Financial hardship, positive financial behaviour, and behavioural health outcomes among U.S. soldiers

Abstract

Introduction:

Financial well-being is an ongoing concern among military personnel, and more research is needed to understand the implications of both financial hardship and positive financial behaviours on behavioural health and well-being.

Methods:

Using a sample of active duty U.S. Army personnel (N = 850), the authors estimated the prevalence of self-reported past-year financial hardships and positive financial behaviors and examined the relationship of these factors with behavioural health.

Results:

At least one financial hardship was reported by 31% of participants, whereas 74% engaged in at least one positive financial behaviour. Junior enlisted personnel and personnel with lower income, less education, and larger families reported more financial hardship and fewer positive behaviours. Adjusted multivariate logistic regression analyses indicated that financial hardship was associated with posttraumatic stress disorder, depression, anxiety, fewer sleep hours, insomnia, and self-rated health, but not alcohol misuse. Following a budget was associated with lower alcohol misuse, but there were no other significant relationships between positive financial behaviors and the outcomes.

Discussion:

This study demonstrates that financial hardship is a risk factor for behavioural health problems among military personnel. Findings illustrate the need to evaluate existing military financial literacy and support programs and regulations intended to improve financial well-being or prevent poor financial decision-making. Future research should contemplate fine-tuned measurement strategies and the role of individual differences in these relationships of interest.

Lay Summary

Financial hardship, such as difficulty paying for expenses or having to borrow money from family and friends to pay for needs, is of concern for several reasons, including how it affects mental and physical health. The authors wanted to provide more detailed information on which aspects of health it affects and were also curious about whether positive financial behaviors affected the health of military personnel. This study found that service members who reported more financial hardship also reported higher levels of depression, anxiety, posttraumatic stress disorder, insomnia, and physical aggression, poorer general health, and less sleep. However, positive financial behaviors had little effect on any of the health outcomes. Findings suggest that focusing on reducing financial hardship will be more effective in improving mental health than encouraging positive financial behaviors. This research has implications for the ongoing military efforts to improve financial literacy and reduce financial hardship.

Introduction

In yearly studies conducted since 2007, the American Psychological Association has shown that Americans report money issues as a top source of stress.¹ The COVID-19 pandemic intensified these concerns, because many individuals struggled to make ends meet, coped with increased job insecurity,² and dealt with rising inflation.¹ The relationship between financial stressors and behavioural health had received growing attention over the past two decades. Indeed, prior work has found that financial hardship is related to outcomes such as depression,³ poor-quality sleep,^4,5 decreased self-rated health,⁶ substance abuse,⁷ declines in job performance,⁸ decreased life satisfaction,⁹ suicide, and psychological disorders.^7,10

U.S. military families are not immune to the financial stressors faced by the broader population, but they often face unique challenges.¹¹ These challenges, such as the precariousness of spousal employment due to factors such as frequent relocations, can place strain on military families.¹² Compared with civilian spouses, military spouses are more likely to be unemployed or underemployed and to earn less.¹² Research also shows that military members may exhibit more problematic financial behaviors (e.g., credit card debt) than civilian populations,¹³ and those aged 18–24 years are more likely than civilians to have auto loans and mortgages.¹⁴ This likely occurs because of factors such as financial inexperience and deployments.¹⁵

The location and topography of many military installations may also inadvertently contribute to debt. Some installations are located far from large urban areas and have little public transit, and several installations cover a large area of land, which requires intra-installation transportation to go from one location to another. This may explain why an examination of service member credit reports showed that assignment to a first duty station is strongly associated with getting an auto loan.¹⁴ Last, younger service members (aged 18–25 years) are more likely to have spouses and children than comparably aged civilians,¹⁶ and this, combined with the factors previously identified, such as spouse unemployment or underemployment, may compound financial hardship.

Financial hardship has implications for service member job performance, which is why the military promotes financial readiness, defined as “a state in which successful management of personal financial responsibilities supports a service member’s ability to perform his or her wartime responsibilities.”^{17(p. 3)} Mission readiness can be compromised by poor financial readiness because service members who have financial challenges are more distressed, less satisfied with military life, and more likely to attrite.¹⁷ Furthermore, service members’ careers can be negatively affected if they face financial issues such as bankruptcy that affect the maintenance of security clearances.¹⁷ It should be noted that existing data suggest that financial hardship varies on the basis of service branch; army personnel, on average, have less hardship than navy personnel but more than air force personnel.¹⁷

Financial hardship has been implicated in a wide array of health outcomes among both military personnel and Veterans (former military personnel). For instance, credit card debt and lower net worth are associated with lower well-being among U.S. soldiers.¹¹ Foran et al. also found that financial hardship,¹⁸ along with job satisfaction and depression, mediated the relationship between community functioning and alcohol abuse in the U.S. Air Force. Poor adjustment and problematic anger have also been linked to financial problems,¹⁹ and several studies show that financial hardship is related to suicide attempts and suicidal ideation.^20,21 It is also important to note that, although junior enlisted personnel often report greater financial hardship,²² some research has concluded that financial hardship is unrelated to family income.²¹ As such, financial hardship may have a broader impact beyond the military populations that are traditionally emphasized (e.g., junior enlisted personnel).²² Relatedly, a fairly sizable body of research shows that financial hardship is associated with higher levels of family distress and difficulties and relationship problems for military families,^23,24 as well as with greater food insecurity.^25,26

Although some research indicates that military personnel may be more likely to experience financial hardship, the connection to behavioural health outcomes is less clear. Additionally, many published studies focus on Veterans, rather than active duty military personnel. This study extends the literature in three ways. First, it documents the rates of financial hardship experienced by active duty military personnel and examines demographic differences in rates. Second, little to no research has investigated the prevalence of positive financial behaviours among military samples. This study examines the prevalence of two forms of positive financial behaviours — following a budget and saving. These behaviours are important to examine because they are actionable through behavioural intervention, potentially reduce the likelihood of financial hardship, and may enable soldiers to cope with financial hardship when experienced. Finally, it examines the impact of both financial hardship and positive financial behaviours on several behavioural health outcomes. This study extends prior research on behavioural health outcomes and financial hardship and addresses whether positive financial behaviours are beneficial in addressing such outcomes.

Methods

Participants

As part of a larger study of military well-being, the Land Combat Study, approved by the Walter Reed Army Institute of Research Institutional Review Board, self-report questionnaires were administered in 2018 to active duty soldiers from a combat arms brigade at two army posts. Opportunities to recruit soldiers were coordinated with unit commanders. In-person recruitment briefings, which included a description of the study, its voluntary nature, informed consent procedures, and how anonymity and confidentiality would be protected, were provided to groups of soldiers by the study team. Overall, 87.1% (841/966) of soldiers who attended the recruitment briefings gave consent for study inclusion. For the current study, the soldiers who responded to the financial hardship questions (N = 837) were selected. Table 1 shows the demographics of the sample. The modal age group was 20–24 years, and the modal education level was a high school diploma or General Educational Development (GED). The majority were male, junior enlisted, married and had no children in their household. Last, a majority reported their past year’s pre-tax total family income was less than $40,000.

