Strength of motivation and academic performance of medical students: a longitudinal study

Abstract

Background

The strength of motivation for medical school reflects a student’s perseverance in continuing medical training, regardless of personal sacrifices and academic or situational setbacks. Recognizing the patterns of changes in the strength of motivation may be beneficial in pinpointing the time(s) when students struggle to adapt to the rigors of the training, allowing educators to provide appropriate support. We examined the strength of motivation longitudinally and its association with examination performance during the basic science and core clerkship periods.

Methods

A prospective longitudinal cohort study was conducted at the Burnett School of Medicine from November 2020 through November 2023. First-year medical students were enrolled in the study (n = 51). The Strength of Motivation for Medical School-Revised version (SMMS-R) questionnaire, which consists of three subscales (Willingness to Sacrifice, Readiness to Start, and Persistence), was used at four distinct points during the preclinical and core clinical training. We compared the SMMS-R scores across four measurement points. Average scores from sets of summative assessments corresponding to the SMMS-R data collection time points were used to study correlation with SMMS-R scores.

Results

A repeated-measures ANOVA with Wilks’ lambda determined a significant effect of time on the mean composite SMMS-R scores (p < 0.001), with a medium effect size ( = 0.11). Subscale scores of Willingness to Sacrifice and Persistence showed significant variation in the strength of motivation across time with a medium effect size, p = 0.015, = 0.07 and p = 0.007, = 0.08, respectively. Examination performance varied significantly over time (p < 0.001), with a large effect size ( = 0.16). However, no significant correlation was found between the SMMS-R and examination scores.

Conclusion

Students often enter medical school with high levels of motivation, yet their strength of motivation may fluctuate as they encounter the realities and rigor of the curriculum. Results from our study revealed a significant decline in the strength of motivation and examination performance as medical students advanced in basic science and core clinical training. Our findings can inform the implementation of student-supporting mechanisms that could help sustain original (or higher) levels of strength of motivation as medical students advance in their training.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12909-025-07733-3.

Background

Motivation plays a crucial role in medical education. It is a major determinant of success in medical school, linking it to the quality of learning [1]. Highly motivated medical students tend to implement more effective learning strategies, persevere in the face of difficulties, and achieve higher academic performance than their less motivated peers [2, 3].

Researchers have attempted to define motivation in terms of its “quality” (types) [4, 5] as well as its “strength” [6, 7]. Focusing on the quality of motivation, Maslow’s Comprehensive Theory [8] posits that motivation directs an individual’s behavior to achieve something in which the individual has internally generated a deep interest to acquire. The Self Determination Theory (SDT) [4] qualitatively distinguishes different types of motivation and subdivides it into internal, external, and amotivation. Motivational quality generalizes the idea of different sources of motivation, ranging along a continuum from totally extrinsic (external) to totally intrinsic (internal). Intrinsic motivation is doing a task a person inherently finds interesting and enjoyable. It refers to an internal drive to pursue goals or engage in activities for personal satisfaction, genuine interest, or a sense of purpose, and stems from an individual’s values, curiosity, and goals. Extrinsic motivation, on the other hand, drives a person to complete a task because of the associated outcomes, i.e. grades (examination scores) or monetary gains. An amotivational state is when a person has no motivation, intrinsic or extrinsic, to pursue a task. Vallerand et al. [9] developed the Academic Motivation Scale (AMS) to measure the quality or type (intrinsic or extrinsic) of motivation; however, it does not measure the strength of motivation.

Nieuwhof et al. [6] explored the idea of the strength of motivation independent of the quality of motivation. They suggest that motivation to become a physician may arise from a desire for self-esteem, self-actualization, or knowledge and understanding. Measuring the strength of motivation in terms of time and energy invested, along with the sacrifices made for academic achievement and realizing these desires could be beneficial to measuring the direct impact of these desires on students’ strength of motivation to continue medical training. The authors define the strength of motivation for medical school as the student’s readiness to start and continue medical training regardless of sacrifices, setbacks, misfortune or disappointing perspectives, reflecting a student’s commitment to the rigorous and highly specific training required for this profession.

