Abstract
With such high rates of undergraduate sleep problems, students have chosen to take melatonin, an over-the-counter supplement that can facilitate sleep. Questions remain as to the effectiveness of melatonin for sleep problems, and questions have emerged about its impact on mental health. Accordingly, the current study examined how ongoing melatonin usage might impact relative changes in college students’ sleep disturbance and ultimately their depressive symptoms. The two-wave (baseline and 2-month follow-up), online sample consisted of 331 undergraduates (86% female; Mage = 21.3, SD = 2.4), who reported on melatonin usage, sleep disturbance, and depressive symptoms. Controlling for sleep hygiene, socio-economic status, and gender, our model demonstrated a significant indirect effect from ongoing melatonin usage to depressive symptoms. Specifically, melatonin consumption predicted relative increases in sleep disturbance, which, in turn, predicted corresponding increases in students’ depressive symptoms. Given the increasing prevalence of melatonin usage, the potential for unforeseen consequences remains high. Results suggest that the negative consequences of melatonin use can include both college students’ mental health and their sleep. Given the efficacy of addressing sleep problems with cognitive or behavioral strategies, it is essential that student support services highlight alternatives to melatonin and the potential problems associated with its use.
Keywords: Melatonin, Sleep disturbance, Depressive symptoms, College students
Introduction
The mental health epidemic facing college students is robustly linked to their sleep problems [1–4]. Students report high rates of depressive and anxiety symptoms, with approximately 60% reporting insufficient and poor-quality sleep [5–7]. With evidence supporting the use of melatonin for sleep (e.g., [8, 9]), many students have begun to use over-the-counter (OTC) melatonin supplements to manage their sleep problems. In fact, rates of melatonin usage across the U.S. have risen five-fold over the past 2 decades [10], and recent reports have questioned the relative safety of melatonin [11], particularly in regard to suicidal ideation [12]. Due to its OTC availability, college students often engage in melatonin supplementation with a lack of understanding of how melatonin works, often without knowing the actual dosage they are taking, and without seeking proper supervision or guidance. This raises additional questions as to the real-world effectiveness of its unregulated and unstructured use in student populations. Accordingly, the current study sought to examine the longitudinal impact of melatonin consumption on students’ sleep problems. In addition, given the strong association between sleep problems and depressive symptoms in this population [6], we also investigated the process through which melatonin usage might impact their mental health.
Sleep and mental health problems in college students
Extensive research supports the strong connection between college students’ sleep disturbance and mental health problems [1, 13, 14]. Not only do lower sleep durations predict increased depressive symptoms, but the negative consequences of students experiencing high levels of both sleep disturbance and depressive symptoms includes elevated fatigue during classes in addition to other forms of poorer cognitive, academic, and physical functioning [1, 15]. Sleep disturbance is also associated with increases in suicidal ideation in both adolescents and adults [16–18]. Evidence also suggests that the associations between sleep and mood disturbances are bidirectional [19, 20], with psychological inflexibility as a potential mechanism linking these constructs [14].
Melatonin usage, depressive symptoms, and suicidality
As a dietary supplement, melatonin is generally well tolerated, has relatively few side effects, and has been shown to be effective for treating sleep disturbance and depression [8, 9, 21, 22], supporting the hypothesis that melatonin might have robust efficacy. However, adverse effects of melatonin usage have been found [11]. In fact, Hoier and colleagues [12], in their nationwide study of almost 6 million individuals in Denmark, found that people in treatment with melatonin had a rate of suicide attempts that was five-times higher and a death-by-suicide rate that was four-times higher than the general population, suggesting that melatonin might have questionable efficacy. This study had several limitations, including the low rate of death-by-suicide, especially by those who were using melatonin, and, most importantly, the lack of causal evidence due to the study’s design. As a result, researchers have called into question any causal link between melatonin usage and suicidality, instead highlighting the evidence linking sleep disturbances and other mental health disorders as independent predictors of suicide risk [23]. For instance, nocturnal wakefulness and its impact on executive functioning have been shown to be strong predictors of suicide attempts and completions [24, 25].