Table 1.

Sample demographic characteristics (N = 837)

Characteristic	No.	(%)
Age, y
17–19	69	(8.4)
20–24	353	(43.2)
25–29	228	(27.9)
30–39	167	(20.4)
Gender*
Male	693	(85.1)
Female	121	(14.9)
Education
High school diploma or GED	361	(44.2)
Some college or 2 y degree	313	(38.4)
≥Bachelor’s degree	142	(17.4)
Rank
Junior enlisted	523	(62.7)
NCO	202	(24.2)
Officer or warrant officer	109	(13.1)
Marital status
Single	313	(38.9)
Married	414	(51.4)
Separated or divorced	78	(9.7)
Children in household
0	505	(61.9)
1	136	(16.7)
2	98	(12.0)
≥3	77	(9.4)
Family oncome
Low	473	(58.2)
Middle	234	(28.8)
High	106	(13.0)

Note: Missing data for the characteristics range from <1% to 3.8%, so numbers do not sum to 837.

* The survey question asked participants for their gender but had male and female, which are regarded as sex categories, as the response options.

GED = General Educational Development, NCO = non-commissioned officer.

Measures

Soldiers were asked to respond no or yes to 10 questions related to their financial circumstances. The question stem was “In the past year, have you,” and the items were “had problems paying your bills,” “had credit card debt,” “pawned or sold something because you needed money,” “asked for help from welfare/community organizations,” “asked for financial help from friends or family,” “cut the amount of food you ate or skipped meals because you did not have enough money,” “had debt that you feel you can’t get out of,” “used an emergency loan service (e.g., payday loan, car title loan, home equity loan),” “followed a budget or a savings plan,” and “saved for retirement or future expenses like your child’s education.” The bill paying question was adapted from Linstrom and Rosvall.²⁷ The debt question was adapted from Averett and Smith.²⁸ Questions about pawning, help from organizations, or help from friends and family were adapted from Bray.²⁹ The food and meals question was adapted from Williamson et al.³⁰ The other four questions were developed for this study.

Seven questions were used to construct an overall measure of financial hardship, which was operationalized as endorsing at least one question. A question about credit card debt was omitted from this overall measure because it was not specific enough to indicate hardship. Cronbach’s α for these seven items was 0.79. The last two questions measured positive financial behaviours. An overall measure was constructed to indicate whether participants endorsed at least one of the two. Cronbach’s α was not computed for this measure because it had too few items.

Depression was measured with the Patient Health Questionnaire-9,³¹ which has been validated in military populations.^32–34 To meet screening criteria for probable depression, respondents had to endorse at least five symptoms, including “feeling down, depressed or hopeless” or “having little interest in doing things” for more than half the days in the past month and indicate impairment in work, at home, or in interpersonal functioning at the very difficult or extremely difficult level. A total of 5.3% of participants met criteria for probable depression.

Anxiety was measured with the items from the Generalized Anxiety Disorder seven-item scale,³⁵ which has been validated with military populations.^32,33,36 Items were summed, and respondents who scored 10 or greater, and who indicated home or interpersonal functioning difficulties (as with depression), met screening criteria for anxiety. A total of 7.6% of the sample met criteria for anxiety.

Posttraumatic stress disorder (PTSD) was measured using the 20-item Posttraumatic Stress Disorder Checklist for the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition,³⁷ which has been validated with military populations.^32,38–40 To meet criteria for probable PTSD, respondents had to indicate that at least one symptom in clusters B and C and two symptoms in clusters D and E bothered them moderately or higher, in addition to a total score of 38 or greater. A total of 7.5% of the sample met criteria for PTSD.

Alcohol misuse was measured using the Alcohol Use Disorders Identification Test-Consumption,⁴¹ which has been validated with military populations.⁴² Items were summed and then dichotomized so participants who scored seven or higher were classified as misusers.⁴³ Cronbach’s α was 0.79. A total of 8.8% of the sample met criteria for alcohol misuse.

Sleep duration was assessed with a question about average daily sleep in the past week. Responses were dichotomized so that three or fewer hours to six hours was coded as inadequate sleep and seven or more hours was coded as adequate sleep. A total of 79.3% of the sample reported inadequate sleep.

Insomnia was measured with the Insomnia Severity Index.⁴⁴ Caseness was scored following an established criterion, where a sum score of 10 or greater was coded as meeting criteria for probable insomnia (α = 0.92). A total of 34.8% of the sample met the criteria for insomnia.

For self-rated health, participants were asked to rate their general health in the past month on a five-point response scale ranging from excellent (1) to poor (5).⁴⁵ Responses were dichotomized; poor and fair were collapsed into one category, and good, very good, and excellent were collapsed into the other. A total of 17.4% of the sample reported poor or fair health.

Physical aggression was measured by four items adapted from the Physical Aggression subscale of the Buss-Perry Aggression Questionnaire.⁴⁶ The four Physical Aggression items (α = 0.70) were selected for the overall study because they were the most serious physically aggressive behaviours from the original nine-item Physical Aggression subscale. Participants who responded they “couldn’t control the urge to strike another person,” “got into fights,” “were pushed so far by others that it came to blows,” or “became so mad that I broke things” one or more times in the past month were coded as reporting physically aggressive behaviour. A total of 16.2% of the sample reported engaging in any physically aggressive behaviour in the past month.

Data analyses

Analyses were performed with IBM SPSS (version 24) and Microsoft Excel (2016). Chi-square analysis was used to assess the association between demographic characteristics, financial hardship items, and the positive financial behaviour item with SPSS. In Excel,⁴⁷ post hoc analyses with Bonferroni-adjusted αs of the significant χ² results were conducted to determine which cells with adjusted residuals greater than two had counts that were greater or fewer than expected.⁴⁸ Logistic regression models were estimated in SPSS to assess the association of financial hardship and positive financial behaviours with depression, anxiety, PTSD, alcohol misuse, self-rated health, sleep duration, insomnia, and physical aggression. The two positive financial behaviour items were analyzed separately because they were only moderately correlated with each other (r = 0.34) and had different patterns of correlation with the financial hardship items. The models were adjusted for demographic variables that were associated with the outcomes — education, rank, marital status, number of children, and family income. No substitutions were made for missing data for either the χ² tests or the logistic regressions.

