TESTING AN MTM THEORY-BASED INTERVENTION ON REDUCING DROWSY DRIVING BEHAVIOR, "STAY AWAKE, STAY ALIVE, ©" AMONG COLLEGE STUDENTS: AN EDUCATIONAL RANDOMIZED CONTROLLED TRIAL
TESTING AN MTM THEORY-BASED INTERVENTION ON REDUCING DROWSY DRIVING BEHAVIOR, "STAY AWAKE, STAY ALIVE, ©" AMONG COLLEGE STUDENTS: AN EDUCATIONAL RANDOMIZED CONTROLLED TRIAL
The goal of this randomized controlled educational study is to learn whether a structured, theory-based program can help reduce drowsy driving among college students (18 years and older) in Nevada. Drowsy driving means driving when you are very sleepy, tired, or struggling to stay alert. It is a serious safety problem because it can slow reaction time, reduce attention, and increase the risk of crashes, injuries, and even deaths. Many college students have irregular sleep schedules due to classes, jobs, late-night studying, and social activities, which can increase tiredness and increase the likelihood of drowsy driving.
Research question
Researchers will compare two groups to see which approach leads to greater improvement:
Group 1: MTM-based "Stay Awake, Stay Alive" program (interactive weekly sessions designed using behavior change theory).
Group 2: Standard drowsy driving education program, AAA (American Automobile Association) based education.
By comparing these groups, researchers can see whether the MTM-based program provides added benefit beyond standard education alone. Both groups receive the same overall time and attention, so differences in results can be linked more clearly to the program's strategies rather than to simply receiving education.
Participants will:
The study will measure changes in drowsy driving behavior and in MTM-related factors that may explain why these changes occur. For example, the MTM-based program helps students think about the benefits of avoiding drowsy driving (and the risks of continuing it), build behavioral confidence to choose safer options, and identify practical environmental supports (such as a safe place to rest, asking a friend for a ride, using ride-share or public transportation, or adjusting trip timing). It also supports emotional transformation (turning concern into motivation), practice for change (setting goals and tracking progress), and building a supportive social environment (friends and family encouraging safer choices).
During the sessions, participants may learn and practice real-world skills such as recognizing early warning signs of sleepiness (heavy eyelids, frequent yawning, drifting lanes, missing exits), using short rest breaks and safe "pull-over" plans, managing schedules to reduce late-night driving, and creating a personal action plan for high-risk situations (after work shifts, long study nights, or long-distance travel). The follow-up survey helps researchers see whether any improvements continue beyond the end of the 4-week program.
At the end of the study, results will help colleges, public health professionals, and road safety programs understand what types of education are most effective for preventing drowsy driving in young adults. If the MTM-based program is effective, it could be adapted and used more widely to improve student safety and reduce injuries related to drowsy driving. Participants who complete the final follow-up survey will receive an incentive.
Drowsy driving among college students Drowsy driving among college students represents a significant public health and roadway safety concern due to the convergence of developmental, academic, and lifestyle-related risk factors. Emerging adulthood is characterized by irregular sleep-wake patterns, heightened academic demands, and social behaviors that may compromise sleep duration and quality. In a 2023 cross-sectional survey administered via Qualtrics (n = 725), 49.4% of respondents reported engaging in drowsy driving within the past month, underscoring the prevalence of this behavior in this population.
Insufficient sleep has been shown to increase crash risk by impairing critical cognitive and psychomotor functions, including sustained attention, processing speed, decision-making, and reaction time, all of which are essential for safe vehicle operation. Additionally, reliance on caffeine and energy drinks to counteract fatigue may produce a transient perception of alertness without fully restoring cognitive performance, potentially contributing to risk compensation and continued unsafe driving behavior.
