=Paper=
{{Paper
|id=Vol-3124/paper12
|storemode=property
|title=Initial Experiences with Longitudinal Self-Tracking of Sleep and Low Back Pain
|pdfUrl=https://ceur-ws.org/Vol-3124/paper12.pdf
|volume=Vol-3124
|authors=Andy Alorwu,Aku Visuri,Simo Hosio
|dblpUrl=https://dblp.org/rec/conf/iui/AlorwuVH22
}}
==Initial Experiences with Longitudinal Self-Tracking of Sleep and Low Back Pain==
https://ceur-ws.org/Vol-3124/paper12.pdf
Initial Experiences with Longitudinal Self-Tracking of Sleep
and Low Back Pain
Andy Alorwu1 , Aku Visuri1 and Simo Hosio1
1
Center for Ubiquitous Computing, University of Oulu, Pentti Kaiteran katu 1, 90570 Oulu, Finland
Abstract
Low Back Pain (LBP) is a leading cause of disability globally, making it a serious public health concern. In this paper we
present the initial results and analysis of a longitudinal self-tracking study on sleep and LBP using a custom built mobile
application. We designed and deployed a mobile app for a period of 7 months to collect daily and monthly sleep and low back
pain data using custom and standardized questionnaires. We discuss the feasibility of our approach for longitudinal data
collection. Our data analysis reveals heterogeneity in user perceptions of factors that affect their sleep and LBP. Combining
our quantitative and qualitative analyses, we contribute to literature on sleep and LBP.
Keywords
Low Back Pain (LBP), Sleep, Longitudinal study, Self-tracking
1. Introduction We present an exploratory study where we used a
custom-built mobile application “Sleep Better with Back
The global population of people aged 60 and above has Pain” to investigate if, and in what ways, the felt pain
been growing steadily. Aided by advances in technology, affects the quality of sleep among people living with LBP.
healthcare delivery and the medical field, the average life Our main contributions are:
expectancy seems to be increasing. The longer people
live, the more susceptible they become to conditions such 1. A contribution to the literature on sleep and LBP,
as Low Back Pain (LBP) [1]. Thus, LBP has become a by investigating the relationship between LBP
central concern in the public health domain [2]. The and sleep.
economic effect of LBP on individuals, families, and the 2. An initial prototype of a mobile application to
society at large is high, with societal costs estimated to collect massive amount of subjective data on sleep
be 1% to 2% of the gross national product in Western and LBP.
countries, with a vast majority of these costs caused by 3. A feasibility study that highlights important con-
disability and loss of work productivity [3, 4, 5]. textual aspects that must be considered in future
Sleep is a vital biological function essential for the deployments.
overall health of mammalian organisms [6] and allows 4. We discuss how factors such as sleep time, wake
for psychological recuperation and memory consolida- up time, sleep disruptions, and pain intensity at
tion [5, 7]. In the same vein, poor sleep poses a potent night impact the felt restfulness of participants.
risk factor for a number of physical and psychological ail- 5. Factors leading to poor sleep among people living
ments including obesity, dementia, diabetes, and chronic with LBP is heterogeneous and not only due to
pain [8, 9, 5, 10]. Poor sleep quality is common among pain.
people suffering from chronic or acute pain such as LBP
The results from our study are also encouraging con-
[5].
cerning the number of completed daily surveys about
We conducted a long term study that offered daily
sleep and LBP for several months, which is promising
observations from the perspectives of people living with
considering our future deployment of the next version
LBP to investigate the effects of LBP on sleep: how does
of the application.
