Leanne Hassett

Dr. Leanne Hassett

orcid

Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2018 in Journal of Physiotherapy
Verified
Journal Article
Open access
DTDaniel Treacy
Daniel Treacy
LHLeanne Hassett
Leanne Hassett

2 March 2017 in Physical Therapy
Verified
Journal Article
Open access
PDF file
DTDaniel Treacy
Daniel Treacy
LHLeanne Hassett
Leanne Hassett
KSKarl Schurr
Karl Schurr
SCSakina Chagpar
Sakina Chagpar
SPSerene S. Paul
Serene S. Paul
CSCatherine Sherrington
Catherine Sherrington
Background. Commonly used activity monitors have been shown to be accurate in counting steps in active people; however, further validation is needed in slower walking populations. Objectives. To determine the validity of activity monitors for measuring step counts in rehabilitation inpatients compared with visually observed step counts. To explore the influence of gait parameters, activity monitor position, and use of walkers on activity monitor accuracy. Methods. One hundred and sixty-six inpatients admitted to a rehabilitation unit with an average walking speed of 0.4 m/s (SD 0.2) wore 16 activity monitors (7 different devices in different positions) simultaneously during 6-minute and 6-m walks. The number of steps taken during the tests was also counted by a physical therapist. Gait parameters were assessed using the GAITRite system. To analyze the influence of different gait parameters, the percentage accuracy for each monitor was graphed against various gait parameters for each activity monitor. Results. The StepWatch, Fitbit One worn on the ankle and the ActivPAL showed excellent agreement with observed step count (ICC2,1 0.98; 0.92; 0.78 respectively). Other devices (Fitbit Charge, Fitbit One worn on hip, G-Sensor, Garmin Vivofit, Actigraph) showed poor agreement with the observed step count (ICC2,1 0.12–0.40). Percentage agreement with observed step count was highest for the StepWatch (mean 98%). The StepWatch and the Fitbit One worn on the ankle maintained accuracy in individuals who walked more slowly and with shorter strides but other devices were less accurate in these individuals. Limitations. There were small numbers of participants for some gait parameters. Conclusions. The StepWatch showed the highest accuracy and closest agreement with observed step count. This device can be confidently used by researchers for accurate measurement of step counts in inpatient rehabilitation in individuals who walk slowly. If immediate feedback is desired, the Fitbit One when worn on the ankle would be the best choice for this population.

1 October 2004 in Brain Injury
Verified
Journal Article
Closed access
MLM. A. van Loo
M. A. van Loo
AMA. M. Moseley
A. M. Moseley
JBJ. M. Bosman
J. M. Bosman
RBR. A. de Bie
R. A. de Bie
LHLeanne Hassett
Leanne Hassett
Primary objective: Assess the test–re-test reliability of walking speed, step length and step width measurement in people with traumatic brain injury (TBI). Research design: Repeated measures (two test occasions). Methods: Thirteen people with TBI completed four comfortable and four fast-paced walking trials of the 10 m walk test and two trials of the 6-minute walk test (6MWT). Walking speed, step length and step width were measured during the 10 m walk test and walking distance and average speed were measured during the 6MWT. The tests were repeated 1-week later. Main results: Walking speed and distance showed excellent test–re-test reliability, with an intra-class correlation coefficient (ICC) of 0.95–0.96. Reliability was also high for step length and width measurement (ICC 0.91–0.98). Conclusions: This test–re-test reliability means that walking speed and distance and step length and width can be used by physiotherapists to monitor improvements in walking after TBI.

