Risk and protective factors for post-traumatic stress among New Zealand military personnel: A cross sectional study.

BACKGROUND: Post-traumatic stress (PTS) is prevalent among military personnel. Knowledge of the risk and protective factors associated with PTS in this population may assist with identifying personnel who would benefit from increased or targeted support. AIMS: To examine factors associated with PTS among New Zealand military personnel.
METHODS: For this cross-sectional study, currently serving and retired military personnel were invited to complete a questionnaire. The questionnaire included a measure of PTS (the Military Post-traumatic Stress Disorder Checklist; PCL-M), where scores ≥30 indicate the experience of significant PTS symptoms and scores ≥45 indicate a presumptive clinical diagnosis of post-traumatic stress. Potential risk and protective factors associated with PTS were examined using logistic regression modelling.
RESULTS: 1817 military personnel completed the questionnaire. PCL-M scores were ≥30 for 549 (30%) participants and ≥45 for 179 (10%) participants. Factors associated with higher PCL-M scores were trauma exposure, older age, male sex, and Māori ethnicity. Factors associated with lower PCL-M scores were greater length of service, psychological flexibility, and better quality sleep.
CONCLUSIONS: PTS was found to be prevalent among New Zealand military personnel. The experience of trauma was strongly associated with PTS. However, factors such as psychological flexibility (the ability to adapt to changes in circumstances) and good sleep were protective, suggesting that these factors could be key targets for interventions designed to reduce PTS among military personnel in New Zealand.

Introduction

In New Zealand, the Defence Force has three primary personnel groups: the Regular Force, Reserve Forces, and Civilians (including those employed by the Defence Force and working overseas) [1]. These military personnel are responsible for contributing to the defence, security and wellbeing of the country. Research from other countries suggests that while many military personnel cope well with their roles [2], they are exposed to higher rates of both military and non-military trauma compared to the general population [3-5], and can be at greater risk of experiencing post-traumatic stress (PTS) [6, 7]. An elevated risk has been identified among some military personnel even during periods of low deployment activity [8-10].

Two critical events are commonly described in the military ‘life course’–achievement of veteran status through operational deployment, and transition from military to civilian life. Operational deployment and witnessing atrocities has been associated with PTS [11, 12], while the period of transition from the military to civilian life has been found to confer an elevated risk of suicide, regardless of deployment history [13]. A lack of support during this period (including social and family support) serves to amplify suicide risk, and has been found to contribute to the experience of PTS [14].

While the two critical events described have been identified across diverse military samples [14], estimates of the prevalence of PTS vary dramatically both across and within countries. For example, the prevalence of PTS identified among deployed members of the United Kingdom Armed Forces is estimated to be 6% [15]. This is lower than estimates reported for deployed military personnel serving in the United States, Australia, and Canada, which range from 8–20% [16, 17]. Although differences are partially attributable to variation in sampling strategies, research methods, and diagnostic thresholds, differences in exposure to risk factors are also likely to play a role [16]. Research in veteran populations suggests that factors that can negatively affect adaptation to deployment and civilian transition include: female gender, ethnicity, high number of and longer duration deployments, prior adverse life events, pre-existing psychological disorders, trauma exposure, and alcohol misuse [14, 18–21]. Conversely, sleep [22, 23], social support [24, 25], and psychological flexibility (the ability to flexibly choose behaviour that is in line with personal goals and values) [26] are factors that have potential to protect against poor mental health outcomes, including PTS.

A significant number of New Zealand military personnel have been exposed to high levels of combat-related trauma and others have been deployed on peace-keeping missions [27]. Moral injury is one stressor associated with peace-keeping missions, defined as “perpetrating, failing to prevent, bearing witness to, or learning about acts that transgress deeply held moral beliefs and expectations” [28]. Other stressors include the restrictive rules of engagement [29], monotony and boredom, personnel encounter difficulties, and separation from family [30]. Pre-deployment and follow-up stages are also important to consider; these were the most stressful periods, and had the greatest effect on mental and physical health, in a longitudinal study of 277 New Zealand military personnel deployed on peacekeeping duties [27].

While 10% of a community sample of New Zealand Vietnam War veterans were found to experience PTS [31], the prevalence of PTS among New Zealand military personnel more generally has not previously been reported. One reason for this is low response rates to post-deployment screens for PTS [32]. Research is also yet to identify the key risk and protective factors associated with PTS in this population. These factors may differ to those that have been identified in other military populations because of the significant contextual variation that exists across countries [16]. For example, the United States has a Veterans Health Administration that provides comprehensive and integrated healthcare specifically tailored to meet the unique needs of military personnel whereas such a system does not exist in New Zealand. Information on risk and protective factors is important to detect individuals who would benefit from targeted support following transition from the military, in order to reduce their risk of experiencing PTS. The aims of this cross-sectional study were to: 1) determine the prevalence of PTS (symptomology and presumptive clinical cases), and 2) identify protective and risk factors most strongly associated with PTS in a large sample of New Zealand military personnel.

Materials and methods

Sample

An online or paper questionnaire was available during June to December 2018 for completion by military personnel living in New Zealand. We defined ‘military personnel’ as any individuals who had served in the New Zealand Defence Force on active duty or in the reserves, regardless of whether they were still in service or had separated from the military. All military personnel residing in New Zealand were eligible to participate in the study. With respect to exclusion criteria, individuals who had not served in the Armed Forces were excluded, such as members of the national police force and Fire and Emergency New Zealand volunteers and staff. We attempted to recruit as many personnel as possible through an intensive recruitment campaign. According to the New Zealand Defence Force (NZDF), the number of currently serving personnel as of June 2018 was 14770 individuals. Of these, 9354 were regular personnel (2127 Navy, 4673 Army, 2554 Air Force), 2420 were reserves (480 Navy, 1685 Army, 255 Air Force), and 2996 were civilian personnel. Unfortunately the total number of living retired personnel at the time of this questionnaire study could not be determined. Since the end of World War II, in excess of 94,000 New Zealand Operational Service Medals (OSM, indicating operational veteran status) have been awarded but many of these may have been awarded posthumously.

Procedure

Two different strategies were used to invite different types of personnel to take part. The NZDF hosts a secure Defence Intranet Exchange System (DIXS), and in mid-June, a message with an invitation to participate, and a link to the study web site, was sent on DIXS to the 3874 currently serving regular and reserve New Zealand Defence Force (NZDF) OSM holders. Retired military personnel were recruited through study posters distributed to the 43 local social clubs of the Royal New Zealand Returned and Services Association (RSA) identified by the RSA national office to be ‘veteran active.’ Paper questionnaires were also deposited at the RSAs along with instructions for how to return these to the research team. Announcements about the study were made on military social media pages, and both retired and currently serving personnel were invited to participate through an announcement on the No Duff Charitable Trust website; No Duff is a registered charity committed to providing confidential support for military personnel and their families in New Zealand [33].

All study invitations (including emails, posters, and announcements) described the study as a survey designed to examine the health and wellbeing of current and former service personnel. Potential participants were informed that results from the survey would be used to help identify military personnel who might benefit from extra support. No mention of PTS was made on any of the study advertisements, minimising the potential for responder bias. Study posters and announcements included a link to a website from which interested personnel could access the online questionnaire. Advertisements of the study also advised all potential participants that they could request a paper version of the questionnaire from the research team if this was their personal preference.

Military personnel who visited the study website were required to enter their name and email address. This resulted in a personalised link being sent to their email address from which they could complete an online secure version of the questionnaire. Upon accessing this, participants were provided with an information sheet that documented the benefits and risks associated with the study as well as contact details for organisations that provide support for New Zealand military personnel. The information sheet noted that the questionnaire would take approximately 20 minutes to complete, that all study data would be kept strictly confidential to the research team, and that all participants would go into a prize draw to win a weekend holiday for two in New Zealand. Paper versions of the study information sheet and questionnaire were posted out to all personnel who contacted the research team indicating that this was their preference. These were posted with a return postage envelope. The study received approval from the Southern Health and Disability Ethics Committee of New Zealand (15/STH/40/AM02). We consulted with the Ngāi Tahu Research Consultation Committee in order to assess the importance of the project to Māori, New Zealand’s indigenous population.

