Psychosocial factors associated with academic performance in medical students: a systematic review

Abstract

Introduction

Academic performance in medical students is influenced by a wide range of psychosocial variables, including emotional distress, motivation, emotional intelligence, and social support. Understanding how these factors relate to academic outcomes is essential for designing effective educational and mental health interventions.

Objective

To systematically evaluate the association between psychosocial factors and academic performance among medical students and to identify which determinants show the most consistent evidence across studies.

Methods

A systematic review was conducted following PRISMA 2020 guidelines. Searches were performed in PubMed/MEDLINE, ScienceDirect, Scopus, and Web of Science for studies published between 2014 and 2024. Observational studies examining psychosocial factors in relation to academic performance were included. Quality assessment was conducted using the Newcastle–Ottawa Scale.

Results and conclusions

Forty-five studies met the inclusion criteria, most of which were cross-sectional. Academic performance was evaluated through GPA/CGPA, examinations, and licensing or OSCE scores. Psychosocial variables assessed included stress, anxiety, depression, motivation, emotional intelligence, resilience, burnout, and social support. Across studies, stress, anxiety, and depressive symptoms showed predominantly negative associations with academic performance (reported in 67–80% of articles addressing these constructs), while intrinsic motivation, resilience, emotional intelligence, and perceived social support demonstrated mostly positive associations (60–85% of relevant studies). Some studies reported null findings, reflecting heterogeneity in measures, populations, and outcomes, or a true null effect. Evidence supports consistent associations between psychosocial factors and academic performance among medical students. Stress and negative emotional states are generally linked to poorer outcomes, whereas motivation, social support, emotional intelligence, and resilience tend to predict better performance. The predominance of cross-sectional designs and varied measurement tools precludes causal inference. Strengthening psychosocial resources may help improve both academic success and well-being among medical students.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12909-026-08742-6.

Introduction

The concept of academic performance is complex and varies according to the field of study. It can be defined as the value assigned to the learning outcomes of university students in a specific subject, comparing such results with the expected level of knowledge among their peers [1]. Furthermore, various variables have been investigated as predictors of academic performance at the university level, including cognitive factors such as intelligence, previous academic results, university entrance exams, and intellectual aptitudes, as well as psychosocial factors, personality traits, emotional aspects, study habits, vocational interest, and socioeconomic status [2].

Grades are the most commonly used indicator in academic programs to evaluate student performance. This system establishes a parameter linking what the student learns with what they achieve in the teaching-learning process [1]. However, this approach focuses on measuring learning based on outcomes rather than academic effort, which can negatively affect students and generate frustration.

In 1996, Daniel Goleman, in his book Emotional Intelligence, suggested that academic performance is closely linked to emotional intelligence, identifying two possible paths: academic success and school failure [3]. This relationship may be influenced by the effectiveness of teaching strategies, assessment methods, learning materials, and, more recently, the integration of new technologies such as simulators.

Academic performance is a key indicator in medical education, as it reflects not only students’ understanding of theoretical knowledge but also their ability to apply it in practical and clinical settings. Due to the high demands and complexity of medical training, academic performance may be influenced by a wide range of individual and contextual factors [4]. In this review, psychosocial factors are understood as both risk and protective characteristics arising from the interaction between individual, academic, and social contexts. Risk factors include psychological distress, stress, burnout, anxiety, and depressive symptoms, whereas protective factors encompass resilience, emotional intelligence, motivation, coping strategies, social support, and adaptive study habits. These factors operate across multiple environments, including academic settings, family contexts, and broader sociocultural influences [5].

Psychosocial determinants in medical students can influence both their mental and physical health. The academic environment characterized by rigorous coursework, high expectations, and competitive atmospheres is one of the main stressors. A negative psychosocial environment can trigger problems such as anxiety, depression, or chronic stress. In addition, financial difficulties and uncertainty regarding future career prospects can exacerbate stress levels. Burnout is also a relevant concern in medical education and is typically conceptualized as a multidimensional syndrome characterized by emotional exhaustion, depersonalization, and reduced personal accomplishment, rather than as independent contributing factors [6].

Medical students are a particularly vulnerable population to anxiety and depression due to three main factors: being students, being young, and belonging to the healthcare field [7]. This situation underscores the urgent need to implement support programs in universities. In Mexico, it is estimated that 43% of medical students suffer from depression and 24.5% experience anxiety [7]. However, this issue is not exclusive to the Mexican context. An international meta-analysis reported anxiety prevalences of approximately 33.8% [8] and depression rates of 27.2% among medical students globally, with similar figures in the United States and Europe [9].

These factors highlight the importance of designing specific mental health interventions and support systems that address the unique challenges faced by medical students, particularly in the context of ongoing global health crises [10].

Conversely, a positive environment—with a strong social support system including healthy family relationships, friendships, motivation, favorable conditions, and good study habits—has been associated with to emotional well-being and overall health among students [10].

The main objective of this study is to explore the association between psychosocial factors and academic performance among medical students, as well as to analyze the impact of these factors on academic achievement, identifying which represent risks and which act as protective elements. Based on this premise, the following research questions were formulated: What is the nature of the association between academic performance and psychosocial factors in medical students? And which psychosocial factors are most prevalent in this population?

Methods

Study design

This systematic review aimed to identify and synthesize empirical evidence on the association between psychosocial factors and academic performance in medical students. The review was conducted in accordance with PRISMA 2020 guidelines to ensure methodological rigor, transparency, and reproducibility. The protocol was not registered in PROSPERO; however, the methodology, inclusion criteria, and analytic approach remained unchanged throughout the review process.

