Growth in basic science knowledge in first-year medical school and USMLE Step 1 results: a longitudinal investigation at one school.

PURPOSE: Our US medical school uses National Board of Medical Examiners (NBME) tests as progress tests during the pre-clerkship curriculum to assess students. In this study, we examined students' growth patterns using progress tests in the first year of medical school to identify students at risk for failing United States Medical Licensing Examination (USMLE) Step 1. METHOD: Growth Mixture Modeling (GMM) was used to examine the growth trajectories based on NBME progress test scores in the first year of medical school. Achieving a passing score on the USMLE Step 1 at the end of the second year of medical school was used as the distal outcome, controlling for Medical College Admissions Test (MCAT) scores and underrepresented in medicine (URiM) status. RESULTS: A total of 518 students from a US medical school were included in the analysis. Five different growth patterns were identified based on students' NBME test results. Seventy-eight students identified in Group 1 had the lowest starting NBME test score (mean = 33.6, 95% CI 32.0-35.2) and lowest growth rate (mean = 2.30, 95% CI 2.06-2.53). All 26 students who failed Step 1 at the end of the second year were in Group 1 (failing rate = 33%). Meanwhile Group 4 (n = 65 students) had moderate starting NBME test scores (mean = 37.9, 95% CI 36.3-39.0) but the highest growth rate with mean slope at 6.07 (95% CI 5.40-6.73). This group of students achieved significant higher USMLE Step1 scores comparing with the 3 other groups of students (P < 0.05). CONCLUSIONS: Our study found students had heterogeneous growth patterns in progress test results in their first year of medical school. Growth patterns were highly predictive of USMLE step 1 results. This study can provide performance benchmarks for our future students to assess their progress and for medical educators to identify students who need support and guidance.

Victorian Lung Cancer Service Redesign Project: impacts of a quality improvement collaborative on timeliness and management in lung cancer.

BACKGROUND: Lung cancer management is characterised by a high disease burden, poor survival and substantial variation in management and outcomes. Service redesign provides opportunities for quality improvement (QI) and this improvement may be leveraged across multiple sites using QI collaboration. AIM: This initiative targeted Quality Improvement (QI) in lung cancer management, engaging a QI collaborative using service redesign methodologies in five Victorian hospitals. QI targets included timeliness from referral and diagnosis to treatment, multi-disciplinary meeting (MDM) presentation and supportive care screening. Redesign strategies targeted process sustainability through enhanced team capability. METHODS: This study engaged a prospective quality improvement cohort design targeting newly diagnosed tissue confirmed lung cancer with 6-month pre-intervention period and 6-month redesign implementation period, between September 2016 and August 2017, evaluated using Interrupted Time Series Analysis. Hospital sites included three regional and two metropolitan hospitals in Victoria. QI redesign targeted time intervals from referral to first specialist appointment (FSA), referral to diagnosis, diagnosis to first treatment (any intent), MDM documented in medical records and Supportive Care Screening Tool documented in medical records. RESULTS: There was a marked reduction in referral to FSA interval across all sites, with median (interquartile range) falling from 6 (0-15) to 4 (1-10) days, and proportion seen by a specialist within 14 days increased from 74.3% to 84.2%. The interval between diagnosis and treatment was not substantively changed in the 6-month implementation period. The proportion of subjects with documented presentation to the MDM increased from 61% to 67%. The proportion for which Supportive Care Screening documentation remained low at 26.3% post-intervention. CONCLUSIONS: Data-driven redesign initiatives enable identification and analysis of clinical practice variation and may be utilised to enhance timeliness of cancer care and improve local data service capabilities.

Using Markov chain model to evaluate medical students' trajectory on progress tests and predict USMLE step 1 scores---a retrospective cohort study in one medical school.