Statement of the Problem Drowsy driving, defined as operating a motor vehicle while experiencing substantial sleepiness or fatigue, represents a significant public health and traffic safety concern, particularly among college-aged populations. Fatigue impairs neurocognitive and psychomotor functioning, including sustained attention, executive decision-making, vigilance, reaction time, and information processing speed, thereby increasing the likelihood of motor vehicle collisions. Although often underrecognized, drowsy driving is estimated to contribute to approximately 10%-20% of motor vehicle crashes in the United States, underscoring its substantial contribution to preventable injuries and fatalities.
College students constitute a high-risk group due to the convergence of academic demands, late-night study habits, part-time employment, irregular sleep-wake cycles, and socially driven sleep restriction. Emerging adulthood is also characterized by circadian phase delay, which may further reduce sleep duration and quality. Many students rely on caffeine and energy drinks to counteract fatigue. While these stimulants may temporarily enhance perceived alertness, they can disrupt sleep patterns and contribute to persistent daytime sleepiness, thereby sustaining risk. Nearly half of college students report engaging in drowsy driving, highlighting the widespread nature of this behavior.
A major challenge is the gradual onset of sleep-related impairment. Early warning signs such as frequent yawning, difficulty keeping eyes open, reduced situational awareness, and unintended lane drifting are often subtle and dismissed. The use of sedating medications and alcohol further exacerbates impairment. These factors emphasize the need for targeted, theory-driven, evidence-based interventions to promote sleep health and reduce drowsy driving among college students.
Research Questions and Statistical Hypotheses
Is there a statistically and practically significant difference in the mean score of drowsy driving behavior in the experimental group (MTM theory-based intervention, Stay Awake, Stay Alive©) and comparison group (standard AAA program-based intervention) from pre-intervention to post-intervention to two-week follow-up?
Null Hypothesis (H1₀):
There is no statistically significant difference in the mean score of drowsy driving behavior days between the experimental group and the comparison group from pre-intervention to post-intervention to two-week follow-up.
Alternative Hypothesis (H1₁):
There is a statistically significant difference in the mean score of drowsy driving behavior days between the experimental group and the comparison group from pre-intervention to post-intervention to two-week follow-up.
Is there a statistically and practically significant difference in the mean score of participatory dialogue between the experimental group (MTM-based intervention, Stay Awake, Stay Alive©) and the comparison group (standard AAA program-based intervention) from pre-intervention to post-intervention to two-week follow-up?
Null Hypothesis (H2₀):
There is no statistically or practically significant difference in the mean score of participatory dialogue between the experimental group (MTM-based intervention, Stay Awake, Stay Alive©) and the comparison group (standard AAA program-based intervention) from pre-intervention to post-intervention to two-week follow-up.
Alternative Hypothesis (H2₁):
There is a statistically and practically significant difference in the mean score of participatory dialogue between the experimental group (MTM-based intervention, Stay Awake, Stay Alive©) and the comparison group (standard AAA program-based intervention) from pre-intervention to post-intervention to two-week follow-up.
Is there a statistically and practically significant difference in the mean score of behavioral confidence between the experimental group (MTM-based intervention, Stay Awake, Stay Alive©) and the comparison group (standard AAA program-based intervention) from pre-intervention to post-intervention to two-week follow-up?
Null Hypothesis (H₀):
There is no statistically or practically significant difference in the mean score of behavioral confidence between the experimental group (MTM-based intervention, Stay Awake, Stay Alive©) and the comparison group (standard AAA program-based intervention) from pre-intervention to post-intervention to two-week follow-up.
Alternative Hypothesis (H3₁):
There is a statistically and practically significant difference in the mean score of behavioral confidence between the experimental group (MTM-based intervention, Stay Awake, Stay Alive©) and the comparison group (standard AAA program-based intervention) from pre-intervention to post-intervention to two-week follow-up.
Is there a statistically and practically significant difference in the mean score of changes in the physical environment between the experimental group (MTM-based intervention, Stay Awake, Stay Alive©) and the comparison group (standard AAA program-based intervention) from pre-intervention to post-intervention to two-week follow-up?