Previous studies have explored primarily the quality (type) of motivation among medical students and have found its positive impact on academic success [2, 3, 5]. However, there is limited data evaluating the strength of motivation throughout their training as a potential indicator of success. Most studies exploring the strength of motivation in medical students have used a cross-sectional study design [10–16]. Kusurkar et al. explored the effects of gender, academic background, and maturity on the strength of motivation in a cross-sectional study [11]. Shahid et al. found academic performance to be independent of the strength of motivation [16]. Similarly, Wouters et al. found no significant relationship between strength and type of motivation during medical training [12]. Paul et al. found no significant difference between the two groups when comparing the strength of motivation of medical students at entry and upon completion of training [15]. While Ahmed et al. found no difference in the strength of motivation between dental students at public and private dental schools [13], Faihs et al. reported a positive correlation between professional identity and strength of motivation [14], suggesting that individual psychological constructs may play a significant role in shaping student motivation. Although one study has examined the strength of motivation longitudinally and showed a decline in the strength of motivation over time [17], the existing literature remains sparse on this topic. Moreover, a potential association between strength of motivation and academic performance remains unexplored.

Recognizing the limited longitudinal data on how the strength of motivation fluctuates as medical students advance in their training sparked our interest to further explore this topic. We utilized Nieuwhof et al.’s [6] conceptual framework for the strength of motivation to design a study addressing: (1) Does the strength of motivation for medical students change over the course of the preclinical and core clinical training periods? and (2) Is the strength of motivation associated with student learning outcomes measured by student performance on periodic examinations built in the preclinical and core clinical training period?

We hypothesized that a student’s strength of motivation for medical training would decrease over time during the preclinical and core clinical training periods, as influenced by the inherent challenges associated with the medical training program, along with disruptions to the surrounding social, psychosocial, health, and economic environment.

Methods

We conducted this prospective longitudinal cohort study at the Anne Burnett Marion School of Medicine at Texas Christian University in Fort Worth, Texas, and collected data from November 2020 through November 2023. The study received approval from our university’s Institutional Review Board (approval number 1920 − 343). Informed consent was obtained from all participating students. Students enrolled voluntarily and could withdraw at any time without penalty.

MD curriculum

Sixty students are enrolled in the MD program each year. The medical school curriculum is structured in three Phases (Phase 1, Phase 2, and Phase 3). It employs an organ system-based integrated approach that embraces an active-learning flipped classroom model. Phase 1 (15 months) emphasizes basic sciences presented in clinically relevant frameworks. This phase integrates early exposure to clinical sciences and skills training through a Longitudinal Integrated Clerkship (LIC) model, allowing students to develop clinical competencies alongside basic science mastery. Phase 2 (13 months) is devoted to an intensified focus on clinical sciences. During this Phase, students engage more deeply in the clinical experiences while integrating the basic science concepts and encompasses the completion of all the core clinical clerkships. Finally, Phase 3 (18 months) allows students to explore specialized areas of interest through a series of elective rotations and sub-internships.

Study subjects

Eligible study subjects included first-year medical students from the MD class of 2024 (MD2024) and the MD class of 2025 (MD2025). Each student received an invitation to participate in the study from the principal investigator (PI). This email included a brief description of the purpose and goals of the study. Students who expressed interest in participating joined an online meeting with the principal investigator (PI) to review the study proposal and informed consent in detail.

Study tool

The Strength of Motivation for Medical School-Revised version (SMMS-R) was used [7] to collect self-reported data from the participants. It consists of a 15-item questionnaire with a five-point Likert scale to record students’ level of agreement with the statements (Appendix 1). Eight of the items are indicative and suggest a positive relation to motivation (e.g., “I would always regret my decision if I hadn’t availed myself of the opportunity to study medicine”), while the remaining seven items (items 2, 4, 8, 9, 11, 13 and 14) are counter indicative and suggest a negative relation to motivation (e.g., “If studying took me more than an average of 60 hours a week, I would seriously consider quitting”). Counter-indicative items are reverse scored; the option chosen by the participant is subtracted from six. For example, if the level of agreement to a counter-indicative item is selected as two, reverse scoring would yield four as the value to be used [7, 18]. The SMMS-R questionnaire has three subscales: Willingness to Sacrifice (Subscale 1), Readiness to Start (Subscale 2), and Persistence (Subscale 3). Items are divided across the subscales as follows: items 5, 7, 9, 10, and 12 make up Subscale 1; items 1, 3, 6, 11, and 15 make up Subscale 2, while items 2, 4 8, 13, and 14 make up Subscale 3. The overall score (total) on the SMMS-R ranges from 15 to 75, and that of each subscale from 5 to 25.