Measures

The questionnaire included standardised measures of PTS (outcome) and six exposures.

Potentially adverse exposures examined included trauma, general distress, and hazardous drinking. Protective exposures included social support, sleep, and psychological flexibility.

Symptoms of PTS were assessed using the post-traumatic stress disorder (PTSD) checklist–military version (PCL-M). The PCL-M includes 17 items that ask about DSM-IV symptoms of PTS related to stressful military experiences, with response options ranging from 1 ‘Not at all’ to 5 ‘Extremely’ [34]. A total symptom severity score is calculated by summing responses to each option (range = 17–85). While scores of 30–35 indicate significant PTS symptomology and probable cases of PTSD, scores of ≥45 indicate a presumptive PTSD diagnosis [34]. In the present investigation, we present findings in relation to the two different cut-offs. This is because their utility is dependent on whether PTS scores are to be used for clinical objectives (such as to inform decisions about referral for clinical evaluation) or to estimate prevalence in a particular population [35]. The PCL-M has been identified as a widely used and well-validated measure in military populations [36].

The Brief Trauma Questionnaire (BTQ) was used to assess exposure to trauma. The BTQ consists of 10 items that screen for a range of different traumatic experiences [31]. For each item, participants are required to respond ‘yes’ or ‘no’ to indicate whether they have experienced the event and if so, whether they considered the event to present a threat to life or serious injury, and whether or not the event resulted in serious injury. Exposure to an event is scored as positive if a respondent says ‘yes’ to indicate life threat or serious injury from combat trauma, a serious car accident, a natural disaster, life-threatening illness, and physical or sexual abuse, or to indicate exposure to violent death [37]. The BTQ is considered a reliable and valid measure to assess trauma exposure in defence force personnel [38].

Symptoms of distress were screened for using the General Health Questionnaire 12 (GHQ-12). This measure includes 12 items with a four-point response scale [39], which participants use to describe how they have been feeling over the past few weeks e.g. ‘better than usual, same as usual, less than usual, much less than usual’. Using the Likert scoring method, items are summed to yield an overall total score (range = 0–36), with higher scores indicating greater distress [39]. The GHQ-12 is a reliable and valid measure [39] that has been used among military personnel in a number of different countries e.g. [10, 40].

The AUDIT-C is a 3-item measure that was used to identify potentially hazardous drinking [41]. Each item is answered using five response options, with possible total scores ranging from 0 to 12 [41]. A total score of ≥3 for women, and ≥4 for men, was used to identify participants engaging in hazardous drinking. The AUDIT-C has been validated in veteran populations [42, 43].

The Social Provisions Scale (SPS) was used to examine participant perceptions of the availability of different dimensions of social support. This theory-based social support instrument includes 24 items distributed across six subscales: reliable alliance, attachment, nurturance, social integration, reassurance of worth, and guidance [44]. Each item is rated on a 4-point Likert scale with responses ranging from ‘strongly disagree’ to ‘strongly agree’ [44]. After reversal of negatively worded items a total score was computed by summing all items (range = 24–96). Higher scores (including total scores and individual subscale scores) indicate higher levels of perceived social support. The construct validity, internal consistency, and test-retest reliability of the measure has been established across diverse populations [44, 45]. Scores on the SPS have been associated with psychological outcomes in military personnel [46, 47].

To screen for insomnia disorder based on DSM-5 criteria we used the 8-item Sleep Condition Indicator (SCI) [48]. All items were scored on a four point scale (0 to 4), with possible summed scores on this measure range from 0 to 32; scores were then re-scaled to a 0 to 10 scale [48]. Higher scores are indicative of better sleep. While the SCI is a relatively new measure, it has been validated in a number of different countries in a diverse range of populations [49].

To evaluate psychological flexibility, the 10-item Acceptance and Action Questionnaire II (AAQ-II) was used [50]. Responses to each item are made on a 7-point response scale, with options ranging from ‘never true’ to ‘always true’. After reversing negatively worded items, the items of the scale were summed to obtain a total score (possible range 10 to 70), with higher scores indicative of greater psychological flexibility (less experiential avoidance) [50]. The AAQ-II has demonstrated internal construct validity in mild to moderately depressed and anxious populations [51], and scores on this measure have been identified as an important predictor of PTS among trauma-exposed military personnel [52].

The questionnaire also included a series of sociodemographic questions (gender, ethnicity, marital status, education level, employment status) and questions about service history, rank, and deployments.

Analyses

Statistical analyses were completed using Stata 15 software [53]. First, descriptive statistics were used to describe the demographic characteristics of participants. Next, exploratory analyses investigated univariate associations between demographic, hazardous and protective factors, and the PTS outcomes (PCL-M ≥30 and PCL-M ≥45), with odds ratios (ORs) and 95% confidence intervals (CIs) estimated using logistic regression. Following this, multivariable logistic regression (adjusted for age, sex, service years, and deployment status) was performed to identify exposures associated with PTS using a backward elimination process; variables with a p-value >0.10 were sequentially dropped from the model. With respect to missing data, if only one item was missing on a particular measure then this was imputed with the mean of the remaining items; if more than one item was missing then the participant was excluded from the analyses. The only exception to this was for the GHQ-12, where the standard procedure to count omitted items as low scores (0) was followed [39]. Only participants with complete data were included in the multivariable analyses.

In order to examine six risk and protective factors significantly associated with PTS (trauma exposure, distress, hazardous drinking, social support, sleep and psychological flexibility), a sample of at least 600 participants was required. These variables were chosen because they are potentially modifiable and have previously been associated with PTS in studies involving military personnel. We endeavoured to recruit as many participants as possible to maximise the generalisability of our findings.

Results

A total of 1817 military personnel completed the questionnaire; 90 of the participants completed a paper version. Among participants, 549 (30%) reported PCL-M scores of ≥30 indicating significant PTS symptomology (probable PTSD), and 179 (10%) reported PCL-M scores of ≥45, indicative of presumptive clinical PTS.

The demographic characteristics of participants categorised according to the experience of probable (scores ≥30) and clinically significant PTS (scores≥45) are presented in Table 1.

Table 1

Characteristics of participants according to PCL-M scores.