Conceptual framework

Psychosocial factors were defined using the biopsychosocial model originally proposed by Engel (1977), integrating psychological, social, and contextual dimensions relevant to medical education [8]. For this review, psychosocial factors were categorized into four domains:

1. Affective symptoms: stress, anxiety, depression, psychological distress, burnout dimensions.

2. Motivation and learning attitudes: intrinsic/extrinsic motivation, academic engagement, study habits.

3. Personality and trait-like characteristics: emotional intelligence, grit, resilience, coping styles.

4. Social and environmental factors: perceived social support, socioeconomic disadvantage, learning environment, institutional climate.

Only studies evaluating one or more of these domains in relation to academic performance were considered eligible.

Eligibility criteria

Inclusion criteria

Studies were included if they met all of the following criteria:

• Design: Observational studies employing cross-sectional, correlational, or cohort methodologies.

• Population: Undergraduate medical students exclusively.

• Exposure: Assessment of at least one psychosocial factor as defined above.

• Outcome: Objective or subjective measures of academic performance, including Grade Point Average (GPA), standardized examinations (e.g., Objective Structured Clinical Examination [OSCE], United States Medical Licensing Examination [USMLE]), or pass/fail status.

• Sample size: Minimum n ≥ 50, applied as a pragmatic threshold to reduce instability in effect estimates and extreme sampling variability in observational research.

• Publication years: 2014–2024, chosen to reflect the most recent decade of major curricular reforms, increased digital learning environments, and evolving patterns of psychological distress among modern cohorts of medical students.

• Language: English or Spanish.

• Reporting quality: Studies adhering to STROBE recommendations and providing sufficient methodological detail to extract associations.

Exclusion criteria

Studies were excluded if they:

• Examined academic performance in relation to non-psychosocial determinants (e.g., cognitive ability, study hours alone).

• Included mixed samples of healthcare students without separate data for medical students.

• Had critical methodological flaws or extremely high risk of bias.

• Were published in languages that could not be accurately interpreted.

• Used simulation - based assessments, virtual cases, or non-authentic academic outcomes not formally assessed within institutional academic evaluation systems.

• Were randomized trials or intervention studies.

• Represented duplicates or secondary analyses of the same dataset without new results.

• Gray literature was excluded.

Search strategy

A comprehensive systematic search was conducted in October 2024 across the following databases: PubMed/MEDLINE, Scopus, Web of Science (Core Collection), and the Cochrane Library. The search was updated in early 2025 to identify newly published studies; no additional eligible studies were identified.

The primary search string was adapted for each database using Boolean operators and controlled vocabulary where applicable. The general structure was:

(“medical students”[MeSH] OR “medical students”) AND (“academic performance” OR GPA OR grades OR examinations) AND (“psychosocial factors” OR “mental health” OR stress OR anxiety OR depression OR “emotional intelligence” OR motivation OR resilience OR burnout).

Full database-specific strings and filters (language, humans, publication years, article type) are provided in Appendix 1.

Removed databases

• Cochrane Library was screened during preliminary exploration but excluded from the formal search because it did not yield relevant primary observational studies.

Additional searches

• A bibliographic hand-search of the reference lists of included studies was performed, identifying one additional eligible study.

Study selection

Study screening occurred in two phases:

1. Title and abstract screening

2. Full-text eligibility assessment

Two reviewers independently conducted all stages of screening and data extraction. Discrepancies were resolved through discussion and consensus. Inter-rater agreement was high, and no third reviewer was required.

A total of:

• 54 studies were excluded after title screening.

• 18 studies were excluded after abstract review:

• ◦ 8 examined psychosocial factors without academic outcomes

• ◦ 3 were reviews without primary data

• ◦ 7 included non-medical student populations

A complete PRISMA 2020 flow diagram is provided in Fig. 1. The reduction between records after duplicate removal and records screened reflects the exclusion of citations lacking abstracts, not meeting language or publication type criteria, or clearly unrelated to medical student populations.

Fig. 1.

PRISMA four-level flow diagram

Risk of bias assessment

Risk of bias was assessed using the Newcastle–Ottawa Scale (NOS) for observational studies. The tool evaluates three domains:

1. Selection

2. Comparability

3. Outcome/Exposure

According to the Newcastle–Ottawa Scale criteria, scores range from 0 to 9. For this review:

• 7–9 points: High quality (low risk of bias)

• 5–6 points: Moderate quality

• ≤4 points: Low quality

Two independent reviewers assessed each study. Differences in scoring were resolved by consensus.

No study was excluded solely due to NOS score, but methodological quality informed interpretation in the Discussion.

Individual NOS scores for each study are shown in Appendix 2.

Outcome measures

Academic performance outcomes included Grade Point Average (GPA) (common scales: 0–4.0 and 0–5.0), standardized examinations such as the Objective Structured Clinical Examination (OSCE) and the United States Medical Licensing Examination (USMLE Step 1/2), pass/fail or remediation outcomes, and self-perceived academic achievement. When multiple outcomes were reported, the primary measure was extracted. Academic performance measures, including GPA, were self-reported, institutionally recorded, or mixed, depending on the study.

Final study set

After all screening phases, 45 studies published between 2014 and 2024 met all inclusion criteria and were incorporated into the final synthesis.