18 February 2020 in PLOS Medicine
Verified
Journal Article
Open access
PDF file
LHLeanne Hassett
Leanne Hassett
MBMaayken Van Den Berg
Maayken Van Den Berg
RLRichard I Lindley
Richard I Lindley
MCMaria Crotty
Maria Crotty
AMAnnie McCluskey
Annie McCluskey
CSCatherine Sherrington
Catherine Sherrington
Digitally enabled rehabilitation may lead to better outcomes but has not been tested in large pragmatic trials. We aimed to evaluate a tailored prescription of affordable digital devices in addition to usual care for people with mobility limitations admitted to aged care and neurological rehabilitation. We conducted a pragmatic, outcome-assessor-blinded, parallel-group randomised trial in 3 Australian hospitals in Sydney and Adelaide recruiting adults 18 to 101 years old with mobility limitations undertaking aged care and neurological inpatient rehabilitation. Both the intervention and control groups received usual multidisciplinary inpatient and post-hospital rehabilitation care as determined by the treating rehabilitation clinicians. In addition to usual care, the intervention group used devices to target mobility and physical activity problems, individually prescribed by a physiotherapist according to an intervention protocol, including virtual reality video games, activity monitors, and handheld computer devices for 6 months in hospital and at home. Co-primary outcomes were mobility (performance-based Short Physical Performance Battery [SPPB]; continuous version; range 0 to 3; higher score indicates better mobility) and upright time as a proxy measure of physical activity (proportion of the day upright measured with activPAL) at 6 months. The dataset was analysed using intention-to-treat principles. The trial was prospectively registered with the Australian New Zealand Clinical Trials Registry (ACTRN12614000936628). Between 22 September 2014 and 10 November 2016, 300 patients (mean age 74 years, SD 14; 50% female; 54% neurological condition causing activity limitation) were randomly assigned to intervention (n = 149) or control (n = 151) using a secure online database (REDCap) to achieve allocation concealment. Six-month assessments were completed by 258 participants (129 intervention, 129 control). Intervention participants received on average 12 (SD 11) supervised inpatient sessions using 4 (SD 1) different devices and 15 (SD 5) physiotherapy contacts supporting device use after hospital discharge. Changes in mobility scores were higher in the intervention group compared to the control group from baseline (SPPB [continuous, 0–3] mean [SD]: intervention group, 1.5 [0.7]; control group, 1.5 [0.8]) to 6 months (SPPB [continuous, 0–3] mean [SD]: intervention group, 2.3 [0.6]; control group, 2.1 [0.8]; mean between-group difference 0.2 points, 95% CI 0.1 to 0.3; p = 0.006). However, there was no evidence of a difference between groups for upright time at 6 months (mean [SD] proportion of the day spent upright at 6 months: intervention group, 18.2 [9.8]; control group, 18.4 [10.2]; mean between-group difference −0.2, 95% CI −2.7 to 2.3; p = 0.87). Scores were higher in the intervention group compared to the control group across most secondary mobility outcomes, but there was no evidence of a difference between groups for most other secondary outcomes including self-reported balance confidence and quality of life. No adverse events were reported in the intervention group. Thirteen participants died while in the trial (intervention group: 9; control group: 4) due to unrelated causes, and there was no evidence of a difference between groups in fall rates (unadjusted incidence rate ratio 1.19, 95% CI 0.78 to 1.83; p = 0.43). Study limitations include 15%–19% loss to follow-up at 6 months on the co-primary outcomes, as anticipated; the number of secondary outcome measures in our trial, which may increase the risk of a type I error; and potential low statistical power to demonstrate significant between-group differences on important secondary patient-reported outcomes. In this study, we observed improved mobility in people with a wide range of health conditions making use of digitally enabled rehabilitation, whereas time spent upright was not impacted. The trial was prospectively registered with the Australian New Zealand Clinical Trials Register; ACTRN12614000936628

2 May 2023 in Clinical Rehabilitation
Verified
Journal Article
Closed access
LPLouise Pearce
Louise Pearce
NCNathalia Costa
Nathalia Costa
CSCatherine Sherrington
Catherine Sherrington
LHLeanne Hassett
Leanne Hassett
Objective: Digital health interventions have potential to enhance rehabilitation services by increasing accessibility, affordability and scalability. However, implementation of digital interventions in rehabilitation is poorly understood. This scoping review aims to map current strategies, research designs, frameworks, outcomes and determinants used to support and evaluate the implementation of digital interventions in rehabilitation. Data sources: Comprehensive searches from inception until October 2022 of MEDLINE, CINAHL, PsycINFO, PEDro, SpeechBITE, NeuroBITE, REHABDATA, WHO International Clinical Trial Registry and the Cochrane Library. Methods: Two reviewers screened studies against the eligibility criteria. Implementation science taxonomies and methods, including Powell et al.'s compilation of implementation strategies, were used to guide analysis and synthesis of findings. Results: The search retrieved 13,833 papers and 23 studies were included. Only 4 studies were randomised controlled trials and 9 studies (39%) were feasibility studies. Thirty-seven discrete implementation strategies were reported across studies. Strategies related to training and educating clinicians (91%), providing interactive assistance (61%), and developing stakeholder interrelationships (43%) were most frequently reported. Few studies adequately described implementation strategies and methods for selecting strategies. Almost all studies measured implementation outcomes and determinants; most commonly, acceptability, compatibility and dose delivered of digital interventions. Conclusion: The rigour of implementation methods in the field is currently poor. Digital interventions require carefully planned and tailored implementation to facilitate successful adoption into rehabilitation practice. To keep pace with rapidly advancing technology, future rehabilitation research should prioritise using implementation science methods to explore and evaluate implementation while testing effectiveness of digital interventions.

1 November 2003 in Clinical Rehabilitation
Verified
Journal Article
Closed access
MLM A van Loo
M A van Loo
AMA M Moseley
A M Moseley
JBJ M Bosman
J M Bosman
RBR A de Bie
R A de Bie
LHLeanne Hassett
Leanne Hassett
Objective: To assess the inter-rater reliability and concurrent validity of walking speed measurement after traumatic brain injury. Design: Twelve subjects each completed five comfortably paced and five fast-paced walking trials. Walking speed was measured simultaneously by five observers using a stopwatch (clinical procedure) and by infrared timing gates (gold standard). Setting: Brain injury rehabilitation unit. Subjects: People with traumatic brain injury who could walk independently and were participating in a rehabilitation programme. Main outcome measures: Walking speed over a 10-metre distance. Results: The inter-rater reliability of walking speed measured using a stopwatch was very high, with an intraclass correlation coefficient of at least 0.998 for both comfortable and fast-paced tests. Concurrent validity was excellent for comfortable and fast tests, with perfect correlations between the stopwatch and infrared timing gate measurement procedures. Conclusions: Physiotherapists can use a stopwatch as a reliable and valid measurement tool to quantify walking speed over a short distance at both comfortable and fast paces in people who have sustained traumatic brain injuries.