The researchers assessed students face to face between January 2024 and January 2026 at the Faculty of Physical Therapy and Rehabilitation in Ankara. Of 136 volunteers who provided written informed consent, 132 met the eligibility criteria: 70 were third-year students and 62 were fourth-year students. Volunteers also had to report no pain at the time of assessment under the Extended Nordic Musculoskeletal Questionnaire. Exclusion criteria included spinal or extremity pain during the preceding three months, physician-diagnosed scoliosis, limb-length discrepancy, congenital or severe deformities, previous spinal surgery, inflammatory, infectious or neoplastic conditions, neurological or cognitive disorders, cardiorespiratory disease, current use of antidepressant or attention-enhancing medication, and menstrual irregularities. The investigators followed the STROBE reporting checklist, and the protocol was prospectively registered on ClinicalTrials.gov.

Spinal surface geometry was measured non-invasively with the DIERS Formetric 4D rasterstereography system. Participants removed upper-body clothing and jewelry, stood on a predefined line two metres from the device, faced away from the examiner and assumed their usual relaxed standing posture before remaining motionless. The equipment captured the surface topography of the back and reconstructed a three-dimensional model of the trunk, with software automatically identifying anatomical landmarks. Investigators derived three outcomes: trunk length between the vertebral prominens and the centre point between the sacral dimples, the maximum kyphotic angle between the cervicothoracic and thoracolumbar transition points, and the maximum lordotic angle between the thoracolumbar and lumbosacral transition points. All assessments occurred in the morning and used the same device and standardized procedure, although the exact assessment time, hydration status and recent physical loading were not standardized or controlled.

Third- and fourth-year students differed clearly in several non-spinal characteristics. Fourth-year students reported longer school-based standing and shorter school-based sitting durations, with both differences reported at p < 0.001. They also recorded lower trait-anxiety and burnout scores and more walking activity. By contrast, the three objective spinal measurements did not differ significantly between the cohorts. The kyphotic angle was numerically lower among fourth-year students but narrowly missed the threshold for statistical significance at p = 0.051. Thus, the clearest difference in the students’ learning environment—greater exposure to clinical training rather than predominantly classroom-based study—did not translate into a demonstrable between-year difference in the measured spinal parameters.

Trunk length nevertheless showed several adjusted statistical associations. In the first hierarchical regression model, height had a particularly strong positive association with trunk length, while body weight had a negative association. Academic year and time spent standing and sitting at school were not independently associated with trunk length after those initial adjustments. Adding psychological variables improved the model’s explanatory power, and higher trait-anxiety scores were associated with shorter trunk length. Adding sleep quality improved the model again: because higher Pittsburgh Sleep Quality Index scores represent poorer sleep, the result indicated that poorer sleep quality was associated with shorter trunk length. In the fully adjusted model, trait anxiety had a standardized coefficient of −0.148 and sleep quality a coefficient of −0.139. Together with the anthropometric, academic-year, school-exposure and physical-activity variables, the model explained 68.4% of trunk-length variance.

Physical activity did not add a statistically significant amount of explanatory power once the other factors were included. A similar pattern appeared for the spinal angles. The initial model explained 14.4% of kyphotic-angle variance, with academic year and body weight contributing to that model, but anxiety, burnout, sleep and physical activity did not substantially improve prediction. For lordotic angle, the initial model explained 28.1% of the variance, with age, weight and height contributing, while the later additions of psychophysiological measures, sleep and activity also failed to produce a significant improvement. The clearest adjusted relationships with trunk length therefore concerned trait anxiety and sleep, whereas the two angle measures were more closely associated with anthropometric and basic workload-related variables.