Null Hypothesis (H4₀):
There is no statistically or practically significant difference in the mean score of changes in the physical environment between the experimental group (MTM-based intervention, Stay Awake, Stay Alive©) and the comparison group (standard AAA program-based intervention) from pre-intervention to post-intervention to two-week follow-up.
Alternative Hypothesis (H4₁):
There is a statistically and practically significant difference in the mean score of changes in the physical environment between the experimental group (MTM-based intervention, Stay Awake, Stay Alive©) and the comparison group (standard AAA program-based intervention) from pre-intervention to post-intervention to two-week follow-up.
Is there a statistically and practically significant difference in the mean score of change in the emotional transformation between the experimental group (MTM-based intervention, Stay Awake, Stay Alive©) and the comparison group (standard AAA program-based intervention) from pre-intervention to post-intervention to two-week follow-up?
Null Hypothesis (H5₀):
There is no statistically or practically significant difference in the mean score of emotional transformation between the experimental group (MTM-based intervention, Stay Awake, Stay Alive©) and the comparison group (standard AAA program-based intervention) from pre-intervention to post-intervention to two-week follow-up.
Alternative Hypothesis (H5₁):
There is a statistically and practically significant difference in the mean score of emotional transformation between the experimental group (MTM-based intervention, Stay Awake, Stay Alive©) and the comparison group (standard AAA program-based intervention) from pre-intervention to post-intervention to two-week follow-up.
Is there a statistically and practically significant difference in the mean score of change in the practice for change between the experimental group (MTM-based intervention, Stay Awake, Stay Alive©) and the comparison group (standard AAA program-based intervention) from pre-intervention to post-intervention to two-week follow-up?
Null Hypothesis (H6₀):
There is no statistically or practically significant difference in the mean score of change in the practice for change between the experimental group (MTM-based intervention, Stay Awake, Stay Alive©) and the comparison group (standard AAA program-based intervention) from pre-intervention to post-intervention to two-week follow-up.
Alternative Hypothesis (H6₁):
There is a statistically and practically significant difference in the mean change in the practice for change scores between the experimental group (MTM-based intervention, Stay Awake, Stay Alive©) and the comparison group (standard AAA program-based intervention) from pre-intervention to post-intervention to two-week follow-up.
Is there a statistically and practically significant difference in the mean scores of changes in the social environment between the experimental group (MTM-based intervention, Stay Awake, Stay Alive©) and the comparison group (standard AAA program-based intervention) from pre-intervention to post-intervention to two-week follow-up?
Null Hypothesis (H7₀):
There is no statistically or practically significant difference in the mean scores of changes in the social environment between the experimental group (MTM-based intervention, Stay Awake, Stay Alive©) and the comparison group (standard AAA program-based intervention) from pre-intervention to post-intervention to two-week follow-up.
Alternative Hypothesis (H7₁):
There is a statistically and practically significant difference in the mean scores of changes in the social environment between the experimental group (MTM-based intervention, Stay Awake, Stay Alive©) and the comparison group (standard AAA program-based intervention) from pre-intervention to post-intervention to two-week follow-up.
Is there a statistically and practically significant difference in the mean score (pre-intervention to post-intervention to two-week follow-up) for the intent to initiate reducing drowsy driving between the experimental (MTM-based intervention, Stay Awake, Stay Alive©) and comparison (standard AAA program-based intervention) groups?
Null Hypothesis (H8₀):
There is no statistically significant difference in the mean scores for intent to initiate reducing drowsy driving between the experimental (MTM-based intervention, Stay Awake, Stay Alive©) and comparison groups (standard AAA program-based intervention) from pre-intervention to post-intervention to two-week follow-up.
Alternative Hypothesis (H8₁):
There is a statistically significant difference in the mean scores for intent to initiate reducing drowsy driving between the experimental (MTM-based intervention, Stay Awake, Stay Alive©) and comparison groups (standard AAA program-based intervention) across pre-intervention to post-intervention to two-week follow-up.