Results

Tables 2 and 3 show the overall rates of each financial hardship and positive financial behaviour both overall and broken down by demographics. About one-third of the sample reported experiencing at least one form of financial hardship in the past year. About 40% of those (12.4% of the sample) reported one hardship, another third (11.7% of the sample) reported two or three hardships, and the remainder (6.9%) reported four or more hardships. Regarding the specific hardships, four were experienced by more than 10% of the sample, including having to seek help from family or friends, trouble paying bills, cutting food or skipping meals, and intractable debt. Fewer than 10% reported pawning or selling items to raise money, taking emergency loans, or seeking welfare or help from community organizations. Conversely, close to three-quarters reported engaging in at least one positive financial behaviour, with more than half reporting following a budget and saving for retirement or future expenses. Engaging in positive financial behaviours was not strongly related to whether one experienced financial hardship; 33% of those who experienced hardship also engaged in at least one positive behaviour, whereas 27% of those who did not experience hardship engaged in at least one positive behaviour.

Table 2.

Demographic distribution of financial hardships

Characteristic	Those who endorsed yes, %*
	Trouble paying bills	Pawning or selling	Welfare or community organization help	Family or friends help	Cutting food or skipping meals	Intractable debt	Emergency loan	Any hardship
Overall	14.0	9.6	3.3	14.8	13.9	12.4	7.3	31.1
Age, y
17–19	7.2	2.9	0.0	17.4	18.8	2.9	2.9	26.1
20–24	14.2	11.6	2.8	18.3	17.0†	10.2	7.1	32.9
25–29	14.9	8.4	3.9	11.8	11.4	14.7	7.5	29.8
≥30	15.0	8.4	4.8	12.0	9.0†	16.9	9.0	30.5
χ23	2.92	5.99	4.04	6.14	8.77†	11.57†	2.72	1.52
Gender
Male	14.0	9.8	3.2	14.9	14.1	11.7	7.4	31.6
Female	12.4	5.8	4.1	15.8	11.6	13.3	5.8	26.4
χ21	0.22	2.01	0.29	0.67	0.57	0.25	0.37	1.28
Education
High school diploma or GED	13.0	10.2	2.8	20.1†	16.9	8.3†	6.7	34.9
Some college or 2 y degree	18.2†	11.5	4.8	15.1	15.3	17.4†	9.6	33.9
≥Bachelor’s degree	7.0†	2.1†	1.4	2.8†	3.5†	10.6	3.5	14.8†
χ22	10.63†	10.91†	4.12	23.36†	15.96†	13.27†	5.77	21.22†
Rank
Junior enlisted	15.3	11.3	3.6	19.4†	18.0†	12.1	7.9	35.0†
NCO	15.3	9.4	4.0	9.9	9.9	15.1	8.4	32.2
Officer or warrant officer	5.5†	0.9†	0.9	1.9†	1.8†	8.3	2.8	10.1†
χ22	7.55†	11.33†	2.35	26.99†	23.28†	3.10	3.94	26.27†
Marital status
Single	8.0†	6.4	1.0†	11.9†	12.8	6.7†	2.3†	24.6†
Married	16.4	9.9	4.8	16.0	12.6	14.9	10.4†	33.8
Separated or divorced	24.4†	17.9†	5.1	23.1	25.6†	21.8†	11.5	41.0
χ22	18.46†	10.22†	9.04†	6.54†	9.93†	18.04†	19.55†	11.21†
No. children in household
0	10.9†	8.1	1.6†	12.9	13.1	10.5	4.2†	27.3
1	17.6	8.1	3.7	16.2	11.0	12.6	8.9	30.1
2	16.3	13.4	8.2†	18.4	11.2	12.5	14.3†	37.8
≥3	23.4	14.3	7.9	24.0	24.7†	20.8	15.6†	45.5†
χ23	11.71†	5.26	16.95†	7.41	9.39†	6.70	22.76†	12.88†
Family income
Low	16.5	11.7†	3.6	18.2†	18.6†	11.9	8.3	35.3†
Middle	14.1	7.3	3.4	12.4	8.1†	13.9	7.3	27.8
High	2.8†	4.7	1.9	7.8	5.7	10.4	2.9	19.8†
χ22	13.41†	6.74†	0.77	9.18†	21.96†	0.96	3.74	11.41†

* χ² = Pearson χ².

^† p < 0.05.

GED = General Educational Development, NCO = non-commissioned officer.

Table 3.

Demographic distribution of positive financial behaviours

Characteristic	Those who endorsed yes, %*
	Followed budget or savings plan	Saved for retirement or future expenses	Any positive behaviour
Overall	60.7	54.2	73.5
Age, y
17–19	39.1†	30.4†	47.8†
20–24	60.5	48.7†	70.8
25–29	63.9	58.8	76.8
≥30	64.7	71.9†	85.0†
χ23	15.48†	42.88†	37.23†
Gender
Male	59.0	53.0†	72.3
Female	67.8	64.5	79.3
χ21	3.275	5.47†	2.62
Education
High school diploma or GED	54.6†	41.2†	63.7†
Some college or 2 y degree	61.7	57.1	77.0
≥Bachelor’s degree	73.2†	84.4†	90.8†
χ22	15.06†	77.21†	41.69†
Rank
Junior enlisted	42.2	44.9†	67.7†
NCO	59.9	61.0	78.2
Officer or warrant officer	75.2†	87.0†	92.7†
χ2 (2)	11.33†	68.75†	31.93†
Marital status
Single	54.3†	46.5†	65.8†
Married	66.3†	61.1†	80.2†
Separated or divorced	59.0	56.4	71.8
χ22	10.80†	15.34†	19.23†
Children in household
0	58.8	48.7†	69.3†
1	63.2	66.9†	80.1
2	61.2	61.2	77.6
≥3	64.9	62.3	83.1
χ23	1.65	18.94†	12.10†
Family income
Low	56.9	45.6†	68.3†
Middle	67.5	65.7†	81.6†
High	62.3	72.4†	81.1
χ22	7.51†	40.15†	17.79†

* χ² = Pearson χ².

^† p < 0.05.

GED = General Educational Development, NCO = non-commissioned officer.

Table 2 demonstrates the demographic distributions of participants who reported financial hardship in the past year. There were no age group or gender differences in the percentages who reported each financial hardship or the overall measure (based on the post-hoc analyses). The proportion of participants with a bachelor’s or graduate degree, in the officer or warrant officer rank, who were never married, and in the high family income group who reported any financial hardship was statistically significantly lower (p < 0.05) compared with the other education, rank, marital status, and family income categories. Last, the proportion of participants with three or more children experiencing any financial hardship was statistically significantly higher (p < 0.05) compared with the proportion of those with fewer children. The proportions of males and females reporting any financial hardships were not statistically significantly different. Displayed in Table 3 are the demographic distributions of participants who reported positive financial behaviours. The lowest percentages for any positive financial behaviour (p < 0.05) were reported by those in the youngest age group, with a high school diploma, junior enlisted, never married, non-parents, and in the low family income group. Although the percentage of males reporting saving for retirement or future expenses was statistically significantly lower than the percentage for females, the proportion of males and females reporting any positive financial behaviour were not statistically significantly different.