Characteristic	PCL-M Score ≥30		PCL-M Score ≥45		Total
	Low PCL-M Score 17–29 (n = 1268)	High PCL-M Score ≥30 (n = 549)	Low PCL-M Score 17–44 (n = 1638)	High PCL-M Score ≥45 (n = 179)	n = 1817
Age (years)
20–29	124 (84%)	24 (16%)	141 (95%)	7 (5%)	148 (8%)
30–39	264 (75%)	86 (25%)	335 (96%)	15 (4%)	350 (19%)
40–49	327 (71%)	134 (29%)	418 (91%)	43 (9%)	461 (25%)
50–59	247 (69%)	111 (31%)	331 (92%)	27 (8%)	358 (20%)
60–69	176 (63%)	103 (37%)	240 (86%)	39 (14%)	279 (15%)
70+	127 (59%)	89 (41%)	169 (78%)	47 (22%)	216 (12%)
missing	3 (60%)	2 (40%)	4 (80%)	1 (20%)	5 (1%)
Sex
Female	183 (77%)	54 (23%)	224 (95%)	13 (5%)	237 (13%)
Male	1065 (69%)	488 (31%)	1389 (89%)	164 (11%)	1553 (85%)
missing	20 (74%)	7 (26%)	25 (93%)	2 (7%)	27 (2%)
Ethnicity
NZ European	997 (70%)	418 (30%)	1289 (91%)	126 (9%)	1415 (78%)
Māori	177 (69%)	79 (31%)	218 (85%)	38 (15%)	256 (14%)
Other	94 (64%)	52 (36%)	131 (90%)	15 (10%)	146 (8%)
Service Years
0–9	213 (62%)	132 (38%)	290 (84%)	55 (16%)	345 (19%)
10–19	350 (70%)	153 (30%)	454 (90%)	49 (10%)	503 (28%)
20–29	390 (73%)	144 (27%)	487 (91%)	47 (9%)	534 (29%)
30–39	181 (69%)	80 (31%)	244 (93%)	17 (7%)	261 (14%)
40–49	43 (65%)	23 (35%)	57 (86%)	9 (14%)	66 (4%)
missing	91 (84%)	17 (16%)	106 (98%)	2 (2%)	108 (6%)
Deployed
No	186 (67%)	92 (33%)	245 (88%)	33 (12%)	278 (15%)
Yes	1012 (71%)	415 (29%)	1295 (91%)	132 (9%)	1427 (79%)
missing	70 (63%)	42 (37%)	98 (88%)	14 (12%)	112 (6%)
Service Status
Retired	453 (57%)	337 (43%)	650 (82%)	140 (18%)	790 (43%)
Currently Serving	805 (80%)	204 (20%)	973 (96%)	36 (4%)	1009 (56%)
missing	10 (55%)	8 (45%)	15 (83%)	3 (17%)	18 (1%)
Hazardous Drinking
No	537 (71%)	221 (29%)	677 (89%)	81 (11%)	758 (42%)
Yes	625 (70%)	273 (30%)	819 (91%)	79 (9%)	898 (49%)
missing	106 (66%)	55 (34%)	142 (88%)	19 (12%)	161 (9%)
Trauma Exposure
No	460 (87%)	68 (13%)	517 (98%)	11 (2%)	528 (29%)
Yes	743 (63%)	444 (37%)	1031 (87%)	156 (13%)	1187 (65%)
missing	65 (64%)	37 (36%)	90 (88%)	12 (12%)	102 (6%)

The median age of participants was 49.1 years (interquartile range, IQR = 38.7–61.1 years). The majority were male (87%) and were of New Zealand European ethnicity (78%); 14% of participants identified as Māori, similar to that of the NZDF as a whole, reported as 15%. Most participants had served in the military for at least 10 years (80%) and had been deployed at least once (84%). A majority of participants were currently serving (56%).

A median score of 11 was found for the 1735 participants who completed the GHQ-12 (IQR = 8–14; mean = 11.9; standard deviation, SD = 5.1), a median score of 75 was found for the 1778 participants who completed the SPS (IQR = 40–96; mean = 75.8; SD = 10.8), a median score of 54 was found for the 1734 participants who completed the AAQ-II (IQR = 46–60; mean = 52.3; SD = 10.1), and a median score of 5.6 was found for the 1711 participants who completed the SCI (IQR = 4.4–7.8; mean = 5.9, SD = 2.2).

Of the 1656 participants who completed the AUDIT-C, 898 (54%) reported hazardous drinking. Of the 1715 participants who completed the BTQ, the majority (n = 1187, 69%) had been exposed to trauma (see S1 Table). 1006 (59%) had served in a war zone and 736 (73%) of these individuals reported that this presented a threat to life and/or a threat of serious injury. The proportion of participants experiencing other traumatic events, including childhood physical and sexual abuse, was also high (35% and 16% respectively).

Univariate analyses

Results of univariate analyses describing associations between exposure variables (demographic, risk, and protective factors) and PTS are presented in Table 2, showing both the odds of experiencing symptoms of PTS (PCL-M scores ≥30) and the odds of experiencing clinically relevant PTS (scores ≥45). With respect to PTS symptomology, older age, male sex, higher distress, and exposure to trauma were significantly associated with increased likelihood of PTS symptoms. In contrast, increased number of years in service, current participation in service, social support, psychological flexibility, and sleep were significantly associated with lower odds of experiencing PTS symptoms. The same pattern of associations was also found for clinically relevant PTS, in addition to greater odds of clinical PTS among individuals identifying as Māori compared to those of NZ European ethnicity.

Table 2

Univariate associations between exposure variables and elevated PCL-M scores (≥30 and ≥45 respectively).

Characteristic	PCL-M Score ≥30							PCL-M Score ≥45
	N PCL-M Score <30	N PCL-M Score ≥30	AR	OR	95% CI for OR	p	n	N PCL-M Score <45	N PCL-M Score ≥45	AR	OR	95% CI for OR	p	n
Age (Years)*	*	*		1.02	1.01, 1.03	<0.01	1812	*	*		1.03	1.02, 1.05	<0.01	1812
Sex
Female	183	54		Ref				224	13		Ref
Male	1065	488	0.09	1.55	1.13, 2.14	0.01	1790	1389	164	0.05	2.03	1.14, 3.64	0.02	1790
Ethnicity
NZ European	997	418		Ref				1289	126		Ref
Māori	177	79	0.01	1.06	0.80, 1.42	0.67		218	38	0.06	1.78	1.21, 2.63	<0.01
Other	94	52	0.06	1.32	0.92, 1.89	0.13	1817	131	15	0.01	1.17	0.67, 2.06	0.58	1817
Service Years*	*	*		0.99	0.98, 1.00	0.03	1709	*	*		0.97	0.96, 0.99	<0.01	1709
Deployed
No	186	92		Ref				245	33		Ref
Yes	1012	415	-0.04	0.83	0.63, 1.10	0.18	1705	1295	132	-0.03	0.76	0.50, 1.13	0.18	1705
Currently Serving
No	453	337		Ref				650	140		Ref
Yes	805	204	-0.22	0.34	0.28, 0.42	<0.01	1799	973	36	-0.14	0.17	0.12, 0.25	<0.01	1799
Distress*	*	*		1.27	1.23, 1.30	<0.01	1735	*	*		1.21	1.18, 1.25	<0.01	1735
Social Support*	*	*		0.91	0.90, 0.93	<0.01	1778	*	*		0.91	0.90, 0.93	<0.01	1778
Psychological Flexibility*	*	*		0.84	0.82, 0.85	<0.01	1734	*	*		0.84	0.82, 0.86	<0.01	1734
Sleep*	*	*		0.53	0.49, 0.57	<0.01	1711	*	*		0.41	0.36, 0.46	<0.01	1711
Hazardous Drinking
No	537	221		Ref				677	81		Ref
Yes	625	273	0.01	1.06	0.86, 1.31	0.58	1656	819	79	-0.02	0.81	0.58, 1.12	0.20	1656
Trauma Exposure
No	460	68		Ref				517	11		Ref
Yes	743	444	0.25	4.04	3.05, 5.35	<0.01	1715	1031	156	0.11	7.11	3.82, 13.23	<0.01	1715

*Continuous variable (no reference group); AR = absolute risk.

Multivariate analyses

Results of multivariate analyses describing associations between exposure variables and PTS, after adjustment for age, sex, service years and deployment status, are presented in Table 3, including for odds of experiencing PTS symptomology (PCL-M scores ≥30) and for odds of clinically relevant PTS (scores ≥45). With respect to PTS symptomology, older age, male sex, higher distress, and exposure to trauma were significantly associated with an increased likelihood of PTS. Increased number of years in service, psychological flexibility, and sleep were significantly associated with decreased odds of experiencing PTS symptoms; social support was no longer significantly associated with this outcome. A single unit increase in sleep score corresponded to a 30% reduction in odds of experiencing significant PTS symptoms. The same pattern of results was found for clinically-relevant PTS, with the exception of higher distress, which was not significantly associated. In addition, Māori participants were found to have greater odds of experiencing clinically relevant PTS when compared to New Zealand Europeans.

Table 3

Multivariate associations between exposure variables and elevated PTSD (scores ≥ 30 and scores ≥ 45).

