BEU, Alm.del - 2020-21 - Bilag 179: Orientering om artikel fra NFA og Veterancenteret om hjemvendte soldaters sandsynlighed for at komme i beskæftigelse, fra beskæftigelsesministeren og forsvarsministeren

Beskæftigelsesudvalget 2020-21
BEU Alm.del Bilag 179
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Deployment experiences and mental health problems as predictors of post-deployment

unemployment length: A prospective, register-based study among Danish soldiers

Andreas F. Elrond AF

1,2

, Paul M. Conway

, Søren B. Andersen

, Karen-Inge Karstoft

1,2

, Mia S. Vedtofte

Jacob Pedersen

Research and Knowledge Centre, The Danish Veteran Centre,

Garnisonen 1, 4100 Ringsted, Denmark

Department of Psychology, University of Copenhagen,

Øster Farimagsgade 2A, 1353 Copenhagen K, Denmark

National Research Centre for the Working Environment,

Lersø Parkallé 105, 2100 Copenhagen Ø, Denmark

Correspondence to:

Andreas Friis Elrond

Research and Knowledge Centre

The Danish Veteran Centre

Garnisonen 1, 4100 Ringsted, Denmark

E-mail: [email protected]

Word count:

2998

Tables and figures:

2 tables and 1 figure.

Running head:

Deployment-related predictors of unemployment length

BEU, Alm.del - 2020-21 - Bilag 179: Orientering om artikel fra NFA og Veterancenteret om hjemvendte soldaters sandsynlighed for at komme i beskæftigelse, fra beskæftigelsesministeren og forsvarsministeren BEU, Alm.del - 2020-21 - Bilag 179: Orientering om artikel fra NFA og Veterancenteret om hjemvendte soldaters sandsynlighed for at komme i beskæftigelse, fra beskæftigelsesministeren og forsvarsministeren

Abstract

Objectives: Military deployment experiences and post-deployment posttraumatic stress disorder (PTSD)

and depression may affect formerly deployed soldiers’ (FDS) probability of gaining employment after

leaving the military. However, previous studies have provided mixed evidence on these relationships. This

study tested questionnaire responses on deployment experiences in combination with screening levels of

PTSD and depression approximately 6 months after homecoming as predictors of subsequent probability of

gaining employment when unemployed from 6 months to 5 years post-deployment.

Methods: FDS responders (n = 3,935) and non-responders

= 3,046) to a 6-month post-deployment

screening questionnaire after returning from a first ever deployment to Kosovo, Iraq, or Afghanistan (2002

– 2012) were included in the study. Three Cox regression models including (1a) deployment experiences,

(1b) PTSD and depressive symptoms, (2) deployment experiences, PTSD and depressive symptoms for FDS

responders, and a fourth model on for all FDS (3) with indication on whether they responded to the

questionnaire were used to assess time-to-event transitioning from unemployment to employment from 6

months to 5 years post-deployment. All models were controlled for age group and region of residence and

were stratified for education and the underlying time period.

Results: Deployment experiences, PTSD and depressive symptoms were not significant predictors of

transitioning from unemployment to employment in any of the tested models. A tendency among non-

respondents to have a lower probability of transitioning from unemployment to employment was found

(HR = 0.90, 95% CI = 0.81 – 1.00).

Conclusion: Deployment experiences, PTSD and depressive symptoms, as measured at a 6-month follow-

up, did not predict differences in the probability of gaining employment when unemployed within 5 years

post-deployment. However, the findings suggest that those with the least probability of transitioning from

unemployment to employment can be found among the non-responders to the post-deployment screening

questionnaire.

Keywords

Military; Veterans; Post-deployment; Functioning; Employment: Unemployment; Cohort studies

Strengths and limitations of this study



This study accounted for previous methodological limitations in the field by using a registry-based

outcome to assess the exact time in unemployment before gaining employment, while using

validated scales from a systematically deployed screening questionnaire to account for deployment

experiences, and PTSD and depressive symptoms.