Is there a statistically and practically significant difference in the mean score (pre-intervention to post-intervention to two-week follow-up) for the intent to sustain the reduction of drowsy driving between the experimental (MTM-based intervention, Stay Awake, Stay Alive©) and comparison (standard AAA program-based intervention) groups?
Null Hypothesis (H9₀):
There is no statistically significant difference in the mean scores for intent to sustain reduction of drowsy driving between the experimental (MTM-based intervention, Stay Awake, Stay Alive©) and comparison groups (standard AAA program-based intervention) across pre-intervention to post-intervention, to two-week follow-up.
Alternative Hypothesis (H9₁):
There is a statistically significant difference in the mean scores for intent to sustain reduction of drowsy driving between the experimental (MTM-based intervention, Stay Awake, Stay Alive©) and comparison groups (standard AAA program-based intervention) across pre-intervention to post-intervention, to two-week follow-up.
Theoretical Framework The Multi-Theory Model (MTM) is a contemporary health behavior change theory that explains both initiation and sustenance of behavior change. It blends cognitive, conative, and environmental elements from established theories and is intended to be parsimonious, culturally adaptable, and applicable across individual, group, and community contexts. MTM has shown usefulness in college populations for behaviors such as handwashing, telehealth adoption, and gambling behavior change. In this study, MTM guides the development and evaluation of an intervention to reduce drowsy driving. MTM includes six constructs across two phases. Initiation involves participatory dialogue about pros and cons, behavioral confidence to avoid drowsy driving, and changes in the physical environment that support safer choices. Sustenance involves emotional transformation, practice for change through self-regulation, and changes in the social environment via supportive peers and accountability, safely over time.
Innovation of the Study The present study introduces innovation by employing the Multi-Theory Model (MTM) of health behavior change, a modern fourth-generation framework, to examine the antecedents of drowsy driving among college students. A key strength of MTM is its clear differentiation between two phases of behavior change: initiation and sustenance. The initiation phase includes three constructs: (a) participatory dialogue, conceptualized as the perceived balance between advantages and disadvantages of behavior change; (b) behavioral confidence, defined as an individual's perceived certainty in their ability to initiate change; and (c) changes in the physical environment, reflecting access to resources and environmental supports that facilitate behavior modification. The sustenance phase similarly includes three constructs: (a) emotional transformation, which involves directing emotions toward goal commitment and self-motivation; (b) practice for change, describing ongoing self-regulation strategies to overcome barriers and remain focused; and (c) changes in the social environment, emphasizing the role of supportive interpersonal relationships in maintaining behavior over time.
To the best of my knowledge, this is the first study to apply MTM to understand drowsy driving behaviors among college students. By using MTM, the study contributes a novel theoretical lens to a critical public health problem and generates practical insights into both the initiation and long-term maintenance of safer driving behavior. This approach strengthens the scientific foundation for developing targeted, theory-driven interventions that can reduce drowsy driving in college populations.
Significance of the Study Reducing drowsy driving among college students is highly significant because this population is especially vulnerable to fatigue due to academic stress, inconsistent schedules, and lifestyle-related sleep disruption. Drowsy driving is a major safety concern, as fatigue impairs reaction time, judgment, and sustained attention skills essential for safe driving. Younger drivers may also underestimate their level of impairment, further increasing crash risk. Evidence suggests that the effects of sleep deprivation can resemble alcohol-related impairment, heightening the likelihood of collisions among young adults. Notably, nearly half of college students surveyed reported engaging in drowsy driving within the past month, demonstrating the magnitude of this issue in this population.
Beyond immediate risk, drowsy driving carries broader public health consequences, including preventable injuries, fatalities, and increased healthcare costs. Emerging approaches, such as drowsiness monitoring and detection systems, may improve real-time driver awareness and enhance safety outcomes. However, technology alone is insufficient without behavior-focused strategies that address underlying determinants of fatigue-related driving. This highlights the importance of targeted educational and behavioral interventions that promote safe sleep practices and strengthen students' ability to recognize and respond to warning signs of fatigue.