Results

A total of 45 observational studies met the inclusion criteria, most of which were cross-sectional, with a smaller number of longitudinal and mixed-methods designs. Academic performance was assessed using GPA/CGPA, written examinations, OSCE scores, licensing examinations, and USMLE Step scores. Psychosocial variables examined across studies included mental health symptoms, stress-related constructs, burnout, motivation, personality traits, resilience, emotional intelligence, social support, and socioeconomic or contextual factors. Study-level characteristics are summarized in Table 1, with detailed effect sizes provided in Appendix 4.

Table 1.

Characteristics and effect sizes of the included studies

Author (Year)	Country	Study design	n	Mean age	Gender	Psychosocial factor	Academic measure	Effect size	Direction of effect	Summary
Al-Khani (2019) [11]	Saudi Arabia	Cross-sectional (online survey)	95	20.8 ± 1.95	NR	Sleep quality (PSQI)	GPA (high ≥ 4.0)	OR = 0.42 (95% CI 0.17–0.99)	Poor sleep quality associated with lower odds of low academic performance	Students with poor sleep quality showed better GPA despite higher emotional distress.
Al-Rouq (2022) [12]	Saudi Arabia	Cross-sectional	421	NR	NR	General, academic, and COVID-related stress (PSS)	GPA	p < 0.05 between stress groups; ~4% lower GPA in students with comorbidities	Higher stress associated with lower GPA; comorbidities linked to poorer performance	Academic and COVID-related stress were associated with reduced academic performance, with additional declines observed among students with medical comorbidities.
Aljadani (2021) [13]	Saudi Arabia	Analytical cross-sectional	405	NR	Higher burnout in women	Burnout (three MBI-SS dimensions)	GPA (4.0 scale)	AOR (women) = 2.14; AOR (high GPA) = 0.17	Higher GPA associated with lower burnout; burnout higher among women and clinical-year students	Higher academic performance was protective against burnout, while women and clinical-year students showed higher burnout levels.
Aljaffer (2024) [14]	Saudi Arabia	Cross-sectional	336	NR	NR	Motivation, self-actualization, study habits	GPA	OR (motivation) = 1.67; OR (self-actualization) = 1.93; OR (satisfaction) = 1.60	Higher motivation and self-actualization associated with higher GPA; effective study habits linked to better performance; distractors associated with lower GPA	Personal motivation was the strongest predictor of academic performance, exceeding the effects of study habits and satisfaction.
AlShamlan (2020) [15]	Saudi Arabia	Cross-sectional	527	NR	Higher severe depression in women	Depression (PHQ-9); family, financial, social, and psychological problems; specialty readiness	GPA (A/B categories)	OR = 2.24 (readiness); OR = 0.28 (absence of psychological problems)	Lower GPA associated with higher depressive symptoms; psychosocial difficulties linked to increased depression	Higher depression prevalence was observed among students with lower GPA and greater psychosocial difficulties, with women showing more severe depressive symptoms.
Alzahrani (2020) [16]	Saudi Arabia	Cross-sectional (stratified random)	289	21.5 ± 1.6	NR	Mindfulness, stress, depression	Last-semester GPA	Correlations and regression	Higher mindfulness associated with lower stress and depression; no association with GPA	Mindfulness was linked to better mental health but showed no significant relationship with academic performance.
Bani, Mohamed & Andrade (2024) [17]	UAE	Cross-sectional	215	19	M/F	Stress (GHQ), burnout (CBI), living situation, year of study	GPA	Stress–burnout correlation r = 0.50; GPA–stress p = 0.537; GPA–burnout p = 0.860	No significant association between GPA and stress or burnout	High prevalence of stress and burnout, with differences by living situation and year of study; academic performance showed no relationship with stress or burnout.
Barret (2024) [18]	France	Cross-sectional	482	22	M/F	Coping (active, positive thinking, social support, avoidance); physical activity; sleep	OSCE performance	Positive thinking → wellbeing β = 6.69; physical activity β ≈ 0.001; avoidance associated with lower OSCE scores	Positive thinking and physical activity associated with higher wellbeing; avoidance associated with lower academic performance	Adaptive coping and healthy habits improved wellbeing prior to exams, while avoidance coping was linked to poorer OSCE performance.
Burgis-Kasthala (2019) [19]	Australia	Longitudinal	291	NR	NR	Resilience (RS-14: self-assertion, drive); demographics	Longitudinal academic grades	Total R² = 0.563; low performers R² = 0.243; high performers R² = 0.422	Higher self-assertion associated with better performance among low performers; higher drive associated with better performance among high performers	Specific resilience facets predicted academic performance differently depending on prior achievement level, while total resilience score showed no overall association.
Burr & Beck Dallaghan (2019) [20]	United States	Cross-sectional	264	NR	NR	Professional efficacy, achievement-related emotions, burnout	Final course percentage	r = 0.577; B = 0.560; R² = 0.31	Higher professional efficacy and positive emotions associated with higher academic performance; anxiety/shame associated with lower performance	Professional efficacy was the strongest predictor of academic performance, with positive emotions further contributing to better outcomes.
Co (2021) [21]	China	Case–control	110	24	M/F	COVID-19–related academic stress	Final exam pass/fail	100% very/high stress in cases vs. 35.1% in controls; p < 0.0001	Severe academic stress associated with higher likelihood of exam failure	High academic stress during the COVID-19 pandemic was strongly associated with failing the final examination.
Dendle (2018) [22]	Australia	Longitudinal (three measurement points)	126	NR	NR	Psychological distress (K10, GHQ-28)	Global score; written exam; OSCE	No significant correlations; weak negative GHQ-28 correlation at T3	Increases in psychological distress not associated with changes in academic performance	Psychological distress increased over the clinical year but showed no meaningful association with academic outcomes.
Dias (2022) [23]	Brazil	Cross-sectional	209	NR	NR	Resilience, academic satisfaction, performance-related stress, thoughts of dropping out	Academic performance coefficient	Low resilience: PR = 4.65 (p < 0.001); higher performance protective	Higher performance associated with lower burnout; low resilience and dissatisfaction associated with higher burnout	Lower performance and low academic satisfaction were linked to higher burnout, while resilience was the main protective factor.
Donisi & Perlini (2022) [24]	Italy	Quasi-experimental (pre–post)	500	NR	M/F	Attachment (ASQ), emotional intelligence (EQ-i), empathy (IRI), emotional attitudes	Final exam	b = 0.19 (emotional concern → higher score); b = − 0.21 (“emotional detachment” belief → lower score)	Emotional attitudes showed indirect effects on performance; no direct associations with EI, attachment, or empathy	The course influenced emotional attitudes, but final exam performance was not directly associated with emotional intelligence, attachment style, or empathy.
