Investigating the Effects of Applying Different Actigraphy Processing Approaches to Examine the Sleep Data of Patients With Neuropathic Pain

in Journal for the Measurement of Physical Behaviour

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Hannah J. Coyle-AsbilDepartment of Human Health and Nutritional Sciences, University of Guelph, Guelph, Canada
Department of Anesthesiology and Pain Management, Women’s College Hospital, Toronto, Canada
Department of Anesthesiology and Pain Management, University Health Network, University of Toronto, Toronto, Canada

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Anuj BhatiaDepartment of Anesthesiology and Pain Management, Women’s College Hospital, Toronto, Canada
Department of Anesthesiology and Pain Management, University Health Network, University of Toronto, Toronto, Canada
Department of Anesthesia and Pain Medicine, University of Toronto, Toronto, Canada

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Andrew LimDepartment of Anesthesia and Pain Medicine, University of Toronto, Toronto, Canada
Department of Neurology, Sunnybrook Health Sciences Center, Toronto, Canada

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Mandeep SinghDepartment of Anesthesiology and Pain Management, Women’s College Hospital, Toronto, Canada
Department of Anesthesiology and Pain Management, University Health Network, University of Toronto, Toronto, Canada
Department of Anesthesia and Pain Medicine, University of Toronto, Toronto, Canada

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Individuals suffering from neuropathic pain commonly report issues associated with sleep. To measure sleep in this population, researchers have used actigraphy. Historically, actigraphy data have been analyzed in the form of counts; however, due to the proprietary nature, many opt to quantify data in its raw form. Various processing techniques exist to accomplish this; however, it remains unclear how they compare to one another. This study sought to compare sleep measures derived using the GGIR R package versus the GENEActiv (GA) R Markdown tool in a neuropathic pain population. It was hypothesized that the processing techniques would yield significantly different sleep outcomes. One hundred and twelve individuals (mean age = 52.72 ± 13.01 years; 60 M) with neuropathic pain in their back and/or lower limbs were included. While simultaneously undergoing spinal cord stimulation, actigraphy devices were worn on the wrist for a minimum of 7 days (GA; 50 Hz). Upon completing the protocol, sleep outcome measures were calculated using (a) the GGIR R package and (b) the GA R Markdown tool. To compare these algorithms, paired-samples t tests and Bland–Altman plots were used to compare the total sleep time, sleep efficiency, wake after sleep onset, sleep onset time, and rise times. According to the paired-samples t test, the GA R Markdown yielded lower total sleep time and sleep efficiency and a greater wake after sleep onset, compared with the GGIR package. Furthermore, later sleep onset times and earlier rise times were reported by the GGIR package compared with the GA R Markdown.

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  • Activinsights. (2019). Activinsights speaking & exhibiting at ICAMPAM, Maastricht. https://www.activinsights.com/activinsights-speaking-exhibiting-at-icampam-maastricht-june-26-28-2019/

    • Search Google Scholar
    • Export Citation
  • Andrews, N.E., Strong, J., Meredith, P.J., & D’Arrigo, R.G. (2014). Association between physical activity and sleep in adults with chronic pain: A momentary, within-person perspective. Physical Therapy, 94(4), 499510. https://doi.org/10.2522/ptj.20130302

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Antczak, D., Lonsdale, C., del Pozo Cruz, B., Parker, P., & Sanders, T. (2021). Reliability of GENEActiv accelerometers to estimate sleep, physical activity, and sedentary time in children. International Journal of Behavioral Nutrition and Physical Activity, 18(1), 73. https://doi.org/10.1186/s12966-021-01143-6

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Attal, N., Lanteri-Minet, M., Laurent, B., Fermanian, J., & Bouhassira, D. (2011). The specific disease burden of neuropathic pain: Results of a French nationwide survey. Pain, 152(12), 28362843. https://doi.org/10.1016/j.pain.2011.09.014

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bjurstrom, M.F., & Irwin, M.R. (2016). Polysomnographic characteristics in nonmalignant chronic pain populations: A review of controlled studies. Sleep Medicine Reviews, 26, 7486. https://doi.org/10.1016/j.smrv.2015.03.004

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bland, J.M., & Altman, D.G. (2010). Statistical methods for assessing agreement between two methods of clinical measurement. International Journal of Nursing Studies, 47(8), 931936. https://doi.org/10.1016/j.ijnurstu.2009.10.001