Research indicates that many students fail to fully recognize how fatigue affects driving performance, increasing their risk of unsafe decisions. University-based workshops that emphasize sleep hygiene and the direct relationship between adequate sleep and driving safety may help students better assess fatigue and adopt safer behaviors. Such interventions can enhance well-being and reduce preventable harm.
Study Design This study will employ an educational randomized controlled trial (RCT) design to evaluate the effectiveness of a theory-driven intervention in reducing drowsy driving among college students. Random assignment to two study arms will be used to ensure that participants in the experimental group (receiving the Multi-Theory Model [MTM]-based intervention) and the comparison group (completing the standard American Automobile Association [AAA] online certification course) are comparable at baseline. This design will strengthen internal validity by reducing selection bias and distributing known and unknown confounders evenly across groups.
The primary purpose of the study is to compare the MTM-based intervention with a standard AAA program in reducing self-reported drowsy driving behaviors. Participants will complete surveys at three time points: baseline (pretest), immediately after the four-week intervention (post-test), and two weeks after completion (follow-up). These assessments will evaluate changes in drowsy driving frequency, intention to initiate and sustain safer driving behaviors, and the six MTM constructs.
Randomization will be conducted using a computer-generated sequence with stratification by key demographic variables such as gender and academic level to ensure balanced representation across groups. This trial is informed by prior findings indicating that nearly 50% of college students reported drowsy driving in the past month, highlighting the urgency of targeted prevention strategies. In the same study, participatory dialogue and behavioral confidence significantly predicted initiation of behavior change, while emotional transformation and practice for change predicted sustenance; changes in the physical and social environments were not significant predictors, suggesting that individual-level approaches may be particularly relevant.
Participants in the intervention arm will receive structured MTM-based activities delivered across four weekly sessions, while those in the comparison arm will complete the AAA online certification course. Because the AAA course requires approximately five hours, both conditions will be matched for time and delivered across four sessions to maintain consistent intervention dosage. A follow-up assessment will be conducted in week six to evaluate maintenance of outcomes. All participants will receive an incentive after completing the final follow-up survey.
Target Population and Sampling Strategies The target population for this study will include college students enrolled at a university in Nevada. Eligible participants must be at least 18 years of age, currently enrolled in an undergraduate or graduate program, and able to provide informed consent. This study will follow a randomized controlled trial (RCT) design consistent with CONSORT guidelines to ensure methodological rigor and transparent reporting. Interested students will be directed to an online screening survey, where eligibility will be assessed following informed consent procedures. Students who meet the inclusion criteria will be enrolled and complete a baseline assessment before randomization.
After baseline data collection, participants will be randomly assigned to one of two study arms: (1) the experimental group receiving the Multi-Theory Model (MTM)-based intervention or (2) the comparison group completing the standard American Automobile Association (AAA) program-based intervention. Randomization will be conducted using a computer-generated allocation sequence to reduce selection bias and ensure comparability between groups.
Sample size will be determined through a priori power analysis using G*Power Version 3.1.9.7 for Windows. Assuming an alpha level of 0.05, power of 0.80, and a medium effect size of 0.30, the required sample size is estimated at 60 participants. To account for attrition and inclusion of covariates, the sample will be increased by 20%, resulting in a final target sample size of 72 participants.
Instrumentation Evidence supporting the reliability of this instrument is drawn from a prior cross-sectional study that administered a closely related 42-item web-based survey to 725 college students. That study demonstrated strong internal consistency across the MTM subscales and the overall measure: Cronbach's α = 0.88 (Perceived Advantages), 0.78 (Perceived Disadvantages), 0.81 (Behavioral Confidence), 0.87 (Changes in Physical Environment), 0.90 (Emotional Transformation), 0.83 (Practice for Change), 0.83 (Changes in Social Environment), 0.86 (Initiation scale), 0.92 (Sustenance scale), and 0.93 (overall MTM scale) Internal Consistency and Construct Validity Cronbach's alpha values, along with their 95% confidence intervals (CIs), were reported for all scales used in the instrument. Each alpha value surpassed the 0.70 benchmark, indicating that the scales and subscales developed to measure initiation and sustenance processes demonstrated satisfactory internal consistency. The results are presented in Table 1.