The use of registries allowed for the relation between non-response to the screening questionnaire

and the chance of gaining employment when unemployed to be tested separately.



The setup, however, did not allow to control for the effects of mental health treatment based on

the results of the screening questionnaire, or for incorporating information on the reason for

soldiers to separate from the defence before the unemployment.

INTRODUCTION

Formerly deployed soldiers´ (FDS) ability to gain employment after leaving the armed forces remain an area

of interest and concern. Identification of factors predictive of employment problems may provide the

possibility of identifying and targeting FDS in need of aid to secure a foothold in the labour market. Studies

have suggested posttraumatic stress disorder (PTSD) [1–5] and depression [4,6–10], independently and in

combination [9,11], to be related to higher levels of post-deployment unemployment and non-employment

in soldier populations, and to have an effect on the ability of FDS to work and function to their full

capabilities [2,12–15]. However, several other studies have found PTSD [6–8,11,13,14] and depression

[8,11,13,14] to have no or a limited relationship to subsequent unemployment for FDS. Depletion in

functioning [14] and lack of trust in one’s ability to gain employment [2,10] rather than a complete inability

to work have been suggested as the consequence of PTSD and depression. This may affect those who are

unemployed and looking for employment. Research into the effects of deployment on unemployment,

independent and beyond the effects of PTSD and depression, remains limited, with studies both supporting

[13,16,17] and not supporting [8,18] a relationship. However, no study has previously examined the effects

of deployment experiences and PTSD or depressive symptoms as predictors of transitioning from

unemployment to employment in FDS.

Previous research presents a series of methodological issues that limits conclusions about FDS’ ability to

gain employment. Differences in results across employment studies may among other factors be attributed

to considerable variation in duration and timing of post-deployment symptom assessments [19]. Moreover,

the timing of the employment outcomes (ranging from days to years [16,20]), as well as disparity of the

underlying periods [16,20] may affect the results. The widespread use of cross-sectional data or data from

treatment- and help-seeking veteran populations further limits the possibility of drawing conclusions about

causal relationships between deployment experiences, mental health problems and post-deployment

employment [21,22]. Non-response to predominantly voluntary screening programs is high [23], and has

been related to poorer mental health outcomes [24,25]. Finally, the use of a single-point follow-up, which

only allows for dichotomous outcome categories (e.g., unemployed vs. employed), does not allow for the

study of FDS’ transitions in the labour market.

Against this background, the primary aim of this study was to investigate deployment experiences as well

as PTSD and depressive symptoms at screening as predictors of gaining employment when unemployed,

from 6 months to 5 years after the first-ever military deployment. To this end, we used a systematically

distributed screening questionnaire and national register data on employment status. Given a non-

response rate of 43% of the identified population, a secondary aim was to investigate non-response to the

questionnaire as a predictor of gaining employment when unemployed.

METHOD

Data

We used the deployment database of the Danish Veteran Centre [26] to identify period and country of

deployment as well as previous deployments. From the Danish Veteran Centre, we obtained data from self-

report questionnaires on Psychological Reactions following International Missions (PRIM). PRIM has been

routinely distributed by personal mail since 1998 to Danish FDS approximately 6 months after homecoming

to assess deployment experiences and post-deployment reactions in order to identify those in need of

support by military psychologists. PRIM consists of 125 individual items covering deployment experiences,

post-deployment reactions and post-deployment support, as well as five validated scales, here amongst

PTSD- and depressions symptoms as well as deployment experiences (see “Predictors” below for included

items and scales). The questionnaire has an average response rate of 60% across all deployments [27]. Data

on labour market transitions came from the Danish Register for Evaluation of Marginalization (DREAM),

which contains weekly records of social benefit payments for all Danes since 1991 [28]. All data was hosted

by Statistics Denmark and linked via a unique personal identification number, and the analyses were

conducted on de-identified records on Statistics Denmark’s servers. Due to the low rates of missing data we

excluded subjects if they had missing data on any of the selected measures.

