| Literature DB >> 27703751 |
David Forbes1, Meaghan O'Donnell1, Rachel M Brand2, Sam Korn3, Mark Creamer4, Alexander C McFarlane5, Malcolm R Sim1, Andrew B Forbes6, Graeme Hawthorne7.
Abstract
BACKGROUND: The mental health outcomes of military personnel deployed on peacekeeping missions have been relatively neglected in the military mental health literature. AIMS: To assess the mental health impacts of peacekeeping deployments.Entities:
Year: 2016 PMID: 27703751 PMCID: PMC4995565 DOI: 10.1192/bjpo.bp.115.001321
Source DB: PubMed Journal: BJPsych Open ISSN: 2056-4724
Participant demographics (n=1025)
| Total, % | |
|---|---|
| Age group, years | |
| 0–39 | 19.5 |
| 40–49 | 48.8 |
| 50–59 | 23.8 |
| 60+ | 7.8 |
| Age, years: mean | 46.5 |
| Gender | |
| Male | 95.5 |
| Female | 4.5 |
| Educational attainment | |
| Primary school | 1.3 |
| Trade certificate | 42.0 |
| High school | 35.6 |
| University/College degree | 21.1 |
| Relationship | |
| Single | 7.0 |
| Married/de facto | 81.3 |
| Divorced/separated | 11.7 |
| Work status (current) | |
| Working full or part-time | 74.9 |
| Out of workforce | 4.9 |
| Retired or on benefits | 20.2 |
| Household income, $ | |
| 0–24 999 | 4.0 |
| 25 000–49 999 | 12.2 |
| 50 000–74 999 | 24.7 |
| 75 000–99 999 | 20.4 |
| 100 000+ | 38.5 |
| Pension status | |
| Receiving benefits | 43.4 |
| Not receiving benefits | 56.6 |
| Number of times deployed[ | |
| 1 | 73.6 |
| 2 | 19.1 |
| 3+ | 7.3 |
| Number of study deployments[ | |
| 1 | 87.0 |
| 2+ | 13.0 |
Number of times deployed refers to the number of deployments in the participant’s career, including deployments outside of the study deployments.
Number of study deployments refers solely to the number of times participants have been deployed specifically to the peacekeeping deployments in the scope of this study.
Deployment-related traumatic stress exposure assessed by the Traumatic Stress Exposure Scale – R2 (TSES-R2), by deployment
| Deployment | TSES-R2: frequency | TSES-R2: fear and/or horror at the time | TSES-R2: fear and/or horror now | ||||
|---|---|---|---|---|---|---|---|
| Mean | s.d. | Mean | s.d. | Mean | s.d. | ||
| Cambodia | 293 | 9.43 | 4.83 | 9.00 | 6.38 | 5.56 | 6.54 |
| Namibia | 193 | 8.03 | 4.91 | 7.81 | 5.67 | 4.70 | 5.54 |
| Rwanda | 110 | 11.51 | 5.09 | 10.92 | 6.78 | 8.54 | 8.09 |
| W. Sahara | 38 | 6.55 | 5.16 | 7.61 | 7.35 | 5.21 | 8.11 |
| Somalia | 214 | 11.44 | 4.81 | 10.84 | 6.85 | 8.21 | 8.29 |
| INTERFET | 65 | 8.14 | 5.49 | 7.58 | 6.04 | 3.68 | 4.87 |
| UNTAET | 101 | 7.37 | 4.81 | 6.09 | 5.09 | 4.43 | 5.44 |
| Total | 1014 | 9.42 | 5.16 | 8.97 | 6.48 | 6.07 | 7.03 |
| Statistics | Kruskal–Wallis χ2=95.28, d.f.=6, | Kruskal–Wallis χ2=59.89, d.f.=6, | Kruskal–Wallis χ2=47.17, d.f.=6, | ||||
INTERFET, International Forces East Timor; UNTAET, United Nations Transitional Administration in East Timor.
TSES-R2 data were available for 1014 of the 1025 participants.