Scale Cronbach's Alpha (95% CI) Perceived Advantage 0.88 (0.86, 0.91) Perceived Disadvantage 0.78 (0.75, 0.81) Behavioral Confidence 0.81 (0.79, 0.84) Changes in the Physical Environment 0.87 (0.84, 0.89) Overall Initiation Scale 0.86 (0.83, 0.89) Emotional Transformation 0.90 (0.88, 0.92) Practice for Change 0.83 (0.80, 0.86) Changes in the Social Environment 0.83 (0.80, 0.86) Overall Sustenance Scale 0.92 (0.90, 0.94) Overall Scale 0.93 (0.91, 0.95) Table-1 Internal consistency of the initiation and sustenance scales and subscales.
The majority of fit indices used to evaluate the overall adequacy of the initiation model met the standard criteria for acceptable model fit. The estimated values included an RMSEA of 0.08, SRMR of 0.06, and CFI of 0.90, with the TLI at 0.88 slightly below but near the acceptable cutoff. The standardized factor loadings were found to range between 0.40 and 0.93.
Figure-1 Structural equation model for the initiation of safe driving behavior. For clarity of interpretation, only parameter estimates that reached statistical significance are shown.
These results demonstrated that the initiation scale effectively captured its intended constructs, namely, perceived advantages, perceived disadvantages, behavioral confidence, and changes in the physical environment. Among these, perceived advantages, behavioral confidence, and changes in the physical environment showed small to moderate, positive, and statistically significant direct effects on the initiation of safe driving behavior, with effect sizes ranging from 0.08 to 0.58.
Similarly, increases in emotional transformation and changes in the social environment were associated with greater sustenance of safe driving behavior. However, the construct "practice for change" did not show a significant effect on sustaining this behavior. Despite this, there were significant interrelationships among emotional transformation, practice for change, and changes in the social environment.
For the sustenance model, the overall model fit was excellent, as indicated by the fit indices: CFI = 0.99, TLI = 0.94, RMSEA = 0.05, and SRMR = 0.02. Standardized factor loadings for the sustenance scale ranged from 0.61 to 0.92, supporting its validity in measuring emotional transformation, practice for change, and changes in the social environment. Emotional transformation and social environment changes had small to moderate and statistically significant effects on sustaining safe driving behavior, with effect sizes of 0.50 and 0.17.
Figure-2 Structural equation model for the sustenance of safe driving behavior. For conceptual clarity, only the statistically significant parameter estimates are presented.
This indicates that higher levels of emotional transformation and changes in the social environment were associated with greater maintenance of safe driving behavior. However, practice for change did not have a significant impact on sustaining this behavior. Nonetheless, significant associations were observed among emotional transformation, practice for change, and changes in the social environment.
MTM-based intervention (Stay Awake, Stay Alive©) The intervention is grounded in the Multi-Theory Model (MTM) and targets both initiation and sustenance of behavior change.
To support initiation, participatory dialogue will be facilitated through guided group discussions in which students identify perceived benefits and challenges of reducing drowsy driving. This will be complemented by a brief educational lecture and interactive debate using case studies and real-life scenarios to help participants weigh advantages versus disadvantages. Behavioral confidence will be strengthened through a short psychodrama film illustrating the consequences of drowsy driving, followed by structured reflection and discussion focused on barriers and practical strategies such as improving sleep habits, proactive trip planning, selecting a designated driver, and seeking social support. Changes in the physical environment will be addressed by introducing campus and community resources (e.g., transportation services, student health services) and engaging participants in brainstorming how to access and apply these supports, including creating a personalized resource map.