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Blake, C., Cunningham, J., Power, C.K., Horan, S., Spencer, O., & Fullen, B.M. (2016). The impact of a cognitive behavioral pain management program on sleep in patients with chronic pain: Results of a pilot study. Pain Medicine, 17(2), 360369. https://doi.org/10.1111/pme.12903

    • Search Google Scholar
    • Export Citation
  • Bouhassira, D., Lantéri-Minet, M., Attal, N., Laurent, B., & Touboul, C. (2008). Prevalence of chronic pain with neuropathic characteristics in the general population. Pain, 136(3), 380387. https://doi.org/10.1016/j.pain.2007.08.013

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Burgess, H.J., Rizvydeen, M., Kimura, M., Pollack, M.H., Hobfoll, S.E., Rajan, K.B., & Burns, J.W. (2018). An open trial of morning bright light treatment among US military veterans with chronic low back pain: A pilot study. Pain Medicine, 20(4), 770778. https://doi.org/10.1093/pm/pny174

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Curtis, A.F., Williams, J.M., McCoy, K., & McCrae, C.S. (2018). Chronic pain, sleep, and cognition in older adults with insomnia: A daily multilevel analysis.. Journal of Clinical Sleep Medicine, 14(10), 17651772. https://doi.org/10.5664/jcsm.7392

    • Crossref
    • Search Google Scholar
    • Export Citation
  • De Jaeger, M., Goudman, L., De Groote, S., Rigoard, P., Monlezun, O., & Moens, M. (2019). Does spinal cord stimulation really influence sleep? Neuromodulation: Technology at the Neural Interface, 22(3), 311316. https://doi.org/https://doi.org/10.1111/ner.12850

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fishbain, D.A., Cole, B., Lewis, J.E., & Gao, J. (2010). What is the evidence for chronic pain being etiologically associated with the DSM-IV category of sleep disorder due to a general medical condition? A structured evidence-based review. Pain Medicine, 11(2), 158179. https://doi.org/10.1111/j.1526-4637.2009.00706.x

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guntel, M., Huzmeli, E.D., & Melek, I. (2021). Patients with neuropathic pain have poor sleep quality. The Journal of Nervous and Mental Disease, 209(7), 505509. https://doi.org/10.1097/nmd.0000000000001325

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jank, R., Gallee, A., Boeckle, M., Fiegl, S., & Pieh, C. (2017). Chronic pain and sleep disorders in primary care. Pain Research and Treatment, 2017, Article 9081802. https://doi.org/10.1155/2017/9081802

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lunde, L.-H., Pallesen, S., Krangnes, L., & Nordhus, I.H. (2010). Characteristics of sleep in older persons with chronic pain: A study based on actigraphy and self-reporting. Clinical Journal of Pain, 26(2), 132137. https://doi.org/10.1097/AJP.0b013e3181b61923

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Migueles, J.H., Rowlands, A.V., Huber, F., Sabia, S., & van Hees, V.T. (2019). GGIR: A research community–driven open source r package for generating physical activity and sleep outcomes from multi-day raw accelerometer data. Journal for the Measurement of Physical Behaviour, 2(3), 188196. https://doi.org/10.1123/jmpb.2018-0063

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Morin, C.M., Gibson, D., & Wade, J. (1998). Self-reported sleep and mood disturbance in chronic pain patients. The Clinical Journal of Pain, 14(4), 311314. https://journals.lww.com/clinicalpain/Fulltext/1998/12000/Self_Reported_Sleep_and_Mood_Disturbance_in.7.aspx

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Plekhanova, T., Rowlands, A.V., Yates, T., Hall, A., Brady, E.M., Davies, M., Khunti, K., & Edwardson, C.L. (2020). Equivalency of sleep estimates: Comparison of three research-grade accelerometers. Journal for the Measurement of Physical Behaviour, 3(4), 294303. https://doi.org/10.1123/jmpb.2019-0047