back pain affect one’s sleep quality? In this vein, we also
consider how factors such as time of sleep, wake up time,
and sleep interruptions among others affect the perceived 2. Related Work
sleep quality and/or felt pain intensity of people living
with LBP. 2.1. Low Back Pain
Joint Proceedings of the ACM IUI Workshops 2022, March 2022, Low Back Pain (LBP) adversely affects the quality of life
Helsinki, Finland of people [11] and produces annual global costs exceed-
$ andy.alorwu@oulu.fi (A. Alorwu); aku.visuri@oulu.fi
ing $100 billion [12]. Although there are numerous pain
(A. Visuri); simo.hosio@oulu.fi (S. Hosio)
© 2022 Copyright for this paper by its authors. Use permitted under Creative conditions, back pain carries the greatest societal burden,
Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
Workshop
Proceedings
http://ceur-ws.org
ISSN 1613-0073 CEUR Workshop Proceedings (CEUR-WS.org) affecting nearly every adult at least once in their lifetime
[12]. The Global Burden of Disease (GBD) study esti- 3.1. On-boarding and Daily Use
mated that among 306 conditions, LBP ranked highest as
The setup of the app was designed to be simple for the
the most significant condition with respect to the number
users. It has a welcome screen (Fig. 1a) that on-boards
of years lived with disability [13, 1].
users by asking preliminary questions about user demo-
graphics and past experience with pain. This welcome
2.2. Sleep screen also displays a consent checkbox which the user
Recent studies have reported that sleep difficulties such must agree to in order to proceed. A consent statement
as initiating and maintaining sleep, as well as experienc- is provided beside the checkbox and contains links to
ing inadequate sleep, can affect 20-30% of the western the “user agreement” and “privacy policy” screens. Af-
population on a daily to weekly basis [5, 14]. Sleep loss ter a successful on-boarding, the home screen (Fig. 1b)
has been reported to impair cognition, psychomotor func- that displays daily surveys to be taken by the user is pre-
tion, decision making, and immune function [15]. Poor sented. Clicking on a list item opens up a detailed view
sleep quality has also been considered to be a significant with a list of survey questions (Fig. 1d). After successfully
risk factor for people suffering with diseases such as dia- answering and submitting the answers to a survey, the
betes, dementia, depression, obesity, pain, among others completed survey is removed from the list depending on
[16, 9]. The physical and psychological changes associ- whether it is a daily or monthly survey. Monthly surveys
ated with poor sleep can significantly affect the quality are removed from the list for the given month once an-
of life and overall well-being of people [17]. Inadequate swered. Daily surveys on the other hand are removed for
sleep also negatively impacts productivity and leads to the given day only, and are displayed again the next day.
substantial financial and non-financial costs, ultimately The app also has a settings screen (Fig. 1c) that enables
becoming an important social and economic burden [18]. the user to customize the application. Most importantly is
the notification time for the delivery of daily reminders to
answer a survey. Users receive daily push notifications at
2.3. The Relation Between Sleep and Pain the selected time to remind them to take the daily survey.
The exact mechanisms underpinning the sleep and pain A set of two emojis (one happy face and one sad face) are
relationship are unclear but likely to involve multiple con- displayed one at a time on the home screen indicating a
tributors [19], such as depression [20], and daytime nap- completed survey (happy face) or a missing daily survey
ping [21]. The comorbidities between chronic pain and (sad face).
sleep impairments have been shown in various studies The “Sleep Better with Back Pain” app includes three
[5, 22]. Similarly, studies suggest that the management in-app questionnaires: daily survey, sleep survey, and
of sleep may consequently improve co-morbid diseases quality of life survey. The “daily” survey is taken daily
[23, 24]. The interaction between sleep and pain is com- while the “sleep survey” and “quality of life survey” are
plex and challenging to understand [25]. A study by taken monthly.