Due to melatonin being an OTC supplement, it has been virtually impossible to effectively track consumption within the general population or its subsequent benefits or consequences. For college students, the concerns regarding melatonin consumption extend primarily to those who self-prescribe, as they are unlikely to have ongoing clinical supervision or guidance. Furthermore, because melatonin is an unregulated supplement, the actual quantity of melatonin within any specific pill varies widely, with content ranging from − 87% to + 478% [26]. Finally, students might take melatonin believing that it is an effective hypnotic; unfortunately, melatonin’s hypnotic effects are minimal [27]. Given the relative paucity of studies examining melatonin usage in college students, the current study sought to examine the role of melatonin for ongoing users and how it might impact their sleep and mood.
The current study
A body of research supports the efficacy of melatonin for treating sleep problems suggesting that it could potentially have robust effectiveness (Hypothesis 1) when delivered as a freely available OTC supplement. However, recent empirical connections between melatonin usage, sleep disturbance, and depressive symptoms as well as concerns surrounding the effectiveness of melatonin use (given its unsupervised usage and unregulated production), it is also possible that melatonin might have questionable effectiveness as a supplement (Hypothesis 2), particularly for college students. The current study sought to leverage multi-wave assessments (baseline and 2-month follow-up) to examine the role of ongoing melatonin consumption on college students’ sleep and psychosocial well-being, thereby directly contrasting these two hypotheses.
To test these contrasting process-oriented associations, we modeled the indirect effect of ongoing melatonin usage on residual change in students’ depressive symptoms via corresponding changes in their sleep. To ensure that students’ sleep-related habits would not unduly influence the results, we controlled for students’ sleep hygiene when estimating this model. Given the evidence supporting melatonin’s positive effect on sleep as well as mood [8, 9, 21], we expected the following regarding melatonin’s robust effectiveness: Hypothesis 1a) ongoing melatonin users would report residual decreases in sleep disturbance and Hypothesis 1b) decreases in sleep disturbance would predict decreases in students’ depressive symptoms. We contrasted those hypotheses with alternative hypotheses based on melatonin’s questionable effectiveness, predicting that Hypothesis 2a) ongoing melatonin users would report residual increases in sleep disturbance and Hypothesis 2b) increases in sleep disturbance would predict corresponding increases in students’ depressive symptoms. We further proposed (Hypothesis 3) that residual changes in sleep disturbance would mediate the association between ongoing melatonin usage and residual changes in depressive symptoms. Finally, we also ran an exploratory analysis to examine the impact of ongoing melatonin usage on suicidal ideation via sleep disturbance.
Materials and methods
Participants
The final sample consisted of 331 participants (86% female). The mean age of this current sample was 21.3 years (SD = 2.4; range 18–34), and 65.9% of participants were white, with 18.4% Asian or Pacific Islander, 6.6% Latinx, and 5.7% Black and 3.3% multi-racial or other. Approximately 54% of the sample lived on campus in residential facilities provided by their respective institutions, and 61% maintained part- or full-time employment while attending school. Students’ mean family income was $108,391 (SD = $62,579), with approximately 22% of students reporting family incomes of $50,000 or less and 16.3% with family incomes greater than $200,000. Finally, 23.6% of the sample reported that they regularly took prescribed psychotropic medications (e.g., fluoxetine, sertraline).
Procedure
The Institutional Review Boards associated with each data collection site approved of the current study, and informed consent was obtained from each respondent prior to participation. Participants were recruited via email-based announcements, flyers, and word-of-mouth. Both online assessments (i.e., baseline and 2-month follow-up) were completed online during the Spring semester of 2023 (starting February 22nd and ending May 13th), and each took roughly 20–25 min to complete. Respondents were incentivized to participate by being entered into a lottery to win prizes (i.e., $50-$100 gift card), and by receiving course credit for participating in the study (if eligible).
