Abstract
Background
College students are increasingly experiencing psychological distress, which adversely affects their academic performance, social functioning, and overall quality of life. While many studies have investigated the prevalence and correlates of psychological symptoms in this population, fewer have explored how psychological symptoms and their co-occurrence relate to self-reported mental health service needs.
Methods
We conducted a cross-sectional study involving 22,624 college students to explore the complex relationships between various psychological symptoms and their implications for self-reported mental health service needs. Standardized assessments, such as the Generalized Anxiety Disorder 7 (GAD-7), Patient Health Questionnaire 9 (PHQ-9), Insomnia Severity Index (ISI), and Impact of Event Scale (IES-R), were utilized to evaluate psychological symptoms. A self-developed questionnaire was used to gather data on mental health service requirements. Mediation analysis was used to explore the reciprocal mediation effects between different psychological symptoms on the self-reported mental health service needs. Network analysis was employed to explore the interrelationships between psychopathological symptoms and their impact on self-reported mental health service needs.
Results
Overall, 2.2% of all respondents and 5.0% of those with at least one psychological symptom reported mental health needs. Self-reported mental health needs differed among individuals with different psychological symptoms and comorbidity. Individuals with anxiety alone exhibited a higher self-reported mental health service needs compared to individuals with depression alone, insomnia alone, and PTSD alone. Unlike other comorbid conditions, anxiety comorbid with other symptoms does not significantly increase their self-reported mental health needs. Reciprocal mediation effects were observed between psychological symptoms and self-reported mental health service needs. Anxiety symptoms showed the strongest mediation effects, accounting for 42.7% of the total needs for depression symptoms, 42.2% for insomnia symptoms, and 44.6% for PTSD symptoms. Network analysis revealed that PHQ-9 item related to suicidal ideation (item 9) had the strongest correlation with self-reported mental health needs, with psychological hotline services and self-learning psychological knowledge being the preferred service types.
Conclusion
The self-reported mental health needs of college students are closely linked to their psychological symptoms and comorbidities, with anxiety playing a key mediating role in driving service demands. Universities should implement stratified interventions by prioritizing early anxiety screening and management, providing urgent support for suicidal thoughts, and reallocating resources toward symptom-specific care.
Keywords: College students, Self-reported mental health needs, Psychopathology, Comorbidity, Intervention
Introduction
In recent years, there has been increasing attention to mental health issues among college students, reflecting the unique challenges and pressures they face during psychological development and social adaptation [1–3]. College students are undergoing a critical transition from adolescence to adulthood, a phase that involves not only academic stress and anxiety about future career plans but also self-identity exploration and complex interpersonal relationships [4, 5]. The interplay of various factors significantly increases the vulnerability of this population to mental health issues, leading to a rising incidence of symptoms such as depression, anxiety, and emotional disorders [6, 7]. These symptoms negatively impact students’ academic performance, social abilities, and quality of life, and may pose serious threats to their overall health and future development [8, 9].
During the COVID-19 pandemic, college students experienced a range of acute stressors, including prolonged campus lockdowns, remote learning, social isolation, and uncertainty about the future. These environmental disruptions had a profound impact on their mental health. Previous studies have shown that the pandemic significantly increased the prevalence of negative psychological states among college students, such as depression, anxiety, and PTSD, while also influencing their mental health service needs [10–13]. Help-seeking is a complex process influenced by various individual and contextual factors [14, 15]. The pandemic may have reshaped students’ perceptions and willingness to engage with mental health services, thereby affecting both their preferences and expressed needs. A systematic review indicated that, during the early stages of the pandemic, many students experiencing notable psychological symptoms did not reach out for professional psychological support, revealing patterns of delayed or absent help-seeking [10]. A study among Vietnamese university students found that the high-pressure environment of COVID-19 heightened tendencies toward self-concealment, which in turn suppressed their willingness to seek external psychological assistance [16]. Similarly, a large-scale cross-sectional survey conducted in Germany found that nearly one-third of students were unaware of on-campus psychological services, and 17–19% reported unwillingness to seek help despite recognizing psychological issues [17].
Although research on mental health issues among college students has increased, most studies focus on the prevalence of psychological symptoms and their associated factors, with less emphasis on specific mental health service needs [18–21]. Particularly, there is a lack of research on the service needs of individuals who have been screened positive for symptoms [22].
Additionally, the phenomenon of comorbidity is widespread among college students. In comorbid states, individuals may experience multiple mental health symptoms simultaneously, leading to more complex symptom presentations and increasing the diversity and complexity of their mental health service needs [23]. For example, a student with depression who also exhibits anxiety symptoms may demonstrate different service needs compared to those with a single symptom. Comorbidity can not only exacerbate the severity of symptoms but also affect the specific needs and preferences for services [24]. Moreover, there may be variations in mental health service needs and their preferred forms between different symptom items, which remain unclear at present. By analyzing a large sample of 22,624 college students, we aim to utilize mediation and network analyses to investigate the complex relationships between various symptoms and their implications for mental health service needs. This approach will contribute to a more personalized and informed strategy for mental health support in academic settings, ultimately optimizing resource allocation and improving the effectiveness and quality of interventions.