Characteristic	PCL-M Score ≥30, n = 1532					PCL-M Score ≥45, n = 1567
	N PCL-M Score <30	N PCL-M Score ≥30	OR	95% CI for OR	p	N PCL-M Score <45	N PCL-M Score ≥45	OR	95% CI for OR	p
Age (Years)*	*	*	1.02	1.01, 1.03	<0.01	*	*	1.04	1.03, 1.06	<0.01
Sex
Female	145	45	Ref			152	46	Ref
Male	915	427	1.84	1.14, 2.98	0.01	933	436	1.69	0.74, 3.86	0.21
Ethnicity	*	*
NZ European						856	367	Ref
Māori						151	71	2.80	1.54, 5.10	<0.01
Other						78	44	0.97	0.40, 2.31	0.94
Service Years*	*	*	0.98	0.97, 1.00	0.01	*	*	0.97	0.95, 0.99	<0.01
Deployed
No	162	83	Ref			166	84	Ref
Yes	898	389	1.31	0.85, 2.00	0.22	919	398	1.54	0.84, 2.81	0.16
Distress*	*	*	1.07	1.03, 1.11	<0.01
Psychological Flexibility*	*	*	0.87	0.85, 0.89	<0.01	*	*	0.87	0.85, 0.90	<0.01
Sleep*	*	*	0.70	0.64, 0.77	<0.01	*	*	0.56	0.49, 0.66	<0.01
Hazardous Drinking
No	500	212	Ref
Yes	560	261	1.11	0.96, 1.77	0.08
Trauma Exposure
No	396	61	Ref			405	62	Ref
Yes	664	411	3.03	2.07, 4.41	<0.01	680	420	3.34	1.54, 7.27	<0.01

Variables with a p-value less than 0.10 after adjustment for age, sex, service years, and deployment status are included in the model.

*Continuous variable (no reference group).

Discussion

This cross-sectional study identified a high prevalence of PTS in a large sample of currently serving and retired New Zealand military personnel. Thirty percent of participants reported experiencing probable PTS and 10% were identified as having clinically relevant PTS. These findings are similar to those reported in an earlier study, which found evidence of PTS among 10% of New Zealand Vietnam war veterans [31]. Our results indicate that it is not only retired personnel who are at risk. While substantial differences in PTS have been documented in response to different traumatic events [54], the weighted prevalence of PTS in response to war related trauma (3.5%) is similar to the weighted prevalence of PTS associated with random traumatic events (4%) [55]. This may explain why the prevalence of probable PTS found in our study is similar to that documented in other trauma population samples [35]. Our results highlight that support to deal with PTS is needed for a large number of New Zealanders who are serving, or have served, in the military.

As a consequence of the sampling methods used and the limited response rate to our survey, findings can provide only a rough estimate of the prevalence of PTS. Nevertheless, they suggest that the prevalence of clinically significant PTS is higher among military personnel compared with the general population of New Zealand, where the prevalence is estimated to be 3% [56]. The finding that 10% of participants reported symptoms indicative of a clinical diagnosis of PTSD is in line with point prevalence estimates of combat-related PTSD in US military veterans, ranging from approximately 2% to 17% [6]. Summary estimates of PTSD prevalence for military personnel and veterans from a number of countries range from 1.1% to 34.8% [14]. The prevalence of PTS identified in our study is higher than that documented among UK military personnel [15], although this may be attributable to variation in sampling strategies and data collection methods used. Participants in the UK study were individually invited to participate in an online survey via postal invitation, with non-responders sent a repeat invitation and subsequent postal questionnaire [15]. In addition, there was an intensive period of follow-up and tracing of non-responders. Differences in PTS estimates may also be due to variation in socio-political and cultural factors that vary across nations [6].

Trauma exposure was most strongly associated with odds of experiencing PTS symptomology and clinically relevant PTS in the present study, and is a prerequisite for a DSM IV diagnosis of PTSD. General distress was significantly associated with increased odds of PTS symptoms, although was not significantly associated with odds of clinical PTS after adjustment for age, sex, service years, and deployment status. This is consistent with findings from a meta-analysis of risk factors for combat-related PTS among military personnel and veterans, which did not identify general distress to be a significant risk factor, although a history of prior psychological problems and trauma exposure were [14].

Māori participants had greater odds of reporting clinical PTS than their New Zealand European counterparts. Higher levels of PTS among Māori were also detected in a sample of 756 New Zealand Vietnam War veterans, however, the effect of ethnicity on PTS was mediated by higher levels of combat stressors experienced by Māori, including stressors related to combat exposure, rank, and combat role [57].

Consistent with findings of a study examining predictors of persistent PTS in UK military personnel [58], older age was significantly associated with increased odds of experiencing PTS. However, in contrast to other studies examining PTS in military personnel, males were at greater risk of experiencing PTS than females. It is important to note that other studies identifying females to be at greater risk of PTS have focused on combat-related PTS [14], and our sample includes personnel who never deployed. A 2014 NZDF report noted that only 6% of officers in combat/operations were women [59]. Therefore, greater exposure to combat-related trauma among male military personnel in New Zealand may explain why they reported more PTS symptoms than female personnel.

Despite older age being associated with increased odds of PTS, a greater number of service years was associated with reduced odds of PTS. Rather than this reflecting a causal role of service duration in relation to PTS, this may reflect a resilience that develops over time among long-serving personnel, or may be due to individuals with PTS leaving military service earlier as has been reported among UK Armed Forces Personnel [60].

Better self-reported sleep was also associated with fewer PTS symptoms among military personnel in our sample. Sleep-related problems have been identified as the most frequently endorsed PTS symptom, occurring in 60–90% of people with the disorder [61]. Sleep disturbance is highly prevalent among military personnel. In a sample of 80 personnel who had recently returned from combat, 74% reported insomnia and 61% experienced distressing nightmares [62]. Sleep disturbance was associated with higher PTS and depression severity scores and these associations persisted over a six month period [62]. While PTS and depression decreased in the sample over time, insomnia remained prevalent. Therefore, the bidirectional relationship between sleep disturbance and PTS may be perpetuated by poor sleep exacerbating other symptoms of PTS and diminishing the capacity of military personnel to manage these.

There is preliminary evidence to indicate that early intervention among military personnel experiencing sleep disturbance may help to reduce PTS symptoms. An investigation of 44 military personnel who received cognitive behavioural therapy for insomnia found that participants who experienced improved sleep quality from pre- to post-treatment (n = 28) had significant declines in depression and PTS symptoms [23]. In contrast, those whose sleep did not improve had no changes in their psychiatric symptoms, as well as a reduction in health-related quality of life.

In the present study, psychological flexibility was associated with reduced odds of reporting PTS. However, it is important to interpret our findings with caution as there have been criticisms of the AAQ-II, with several researchers arguing that it may be measuring psychological distress rather than psychological inflexibility [63]. Furthermore, numerous versions of the AAQ-II exist which can make it difficult to compare findings across studies. Despite few studies examining psychological flexibility among military personnel, techniques designed to increase psychological flexibility (such as acceptance and commitment therapy) are being investigated as potential treatments for PTS in this population [64-66], and evidence for their effectiveness is emerging [67].

Strengths of this study include the large sample, and the inclusion of those who have never been deployed. Our study also serves to provide a snapshot of New Zealand military personnel, for which the total number of those who have served and are alive is unknown. We do however know that the invitation was specifically sent to 3874 NZDF members who were ‘currently serving’ veterans with access to the military system in June 2018, and that the majority of responses were received in the following few weeks. Although the number of individuals in the sample who had never been deployed was small, our findings suggest that these individuals are also at risk of PTS. Evidence that personnel who have never deployed are at greater risk of PTS than the general population is growing [10, 68]. It is clear that factors other than deployment have an important role to play in the experience of PTS among military personnel.