Population and procedure

We included FDS who had a single deployment to Kosovo, Iraq or Afghanistan from 2002–2012 (see Figure

1 for attrition). Of 10,974 FDS deployed to one of these countries and during the period of interest, 2550

were excluded due to having previous deployments, and 633 for being deployed again before the follow-up

period 6 months after the first homecoming. This was done to exclude potential effects of previous or

subsequent deployment experiences. In addition, 3348 (43.0%) did not have a corresponding PRIM record,

while the correct record could not be identified in 18 cases. In the study period the Danish defence used

temporary contracts or permanent contracts that terminate at 36 (or 60) years of age. The contract

terminating at age 36 includes the possibility for subsequently taking civilian education for a period while

still getting wage by the defence. To avoid possible systematic bias at 36 years of age, we further excluded

275 FDS that were age 36 or older at the start of follow-up or that were otherwise censored (e.g.,

deceased). Finally, 215 FDS were excluded for having missing data on the PRIM questionnaire used in the

study. This resulted in a final sample of 3935 for the primary analysis. The secondary analysis included 3046

non-responders of PRIM who otherwise met the follow-up criteria just specified.

(Figure 1 here)

Patient and Public involvement

No patients involved. As the study was conducted on de-identified data, the FDS included in this study were

not directly involved in shaping the research question, methods or dissemination. The results will be

disseminated through the Danish Veteran Centre, which is a public institution formed to support and

inform work with the population.

Measures

Unemployment periods and employment

Unemployment periods were identified based on information on weekly payments of unemployment

benefits from the DREAM register. We identified periods of employment as periods without any social

payments. We included all periods of unemployment into the study and counted all unemployment periods

immediately succeeded by an employment period as a transition/event. Periods of other social payments

like sickness absence, education benefits were censored.

Predictors

From the PRIM questionnaire, we included the PRIM-PTSD scale in which scores range from 12–48 and the

cut-off score of 24.5 is used to screen for possible PTSD (No-PTSD/Possible PTSD). The PRIM-PTSD and the

cut-off score have previously been validated [27]. We also included the 8-item PRIM Depression scale

(PRIM-DEP8), which has been validated and shown to be reliable across cohorts [29]. Scores range from 0–8

and a previously established cut-off score of 6 is used to screen for depression [30]. From PRIM we also

included the Rasch validated Exposure to Danger and Combat Scale (EDCS) and the Witnessing

Consequences of War Scale (WCWS) to account for exposure to adverse deployment experiences. EDCS

scores range from 6–24 and WCWS scores range from 4–16 [31], with higher scores indicating a more

dangerous environment. Finally, for the secondary analysis, we included a binary variable indicating

response or non-response to the PRIM questionnaire.

From the registers, we included information on gender and time-dependent information on age group (18–

24, 25–35), highest achieved education (short/preparatory and longer/vocational). Finally, we included

information on habitation in the five geographical regions of Denmark to account for any regional

differences in the chance of gaining employment (e.g. between the Capital region and other less dense

regions).

Statistical analyses

Initial analyses tested the differences in the probability of having a period of unemployment, in relation to

PTSD and depression symptoms, using chi-squared test (ꭓ

). The prospective association of deployment

experiences and mental health problems assessed in PRIM, and response to PRIM with subsequent

unemployment-employment transitions was examined with a four-step Cox regression model [32,33].

We modelled the probability of transitioning from unemployment to employment with the timeline being

the days from 6 months to 5 years post-deployment, and the possibility of late entry (i.e. entering the

model later than at 6 months exactly). FDS were allowed to have multiple and recurrent unemployment

periods and individual variance was accounted for by including a frailty model [32,34]. Soldiers were right-

censored if they redeployed, received a disability pension, died or had turned 36 years of age and thus

could have their contract terminated. FDS were treated as being temporarily censored from the model,

with the possibility of re-entering, when they were not receiving unemployment benefits or if they had

emigrated. We adjusted for changes in employment rates, by dividing the follow-up period into the four

time-periods: 2002–2005, 2006–2009, 2010–2013, and 2014–2017, in which the employment rates were

fairly stable. We stratified the Cox-regression by each period, which allowed for separate baseline hazards

in each time-period.