Administration of the survey tool and data collection

All study participants completed informed consent prior to receiving the survey. In addition to the SMMS-R questionnaire items, the survey included questions capturing participants’ demographic information and was administered via Qualtrics (Qualtrics, Provo, UT, USA; https://www.qualtrics.com). It was distributed via email at four measurement points (T1, T2, T3, T4) across Phase 1 and Phase 2 of medical training. The first survey aligned with the completion of the first third of their basic science training, that is, after having taken the fourth summative customized National Board of Medical Examination (NBME) test (4th of the 12 examinations). The second survey was completed after the eighth customized NBME examination, while the third was completed after the twelfth customized NBME examination during Phase 1. The final survey was then completed at the end of Phase 2 at the time of completion of all NBME Subject examinations.

Survey responses were securely captured in a password-protected Qualtrics account. Once data collection was complete for all participants, survey responses were automatically compiled into an Excel spreadsheet and linked to individual student assessment scores obtained from the Office of Assessment and Evaluation. Responses were then deidentified, replacing student names with a unique alphanumeric code. The study team maintained strict confidentiality protocols throughout the research process, from data collection to analysis.

Correlation with student academic performance

The twelve NBME customized examinations from Phase 1 were grouped chronologically into three sets of four examinations (i.e., ExamSet1(1–4), ExamSet2 (5–8), and ExamSet3 (9–12). The average score from each examination set was then used in data analysis. The average score on the set of NBME Subject examinations at the end of Phase 2 constituted the fourth examination set (ExamSet4). The strength of motivation SMMS-R scores were then correlated to the corresponding average examination scores from an individual participating student across the four measurement time points.

Data analysis

The study data were analyzed with IBM SPSS Statistics for Windows version 29 (Armonk, NY: IBM Corp). Descriptive statistics were calculated for demographics, SMMS-R scores, and examination scores. We compared SMMS-R scores and examination scores for participants across the four time points collected during Phase 1 and Phase 2 of our curriculum using repeated-measures ANOVA. We report Wilks’ Lambda ( with corresponding F-value and p-value, along with partial eta squared () values to quantify the effect size, an indicator of practical significance. Specifically, represents the proportion of variance in motivation explained by the independent variable (time), where thresholds for small (0.01–0.06), medium (0.06–0.14), and large (> 0.14) effects are applied [19]. We adopt a more conservative approach to defining statistical significance for these differences, utilizing the Bonferroni post-hoc test to minimize the risk of Type I error associated with multiple comparisons. Pearson’s correlation was applied to identify correlations between the strength of motivation and examination scores. Spearman rho values (r_s) were observed to identify associations of demographic factors with the strength of motivation and examination scores. We also calculated Cronbach’s alpha, an index of reliability for the study questionnaire (SMMS-R). Statistical significance was determined for all comparisons using a p-value less than 0.05 as the threshold; all p-values were 2-sided.

Results

Demographics

First-year medical students from the MD class of 2024 (N = 60) and the MD class of 2025 (N = 60) were eligible to participate in the study. Of those 120 eligible participants, 61 enrolled in the study. Survey data from seven students were incomplete, as they did not participate in all four measurement points. Three students did not progress to Phase 2 of training. Data from these ten students were excluded from the analysis. As a result, the analytic set includes data from the 51 participants who completed the SMMS-R questionnaires at all four measurement points. The resulting study population was diverse, with 53% female; 60.8% white, 11.8% Asian, 7.8% black, 5.9% Hispanic, and 11.8% identifying as more than one race; and majority in the age range of 21–24 (72.5%) (Table 1). One student preferred not to disclose demographic data. Majority of participants had Medical College Admission Test (MCAT) scores in the range of 510–516 (51%), followed by 39.2% in the 500–509, 3.9% in 517–520, and 2% in the 450–499 range. Seventy-two and a half percent of participants had a grade point average (GPA) between 3.6 and 4.0, while 27.5% had a GPA between 3.0 and 3.5.