Twelve-month CIDI diagnosed psychiatric disorder comparisons
| PK total sample ( | NSMHWB sample ( | Statistics | |
|---|---|---|---|
| Post-traumatic stress disorder | 16.8 | 6.0 | |
| Generalised anxiety disorder | 4.7 | 2.9 |
|
| Major depressive episode | 7.0 | 2.8 |
|
| Alcohol misuse | 12.0 | 3.5 |
|
| Alcohol dependence | 11.3 | 3.6 |
|
| Substance dependence | 2.6 | 0.7 |
|
| Suicidal ideation | 10.7 | 2.7 |
|
| Suicide plan | 5.8 | 0.7 |
|
| Suicide attempt | 1.0 | 0.2 | |
| Number of CIDI disorders | |||
| 1 | 21.6 | 9.7 | |
| 2 | 6.8 | 1.7 | |
| 3+ | 1.5 | 0.8 |
|
CIDI, Composite International Diagnostic Interview; NSMHWB, National Survey of Mental Health and Wellbeing; PK, peacekeeper.
Predictors of psychiatric disorder: univariate analyses, by disorder
| Test statistic (d.f.) | ||||||
|---|---|---|---|---|---|---|
| Statistical test | Post-traumatic stress disorder | Generalised anxiety disorder | Major depressive episode | Alcohol misuse | Alcohol dependence | |
| Demographics | ||||||
| Marital status: unpartnered | Chi-squared | 7.37 (2) | 2.94 (2) ns | 2.99 (2) ns | 5.32 (2) ns | 6.03 (2) |
| Age: older | Chi-squared | 0.86 (3) | 0.73 (3) ns | 1.46 (3) ns | 2.03 (3) ns | 2.71 (3) ns |
| Employment: retired/sickness benefit | Chi-squared | 40.03 (2) | 37.37 (2) | 52.13 (2) | 13.74 (2) | 10.94 (2) |
| Income | Chi-squared | 19.72 (4) | 6.88 (4) ns | 17.97 (4) | 13.08 (4) | 11.58 (4) |
| Trauma exposure/deployments | ||||||
| Age at deployment: older | Kruskal–Wallis | 7.50 (1) | 0.45 (1) ns | 0.20 (1) ns | 0.24 (1) ns | 0.11 (1) ns |
| No. of deployments: >1 | Chi-squared | 5.23 (1) | 0.24 (1) ns | 17.81 (1) | 1.44 (1) ns | 1.34 (1) ns |
| Deployment-related PTEs | Unpaired | 9.35 (1012) | 5.83 (1012) | 5.33 (1012) | 2.99 (1012) | 9.59 (1012) |
| Fear/horror at time | Kruskal–Wallis | 93.69 (1) | 25.12 (1) | 23.62 (1) | 17.59 (1) | 17.50 (1) |
| Lifetime PTEs | Kruskal–Wallis | 58.13 (1) | 29.67 (1) | 10.37 (1) | 11.51 (1) | 6.85 (1) |
ns, not significant; PTE, potentially traumatic event.
For the purpose of univariate analyses, demographic variables were categorised as shown in Table 1. Trauma exposure/deployment variables were dichotomised (other than deployment related PTEs which was treated as a continuous variable).
P<0.05;
P<0.01;
P<0.001.
Logistic regression model for 12-month CIDI-diagnosed post-traumatic stress disorder
| Predictor | Base | Comparator | Odds ratio | 95% CI |
|---|---|---|---|---|
| Life events checklist | 0–4 events | 5+ events | 2.98 | 1.85–4.82 |
| Number of exposures from the TSES-R2 | 0–9 events | 10+ events | 1.60 | 1.00–2.54 |
| Fear and/or horror from deployment exposures at the time | No feelings of fear or horror | Feelings of fear or horror at the time | 2.73 | 1.70–4.40 |
| Employment | Working full or part-time | Retired/sickness benefits | 1.94 | 1.32–2.84 |
CIDI, Composite International Diagnostic Interview; TSES-R2, Traumatic Stress Exposure Scale-Revised 2.
Logistic regression model statistics: Hosmer & Lemeshow χ 2=4.12, d.f.=6, P=0.66. −2LL=777.80. Model correctly classified 82.4% of study participants. Age, marital status, income, age at deployment and number of deployments were all entered into the model as categorical variables (as categorised in Table 1), but were not found to be significant predictors.