Table 4 reports the results of a series of logistic regressions showing the associations of the behavioural health outcomes with both overall financial hardship and the two positive financial behaviours after adjusting for education, rank, marital status, number of children, and family income. Financial hardship was associated with a greater likelihood of depression (adjusted odds ratio [AOR] 9.03; 95% confidence interval [CI], 4.00–20.35), anxiety (AOR 4.76; 95% CI, 2.62–8.64), PTSD (AOR 4.05; 95% CI, 2.22–7.36), shorter sleep duration (AOR 0.38; 95% CI, 0.24–0.61), insomnia (AOR 3.14; 95% CI, 2.24–4.40), poor self-rated health (AOR 0.37; 95% CI, 0.24–0.54), and physical aggression (AOR 2.81; 95% CI, 1.86–4.26). The only outcome not associated with financial hardship was alcohol misuse. Following a budget or savings plan was associated with less frequent alcohol misuse (AOR 0.55; 95% CI, 0.32–0.95) but no other outcomes. Saving for retirement or future expenses was not associated with any outcome.

Table 4.

Multivariate relationships between behavioural health, financial hardship, and positive financial behaviours

Key independent variable	Depression	Anxiety	PTSD	Alcohol misuse	Sleep duration	Insomnia	Self-rated health	Physical aggression
Financial hardship
B (SE)	2.20 (.42)	1.56 (0.31)	1.40 (0.31)	0.48 (0.28)	−0.97 (0.24)	1.14 (0.17)	−1.00 (0.21)	1.03 (0.21)
Wald	28.13	26.21	21.07	2.98	15.95	44.04	22.22	23.85
AOR (95% CI)	9.03 (4.00–20.35)	4.76 (2.62–8.64)	4.05 (2.23–7.36)	1.62 (0.94–2.80)	0.38 (0.24–0.61)	3.14 (2.24–4.40)	0.37 (0.24–0.56)	2.81 (1.86–4.26)
Following a budget or savings plan
B (SE)	0.22 (.39)	−0.12 (0.31)	0.04 (0.31)	−0.59 (0.28)	0.00 (0.21)	0.08 (0.18)	0.09 (0.22)	0.26 (0.23)
Wald	0.31	0.15	0.02	4.57	0.00	0.21	0.16	1.30
AOR (95% CI)	1.24 (0.58–2.65)	0.89 (0.49–1.62)	1.04 (0.57–1.92)	0.55 (0.32–0.95)	1.00 (0.66–1.51)	1.08 (0.77–1.53)	1.09 (0.71–1.68)	1.30 (0.83–2.03)
Saved for retirement or future expenses
B (SE)	−0.18 (0.36)	0.15 (0.30)	−0.27 (0.31)	−0.15 (0.29)	0.26 (0.22)	−0.02 (.18)	0.19 (0.22)	0.32 (0.22)
Wald	0.25	0.23	0.77	0.26	1.34	0.01	0.74	2.10
AOR (95% CI)	0.84 (0.41–1.70)	1.16 (0.64–2.10)	0.76 (0.42–1.40)	0.86 (0.49–1.53)	1.29 (0.84–1.99)	0.98 (0.69–1.39)	1.21 (0.78–1.88)	1.38 (0.89–2.14)
Significant covariates	Marital status,† no. of children‡	None	None	None	Education,§ family income¶	Rank**	Education,†† rank,†† marital status§§	Marital status¶¶
Nagelkerke R2	0.22	0.11	0.12	0.05	0.13	0.13	0.13	0.11

Notes: Boldface indicates significant results. Bolded AORs are statistically significant at p < 0.05. N = 775–780 for all analyses.

* Adjusted for education, rank, marital status, number of children, and family income (Supplemental Appendix 1 includes complete results).

^†Compared with those who were separated or divorced, married soldiers were more likely to meet criteria for depression.

^‡ Compared with those with no children, soldiers with two children were less likely to meet criteria for depression.

^§Education overall was significantly related, but there were no significant sub-group differences.

^¶ Family income overall was significantly related. Compared with high income, low and middle income participants reported longer sleep duration.

** Rank overall was significantly related. Also, compared to officers, junior enlisted (E1-E4) and senior enlisted (E5-E9) were more likely to report insomnia.

^†† Education overall was significantly related. Compared to those with a bachelor’s degree or more, those with high school/GED and some college or associate’s degree education were more likely to report better health.

^‡‡ Rank overall was significantly related. Compared with officers, junior enlisted (E1-E4) and senior enlisted (E5-E9) were less likely to report better health.

^§§ Compared with the separated or divorced, married soldiers were less likely to report better health.

^¶¶ Compared with those who were separated or divorced, single soldiers were less likely to report physical aggression.

Wald = Wald statistic. AOR = adjusted odds ratio, CI = confidence interval, SE = standard error.

Discussion

Financial hardship is widely recognized as an important source of stress for Americans. Some research has investigated financial hardship in both Veteran and active duty military samples, although more research is needed on prevalence and the association with behavioural health outcomes. Less research has investigated the potential behavioural health benefits of positive financial behaviours. This study investigated these issues in a large sample of active duty soldiers. It found fairly high rates of financial hardship; more than 30% of the sample reported experiencing at least one hardship in the past year, which is close to the 25% reporting financial challenges on the Status of the Forces Survey (SOFS), which used mostly different questions.¹⁷ This high rate of hardship suggests the need to continue to enhance the existing programs and regulations geared toward helping soldiers avoid financial hardship before it occurs and to avoid further hardship, particularly for the groups most affected, such as junior enlisted members and soldiers with larger families.

Programs and regulations may have to serve as the primary prevention and intervention approaches; the U.S. military is unlikely to increase pay because, according to the 13th Quadrennial Review of Military Compensation, enlisted personnel pay exceeded the 70th percentile benchmark of the pay of comparable civilians.⁴⁹ In addition to an annual assessment of service member financial readiness (SOFS),⁵⁰ which began in 2015, Congress enacted legislation to bolster consumer protections such as regulations on lending and financial products. Additionally, service members have an office within the Consumer Financial Protection Bureau dedicated to education and monitoring complaints about financial services.⁵⁰ Financial literacy has also been a focus of Congress and the military, with changes made in 2016 to mandate financial literacy training at several career junctures, including at initial entry training and at service members’ arrival at their first and subsequent stations.⁵⁰ Last, military families have access to needs-based financial aid such as the Basic Needs Allowance, which was authorized in fiscal year 2022 and caters to families with household income lower than 130% of federal poverty guidelines.⁵⁰

However, it is unknown to what extent, despite the mandate, financial literacy programs were implemented across the career life cycle, whether they adhere to documented best practices,¹⁷ and whether service members consider them useful. The authors hope that recent army initiatives to standardize financial education and improve implementation will help ensure training effectiveness.¹⁷

It was previously noted that there were no age or gender differences in financial hardship. However, less-educated, lower-ranked, previously married, lower-income soldiers with larger families reported greater levels of hardship. The financial well-being of these soldiers may be exacerbated by the comparably low rates of the positive behaviours. Findings about the proportion who reported following a budget or a savings plan are consistent with the active duty service members rate (55%) on the SOFS.¹⁷ However, the prevalence of savings this study reported is not comparable to what was reported on the SOFS because this study’s question focused on saving for retirement or future expenses,¹⁷ whereas the SOFS question focused on savings account contributions. The SOFS also noted that junior enlisted service members were less likely to report positive financial behaviours but did not provide a percentage.¹⁷ These findings highlight the need for targeted strategies to address groups at most risk for hardship. For example, what is important for junior enlisted personnel with families may differ considerably from what is needed for officers approaching retirement.