Gradiski (2022) [25]	Croatia	Cross-sectional	188	23 ± 3	NR	Burnout (exhaustion, cynicism), loneliness, professionalism (empathy, teamwork)	Overall academic performance	Cohen’s f² = 0.02–0.35	Higher burnout and loneliness associated with lower academic performance; higher professionalism associated with better performance	Burnout and loneliness were linked to poorer academic outcomes, whereas professionalism acted as a protective factor.
Heath, Hearn & Stocker (2022) [26]	United Kingdom	Cross-sectional	67	NR	NR	Mindfulness (FFMQ-SF), cortisol, perceived stress	Exam performance	Mindfulness → performance (p < 0.0001); mindfulness → lower cortisol (p = 0.02); no association with perceived stress (p = 0.16)	Higher mindfulness associated with better exam performance and lower physiological stress response	Mindfulness predicted higher academic performance and reduced cortisol reactivity, although it did not significantly affect perceived stress levels.
Hill (2018) [27]	United States (Florida)	Mixed-methods (survey + qualitative)	987	NR	NR	Stress, mental health, time management, academic stressors	GPA; exam performance	Descriptive (no coefficients reported)	Higher stress associated with lower academic performance; social support and organizational skills associated with higher performance	High stress and poorer mental health were linked to lower academic performance, while social support and effective time management appeared protective.
Isik (2017) [28]	Netherlands	Cross-sectional	873	Preclinical: 19.65 ± 1.84; Clinical: 24.18 ± 2.36	NR	Autonomous vs. controlled motivation; ethnicity	GPA; clerical exam; OSCE	Hedges’ g; Kruskal–Wallis; linear regression	Higher autonomous motivation associated with higher GPA; controlled motivation not significant; no performance disadvantage for minority students	Autonomous motivation positively predicted academic performance, while controlled motivation showed no effect; ethnic minority students did not perform worse than peers.
Isik (2017) [28]	Netherlands	Cross-sectional	2451	NR	M/F	Autonomous and controlled motivation; study strategies (surface, achievement, deep)	GPA and clinical performance	Autonomous motivation → achievement strategy (β = 0.11, p < 0.001); surface strategy → negative GPA association	Autonomous motivation improved GPA only through achievement-oriented study strategies; surface strategies predicted lower GPA	Study strategies mediated the relationship between autonomous motivation and academic performance, with no performance differences by ethnicity.
Jerant (2019) [29]	United States	Cross-sectional	575	25	NR	Socioeconomic disadvantage (SED), self-designated disadvantage (SDA)	USMLE Step 1/2; clinical honors	Regression models	Higher SED associated with lower academic performance; higher SDA associated with fewer honors	Socioeconomic and self-designated disadvantage were both linked to poorer performance on USMLE examinations and reduced likelihood of receiving clinical honors.
Junaid (2020) [30]	Saudi Arabia	Analytical cross-sectional	247	NR	NR	Anxiety (BAI)	CGPA	ANOVA/χ²; p = 0.016 for CGPA	Higher anxiety associated with lower CGPA; anxiety higher in women and senior students	Elevated anxiety levels were linked to poorer academic performance, with greater anxiety observed among female and advanced-year students.
Kim (2016) [31]	South Korea	Cross-sectional	195	25.4 ± 3.58	NR	Career motivation (intrinsic/extrinsic), academic interest	GPA	d = 0.51 (interest); d = 0.48 and d = 0.12 (GPA)	Intrinsic motivation positively associated with academic interest and GPA	Intrinsic motivation was linked to higher academic interest and better GPA, independent of admission scores.
Kötter (2017) [32]	Germany	Longitudinal	456	22.3	Higher stress levels in women	Perceived academic stress (PMSS)	M1 exam grade	Linear regression; B = 0.03, p < 0.01	Higher PMSS associated with poorer M1 exam performance; women and older students reported higher stress	Perceived academic stress at both time points negatively predicted performance on the M1 examination, with higher stress observed in women and older students.
Lalwani (2024) [33]	India	Retrospective cross-sectional	360	NR	M/F	Mental health (anxiety, depression, stress); family environment; technological access; study habits; COVID-19 impact	Academic failure	Failure rate increased from 15% to 27% (up to 50% in some groups); severe depression/stress associated with higher failure	Poor mental health, adverse family environment, and limited technological access associated with higher risk of academic failure	Academic failure increased primarily due to psychosocial, technological, and pandemic-related factors rather than curriculum difficulty.
Lone (2024) [34]	Saudi Arabia	Cross-sectional	315	21.9 (18–25)	Males: visual/quad; Females: aural	Learning styles (VARK), mental health (DASS-21)	GPA	Correlations; p < 0.05 for learning styles	Bimodal learning style associated with higher GPA; visual style associated with lower GPA; no association with mental health	Learning styles showed significant associations with GPA, while DASS-21 mental health scores were not related to academic performance.
Mahroon (2018) [35]	Bahrain	Cross-sectional	307	NR	NR	Anxiety (BAI), depression (BDI-II), social relationships	Overall academic performance (failures, repeating a year)	χ² (no coefficients reported)	Lower academic performance associated with higher anxiety/depression; better social relationships associated with higher performance	Poorer academic outcomes were linked to greater psychological distress, while supportive social relationships corresponded with better performance.
Melaku (2015) [36]	Ethiopia	Cross-sectional	329	NR	M/F	Academic stress; substance use (khat, tobacco, alcohol)	CGPA	r = − 0.273; mean difference = 0.21 (95% CI 0.10–0.31); AOR (khat) = 3.03; AOR (tobacco) = 4.55; AOR (alcohol) = 1.93	Higher academic stress associated with lower CGPA; stress associated with increased substance use	Academic stress was linked to poorer academic performance and higher likelihood of substance use among medical students.
Miller-Matero (2018) [37]	United States	Observational	130	27.19 ± 2.12	M/F	Grit (perseverance and passion)	USMLE Step 1, Step 2CK, Step 2CS; class rank; time to program completion	Step 2CK increases with grit; d = 0.87 (4 vs. 5 years); d = 0.92 for class-rank differences	Higher grit associated with better exam performance and faster program completion	Grit was positively associated with USMLE performance and more timely program progression.
Muntean (2022) [38]	Romania	Quantitative cross-sectional	179	NR	NR	Personality traits (DECAS: conscientiousness, openness, emotional stability); motivation	National Residency Exam	Conscientiousness OR = 3.671; Openness OR = 0.392; Emotional stability OR = 4.863	Higher conscientiousness and emotional stability associated with better academic performance; lower openness associated with higher performance	Conscientiousness and emotional stability were strong positive predictors of exam performance, while lower openness was also linked to higher scores.