To support sustenance, emotional transformation will be cultivated through a psychodrama video featuring successful real-life behavior change stories, followed by reflection on emotions and motivation-building strategies. Practice for change will be reinforced through weekly sleep journaling and progress reviews, with guidance to modify routines and reduce risk. Finally, changes in the social environment will be promoted using peer support groups, accountability partners, and role-playing exercises to build supportive communication and sustained behavior change.
Study Procedure This study will undergo review and approval by the Institutional Review Board (IRB) at the University of Nevada, Las Vegas (UNLV) to ensure compliance with ethical standards for the protection of human subjects. Participant recruitment will occur on campus-wide through multiple outreach strategies, including electronic communications, printed flyers, and structured campus engagement efforts. All intervention sessions will be conducted at the School of Public Health at UNLV and facilitated by the principal investigator, who maintains certification in human subjects' research through the Collaborative Institutional Training Initiative (CITI) program.
Following baseline assessment, participants will be randomly allocated to one of two study arms: an experimental group receiving the Multi-Theory Model (MTM)-based, theory-driven intervention or a comparison group receiving a knowledge-based intervention modeled after the American Automobile Association (AAA) program. Randomization will be conducted using the Statistical Package for the Social Sciences (SPSS) software to generate a computer-based allocation sequence, thereby minimizing selection bias and supporting internal validity.
A research assistant trained and certified through the CITI program will supervise participant check-in procedures and monitor attendance across all sessions. The assistant will also provide logistical and administrative support, including preparation of intervention materials, distribution of educational resources related to drowsy driving prevention, and facilitation assistance during MTM-based activities in the experimental arm. The trial will be implemented and reported in accordance with the Consolidated Standards of Reporting Trials (CONSORT) guidelines to ensure methodological rigor and transparency.
Interventions The experimental group will receive the Multi-Theory Model (MTM) based intervention, delivered by the principal investigator. Beyond structured educational content, the intervention will integrate experiential and participatory learning strategies designed to enhance engagement and promote behavior change. These strategies will include role-playing exercises, video-based dramatizations illustrating real-world consequences of drowsy driving, guided reflective journaling, and facilitated peer discussions. Participants will be instructed to monitor and record nightly sleep duration and any occurrences of drowsy driving using a structured sleep journal. In addition, they will document emotional and situational triggers associated with fatigue and discuss these reflections during weekly group sessions to support self-awareness and self-regulation.
At the outset of the program, each participant in the experimental group will receive a safety resource kit designed to reinforce environmental support for behavior change. The kit will include a sleep mask, information on local public transportation routes, resources for obtaining a bus pass, a personal journal, and educational materials related to drowsy driving prevention. Upon completion of the intervention and submission of the follow-up assessment, participants will receive a gift card as compensation for their time and participation.
Participants assigned to the comparison group will complete a five-hour online educational program focused on drowsy driving prevention, modeled after the American Automobile Association (AAA) curriculum. The course will be structured into four sessions of approximately 75 minutes each, matching the duration and contact time of the experimental intervention to maintain consistency in exposure. All sessions will be conducted under investigator's supervision. The course fee will be covered by the study team. The comparison intervention will be administered using desktop computers and audio equipment provided by the School of Public Health. Upon successful completion of the program, participants will receive a certificate of completion, a gift card, and a drowsy driving prevention resource kit.
Process Evaluation Using the RQFSM Model The RQFSM model, comprising Reach, Quality, Fidelity, Satisfaction, and Maintenance, will be employed as a structured framework to guide the process evaluation of the proposed public health intervention. This model enables systematic assessment of implementation-related dimensions to complement outcome evaluation measures. Within this theory-driven intervention designed to reduce drowsy driving among college students using MTM constructs, the RQFSM model will provide a comprehensive mechanism for evaluating implementation processes alongside behavioral outcomes. Behavioral interventions are highly dependent on delivery quality, participant engagement, and adherence to theoretical constructs. Therefore, the RQFSM framework will facilitate a multidimensional assessment of program implementation, ensuring that conclusions regarding effectiveness are interpreted within the context of implementation integrity and sustainability rather than outcome data alone.
Inclusion criteria