Materials and methods
Study design
This cross-sectional study employed nonprobability sampling. Prior to data collection, a preparatory phase of approximately one month was conducted, which included campus-wide mental health awareness campaigns and educational lectures. Following this phase, an online questionnaire—hosted on a web-based platform and accessible via a Quick Response (QR) code—was distributed to WeChat groups of college students in Hebei Province. Specifically, data collection occurred between December 31, 2022, and January 7, 2023. A total of 25,737 pieces of poll data were collected and further analyzed. Electronic informed written consent was obtained from all respondents before data collection. The study was approved by the Ethics Committee of Peking University Sixth Hospital (Approval number: 2022-9-5-1).
Measurements
Sociodemographic characteristics and COVID-19 infection
The demographic questions were used to obtain sociodemographic data including gender, age, education, discipline classification. This study was conducted after the peak of the COVID-19 outbreak in China. Therefore, data on COVID-19 infection was also collected in this study and categorized into three groups: not infected, recovered from infection, and unrecovered from infection.
Self-reported mental health needs
A self-designed questionnaire was used to collect information on perception of need for mental health help:
Your current situation needs psychological support or counseling? (Yes/No)
-
Which of the following psychological interventions you are willing to accept (multiple responses):
- Face-to-face counseling
- Psychological hotline
- Online psychological counseling
- Self-learning psychological knowledge
Psychological symptoms
Generalized anxiety disorder 7-item (GAD-7) scale
The Generalized Anxiety Disorder 7 (GAD-7) scale was employed in this study to assess anxiety symptoms and determine their severity. This scale comprised seven items, with each item rated on a four-point scale: 0 (not at all), 1 (some of the time), 2 (more than half the time), and 3 (nearly every day). The total GAD-7 score ranges from 0 to 21. Based on the score, anxiety severity is classified as follows: 0–4 (no anxiety), 5–9 (mild anxiety), 10–14 (moderate anxiety), and 15 or more (severe anxiety). The scale has proven to be effective and reliable and is widely used in epidemiological surveys [25]. The internal consistency of the scale in this study, as measured by Cronbach’s alpha coefficient, was calculated to be 0.926, indicating high reliability.
Patient health questionnaire-9 (PHQ-9)
The Patient Health Questionnaire 9 (PHQ-9) scale was utilized in this study to assess depressive symptoms and determine their severity. This scale consisted of nine items, with each item rated on a four-point scale: 0 (not at all), 1 (some of the time), 2 (more than half the time), and 3 (nearly every day). The total PHQ-9 score ranges from 0 to 27. Based on the score, depression severity is categorized as follows: 0–4 (no depression), 5–9 (mild depression), 10–14 (moderate depression), 15–19 (moderate to severe depression), and 20 or more (severe depression). The scale has proven to be effective and reliable and is widely used in epidemiological surveys [26]. The internal consistency of the scale, as assessed by Cronbach’s alpha coefficient, was found to be 0.895, indicating good reliability.
Insomnia severity index (ISI)
The Insomnia Severity Index (ISI) scale, comprising seven items with scores ranging from 0 to 4, was employed in this study to screen for insomnia symptoms and assess their severity. The total score on the ISI scale ranges from 0 to 28. Insomnia severity is classified as follows: 0–7 (no insomnia), 8–14 (mild insomnia), 15–21 (moderate insomnia), and 22 or more (severe insomnia). The scale has proven to be effective and reliable and is widely used in epidemiological surveys [27, 28]. The internal consistency of the scale, as measured by Cronbach’s alpha coefficient, was found to be 0.905 in this study, indicating a high level of reliability.
Impact of events scale-revised (IES-R)
The Impact of Event Scale-Revised (IES-R), developed by Weiss and Marmar, is a self-report questionnaire comprising 22 items that align with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria for post-traumatic stress disorder (PTSD) [29]. Participants use a scale ranging from 0 (not at all) to 4 (extremely) to indicate the level of distress experienced over the past seven days for each item. The total score on the IES-R ranges from 0 to 88. Based on the scores, psychological impact is categorized as follows: 0–23 (usual psychological impact), 24–32 (mild), 33–36 (moderate), and 37 or more (severe). The scale has proven to be effective and reliable and is widely used in epidemiological surveys [30, 31]. In this study, the Cronbach’s alpha coefficient for the IES-R scale was calculated to be 0.953, indicating a very high level of internal consistency and reliability. In light of the conditions for using the scale previously published online by Professor Daniel S.Weiss, the author of the scale, the relevant circumstances are explained as follows: Prior to publication, we attempted to contact Dr. Weiss through multiple available channels to obtain formal permission, but failed to establish direct communication. According to a 2019 publication, Dr. Weiss stated that the Impact of Event Scale-Revised (IES-R) is “out of copyright” and may be freely used for academic purposes [32]. In accordance with this statement, we confirm that the use of the IES-R in this study fully complies with the following principles: it is strictly for non-commercial use, without any modifications, and with full attribution to its original source.