BACKGROUND: Medical students must meet curricular expectations and pass national licensing examinations to become physicians. However, no previous studies explicitly modeled stages of medical students acquiring basic science knowledge. In this study, we employed an innovative statistical model to characterize students' growth using progress testing results over time and predict licensing examination performance. METHODS: All students matriculated from 2016 to 2017 in our medical school with USMLE Step 1 test scores were included in this retrospective cohort study (N = 358). Markov chain method was employed to: 1) identify latent states of acquiring scientific knowledge based on progress tests and 2) estimate students' transition probabilities between states. The primary outcome of this study, United States Medical Licensing Examination (USMLE) Step 1 performance, were predicted based on students' estimated probabilities in each latent state identified by Markov chain model. RESULTS: Four latent states were identified based on students' progress test results: Novice, Advanced Beginner I, Advanced Beginner II and Competent States. At the end of the first year, students predicted to remain in the Novice state had lower mean Step 1 scores compared to those in the Competent state (209, SD = 14.8 versus 255, SD = 10.8 respectively) and had more first attempt failures (11.5% versus 0%). On regression analysis, it is found that at the end of the first year, if there was 10% higher chance staying in Novice State, Step 1 scores will be predicted 2.0 points lower (95% CI: 0.85-2.81 with P < .01); while 10% higher chance in Competent State, Step 1scores will be predicted 4.3 points higher (95% CI: 2.92-5.19 with P < .01). Similar findings were also found at the end of second year medical school. CONCLUSIONS: Using the Markov chain model to analyze longitudinal progress test performance offers a flexible and effective estimation method to identify students' transitions across latent stages for acquiring scientific knowledge. The results can help identify students who are at-risk for licensing examination failure and may benefit from targeted academic support.

Exploring the relationship between body mass index, mental health and outcomes of a regional physiotherapy-led post-arthroplasty review clinic.

OBJECTIVE: To determine whether 12-month hip and knee outcomes of a regional arthroplasty clinic were comparable to results from metropolitan-based clinics, and to explore a possible relationship between body mass index and depression to identify groups at risk of not achieving optimal outcomes. DESIGN: A prospective observational study. SETTING: A regional physiotherapy-led post-arthroplasty review clinic. PARTICIPANTS: Patients after hip or knee replacement. INTERVENTIONS: Patients underwent either total hip or total knee joint arthroplasty. MAIN OUTCOME MEASURES: SF-12 Health Survey, Oxford Hip/Knee Scale, 10-minute walk test, knee range of motion, body mass index and the Hospital Anxiety and Depression Scale. RESULTS: Physical outcomes were comparable to those reported by metropolitan-based clinics. People with a high body mass index showed most improvement in the severity of depression compared to those with a lower body mass index. CONCLUSION: It is important to consider the long-term effects of obesity on arthroplasty outcomes.

Randomized controlled trial of the effect of additional functional exercise during slow-stream rehabilitation in a regional center.

OBJECTIVE: To evaluate whether adding functional exercise training to standard physiotherapy during residential slow-stream rehabilitation (SSR) improves discharge outcomes and functional ability. DESIGN: Randomized controlled trial. SETTING: A regional hospital. PARTICIPANTS: Older people (N=60) admitted to SSR. INTERVENTION: All participants received standard physiotherapy. An individualized functional incidental training (FIT) program was implemented for intervention participants consisting of 4 extra episodes of functional exercise daily for the period of SSR. Research assistants visited twice weekly to practice and progress FIT programs. MAIN OUTCOME MEASURES: Outcome measures included discharge destination, participant-expected discharge destination, and functional tests of the Berg Balance Scale (BBS), de Morton Mobility Index (DEMMI), and 5 times sit-to-stand test (FTSTS) at admission and discharge. RESULTS: Fifty-two participants completed the study. At baseline, the SSR group achieved higher scores on the BBS, DEMMI, and FTSTS. There was no significant difference in discharge destination between groups (P=.305). The difference in functional change between groups from admission to discharge on the BBS, DEMMI, and FTSTS was not significant. Participant-expected discharge destination was significantly associated with eventual discharge destination (χ1(2)=8.40, P=.004). CONCLUSIONS: Adding FIT to standard physiotherapy did not improve discharge outcomes and did not have a statistically significant effect on function, but may have a small effect on balance. Patient expected and actual discharge destinations were associated.

