Abstract
The stress of veterinary students ranges from the financial stress associated with high student loan debt combined with possible credit card debt, to relational stress due to lack of time to commit to social activities, to uncertainty regarding the ability to perform at the highest level. While this study considers a multifaceted approach to veterinary student stress and ultimate depressive symptoms, the focus is on the financial stress. A common strategy for reducing debt is to increase financial literacy. While this has the potential to help, it is not the sole solution given that students opt into the program for non-financial reasons. A path analysis was used to explore the predictors of financial satisfaction (the inverse of financial stress). The results were then used to predict depression among pre-vet and veterinary students in combination with relationship stress and demographic characteristics. Results indicate that current and expected student loan debt negatively influence financial satisfaction of pre-veterinary and veterinary students. Lower financial and relational satisfaction predict depressive symptoms among students. Among pre-veterinary students, feeling less intelligent than peers and being a sophomore versus a freshman is associated with depressive symptoms. Among current veterinary students, third-year students are more likely to report depressive symptoms than first-year students.
Student loans have received much attention in the popular press and the research literature, with much of the attention focused on undergraduate costs and benefits1,2 and undergraduate investment choices.3 It is well-understood that the costs of a veterinary education are also increasing due to decreased state funding.4 Veterinary student loan debt rose by over 5% in a 10-year time span.4 For veterinarians, student loan debt load averages $144,000 (the average increases to $168,000 when you exclude graduates with no student loan debt5). For graduates who defer their student loans to obtain internship or residency experience, their balance can easily double due to accrued interest. Students tend to underestimate their expected student loan debt accumulation by about $12,000.6 There is also the case of additional non-student loan debt, such as credit card debt, and the inability to find employment. Regardless of specific situations, the general picture is grim. The high debt loads can lead to depression and possibly even suicidal thoughts.7
The AVMA is aware of the debt problem and has formed the Fix the Debt Initiative.8 Among their strategies for reducing debt is increasing financial literacy. While this has the potential to help, it is not the sole solution given that students opt into the program for non-financial reasons.4 Increasing financial literacy may help with everyday matters, yet a more holistic approach that addresses the psychological dimension, including the motivation for pursuing veterinary medicine, seems warranted.
If students are opting into veterinary medicine for personal attachment reasons versus financial benefit, there is an enhanced concern about their understanding of eventual student loan burdens and implications. According to interim dean of veterinary medicine at one university, a large number of veterinary students apply to the program because of some attachment they have to animals. A pet may have been their best friend as a child—their confidant—who got them through hard times. Students may have a strong desire to save animals regardless of the costs (B. Rush, personal interview, 2017). This strong passion could be concerning from a mental health perspective in that veterinarians tend to share common personality characteristics that might predispose them to higher mental illness rates than the general population.9
There are some endogeneity issues to consider in terms of financial stress contributing to lower mental health well-being of veterinary students versus lower mental health status contributing to higher perceived financial stress. According to McLennan and Sutton,10 except for second-year students, finances ranked as the top one or two sources of stress in their life. The aim of this study is to first explore the predictors of financial satisfaction (the inverse of financial stress) and then use that to predict depression among pre-vet and veterinary students. Given the background literature in this area, descriptive statistics are also provided for current and expected student loan debt accumulation, financial literacy level, and mental health status of pre-vet and veterinary students.
Data collection was approved by the Kansas State University Institutional Review Board for Human Subjects. Data were collected during the first 2 weeks of the fall 2017 academic school year at a large public university in the Midwest. We emailed an online Qualtricsa survey link to two sample student populations: the first sample was drawn from a population of undergraduate college of agriculture pre-veterinary (pre-vet) students, and the second sample consisted of current graduate veterinary (vet) students. The undergraduate sample of pre-vet students had an estimated response rate of 28% (n = 224/~800 students). The vet students had an estimated response rate of 53% (n = 230/~430 students).