Table 1.

Demographic data

Age, n (%)
21–25	37 (72.5%)
26–30	11 (21.6%)
31–35	3 (5.9%)
Race/Ethnicity, n (%)
White	31 (60.8%)
Black	4 (7.8%)
Hispanic	3 (5.9%)
Asian	6 (11.8%)
Multiple races	6 (11.8%)
Unknown	1 (2%)
Degree, n (%)
Bachelors	36 (70.6%)
Masters	14 (27.5%)
Doctorate	1 (2%)
GPA, n (%)
3.0–3.5	14 (27.5%)
3.6–4.0	37 (72.5%)
MCAT, n (%)
450–499	2 (3.9%)
500–509	20 (39.2%)
510–516	27 (52.9%
517–520	2 (3.9%)

Internal consistency of the SMMS-R questionnaire

The Cronbach’s alpha coefficient of the full questionnaire was 0.79, demonstrating acceptable internal consistency. The Willingness to Sacrifice subscale (consisted of 5 items) had an alpha coefficient of 0.80, the Readiness to Start subscale (consisted of 5 items) had an alpha coefficient of 0.74, and the Persistence subscale (consisted of 5 items) had an alpha coefficient of 0.72.

Comparison of mean composite scores for SMMS-R total and subscales

Mean composite scores for SMMS-R total and subscales are summarized across measurement times in Table 2. A repeated-measures ANOVA with Wilks’ lambda determined a significant effect of time on the mean composite scores for strength of motivation, = 0.79, F(3, 150) = 6.46, p < 0.001. Our analysis revealed a medium effect size, = 0.11. A post-hoc analysis with Bonferroni adjustment further revealed statistically significant differences in the strength of motivation between the first and fourth (p = 0.006) and second and fourth (p = 0.01) measurement points, suggesting a declining trend in motivation strength as students progress through their medical training to the end of Phase 2.

Table 2.

SMMS-R mean composite scores (SD) as measured at four measurement points (T1, T2, T3, and T4) during phases 1 and 2 of medical training

SMMS-R Score	Maximum Value	T1	T2	T3	T4
Total	75	56.47 (7.65)	56.25 (7.54)	55.41 (9.04)	53.39 (9.00)
Willingness to Sacrifice	25	17.80 (3.33)	17.76 (3.07)	17.37 (3.74)	16.70 (3.82)
Readiness to Start	25	18.71 (3.28)	18.72 (3.19)	18.31 (3.70)	17.78 (3.55)
Persistence	25	19.96 (2.60)	19.77 (2.96)	19.73 (3.23)	18.90 (3.31)

Within the subscales of Willingness to Sacrifice and Persistence, repeated-measures ANOVA showed significant variation in strength of motivation across time, = 0.84, F(3, 130) = 3.85, p = 0.015 and = 0.83, F(3, 150) = 4.16, p-value = 0.007, respectively. The effect sizes were similar at = 0.07 and = 0.08 and represent a medium-sized effect. The Bonferroni adjusted post-hoc analysis for subscale of Willingness to Sacrifice revealed a statistically significant difference in mean score between the second and fourth measurement points (p = 0.02), suggesting a decline in the willingness to make personal sacrifices by the end of Phase 2 of clinical training as compared to basic science training in Phase 1. Similarly, post-hoc analysis for subscale of Persistence showed a statistically significant difference in mean scores between the first and fourth measurement points (p= 0.02), again suggesting motivation strength declines as students progress in their medical training from Phase 1 through the completion of Phase 2.

Repeated-measures ANOVA, however, found the effect of time on the strength of motivation to have no statistical significance within the subscale of Readiness to Start, = 0.90, F(3, 132) = 2.32, p-value = 0.09. Correspondingly, the effect size was small, = 0.04, and no post-hoc analysis was completed for this subscale.

Student academic performance

A repeated-measures ANOVA showed examination performance varied significantly across the time points in Phase 1 and Phase 2, = 0.74, F(2, 108) = 9.24, p < 0.001, with a large effect size ( = 0.16). A Bonferroni adjusted post-hoc analysis revealed significant differences in performance between examination sets one and four (82 (10.37) v. 72.53 (18.90); p < 0.001), two and four (78.73 (8.57) v. 72.53 (18.90); p < 0.05), and three and four (77.76 (10.55) v. 72.53 (18.90); p < 0.05), suggesting a notable declining trend in examination scores from across the assessment sets in Phase 1 to end of Phase 2 assessment.