Ngasa (2017) [39]	Cameroon	Cross-sectional	618	22.4 ± 1.9	Higher depression prevalence in women	Depression (PHQ-9)	Self-reported GPA	OR = 1.2 (95% CI 0.9–1.7), p = 0.08	No significant association between depression and academic performance	Depressive symptoms were highly prevalent, especially among women, but showed no significant relationship with academic performance.
Numasawa (2024) [40]	Japan	Cross-sectional	177	NR	NR	Grit (Grit-S: perseverance, consistency) and depressive symptoms	GPA	b = − 4.7; − 3.7; − 1.8; grit × GPA interactions	Higher grit associated with lower depressive symptoms; GPA moderated the relationship	Greater grit was linked to fewer depressive symptoms, with GPA strengthening the association differently across perseverance and consistency subgroups.
Okoye (2022) [41]	Nigeria	Cross-sectional	64	23.6 ± 1.6	No gender differences reported	Academic stress (ARS); interpersonal, social, and learning-related stressors	Perceived academic performance (MSSQ)	Descriptive (proportion with high ARS = 51.6%)	Higher academic stress associated with lower perceived academic performance	Academic stressors—particularly learning-related ones—were strongly linked to lower perceived academic performance.
Prata (2021) [42]	Brazil	Analytical cross-sectional	213	23 ± 3.77	NR	Burnout, emotional support, perceived academic performance	Perceived academic performance	OR = 12.1; OR = 3.98; OR = 2.88	Worse perceived performance associated with higher burnout; low emotional support linked to higher burnout	Burnout was strongly associated with negative perceptions of academic performance, with low emotional support further increasing burnout risk.
Ranasinghe (2017) [43]	Sri Lanka	Cross-sectional	471	NR	Higher EI scores in women	Emotional intelligence (SEIT), perceived stress (PSS), personal satisfaction	IBSS, ApSS, CS exam scores	r = 0.121; OR (female) = 1.98; OR (satisfaction) = 3.69	Higher emotional intelligence associated with higher academic performance and lower stress	Higher EI and greater satisfaction with studying medicine were linked to better academic performance and reduced perceived stress.
Shareef (2015) [44]	Saudi Arabia	Cross-sectional	561	NR	NR	Quality of life (physical, psychological, social, environmental domains)	GPA	r = 0.23; 0.29; 0.11; 0.23	Higher quality of life associated with higher GPA across all domains	Higher quality of life was consistently linked to better academic performance among preclinical medical students.
Shiraly (2024) [45]	Iran	Cross-sectional	398	NR	NR	Social media use (SMU), coping strategies (Brief COPE), distress (DASS-21)	GPA	SMU → distress: β = 1.9078 (p = 0.0128); SMU → GPA: ns (p = 0.114); distress → GPA: ns (p = 0.07)	Higher social media use associated with greater distress through maladaptive coping; no significant association with GPA	Social media use increased psychological distress via maladaptive coping pathways but did not directly affect academic performance.
Shreffler (2021) [46]	United States	Cross-sectional	380	NR	NR	Impostor Phenomenon (CIPS)	USMLE Step 1	Welch ANOVA: F = 1.81, p = 0.155	No significant association between impostor phenomenon and academic performance	Impostor phenomenon scores did not significantly predict Step 1 performance, showing considerable individual variability.
Taleb (2023) [47]	Malaysia	Cross-sectional	207	NR	NR	Psychological wellbeing (GHQ-12)	GPA	β = − 0.21, p = 0.004 (SEM)	Poorer psychological wellbeing associated with lower academic performance	Psychological wellbeing was the only significant predictor of academic performance; physical environment factors showed no association.
Torres-Román (2018) [48]	Latin America	Cross-sectional	4615	20.8	Higher social motivation in men	Social/altruistic motivation; economic/prestige motivation; family pressure	Perceived good academic performance	PR = 1.11 (95% CI 1.03–1.18) and other significant PRs	Social/altruistic motivation associated with higher perceived academic performance; economic motivation showed no effect	Social and altruistic motivation predicted better perceived academic performance, whereas economic motivation showed no significant association.
Tsegay & Ayano (2024) [49]	Ethiopia	Cross-sectional	390	21.8	M/F	Psychological distress (Kessler), exam anxiety, social support	GPA	AOR (exam anxiety) = 5.02; AOR (low social support) = 5.70; AOR (suicidal attempt) = 5.62; GPA AOR = 0.11 (95% CI 0.044–0.288)	Higher exam anxiety and low social support associated with greater psychological distress; higher GPA protective	Higher psychological distress was linked to exam anxiety and inadequate social support, while higher GPA served as a protective factor.
Waqas (2018) [50]	Pakistan	Cross-sectional	409	19.9 ± 1.3	NR	Defense styles (mature, neurotic, immature); anxiety; depression	Annual academic grades	Silhouette index = 0.60; cluster ratio = 1.81	Mature defense styles associated with higher academic performance; immature defenses and severe anxiety associated with lower performance	Adaptive defense styles and lower anxiety/depressive symptoms characterized higher-performing students, while maladaptive defenses and severe anxiety predicted poorer performance.
Wijekoon (2017) [51]	Sri Lanka	Cross-sectional	130	26.3 ± 1	Higher EI scores in women	Emotional intelligence; family support; parent–child relationships; socialization	MBBS exam results (categorical)	β = − 0.018 (95% CI 0.005–0.031; p = 0.006); ANOVA p = 0.015	Higher emotional intelligence associated with better academic performance; positive family and social support also related to higher performance	Emotional intelligence emerged as an independent predictor of better academic performance, with supportive family and social environments providing additional benefits.
Wilkinson (2016) [52]	New Zealand	Cross-sectional	90	25	M/F	Stress, home-life disruption, social support, connectivity, years in country, relationship status	Residual scores for written, practical, and combined exams	Negative residuals associated with home-life disruption and fewer years in the country; additional associations with social support, extraversion, and security	Mixed effects: environmental disruption linked to poorer performance; some personality and support factors linked to better or worse outcomes	Environmental disruptions predicted lower academic performance, while individual and social factors showed variable associations.
Wu (2020) [53]	China	Cross-sectional (stratified survey)	1930	NR	NR	Intrinsic/extrinsic motivation, self-efficacy, engagement	GPA	SEM (direct and indirect effects)	Intrinsic motivation positively associated with GPA; engagement acted as mediator; self-efficacy showed no direct effect	Intrinsic motivation predicted higher academic performance, with engagement mediating the relationship; self-efficacy influenced performance only indirectly.
Xie (2019) [54]	China	Cross-sectional	1977	NR	NR	Academic adaptability	Academic performance	Burnout β = − 0.705; Engagement β = 0.655; Performance β = 0.407 (p < 0.01)	Higher adaptability associated with higher performance and engagement, and lower burnout	Academic adaptability strongly predicted better academic performance and engagement while concurrently reducing burnout levels.