All descriptive statistics shown in Table 1 were self-reported. Demographic characteristics used as control variables in the path analysis included gender, race, year in the program, perceived intelligence, and small animal only focus. We measured perceived intelligence with the question “How would you rate your intelligence compared to your peers?” Responses were rated on a 5-point scale (1 = much lower than average, 2 = slightly below average, 3 = average, 4 = slightly better than average, 5 = much higher than average). Small animal only focus was coded “1” if respondents expected to work exclusively with small animals; otherwise, 0.
|
| Pre-vet students (N = 224) | Vet students (N = 230) | |||||
| Variable | M | SD | Range | M | SD | Range |
| Female | .85 | .36 | 0–1 | .87 | .34 | 0–1 |
| Age* | 19.42 | 2.20 | 17–40 | 24.57 | 2.75 | 21–43 |
| White | .88 | .32 | 0–1 | .93 | .25 | 0–1 |
| Freshman/1st year | .37 | .48 | 0–1 | .22 | .42 | 0–1 |
| Sophomore/2nd year | .27 | .45 | 0–1 | .30 | .46 | 0–1 |
| Junior/3rd year | .21 | .41 | 0–1 | .23 | .42 | 0–1 |
| Senior/4th year | .14 | .35 | 0–1 | .20 | .40 | 0–1 |
| House officer | – | – | 0–1 | .04 | .20 | 0–1 |
| Perceived intelligence | 3.72 | .69 | 2–5 | 3.29 | .81 | 1–5 |
| Small animal focus | .51 | .50 | 0–1 | .52 | .50 | 0–1 |
| Expected income | 2.28 | 1.16 | 1–7 | 2.20 | .96 | 1–6 |
| Current student loan debt ($) | 10,947 | 20,213 | 0–175,000 | 90,998 | 80,875 | 0–400,000 |
| Anticipated student loan debt ($) | 81,618 | 83,246 | 0–520,000 | 155,070 | 106,520 | 0–400,000 |
| Credit card debt ($) | 274.93 | 1,808 | 0–15,000 | 492.03 | 1,870 | 0–15,000 |
| Relational satisfaction | 5.33 | 1.49 | 1–7 | 5.01 | 1.67 | 1–7 |
| Financial satisfaction | 4.20 | 1.62 | 1–7 | 3.19 | 1.63 | 1–7 |
| Depressive symptoms | 4.92 | 4.83 | 0–27 | 7.02 | 5.12 | 0–24 |
* Age shown for descriptive purposes only; variable was not used in analyses
Financial knowledge (shown separately in Table 2) was captured by correct responses to three commonly accepted indicators of literacy.11 The first question was “Suppose you had $100 in a savings account and the interest rate was 2% per year. After 5 years, how much do you think you would have in the account if you let the money to grow?” Possible answers were “more than $102” (the correct response), “exactly $102,” “less than $102,” or “don’t know.” The second question was “Imagine that the interest rate on your savings account was 1% per year and inflation was 2% per year. After 1 year, how much would you be able to buy with the money in this account?” Possible answers were “more than today,” “exactly the same,” “less than today” (the correct response), or “don’t know.” The third question was “Finally, please tell me whether this statement is true or false: buying a single company’s stock usually provides a safer return than a stock mutual fund.” “False” was the correct response, with “don’t know” as an option choice. For students who answered “don’t know” or did not answer the questions, these were coded as incorrect options.
|
| National average of 23- to 28-year olds | Pre-vet | Vet | |
| Interest rate | 79.3 | 93.1 | 93.9 |
| Inflation | 54.0 | 74.2 | 88.5 |
| Risk diversification | 46.7 | 88.7 | 98.4 |
Financial knowledge was captured by correct responses to three commonly accepted indicators of literacy.11
We asked students to self-report their expected future income, current student loan debt, and the amount of debt they expect to accumulate before graduation, as well as their current credit card debt accumulation. Expected future income was selected from the following seven categories:
less than $60,000,
$60,001–$70,000,
$70,001–$80,000,
$80,001–$90,000,
$90,001–$100,000,
$101,001–$110,000, or
more than $110,000.
Debt levels were recorded on a continuous basis.
Outcomes for the path analysis included indicators of satisfaction and well-being as reported by the absence or presence of depressive symptoms. Respondents were asked to report their levels of financial satisfaction and relational satisfaction. Response options ranged from 1 = extremely dissatisfied to 7 = extremely satisfied.