Findings also showed that financial hardship was associated with greater risk of several behavioural health outcomes. Conservation of resources (COR)^51,52 theory highlights that the loss, or threatened loss, of financial resources constitutes an important life stressor that may directly account for greater psychological difficulties. Other research proposes that chronic stressors, such as financial hardship, undermine personal resources such as self-esteem or social resources such as social support.⁵³ COR theory offers an explanatory framework to develop further hypotheses about these relationships because, for example, expending efforts to deal with one’s financial situation might lessen the resources available to contend with mental health difficulties. Conversely, successful efforts to cope with one’s financial situation may generate additional resources that benefit one’s mental health.

Although this was not directly examined, financial hardship may exacerbate difficulties associated with other stressors. For example, soldiers who experienced more occupational stressors, including combat exposure, may have greater difficulties in recovering from PTSD or depression. Similarly, sleep problems associated with financial hardship may exacerbate the impact of military stressors on behavioural health. This implies that financial hardship might moderate the relationship between military stressors and behavioural health outcomes or might influence the trajectory of recovery from these problems, both of which would be interesting to examine in future research.

As noted previously, the only significant relationship between positive financial behaviours and behavioural health was the inverse relationship between following a budget and lower rates of alcohol misuse. Although this finding suggests some benefits of positive financial behaviour, financial hardship was more clearly associated with behavioural health outcomes. However, it is important to keep in mind that only two positive financial behaviours were measured. Other types of positive financial behaviours, such as emergency savings, may have yielded different prevalence estimates and might be more useful for identifying the most meaningful components of financial interventions. For example, research shows that behaviours before deployment, such as low credit card debt and greater emergency savings, are beneficial in minimizing future financial problems.⁵⁴ Additionally, the impact of some positive behaviours may differ depending on the status of other positive behaviours — for example, some individuals may eschew traditional savings accounts, opting instead for alternate investment strategies. Nonetheless, the findings offer some preliminary evidence of the potential need for further attention to positive financial behaviours in the military context.

This study also found that the relationship between financial hardship and positive financial behaviour was not strong. On the one hand, a negative relationship might be expected in that those who engage in more positive behaviours would be at less risk for hardship. On the other hand, it could be the case that some soldiers do not engage in positive financial behaviours until they experience hardship. In other words, positive financial behaviour may be a proactive response for some and a reactive response for others. Future research should investigate these possible differences, ideally with more comprehensive measures of positive financial behaviour, knowledge and skills, and values.

Limitations

A few important limitations should be addressed in future research. First, the cross-sectional design limits the extent to which causal inferences can be drawn. This is especially important because it is plausible that financial hardship leads to behavioural health problems and that people experiencing greater behavioural health difficulties experience financial hardship. For example, financial hardship may trigger depression even as the experience of depression makes it more difficult to cope with financial concerns. Similarly, the relationship between financial hardship and some behavioural health outcomes may be indirect. For example, the outcomes investigated here may be proximal predictors of other outcomes, such as suicidality.⁵⁵ Longitudinal research is needed to study the mutual effects of financial hardship and health in military populations. Such research would both help clarify the hardship-health relationship and potentially inform research on the trajectory of behavioural health outcomes, such as, for example, whether financial hardship might lead to slower recovery from trauma.

Second, although not a limitation per se, it is important to note that this study focused on active duty personnel. Prior literature on financial stress in the military context has typically focused on either active duty personnel or Veterans. The authors know of no research that has directly investigated potential contextual differences between these populations, in either the prevalence or the impact of financial hardship, other than analysis done by the Consumer Financial Protection Bureau that compared former service members with 1 year, 2.5 years, and 5 or more years in service.^14,25 Similarly, it is unclear to what extent studies of military samples generalize to civilian settings or vice versa. The special characteristics of military personnel, with large numbers of younger personnel exposed to deployments, frequent moves, challenges with maintaining spousal employment, and so forth, are quite different from the civilian context, and military-focused research is needed to understand hardship in this context. Relatedly, the data were collected from soldiers in combat arms brigades, and these findings may not generalize to all soldiers. Finally, the geographical locations of the sample may represent a potential generalizability concern given that cost of living may vary depending on where military units are located. However, most of the geographical variations in housing and utility costs are addressed by the basic housing allowance, which is adjusted yearly based on median rates for housing and utilities in different regions.

Third, the data reported in this study were collected in 2018, and the financial well-being of service members may be time limited. Data could not reflect the impact of initiatives such as the revised financial literacy program and the availability since 2022 of Basic Needs Allowance payments, which were implemented after the study was conducted. More studies are needed to determine whether the findings reported here are reliable.

Another potential limitation is that the relationships of interest in this study may be stronger or weaker depending on individual difference moderators. For example, researchers have found that some personal factors, such as subjective financial knowledge, a sense of self-mastery, and decreased anxiety around finances, have a positive impact on financial behaviours.⁵⁴ Furthermore, other studies identified individual resources that are protective and influence how people respond to financial hardship. Examples include locus of control and self-esteem,^56,57 both of which might be important factors to incorporate in future military financial hardship research. In particular, studies should examine whether these, or other individual differences, influence soldiers’ reactions to, or experience of, financial hardship.

Finally, it is important to note that the key constructs were assessed by self-report. This raises a couple of potentially relevant concerns. First, socially desirable responding biases might have led participants to inaccurately report hardship experiences, positive behaviours, or behavioural health. One potential effect of social desirability in this circumstance would be lower variability in the hardship and outcome measures, which would mean this study is a conservative test of the relationship between these constructs. However, participants might inaccurately report positive behaviours, which might lead to distorted prevalence estimates. The other potential concern with a sole reliance on self-report is common method bias leading to inflated estimates. Although this is a relevant issue, some researchers have concluded that concerns about common method biases are over-inflated relative to their actual impact on studies.⁵⁸ In any case, future research should extend these findings by using objective measures such as direct measures of income, savings, and debt and clinician diagnoses.

Conclusion

Financial hardship continues to be a prevalent concern for military personnel, with higher rates observed for junior enlisted personnel as well as those with larger families. Moreover, financial hardship tends to be associated with higher rates of behavioural health problems, although the causal direction of this relationship is potentially ambiguous. Future research should evaluate the effectiveness of current military financial literacy and support programs, assess the extent to which the regulations to protect service members from predatory lending are adhered to, and further investigate the potential role of individual differences in the relationship between financial hardship and behavioural health.