Attrition
Of the 642 participants who completed the baseline survey, a total of 570 respondents (88.8%) provided email addresses and were sent up to 3 invitations to complete the follow-up survey. Of those respondents, a total of 331 (58.1%) completed the 2-month follow-up. ANOVA and Χ2 analyses suggested that the respondents participating in the follow-up survey did not differ from participants who only completed the baseline survey (n = 311) on sleep disturbance (t(639) = 1.07, ns, Cohen’s d = 0.08), depressive symptoms (t(628) = 0.41, ns, Cohen’s d = 0.03), and SES (t(637) = − 0.01, ns, Cohen’s d = 0.001). Respondents who did not complete the follow-up survey did evidence slightly lower baseline levels of sleep hygiene (t(638) = − 2.51, p < 0.05, Cohen’s d = 0.20), and included more male participants (Χ2(1) = 7.56, p < 0.01, phi = 0.11) and melatonin users (Χ2(1) = 10.35, p < 0.01, phi = 0.13).
Measures
Melatonin usage
We asked participants both at baseline and at the 2-month follow-up if they took melatonin to help them sleep at night (Yes = 1, No = 0). Ongoing melatonin users reported consumption at both baseline and follow-up. Although we did not include other descriptive variables in the analyses, to better understand participants’ usage of melatonin, we assessed frequency of usage (“less than once a month” = 0 to “every night” = 4), amount of melatonin (milligrams) that they took, and the approximate time that they consumed melatonin.
Sleep disturbance
Participants’ perceptions of sleep disturbance were assessed with the 8 items of the Patient-Reported Outcomes Measurement Information System (PROMIS) Sleep Disturbance scale [28]. In addition to specifically rating sleep quality over the past week, these items also assessed respondents’ perceptions of their sleep over the past week (e.g., “I had difficulty falling asleep”). All items were rated on 5-point scales and were summed so that higher scores indicated higher levels of sleep disturbance (αbaseline = 0.89; αfollow-up = 0.89).
Depressive symptoms
Depressive symptoms were assessed with seven of the 9 items of the Patient Health Questionnaire (PHQ-9) [29]. After removing the items measuring sleep disturbance and fatigue, the remaining 7 items corresponded to the criteria for Major Depressive Disorder in the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) [30], which included suicidal ideation. Respondents indicated for each of the seven depressive symptoms whether during the previous 2 weeks, the symptom had bothered them: 0 = “not at all” to 3 = “nearly every day.” The continuous variable was the sum of scores of the 7 items (αbaseline = 0.85; αfollow-up = 0.85), which ranged from 0 to 21 with higher scores indicating more depressive symptoms.
Covariates
The mediation model included gender identity (male = 1; female = 0), socioeconomic status (SES), and sleep hygiene as covariates. Students reported on their family’s SES, which was calculated by averaging the standardized values of total family annual income and the highest level of caregivers’ years of education (r = 0.50, p < 0.001). Higher scores indicate higher family SES. Sleep hygiene was assessed at baseline with the 28-item Adolescent Sleep Hygiene Scale [31], which assesses sleep-facilitating and sleep-inhibiting practices. Items were rated on 6-point response scales (0—“always” to 5—“never”), and a total score was calculated by averaging the individual items such that higher scores indicate better sleep hygiene practices (αbaseline = 0.81).
Analytical strategy
To examine the indirect effect of ongoing melatonin usage on college students’ depressive symptoms, we employed the PROCESS macro (model 4) for SPSS [32]. Our mediational model allowed us to test our hypotheses regarding the indirect effect of ongoing melatonin usage on residual changes in students’ depressive symptoms via changes in sleep disturbance. To examine residual change over time across sleep disturbance and depressive symptoms, we individually regressed 2-month follow-up values for each construct onto their baseline values and saved the unstandardized residuals, which were then entered into our mediation analysis. Missing data within the final sample were exceedingly rare (range: 0–9.7%), and data were missing completely at random (X2(28) = 32.02; p = 0.274).
To examine the possibility of alternative models of prediction, we ran a secondary analysis in which ongoing melatonin usage predicted residual change in sleep disturbance via residual changes depressive symptoms. In addition, to explore the connection between melatonin usage, changes in sleep disturbance, and suicidal ideation, we ran an exploratory analysis in which ongoing melatonin usage predicted suicidal ideation at the 2-month follow-up via changes in sleep disturbance. We used the 2-month follow-up assessment as our outcome in this exploratory model because ideation was measured with a single PHQ-9 item and its relatively restricted range limited the capacity for residual change.