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Quan, S.F., Griswold, M.E., Iber, C., Nieto, F.J., Rapoport, D.M., Redline, S., Sanders, M., & Young, T. (2002). Short-term variability of respiration and sleep during unattended nonlaboratory polysomnography—The sleep heart health study. Sleep, 25(8), 843849.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ross, A.J., Yang, H., Larson, R.A., & Carter, J.R. (2014). Sleep efficiency and nocturnal hemodynamic dipping in young, normotensive adults. American Journal of Physiology-Regulatory, Integrative and Comparative Physiology, 307(7), R888R892. https://doi.org/10.1152/ajpregu.00211.2014

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Salin-Pascual, R.J., Roehrs, T.A., Merlotti, L.A., Zorick, F., & Roth, T. (1992). Long-term study of the sleep of insomnia patients with sleep state misperception and other insomnia patients. The American Journal of Psychiatry, 149(7), 904908. https://doi.org/10.1176/ajp.149.7.904

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tang, N.K.Y., Goodchild, C.E., & Salkovskis, P.M. (2012). Hybrid cognitive-behaviour therapy for individuals with insomnia and chronic pain: A pilot randomised controlled trial. Behaviour Research and Therapy, 50(12), 814821. https://doi.org/10.1016/j.brat.2012.08.006

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Toth, C., Lander, J., & Wiebe, S. (2009). The prevalence and impact of chronic pain with neuropathic pain symptoms in the general population. Pain Medicine, 10(5), 918929. https://doi.org/10.1111/j.1526-4637.2009.00655.x

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Turk, D.C. (2002). Clinical effectiveness and cost-effectiveness of treatments for patients with chronic pain. The Clinical Journal of Pain, 18(6), 355365. https://doi.org/10.1097/00002508-200211000-00003

    • Crossref
    • Search Google Scholar
    • Export Citation
  • van Hees, V.T., Fang, Z., Langford, J., Assah, F., Mohammad, A., da Silva, I.C., Trenell, M.I., White, T., Wareham, N.J., & Brage, S. (2014). Autocalibration of accelerometer data for free-living physical activity assessment using local gravity and temperature: An evaluation on four continents. Journal of Applied Physiology(1985), 117(7), 738744. https://doi.org/10.1152/japplphysiol.00421.2014

    • Crossref
    • Search Google Scholar
    • Export Citation
  • van Hees, V.T., Gorzelniak, L., Dean Leon, E.C., Eder, M., Pias, M., Taherian, S., Ekelund, U., Renstrom, F., Franks, P.W., Horsch, A., & Brage, S. (2013). Separating movement and gravity components in an acceleration signal and implications for the assessment of human daily physical activity. PLoS One, 8(4), Article e61691. https://doi.org/10.1371/journal.pone.0061691

    • Crossref
    • Search Google Scholar
    • Export Citation
  • van Hees, V.T., Sabia, S., Anderson, K.N., Denton, S.J., Oliver, J., Catt, M., Abell, J.G., Kivimäki, M., Trenell, M.I., & Singh-Manoux, A. (2015). A novel, open access method to assess sleep duration using a wrist-worn accelerometer. PLoS One, 10(11), Article e0142533. https://doi.org/10.1371/journal.pone.0142533

    • Crossref
    • Search Google Scholar
    • Export Citation
  • van Hees, V.T., Sabia, S., Jones, S.E., Wood, A.R., Anderson, K.N., Kivimaki, M., Frayling, T.M., Pack, A.I., Bucan, M., Trenell, M.I., Mazzotti, D.R., Gehrman, P.R., Singh-Manoux, B.A., & Weedon, M.N. (2018). Estimating sleep parameters using an accelerometer without sleep diary. Scientific Reports, 8(1), 12975. https://doi.org/10.1038/s41598-018-31266-z

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wendt, A., da Silva, I.C.M., Gonçalves, H., Menezes, A., Barros, F., & Wehrmeister, F.C. (2020). Short-term effect of physical activity on sleep health: A population-based study using accelerometry. Journal of Sport and Health Science. Advance online publication. https://doi.org/10.1016/j.jshs.2020.04.007

    • Search Google Scholar
    • Export Citation
  • Yang, A.F., & Xu, S. (2021). 455 Correlation between objective measures of sleep and nocturnal scratch in children with atopic dermatitis. Journal of Investigative Dermatology, 141(5 Suppl. 1). S79. https://doi.org/10.1016/j.jid.2021.02.478

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    • Search Google Scholar
    • Export Citation
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