It is also important to acknowledge the limitations associated with this study. At the time the questionnaire was distributed there were 14770 currently serving personnel in the NZDF, of whom 9354 were regular personnel, 2420 were reservists and 2996 were civilians. Very few reservists will have received the email invitation to participate: access to the secure email system through which the link to the study was distributed is extremely limited unless in a ‘command’ role. The majority of questionnaires were completed by currently serving personnel, indicating a response rate in the order of 19% when excluding both reservists and civilians. This response rate and the large proportion of currently serving personnel in our sample gives rise to potential sampling bias. Results may not be generalisable to all New Zealand military personnel, particularly those who are no longer serving. It is also important to note that military personnel with higher PTS may have been more likely to participate, giving rise to inflated estimates of PTS prevalence. Conversely, our findings may underestimate the prevalence of PTS in this population if those without PTS were more inclined to participate.

The response rate to this study was low relative to other studies conducted with military personnel which is likely attributable to the recruitment method used. In contrast to studies that recruited directly from veteran-specific treatment programs [69, 70], we did not approach participants directly. Other studies have targeted pre-defined populations (e.g. US Gulf veterans) for which information on the approximate number of personnel is available, in addition to opportunities for direct contact e.g. [71]. It is possible that New Zealand military personnel were not exposed to study advertisements and were therefore unaware that the study was taking place; this is particularly true of retired military personnel who were not emailed about the study.

Information on the way in which participants were recruited (for example, from an email invitation or alternative study advertisement) was not collected. This precluded sensitivity analyses comparing estimates with respect to the different sampling strategies used. With respect to missing data, complete case analyses was used as the assumptions necessary for multiple imputation were not met by the missing data within our sample. Another limitation of the study is the cross-sectional design which precludes the identification of cause and effect relationships between exposures and PTS. Additionally, although we assessed and accounted for a range of known confounders, it is possible some important confounders were not considered and that these may explain significant relationships between exposures and PTS.

It is unclear how generalisable the study findings are to countries outside of New Zealand, where the characteristics of military personnel, deployment experiences, and post-deployment support services are likely to differ [16]. Nevertheless, health support for military personnel in New Zealand follows that provided by American, Canadian, British, and Australian Defence Forces.

Conclusions

Knowledge of the risk and protective factors associated with PTS may allow for early identification of military personnel who would benefit from targeted support to promote their wellbeing. Our findings suggest that trauma exposure is most strongly associated with high levels of PTS, while good sleep and psychological flexibility are protective. As these protective factors are amenable to standardised measurement and modification, screening could facilitate early intervention to prevent or reduce PTS. Future research is needed to identify whether relationships in our study can be found longitudinally. This would establish the sequence of events (for example, whether changes in sleep are associated with subsequent changes in PTS), providing further evidence regarding New Zealand military personnel most at risk of experiencing PTS.

Participant responses to the Brief Trauma Questionnaire (BTQ), (N = 1817).

(DOCX)

Click here for additional data file.

22 Oct 2019

PONE-D-19-23666

Post-Traumatic Stress among New Zealand military personnel: a cross sectional study

PLOS ONE

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Reviewer #1: 1. The original sample and response rates are unclear. I suggest including a breakdown of how many people were invited to take part in the study. If people were not invited directly it should be made clear how the survey was made available or accessed (e.g. hosted on a website). While the number of people in the study is perhaps reasonable (1817) it is difficult to ascertain the response rate. Please provide the number of currently serving personnel, the number of current reserves, and the number of retired personnel. This way you can give good estimates of the response rate by group. e.g. are retired personnel underrepresented? Also in Table 1, provide information on the number of currently serving, reserve and retired.

2. Table 2 is not mentioned in the text and so currently serves little purpose. Perhaps these statistics could be mentioned in the text instead (and the table removed).

3. Table 4 is confusing because a number of variables with a p-value >0.1 are included in the table which seems to contradict the footnote (e.g. deployed, Female in the >=45 column).

4. Discussion. Why were reservists unlikely to receive the email invitation? More information about the recruitment methods are required to increase reader confidence in how the study was undertaken.

Reviewer #2: This paper explores the prevalence of and risk factors associated with post traumatic stress (PTS) in the New Zealand military. The survey was based on 1817 military personnel and reports a prevalence of PTS of 10%-30% depending on the cut-off used. The authors report on the factors associated with PTS and suggest factors that could be targeted to reduce PTS within military personnel.

The health and wellbeing of military and veteran personnel is receiving much attention internationally and this is one of the first studies emerging from New Zealand.

My main concern is regarding the methodology employed, this needs to be more clearly articulated in the paper. For example, further details of the size of the population approached (number of serving personnel, reserves and veterans), recruitment methods used and exclusion criteria applied are required. What attempts were made to ensure all currently serving and veteran personnel were given the opportunity to participate? This level of detail is needed to enable to reader to determine the possible presence of response bias and the generalisability of the results. Further details are required in the methods and the subsequent limitations and implications more clearly addressed in the discussion.

Introduction:

- the authors state that military personnel are at greater risk of PTS than the general populatlion. This is not the case in all nations and this should be recognised by the authors.

- please define the term veteran and be conscious that term is used differently across nations and studies.

- a limited number of references are provided to support the statements made, please ensure a broad range of references are included (where appropriate).

Procedure:

- this details the approach used for currently serving personnel, what about veterans?

- please clarify the sample size included and what is meant by cases? Should this be participants? If it is cases then the study is underpowered as less than 600 cases were identified. What are the implications of this for the analyses conducted and conclusions drawn?

Measures:

- need to consistently report details of all measures used, for example, range, response options and validity within the population under study.

Analyses:

- the authors state that missing data were dealt with using "developer recommendations", details need to be provided of what these recommendation are for each measure.

- only participants with complete data were included in the multivariable analysis, please state number and % of total sample.

- further justification for using two cut-offs for the PCL need to be provided. Why are two cut-offs being used? Could the authors focus on one cut-off for the paper with the other results being provided as supplementary material?

- has the analytical approach applied been discussed with a statistican?

Results:

- given the existing interest in differences between serving and ex-service personnel, all analyses should take serving status into account.

Table 1:

- need to report the overall numbers and %'s for each characteristic

- why are row and not column %'s reported?

Table 3:

- need to include numbers and %'s for each characteristic by PCL score (including those in the baseline category)

- a number of variables appear in this table which should be included in Tables 1 or 2, for example, hazardous drinking and trauma exposure

Discussion:

- how do the prevalence estimates reported within the military population compare with the general population of New Zealand?

Conclusion:

- please justify the statement regarding longitudinal data and how that will help identify those most at risk of PTS

Data availability:

- the authors state that the full data won't be made available and that some restrictions will apply. Could they clarify what will be made available and what restrictions will be in place?

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Reviewer #1: Yes: Dr Michael Waller

Reviewer #2: No

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Submitted filename: PONE-D-19-23666_Editor comments.pdf

Click here for additional data file.

19 Dec 2019

Response

We would like to thank the reviewers and academic editor for their considered comments on our manuscript. These comments are addressed below. Changes to the manuscript have been made using track changes.

Reviewer One Comments:

1. The original sample and response rates are unclear. I suggest including a breakdown of how many people were invited to take part in the study. If people were not invited directly it should be made clear how the survey was made available or accessed (e.g. hosted on a website). While the number of people in the study is perhaps reasonable (1817) it is difficult to ascertain the response rate. Please provide the number of currently serving personnel, the number of current reserves, and the number of retired personnel. This way you can give good estimates of the response rate by group. e.g. are retired personnel underrepresented? Also in Table 1, provide information on the number of currently serving, reserve and retired.

A number of different approaches were used to invite people to take part in the study. However, the strategies used differed for currently serving and retired personnel. These strategies have now been clarified in the methods section of the manuscript (see page 5, paragraph 3; page 6, paragraph 1 and 3).