Subzero temperature chromatography and top-down mass spectrometry for protein higher-order structure characterization: method validation and application to therapeutic antibodies.

Characterization of the higher-order structure and structural dynamics of proteins is crucial for in-depth understanding of their functions. Amide hydrogen/deuterium exchange (HDX), monitored by mass spectrometry (MS), is now a popular technique for measuring protein higher-order structural changes. Although the proteolysis-based HDX-MS approach is most commonly used, the "top-down" approach, which fragments intact proteins directly using electron-based dissociation, is becoming an important alternative and has several advantages. However, the commonly used top-down strategies are direct-infusion based and thus can only be used with volatile buffers. This has meant that the "top-down" approach could not be used for studying proteins under physiological conditions-the very conditions which are often very important for preserving a protein's native structure and function. More complex proteins such as those with disulfide bonds present another challenge. Therefore, there is significant interest in developing novel top-down HDX methods that are applicable to all types of protein samples. In this paper, we show how top-down electron capture dissociation and subzero temperature HPLC can be combined and used for this purpose. This method keeps the back-exchange level as low as 2% and has no limitations in terms of protein type and sample solution conditions. Close to single-residue level protein structural information can be generated. The new method is validated through comparison with NMR data using calmodulin as a model protein. Its capability of determining structural changes in therapeutic antibodies (Herceptin) is also demonstrated.

Mass spectrometry in high-throughput clinical biomarker assays: multiple reaction monitoring.

Clinical biomarker discovery, verification, and validation are facilitated by the latest technological advances in mass spectrometry. It is now possible to analyze simultaneously group of tens or hundreds of biomarkers in a blood sample using multiple reaction monitoring (MRM), a tandem mass spectrometric method. However, these newly-developed methods face new challenges, including standardization, calibration, and the determination of analytical and biological variation. Here we illustrate the background, pre-analytical sample preparation, and biomarker assay development using an MRM-mass spectrometric method. In addition, special attention is given to future standardization methods to enable widespread use of the technology.

The moderating role of psychological resilience in the relationship between fear of COVID-19 and psychological distress, in a cohort of rural and regional healthcare workers. During major lockdowns in Victoria, Australia 2020-2021.

The emergence of the COVID-19 pandemic resulted in substantial pressures for healthcare workers across the world. The association between fear of COVID-19 and psychological distress, and the role of psychological resilience have gained research interest. The current study aimed to investigate the cross-sectional association between fear of COVID-19 and psychological distress, in Australian rural/regional healthcare workers and determine whether resilience modifies this association. Most participants were nurses (38.0%), mean age was 44.9 years, and 80.5% were female (N = 1313). An adjusted logistic regression analysis showed that the highest tertile of the Fear of COVID-19 scale was associated with higher odds of moderate to severe symptoms of anxiety (OR = 3.72, 95% CI = 2.27, 6.11; p < 0.001) and depression (OR = 3.48, 95% CI = 2.30, 5.28; p < 0.001). Healthcare workers with high level of fear of COVID-19 and low level of resilience were much more likely to report moderate to severe symptoms of anxiety (OR = 12.27, 95% CI = 6.65-22.65, p < 0.001) and depression (OR = 12.21, 95% CI = 6.93-21.50, p < 0.001) when compared to healthcare workers with low level of fear of COVID-19 and high level of resilience. A cross-sectional design was used and therefore cause and effect between fear of COVID-19 and psychological distress cannot be inferred. Longitudinal research is needed to investigate the possible causal relationship. These findings highlight the potential mental health effects of fear of COVID-19 on HCWs and demonstrate the importance of resilience as a possible moderator of these effects.

Health and Wellbeing of Regional and Rural Australian Healthcare Workers during the COVID-19 Pandemic: Baseline Cross-Sectional Findings from the Loddon Mallee Healthcare Worker COVID-19 Study-A Prospective Cohort Study.