The exploratory mediation analysis produced a more limited result concerning emotional exhaustion. Using sleep quality as the proposed mediator, the researchers estimated an indirect association with trunk length of B = −0.300, with a bias-corrected 95% bootstrap confidence interval from −0.686 to −0.062 and p = 0.048. No significant direct or total association between emotional exhaustion and trunk length was detected, and no significant indirect effects appeared for state anxiety, trait anxiety, depersonalization or personal accomplishment. The analysis used 5,000 bootstrap resamples and 123 complete cases, with adjustment for class group, age, weight, height, total physical activity and standing and sitting durations. Because all variables were assessed cross-sectionally, the result cannot show that emotional exhaustion impaired sleep and that impaired sleep shortened the trunk, or that trunk length influenced either of the other measures. It is an adjusted statistical pathway that requires longitudinal testing.

The sleep result is compatible with evidence cited in the study that spinal dimensions and intervertebral-disc characteristics vary across daily loading and recovery cycles. Intervertebral discs undergo changes in height and volume as axial compression accumulates and is subsequently relieved, while sleep is a restorative process during which disc rehydration and partial restoration of spinal height can occur. Psychosocial strain has also been linked to impaired sleep continuity and depth, and trait anxiety represents a generally persistent psychological characteristic rather than a temporary state. These observations offer possible mechanisms, but the present study did not measure disc hydration, within-day spinal-height changes or the sequence of events, so it did not directly test any proposed biological pathway.

The use of three-dimensional objective assessment was one of the study’s methodological strengths. Earlier research in healthcare students has often relied on symptoms, observational posture tools such as the Rapid Entire Body Assessment and Rapid Upper Limb Assessment, or clinical scales such as the New York Posture Scale. Rasterstereography provided a radiation-free, non-invasive measure of trunk surface geometry and allowed investigators to examine subtle spinal characteristics alongside psychological burden, sleep, physical activity and educational exposure. The results suggest a reason to consider student spinal health through more than ergonomics alone: objective posture measures did not separate the academic years, while psychological and recovery-related variables were associated with one measured spinal parameter. The authors propose that educational strategies may benefit from considering biomechanics, psychological well-being and sleep recovery as interacting dimensions, but the study neither tested an educational intervention nor demonstrated improved student health outcomes.

Several limitations constrain how far the findings can be generalized. The cross-sectional design prevents causal and temporal conclusions; self-reported anxiety, burnout, sleep, physical activity and school-based exposure may contain reporting bias; and physical exposures outside the educational setting were not comprehensively measured. The study involved one institution, and the academic-year groups differed in sex distribution. Although the regressions accounted for major anthropometric and educational variables, other potentially relevant factors were not fully controlled. Complete-case regression analyses used 123 participants because a small amount of data were missing, and no prior sample-size calculation was performed. A sensitivity analysis based on the final model estimated a minimum detectable effect size of approximately f² = 0.16. Variations in exact assessment time, hydration, recent loading and menstrual-cycle phase may also have influenced the spinal measurements. Larger longitudinal studies and educational-intervention trials would be needed to determine whether the observed associations persist over time, change during training or respond to changes in student well-being practices.

Subject of Research: Associations of sleep, anxiety and burnout with objective spinal parameters in physiotherapy students

Article Title: Academic-year differences and psychophysiological associations with objective spinal parameters in physiotherapy students: a cross-sectional DIERS formetric 4D study

Article References: Numanoğlu, E. A., Arık, A., Pamukçu, E., Tanımlı, Y. G., & Ergit, B. (2026). Academic-year differences and psychophysiological associations with objective spinal parameters in physiotherapy students: a cross-sectional DIERS formetric 4D study. BMC Medical Education, 26(1), Article 1703. https://doi.org/10.1186/s12909-026-10505-2

Image Credits: AI Generated

DOI: 10.1186/s12909-026-10505-2

Keywords: physiotherapy students, trunk length, sleep quality, trait anxiety, emotional exhaustion, spinal posture, rasterstereography, academic training, cross-sectional study, Academic-year, differences, psychophysiological