Biographies

Lyndon A. Riviere, PhD, is a sociologist who researches soldier behavioural health, relationship functioning, the influence of social factors on health, and military spouse well-being. He is employed as a Research Scientist in the Center for Military Psychiatry and Neurosciences at the Walter Reed Army Institute of Research (WRAIR). He is the principal investigator of several studies focused on characterizing soldier well-being and is a member of the WRAIR Institutional Review Board.

Robert R. Sinclair, PhD, is a professor of Industrial-Organizational Psychology at Clemson University. He is a past president of the Society for Occupational Health Psychology and founding Editor-in-Chief of Occupational Health Science. Sinclair is an editorial board member of the Journal of Business and Psychology, Journal of Applied Psychology, Journal of Occupational Health Psychology, and Group and Organization Management. His work includes more than 100 papers and chapters covering topics such as economic stress, organizational climate, and resilience and well-being.

Baylor Graham, MS, is a PhD candidate in the Industrial and Organizational Psychology Program at Clemson University. She has an MS in applied psychology and is currently working toward an MS in data science and analytics. Her research interests include economic stress, employee health and well-being, workplace mistreatment, and research methodology.

Appendix 1. Financial Hardship Logistic Regression Full Results

Logistic Regression Results for Depression

Model summary
Step	−2 log likelihood	Cox & Snell R2	Nagelkerke R2
1	262.197*	0.073	0.216

* Estimation terminated at iteration number 8 because parameter estimates changed by less than 0.001.

Variables in the equation

Step 1*	B	SE	Wald	df	p	Exp(B) odds ratio	95% CI
							Lower	Upper
Any financial hardship	2.200	0.415	28.130	1	< 0.001	9.026	4.003	20.352
In the past year have you followed a budget or a savings plan	0.216	0.387	0.313	1	0.576	1.242	0.582	2.649
In the past year have you saved for retirement or future expenses like your child’s education	−0.181	0.363	0.249	1	0.618	0.835	0.410	1.698
Education (ref = ≥bachelor’s degree)			3.675	2	0.159
High school or GED	−0.740	0.797	0.861	1	0.353	0.477	0.100	2.276
Some college or associate’s degree	−0.007	0.763	0.000	1	0.993	0.993	0.223	4.434
Rank (ref = officer)			0.307	2	0.858
Junior enlisted (E1-E4)	0.585	1.086	0.290	1	0.590	1.795	0.213	15.095
Senior enlisted (E5-E6)	0.459	1.074	0.183	1	0.669	1.583	0.193	13.004
Marital status (ref = separated or divorced)			4.840	2	0.089
Single (never married)	−0.021	0.441	0.002	1	0.963	0.980	0.413	2.325
Married	0.961	0.480	4.003	1	0.045	2.613	1.020	6.696
No. of children (ref = 0)			4.906	3	0.179
1	−0.319	0.495	0.415	1	0.520	0.727	0.276	1.918
2	−1.763	0.801	4.838	1	0.028	0.172	0.036	0.825
≥3	−0.198	0.583	0.116	1	0.734	0.820	0.261	2.573
Family income (ref = high)			2.748	2	0.253
Low	1.490	1.083	1.893	1	0.169	4.437	0.531	37.062
Middle	1.760	1.074	2.686	1	0.101	5.814	0.708	47.727
Constant	−5.726	1.297	19.499	1	< 0.001	0.003

* Variable(s) entered in Step 1: Any financial hardship, In the past year have you followed a budget or a savings plan, in the past year have you saved for retirement or future expenses like your child’s education, education, rank, marital status, recoded number of children in household, family income.

CI = confidence interval, ref = reference, GED = General Educational Development, SE = standard error.

Logistic Regression Results for Anxiety

Model summary
Step	−2 log likelihood	Cox & Snell R2	Nagelkerke R2
1	380.834*	0.047	0.112

* Estimation terminated at iteration number 6 because parameter estimates changed by less than 0.001.

Variables in the equation

Step 1*	B	SE	Wald	df	p	Exp(B) odds ratio	95% CI
							Lower	Upper
Any financial hardship	1.559	0.305	26.207	1	< 0.001	4.755	2.618	8.639
In the past year have you followed a budget or a savings plan	−0.118	0.306	0.150	1	0.699	0.889	0.488	1.617
In the past year have you saved for retirement or future expenses like your child’s education	0.146	0.303	0.232	1	0.630	1.157	0.639	2.095
Education (ref = ≥bachelor’s degree)			0.770	2	.681
High school or GED	−0.393	0.615	0.409	1	0.523	0.675	0.202	2.252
Some college or associate’s degree	−0.141	0.596	0.056	1	0.813	0.869	0.270	2.791
Rank (ref = officer)			0.737	2	0.692
Junior enlisted (E1-E4)	.098	.773	.016	1	.899	1.103	.242	5.018
Senior enlisted (E5-E6)	0.399	0.755	0.279	1	0.597	1.490	0.339	6.544
Marital status (ref = separated or divorced)			2.142	2	0.343
Single (never married)	−0.108	0.359	0.090	1	0.764	0.898	0.444	1.815
Married	0.517	0.415	1.550	1	0.213	1.677	0.743	3.782
No, of children (ref = 0)			3.136	3	0.371
1	−0.632	0.462	1.878	1	0.171	0.531	0.215	1.313
2	−0.681	0.508	1.796	1	0.180	0.506	0.187	1.370
≥3	−0.080	0.472	0.029	1	0.866	0.923	0.366	2.329
Family income (ref = high)			0.448	2	0.799
Low	0.295	0.542	0.297	1	0.586	1.343	0.465	3.884
Middle	0.064	0.528	0.015	1	0.903	1.066	0.379	2.999
Constant	−3.217	0.667	23.247	1	< .001	0.040

* Variable(s) entered in step 1: any financial hardship, in the past year have you followed a budget or a savings plan, in the past year have you saved for retirement or future expenses like your child’s education, education, rank, marital status, recoded number of children in household, family income.

CI = confidence interval, ref = reference, GED = General Educational Development, SE = standard error.

Logistic Regression Results for Posttraumatic Stress Disorder

Model summary
Step	−2 log likelihood	Cox & Snell R2	Nagelkerke R2
1	372.631*	0.050	0.121

* Estimation terminated at iteration number 6 because parameter estimates changed by less than 0.001.

