| Literature DB >> 31923264 |
Wejdan Shahin1, Gerard A Kennedy1, Wendell Cockshaw1, Ieva Stupans1.
Abstract
BACKGROUND: Illness perceptions may vary between different populations. This raises the question as to whether refugees and migrants of the same ethnic background have different perceptions. Understanding differences may have a significant impact on enhancing medication adherence in these groups.Entities:
Mesh:
Year: 2020 PMID: 31923264 PMCID: PMC6953853 DOI: 10.1371/journal.pone.0227326
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Demographics and clinical characteristics for refugees and migrants (n = 319).
| Variables | Refugee | Migrant | |||
|---|---|---|---|---|---|
| Age | 30–40 | 23 (13.8%) | 29 (19.2%) | 20.78(3) | 0.001 |
| 41–50 | 35 (21%) | 59 (39.1%) | |||
| Above 50 | 108 (64.7%) | 60 (39.7%) | |||
| Missing | 1 (0.6%) | 1 (0.66%) | |||
| Sex | Male | 83 (49.4%) | 64 (42.4%) | 1.58(1) | 0.20 |
| Female | 85 (50.6%) | 87 (57.6%) | |||
| Education | Lower secondary | 88 (53.7%) | 42 (28.4%) | 40.57(4) | 0.0001 |
| Higher secondary | 41 (25%) | 26 (17.6%) | |||
| Diploma | 7 (4.3%) | 18 (12.2%) | |||
| Bachelor | 22 (13.4%) | 34 (23%) | |||
| Higher than bachelor | 6 (3.7%) | 28 (18.9%) | |||
| Missing | 4 (2.3%) | 3 (1.98%) | |||
| Occupation | Home/Not working | 139 (84.8%) | 84 (55.6%) | 38.35(2) | 0.001 |
| Self-employer | 4 (2.4%) | 31 (20.5%) | |||
| Governmental/private | 21 (12.8%) | 36 (23.8%) | |||
| Missing | 4 (2.3%) | - | |||
| Arrival year to Australia | 2015–2018 | 58 (34.7%) | 23 (15.4%) | 24.35(3) | 0.0001 |
| 2010–2015 | 55 (32.9%) | 42 (28.2%) | |||
| 2000–2010 | 33 (19.8%) | 41 (27.5%) | |||
| Before 2000 | 21 (12.6%) | 43 (28.9%) | |||
| Missing | 1 (0.6%) | 2 (1.3%) | |||
| Co-morbidities | Having ≥ 2 chronic illnesses | 54 (32.1%) | 35 (23.2%) | 5.5 (1) | 0.02 |
| Diabetes Mellitus | 61 (39.4%) | 38 (25.7%) | 6.44 (1) | 0.01 | |
| Mental illness | 12 (7.4%) | 3 (2%) | 4.98 (1) | 0.03 | |
| COPD | 7 (4.2%) | 6 (4%) | 0.01 (1) | 0.9 | |
| Asthma | 16 (10.3%) | 14 (9.5%) | 0.06 (1) | 0.8 | |
| Back pain | 57 (35.4%) | 42 (28%) | 1.96 (1) | 0.16 | |
| Arthritis | 42 (26.3%) | 36 (24.2%) | 0.18 (1) | 0.67 | |
| Country of birth | Iraq | 83 (49.4%) | 17 (11.2%) | - | - |
| Syria | 54 (32.1%) | 18 (11.8%) | - | - | |
| Lebanon | 17 (10.12%) | 45 (29.6%) | - | - | |
| Egypt | 3 (1.8%) | 18 (11.8%) | - | - | |
| Morocco | 2 (1.2%) | 11 (7.23%) | - | - | |
| Jordan | NA | 13 (8.55%) | - | - | |
| Algeria | 1 (0.6%) | 5 (3.3%) | - | - | |
| Kuwait | NA | 9 (6.3%) | - | - | |
| Emirates | NA | 4 (2.8%) | - | - | |
| Saudi Arabia | NA | 4 (2.8%) | - | - | |
| Other Arab countries | 6 (3.6%) | 8 (5.3%) | - | - | |
Refugee and Migrant causal attributions for hypertension.