BACKGROUND: Coronavirus 19 (COVID-19) has created complex pressures and challenges for healthcare systems worldwide; however, little is known about the impacts COVID-19 has had on regional/rural healthcare workers. The Loddon Mallee Healthcare Worker COVID-19 Study (LMHCWCS) cohort was established to explore and describe the immediate and long-term impacts of the COVID-19 pandemic on regional and rural healthcare workers. METHODS: Eligible healthcare workers employed within 23 different healthcare organisations located in the Loddon Mallee region of Victoria, Australia, were included. In this cohort study, a total of 1313 participants were recruited from November 2020-May 2021. Symptoms of depression, anxiety, post-traumatic stress, and burnout were measured using the Patient Health Questionnaire-9 (PHQ-9), Generalised Anxiety Disorder-7 (GAD-7), Impact of Events Scale-6 (IES-6), and Copenhagen Burnout Inventory (CBI), respectively. Resilience and optimism were measured using the Brief Resilience Scale and Life Orientation Test-Revised (LOT-R), respectively. Subjective fear of COVID-19 was measured using the Fear of COVID-19 Scale. RESULTS: These cross-sectional baseline findings demonstrate that regional/rural healthcare workers were experiencing moderate/severe depressive symptoms (n = 211, 16.1%), moderate to severe anxiety symptoms (n = 193, 14.7%), and high personal or patient/client burnout with median total scores of 46.4 (IQR = 28.6) and 25.0 (IQR = 29.2), respectively. There was a moderate degree of COVID-19-related fear. However, most participants demonstrated a normal/high degree of resilience (n = 854, 65.0%). Based on self-reporting, 15.4% had a BMI from 18.5 to 24.9 kgm2 and 37.0% have a BMI of 25 kgm2 or over. Overall, 7.3% of participants reported they were current smokers and 20.6% reported alcohol consumption that is considered moderate/high-risk drinking. Only 21.2% of the sample reported consuming four or more serves of vegetables daily and 37.8% reported consuming two or more serves of fruit daily. There were 48.0% the sample who reported having poor sleep quality measured using the Pittsburgh Sleep Quality Index (PSQI). CONCLUSION: Regional/rural healthcare workers in Victoria, Australia, were experiencing a moderate to high degree of psychological distress during the early stages of the pandemic. However, most participants demonstrated a normal/high degree of resilience. Findings will be used to inform policy options to support healthcare workers in responding to future pandemics.

Upconversion Nanoparticles as Imaging Agents for Dental Caries.

Dental caries (cavities) is the most prevalent disease worldwide; however, current detection methods suffer from issues associated with sensitivity, subjective interpretations, and false positive identification of carious lesions. Therefore, there is a great need for the development of more sensitive, noninvasive imaging methods. The 30 nm core@shell NaYF4; Yb20%, Er2%@NaYF4 upconversion nanoparticles (UCNPs), exhibiting strong upconversion emission from erbium upon excitation at 975 nm, were used in the imaging of locations of demineralized enamel and oral biofilm formation for the detection of dental caries. UCNPs were modified with poly(acrylic acid) (PAA) or poly-d-lysine (PDL), and targeting peptides were conjugated to their surface with affinity for either hydroxyapatite (HA), the material dentin is composed of, or the caries causing bacteria Streptococcus mutans. A statistical difference in the binding of targeted vs nontargeted UCNPs to HA was observed after 15 min, using both upconversion fluorescence of UCNP (p < 0.001) and elemental analysis (p = 0.0091). Additionally, using the HA targeted UCNPs, holes drilled in the enamel of bovine teeth with diameters of 1.0 and 0.5 mm were visible by the green emission after a 20 min incubation with no observable nonspecific binding. A statistical difference was also observed in the binding of targeted versus nontargeted UCNPs to S. mutans biofilms. This difference was observed after 15 min, using the fluorescence measurements (p = 0.0125), and only 10 min (p < 0.001) using elemental analysis via ICP-OES measurements of Y3+ concentration present in the biofilms. These results highlight the potential of these UCNPs for use in noninvasive imaging diagnosis of oral disease.