Variables in the equation

Step 1*	B	SE	Wald	df	p	Exp(B) odds ratio	95% CI
							Lower	Upper
Any financial hardship	1.399	0.305	21.067	1	< 0.001	4.050	2.229	7.359
In the past year have you followed a budget or a savings plan	0.043	0.310	0.019	1	0.891	1.043	0.568	1.916
In the past year have you saved for retirement or future expenses like your child’s education	−0.270	0.307	0.771	1	0.380	0.764	0.418	1.395
Education (ref = ≥bachelor’s degree)			3.093	2	0.213
High school or GED vs.	0.417	0.796	0.274	1	0.601	1.517	0.319	7.222
Some college or associate’s degree	0.888	0.772	1.323	1	0.250	2.431	0.535	11.050
Rank (ref = officer)			0.138	2	0.933
Junior enlisted (E1-E4)	0.342	0.928	0.136	1	0.712	1.408	0.228	8.684
Senior enlisted (E5-E6)	0.288	0.913	0.099	1	0.752	1.334	0.223	7.976
Marital status (ref = separated or divorced)			3.774	2	.152
Single (never married)	−0.221	0.372	0.353	1	0.553	0.802	0.387	1.662
Married	0.628	0.403	2.431	1	0.119	1.874	0.851	4.127
No. of children (ref = 0)			1.447	3	0.695
1	−0.166	0.412	0.163	1	0.687	0.847	0.378	1.899
2	−0.501	0.487	1	1	0.303	0.606	0.233	1.572
≥3	−0.462	0.522	0.782	1	.377	0.630	0.226	1.754
Family income (ref = high)			1.217	2	0.544
Low	−0.531	0.510	1.085	1	0.298	0.588	0.216	1.597
Middle	−0.247	0.503	0.242	1	0.623	0.781	0.292	2.092
Constant	−3.419	0.746	20.975	1	< 0.001	0.033

* Variable(s) entered in step 1: any financial hardship, in the past year have you followed a budget or a savings plan, in the past year have you saved for retirement or future expenses like your child’s education, education, rank, marital status, recoded number of children in household, family income.

CI = confidence interval, ref = reference, GED = General Educational Development, SE = standard error.

Logistic Regression Results for Alcohol Misuse

Model summary
Step	−2 log likelihood	Cox & Snell R2	Nagelkerke R2
1	444.818*	0.020	0.046

* Estimation terminated at iteration number 6 because parameter estimates changed by less than .001.

Variables in the equation

Step 1*	B	SE	Wald	df	p	Exp(B) odds ratio	95% CI
							Lower	Upper
Any financial hardship	0.482	0.279	2.983	1	0.084	1.620	0.937	2.799
In the past year have you followed a budget or a savings plan	−0.593	0.277	4.567	1	0.033	0.553	0.321	0.952
In the past year have you saved for retirement or future expenses like your child’s education	−0.149	0.291	0.261	1	0.609	0.862	0.487	1.525
Education (ref = ≥bachelor’s degree)			2.425	2	0.297
High school or GED	0.772	0.686	1.268	1	0.260	2.164	0.564	8.298
Some college or associate’s degree	0.365	0.679	0.289	1	0.591	1.440	0.380	5.452
Rank (ref = officer)			0.181	2	0.914
Junior enlisted (E1-E4)	−0.321	0.759	0.179	1	0.672	0.725	0.164	3.211
Senior enlisted (E5-E6)	−0.292	0.747	0.153	1	0.696	0.747	0.173	3.228
Marital status (ref = separated or divorced)			1.491	2	0.475
Single (never married)	0.369	0.336	1.208	1	0.272	1.446	0.749	2.793
Married	0.368	0.434	0.721	1	0.396	1.445	0.618	3.381
No. of children (ref = 0)			0.620	3	0.892
1	0.301	0.393	0.589	1	0.443	1.352	0.626	2.920
2	0.072	0.462	0.024	1	0.877	1.074	0.434	2.656
≥3	0.158	0.479	0.109	1	0.741	1.172	0.458	2.996
Family income (ref = high)			1.652	2	0.438
Low	−0.382	0.453	0.712	1	0.399	0.683	0.281	1.657
Middle	0.040	0.438	0.008	1	0.927	1.041	0.441	2.455
Constant	−2.402	0.573	17.584	1	< 0.001	0.091

* Variable(s) entered in step 1: any financial hardship, in the past year have you followed a budget or a savings plan, in the past year have you saved for retirement or future expenses like your child’s education, education, rank, marital status, recoded number of children in household, family income.

CI = confidence interval, ref = reference, GED = General Educational Development, SE = standard error.

Logistic Regression Results for Sleep Duration

Model summary
Step	−2 log likelihood	Cox & Snell R2	Nagelkerke R2
1	725.777*	0.083	0.129

* Estimation terminated at iteration number 5 because parameter estimates changed by less than 0.001.

Variables in the equation

Step 1*	B	SE	Wald	df	p	Exp(B) odds ratio	95% CI
							Lower	Upper
Any financial hardship	−0.970	0.243	15.947	1	< 0.001	0.379	0.236	0.610
In the past year have you followed a budget or a savings plan	0.001	0.210	0.000	1	0.995	1.001	0.663	1.512
In the past year have you saved for retirement or future expenses like your child’s education	0.255	0.220	1.335	1	0.248	1.290	0.838	1.987
Education (ref = ≥bachelor’s degree)			8.834	2	0.012
High school/GED vs.	0.642	0.432	2.209	1	0.137	1.900	0.815	4.427
Some college or associate’s degree	−0.007	0.435	0.000	1	0.987	0.993	0.424	2.327
Rank (ref = officer)			4.347	2	0.114
Junior enlisted (E1-E4)	−0.531	0.492	1.168	1	0.280	0.588	0.224	1.541
Senior enlisted (E5-E6)	−0.952	0.503	3.584	1	0.058	0.386	0.144	1.034
Marital status (ref = separated or divorced)			4.066	2	0.131
Single (never married)	0.400	0.227	3.102	1	0.078	1.491	0.956	2.326
Married	−0.168	0.382	0.195	1	0.659	0.845	0.400	1.785
No. of children (ref = 0)			1.508	3	.680
1	−0.090	0.295	0.092	1	0.761	0.914	0.513	1.630
2	−0.337	0.368	0.839	1	0.360	0.714	0.347	1.469
≥3	−0.403	0.417	0.930	1	0.335	0.669	0.295	1.515
Family income (ref = high)			7.605	2	0.022
Low	0.842	0.403	4.362	1	0.037	2.321	1.053	5.117
Middle	1.042	0.378	7.582	1	0.006	2.835	1.350	5.953
Constant	−1.914	.425	20.254	1	< 0.001	0.148

* Variable(s) entered on step 1: Any financial hardship, In the past year have you Followed a budget or a savings plan, In the past year have you Saved for retirement or future expenses like your child’s education, education, rank, marital status, recoded # of children in household, family income.

CI = confidence interval, ref = reference, GED = General Educational Development, SE = standard error.

Logistic Regression Results for Insomnia

Model summary
Step	−2 log likelihood	Cox & Snell R2	Nagelkerke R2
1	932.168*	0.091	0.126

* Estimation terminated at iteration number 4 because parameter estimates changed by less than .001.