Model 1a included the war exposure scales EDCS and WCWS. Model 1b included the variables assessing

possible PTSD and depression at the 6-month follow-up. As the questionnaire measures was given only

once to each individual, it was not possible to model a possible mediating relationship between

experiences, mental health problems and the probability of employment; however, model 2 included all

variables of model 1a and 1b to test if experiences had a unique effect on unemployment length after

mental health was factored in. Finally, a second analysis was conducted including the large proportion of

individuals that did not have a PRIM response, and the follow-up response model 3 included an indicator of

response or non-response to test the effect of not responding to the PRIM. All models were adjusted for

gender, age group and region of habitation, and were further stratified by periods of similar employment

rates and education level. The proportional hazard assumption of the predictors in the four models was

evaluated and found acceptable by the use of scaled Schoenfeld residuals through the survival package in R

[36]. Education level was included as a second stratifying variable as it did not meet the proportional hazard

assumption.

A supplementary analysis introduced PTSD and depressive symptoms, which are known to correlate [37],

separately into the models. Further, we conducted a supplementary analysis of the interaction of PTSD and

depressive symptoms that has previously been found elsewhere [11]. Finally, as lower symptomatology has

been previously shown to have weaker association with employment problems [2,15], we also tested the

models using stricter established cut-offs corresponding to a probable PTSD and depression diagnosis (29.5

and seven respectively) [27,29,30] as a sensitivity analysis.

All analyses were performed using base R (version 3.5.1) and the R Survival package (version 2.43.1) [36].

RESULTS

Table 1 shows the baseline characteristics of the FDS population at the beginning of the follow-up period.

Most of the first-ever deployments were to Kosovo and fewest were to Iraq, with Afghanistan being in

between. The majority of FDS were male, and at the beginning of follow-up, the majority were between 18

and 24 years old and had a preparatory or low level of education. Further, 9.9% met the screening criteria

for PTSD, and 8.7% the screening criteria for depression.

Table 1.

FDS population characteristics at the start of follow-up time (6 months after homecoming)

Characteristics

Military deployment

Afghanistan

Iraq

Kosovo

Gender

Female

Age group

18–24

25–35

Education*

Low level

High level

Period

2002–2005

2006–2009

2010–2013

2014–2017

Region of residence

1193

922

1820

251

3082

853

2902

1020

1045

1929

961

Responders

(n = 3935)

30.3

23.4

46.3

6.4

78.3

21.7

74.0

26.0

26.6

49.0

24.4

607

1387

1052

2250

771

2308

738

114

1323

516

1207

Non-responders

(n = 3046)

43.4

17.0

39.6

3.7

75.8

24.2

74.5

25.5

19.9

45.5

34.5

0.007

<0.001

0.667

0.013

<0.001

χ2 test,

p value

<0.001

Capital region

Region Sealand

Region northern Jutland

Region mid Jutland

Region South

Deployment experiences (scales)

EDCS

WCWS

PTSD screening

No PTSD

Screening level PTSD

Depression screening

No depression

Screening level depression

870

528

610

1012

915

3935

3544

391

3591

344

22.1

13.4

15.5

25.7

23.3

Mean (SD)

2.7 (1.9)

3.9 (3.4)

90.1

9.9

91.3

8.7

717

441

483

667

738

23.5

14.5

15.9

21.9

24.2

EDCS = Exposure to Danger and Combat Scale; SD = standard deviation; WCWS = Witnessing Consequences

of War Scale. *No information on education at beginning of follow-up for 13 FDS.

Of the 3935 FDS included, 947 (24.1%) had at least one unemployment period, and of these, 824 (86.9%)

FDS were reemployed within the follow-up period. The proportion having an unemployment period was

significantly higher for the group that screened positive for PTSD (34.5%) than for the group that did not

(22.9%) (ꭓ2 (1) = 25.22, P < .001). Similar results were found for those who screened positive for depression

(33.1%) compared with those who did not (23.2%) (ꭓ2 (1) = 16.32, P < .001).