An invitation and link to the online questionnaire were emailed to all currently serving military personnel and reservists in mid-June 2018. However, a different approach was used to invite retired personnel who were recruited through study posters distributed to the largest branches of the Royal New Zealand Returned and Services Association (RSA) and through announcements on social media. The posters and announcements contained a link to a study website where individuals could enter their name and email address. This resulted in a personalised link being sent to their email address from which they could complete an online secure version of the questionnaire.

We have now described the number of currently serving and the number of retired personnel in our sample (see page 12, paragraph 1), as well as best possible estimates of the number of these personnel in the New Zealand population (see page 5, paragraph 2). Information on the number of currently serving personnel as of June 2018 was provided by the New Zealand Defence Force (NZDF). However, it is unclear how many living retired personnel there were in New Zealand at the time of our survey. Since the end of World War II, 76,000 operational service medals have been awarded but many of these may have been awarded posthumously.

The number of currently serving personnel and the number of retired personnel who participated in the study is now reported in Table 1.

2. Table 2 is not mentioned in the text and so currently serves little purpose. Perhaps these statistics could be mentioned in the text instead (and the table removed).

The results presented in Table 2 are now reported in text (see page 12, paragraph 2).

3. Table 4 is confusing because a number of variables with a p-value >0.1 are included in the table which seems to contradict the footnote (e.g. deployed, Female in the >=45 column).

The footnote notes that the analysis has been adjusted for age, sex, service years, and deployment status. This means that these 4 variables were retained in the model irrespective of their p-values.

4. Discussion. Why were reservists unlikely to receive the email invitation? More information about the recruitment methods are required to increase reader confidence in how the study was undertaken.

Very few reservists will have received the email invitation as access to the secure email system through which the questionnaire was distributed is extremely limited unless in a ‘command’ role. The majority of reservists cannot access the secure system. This is now noted in the discussion (see page 21, paragraph 3) and more information about recruitment methods is now provided in the methods section of the manuscript (see page 5, paragraph 3; page 6, paragraph 1 and 3).

Reviewer Two Comments:

My main concern is regarding the methodology employed, this needs to be more clearly articulated in the paper. For example, further details of the size of the population approached (number of serving personnel, reserves and veterans), recruitment methods used and exclusion criteria applied are required. What attempts were made to ensure all currently serving and veteran personnel were given the opportunity to participate? This level of detail is needed to enable to reader to determine the possible presence of response bias and the generalisability of the results. Further details are required in the methods and the subsequent limitations and implications more clearly addressed in the discussion.

Please see response to reviewer one, comment one.

With respect to inclusion criteria, all military personnel residing in New Zealand were eligible to participate in the study. With respect to exclusion criteria, individuals who had not served in the Armed Forces were excluded, such as members of the national police force and Fire and Emergency New Zealand volunteers and staff. This information has been added to the methods section (see page 5, paragraph 2).

The limitations associated with our study design, and the implications of this for the generalisability of findings, have now been elaborated on in the discussion of the manuscript (see page 21, paragraph 3; page 22, paragraph 1, 2, 3).

Introduction:

- The authors state that military personnel are at greater risk of PTS than the general population. This is not the case in all nations and this should be recognised by the authors.

We thank the reviewer for bringing this to our attention. This statement has been modified to acknowledge that military personnel can be at greater risk of PTS (see page 3, paragraph 1).

- Please define the term veteran and be conscious that term is used differently across nations and studies.

Given the variation in the term veteran across nations and studies we endeavoured to consistently use the slightly broader term ‘military personnel’ throughout our manuscript. The different types of military personnel in New Zealand are described at the beginning of the introduction (see page 3, paragraph 1). We have also added a description of how we defined military personnel in our study to the beginning of the methods section (see page 5, paragraph 2).

- A limited number of references are provided to support the statements made, please ensure a broad range of references are included (where appropriate).

Additional references have now been added to the introduction section.

Procedure:

- This details the approach used for currently serving personnel, what about veterans?

Please see response to Reviewer One, Comment One.

- Please clarify the sample size included and what is meant by cases? Should this be participants? If it is cases then the study is underpowered as less than 600 cases were identified. What are the implications of this for the analyses conducted and conclusions drawn?

We apologise for the confusion caused by the statement about cases. This statement was intended to identify the minimum number of participants that would be required to examine six risk and protective factors in multivariable models. The sentence has been rewritten and moved to the analyses section of the methods (see page 10, paragraph 2). The total number of participants included in the multivariable analyses is presented in the top row of Table 4 (1532 participants when examining factors associated with scores ≥30 and 1567 when examining factors associated with scores ≥45).

Measures:

- Need to consistently report details of all measures used, for example, range, response options and validity within the population under study.

An effort has been made to ensure that details of all measures are now reported consistently, including the response options for each measure, the possible range of total scores, and the validity of the measure within military personnel (see page 7, paragraph 4; page 8, paragraph 1, 2; page 9, paragraph 1, 2, 3).

Analyses:

- The authors state that missing data were dealt with using "developer recommendations", details need to be provided of what these recommendation are for each measure.

With respect to missing data, if only one item was missing on a particular measure then this was imputed with the mean of the remaining items; if more than one item was missing then the participant was excluded from the analyses. The only exception to this was for the GHQ-12, where the standard procedure to count omitted items as low scores (0) was followed. This information is now reported in the analyses section (see page 10, paragraph 1).

- Only participants with complete data were included in the multivariable analysis, please state number and % of total sample.

The number of participants included in the multivariable analyses is presented at the top of Table 4 (n = 1532 for analyses exploring PCL-M Score ≥30 and n = 1567 for analyses exploring PCL-M Score ≥45). Numbers can be used by readers to calculate the percentage of the total sample (84% and 86% respectively).

- Further justification for using two cut-offs for the PCL need to be provided. Why are two cut-offs being used? Could the authors focus on one cut-off for the paper with the other results being provided as supplementary material?

The two cut-offs were used to provide readers with information on the proportion of participants reporting PTS symptomology and the proportion of participants likely to meet clinical criteria for a PTSD diagnosis. Both are important to know about as the different cut-offs can be used for different purposes (e.g. clinical rather than population objectives). This, in turn, will alter the way in which findings are considered. In populations with high PTS prevalence (such as trauma-exposed populations), cut-off values of 44 or higher will likely underestimate prevalence. Therefore, if an aim is to use the PCL-M as a clinical detection tool, a low cut-off value may be preferable to use. A justification for our presentation of findings in relation to both cut-offs is now provided (see page 7, paragraph 4).

- Has the analytical approach applied been discussed with a statistician?

Yes. Author Ari Samaranayaka is a biostatistician who was responsible for conducting the analyses reported in the manuscript.

Results:

- Given the existing interest in differences between serving and ex-service personnel, all analyses should take serving status into account.

Our current multivariable analyses adjust for factors with a previously demonstrated relationship with PTS among military personnel, that is, age, sex, service years, and deployment status.

References:

- Owens GP, Steger MF, Whitesell AA, Herrera CJ. Posttraumatic stress disorder, guilt, depression, and meaning in life among military veterans. Journal of Traumatic Stress. 2009;22(6):654-7.

- Xue C, Ge Y, Tang B, Liu Y, Kang P, Wang M, Zhang L. A meta-analysis of risk factors for combat-related PTSD among military personnel and veterans. PloS One;10(3):e0120270.

Table 1:

- Need to report the overall numbers and %'s for each characteristic

The number for each overall characteristic is the same as that reported in the column heading.

- Why are row and not column %'s reported?

Column percentages describe the distribution of each PCL-M group across categories of a characteristic. Row percentages compare the presence of PTS within each category of a characteristic. Which of these is more important (or easier to interpret) is dependent on personal preference. We used row percentages because they compare PTS within groups, which is consistent with what our main analysis method (i.e., logistic regression).