Variables in the equation

Step 1*	B	SE	Wald	df	p	Exp(B) odds ratio	95% CI
							Lower	Upper
Any financial hardship	1.143	0.172	44.042	1	< 0.001	3.136	2.238	4.395
In the past year have you followed a budget or a savings plan	0.081	0.176	0.211	1	0.646	1.084	0.768	1.529
In the past year have you saved for retirement or future expenses like your child’s education	−0.019	0.179	0.011	1	0.917	0.981	0.691	1.394
Education (ref = ≥bachelor’s degree)			4.078	2	0.130
High school or GED	−0.543	0.339	2.570	1	0.109	0.581	0.299	1.128
Some college or associate’s degree	−0.232	0.331	0.493	1	0.483	0.793	0.415	1.516
Rank (ref = officer)			6.084	2	0.048
Junior enlisted (E1-E4)	1.011	0.411	6.058	1	0.014	2.749	1.229	6.150
Senior enlisted (E5-E6)	0.884	0.406	4.733	1	0.030	2.420	1.092	5.366
Marital status (ref = separated or divorced)			2.852	2	0.240
Single (never married)	−0.211	0.201	1.097	1	0.295	0.810	0.546	1.202
Married	0.266	0.271	0.963	1	0.326	1.305	0.767	2.219
No. of children (ref = 0)			0.543	3	0.909
1	−0.033	0.239	0.019	1	0.891	0.968	0.606	1.545
2	0.163	0.266	0.374	1	0.541	1.177	0.698	1.983
≥3	0.090	0.288	0.097	1	0.755	1.094	0.622	1.925
Family income (ref = high)			1.308	2	0.520
Low	−0.301	0.289	1.082	1	0.298	0.740	0.420	1.305
Middle	−0.111	0.275	0.162	1	0.688	0.895	0.522	1.535
Constant	−1.357	0.347	15.334	1	< 0.001	0.257

* Variable(s) entered on step 1: Any financial hardship, In the past year have you Followed a budget or a savings plan, In the past year have you Saved for retirement or future expenses like your child’s education, education, rank, marital status, recoded # of children in household, family income.

CI = confidence interval, ref = reference, GED = General Educational Development, SE = standard error.

Logistic Regression Results for Self-Rated Overall Health

Model summary
Step	−2 log likelihood	Cox & Snell R2	Nagelkerke R2
1	646.485*	0.075	0.125

* Estimation terminated at iteration number 5 because parameter estimates changed by less than .001.

Variables in the equation

Step 1*	B	SE	Wald	df	p	Exp(B) odds ratio	95% CI
							Lower	Upper
Any financial hardship	−1.003	.213	22.223	1	< 0.001	0.367	0.242	0.557
In the past year have you followed a budget or a savings plan	0.088	0.220	0.161	1	0.688	1.092	0.710	1.681
In the past year have you saved for retirement or future expenses like your child’s education	0.192	0.224	0.735	1	0.391	1.211	0.781	1.878
Education (ref = ≥bachelor’s degree)			14.950	2	< 0.001
High school or GED	1.493	0.386	14.934	1	< 0.001	4.450	2.087	9.487
Some college or associate’s degree	1.202	0.375	10.254	1	0.001	3.327	1.594	6.944
Rank (ref = officer)			7.865	2	0.020
Junior enlisted (E1-E4)	−1.444	0.520	7.716	1	0.005	0.236	0.085	0.654
Senior enlisted (E5-E6)	−1.084	0.511	4.499	1	0.034	0.338	0.124	0.921
Marital status (ref = separated or divorced)			5.434	2	0.066
Single (never married)	0.016	0.258	0.004	1	0.952	1.016	0.612	1.685
Married	−0.681	0.311	4.794	1	0.029	0.506	0.275	0.931
No. of children (ref = 0)			4.318	3	0.229
1	−0.084	0.307	0.075	1	0.784	0.919	0.503	1.678
2	−0.558	0.329	2.879	1	0.090	0.572	0.300	1.090
≥3	−0.551	0.351	2.458	1	0.117	0.576	0.289	1.148
Family income (ref = high)			1.261	2	0.532
Low	−0.438	0.395	1.228	1	0.268	0.645	0.297	1.400
Middle	−0.265	0.385	0.473	1	0.492	0.767	0.361	1.632
Constant	2.444	.478	26.180	1	< 0.001	11.517

* Variable(s) entered in step 1: any financial hardship, in the past year have you followed a budget or a savings plan, in the past year have you saved for retirement or future expenses like your child’s education, education, rank, marital status, recoded number of children in household, family income.

CI = confidence interval, ref = reference, GED = General Educational Development, SE = standard error.

Logistic Regression Results for Physical Aggression

Model summary
Step	−2 log likelihood	Cox & Snell R2	Nagelkerke R2
1	635.037*	0.067	0.114

* Estimation terminated at iteration number 5 because parameter estimates changed by less than .001.

Variables in the equation

Step 1*	B	SE	Wald	df	p	Exp(B) odds ratio	95% CI
							Lower	Upper
Any financial hardship	1.033	0.212	23.851	1	< 0.001	2.811	1.857	4.255
In the past year have you followed a budget or a savings plan	0.260	0.228	1.303	1	0.254	1.297	0.830	2.027
In the past year have you saved for retirement or future expenses like your child’s education	0.324	0.224	2.104	1	0.147	1.383	0.892	2.144
Education (ref = ≥bachelor’s degree)			3.709	2	0.157
High school or GED	0.266	0.432	0.380	1	0.538	1.305	0.559	3.046
Some college or associate’s degree	−0.187	0.432	0.187	1	0.665	0.830	0.356	1.933
Rank (ref = officer)			2.137	2	0.344
Junior enlisted (E1-E4)	0.853	0.584	2.135	1	0.144	2.346	0.747	7.364
Senior enlisted (E5-E6)	0.723	0.576	1.578	1	0.209	2.061	0.667	6.371
Marital status (ref = separated or divorced)			5.267	2	0.072
Single (never married)	−0.598	0.261	5.253	1	0.022	0.550	0.330	0.917
Married	−0.159	0.342	0.216	1	0.642	0.853	0.437	1.667
No. of children (ref = 0)			0.868	3	0.833
1	−0.050	0.298	0.029	1	0.866	0.951	0.531	1.704
2	0.008	0.337	0.001	1	0.982	1.008	0.520	1.952
≥3	0.289	0.351	0.678	1	0.410	1.336	0.671	2.660
Family income (ref = high)			0.786	2	0.675
Low	0.320	0.403	0.629	1	0.428	1.377	0.625	3.035
Middle	0.133	0.395	0.114	1	0.736	1.143	0.527	2.478
Constant	−3.227	0.529	37.265	1	< 0.001	0.040

* Variable(s) entered in step 1: any financial hardship, in the past year have you followed a budget or a savings plan, in the past year have you saved for retirement or future expenses like your child’s education, education, rank, marital status, recoded number of children in household, family income.

CI = confidence interval, ref = reference, GED = General Educational Development, SE = standard error.

Funding Statement

No funding was received for this article.