The research, led by Kwong Ming Tse of Swinburne University of Technology and the University of Melbourne, together with Dale Robinson, Melanie Franklyn of Australia’s Defence Science and Technology Group, and Peter Vee Sin Lee of the University of Melbourne, tackled a problem that has long frustrated injury biomechanics researchers. Most existing spinal injury criteria were derived from tests on entire spinal columns or large spinal sections, which provide useful system-level tolerance estimates but reveal little about which individual vertebra is most likely to fail. Earlier work had hinted at the importance of this question. Studies of vertical accelerations simulating aircraft ejection showed that as acceleration increases, injuries migrate from the thoracolumbar junction down toward the lower lumbar spine. Sled experiments simulating underbelly blast found that longer-duration seat pulses of 55 milliseconds reduced spinal responses by 68 to 78 percent compared with shorter 10-millisecond pulses, producing fewer pelvic and spinal injuries. But none of these approaches could isolate the vulnerability of each lumbar level.

To fill this gap, the team took an unusual two-pronged approach. They obtained five cadaveric lumbar spine specimens, each free of severe abnormalities as confirmed by radiography and visual inspection, and used dual-energy X-ray absorptiometry to verify that all specimens had areal bone mineral density values within the normal range reported for young adult males aged 17 to 25 years, despite the donors being under 62 years of age. From each spine they isolated a three-vertebra segment — a central vertebra flanked by its neighbours and two intervertebral discs — with the outer vertebrae partially embedded in dental plaster potting fixtures and the middle vertebra deliberately left exposed. Each segment was then compressed at approximately one metre per second on a mechanical testing machine, a rate chosen to bridge conventional quasi-static testing and the more severe blast-level conditions, where reported vehicle floor velocities in live-fire blast events range from 2.2 to 12.8 metres per second. The researchers note that the velocity actually experienced by the lumbar spine is lower than the floor velocity because the seat, pelvis, and surrounding soft tissues attenuate the load.

Alongside the physical tests, the team built specimen-specific finite element models of each three-vertebra segment from high-resolution computed tomography scans with a pixel size of just 0.098 millimetres. The models were anatomically meticulous: vertebral bodies were discretised with roughly 145,000 tetrahedral elements each, cortical shells were divided into seven regions with distinct properties, intervertebral discs comprised ten annulus layers surrounding a nucleus pulposus modelled with hyperelastic material laws, and all seven major spinal ligaments were represented as membrane elements. Crucially, the CT data were used to assign bone material properties element by element, using a calibration phantom to convert Hounsfield units to bone density and a power-law regression to derive Young’s modulus for the trabecular bone. When the models were run in an explicit finite element solver replicating the compression experiments, they reproduced the measured force–displacement responses with coefficients of determination between 0.93 and 0.98, and predicted fracture loads within 10 to 34 percent of the experimental values. The models also captured the observed failure patterns, including coronal split fractures of the vertebral body, impaction fractures of the superior endplate, and isolated trabecular fractures — morphologies consistent with those reported clinically in underbelly blast casualties.

With the models validated, the researchers unleashed them on a series of parametric simulations that would be impossible to perform experimentally. They varied spinal posture by adding 10 degrees of flexion or extension, mimicking the range of sagittal intervertebral rotation during maximal seated trunk movement, and added 10 degrees of lateral bending comparable to voluntary side-bending. They scaled vertebral height and cross-sectional area by plus or minus 10 percent, reflecting anthropometric variation across a military population. And they swept areal bone mineral density across a physiologically relevant range of 0.8 to 1.4 grams per square centimetre, corresponding to young healthy soldiers. The results revealed a striking level-dependence that no whole-column experiment could have exposed.

Posture emerged as a powerful, level-specific modulator of fracture risk. At L1, L2, and L4, flexion generally reduced the likelihood of injury, shifting the fracture probability curves rightward, while extension increased the risk. At L3 the trend reversed, and at L5 both flexion and extension reduced fracture tolerance — a unique behaviour the authors attribute to the biomechanical complexity of the lowest lumbar vertebra, including its adjacency to the sacrum and its altered facet joint geometry. Lateral bending increased fracture susceptibility at the lower lumbar levels, particularly L5, where the decreased fracture load coincided with a marked increase in vertebral body loading. The stiffness analysis added another layer of nuance: at the L4–L5–S1 segment, flexion cut the compressive load at 5 millimetres of displacement from 6,545 newtons to 2,499 newtons, a 62 percent reduction. Importantly, changes in axial stiffness did not consistently translate into changes in fracture load, underscoring that stiffness and strength are distinct metrics that both matter when assessing injury tolerance.