Statistical analyses
Descriptive analysis was performed using absolute and prevalence for categorical variables. Bootstrapping was used to estimate 95% confidence interval (95% CI), offering distribution-free intervals robust to skewed proportions. The chi-square test was used to compare the proportions. Univariate and multivariate logistic regression models were performed to estimate the odds ratio (OR) with a 95% CI of psychological symptoms and psychological comorbidities on self-reported mental health needs among college students. This comprehensive analysis aimed to quantify the strength and direction of the relationships between individual psychological symptoms and their combined effects on the demand for mental health services. The mediation command in Stata was employed to examine the reciprocal mediation effects among various psychological symptoms and their impact on mental health service needs. This analysis aimed to uncover how different symptoms interact and mediate each other’s effects on the demand for mental health services. Statistical tests were two-tailed with p < 0.05, and data were analyzed by STATA 18.0 (StataCorp, College Station, Texas, USA).
Network analysis was conducted using R (Version 4.3.3) to explore the associations between individual symptoms and specific types of mental health services [33]. This analytical approach enabled the creation of detailed networks that illustrate how various psychological symptoms are interconnected and how these connections influence the need for particular forms of mental health support. In the network model, each symptom was represented as a node, with edges denoting pairwise correlations between nodes. The network structure was estimated using the “Estimate Network” function from the “bootnet” package, employing the Gaussian graphical model with EBIC for edge shrinkage (tuning parameter = 0.5) [34]. Spearman’s correlation method was used due to the ordinal nature of the data. The “qgraph” package was utilized to visualize the network, with edge thickness indicating the strength of associations, purple edges representing positive associations, and red edges representing negative associations [35]. Additionally, self-reported mental health needs were incorporated into the psychological symptoms network to explore their associations with the symptoms.
Results
Sociodemographic characteristics and self-reported mental health needs
After excluding 3,113 cases with incomplete information or suspected random responses (response time fewer than 150 s), a total of 22,624 college students were included in the final analysis. These students had a median age of 20.4 years (interquartile range, 19.3–21.5). Among the included participants, 53.5% were female, 69.7% were undergraduates, and 11.4% were majoring in medicine (see Table 1). Additionally, 2.2% reported a need for mental health services. The self-reported prevalence rates of anxiety symptoms, depression symptoms, insomnia symptoms, and PTSD symptoms were found to be 12.7% (n = 2,869), 25.8% (n = 5,836), 11.6% (n = 2,616), and 7.9% (n = 1,783) respectively. Overall, a total of 6,723 college students reported experiencing at least one of the four symptoms, resulting in a prevalence rate of 29.7%.
Table 1.
Characteristic distribution of anxiety, depression, insomnia, and PTSD among 22,624 college students
| Characteristic | Group | N(%) | Anxiety | Depression | Insomnia | PTSD |
|---|---|---|---|---|---|---|
| Prevalence (95%CI) | Prevalence (95%CI) | Prevalence (95%CI) | Prevalence (95%CI) | |||
| Gender | Male | 10,527(46.5) | 12.2(11.6–12.9) | 23.7(22.8–24.6) | 11.6(11.1–12.2) | 7(6.5–7.6) |
| Female | 12,097(53.5) | 13.1(12.5–13.7) | 27.6(26.7–28.6)⁎⁎⁎ | 11.5(11.0–12.0) | 8.7(8.2–9.2)⁎⁎⁎ | |
| Major | Medicine | 2579(11.4) | 13.3(12.1–14.5) | 26.7(25.4–28.0) | 11.7(10.3–13.2) | 9.5(8.2–11.0) |
| Others | 20,045(88.6) | 12.6(12.2–13.0) | 25.7(25.1–26.3) | 11.5(11.2–12.0) | 7.7(7.3–8.1)⁎⁎ | |
| Education level | Junior college | 6821(30.3) | 10.6(9.9–11.4) | 21.0(20.0–22.1) | 11.4(10.6–12.1) | 6.5(5.9–7.2) |
| Undergraduate | 15,803(69.7) | 13.6(13.0–14.1)⁎⁎⁎ | 27.9(27.2–28.6)⁎⁎⁎ | 11.6(11.2–12.1) | 8.5(8.0–9.0)⁎⁎⁎ | |
| Need for mental health services | Yes | 486(2.2) | 54.7(50.3–59.1) | 65.4(61.1–69.5) | 45.7(41.3–50.1) | 37.9(33.6–42.3) |
| No | 22,138(97.8) | 11.8(11.3–12.2) ⁎⁎⁎ | 24.9(24.4–25.5) ⁎⁎⁎ | 10.8(10.4–11.2) ⁎⁎⁎ | 7.2(6.9–7.6) ⁎⁎⁎ |
Note: ‶**″ p < 0.01, ‶***″ p < 0.001
Self-reported mental health needs of individuals with psychological symptoms
In total, 340 individuals, representing 5.1% (n = 340) of those experiencing psychological symptoms, reported a need for mental health services. Among them, individuals with PTSD had the highest reported need for mental health services at 10.3% (n = 184), followed by those with anxiety at 9.2% (n = 266), individuals with insomnia at 8.4% (n = 222), and those with depression at 5.4% (n = 318). However, after excluding comorbid psychological symptoms, individuals with isolated anxiety symptoms reported the highest need for mental health services at 5.4% (n = 9). Furthermore, among college students experiencing psychological symptoms, there were significant variations in the need for mental health services based on the severity of their symptoms. Notably, individuals rated as severe or extremely severe exhibited the highest need (p < 0.05, see Table 2).