Learning by doing and creation of the shared discovery curriculum.

BACKGROUND: The Michigan State College of Human Medicine began as an experiment to teach medical students in community-based settings and to create a primary care workforce for the state. Decades later, CHM faced internal and external challenges that spurred creation of a new curriculum - the Share Discovery Curriculum - founded on learning by doing and other learning theories. METHODS: A curricular design group (CDG) developed guiding principles for reform. Based on this, pedagogies and structures were selected to achieve this vision and developed into a curricular structure. Components of the first-year curriculum were piloted with a group of students and faculty members. RESULTS: Six guiding principles were endorsed, grounded in learning theories such as Dewey's Learning by Doing. Based upon these, several key features of the new curriculum emerged: learning communities; one-on-one coaches for students; symptom-based presentations for content; simulation, authentic clinical tasks, flipped classrooms, and modified practice-based learning as primary teaching modalities; early, integrated clinical and scientific learning; milestones as course learning objectives; and a multidimensional, competency-based assessment system. DISCUSSION: The process and outcomes described here are intended as an exemplar for schools undertaking curricular change. Early stakeholder engagement, faculty development, sustainable administrative systems, and managing complexity are core to the success of such endeavors.

Stroke quality metrics: systematic reviews of the relationships to patient-centered outcomes and impact of public reporting.

BACKGROUND AND PURPOSE: Stroke quality metrics play an increasingly important role in quality improvement and policies related to provider reimbursement, accreditation, and public reporting. We conducted 2 systematic reviews examining the relationships between compliance with stroke quality metrics and patient-centered outcomes, and public reporting of stroke metrics and quality improvement, quality of care, or outcomes. METHODS: MEDLINE and EMBASE databases were searched to identify studies that evaluated the relationship between stroke quality metric compliance and patient-centered outcomes in acute hospital settings and public reporting of stroke quality metrics and quality improvement activities, quality of care, or patient outcomes. We specifically excluded studies that evaluated the effect of stroke units or hospital certification. RESULTS: Fourteen studies met eligibility criteria for the review of stroke quality metric compliance and patient-centered outcomes; 9 found mostly positive associations, whereas 5 found no or very limited associations. Only 2 eligible studies were found that directly addressed the public reporting of stroke quality metrics. CONCLUSIONS: Some studies have found positive associations between stroke metric compliance and improved patient-centered outcomes. However, high-quality studies are lacking and several methodological difficulties make the interpretation of the reported associations challenging. Information on the impact of public reporting of stroke quality metric data is extremely limited. Legitimate questions remain as to whether public reporting of stroke metrics is accurate, effective, or has the potential for unintended consequences. The generation of high-quality data examining quality metrics and stroke outcomes as well as the impact of public reporting should be given priority.

Quantitation of spatially-localized proteins in tissue samples using MALDI-MRM imaging.

MALDI imaging allows the creation of a "molecular image" of a tissue slice. This image is reconstructed from the ion abundances in spectra obtained while rastering the laser over the tissue. These images can then be correlated with tissue histology to detect potential biomarkers of, for example, aberrant cell types. MALDI, however, is known to have problems with ion suppression, making it difficult to correlate measured ion abundance with concentration. It would be advantageous to have a method which could provide more accurate protein concentration measurements, particularly for screening applications or for precise comparisons between samples. In this paper, we report the development of a novel MALDI imaging method for the localization and accurate quantitation of proteins in tissues. This method involves optimization of in situ tryptic digestion, followed by reproducible and uniform deposition of an isotopically labeled standard peptide from a target protein onto the tissue, using an aerosol-generating device. Data is acquired by MALDI multiple reaction monitoring (MRM) mass spectrometry (MS), and accurate peptide quantitation is determined from the ratio of MRM transitions for the endogenous unlabeled proteolytic peptides to the corresponding transitions from the applied isotopically labeled standard peptides. In a parallel experiment, the quantity of the labeled peptide applied to the tissue was determined using a standard curve generated from MALDI time-of-flight (TOF) MS data. This external calibration curve was then used to determine the quantity of endogenous peptide in a given area. All standard curves generate by this method had coefficients of determination greater than 0.97. These proof-of-concept experiments using MALDI MRM-based imaging show the feasibility for the precise and accurate quantitation of tissue protein concentrations over 2 orders of magnitude, while maintaining the spatial localization information for the proteins.