The results of the four Cox regression models can be seen in Table 2. Deployment experiences included in

model 1a were not predictive of obtaining employment when unemployed. The mental health predictors in

model 1b yielded similar results, as none of these variables predicted transition into employment. As a

result of this, none of the variables were significant predictors when included in the adjusted model 2. The

final model 3 testing non-response as a predictor, found that non-responers bordered on a significantly

lower probability of gaining employment (HR = 0.90, 95% CI = 0.81 – 1.00). In this model higher age was

related with a significantly lower chance of gaining employment (HR = 0.87, 95% CI = 0.78 – 0.98).

The supplementary analyses, introducing PTSD and depressive symptoms separately into the model, testing

their interaction and using stricter established cut-offs, did not change the non-significant finding (results

not shown).

Table 2.

Cox regression models of Hazard Ratios for transitioning from unemployment to employment

Transitioning from Unemployment

to Employment

Model 1a

Deployment experiences

95% CI

Model 1b

Mental health

95% CI

Model 2

Combined

95% CI

Model 3

Follow-up Response

95% CI

Deployment experiences (scales)

EDCS

1.00

(0.97 – 1.03)

1.00

(0.97 – 1.03)

WCWS

1.01

(0.96 – 1.06)

1.01

(0.96 – 1.06)

PTSD screening

No PTSD

1.00

Screening level PTSD

1.06

(0.84 – 1.33)

1.06

(0.84 – 1.34)

Depression screening

No depression

1.00

Screening level depression

0.82

(0.64 – 1.06)

0.82

(0.64 – 1.06)

Gender

Male

1.00

Female

(0.76 – 1.32)

1.02

(0.77 – 1.35)

1.02

(0.77 – 1.36)

1.05

(0.82 – 1.33)

1.00

Age group

18–24

1.00

25–35

0.93

(0.79 – 1.09)

0.99

(0.79 – 1.09)

0.93

(0.79 – 1.09)

0.87

(0.78 – 0.98)

Region of residence

Capital region

1.00

Sealand

0.84

(0.67 – 1.05)

0.85

(0.68 – 1.06)

0.85

(0.68 – 1.06)

0.93

(0.79 – 1.10)

Northern Jutland

0.92

(0.75 – 1.14)

0.92

(0.75 – 1.14)

0.92

(0.75 – 1.14)

(0.83 – 1.15)

0.98

Mid Jutland

0.93

(0.76 – 1.12)

0.92

(0.76 – 1.11)

0.92

(0.76 – 1.11)

1.03

(0.89 – 1.20)

South

0.98

(0.81 – 1.19)

0.98

(0.81 – 1.19)

0.98

(0.81 – 1.19)

(0.86 – 1.15)

1.00

PRIM response

Responder

1.00

Non-responder

(0.81 – 1.00)

0.90

CI = confidence interval; EDCS = Exposure to Danger and Combat Scale; HR = hazard ratio; PTSD = posttraumatic stress disorder; WCWS = Witnessing

Consequences of War Scale; PRIM = Psychological Reactions following International Missions (questionnaire).

All models are stratified by highest achieved education and time period (era).

DISCUSSION

This study assessed experiences during military deployment and screening levels of PTSD and depression as

predictors of differences in the probability of transitioning from unemployment to employment among FDS

under the age of 36 who had experienced one deployment only. The descriptive analyses suggested that

FDS with screening levels of PTSD or depression had a higher probability of experiencing at least one

unemployment period during follow-up. However, no significant associations were found between

experiences during military deployment and screening levels of PTSD and depression, and the probability of

becoming employed in the period considered in any of the models. The secondary analysis that tested

response to the follow-up questionnaire at approximately 6 months found that non-response bordered on

having a relationship with a lower chance of gaining employment. Higher age was in this analysis

significantly related with a lowered risk of gaining employment. These results did take into account the

periodic changes in the underlying chance of gaining employment throughout the timespan (2002–2017)

e.g. during the financial crisis. To the best of our knowledge, this is the first study to use exact register-

based outcome periods to evaluate the effect of deployment experiences and mental health problems on

subsequent labour market transitioning outside of a treatment-seeking population.