Mental health status was captured by a nine-item depression inventory known as the Patient Health Questionnaire (PHQ-9).12 Students were asked how often they were bothered by each of the following nine symptoms over the past 2 weeks:
little interest or pleasure in doing things,
feeling down, depressed, or hopeless,
having difficulty sleeping,
feeling tired,
having poor appetite or overeating,
feeling like a failure or having let others down,
difficulty concentrating,
moving slowly or quickly, and
having self-harm or suicidal thoughts.
Response options included: 0 = not at all, 1 = several days, 2 = more than half the days, and 3 = nearly every day. Responses were summated for a total possible score of 0 to 27 with high reliability (α = .87). For the descriptive analysis, students were grouped into “moderate or above” depressive symptoms if they scored a 10 or higher; otherwise, they were coded 0 for “less than moderate” depressive symptoms. Correlation matrices for variables used in the path analyses are provided in Appendix 1 and Appendix 2.
The average student loan debt of pre-veterinary students was $10,947 (SD = $20,213, M = $19,157; SD = $23,647 when excluding students with no loans). Pre-veterinary students expect to accumulate a total of $81,618 in debt (SD = $83,246, M = $106,027; SD = $89,468 when excluding students with no current loans) before they finish their veterinary program. This is in stark contrast to the current debt of $90,997 for veterinary students (SD = $80,875, M = $103,362; SD = $78,418 when excluding students with no loans) with expected final debt of $155,070 (SD = $106,520, M = $176,401; SD = $98,285 when excluding students with no current loans).
Similar to Carr and Greenhill,6 we compared expected student loan debt accumulation to the average debt of recent graduates.5 While estimates do not account for inflation or increases in tuition, the story remains consistent in that students are grossly underestimating their total loan amounts. This is especially true for pre-veterinary students: pre-veterinary students expect to accumulate approximately $82,000 compared to the actual average of $144,000—a difference of $62,000. Current veterinary students are slightly closer to the $12,000 discrepancy reported by Carr and Greenhill, with an estimated debt accumulation of $155,000 or a difference of $11,000. Figure 1 illustrates the debt patterns of respondents.
Figure 1: Current and expected student loan debt accumulation
Contrary to hypotheses that financial literacy of veterinary students is suffering, this sample reported much higher financial literacy than the general population as shown in Table 2. The majority of pre-veterinary students (93%) and veterinary students (94%) correctly answered the interest rate question, compared to the national average of 79%.13 A much higher proportion of veterinary students (89%) correctly answered the inflation question compared to pre-veterinary students (74%), but both groups scored much higher than the national average of 54%. Nationally, 47% of young adults can correctly answer the risk diversification question. More than double the veterinary students (98%) correctly answered the question, and 89% of pre-veterinary students answered correctly. Cumulatively, pre-veterinary students scored 2.08/3 and veterinary students scored 2.28/3.
Consistent with prior studies,14,15 26% of veterinary students and 16% of pre-vet students met the initial screening cut-off criteria for moderate or above depressive symptoms. In a recent edition of this journal, Killinger et al.16 cited a rate of 66% for students who met criteria for mild depression or above as well as others reporting clinical rates of depression among 49% to 69% of students.17 When including students who meet the criteria for mild depression, the percentage of students meeting criteria for depressive symptoms increases to 63% (40% among pre-vet students). The estimate for veterinary students is closer to rates reported by Killinger et al. and Reisbig et al. Pre-veterinary students are also experiencing elevated depressive symptoms, although not to the same degree as current veterinary students, as shown in Figure 2.
Figure 2: Depressive symptoms by pre-vet versus current veterinary student status
From a stress and coping perspective, a higher degree of stressors with limited perceived resources to handle such events will be associated with higher distress.18 Resources, and constraints placed on resources (financial knowledge, expected income, current and expected student loans, and credit card debt), were conceptualized as direct influencers of financial satisfaction. Relational satisfaction, financial satisfaction, and demographic characteristics (i.e., gender, race, perceived intelligence, small animal focus, and year in the program) were hypothesized to influence depression.