Table 3:

- Need to include numbers and %'s for each characteristic by PCL score (including those in the baseline category)

- A number of variables appear in this table which should be included in Tables 1 or 2, for example, hazardous drinking and trauma exposure

Numbers and percentages for each characteristic by PCL score are now provided in Table 1, including for categorical exposures (hazardous drinking and trauma exposure).

Discussion:

- How do the prevalence estimates reported within the military population compare with the general population of New Zealand?

The prevalence estimates among the military personnel in our sample are significantly higher than those detected among the general New Zealand population. This information is now reported in the discussion (see page 18, paragraph 1).

Conclusion:

- Please justify the statement regarding longitudinal data and how that will help identify those most at risk of PTS

Longitudinal research can be conducted to detect developments or changes in the characteristics of a target population over time. As a result, this type of research can be used to establish sequences of events (for example, whether changes in sleep precede changes in PTS). The utility of future longitudinal research has now been clarified in the discussion (see page 23, paragraph 1).

Data Availability:

- The authors state that the full data won't be made available and that some restrictions will apply. Could they clarify what will be made available and what restrictions will be in place?

Our ethics approval does not allow us to share person level data, but summary data can be made available upon request to the corresponding author.

Editorial Requests:

Abstract

Interesting that this (PCL-M ≥30) is not much higher than other trauma population samples - worth discussing in the body of the paper?

Prior research has found that while substantial differences in PTS exist in response to different traumatic events, the weighted prevalence of PTS in response to war related trauma (3.5%) is similar to the weighted prevalence of PTS associated with random traumatic events (4%). This may explain why the prevalence of PTS symptomology found in our study is similar to that documented in other trauma population samples. The discussion has been updated to reflect this (see page 17, paragraph 1).

Exposure to trauma - Isn't this obvious that it would be associated? Could be better to focus on other novel findings in the abstract?

The sentence in the abstract reporting on the association between exposure to trauma and PTSD scores has now been removed in order to focus specifically on the novel findings of the study.

Relationship between sleep and PTSD scores - Likely to be bi-directionally related to PTSD, though, given the prevalence and significance of sleep-related symptoms/problems in PTSD

We agree with the editor that the relationship between sleep and PTSD scores is likely to be bidirectional. This bidirectional relationship is now given attention in the discussion section of the manuscript (see page 20, paragraph 2).

Introduction:

Please report the actual prevalence from these studies.

The actual prevalence of PTS found in the international studies described is now reported (see page 3, paragraph 3).

Fix wording/punctuation here.

The wording of this sentence has now been modified (see page 4, paragraph 1).

Is there a reason to believe these would differ from other veteran samples?

There is reason to believe that risk and protective factors associated with PTS in this sample could differ from those identified in other populations because of the significant contextual variation that exists across countries. For example, the United States has a Veterans Health Administration that provides comprehensive and integrated healthcare specifically tailored to meet the unique needs of military personnel whereas such a system does not exist in New Zealand. This is now noted in the introduction (see page 4, paragraph 3).

Prevalence of PTS - Not really likely to be achieved given the sampling techniques used (i.e., they're not likely to be representative of the target population).

We agree that the prevalence of PTS for all military personnel cannot be determined from our study due to the potential for sampling bias. We have modified this aim to read: ‘to determine the prevalence of PTS in a large sample of New Zealand military personnel’ (see page 5, paragraph 1).

Methods:

Please explicitly state the inclusion and exclusion criteria.

All military personnel residing in New Zealand were eligible to participate in the study. With respect to exclusion criteria, individuals who had not served in the Armed Forces were excluded, such as members of the national police force and Fire and Emergency New Zealand staff and firefighters (see page 5, paragraph 2).

This is not a sufficient description of how biases were minimised. Please provide details on how the study was described to participants, what benefit they received from participating (if any) etc.

The methods section has now been updated to include more detail with respect to study procedures and the benefits associated with participation (see page 6, paragraph 2).

How was the study described in the advertisements? It is likely to result in responder bias if it references PTSD prevalence etc.

A description of the content in study advertisements is now provided (see page 6, paragraph 2). It has also been made explicit that PTS was not mentioned in these advertisements, minimising the likelihood of responder bias.

How did the authors choose six variables? Was this also a sufficient rationale for identifying the "prevalence" of PTS?

We have endeavoured to make it clear that 600 participants would be necessary to identify significant associations between risk and protective factors and PTS in our sample. These variables were chosen by reviewing potentially modifiable factors that had been identified in earlier studies (those of which are described in the introduction of our manuscript). This information has now been included in the analyses section of the manuscript (see page 10, paragraph 2). As the Editor has identified, it is not possible to determine the prevalence of PTS for all New Zealand military personnel as a consequence of our study design. We have addressed this by re-wording our objectives (see page 4, paragraph 3; page 5, paragraph 1).

PCL-M - Please state that this is the version of the tool that measures symptoms consistent with the DSM-IV diagnostic criteria.

It is now stated that the PCL-M is a self-report measure reflecting DSM-IV symptoms of PTS (see page 7, paragraph 4).

Analyses:

RE: STROBE points 12d and 12e: sensitivity analyses should compare the estimates with respect to the sampling strategies (i.e., compare those from the whole sample with those recruited via the email advertisement or other advertisements). If the recruitment source was not recorded, the lack of sensitivity tests must be included in the discussion of limitations.

If these data were recorded you could use the suest command in stata to do these sensitivity tests.

Although we advertised the study in multiple ways, we cannot identify which participants responded to different types of advertisements as this information was not collected. Therefore, sensitivity tests were not conducted which is a limitation associated with the study. This is now noted in the discussion of limitations as recommended by the editor (see page 22, paragraph 2). We did collect information on whether participants completed an online or paper version of the questionnaire. Only a small number of participants (~4%) used a paper version and therefore we did not carry out a sensitivity analysis with respect to this.

Backward elimination process - Was this done manually?

The stepwise procedure was performed with Stata software. A manual elimination process would have produced the same results.

Complete case analyses - Please justify this decision. Is it because the total number of cases with missing data was small? Why not use multiple imputation?

Biostatisticians do not consider multiple imputation (MI) to be an approach that can be used indiscriminately. The success of this approach is dependent on a number of assumptions, including the “missing at random” assumption, the ability of non-missing variables to predict missing variables, etc. Complete case analysis (i.e. the simplest approach to missing data) is appropriate if the amount of missing data is small. We had a moderate amount of missing data (approximately 15%). Therefore, there is some potential for bias associated with our complete case analysis, which is now acknowledged in the limitations section of the discussion (see page 22, paragraph 2).

Results:

The letter to the editor references a "good response rate", but how was this determined given the recruitment strategies? Some effort to compare the demographic characteristics of the included sample with the total NZ military population would be useful to understand the representativeness of the cohort.

Information on the potential response rate has been updated in the discussion section of the manuscript (see page 21, paragraph 3). We have attempted to describe the distribution of the currently serving New Zealand military population to the best of our ability with the information that we have available. We have also acknowledged that we cannot compare the characteristics of retired military personnel in our sample with those of all retired military personnel in New Zealand as the number of individuals that make up this population is currently unknown (see page 21, paragraph 2).

Table 2 could more succinctly be reported in text.

The results presented in Table 2 are now reported in text (see page 12, paragraph 2).

Tables 3 and 4 - Report absolute risk and the actual N, % with the outcome from participants included in each analysis. Why do a logistic regression? Did you consider ordinal regression where participants were classified as 0 = no clinically elevated symptoms, 1 = clinically elevated symptoms (30-44) and clinically significant symptoms (45+).

Table 3 presents univariate results and now includes the actual N for each categorical exposure variable as well as absolute risks. Table 4 now reports the actual N associated with categorical exposures. Percentages are not included in the tables as these can be calculated using the Ns provided to suit the preferences of individual readers (i.e. for row or column percentages).