Correlations between the strength of motivation and examination scores over time

No correlation was found between strength of motivation and examination scores for each measurement point (SMMS1 v. ExamSet1 (R² = 0.000), SMMS2 v. ExamSet2 (R² = 0.006), SMMS3 v. ExamSet3 (R² = 0.008), SMMS4 v. ExamSet4 (R² = 0.001)) (Fig. 1).

Fig. 1.

Association between composite SMMS-R scores and examination performance at four measurement points

Graphs a, b, c, and d represent the correlation between composite SMMS-R scores (total score) and average examination scores at four measurement points. SMMS1, SMMS2, SMMS3, and SMMS4 scores represent SMMS-R scores at the first, second, third, and fourth measurement points, respectively. ExamSet1, ExamSet2, ExamSet3, and ExamSet4 scores represent average examination scores at first, second, third, and fourth measurement points, respectively, corresponding to the data collection time points for SMMS-R scores.

Association of strength of motivation with demographic characteristics

Age was found to be positively associated with total motivation strengths (total composite SMMS-R scores). It was significant for the first, second, and third measurement points (Phase 1), with r_s =0.39, p = 0.005; r_s =0.38, p = 0.006; r_s =0.37, p = 0.007, respectively. However, age and examination scores were found to be negatively associated across first and second measurement points, r_s= −0.38, p = 0.006 and r_s= −0.29, p = 0.04, respectively, indicating that increasing age negatively impacted examination performance in the early period of medical training.

A positive and significant correlation was observed between MCAT scores and performance on examination sets 2 (r_s = 0.45, p < 0.001), 3 (r_s = 0.36, p = 0.01), and 4 (r_s =0.28, p = 0.05), which indicates that students who performed well on MCAT also did well in medical school assessments. However, MCAT scores and strength of motivation for medical school did not reveal any significant relationship. In addition, undergraduate GPA before matriculating into medical school did not show a significant correlation with examination performance.

Discussion

Our longitudinal prospective study utilized the Strength of Motivation for Medical School-Revised (SMMS-R) questionnaire to examine how medical students’ strength of motivation fluctuates within the context of their medical education. The findings of our study revealed a notable decline in the strength of motivation over the first two and a half years (or 30 months) of medical training. The decline was significant when comparing the strength of motivation in the early Phase 1 period (basic sciences) to the end of Phase 2 (core clerkships), specifically between the first and fourth and the second and fourth measurement points.

These results align with other studies suggesting that medical students often begin their training with high levels of motivation [12], with burnout impacting students earlier in their training [20]. An and Li reported similar findings in their longitudinal three-year study, showing a declining trend in the quality of motivation, where most of the significant drop occurred within the first year of medical school [17].

A significant decline in the strength of motivation between the early stages of medical school and the end of Phase 2, which marks the completion of core clerkships, may reflect the increased demands and challenges posed by the clinical years on students’ personal, emotional, and social lives [21]. In their systematic review, Frajerman et al. emphasized the high prevalence of burnout among medical students, identifying major contributing factors as emotional exhaustion, depersonalization, and reduced personal accomplishment [22]. While our study did not specifically investigate levels of burnout, it is possible that the rising prevalence of burnout, as documented in the literature, may have contributed to the significant decline in strength of motivation observed at the end of Phase 2 in our cohort of medical students. Further, the significant time commitment required from the outset of medical training, combined with the emotional toll of increased exposure to patients with serious medical conditions, may also contribute to the gradual decline in motivational strength over time [23].

Additionally, scores within the SMMS-R’s subscale of Willingness to Sacrifice showed a significant decline over time, with a notable difference in mean scores between the first and fourth measurement points. Similarly, scores on the Persistence subscale showed a significant decrease between the second and fourth measurement points. This downward trend might reflect the impact of the burdens associated with medical training on students. The long and demanding journey toward becoming a specialized physician, coupled with the personal and professional sacrifices it entails, may contribute to the observed declines in Willingness to Sacrifice and Persistence scores.