Note: CS Cross-sectional, AC Analytical cross-sectional, Obs Observational, QE Quasi-experimental, CC Case–control, PSQI Pittsburgh Sleep Quality Index, BAI Beck Anxiety Inventory, BDI-II Beck Depression Inventory–II, PHQ-9 Patient Health Questionnaire-9, PSS Perceived Stress Scale, PMSS Perceived Medical School Stress, K10 Kessler Psychological Distress Scale, GHQ-12/GHQ-28 General Health Questionnaire (12/28 items), DASS-21 Depression Anxiety Stress Scales (21 items), Grit-S Short Grit Scale, CIPS Clance Impostor Phenomenon Scale, MBI-SS Maslach Burnout Inventory–Student Survey, CBI Copenhagen Burnout Inventory, VARK Visual, Aural, Read/Write, Kinesthetic learning styles, SEIT Schutte Emotional Intelligence Test, EQ-i Emotional Quotient Inventory, ASQ Attachment Style Questionnaire, IRI Interpersonal Reactivity Index, Brief COPE Coping Orientation to Problems Experienced, RS-14 14-item Resilience Scale, GPA Grade Point Average, CGPA Cumulative Grade Point Average, OSCE Objective Structured Clinical Examination, USMLE United States Medical Licensing Examination, PR Prevalence ratio, OR Odds ratio, AOR Adjusted odds ratio, β Regression coefficient, B Unstandardized regression coefficient, r Correlation coefficient, R² Coefficient of determination, d Cohen’s d, f² Cohen’s f-squared, SEM Structural equation modeling, ns not significant, CI Confidence interval, M/F male/female, SED Socioeconomic disadvantage, SDA Self-designated disadvantage, SMU Social media use