Strengths and limitations

The present study has several methodological strengths, which advance methodological limitations of

previous research. In particular, this study was based on bias-free outcomes assessed in register data

including the exact periods of unemployment before transitioning to employment as well as background

characteristics. The objective nature of the outcome enabling us to keep track of individual employment

data on a week-to-week basis, counteracts problems with recall bias or bias relating to differences in risk as

result of differences in follow-up time. Second, the systematic distribution of follow-up questionnaires

across multiple years and missions allowed for inferences to be based on a population with diverse

deployments. Further, the main predictors were measured through validated scales on deployment

experiences, PTSD and depression. However, several limitations must be addressed. First, in the context of

the DREAM data used, employment is characterized by not receiving any public payments and thus being

self-supporting. While this is an accepted method [33], it does not rule out misclassification of the few

persons who become self-supporting without having actual income from employment. Second, the PRIM

questionnaire is typically filled in within 6–8 months after homecoming. However, we did not have the

exact dates the soldiers filled out the PRIM, and consequently all dates were set to 6 months, which is the

approximate time the PRIM questionnaire was first distributed to the FDS. Third, the non-significant

findings in our study may relate to the effects of treatment that is offered by military psychologists based

on the results of the PRIM questionnaire, as well as the help from social workers of the Danish Defence

Veteran Centre, as this select treatment and social help may aid soldiers in gaining employment. This limits

conclusions about the effects of mental health problems independent of treatment. Fourth, we did not

know the reason for departure from the military. Previous studies have found higher levels of attrition from

the military soldiers with mental health problems [38], and a relationship between different reasons for

separation and odds of unemployment [8]. However, our study could not account for any effect of

differences in the reason for separation. Fifth, while the use of self-reported mental health problems is the

general norm within this area of research, the potential underreporting of disability when using self-reports

as compared to more objective measures [39] may lower the contrast between those who responded to

the PRIM. Finally, the setup including the lack of information on the type of work and the FDS’s desire and

satisfaction with the type of employment does not allow us to judge the permanency of the positions

gained when transitioning from unemployment.

Comparison with previous studies

The findings of this study regarding PTSD and depressive symptoms are in agreement with previous cross-

sectional [6,7,11,13] and prospective studies [8,14] conducted outside of treatment-seeking populations,

which did not find PTSD, depression or deployment experiences to predict employment outcomes.

Specifically, our results show that there are no overall differences among FDS in the probability of gaining

employment when unemployed, based on PTSD and depression status as well as deployment experiences.

Still, other cross-sectional studies [2,5–7,9,10] and prospective studies [4] have found such mental health

problems to relate to employment outcomes. Further, our findings on deployment experiences extends

previous findings [13,16,18] on the relationship between combat and unemployment by showing that the

level of exposure to possibly traumatic deployment events was not predictive of the probability of gaining

employment. The differences between our null findings and the positive findings in other studies need to

be addressed. While this study extends previous findings by studying differences in the dynamic transitions

between employment and unemployment, it does not account for the opposite transitions (from

employment to unemployment). Based on this setup we therefore cannot rule out that PTSD and

depression status as well as deployment experiences are predictors of an increased risk of being

unemployed at single time points (e.g. at 1 year post-deployment), as previous studies suggest. Still, the

differences may also pertain to methodological differences. We find that a primary problem in the

literature is the use of cross-sectional data: since unemployment may affect mental health negatively

[9,21,22], cross-sectional studies may inflate the relationship. Second, the use of outcomes sampled at a

single time point allows for differences to coincidentally relate to the timing of assessment more than to

the general risk of unemployment. Third, the differences found between our post 9/11 sample and samples

from other periods may relate to the era of deployment, as several studies have documented major

differences in how military service in different periods affect labour market attachment [1,16,40–42].