Although the use of ordinal logistic regression is attractive because it requires only one model as opposed to two logistic models, it can be used only under the assumption of proportionality. Unfortunately our data did not adhere to this assumption.

Male sex finding - Interesting given that women typically have higher risk. Do you think that this could be an artefact of the sample, and that a higher proportion of men were exposed to trauma?

A 2014 NZDF report noted that only 6% of officers in combat/operations were women. Therefore, greater exposure to combat-related trauma among male military personnel in New Zealand may explain why they reported more PTS symptoms than female personnel. This information has been added to the discussion of the manuscript (see page 19, paragraph 3).

Years in service finding - Discuss the potential that people with significant PTSD symptoms have shorter duration of service, and it is not the duration of service that plays a causal role in PTSS severity.

The discussion currently notes that the association between a greater number of service years and reduced odds of PTS may be due to individuals with PTS leaving military service earlier. A sentence has been added to emphasise that it is not the duration of service that plays a causal role in PTS severity (see page 19, paragraph 4).

Discussion:

Generally you should place the limitations and generalisability towards the end of the discussion - perhaps noting some of the key factors early (e.g., that the study can only provide a rough estimate of the prevalence of PTS given the sampling methods and response rate).

The description of limitations and generalisability of findings is now placed towards the end of the discussion, with only key factors mentioned by the editor identified at the beginning (see page 18, paragraph 1).

Small response rate compared to other studies - This seems to be pretty small compared to other cohorts - discuss?

The response rate to this study was low relative to other studies conducted with military personnel which is likely attributable to the recruitment method used. In contrast to studies that recruited directly from veteran-specific treatment programs, we did not approach participants directly. Other studies have targeted pre-defined populations (e.g. US Gulf veterans) for which information on the approximate number of personnel is available, in addition to opportunities for direct contact. It is possible that New Zealand military personnel were not exposed to study advertisements and were therefore unaware that the study was taking place; this is particularly true of retired military personnel who were not emailed about the study.

This information, along with appropriate references, is now provided in the discussion (see page 22, paragraph 1).

Comparison with UK military personnel - Explicitly name the variations here?

In contrast to our study, participants in the UK study were approached directly through an invitation pack, participated in clinical telephone interviews, and received a cheque or supermarket voucher to compensate them for their time (see page 18, paragraph 1).

Further discuss why you think males had higher risk.

This is now further discussed (see page 19, paragraph 3).

Please discuss sleep with respect to mechanisms of PTSD and sleep-related PTSD symptoms. Emphasise the correlational nature of the association, and that a causal relationship cannot be assumed.

We have now described the bidirectional relationship between PTSD and sleep problems in the discussion of the manuscript (see page 20, paragraph 2). We have also acknowledged that sleep related problems are a common symptom of PTS and emphasised the correlational nature of the association found in our study.

Given that the trauma exposure could be from within military service or outside of service it would be good to see these types of trauma exposures were analysed separately.

The different types of trauma exposures experienced by participants was examined. Information on the number of participants who had served in a war zone and experienced childhood physical and sexual abuse is presented in the text (page 12, paragraph 3). Information on the proportion of participants experiencing all traumatic exposures is now also provided in the appendix.

We would like to thank the reviewers and academic editor once more for their comments. We hope that with the specified changes the manuscript is now acceptable for publication.

Submitted filename: Response to reviewers - PLOS ONE.docx

Click here for additional data file.

10 Feb 2020

PONE-D-19-23666R1

Risk and protective factors for post-traumatic stress among New Zealand military personnel: a cross sectional study

PLOS ONE

Dear Dr. McBride,

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To address the comments raised by Reviewer 2, please do add a column into Table 1 that shows the number (%) of people in the total sample belonging to each of the variable levels, and consider adding the variable "serving status" into Table 2 to demonstrate whether this factor is related to PTSD symptoms. If you choose not to include it in the multivariable analysis (e.g., due to multi-collinearity) then please explain that in your response.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: No

Reviewer #2: No

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Reviewer #2: Yes

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Reviewer #1: Comments have been addressed.

I do not think that the original or underlying datasets have been made available. So clarification regarding the methods of data access may be needed in line with the PLOS One policy.

The standard of English is good.

Reviewer #2: Thank for revising the manuscript based on the reviewers and editorial comments. The paper has been greatly improved. However, there are a couple of outstanding comments that require further consideration. I have detailed these below:

- An overall description of the study population is still absent. It is usual to have a "Table 1" which describes the characteristics of those included, an additional column could be added to the current Table 1.

- Given the existing interest in differences between serving and ex-service personnel, all analyses should take serving status into account. The authors state that "Our current multivariable analyses adjust for factors with a previously demonstrated relationship with PTS among military personnel, that is, age, sex, service years, and deployment status." But serving status has also been previously associated with PTS and thus should be taken into account in the analyses.

- Please ensure the references cited are up to date. The UK references used are old and more recent (and relevant) references are available. This is essential for the statements made regarding comparisons with UK studies.

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Reviewer #1: Yes: Dr Michael Waller

Reviewer #2: No

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2 Mar 2020

We would like to thank the reviewers and academic editor for their considered comments on our manuscript. These comments are addressed below. Changes to the manuscript have been made using track changes.

Reviewer Two Comments:

An overall description of the study population is still absent. It is usual to have a "Table 1" which describes the characteristics of those included, an additional column could be added to the current Table 1.

Thank you for this recommendation. Characteristics of the total sample are now presented in an additional column in Table 1.

Given the existing interest in differences between serving and ex-service personnel, all analyses should take serving status into account. The authors state that "Our current multivariable analyses adjust for factors with a previously demonstrated relationship with PTS among military personnel, that is, age, sex, service years, and deployment status." But serving status has also been previously associated with PTS and thus should be taken into account in the analyses.

We thank the reviewer for alerting us to recent research demonstrating relationships between serving status and PTS. This research suggests that deployment and related stressors (such as having a combat role) may have different associations with PTS among currently serving and ex-serving personnel (Stevelink et al., 2018). However, the research has focused specifically on personnel who have deployed and is therefore based on participants who have been exposed to the stressors of deployment at some point in time (which may include combat exposure, discharging a weapon, witnessing someone being wounded or killed, and severe trauma). Our study was interested in examining predictive factors among all military personnel in New Zealand, including those who had never deployed.

Stevelink SA, Jones M, Hull L, Pernet D, MacCrimmon S, Goodwin L, MacManus D, Murphy D, Jones N, Greenberg N, Rona RJ. Mental health outcomes at the end of the British involvement in the Iraq and Afghanistan conflicts: a cohort study. The British Journal of Psychiatry. 2018;213(6):690-7.

Please ensure the references cited are up to date. The UK references used are old and more recent (and relevant) references are available. This is essential for the statements made regarding comparisons with UK studies.

Thank you for bringing this to our attention. A more recent reference for a widely cited study with a larger and more representative sample of UK military personnel has now been used throughout the manuscript.

Editorial Requests:

To address the comments raised by Reviewer 2, please do add a column into Table 1 that shows the number (%) of people in the total sample belonging to each of the variable levels.

Please see response to Reviewer 2, comment one.

Consider adding the variable "serving status" into Table 2 to demonstrate whether this factor is related to PTSD symptoms. If you choose not to include it in the multivariable analysis (e.g., due to multi-collinearity) then please explain that in your response.

Please see response to Reviewer 2, comment two.

We would like to thank the reviewers and academic editor once more for their comments. We hope that with the specified changes the manuscript is now acceptable for publication.

25 Mar 2020

Risk and protective factors for post-traumatic stress among New Zealand military personnel: a cross sectional study

PONE-D-19-23666R2

Dear Dr. McBride,

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Additional Editor Comments (optional):

Reviewers' comments:

1 Apr 2020

PONE-D-19-23666R2

Risk and protective factors for post-traumatic stress among New Zealand military personnel: a cross sectional study

Dear Dr. McBride:

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