Results
Preliminary analyses
Bivariate correlations and group differences
Across both the baseline and 2-month follow-up assessments, ongoing melatonin usage was positively associated with sleep disturbance (Table 1). In addition, baseline reports of sleep hygiene were associated with both baseline and follow-up reports of sleep disturbance and depressive symptoms such that worse sleep hygiene was associated with greater levels of sleep disturbance and more depressive symptoms. Results from independent t-tests suggested that ongoing melatonin users reported higher levels of sleep disturbance both at baseline, t(329) = 3.55, p < 0.001, and at the 2-month follow-up, t(327) = 3.80, p < 0.001. Ongoing melatonin usage did not differ across males and females (X2(1) = 1.97, ns). Finally, results from independent t-tests suggested that female students reported higher baseline levels of sleep disturbance (t(639) = 3.84, p < 0.001) and depressive symptoms (t(628) = 3.55, p < 0.001), but there were no significant differences in sleep disturbance (t(357) = 1.31, ns) or depressive symptoms (t(321) = 0.49, ns) at the 2-month follow-up.
Table 1.
Descriptives and correlations amongst study variables at baseline and 2-month follow-up
| Measures | Ongoing melatonin users | No melatonin | Bivariate correlations | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Range | M | SD | M | SD | t | d | 1 | 2 | 3 | 4 | 5 | 6 | 7 | |
| Primary predictor | ||||||||||||||
| 1. Melatonin usage (0 = none, 1 = ongoing) | n = 53 (16%) | n = 278 (84%) | – | |||||||||||
| Mediating variables | ||||||||||||||
| 2. Baseline sleep disturbance | 1–31 | 17.0 | 6.5 | 13.5 | 6.7 | 3.55*** | 0.53 | 0.19 | – | |||||
| 3. Follow-up sleep disturbance | 0–31 | 16.4 | 6.5 | 12.8 | 6.4 | 3.80*** | 0.57 | 0.21 | 0.70 | – | ||||
| Outcome variables | ||||||||||||||
| 4. Baseline depressive symptoms | 0–19 | 6.1 | 4.0 | 5.4 | 4.2 | 1.06 | 0.16 | 0.06 | 0.44 | 0.48 | – | |||
| 5. Follow-up depressive symptoms | 0–20 | 6.3 | 4.2 | 5.2 | 4.3 | 1.63 | 0.25 | 0.09 | 0.38 | 0.52 | 0.70 | – | ||
| Control variables (baseline) | ||||||||||||||
| 6. Sex (1 = male; 0 = female) | 92.5% female | 85.3% female | 1.97a | 0.08b | − 0.08 | − 0.12 | − 0.07 | − 0.04 | − 0.05 | – | ||||
| 7. Socio-economic status (SES) | − 1.8 to 1.8 | 0.0 | 1.0 | 0.0 | 0.8 | 0.40 | 0.06 | − 0.02 | − 0.04 | − 0.06 | 0.01 | − 0.04 | − 0.05 | – |
| 8. Sleep hygiene | 1.2–4.6 | 3.4 | 0.5 | 3.4 | 0.5 | 0.89 | 0.13 | − 0.05 | − 0.27 | − 0.31 | − 0.33 | − 0.34 | − 0.04 | 0.08 |
Ongoing melatonin users reported taking melatonin supplements regularly at both baseline and 2-month follow-up and are compared to respondents who reported not taking melatonin during the duration of the study. All bolded correlations are significant at the p < .05 level. SES is a standardized composite of the sum of the standardized versions of respondent's primary caregiver's education and family's annual income
***p < .001
aChi-square value
bPhi coefficient
Melatonin consumption
The subsample of ongoing melatonin users (n = 53) comprised approximately 16% of the total sample. Of these participants at baseline, 28.3% reported taking melatonin “every night,” with 50.9% reporting “a few nights a week,” 7.5% reporting “once a week,” and 13.2% reporting “once or twice a month.” They also reported consuming an average dose of 5.1 mg (SD = 4.3) per usage. Finally, 15.1% reported consuming melatonin “right before bed,” with 49.1% reporting “15–30 min. before bed,” 34% reporting “31–60 min. before bed,” and 1.9% reporting “more than 60 min. before bed.”