The path analyses results are shown in Table 3 for pre-vet students and Table 4 for vet students; significant results are shown in the path diagram in Figure 3, and standardized coefficients are reported in this discussion. For the path analysis on the pre-vet student sample, the standardized root mean square residual (SMSR) was 0.034, and the comparative fit index (CFI) was 0.952. The literature suggests that SMSR should be less than 0.08 and CFI should be greater than 0.9519—both values indicate adequate model fit. For the vet student sample, the SMSR was 0.027, and the CFI was 0.975—again, both values indicate adequate model fit.
|
| Outcome | Predictor | Estimate | Standard error | p | |
| Financial satisfaction | ← | Expected income | 0.088 | (0.075) | 0.239 |
| ← | Current student loans | −0.135 | (0.008) | < .001 | |
| ← | Expected student loans | −0.150 | (0.008) | < .001 | |
| ← | Has credit card | 0.017 | (0.075) | 0.819 | |
| ← | Objective financial knowledge | −0.037 | (0.076) | 0.630 | |
| Depressive symptoms | ← | Financial satisfaction | −0.172 | (0.069) | 0.013 |
| ← | Relationship satisfaction | −0.242 | (0.071) | 0.001 | |
| ← | 2nd year | 0.159 | (0.080) | 0.046 | |
| ← | 3rd year | −0.029 | (0.081) | 0.717 | |
| ← | 4th year | 0.150 | (0.079) | 0.058 | |
| ← | Female | 0.057 | (0.072) | 0.431 | |
| ← | Non-white | −0.026 | (0.073) | 0.727 | |
| ← | Small animal focus | −0.017 | (0.073) | 0.821 | |
| ← | Self-rated intelligence relative to peers | −0.178 | (0.071) | 0.012 |
|
| Outcome | Predictor | Estimate | Standard error | p | |
| Financial satisfaction | ← | Expected income | 0.097 | (0.061) | 0.115 |
| ← | Current student loans | −0.194 | (0.009) | < .001 | |
| ← | Expected student loans | −0.321 | (0.014) | < .001 | |
| ← | Has credit card | −0.044 | (0.064) | 0.491 | |
| ← | Objective financial knowledge | 0.029 | (0.063) | 0.641 | |
| Depressive symptoms | ← | Financial satisfaction | −0.192 | (0.066) | 0.003 |
| ← | Relationship satisfaction | −0.211 | (0.068) | 0.002 | |
| ← | 2nd year | 0.098 | (0.087) | 0.259 | |
| ← | 3rd year | 0.179 | (0.086) | 0.037 | |
| ← | 4th year | −0.012 | (0.084) | 0.891 | |
| ← | House officer | 0.036 | (0.073) | 0.625 | |
| ← | Female | 0.097 | (0.067) | 0.148 | |
| ← | Non-white | −0.070 | (0.067) | 0.298 | |
| ← | Small animal focus | 0.029 | (0.069) | 0.670 | |
| ← | Self-rated intelligence relative to peers | −0.074 | (0.069) | 0.280 |
Figure 3: Path analysis results: standardized parameter estimates for significant effects
Only significant effects (p < .05) are shown in this figure; all variables with statistical significance are displayed in bold.
* p < .05
† p < .001
As shown in Table 3, the results indicate that pre-vet students with lower relational satisfaction (β = −.242, p = .001) and financial satisfaction (β = −.172, p = .013) were significantly more likely to report depressive symptoms. Although this result is unsurprising, the factors influencing financial satisfaction are interesting and useful. The results show that current and expected student loan amounts have a significant negative impact on financial satisfaction (β = −.135, p < .001, β = −.150, p < .001, respectively). Financial knowledge, expected income, and credit card debt did not have significant effects on financial satisfaction.
Of the demographic characteristics, only the self-reported intelligence and year in program had significant effects on depressive symptoms for pre-vet students. Pre-vet students who perceived themselves as more intelligent than their peers were less likely to report depressive symptoms (β = −.178, p = .012). Compared to freshmen, sophomores were significantly more likely to report depressive symptoms (β = .159, p = .046). Although most literature would suggest that females are more likely to suffer from depression than men,17 the results from the study indicated no significant difference between males and females in depressive symptoms. The result is likely due to the high proportion of females (85%) in the pre-vet sample so readers should interpret the results with caution.
