| Literature DB >> 36100895 |
Hemavarni Doma1, Thach Tran2, Pilar Rioseco3, Jane Fisher2.
Abstract
BACKGROUND: Forced migration can lead to loss of social support and increased vulnerability to psychological distress of displaced individuals. The aims were to ascertain the associations of sociodemographic characteristics and social support received by resettled adult humanitarian migrants in Australia; determine the relationship between social support and mental health at different intervals following humanitarian migration; and examine the modification effects of gender, age and migration pathway on that relationship.Entities:
Keywords: Asylum seekers; Humanitarian migrants; Mental health; Refugees; Resettlement; Social support
Mesh:
Year: 2022 PMID: 36100895 PMCID: PMC9472377 DOI: 10.1186/s12889-022-14082-z
Source DB: PubMed Journal: BMC Public Health ISSN: 1471-2458 Impact factor: 4.135
Fig. 1Conceptual framework of the correlation between emotional/instrumental support, informational support and psychological distress
Demographic characteristics at baseline (n = 2264)
| Statistics | |
|---|---|
| 36.6 (13.4) | |
| Men | 1249 (55.2%) |
| Women | 1015 (44.8%) |
| No | 888 (39.2%) |
| Yes | 1376 (60.8%) |
| Africa | 149 (6.6%) |
| Middle East | 1197 (52.9%) |
| South East Asia | 134 (5.9%) |
| Southern Asia | 205 (9.1%) |
| Central Asia | 574 (25.4%) |
| 4.43 (3.26) | |
| 6 or less years of schooling | 815 (36%) |
| 7 to 11 years of schooling | 606 (26.8%) |
| 12 or more years of schooling | 821 (36.3%) |
| Major cities of Australia | 2052 (90.6%) |
| Regional Australia | 212 (9.4%) |
| Onshore | 377 (16.7%) |
| Offshore | 1887 (83.4%) |
| Respondent’s own salary or spouse’s/partner’s/parent’s salary or other | 229 (10.3%) |
| Government payments | 2002 (89.7%) |
| Computer-assisted self-interview | 1582 (69.9%) |
| Computer-assisted personal interview with interviewer | 633 (28%) |
| Computer-assisted personal interview with interpreter | 49 (2.1%) |
Association between demographic characteristics (baseline) and emotional/instrumental support at each time point
| Wave One | Wave Three | Wave Five | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Coef. | 95% CI | Coef. | 95% CI | Coef. | 95% CI | ||||
| Age (in 10 years) | −0.002 | (− 0.010 to 0.061) | 0.667 | − 0.215 | (− 0.302 to − 0.128) | 0.000 | − 0.123 | (− 0.216 to − 0.030) | 0.009 |
| Gender | |||||||||
| Men | Ref | ||||||||
| Women | 0.257 | (0.063 to 0.451) | 0.009 | 0.235 | (0.019 to 0.452) | 0.033 | 0.300 | (0.069 to 0.530) | 0.011 |
| Marital status | |||||||||
| No | Ref | ||||||||
| Yes | 0.112 | (−0.089 to 0.314) | 0.273 | 0.309 | (0.081 to 0.538) | 0.008 | 0.090 | (−0.154 to 0.334) | 0.471 |
| Birth region | |||||||||
| Africa | Ref | ||||||||
| Middle East | −0.106 | (− 0.497 to 0.285) | 0.596 | 0.182 | (−0.319 to 0.683) | 0.476 | −0.653 | (−1.203 to − 0.102) | 0.020 |
| South-East Asia | −0.406 | (− 0.943 to 0.132) | 0.139 | − 0.182 | (− 0.839 to 0.474) | 0.586 | − 0.930 | (− 1.671 to − 0.189) | 0.014 |
| Southern Asia | 0.297 | (− 0.193 to 0.788) | 0.235 | 0.017 | (−0.575 to 0.610) | 0.954 | 0.127 | (−0.537 to 0.792) | 0.707 |
| Central Asia | −0.990 | (−1.413 to − 0.566) | 0.000 | − 0.895 | (− 1.427 to − 0.363) | 0.001 | −0.898 | (−1.485 to − 0.311) | 0.003 |
| English proficiency (score) | 0.132 | (0.095 to 0.169) | 0.000 | 0.0676 | (0.027 to 0.109) | 0.001 | 0.091 | (0.047 to 0.136) | 0.000 |
| Education (pre-arrival) | |||||||||
| 6 or fewer years of schooling | Ref | ||||||||
| 7 to 11 years of schooling | −0.288 | (−0.548 to −0.027) | 0.031 | 0.061 | (−0.229 to 0.352) | 0.679 | −0.057 | (−0.363 to 0.245) | 0.705 |
| 12 or more years of schooling | −0.508 | (−0.790 to − 0.225) | 0.000 | −0.076 | (− 0.389 to 0.237) | 0.634 | − 0.404 | (− 0.740 to − 0.069) | 0.018 |
| Remoteness area | |||||||||
| Major cities | Ref | ||||||||
| Regional Australia | 0.547 | (0.203 to 0.890) | 0.002 | 0.208 | (−0.167 to 0.584) | 0.277 | −0.181 | (−0.580 to 0.218) | 0.374 |
