Jack Parker

Dr. Jack Parker

Human Science Research Centre, University of Derby, Derby DE22 1GB, UK

Research Focus & Metrics

Academic Career Length

37Years (1990-Present)

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

Representative Publications

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3 June 2020 in JMIR mHealth and uHealth
Verified
Journal Article
Open access
CBClaire L Bentley
Claire L Bentley
LPLauren Powell
Lauren Powell
SPStephen Potter
Stephen Potter
JPJack Parker
Jack Parker
GMGail A Mountain
Gail A Mountain
MHMark Hawley
Mark Hawley
Background: Chronic obstructive pulmonary disease (COPD) is highly prevalent and significantly affects the daily functioning of patients. Self-management strategies, including increasing physical activity, can help people with COPD have better health and a better quality of life. Digital mobile health (mHealth) techniques have the potential to aid the delivery of self-management interventions for COPD. We developed an mHealth intervention (Self-Management supported by Assistive, Rehabilitative, and Telehealth technologies-COPD [SMART-COPD]), delivered via a smartphone app and an activity tracker, to help people with COPD maintain (or increase) physical activity after undertaking pulmonary rehabilitation (PR). Objective: This study aimed to determine the feasibility and acceptability of using the SMART-COPD intervention for the self-management of physical activity and to explore the feasibility of conducting a future randomized controlled trial (RCT) to investigate its effectiveness. Methods: We conducted a randomized feasibility study. A total of 30 participants with COPD were randomly allocated to receive the SMART-COPD intervention (n=19) or control (n=11). Participants used SMART-COPD throughout PR and for 8 weeks afterward (ie, maintenance) to set physical activity goals and monitor their progress. Questionnaire-based and physical activity–based outcome measures were taken at baseline, the end of PR, and the end of maintenance. Participants, and health care professionals involved in PR delivery, were interviewed about their experiences with the technology. Results: Overall, 47% (14/30) of participants withdrew from the study. Difficulty in using the technology was a common reason for withdrawal. Participants who completed the study had better baseline health and more prior experience with digital technology, compared with participants who withdrew. Participants who completed the study were generally positive about the technology and found it easy to use. Some participants felt their health had benefitted from using the technology and that it assisted them in achieving physical activity goals. Activity tracking and self-reporting were both found to be problematic as outcome measures of physical activity for this study. There was dissatisfaction among some control group members regarding their allocation. Conclusions: mHealth shows promise in helping people with COPD self-manage their physical activity levels. mHealth interventions for COPD self-management may be more acceptable to people with prior experience of using digital technology and may be more beneficial if used at an earlier stage of COPD. Simplicity and usability were more important for engagement with the SMART-COPD intervention than personalization; therefore, the intervention should be simplified for future use. Future evaluation will require consideration of individual factors and their effect on mHealth efficacy and use; within-subject comparison of step count values; and an opportunity for control group participants to use the intervention if an RCT were to be carried out. Sample size calculations for a future evaluation would need to consider the high dropout rates.

14 November 2018 in Sensors
Verified
Journal Article
Open access
PDF file
Mario Munoz-OrganeroMario Munoz-Organero
Mario Munoz-Organero
LPLauren Powell
Lauren Powell
BHBen Heller
Ben Heller
VHVal Harpin
Val Harpin
JPJack Parker
Jack Parker
Attention deficit and hyperactivity disorder (ADHD) is a neurodevelopmental disorder, which is characterized by inattention, hyperactivity and impulsive behaviors. In particular, children have difficulty keeping still exhibiting increased fine and gross motor activity. This paper focuses on analyzing the data obtained from two tri-axial accelerometers (one on the wrist of the dominant arm and the other on the ankle of the dominant leg) worn during school hours by a group of 22 children (11 children with ADHD and 11 paired controls). Five of the 11 ADHD diagnosed children were not on medication during the study. The children were not explicitly instructed to perform any particular activity but followed a normal session at school alternating classes of little or moderate physical activity with intermediate breaks of more prominent physical activity. The tri-axial acceleration signals were converted into 2D acceleration images and a Convolutional Neural Network (CNN) was trained to recognize the differences between non-medicated ADHD children and their paired controls. The results show that there were statistically significant differences in the way the two groups moved for the wrist accelerometer (t-test p-value <0.05). For the ankle accelerometer statistical significance was only achieved between data from the non-medicated children in the experimental group and the control group. Using a Convolutional Neural Network (CNN) to automatically extract embedded acceleration patterns and provide an objective measure to help in the diagnosis of ADHD, an accuracy of 0.875 for the wrist sensor and an accuracy of 0.9375 for the ankle sensor was achieved.