Table 2.
Self-reported mental health needs of individuals with psychological symptoms (N = 6723)
| With psychological symptoms (n) |
Reported mental health needs (N) |
Corresponding rates (95%CI) | |
|---|---|---|---|
| Anxiety | |||
| Mild | 2217 (77.3%) | 155 (58.3%) | 7.0(6.0-8.2) |
| Moderate | 471 (16.4%) | 66 (24.8%) | 14.0(10.7–18.1) |
| Severe | 181 (6.3%) | 45 (16.9%) | 24.9(19.5–31.1)*** |
| Total | 2869 | 266 | 9.2(8.3–10.3) |
| Depression | |||
| Mild | 4006 (68.6%) | 125 (39.3%) | 3.1(2.7–3.7) |
| Moderate | 1205 (20.6%) | 91 (28.6%) | 7.6(6.3–9.1) |
| Severe | 444 (7.6%) | 61 (19.2%) | 13.7(10.5–17.8) |
| Extremely Severe | 181 (3.1%) | 41 (12.9%) | 22.7(16.4–30.4)*** |
| Total | 5836 | 318 | 5.4(5.0-5.9) |
| Insomnia | |||
| Mild | 2162 (82.6%) | 141 (63.5%) | 6.5(5.7–7.5) |
| Moderate | 370 (14.1%) | 56 (25.2%) | 15.1(11.5–19.6) |
| Severe | 84 (3.2%) | 25 (11.3%) | 29.8(20.7–40.7)*** |
| Total | 2616 | 222 | 8.4(7.5–9.6) |
| PTSD | |||
| Mild | 999 (56.0%) | 60 (32.6%) | 6.0(4.9–7.4) |
| Moderate | 188 (10.5%) | 15 (8.2%) | 8.0(5.0-12.4) |
| Severe | 596 (33.4%) | 109 (59.2%) | 18.3(15.7–21.3)*** |
| Total | 1783 | 184 | 10.3(9.0-11.8) |
| Comorbidity | |||
| Anxiety only | 166 (2.5%) | 9 (2.6%) | 5.4(2.7–10.6) |
| depression only | 2350 (35.0%) | 31 (9.1%) | 1.3(0.9–1.9) |
| Insomnia only | 344 (5.1%) | 3 (0.9%) | 0.9(0.2–3.1) |
| PTSD only | 230 (3.4%) | 3 (0.9%) | 1.3(0.5–3.1) |
| Any two | 1747 (26.0%) | 75 (22.1%) | 4.3(3.5–5.3) |
| Three and above | 1886 (28.1%) | 129 (37.9%) | 11.6(10.2–13.2)*** |
| Total | 6723 | 340 | 5.1(4.6–5.6) |
Note: *** p < 0.001
Self-reported mental health needs of individuals with psychological comorbidities
Results indicated that the presence of anxiety comorbid with other symptoms does not significantly increase the rate of self-reported mental health needs compared to anxiety alone (see Table 3). However, comorbid anxiety, insomnia, and more than three other symptoms were independently associated with greater self-reported mental health needs in individuals with depression symptoms. Similarly, comorbid depression, PTSD, and more than three other symptoms were independently linked to increased self-reported mental health needs in those with insomnia symptoms. For cases with PTSD symptoms, comorbid depression and more than three other symptoms were independently associated with higher self-reported mental health needs. Furthermore, individuals with anxiety alone were found to have more self-reported mental health needs compared to those with depression alone.
Table 3.
