Understanding Personal Determinants of Lifting Strategy to Inform Movement-Focused Ergonomic Interventions
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Introduction: Lift training interventions are needed to reduce risk in jobs with non-modifiable demands, but to date have been generally ineffective. The lack of lift training effectiveness has been partially attributed to insufficient quality of content in the training programs. One way to improve the effectiveness of future lift training interventions may be to first understand what factors influence how a lifter chooses to move in the workplace (i.e., root causes). Previous research has identified that some lifters seem to consistently minimize resultant biomechanical exposures at the low back, but it is unclear why. If we can understand what personal factors influence how a lifter moves, lift training may be better targeted to address modifiable personal factors to minimize exposures during lifting. The overarching objective of this thesis was to quantify the variability in low back exposures during lifting and to further determine if variability could be explained by personal factors including ability to perceive proprioceptive information, expertise, and a range of structural (i.e., body mass and stature) and functional (i.e., strength and flexibility) factors. With this understanding, I then aimed to identify which modifiable personal factors have the greatest prospective benefit of biasing a lifter to adopt a movement strategy with lower resultant biomechanical exposures using a computational modelling approach. The impetus for this thesis is to develop critical evidence as needed to inform the development of future, more efficacious lift training interventions. Methods: A cross-sectional between-subjects experimental design was used to address the thesis objectives. A sample of 72 participants were recruited to perform a lifting protocol consisting of both job-specific and generic lifting tasks. Purposive sampling was used to recruit participants with a range of experience and demographics. Ability to perceive sensory feedback was assessed using lift force and lift posture matching tests. The average and variability in resultant peak low back compression and A-P shear force, as well as kinematic features of whole-body movement strategy, during lifting were quantified as dependent variables. Consistently lower magnitudes of biomechanical exposures within a personal factor group would support that this group defines a movement objective that aims to minimize resultant exposures on the low back. Using the experimentally obtained data, a probabilistic model was then developed that predicts the range of movement strategies and corresponding biomechanical exposures that are likely given a combination of underlying personal factors. Simulations were run to determine if improvements in any of ability to perceive sensory feedback, expertise, flexibility and/or strength capacity resulted in predicted reductions of low back exposure magnitude. Simulations were also conducted across a range of non-modifiable structural factors (i.e., sex, stature, and body mass) to evaluate whether the prospective benefit of improving modifiable factors to reduce low back exposures is generalizable across a working population. Results: Ability to perceive proprioceptive information (both force- and posture-sense) was associated with lower average and variability of low back loads. This suggests that individuals with better ability to perceive proprioceptive information may be more likely to define a movement objective to consistently minimize exposures. Albeit small effect sizes were observed with a maximum of 16% of variance in low back loads explained by proprioceptive ability. Both structural and functional factors were significant predictors of average peak low back loads in lifting. However, except for females having lower variability in exposures than males, no other associations of personal factors to variability in loads was observed. These findings support that the investigated structural and functional factors can bias the range of available movement strategies to lifters, but don’t necessarily influence towards a movement objective aiming to minimize low back loading. No differences in average or variability in peak low back loads were observed across expertise groups. While this finding highlights that expertise doesn’t seem to influence resultant exposures in lifting, differences in lifting kinematics were observed across groups suggesting other movement objectives may be defined as a function of expertise. The prospective ability of reducing peak low back loads by improving modifiable personal factors was assessed using the developed probabilistic model. While improving proprioceptive ability, functional knee range of motion and strength were statistically associated with reducing low back loads, only improving functional knee range of motion was interpreted to have clinically significant effects on reducing low back loads during lifting. Conclusion: In this thesis the variance in peak low back loads during lifting that could be explained independently and inter-dependently by personal factors was investigated. These findings have implications for the development of future lift training interventions where improvements to functional knee range of motion may lead to retained lifting behaviour changes to reduce resultant peak low back loads during lifting. Secondary benefits may also come from improving proprioceptive ability and strength. Future lift training interventions can be developed to leverage these findings in practice where these results support that improvements to underlying flexibility, strength and proprioceptive ability seem to be important factors allowing individuals to adopt lower exposure lifting strategy.
Cite this version of the work
Daniel Armstrong (2023). Understanding Personal Determinants of Lifting Strategy to Inform Movement-Focused Ergonomic Interventions. UWSpace. http://hdl.handle.net/10012/19331