Mass spectrometry-based structural proteomics.

Structural proteomics is the application of protein chemistry and modern mass spectrometric techniques to problems such as the characterization of protein structures and assemblies and the detailed determination of protein-protein interactions. The techniques used in structural proteomics include crosslinking, photoaffinity labeling, limited proteolysis, chemical protein modification and hydrogen/deuterium exchange, all followed by mass spectrometric analysis. None of these methods alone can provide complete structural information, but a "combination" of these complementary approaches can be used to provide enough information for answering important biological questions. Structural proteomics can help to determine, for example, the detailed structure of the interfaces between proteins that may be important drug targets and the interactions between proteins and ligands. In this review, we have tried to provide a brief overview of structural proteomics methodologies, illustrated with examples from our laboratory and from the literature.

Mealtime Support: A Pilot Case Series study of an Effective, Cost-saving Outpatient Hunger-Based Feeding Program for Tube Dependency.

Tube feeding is essential for children who cannot meet nutritional requirements orally. Over time, this can lead to tube dependency with negative impacts on the quality of life of children and families. Objective: We aimed to examine the efficacy of a multidisciplinary child-led, hunger-based approach called "Mealtime Support" at the Stollery Children's Hospital in Edmonton. Nutritional outcomes, parental satisfaction, and cost implications were evaluated over 9 months postprogram completion per child. Methods: The ambulatory meal program was delivered 2-3 times a day, for 2 weeks, by an occupational therapist and dietitian, under medical supervision. Hunger was promoted by reducing tube fed calories by 80% before commencement. Caregivers completed 12-question subjective surveys pre- and postintervention. Microcosting methods compared costs between the program and ongoing tube feeding. Results: From 2016 to 2017, 6 children were enrolled and 5 completed the program. At 1-month postintervention, 4/5 of the children were 100% orally fed. Parents reported improvement in mealtime struggles (P = 0.005), reduction in worry about their child's eating (P = 0.005), and improvement in their child's appetite/variety foods eaten (P = 0.004). Over 2 years, the potential cost savings were estimated at $43,471.00. By 6 months, all feeding tubes were removed. Conclusions: Mealtime support was safe and successful in reducing tube dependency and cost-effective compared to no intervention or hospital based programs, which suggests that there is a need to develop and fund Canadian outpatient feeding programs.

Discovery of biomarker candidates for coronary artery disease from an APOE-knock out mouse model using iTRAQ-based multiplex quantitative proteomics.

Due to the lack of precise markers indicative of its occurrence and progression, coronary artery disease (CAD), the most common type of heart diseases, is currently associated with high mortality in the United States. To systemically identify novel protein biomarkers associated with CAD progression for early diagnosis and possible therapeutic intervention, we employed an iTRAQ-based quantitative proteomic approach to analyze the proteome changes in the plasma collected from a pair of wild-type versus apolipoprotein E knockout (APOE(-/-) ) mice which were fed with a high fat diet. In a multiplex manner, iTRAQ serves as the quantitative 'in-spectra' marker for 'cross-sample' comparisons to determine the differentially expressed/secreted proteins caused by APOE knock-out. To obtain the most comprehensive proteomic data sets from this CAD-associated mouse model, we applied both MALDI and ESI-based mass spectrometric (MS) platforms coupled with two different schemes of multidimensional liquid chromatography (2-D LC) separation. We then comparatively analyzed a series of the plasma samples collected at 6 and 12 wk of age after the mice were fed with fat diets, where the 6- or 12-wk time point represents the early or intermediate phase of the fat-induced CAD, respectively. We then categorized those proteins showing abundance changes in accordance with APOE depletion. Several proteins such as the γ and ß chains of fibrinogen, apolipoprotein B, apolipoprotein C-I, and thrombospondin-4 were among the previously known CAD markers identified by other methods. Our results suggested that these unbiased proteomic methods are both feasible and a practical means of discovering potential biomarkers associated with CAD progression.