7 January 2016 in JMIR Rehabilitation and Assistive Technologies
Verified
Journal Article
Open access
SMSusan Mawson
Susan Mawson
NNNasrin Nasr
Nasrin Nasr
JPJack Parker
Jack Parker
RDRichard Davies
Richard Davies
Huiru ZhengHuiru Zheng
Huiru Zheng
GMGail Mountain
Gail Mountain
Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet

8 January 2020 in Journal of Medical Internet Research
Verified
Journal Article
Open access
JPJack Parker
Jack Parker
LPLauren Powell
Lauren Powell
SMSusan Mawson
Susan Mawson
Background: With advances in technology, the adoption of wearable devices has become a viable adjunct in poststroke rehabilitation. Upper limb (UL) impairment affects up to 77% of stroke survivors impacting on their ability to carry out everyday activities. However, despite an increase in research exploring these devices for UL rehabilitation, little is known of their effectiveness. Objective: This review aimed to assess the effectiveness of UL wearable technology for improving activity and participation in adult stroke survivors. Methods: Randomized controlled trials (RCTs) and randomized comparable trials of UL wearable technology for poststroke rehabilitation were included. Primary outcome measures were validated measures of activity and participation as defined by the International Classification of Functioning, Disability, and Health. Databases searched were MEDLINE, Web of Science (Core collection), CINAHL, and the Cochrane Library. The Cochrane Risk of Bias Tool was used to assess the methodological quality of the RCTs and the Downs and Black Instrument for the quality of non RCTs. Results: In the review, we included 11 studies with collectively 354 participants at baseline and 323 participants at final follow-up including control groups and participants poststroke. Participants’ stroke type and severity varied. Only 1 study found significant between-group differences for systems functioning and activity (P≤.02). The 11 included studies in this review had small sample sizes ranging from 5 to 99 participants at an average (mean) age of 57 years. Conclusions: This review has highlighted a number of reasons for insignificant findings in this area including low sample sizes and the appropriateness of the methodology for complex interventions. However, technology has the potential to measure outcomes, provide feedback, and engage users outside of clinical sessions. This could provide a platform for motivating stroke survivors to carry out more rehabilitation in the absence of a therapist, which could maximize recovery. Trial Registration: PROSPERO CRD42017057715; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=57715

16 October 2013 in Disability and Rehabilitation: Assistive Technology
Verified
Journal Article
Closed access
PDF file
SMSusan Mawson
Susan Mawson
NNNasrin Nasr
Nasrin Nasr
JPJack Parker
Jack Parker
Huiru ZhengHuiru Zheng
Huiru Zheng
RDRichard Davies
Richard Davies
GMGail Mountain
Gail Mountain
Purpose: To develop and evaluate an information and communication technology (ICT) solution for a post-stroke Personalised Self-Managed Rehabilitation System (PSMrS). The PSMrS translates current models of stroke rehabilitation and theories underpinning self-management and self-efficacy into an ICT-based system for home-based post-stroke rehabilitation. Methods: The interdisciplinary research team applied a hybrid of health and social sciences research methods and user-centred design methods. This included a series of home visits, focus groups, in-depth interviews, cultural probes and technology biographies. Results: The iterative development of both the content of the PSMrS and the interactive interfaces between the system and the user incorporates current models of post-stroke rehabilitation and addresses the factors that promote self-managed behaviour and self-efficacy such as mastery, verbal persuasion and physiological feedback. Conclusion: The methodological approach has ensured that the interactive technology has been driven by the needs of the stroke survivors and their carers in the context of their journey to both recovery and adaptation. Underpinned by theories of motor relearning, neuroplasticity, self-management and behaviour change, the PSMrS developed in this study has resulted in a personalised system for self-managed rehabilitation, which has the potential to change motor behaviour and promote the achievement of life goals for stroke survivors.

8 December 2017 in European Child & Adolescent Psychiatry
Verified
Journal Article
Open access
PDF file
LPLauren Powell
Lauren Powell
JPJack Parker
Jack Parker
VHValerie Harpin
Valerie Harpin
A number of technologies to help self-manage attention deficit hyperactivity disorder (ADHD) in children and young people (YP) have been developed. This review will assess the level of evidence for the use of such technologies. The review was undertaken in accordance with the general principles recommended in the Preferred Reporting Items for Systematic Reviews and Meta-Analysis. 7545 studies were screened. Fourteen studies of technology that aim to self-manage difficulties associated with ADHD in children and YP were included. Primary outcome measures were measures that assessed difficulties related to ADHD. Databases searched were MEDLINE, Web of Science (Core collection), CINAHL, the Cochrane Library, ProQuest ASSIA, PsycINFO and Scopus. The methodological quality of the studies was assessed. This review highlights the potential for the use of technology in paediatric ADHD management. However, it also demonstrates that current research lacks robustness; using small sample sizes, non-validated outcome measures and little psychoeducation component. Future research is required to investigate the value of technology in supporting children and YP with ADHD and a focus psychoeducation is needed.