Relationship between Self-reported mental health needs and psychological comorbidity
| Variable | Self-reported mental health needs | |
|---|---|---|
| Crude OR (95%CI) |
Adjusted OR (95%CI) | |
| Anxiety† | ||
| Comorbidity none(Anxiety only) | 1 | 1 |
| Comorbidity depression | 0.89(0.43–1.86) | 0.90(0.43–1.88) |
| Comorbidity insomnia | 0.55(0.07–4.45) | 0.36(0.04–3.08) |
| Comorbidity PTSD | 0.76(0.09–6.27) | 0.67(0.08–5.54) |
| Comorbidity Three and above | 0.94(0.47–1.85) | 1.50(0.67–3.35) |
| Depression† | ||
| Comorbidity none(Depression only) | 1 | 1 |
| Comorbidity anxiety | 3.82(2.40–6.09)*** | 3.82(2.40–6.09)*** |
| Comorbidity insomnia | 2.49(1.38–4.48)** | 1.75(0.82–3.70) |
| Comorbidity PTSD | 3.91(1.77–8.66)** | 3.85(1.74–8.54)** |
| Comorbidity Three and above | 7.13(4.88–10.4)*** | 6.36(3.62–11.18)*** |
| Insomnia† | ||
| Comorbidity none(Insomnia only) | 1 | 1 |
| Comorbidity anxiety, | 3.55(0.36–35.15) | 3.33(0.34–33.10) |
| Comorbidity depression | 3.78(1.11–12.94)* | 3.66(1.07–12.56)* |
| Comorbidity PTSD | 5.50(1.09–27.88)* | 5.29(1.04-27.00)* |
| Comorbidity Three and above | 6.62(2.11–20.75)** | 13.30(4.20-42.06)*** |
| PTSD† | ||
| Comorbidity none(PTSD only) | 1 | 1 |
| Comorbidity anxiety | 3.29(0.33–32.93) | 2.90(0.29–29.21) |
| Comorbidity depression | 3.96(1.03–15.15)* | 4.06(1.06–15.55)* |
| Comorbidity insomnia | 3.66(0.72–18.59) | 2.35(0.43–12.83) |
| Comorbidity Three and above | 4.16(1.32–13.05)* | 6.72(1.98–22.79)** |
| Psychological symptoms and comorbidity⸸ | ||
| Depression only | 1 | 1 |
| Anxiety only | 4.29(2.01–9.17)*** | 4.22(1.97–9.03)*** |
| Insomnia only | 0.66(0.20–2.16) | 0.62(0.19–2.04) |
| PTSD only | 0.99(0.30–3.26) | 0.97(0.29–3.19) |
| Comorbidity, any two | 3.36(2.20–5.12)*** | 3.32(2.18–5.08)*** |
| Comorbidity, three and above | 9.83(6.71–14.39)*** | 9.48(6.47–13.89)*** |
Note: “†" Adjusted for age, gender, education level, major, COVID-19 infection and symptom severity in multivariable logistic regression model,”⸸” Adjusted for age, gender, education level, major, COVID-19 infection in multivariable logistic regression model, ‶*″ p < 0.05, ‶**″ p < 0.01, ‶***″ p < 0.001
Reciprocal mediation effects among psychological symptoms and self-reported mental health service needs
The results of the mediation analysis reveal widespread reciprocal mediation effects among different psychological symptoms and self-reported mental health service needs. Anxiety symptoms exhibit the strongest mediation effects, mediating 42.7%(see Table 4), 42.2%, and 44.6% of the total self-reported mental health service needs associated with depression, insomnia, and PTSD symptoms, respectively. PTSD symptoms follow, mediating 40.4% of the effect on insomnia and 25.2% on anxiety. Insomnia symptoms mediate 21.8% of the effect on anxiety and 37.2% on PTSD. Finally, the mediation effect of depression symptoms is relatively weaker, mediating only 5% of the effect on anxiety-related self-reported mental health service needs.
Table 4.
Reciprocal mediation effects analysis among psychological symptoms and self-reported mental health service needs*
| Path | Coefficient | 95%CI | Path | Coefficient | 95%CI |
|---|---|---|---|---|---|
| Depression→Anxiety→Mental Health Need | Anxiety→Depression→Mental Health Need | ||||
| Indirect Effect | 0.013*** | 0.010–0.016 | Indirect Effect | 0.004** | 0.001–0.006 |
| Direct Effect | 0.017** | 0.006–0.029 | Direct Effect | 0.069*** | 0.057–0.080 |
| Total Effect | 0.030*** | 0.019–0.042 | Total Effect | 0.072*** | 0.061–0.084 |
| Proportion being Mediated | 42.70% | 25.8%−59.5% | Proportion being Mediated | 5.0% | 1.5%−8.4% |
| Insomnia→Anxiety→Mental Health Need | Insomnia→Depression→Mental Health Need | ||||
| Indirect Effect | 0.023*** | 0.018–0.028 | Indirect Effect | −0.006*** | −0.008–0.004 |
| Direct Effect | 0.031*** | 0.021–0.041 | Direct Effect | 0.060*** | 0.048–0.073 |
| Total Effect | 0.054*** | 0.042–0.066 | Total Effect | 0.054*** | 0.042–0.066 |
| Proportion being Mediated | 42.20% | 33.2%−51.2% | Proportion being Mediated | - | - |
| PTSD→Anxiety→Mental Health Need | PTSD→Depression→Mental Health Need | ||||
| Indirect Effect | 0.031*** | 0.023–0.039 | Indirect Effect | −0.008*** | −0.011–0.005 |
| Direct Effect | 0.038*** | 0.025–0.051 | Direct Effect | 0.077*** | 0.061–0.093 |
| Total Effect | 0.069*** | 0.054–0.084 | Total Effect | 0.069*** | 0.054–0.084 |
| Proportion being Mediated | 44.60% | 33.5%−55.8% | Proportion being Mediated | - | - |
| Anxiety→Insomnia→Mental Health Need | Anxiety→PTSD→Mental Health Need | ||||
| Indirect Effect | 0.016*** | 0.011–0.021 | Indirect Effect*** | 0.018 | 0.012–0.024 |
| Direct Effect | 0.056*** | 0.046–0.067 | Direct Effect*** | 0.054 | 0.043–0.065 |
| Total Effect | 0.072*** | 0.061–0.084 | Total Effect*** | 0.072 | 0.061–0.083 |
| Proportion being Mediated | 21.80% | 15.1%−28.5% | Proportion being Mediated | 25.20% | 17.3%−33.2% |
| Depression→Insomnia→Mental Health Need | Depression→PTSD→Mental Health Need | ||||
| Indirect Effect | −0.011*** | −0.014–0.007 | Indirect Effect*** | −0.012 | −0.016–0.009 |
| Direct Effect | 0.041*** | 0.029–0.054 | Direct Effect*** | 0.043 | 0.03–0.056 |
| Total Effect | 0.030*** | 0.019–0.042 | Total Effect*** | 0.030 | 0.019–0.042 |