The non-existing relationship between mental health and unemployment has also been found in several

treatment-seeking samples [3,5,6,9,10,12], where one would expect the contrasts between mental health

status to be smaller. The difference between these results and our findings may be explained by the

systematic non-response on our screening questionnaires. Thus, the use of registries allowed us to test the

effect of non-response by including 3046 soldiers who did not have a corresponding PRIM follow-up. This

finding suggests that non-responders may have a lower probability than responders to transition from

unemployment to employment. Still these veterans may be among those seeking help and such an effect

could add to a larger contrast in the help-seeking samples. Across response patterns, however, previous

results on the present sample have suggested that FDS overall have a greater chance of gaining

employment when unemployed than comparable non-FDS in the 5 years after homecoming [17].

Future directions

Our results indicate that a systematic screening of deployment experiences, PTSD and depression

symptoms 6 months after deployment, may be not useful to predict the ability to get employment among

unemployed FDS. Further studies are, however, needed to determine if these factors predict transitioning

from employment to unemployment. Future studies investigating predictors of labour market outcomes in

the general population of (non-treatment seeking) FDS should also seek to account for treatment and help

received by the veterans in the time until measurement of employment to account for treatment effects on

employability. Also, while complicated, studies should seek to account for the effects of multiple

deployments. Further, our findings of a possible lowered probability of gaining employment among non-

responders may question the ability of voluntary screenings to account for all of those in need of

employment-related aid after military deployments. These results are also of clinical importance and may

call for an increased early focus on veterans who may be in need of help, but do not respond to distributed

screenings. Finally, while our study did not find PTSD and depression to be significant predictors, the

resulting coefficients do suggest a stronger effect of depression than PTSD on remaining unemployed,

which is consistent with the literature [8], and which may raise awareness to possible differences in the

effects of these mental health problems.

Conclusion

This study investigated deployment experiences and screening levels of post-deployment posttraumatic

stress disorder and depression as predictors of the probability of gaining employment when unemployed in

Danish formerly deployed soldiers with a single deployment behind them. We did not find such factors to

be significant predictors of gaining employment in the time from 6 months to 5 years after homecoming.

Nevertheless, increased awareness of and attention to veterans who do not respond to systematically

distributed screenings may be needed, as it may be among them where we will find those most vulnerable,

and with the lowest probability of gaining new employment if they become unemployed.

Acknowledgements

This study was supported by the Research and Knowledge Centre, The Danish Veteran Centre. The Centre

had no formal role in designing, analysing, interpreting, and writing of the manuscript or on the decision to

submit the paper.

Competing interest

The authors have no competing interest to declare.

Ethical considerations

This study followed the procedures of the Danish Data Protection Agency regarding notification of research

projects containing personal data. Subjects answering the PRIM was informed about the use of data

according to the regulations at the time of response, while the access to conducting research on the

anonymized register data was provided under the regulations of Statistics Denmark. All work on data was

conducted on de-identified data via the servers of Statistics Denmark. No ethics committee approval was

required, as the study was a secondary analysis of previously collected data combined with register data

available for the research purpose.

Author’s contribution



Andreas Friis Elrond: Contributed to the design of the study; Data setup; Analyses; Writing of the paper

Paul Maurice Conway: Contributed to the design of the study; Writing of the paper

Søren Bo Andersen: Contributed to the design of the study; Writing of the paper

Karen-Inge Karstoft: Contributed to the design of the study; Writing of the paper

Mia Sadowa Vedtofte: Contributed to the design of the study; Writing of the paper

Jacob Pedersen: Contributed to the design of the study; Data setup; Analyses; Writing of the paper

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Figure Legends

Figure 1.

Fall-out of formerly deployed soldiers until follow-up, responders and non-responders. FDS =

Formerly Deployed Soldiers; PRIM = Psychological Reactions following International Missions

(Questionnaire).