Alcohol and sleep-related substance consumption
On average the sample consumed alcohol on 3.8 days in the month prior to the baseline survey (SD = 4.7), with students reporting having been drunk on an average of 2.4 occasions (SD = 3.2). Specific to their sleep hygiene, 24.2% of students reported that they “sometimes” or more frequently drank beer or other drinks with alcohol after 6:00 pm, 34% reported that they “sometimes” or more frequently consumed drinks with caffeine (e.g., cola, tea, coffee) after 6:00 pm, and 7.3% reported that “sometimes” or more frequently smoked or chewed tobacco after 6:00 pm. Results based on independent samples t-tests suggested that ongoing melatonin users did not significantly differ from non-users across their consumption of alcohol or sleep-related substance consumption.
Primary analysis
Mediation model
As shown in Table 2 (Model 1), the first portion of the mediation model predicted 4.6% of the variance in residual changes in college students’ levels of sleep disturbance, F(4,286) = 3.42, p < 0.01. In support of the questionable effectiveness hypothesis, ongoing melatonin usage across a 2-month interval (β = 0.32, p < 0.05) and worse sleep hygiene (β = − 0.17, p < 0.01) significantly predicted residual increases in sleep disturbance across the 2 months of the study. The second portion of the mediation model predicted 7.8% of the variance in residual changes in students’ depressive symptoms, F(5,285) = 4.84, p < 0.01. Specifically, increases across two months in sleep disturbance (β = 0.23, p < 0.001) predicted residual increases in depressive symptoms across that same 2-month period.
Table 2.
Coefficients from mediational models 1–3
| β | B | SE | p | R2 | |
|---|---|---|---|---|---|
| Model 1 | |||||
| Predicting Mediator: Change in Sleep Disturbance | .046 | ||||
| Intercept | 4.80 | 1.84 | 0.010 | ||
| Ongoing Melatonin Use (0 = no, 1 = yes) | 0.32 | 1.55 | 0.74 | 0.037 | |
| Gender (female = 0; male = 1) | 0.01 | 0.13 | 0.87 | 0.878 | |
| SES | − 0.01 | − 0.08 | 0.32 | 0.814 | |
| Sleep hygiene | − 0.17 | − 1.52 | 0.53 | 0.004 | |
| Predicting Outcome: Change in Depressive Symptoms | .078 | ||||
| Intercept | 1.31 | 1.14 | 0.252 | ||
| Ongoing Melatonin Use (0 = no, 1 = yes) | 0.14 | 0.42 | 0.45 | 0.351 | |
| Change in Sleep Disturbance | 0.23 | 0.15 | 0.04 | < .001 | |
| Gender (female = 0; male = 1) | − 0.04 | − 0.40 | 0.53 | 0.452 | |
| SES | − 0.04 | − 0.15 | 0.20 | 0.434 | |
| Sleep Hygiene | − 0.08 | − 0.43 | 0.33 | 0.187 | |
| Model 2 | |||||
| Predicting Mediator: Change in Depressive Symptoms | 0.026 | ||||
| Intercept | 2.01 | 1.16 | 0.083 | ||
| Ongoing Melatonin Use (0 = no, 1 = yes) | 0.22 | 0.65 | 0.46 | 0.161 | |
| Gender (female = 0; male = 1) | − 0.04 | − 0.38 | 0.54 | 0.486 | |
| SES | − 0.05 | − 0.16 | 0.20 | 0.414 | |
| Sleep Hygiene | − 0.12 | − 0.65 | 0.33 | 0.049 | |
| Predicting Outcome: Change in Sleep Disturbance | 0.097 | ||||
| Intercept | 4.05 | 1.80 | 0.025 | ||
| Ongoing Melatonin Use (0 = no, 1 = yes) | 0.27 | 1.31 | 0.72 | 0.071 | |