| Proportion being Mediated | - | - | Proportion being Mediated | - | - |
| PTSD→Insomnia→Mental Health Need | Insomnia→PTSD→Mental Health Need | ||||
| Indirect Effect | 0.026*** | 0.018–0.034 | Indirect Effect*** | 0.022 | 0.016–0.028 |
| Direct Effect | 0.044*** | 0.030–0.057 | Direct Effect*** | 0.032 | 0.022–0.043 |
| Total Effect | 0.069*** | 0.055–0.084 | Total Effect*** | 0.054 | 0.043–0.066 |
| Proportion being Mediated | 37.20% | 26.0%−48.5% | Proportion being Mediated | 40.40% | 29.4%−51.3% |
Note: “*” Adjusted for age, gender, education level, major and COVID-19 infection,, ‶**″ p < 0.01, ‶***″ p < 0.001; “-” Proportions not reported for effects with opposite signs among indirect, direct, and total effects.
Network analysis between psychological symptoms and self-reported mental health needs
Figure 1 illustrates the flow diagram of psychological symptoms and self-reported mental health needs. Within this network, 14 individual symptoms occupy central positions directly associated with self-reported mental health needs, with PHQ-item 9 (death) in the context of depression showing the strongest correlation. For depressive symptoms, the strongest correlation with self-reported mental health needs was PHQ-item 9 (death), followed by PHQ-item 6 (worthlessness) and PHQ-item 2 (sad mood). For anxiety, the strongest correlation with self-reported mental health needs was GAD-item 2 (uncontrollable worry), followed by GAD-item 4 (trouble relaxing). In terms of insomnia symptoms, ISI-item 7 (sleep-induced distress) showed the strongest correlation with self-reported mental health needs, followed by ISI-item 5 (daytime dysfunction) and ISI-item 3 (early awakening). For PTSD symptoms, the strongest correlation with self-reported mental health needs was IESR3(hyperarousal), followed by IESR1(avoidance).
Fig. 1.
Flow network illustrating the relationship between symptom items and self-reported mental health needs. Note: The edge thickness indicates the strength of associations
Furthermore, a network analysis of various forms of mental health services corresponding to the symptom network uncovered distinct preferences among individuals with different symptoms (see Fig. 2). Specifically, IESR3 (hyperarousal) and GAD-item 4 (trouble relaxing) exhibited the strongest demand for self-learning psychological knowledge, while ISI-item 3 (early awakening) had the highest need for face-to-face counseling. GAD-item 2 (uncontrollable worry) showed a strong preference for online psychological counseling. It’s worth noting that, unlike other PHQ symptom items, PHQ-item 9 (death) had the most pronounced need for psychological hotline services.
Fig. 2.
Flow network illustrating the relationship between symptom items and preferred services. Note: The edge thickness indicates the strength of associations
Discussion
Psychological symptoms and self-reported mental health needs
This study represents one of the largest sample investigations conducted to date, aiming to examine the self-reported mental health needs of college students. The study findings revealed that a mere 5.1% of college students exhibiting psychological symptoms expressed a perceived need for mental health services. This proportion was found to be lower compared to the findings of previous studies [36–39]. In comparison, the World Mental Health International College Student (WMH-ICS) survey found that 24.6% of all students would definitely seek treatment if they experienced emotional problems in the future [38]. A meta-analysis focusing on students with self-reported symptoms or screening-positive results reported that 41% of students expressed willingness to seek help, yet only 28% had actually sought professional psychological support [40]. Several factors may account for this disparity, including variations in cultural settings, target populations, measurement approaches, and investigation periods. Previous research has highlighted several potential reasons for the low help-seeking behavior among college students with psychological symptoms, such as the stigmatization of mental health issues, lack of awareness about available services, limited accessibility to on-campus resources, insufficient support systems, cultural influences, as well as a tendency towards self-reliance and resilience [36, 37, 41, 42]. Furthermore, the relatively low demand for services is also associated with the smaller proportion of individuals rated as having severe symptoms. Nevertheless, the relatively low rate of utilization raises significant questions regarding the barriers and factors that influence the decision-making process among college students when it comes to seeking mental health services. Among the respondents experiencing various psychological symptoms, individuals with severe or severe mental symptoms expressed the highest likelihood of seeking mental health services, which is not surprising. Individuals with severe mental health symptoms may experience more intense and persistent psychological distress, which makes them more likely to report an unmet need for psychological services [43]. Therefore, they are more likely to recognize the need for professional support and interventions to address their mental health needs [44].