A novel proteolytic processing of prolysyl oxidase.

Lysyl oxidase (LOX) is an amine oxidase that is critical for the stability of connective tissues. The secreted proLOX is enzymatically quiescent and is activated through proteolytic cleavage between residues Gly(162) and Asp(163) (residue numbers according to the mouse LOX) by bone morphogenetic protein (BMP)-1 gene products. Here we report a novel processing of proLOX identified in vitro and in vivo. Two forms of mature LOX were identified and characterized by their immunoreactivity to specific antibodies, amine oxidase activity, and mass spectrometry. One form was identified as a well-characterized BMP-1 processed LOX protein. Another was found to be a truncated form of LOX resulting from the cleavage at the carboxy terminus of Arg(192). The truncated form of LOX still appeared to retain amine oxidase activity. The results from the proLOX gene deletion and mutation experiments indicated that the processing occurs independent of the cleavage of proLOX by BMP-1 gene products and likely requires the presence of LOX propeptide. These results indicate that proLOX could be processed by two different mechanisms producing two forms of active LOX.

Medical Student Progress Examination Performance and Its Relationship With Metacognition, Critical Thinking, and Self-Regulated Learning Strategies.

PURPOSE: Metacognition and critical thinking are essential for academic success. The relationship between these components and medical student learning, as assessed with progress examinations, informs curriculum development and efforts to ensure learning progression of all students. This study assessed learning mechanisms by modeling medical students' progress test performance longitudinally at Michigan State University College of Human Medicine. METHOD: Medical students' (n = 184) medical knowledge was assessed 5 times from fall 2017 through spring 2019 using the Comprehensive Basic Science Examination (CBSE). Structural equation modeling was conducted to investigate associations between 3 latent structures-metacognitive awareness, critical thinking, and self-regulation-and their relationship with students' initial CBSE scores and growth in such scores. The authors measured metacognitive knowledge and regulation by the Metacognitive Awareness Inventory, critical thinking skills by the Watson-Glaser Critical Thinking Appraisal, and self-regulation by the Learning and Study Strategies Inventory. RESULTS: Students' aggregate performance on 5 CBSE scores grew 31.0% the first semester, 16.5% the second semester, 30.1% the third semester, and 22.4% the last semester. Critical thinking had a significant positive relationship with initial performance (JOURNAL/acmed/04.03/00001888-202102000-00048/inline-graphic1/v/2021-01-22T214722Z/r/image-tiff1.956, P < .001), self-regulation had a significant positive relationship with growth (JOURNAL/acmed/04.03/00001888-202102000-00048/inline-graphic2/v/2021-01-22T214722Z/r/image-tiff3.287, P < .05), and metacognitive awareness had a negative relationship with growth of student performance in the progress test (JOURNAL/acmed/04.03/00001888-202102000-00048/inline-graphic3/v/2021-01-22T214722Z/r/image-tiff-3.426, P < .01). CONCLUSIONS: This structural equation framework is useful for examining the relationships among 3 latent structures-critical thinking, metacognition, and self-regulation-and their relationships with students' progress scores in academic achievement. The initial status of progress examination scores was explained by students' critical thinking ability, but their learning growth on the progress scores was explained by their self-regulation and metacognitive ability. These findings help explain student performance on standardized progress examinations and can aid in interventions to promote student success.