| Status | Rank | Causes | Score | %( |
|---|---|---|---|---|
| 1 | Stress | 2 | (31) 31% | |
| 2 | Fear from war | 1 | (18) 18% | |
| 3 | Fate | 0 | (11) 11% | |
| 4 | Don't know | 0 | (8) 8% | |
| Heredity | 2 | (8) 8% | ||
| 5 | Close relatives death | 1 | (7) 7% | |
| 6 | Depression | 1 | (5) 5% | |
| 7 | Weather | 0 | (3) 3% | |
| 8 | Not speaking English | 1 | (2) 2% | |
| Salty food | 2 | (2) 2% | ||
| Migration | 1 | (2) 2% | ||
| 9 | Not finding work | 1 | (1) 1% | |
| physical inactivity | 2 | (1) 1% | ||
| Smoking | 2 | (1) % | ||
| 1 | Stress | 2 | (33) 36.7% | |
| 2 | Heredity | 2 | (23) 25.6% | |
| 3 | Obesity | 2 | (10) 11.1% | |
| 4 | Salty food | 2 | (6) 6.7% | |
| 5 | Don’t know | 0 | (5) 5.6% | |
| 6 | Having DM | 2 | (4) 4.4% | |
| 7 | Physical inactivity | 2 | (2) 2.2% | |
| Smoking | 2 | (2) 2.2% | ||
| Aging | 2 | (2) 2.2% | ||
| Economic reasons | 1 | (2) 2.2% |
Relevant = 2, partially relevant = 1, not relevant = 0.
Fig 1Mediation effects of illness perceptions on the relationship between statuses of migration and standardised path weights presented.
Comparisons of refugee and migrant illness perceptions, and medication adherence.
| BIPQ | Refugee | Migrant | ||
|---|---|---|---|---|
| Illness perceptions (one factor) | 12.8(3.9) | 17.9(4.4) | 10.9 (298) | 0.0001 |
| Personal control | 2.88 (0.98) | 3.64(1.09) | 6.47 (302) | 0.0001 |
| Treatment control | 2.89 (1.23) | 3.91 (1.26) | 7.25 (306.5) | 0.0001 |
| Coherence | 2.78 (1.13) | 3.82 (1.18) | 7.86 (296.8) | 0.0001 |
| Illness identity | 3.82 (1.16) | 2.65 (1.26) | 8.56 (302) | 0.0001 |
| Illness consequences | 3.88 (1.24) | 2.8 (1.23) | 7.72 (311) | 0.0001 |
| Causes | 1.08 (0.79) | 1.73 (0.57) | 7.13 (224) | 0.0001 |
| Timeline | 2.8 (0.86) | 3.08 (0.53) | 3.22 (298) | 0.0001 |
| Medication adherence | 1.36 (1.4) | 2.5 (1.4) | 7.26 (305) | 0.0001 |
Correlations between medication adherence scores and other variables in refugees and migrant.
| Variables | MAQ refugee | MAQ migrants | ||
|---|---|---|---|---|
| Age | 0.06 | 0.43 | -0.009 | 0.9 |
| Gender | 0.1 | 0.2 | -0.03 | 0.77 |
| Employment | 0.14 | 0.07 | 0.23 | |
| Education | 0.24 | 0.036 | 0.67 | |
| Arrival year | -0.93 | 0.24 | -0.11 | 0.17 |
| Comorbidity | -0.11 | 0.18 | 0.04 | 0.62 |
| Illness perceptions (one factor) | 0.48 | 0.53 | ||
| Personal control | 0.33 | 0.51 | ||
| Treatment control | 0.44 | 0.41 | ||
| Causes | 0.43 | 0.45 | ||
| Timeline | 0.13 | 0.112 | 0.07 | 0.43 |
| Consequences | -0.22 | -0.31 | ||
| Identity | -0.27 | -0.30 | ||
| Coherence | 0.4 | |||
Bootstrap analyses of the magnitude and statistical significance of indirect effect.
| Independent variable | Dependent variable | Mediator variable | Unstandardized indirect effect | Size effect | 95% CI mean indirect effect (lower and upper) |
|---|---|---|---|---|---|
| Status of migration | Adherence | Illness perceptions | 0.24 | 0.04 | 0.21–0.36 |