As shown in Table 4, the results from the path analysis for vet students were very similar to the pre-vet student results. Vet students with lower relational satisfaction (β = −.211, p = .002) and financial satisfaction (β = −.192, p = .003) were significantly more likely to report depressive symptoms. Current student loans and expected student loans had a significant negative effect on financial satisfaction (β = −.194, p < .001 and β = −.321, p <.001, respectively) while expected income, financial knowledge, and credit card debt did not have a significant effect on financial satisfaction.
Among the demographic characteristics for vet students, only the year in the program had a significant effect on depressive symptoms. Compared to first-year students, third-year vet students were significantly more likely to report depressive symptoms (β = .179, p = .037). As in the pre-vet analysis, there were no significant differences between males and females in depressive symptoms, but readers should note the high proportion of women in the vet student sample (87%).
The data suggest that financial literacy is not the sole solution to the financial stress of veterinary students as pre-vet and vet students alike score much higher than national averages on a well-known financial literacy assessment and financial literacy was not a predictor of financial satisfaction or depressive symptoms. At the same time, pre-veterinary students grossly underestimate how much total debt they are likely to accumulate during professional school which suggests a certain level of financial naivety. The difference in mean expected debt accumulation among pre-vet and current veterinary students is approximately $73,000, as shown in Table 1.
Based on the prevailing predictors of reduced well-being, a 4-year financial therapy curriculum could suit the needs of students and college administrators struggling with the concerns of students. General financial literacy classes are likely to be ineffective in changing behaviors as noted by Carr and Greenhill,6 although education and classes targeted to relevant and timely information are more likely to be retained and applied. Therefore, we recommend that curricula focus on the significant financial-related predictors of depressive symptoms in this study, which include student loan debt awareness and reduction strategies. By focusing on these financial predictors of depressive symptoms, depression can be reduced indirectly through improvement of financial satisfaction and relational issues. Encouraging discussion of and access to personal financial planners will likely have a positive effect on financial satisfaction thereby reducing depressive symptoms among veterinary students.
While neither seems like an academic issue or a veterinary medicine issue, both financial and relational satisfaction significantly influences the rate of depressive symptoms. Encouraging non-academic social activities and inviting significant others and families to functions may influence higher perceived relational satisfaction.
Among veterinary students, third-year students experience significantly higher depressive symptoms as compared to first-year students. Giving particular attention to the needs of third-year students is necessary. As suggested by an anonymous reviewer, one possible explanation for the significant difference between first-year students and third-year students is the timing of the survey. Given that data was collected in the first 2 weeks of entering veterinary school, this time period is likely not representative of the entire first year and likely reflects a type of honeymoon period. Future research might explore this issue in more detail.
As a specific implementation strategy, programs are encouraged to adopt a self-study financial therapy curriculum where students work through exercises individually with required check-ins with a financial planner or counselor, university-sponsored financial counseling programs, and/or academic advisor. This will likely require dedicated resources from veterinary programs to ensure that students have access to needed professionals.
To learn more about financial counseling centers and functions they serve around the country, program leaders would benefit from reading the book Student Financial Literacy: Campus-Based Program Development or similar resources. Other potentially helpful national resources which highlight financial behaviors and needs of college students are available and could be used when developing new programs and services (e.g., Higher Education Financial Wellness Summit, Association for Financial Counseling and Planning Education, Symposium on Collegiate Financial Well-Being at NASPA—Student Affairs Administrators in Higher Education, Study on Collegiate Financial Wellness). By providing empirically-based activities structured to meet specific student needs, students will be able to work through activities when information is relevant.