| Migration pathway | |||||||||
| Onshore | Ref | ||||||||
| Offshore | 0.153 | (−0.121 to 0.427) | 0.274 | 0.904 | (0.575 to 1.234) | 0.000 | 0.549 | (0.185 to 0.914) | 0.003 |
| Main source of income | |||||||||
| Own or spouse/parent’s salary, savings | Ref | ||||||||
| Government payments | 0.020 | (−0.313 to 0.353) | 0.906 | 0.135 | (−0.246 to 0.515) | 0.488 | 0.033 | (−0.257 to 0.323) | 0.824 |
†Statistical significance set at p < 0.05
aMultiple regression coefficient
Association between demographic characteristics (baseline) and informational support at each time point
| Wave One | Wave Three | Wave Five | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Coef. | 95% CI | Coef. | 95% CI | Coef. | 95% CI | ||||
| Age (in 10 years) | −0.647 | (− 0.828 to − 0.465) | 0.000 | −0.979 | (−1.183 to − 0.774) | 0.000 | −1.765 | (−1.991 to −1.540) | 0.000 |
| Gender | |||||||||
| Men | Ref | ||||||||
| Women | −1.674 | (−2.121 to − 1.226) | 0.000 | −2.459 | (− 2.970 to − 1.948) | 0.000 | − 2.639 | (−3.198 to − 2.081) | 0.000 |
| Marital status | |||||||||
| No | Ref | ||||||||
| Yes | 0.312 | (−0.155 to 0.778) | 0.190 | − 0.087 | (− 0.624 to 0.451) | 0.752 | 0.434 | (−0.158 to 1.026) | 0.151 |
| Birth region | |||||||||
| Africa | Ref | ||||||||
| Middle East | −2.169 | (−3.009 to −1.247) | 0.000 | −1.117 | (−2.313 to 0.078) | 0.067 | −2.088 | (−3.440 to −0.737) | 0.002 |
| South-East Asia | −2.221 | (−3.471 to −0.970) | 0.001 | −2.280 | (−3.824 to −0.736) | 0.004 | −5.764 | (−7.556 to − 3.973) | 0.000 |
| Southern Asia | −1.051 | (−2.188 to 0.087) | 0.070 | −2.942 | (−4.351 to −1.533) | 0.000 | − 2.710 | (−4.331 to − 1.090) | 0.001 |
| Central Asia | −1.078 | (− 2.077 to −0.078) | 0.035 | −0.834 | (− 2.101 to 0.433) | 0.197 | −2.398 | (−3.832 to − 0.964) | 0.001 |
| English proficiency (score) | 0.628 | (0.542 to 0.713) | 0.000 | 0.600 | (0.503 to 0.697) | 0.000 | 0.441 | (0.334 to 0.549) | 0.000 |
| Education (pre-arrival) | |||||||||
| 6 or fewer years of schooling | Ref | ||||||||
| 7 to 11 years of schooling | 0.145 | (−0.458 to 0.749) | 0.637 | − 0.037 | (− 0.723 to 0.648) | 0.915 | 0.393 | (− 0.342 to 1.129) | 0.294 |
| 12 or more years of schooling | 0.825 | (0.172 to 1.478) | 0.013 | 1.156 | (0.419 to 1.892) | 0.002 | 1.723 | (0.914 to 2.533) | 0.000 |
| Remoteness area | |||||||||
| Major cities | Ref | ||||||||
| Regional Australia | −0.497 | (−1.281 to 0.287) | 0.214 | 0.868 | (−0.025 to 1.762) | 0.057 | 0.672 | (−0.294 to 1.639) | 0.173 |
| Migration pathway | |||||||||
| Onshore | Ref | ||||||||
| Offshore | −1.036 | (−1.672 to −0.400) | 0.001 | −1.111 | (− 1.893 to − 0.330) | 0.005 | − 0.633 | (−1.505 to 0.239) | 0.154 |
| Main source of income | |||||||||
| Own or spouse/parent’s salary, savings | Ref | ||||||||
| Government payments | −1.549 | (−2.326 to −0.773) | 0.000 | −0.782 | (−1.681 to 0.118) | 0.088 | −0.752 | (−1.451 to − 0.054) | 0.035 |
†Statistical significance set at p < 0.05
aMultiple regression coefficient
Relationship between social support and psychological distress
| Pathway | Path coef.a | 95% CI | |
|---|---|---|---|
| Emotional/instrumental support Wave One → Psychological distress Wave Three | −0.342 | (− 0.607 to − 0.077) | 0.012 |
| Informational support Wave One → Psychological distress Wave Three | 0.000 | (−0.308 to 0.308) | 0.999 |
| Emotional/instrumental support Wave One → Psychological distress Wave Five | −0.192 | (−0.467 to 0.084) | 0.173 |
| Informational support Wave One → Psychological distress Wave Five | −0.313 | (−0.641 to 0.015) | 0.062 |
| Emotional/instrumental support Wave Three → Psychological distress Wave Five | −0.006 | (−0.294 to 0.281) | 0.965 |
| Informational support Wave Three → Psychological distress Wave Five | −0.347 | (−0.689 to − 0.005) | 0.047 |
†Statistical significance set at p < 0.05
aPath coefficients were estimated simultaneously using a path model controlling for all socio-demographic characteristics in Table 1. For full details of this model see Supplementary file 2: Table 1