| Change in Depressive Symptoms | 0.23 | 0.37 | 0.09 | < 0.001 | |
| Gender (female = 0; male = 1) | 0.02 | 0.27 | 0.84 | 0.746 | |
| SES | 0.00 | − 0.01 | 0.31 | 0.963 | |
| Sleep Hygiene | − 0.14 | − 1.27 | 0.52 | 0.014 | |
| Model 3 | |||||
| Predicting Mediator: Change in Sleep Disturbance | 0.045 | ||||
| Intercept | 4.78 | 1.83 | 0.010 | ||
| Ongoing Melatonin Use (0 = no, 1 = yes) | 0.32 | 1.51 | 0.74 | 0.042 | |
| Gender (female = 0; male = 1) | 0.01 | 0.15 | 0.83 | 0.858 | |
| SES | − 0.02 | − 0.11 | 0.32 | 0.743 | |
| Sleep Hygiene | − 0.17 | − 1.51 | 0.53 | 0.004 | |
| Predicting Outcome: Suicidal Ideation at 2-Month Follow-up | 0.063 | ||||
| Intercept | 0.90 | 0.25 | < 0.001 | ||
| Ongoing Melatonin Use (0 = no, 1 = yes) | − 0.10 | − 0.07 | 0.10 | 0.507 | |
| Change in Sleep Disturbance | 0.18 | 0.02 | 0.01 | 0.002 | |
| Gender (female = 0; male = 1) | 0.00 | 0.01 | 0.11 | 0.941 | |
| SES | − 0.04 | − 0.03 | 0.04 | 0.436 | |
| Sleep Hygiene | − 0.13 | − 0.17 | 0.07 | 0.022 |
This mediation model was tested using model 4 of the PROCESS subroutine for SPSS. Both unstandardized (B) and standardized (β) coefficients are presented, and results significant at p < .05 have been bolded
As shown in Fig. 1, residual change in students’ sleep disturbance mediated the association between ongoing melatonin usage and residual change in depressive symptoms as evidenced by a significant indirect effect (B = 0.08, SE = 0.04; 95% Confidence Interval (CI) [0.004,0.163]). These results support the questionable effectiveness hypotheses and suggest that ongoing melatonin usage was associated with increases in sleep disturbance, which, in turn, was associated with increases in students’ depressive symptoms.
Fig. 1.
Results from Mediation Analysis (Model 1)
Secondary analysis
To better understand the paths of influence within our model, we created a model in which ongoing melatonin usage predicted residual change in sleep disturbance via residual changes depressive symptoms. As shown in Table 2 (Model 2), ongoing melatonin usage did not significantly predict changes in depressive symptoms (β = 0.22, ns), although changes in depressive symptoms significantly predicted corresponding changes in sleep disturbance (β = 0.23, p < 0.001). This mediation model was non-significant (B = 0.05, SE = 0.05; 95% CI [− 0.029,0.152]).
Exploratory analysis
To better understand the relationship between ongoing melatonin usage and suicidal ideation, we created a model in which ongoing melatonin usage predicted suicidal ideation at the 2-month follow-up via residual changes sleep disturbance. As shown in.
Table 2 (Model 3), ongoing melatonin usage (β = 0.32, p < 0.05) significantly predicted residual increases in sleep disturbance, which, in turn, predicted higher levels of suicidal ideation at the 2-month follow-up (β = 0.18, p < 0.01). Accordingly, residual change in students’ sleep disturbance mediated the association between ongoing melatonin usage and suicidal ideation as evidenced by a significant indirect effect (B = 0.06, SE = 0.04; 95% CI [0.001,0.143]).