Psychological comorbidities and self-reported mental health needs
Additionally, the presence of comorbid anxiety alongside other symptoms does not significantly increase the rate of self-reported mental health needs when compared to isolated anxiety alone. However, when compared to isolated depression, isolated insomnia, or isolated PTSD, the presence of comorbid other symptoms tends to result in a higher rate of self-reported mental health needs. Our findings extends previous findings by clearly showing that specific symptom combinations, rather than comorbidity in general, drive differences in self-reported mental health needs. Notably, among individuals with depression, comorbid anxiety significantly increases perceived need for care. Similarly, for those with insomnia or PTSD, comorbid depression and PTSD symptoms are associated with higher mental heatlh needs. Neurobiological evidence indicates that anxiety enhances threat sensitivity and functional impairment awareness. It independently promotes help-seeking regardless of comorbidities [45]. Depression and PTSD involve avoidance mechanisms that suppress service recognition [46, 47]. These patterns highlight that certain combinations of symptoms contribute more strongly to help-seeking behavior, and should be prioritized in clinical assessments and interventions. One possible explanation for this finding is that anxiety symptoms can have a significant impact on individuals’ daily lives and functioning, leading to higher levels of perceived mental health needs [44, 48]. Another explanation may be that anxiety symptoms are associated with higher levels of psychological distress and unmet need for care [49], which may drive individuals to seek mental health services more actively. Individuals with anxiety symptoms may be more aware and able to identify and express their mental health needs compared to those experiencing other conditions like depression or PTSD [50, 51]. While prior studies have emphasized the overall association between comorbidity and service needs [52, 53], they have largely focused on comorbidity as a general construct, without delineating how specific symptom combinations may differ in shaping perceived needs. In contrast, our analysis distinguishes between various comorbid profiles and reveals which combinations are more likely to elicit help-seeking, offering empirical evidence for more precise identification of high-need subgroups.
Moreover, individuals with anxiety symptoms mediate a significant proportion of the mental health service needs associated with other psychological symptoms. The strong mediating effect of anxiety symptoms can be attributed to their widespread impact on other psychological symptoms, high comorbidity rates, strong interference, and their early facilitation of service needs [54]. Previous studies have highlighted the prevalence of mental health problems among college students and their substantial influence on service needs [55, 56], but few have explicitly investigated whether anxiety plays a mediating role in models of service utilization. Our findings fill this gap by demonstrating the mediating pathway of anxiety symptoms in shaping service demand, thus providing a more nuanced theoretical basis for assessment and intervention design. These findings indicate that clinical practice may benefit from paying particular attention to anxiety symptoms among college students, especially when intervening in other psychological issues such as depression, insomnia, and PTSD. High levels of anxiety symptoms may exacerbate other mental health problems and affect patients’ willingness to seek help. Therefore, a comprehensive intervention strategy should be employed during interventions, focusing on the management of anxiety symptoms to effectively enhance the fulfillment of overall mental health service needs.
Network analysis between psychological symptoms and self-reported mental health needs
Network analysis found that the demand for mental health services is highest for PHQ-item 9 (death), reflecting the urgent need for rapid and effective intervention for individuals with suicidal thoughts and severe depression. In terms of specific service preferences, PHQ-item 9 (death) has the strongest need for psychological hotline services. In crisis situations, psychological hotlines not only provide timely support and intervention but also protect privacy, helping individuals quickly access help and resources to prevent suicide risk [57, 58]. For other symptoms, individuals with IESR3 (hyperarousal) and GAD-item 4 (trouble relaxing) may prefer self-learning psychological knowledge. This pattern may reflect a preference for self-management strategies and tools to cope with psychological symptoms, reflecting their desire to master coping skills and knowledge at their own pace for better understanding and management of their symptoms. Individuals with ISI-item 3 (early awakening) have the highest need for face-to-face counseling, which may indicate that their sleep issues exhibit significant individual variability. People with insomnia tend to prefer psychological approaches over pharmacological ones, which often leads to better adherence [59, 60]. Furthermore, face-to-face interactions may allow for more targeted assistance. This type of consultation allows professionals to gain a deeper understanding of specific issues and develop personalized intervention strategies, especially for managing complex insomnia symptoms. Individuals with GAD-item 2 (uncontrollable worry) prefer online psychological counseling, possibly due to the privacy and flexibility of online services, allowing them to seek help without revealing their identity [61]. This type of service may be more suitable for those with persistent worries who prefer not to engage in face-to-face communication. Based on the above analysis, more targeted intervention strategies can be primarily developed: Crisis Intervention: For individuals with suicidal thoughts, prioritize psychological hotline and emergency intervention services to ensure timely help during crises; Self-Management and Education: For individuals with anxiety and PTSD symptoms, prioritize interventions focusing on self-learning psychological knowledge and self-management strategies to help them master coping skills; Personalized Face-to-Face Consultation: For insomnia symptoms, particularly early awakening, face-to-face counseling can offer detailed assessment and customized treatment plans; Flexible Online Services: For those who value privacy and convenience, online psychological counseling can serve as an effective supplementary service. In summary, a detailed analysis of psychological symptoms and self-reported mental health needs helps optimize service allocation, ensuring that with different symptoms receive the most appropriate support.
