .004 | .071 | .048 | .644 | .691 |
| N40,000-N54,000 | .144 | .334 | -.416 | .002 | .252 | .453 | .426 | .565 | .991 |
| N55,000 and above | .208 | .084 | .227 | .001 | .023 | .195 | .124 | .780 | .905 |
| Active Total | 1.000 | .007 | 1.000 | 1.000 | |||||
a. Symmetrical normalization
Fig. 5.
Biplot showing the perceived relationship in graphical form.
Remarks: The data was explained by two dimensions. Distance seems not to be perceived hindrance to utilization of mental healthcare services in the studied area.
Acknowledgements
The research was sponsored by the Covenant University Centre for Research, Innovation and Development (CUCRID), Covenant University, Ota, Nigeria.
Footnotes
Transparency data associated with this article can be found in the online version at https://doi.org/10.1016/j.dib.2018.06.086.
Supplementary data associated with this article can be found in the online version at https://doi.org/10.1016/j.dib.2018.06.086.
Transparency document. Supplementary material
Supplementary material
.
Appendix A. Supplementary material
Supplementary material
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Supplementary material
.
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