Discussion
Building on research to better understand the real-world impact of melatonin consumption in a non-clinical sample, the current study provides support via a two-wave design for the significant role that ongoing melatonin usage might play in increasing college students’ depressive symptoms. Specifically, we demonstrated that ongoing melatonin consumption across a 2-month period predicted relative increases in students’ sleep disturbance, which, in turn, predicted relative increases in their depressive symptoms. As the process-oriented results from the current study demonstrate, students’ consumption of melatonin over a prolonged period potentially poses a risk not only to their sleep but also to their mental health.
Not being a randomized-controlled trial, the current study cannot demonstrate causal relations between melatonin usage, sleep disturbance, and depressive symptoms. In fact, it is highly likely that students with sleep disturbances might take melatonin to manage their sleep problems and that students with sleep problems would also be at greater risk for elevated depressive symptoms. Given the many factors that influence students’ sleep problems (e.g., poor sleep habits, environmental disturbances), it is also possible that melatonin usage alone would not improve or greatly impact their sleep. However, the 2-wave design does highlight that continued melatonin usage does not appear to be effective and even seems to present risks for students’ sleep and well-being. There are multiple reasons this might be the case. First, as an unregulated substance, melatonin supplements may not contain the dosage they purport to on their labels [26]. Second, students may know little about how melatonin works, when it should be consumed, and how much should be taken. In the current sample, approximately 79% of the melatonin users consumed an average dose of 4.2 mg from a few nights a week to every night, with approximately 15% taking it right before getting into bed. Although melatonin has been shown to be an effective treatment for sleep disturbance and insomnia [8], behavioral treatments, such as cognitive-behavioral treatment for insomnia, should typically be considered a front-line treatment for sleep problems involving difficulties initiating or maintaining sleep [33].
Limitations and future directions
First, both the mediator and the outcome in our primary model represent residual changes across a 2-month period that are associated with one another and thus cannot elucidate any causal directions. Although the repeated measures data spanned a 2-month interval, the current model proposes a set of co-occurring processes that should be interpreted within a cross-sectional framework. Accordingly, future studies should examine these constructs within a more controlled experiment or across more than two time points to better ascertain the direction of effects. However, only a randomized controlled trial would be able to provide evidence of causality in terms of the effect of melatonin on students’ levels of sleep disturbance and depressive symptoms. With this said, there may be pre-existing differences between melatonin users and non-users (e.g., capacities to change behavioral patterns, interest in taking supplements vs. engaging in sleep-related therapies), and future studies should strive to characterize these differences to highlight not just the effects of melatonin usage but also the types of people most likely to use such a readily available substance. Second, all measures are self-report, increasing the potential for response-bias. Future studies should augment self-reports with additional assessment methods (e.g., actigraphy) to more thoroughly test these associations. Third, the effects that emerged in our analyses were generally small to moderate in magnitude and would benefit from replication in future studies. Finally, the sample was predominately white, female, and from colleges primarily in upstate New York. Accordingly, the findings may only generalize to a similar population and future studies should seek more diverse college samples.
Conclusion
The current study is one of the first to examine college students’ melatonin consumption and its association with their functioning. Given the increases in melatonin consumption and the relative paucity of investigations as to the real-world effectiveness of melatonin, future studies in this area are warranted. With that said, college administrators and counselors remain an essential part of the college students’ support networks, so their understanding of melatonin and its effects is paramount to the health and well-being of their students.
Author contributions
JP and RR contributed to the study conception and design. Participant recruitment and data collection were performed by JP. Material preparation, data management and analysis were performed by JP. The first draft of the manuscript was written by JP and all authors commented on previous versions of the manuscript. Both authors (JP and RR) read and approved the final manuscript.
Funding
No funding was received to support the current study.
Declarations
Conflict of interest
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. The authors have no financial or proprietary interests in any material discussed in this article. Dr. Peltz and Dr. Rogge declare that they have no conflict of interest.
Ethical approval
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The study was approved by the ethics committees of the University of Rochester (No. STUDY00008039) and SUNY Brockport (No. STUDY00003999). Informed consent was obtained from all individual participants included in the study.
Ethical committee permission
The Institutional Review Boards associated with each data collection site approved of the current study, and informed consent was obtained from each respondent prior to participation.
Consent to participate
Informed consent was obtained from all individual participants included in the study.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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