Studies have examined the effect of curriculum type on student motivation. Medical schools are increasingly adopting innovative curricula that employ active-learning instruction methods to enhance student engagement in learning [24]. Del-Ben et al. reported that students in a reformed curriculum with early exposure to clinical experiences maintained higher levels of motivation throughout medical school compared to those in a previous teacher-centered curriculum [25]. Other studies have reported a positive impact of active learning instruction on motivation, critical thinking, and problem-solving skills. Jeno et al. found that students in team-based learning (TBL) courses demonstrated higher levels of autonomous motivation compared to those enrolled in lecture-based courses [26]. In their study, Kim et al. reported a significant increase in motivation levels among nursing students following the implementation of TBL [26, 27]. Likewise, a meta-analysis has found an overall positive effect on motivation of problem-based and case-based instruction [28].

Our curriculum is student-centered, organ system-based, and both horizontally and vertically integrated, utilizing active learning strategies in a flipped classroom format while providing early exposure to clinical experiences. However, despite these innovative features, we observed a trend of declining motivation among our medical students over time. This finding suggests that an innovative, student-centered curriculum alone may not be sufficient to sustain student motivation throughout medical training.

Previous studies have reported that medical students generally enter medical school with high levels of motivation [11, 12]. However, at the time of matriculation, many may lack a realistic understanding of the commitments and sacrifices demanded by the medical profession [6, 11, 29]. A career in medicine is both demanding and enduring, often exposing students to considerable stress and increasing their risk of burnout [30]. Greater awareness of the realities of career structure, working hours, and professional responsibilities may influence students’ motivation levels as they progress through their training.

These findings highlight the importance of implementing mechanisms for faculty to address the cognitive burden of information overload, alongside other challenges medical students face. Incorporating well-being into the curriculum and designing preclinical and clinical schedules that optimize training while prioritizing student well-being could also significantly enhance outcomes [30–32].

Our study also showed a decline in examination performance, reflected by a decrease in mean examination scores from Phase 1 to the end of Phase 2. However, within Phase 1, no significant differences were observed in examination performance among the three measurement points. In contrast, the decline became significant when comparing examination scores from any measurement point in Phase 1 to the scores at the end of Phase 2.

Although our study observed a trend of declining mean scores for both strength of motivation and examination performance over time, no significant correlation was found between the two at any corresponding measurement points. Academic performance may rely on factors beyond one’s motivation and/or intent to succeed. The literature presents mixed evidence on this relationship. Some studies have reported a positive link between higher motivation and improved academic achievement in both pre-clinical and clinical phases [33, 34], while others have found no meaningful correlation between motivation and academic performance [12, 15, 16, 35]. Another study found that declining academic motivation did not affect the academic achievement of first-year medical students [36].

Furthermore, intrinsic motivation has been shown to encourage deep learning approaches, which can, in turn, enhance examination performance [37]. Additionally, deep learning approach and active learning curricula incorporating a flipped classroom design are reported to have a positive impact on academic performance [38–40]. However, in our study, motivation levels reveal no clear correlation with exam scores. The observed decrease in motivation and exam scores between the basic science and clerkship period could be due to other, yet unidentified, factors. One possible explanation is that during the basic science curriculum (Phase 1), students are highly focused on preparing for the United States Medical Licensing Examination (USMLE) Step 1 and may therefore concentrate more on exam-taking strategies. Clinical clerkship (Phase 2) assessments include NBME clinical subject exams. It is possible that the mindset of students in our early clinical immersion curriculum is now focused on excelling in learning clinical practice rather than solely doing their best on Phase 2 exams. Additionally, heavy clinical workloads, time constraints, and an overwhelming array of resources can hinder students’ ability to keep up with self-directed study plans [41]. Another plausible explanation could be that the motivation strength questions assess the potential impact on students’ willingness to pursue medicine, considering the inherent commitment and sacrifices required by the field. As the students advance in their training, they may respond with lower scores on these aspects, reflecting an increased awareness of the challenges ahead. However, these factors may not yet have significantly affected their determination and perseverance, which could explain the lack of significant correlation between motivation strength and examination performance.