Implications
This study underscores the critical need for stratified and targeted mental health interventions within university settings. Given the pronounced mediating role of anxiety symptoms in amplifying mental health service demands, universities may need to consider prioritizing early identification and intervention for anxiety symptoms. This effect goes beyond the impact of depression, insomnia, or PTSD alone. Early identification should be achieved through routine screening embedded in campus health systems. Counseling centers could consider developing specialized protocols for anxiety management, including scalable cognitive-behavioral therapy modules and peer-support networks, to mitigate its cascading effect on comorbid conditions. Furthermore, the acute service needs among students with suicidal or self-harming thoughts highlight the potential importance of structural adaptations. For example, 24/7 crisis hotlines staffed by clinicians trained in suicide risk assessment, coupled with curated digital self-help repositories must be accessible as zero-barrier entry points. Universities could move beyond diagnostic categories when allocating mental health resources, redirecting funding toward symptom-specific pathways. For instance, this could include establishing insomnia clinics with trauma-informed sleep coaches or PTSD support groups co-facilitated by survivors. Ultimately, integrating these approaches requires collaborative frameworks where counseling centers, academic departments, and student unions coordinate to embed mental health stewardship into institutional culture. This spans from training faculty to recognize symptom escalation to implementing policy reforms that mandate wait-time standards for high-risk students.
Limitations
Several limitations of the study should be considered. Firstly, The cross-sectional study design limits the ability to establish causal relationships, emphasizing the need for further longitudinal research. Secondly, we utilized a nonprobability sample survey instead of a random one, the sample may not fully represent the entire college student population, especially those from different regions and cultural settings. Thirdly, the study primarily relied on self-reported questionnaires to assess psychological symptoms and mental health service needs. This self-report method may be subject to bias influenced by the respondents’ subjective opinions. Lastly, the observed relationship between psychological symptoms and self-reported mental health service needs is based on correlation rather than causation, and causality cannot be definitively determined. Additionally, The PHQ-9 is a scale designed to assess depression symptoms, and a single item cannot fully capture the complexity of suicidal ideation or other symptoms. However, the study also has some strengths. Firstly, by utilizing a large sample size, the research may yield more persuasive and reliable results, aiding in a more comprehensive understanding of the different self-reported mental health needs among college students. Secondly, despite the risks of representativeness, this study is the first to report, in a large-scale population survey, the preferred forms of psychological intervention that college students with psychological symptoms find acceptable.
Conclusion
The self-reported mental health needs of college students and the types of services they seek appear to be associated with the types of psychological symptoms and comorbidities they experience. Individuals with anxiety symptoms alone not only have higher self-reported mental health service needs compared to those with depression, insomnia, or PTSD alone, but also play a significant mediating role in the impact of other psychological symptoms on self-reported mental health needs. Additionally, individuals with suicidal or self-harming thoughts show the strongest demand for services, particularly for psychological hotline services and self-learning resources. Therefore, when developing intervention strategies for college students, it may be important to consider not only the needs at the disease level but also the specific service needs at the symptom level, especially those related to suicide risk.
Acknowledgements
None.
Abbreviations
- GAD-7
Generalized anxiety disorder 7
- PHQ-9
Patient health questionnaire 9
- ISI
Insomnia severity index
- IES-R
Impact of event scale-revised
- PTSD
Post-traumatic stress disorder
- QR
Quick Response
- 95% CI
95% Confidence interval
- OR
Odds ratio
- WMH-ICS
World mental health international college student
Authors’ contributions
Hongguang Chen: Conceptualization, Methodology, Supervision, Project administration, Funding acquisition, Writing - Original Draft and Writing - Review & Editing. Yiyang Liu: Formal analysis, Data Curation, Visualization, Writing - Original Draft and Writing - Review & Editing. Dexu Li: Formal analysis, Data Curation, Writing - Original Draft and Writing - Review & Editing. Shuang Xu: Investigation and Writing - Review & Editing. Haolou Feng: Conceptualization, Investigation and Writing - Review & Editing. Peiyue Yang: Investigation and Writing - Review & Editing. Shunfei Li: Formal analysis, Writing - Original Draft and Writing - Review & Editing.
Funding
This work was supported by Capital’s Funds for Health Improvement and Research (Grant: 2022-2G-4116) and the Standard Research Projects (Grant: BWS17B052). The funders had no role in the study design, data collection, analysis, interpretation, writing of the report or decision to submit the article for publication.
Data availability
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
The study was approved by the Ethics Committee of Peking University Sixth Hospital (Approval number: 2022-9-5-1) and was conducted in accordance with the latest revision of the Declaration of Helsinki. Electronic informed written consent was obtained from all respondents.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Shuang Xu, Email: 664214733@qq.com.
Hongguang Chen, Email: chenhg@bjmu.edu.cn.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.