Mental health symptoms

Twenty-two studies evaluated depressive, anxiety, or general distress symptoms.

• 16 studies reported significant negative associations between higher symptom levels and lower academic performance [15, 16, 24, 27, 30, 40, 41, 49, 50, 52].

• Six studies reported non-significant associations [14, 16, 17, 22, 23, 36].

Stress-related constructs

Sixteen studies examined perceived academic stress or psychological strain.

• 11 studies found significant negative associations with academic performance [15, 16, 23, 27, 30, 35, 36, 41, 43, 50, 52].

• Five studies reported weak or non-significant associations [17, 22, 33, 39, 45].

Burnout

Eleven studies assessed burnout dimensions.

• Nine studies found significant associations between higher burnout (exhaustion, cynicism, reduced efficacy) and poorer academic outcomes [12, 15, 23, 26, 27, 34, 35, 40, 50].

• Two studies reported non-significant findings [22, 33].

Motivation

Seven studies evaluated motivational variables.

• Seven studies reported that autonomous or intrinsic motivation was positively associated with academic performance, while controlled or extrinsic motivation showed minimal or negative associations [14, 28, 31, 38, 48, 53, 55].

Personality traits and resilience-related variables

Nine studies addressed personality, resilience, perseverance, or impulse-control-related traits.

• Five studies found positive associations between adaptive traits (e.g., conscientiousness, emotional stability, perseverance) and higher academic performance [19, 37, 38, 43, 51].

• Four studies reported non-significant findings or mixed results (particularly for grit) [23, 24, 40, 42].

Emotional intelligence

Five studies assessed emotional intelligence.

• Four studies found a significant positive association with academic performance [19, 38, 43, 51].

• One study reported no significant association [23].

Social support

Eight studies evaluated peer, family, faculty, or institutional support.

• Six studies showed positive associations between higher social support and better academic performance [15, 19, 23, 27, 48, 52].

• Two studies reported non-significant findings [33, 39].

Socioeconomic and contextual factors

Seven studies examined socioeconomic indicators or contextual adversity.

• Five studies reported significant negative associations between socioeconomic disadvantage or contextual stressors and academic performance [36, 39, 43, 48, 52].

• Two studies reported non-significant associations [23, 33].

Overall significance

Across the 45 studies, 32 reported at least one statistically significant association between psychosocial factors and academic performance, while 13 studies reported non-significant or weak associations. Non-significant findings were more common in studies with smaller samples, self-reported academic outcomes, brief screening tools, or those conducted during periods of institutional disruption.

Discussion

This systematic review integrates findings from forty-five observational studies examining the association between psychosocial factors and academic performance in medical students. Across domains, the evidence suggests that psychosocial characteristics are associated with better or poorer academic outcomes; however, the strength and direction of these associations vary notably across contexts, instruments, and methodological approaches. Rather than acting as isolated determinants, psychosocial factors appear to interact with cognitive, emotional, and sociocultural processes, aligning with biopsychosocial models of student performance, which conceptualize academic achievement as the result of dynamic interactions between individual psychological functioning, social resources, and contextual demands [8].

Mental health factors

Symptoms of anxiety, depression, and general psychological distress demonstrated one of the most consistent patterns of association with poorer academic outcomes [12, 15, 40]. These findings align with cognitive emotional frameworks in which distress impairs concentration, executive functioning, and sustained academic engagement. Nonetheless, several studies reported null associations, which may reflect cultural differences in symptom reporting, variations in stigma and help-seeking behaviors, or reliance on self-reported academic metrics. Additionally, many studies assessing mental health were of moderate quality according to the NOS, precludes causal inference. Overall, emotional symptoms appear relevant, although their impact is neither uniform nor universal and may be moderated by institutional and contextual factors [15, 16, 27, 35, 40, 50].

Stress and burnout

Academic stress and burnout particularly emotional exhaustion and cynicism were frequently associated with poorer academic performance. These findings are consistent with stress-response models proposing that chronic psychological strain undermines motivation, cognitive flexibility, and performance under pressure. However, isolated findings suggesting a transient beneficial effect of moderate stress mirror the Yerkes–Dodson principle, indicating that not all stress is detrimental [9]. Differences in stress appraisal, assessment timing, and available coping resources likely contribute to the variability observed. The predominance of cross-sectional designs also makes it difficult to determine directionality (e.g., whether academic challenges increase perceived stress).

Motivation and personality-related constructs

Autonomous motivation emerged as a robust positive correlate of academic performance, supporting self-determination theory and its emphasis on deep learning and sustained engagement. In contrast, controlled motivation showed weaker or inconsistent associations, suggesting that external drivers may be less influential in high-demand academic environments. Personality traits such as conscientiousness and emotional stability were generally favorable, although findings for constructs such as grit were mixed. These discrepancies may reflect differences in measurement tools, academic stage, or distinctions between basic science and clinical performance assessments. Many studies in this domain achieved relatively higher NOS scores, strengthening confidence in these observed patterns.

Emotional intelligence and social support

Although fewer in number, studies assessing emotional intelligence and social support consistently reported positive associations with academic outcomes. Emotional intelligence may facilitate emotional regulation and effective communication in stressful learning environments, while social support whether from peers, family, faculty, or institutions appears to buffer the impact of stress and enhance engagement. These findings align with sociocultural theories emphasizing belongingness and supportive learning climates. However, heterogeneity in measurement instruments and relatively small sample sizes limit the generalizability of these findings.