We also analyzed the relationships among MCAT scores, strength of motivation, and examination performance. No significant correlation was observed between MCAT scores and strength of motivation. However, MCAT scores demonstrated a significant positive correlation with examination performance in both the pre-clerkship (Phase 1) and core clerkship (Phase 2) years. This is consistent with broader research showing that MCAT scores are significant predictors of medical school performance. Academic performance, particularly in medical school exams, tends to correlate more strongly with standardized measures of academic ability than with self-reported motivation [42, 43].

Qualitative studies on factors influencing academic success have identified active engagement with learning, extracurricular and cooperative studies with peers, ability to reflect on learning methods, and relating what students are learning to future practice as factors that contribute to the academic success of medical students [3, 44, 45]. Awareness of these factors can help medical educators build or enhance a student-centered educational environment in promoting academic success.

In our study, age was positively related to SMMS-R scores but negatively to examination performance, indicating that motivation strengths alone are not the sole factor in determining academic excellence in medical school. Our findings align with Henning et al., who found that older medical students possess higher intrinsic motivation [46]. They also reported higher test anxiety in older students and suggested that it does not necessarily lead to low academic achievement. In line with this, Feil et al. noted that any early differences in academic performance between younger and older cohorts tend to even out as students advance toward the clinical phase of their education [47, 48]. Kusurkar et al. reported that the strength of motivation of medical students increased with age [11]. In contrast, some studies have reported a decrease in intrinsic motivation with age and have attributed this to age-related social pressures [49]. Studies examining the differences in motivations of students who enter medical school after high school or a bachelor’s degree have reported the impact of age on student motivations. Prior educational or professional experience has been positively correlated with higher intrinsic motivation to pursue a career in medicine. Wilkinson et al. reported that graduate-entry students have higher motivation and found age to be a stronger predictor of success in medical school. This may be because graduate-entry students’ prior experiences provide them with a clearer understanding of the demands and rewards of the medical profession, thereby reinforcing their commitment to a medical career [50]. In addition, greater maturity with age may help these students make more informed career choices and adopt deeper learning approaches [50, 51], which further supports their intrinsic motivation.

Furthermore, maturity and life experience can enhance resilience, enabling older students to better manage the stresses and sacrifices required in medical school, which in turn supports sustained motivation [11]. While it is reasonable to hypothesize that medical students with prior educational or professional experience in healthcare fields, such as nursing, may possess advantages in terms of academic performance and intrinsic motivation, the current literature does not provide direct empirical evidence to support this assumption. This literature gap presents an opportunity to explore how the healthcare experience affects student performance and motivation in medical school.

Limitations

While our study offers valuable insights, it is not without limitations. The use of self-reported measures and the potential for response bias should be considered. Additionally, our study was conducted at a single institution with a relatively small sample size, limiting the generalizability of our findings. Future research could adopt a longitudinal mixed-methods approach to better understand the complex factors influencing the strength of motivation among medical students.

Taken together, our results suggest a potentially multifaceted relationship between motivation and academic achievement in medical school. Further research is warranted to examine the complex interplay of personal and environmental factors that may shape medical students’ academic success.

Conclusion

The results of our longitudinal prospective study on the strength of motivation among medical students provide valuable insights into the dynamic nature of motivation within the context of medical education. Strength of motivation, a measure of a medical student’s commitment to continue the rigorous and highly specific training regardless of the sacrifices, setbacks, or disappointing perspectives, is found to decline over time from the time of entry into medical school to the end of the core clinical training period. The lack of correlation with student performance on summative assessments indicates that factors other than the strength of motivation influence academic outcomes. Understanding the patterns of fluctuations in the strength of motivation could allow educators to pinpoint when and why medical students struggle to adapt during their training. Our findings lay the foundation for future studies to better understand the complex factors influencing the strength of motivation and academic performance over time. The findings can help develop and implement targeted student-support interventions to maintain and enhance the strength of motivation of students throughout medical education.

Authors’ contributions

SB and KP designed and administered the study. Both authors contributed to writing and revising the manuscript and approved the submitted version.

Funding

Publication charges for this article were supported by the TCU Library Open Access Fund.

Data availability

The datasets used and/or analyzed during this study are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

This study was conducted in accordance with the Declaration of Helsinki. The study received approval from Texas Christian University’s Institutional Review Board (approval number 1920 − 343). Informed consent was obtained from all participating students.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.