Geometry and bone quality told a more consistent story. Increasing vertebral height reduced axial stiffness and fracture load at all levels except L5, where the opposite trend appeared — a finding that contrasts with earlier ex vivo work reporting a positive correlation between vertebral height and strength, and one the authors suggest may reflect biological factors such as bone mineral density and trabecular connectivity not captured in the models. Larger cross-sectional area, by contrast, consistently enhanced mechanical resistance at every level. Areal bone mineral density proved to be a strong and reliable positive predictor of compressive fracture tolerance across the entire lumbar spine, with higher density producing systematic increases in both stiffness and failure load. Yet the analysis produced a surprise: a measure called axial rigidity, derived from CT-based geometry and material properties, actually outperformed bone mineral density as a predictor of injury risk, yielding injury curves with narrow confidence intervals that converged toward a single vertebra-independent relationship.

The practical implications reach well beyond the laboratory. Fracture tolerance generally increased from L1 to L4, tracking the increasing size and strength of the vertebrae, but L5 consistently bucked the trend, remaining highly vulnerable despite its larger dimensions. This persistent weakness identifies the lower lumbar spine as a critical target for injury mitigation — a finding that could guide the design of vehicle seats, armour, and blast-attenuating flooring. The injury prediction curves, generated using parametric survival analysis with a Weibull distribution, also align closely with injury corridors previously developed for whole lumbar spine segments, lending credibility to the modelling approach. The authors caution that their fracture tolerance values should be read as vertebral-level injury metrics rather than direct operational thresholds, since the experiments isolated axial compression and did not replicate the full combined-loading environment of a real blast, and the experimental component involved one specimen per lumbar level owing to the scarcity of suitable cadaveric material.

Even with those limitations, the study marks a genuine milestone. By integrating spinal posture, vertebral geometry, and bone quality into validated, specimen-specific finite element models, the researchers have created tools for injury prediction that are both anatomically specific and clinically relevant. The framework extends naturally beyond the battlefield: the same biomechanics governs spinal loading in aviation ejections, helicopter crashes, and occupational impact scenarios. And the finding that axial rigidity may be a more robust predictor of vertebral fragility than the bone density measurements routinely used in clinics hints at a future where fracture risk assessment becomes more precise — not just for soldiers facing blast threats, but for anyone whose spine must withstand the sudden, merciless forces of a high-rate impact.

Subject of Research: Level-specific biomechanical tolerance of lumbar vertebrae to high-rate vertical compression relevant to underbelly blast injury

Article Title: Level-Specific Lumbar Spine Injury Tolerance Under High-Rate Vertical Loading Relevant to Underbelly Blast Environments: A Combined Cadaveric Experimental and Finite Element Study of Three-Vertebra Spinal Segments

Article References: Tse, K. M., Robinson, D., Franklyn, M., & Lee, P. V. S. (2026). Level-Specific Lumbar Spine Injury Tolerance Under High-Rate Vertical Loading Relevant to Underbelly Blast Environments: A Combined Cadaveric Experimental and Finite Element Study of Three-Vertebra Spinal Segments. Annals of Biomedical Engineering. https://doi.org/10.1007/s10439-026-04347-8

Image Credits: AI Generated

DOI: 10.1007/s10439-026-04347-8

Keywords: lumbar spine, underbelly blast, finite element model, cadaveric testing, fracture tolerance, bone mineral density, spinal posture, injury prediction curves, military biomechanics, burst fractures, vertebral geometry, axial rigidity