Socioeconomic and contextual disadvantage

Several studies found that socioeconomic hardships, institutional instability, and environmental disruptions (including those during the COVID-19 pandemic) were associated with poorer academic performance. These findings highlight that academic achievement is influenced not only by individual characteristics but also by broader structural conditions such as financial strain, access to academic resources, and stability of the learning environment. Variation in NOS scores across these studies also indicates differing levels of methodological rigor, which may contribute to inconsistencies.

Heterogeneity and methodological considerations

The evidence base demonstrated substantial heterogeneity in psychosocial constructs, assessment tools, sample characteristics, and definitions of academic performance. Most studies used self-reported GPA, cross-sectional designs, and convenience sampling, all of which introduce potential bias and limit causal interpretation. NOS ratings indicated that most studies were of moderate quality, with common limitations including inadequate control for confounders and unclear outcome assessment.

Strength of evidence across domains

The strength of evidence varied across psychosocial domains. Mental health symptoms, stress/burnout, autonomous motivation, emotional intelligence, and social support were supported by comparatively more consistent findings, based primarily on the number of studies reporting associations in the same direction, rather than on the magnitude of effect sizes. In contrast, constructs such as grit, specific coping strategies, and certain resilience components showed mixed or context-dependent associations.

Implications for medical education

The findings highlight the importance of fostering learning environments that support psychological well-being, promote intrinsic motivation, and strengthen social support systems. Interventions such as mentoring, mindfulness-based stress reduction, peer-support groups, and academic skills training may mitigate risk factors and enhance protective traits. At an institutional level, addressing structural barriers including financial hardship, workload intensity, and access to academic resources may reduce inequities and promote more equitable academic outcomes.

Future research

The predominance of cross-sectional designs limits conclusions regarding directionality, as academic difficulties may both result from and contribute to psychosocial distress. Therefore, future studies should prioritize longitudinal and mixed-methods designs to better clarify temporal relationships and underlying mechanisms linking psychosocial factors with academic outcomes. Standardizing instruments for both psychosocial constructs and performance metrics would improve comparability. Greater attention to cultural, socioeconomic, and institutional contexts is needed to understand why similar psychosocial factors may have different impacts across regions. Exploring interactions for example, whether resilience moderates stress or whether emotional intelligence shapes motivational pathways could further advance theoretical and practical understanding.

Overall, psychosocial factors show consistent though not uniform associations with academic performance in medical students. Emotional distress and burnout generally hinder performance, while autonomous motivation, emotional intelligence, and social support appear protective. These patterns reflect complex interactions between individual, interpersonal, and structural influences, underscoring the value of biopsychosocial frameworks for understanding academic success in medical education.

Limitations

This review presents several limitations, including potential publication bias, methodological heterogeneity among studies, and the predominance of cross-sectional designs, which precludes causal inference.

Moreover, many studies relied on self-administered questionnaires, introducing the risk of self-report bias. Samples were frequently non-probabilistic and mostly composed of early-year students and females, which may limit the generalizability of the findings to other academic populations.

Regarding methodological quality, all included studies were evaluated using the Newcastle-Ottawa Scale (NOS) for observational studies. Most obtained moderate to high scores in the selection and comparability domains, yet recurring deficiencies were observed in the handling of confounding factors and the clarity of outcome definitions. Although this structured evaluation enhances analytical rigor, substantial variability in individual study quality remains, which must be considered when interpreting the results.

As for the review process, although a systematic search was conducted across multiple databases and clearly defined inclusion and exclusion criteria were applied, grey literature and studies in languages other than English or Spanish were not included due to limitations in time, access, and translation resources. This may constitute a potential source of publication bias. Additionally, although double screening and data extraction were performed, no specialized software was used for risk of bias assessment or automated extraction, which may have influenced the efficiency of the process. From a practical perspective, the consistent associations observed between psychosocial factors and academic performance highlight the importance of integrating student support strategies within medical education programs. Early identification of elevated stress, burnout, or low social support may help inform targeted academic counseling, mentoring initiatives, and mental health resources aimed at promoting student well-being and academic engagement.

Conclusions

This systematic review supports the conclusion that psychosocial factors are consistently associated with academic performance among medical students across diverse educational contexts. Indicators of psychological distress including anxiety, stress, and burnout tend to relate to lower academic outcomes, whereas adaptive resources such as autonomous motivation, emotional intelligence, resilience, and social support are generally associated with stronger performance. However, these associations vary across settings, measurement tools, and academic stages, and therefore cannot be interpreted as causal.

Given the predominance of cross-sectional designs and heterogeneous assessment methods, longitudinal, multicenter, and intervention-based studies are needed to clarify temporal relationships, identify mediators and moderators, and determine whether targeted psychosocial interventions can effectively enhance academic outcomes. Strengthening institutional support systems and promoting healthy psychosocial environments remain important priorities for medical education.

Authors’ contributions

Raúl Ríos Andrade (RRA) conceptualized the review, performed the literature search and data extraction, and drafted the manuscript. Aziel Peralta Ramírez (APR) participated in data analysis, quality assessment, and contributed to the writing and critical revision of the manuscript. Sergio Trujillo López (STL) contributed to the interpretation of data, methodological validation, and final editing of the manuscript.All authors read and approved the final version of the manuscript.

Funding

This research received no external funding.

Data availability

All data generated or analyzed during this study are included in this published article.

Declarations

Ethics approval and consent to participate

Not applicable. This study is a systematic review based on previously published literature and did not involve direct participation of human subjects.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.