a Qualtrics survey tool, Qualtrics International Inc., Provo, UT, USA. https://www.qualtrics.com/research-core/survey-software/
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| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | ||
| 1 | Female | 1.00 | – | – | – | – | – | – | – | – | – | – | – | – |
| 2 | Non-white | −0.17 | 1.00 | – | – | – | – | – | – | – | – | – | – | – |
| 3 | Year | −0.08 | 0.07 | 1.00 | – | – | – | – | – | – | – | – | – | – |
| 4 | Intelligence | 0.12 | −0.11 | −0.05 | 1.00 | – | – | – | – | – | – | – | – | – |
| 5 | Small animal focus | 0.07 | 0.08 | 0.00 | 0.14 | 1.00 | – | – | – | – | – | – | – | – |
| 6 | Expected income | −0.23 | 0.06 | −0.02 | 0.11 | −0.05 | 1.00 | – | – | – | – | – | – | – |
| 7 | Current student loan balance | 0.01 | −0.04 | 0.24 | −0.07 | −0.09 | −0.11 | 1.00 | – | – | – | – | – | – |
| 8 | Expected student loan balance | 0.03 | −0.19 | 0.21 | 0.01 | 0.06 | 0.10 | 0.47 | 1.00 | – | – | – | – | – |
| 9 | Has credit card | 0.12 | 0.09 | 0.23 | −0.01 | −0.05 | 0.00 | 0.09 | 0.05 | 1.00 | – | – | – | – |
| 10 | Financial knowledge | −0.15 | 0.02 | 0.18 | 0.00 | −0.10 | −0.08 | −0.07 | 0.13 | −0.10 | 1.00 | – | – | – |
| 11 | Financial satisfaction | 0.02 | 0.05 | −0.03 | 0.16 | 0.08 | 0.10 | −0.21 | −0.22 | 0.00 | −0.06 | 1.00 | – | – |
| 12 | Relational satisfaction | 0.11 | −0.13 | 0.21 | 0.10 | 0.06 | −0.09 | 0.04 | 0.11 | 0.18 | 0.04 | 0.24 | 1.00 | – |
| 13 | Depression | 0.00 | 0.03 | 0.03 | −0.22 | −0.11 | −0.06 | −0.03 | −0.03 | 0.01 | 0.04 | −0.27 | −0.28 | 1.00 |
|
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | ||
| 1 | Female | 1.00 | – | – | – | – | – | – | – | – | – | – | – | – |
| 2 | Non-white | 0.05 | 1.00 | – | – | – | – | – | – | – | – | – | – | – |
| 3 | Year | 0.04 | 0.08 | 1.00 | – | – | – | – | – | – | – | – | – | – |
| 4 | Intelligence | −0.07 | 0.02 | −0.01 | 1.00 | – | – | – | – | – | – | – | – | – |
| 5 | Small animal focus | 0.02 | 0.15 | −0.06 | 0.03 | 1.00 | – | – | – | – | – | – | – | – |
| 6 | Expected income | −0.14 | 0.06 | 0.05 | 0.10 | 0.12 | 1.00 | – | – | – | – | – | – | – |
| 7 | Current student loan balance | 0.03 | 0.09 | 0.51 | −0.01 | 0.06 | 0.10 | 1.00 | – | – | – | – | – | – |
| 8 | Expected student loan balance | −0.01 | 0.02 | 0.10 | −0.02 | 0.09 | 0.05 | 0.78 | 1.00 | – | – | – | – | – |
| 9 | Has credit card | −0.10 | −0.01 | 0.11 | 0.05 | 0.05 | −0.01 | 0.26 | 0.22 | 1.00 | – | – | – | – |
| 10 | Financial knowledge | −0.12 | −0.04 | 0.21 | 0.06 | −0.09 | 0.00 | 0.01 | −0.13 | 0.04 | 1.00 | – | – | – |
| 11 | Financial satisfaction | −0.15 | 0.04 | −0.19 | 0.07 | 0.02 | 0.08 | −0.46 | −0.48 | −0.16 | 0.07 | 1.00 | – | – |
| 12 | Relational satisfaction | −0.08 | 0.02 | 0.03 | 0.10 | 0.16 | −0.00 | 0.07 | 0.00 | 0.06 | 0.09 | 0.16 | 1.00 | – |
| 13 | Depression | 0.15 | −0.06 | 0.05 | −0.13 | −0.02 | −0.04 | 0.07 | 0.07 | 0.14 | −0.07 | −0.27 | −0.25 | 1.00 |