Mathias et al. [19] established that adult patients with
chronic pain had worse measures for sleep onset latency 3.1.1. Daily Survey
and efficiency, recurrent awakenings, and time awake
The daily survey comprised of the following items:
after sleep onset and exhibited worse scores on sleep mea-
sures such as total sleep time and light sleep duration, • Sleep time and wake up time, 5-point Likert-style
among others. item: 1 (Earlier than normal) - 5 (Later than nor-
mal)
• Time to fall asleep, 5-point item: 1 (Less time than
3. The “Sleep Better with Back normal) - 5 (More time than normal)
Pain” app • Number of times waking up at night, 5-point item:
1 (Less than normal) - 5 (More than normal)
We designed a cross-platform mobile application to col-
• How rested you feel after waking up, 5-point item:
lect periodical questionnaire data. The application was
1 (Less rest than normal) - 5 (More rest than nor-
built with Flutter1 and runs on both Android and iOS mo-
mal)
bile operating systems. Flutter is a cross-platform mobile
• Severity of LBP pain, 1-point item: 0 (No pain) -
application development framework that makes it easy
10 (Worst imaginable pain)
to build apps for the Android and iOS mobile operating
systems using the same code base. • How pain affected sleep and/or how sleep affected
pain: Free-form text
1
https://flutter.com
(a) On-boarding (b) Home screen (c) Settings screen
(d) Daily survey (e) Sleep survey (f) Quality of life
Figure 1: Different user interfaces of the developed app.
3.1.2. Monthly Questionnaires sleep duration, sleep efficiency, sleep disturbances, sleep
medication, and daytime dysfunction.
The monthly sleep questionnaire is a standardized Pitts-
The quality of life survey is a Patient-Reported Out-
burgh Sleep Quality Index (PSQI) questionnaire devel-
comes Measurement Information System (PROMIS-10)
oped by Buysee et al. [26] as a self-report on subjective
standardized questionnaire comprising of 10 global items
sleep quality over a period of four weeks. It consists of
that each represent a domain of health [27]. Global phys-
19 items from which seven component scores that re-
ical and mental health component scores are computed
veal the severity of various sleep problems are formed.
from the global items. Results from PROMIS-10 can be
These components include: sleep quality, sleep latency,
used to assess patients’ perceptions of their health. The 4.1. Participant Overview
physical health component scale comprises of four items
A total of 35 people participated in our field study. Par-
on: physical health, physical functioning, pain intensity,
ticipants were mainly recruited from our local campus
and fatigue. The mental health component scale includes
through our campus-wide email lists. However, we got
items on: quality of life, mental health, satisfaction with
additional participants via Google’s Play Store as the app
social activities and relationships, and emotional prob-
was published publicly there. Participant ages ranged
lems. Two of the global items (general health and social
between 20-68 (M = 38.03, SD = 12.94) with 20 females
roles) are not used in the calculation of the physical and
and 15 males. Participants had diverse academic quali-
mental component scores.
fications and employment statuses. 20 hold a Master’s
degree or higher, 8 hold a Bachelor’s degree, 2 hold a
3.1.3. Reminder Notifications Vocational degree, and 3 hold a High School diploma
Notifications are delivered from our custom-built back- while 3 did not disclose their educational information.
end application through OneSignal 2 APIs. Data from the Concerning employment, 21 participants identified as
answered surveys are saved in an online Google Sheets having a full-time job, 7 have a part-time job while 3 are
document. User data is saved in a database hosted on our unemployed, 2 are retired, and 2 did not disclose their
own servers. The “Sleep Better with Back Pain” mobile employment status. None of the participants have had
app is hosted on Google Play. their back surgically operated by a doctor and the num-
ber of years lived with LBP ranged from 0-38 (M = 9, SD
= 9.48). 20 participants have been clinically diagnosed
3.2. Pilot Experiment with LBP, 8 have chronic sciatica, 5 non-chronic sciatica,
Before embarking on the longitudinal deployment, we and 20 have no sciatica.
validated the feasibility of the app by conducting usabil- We also inquired about how active participants’
ity tests with four users within our research premises. lifestyle was using a single 0-10 item (0 - not at all ac-
During this session, we discovered some usability issues: tive to 10 - extremely active). The mean value was 5.51
1) mandatory questions were not marked with an asterisk (SD = 1.93). For inquiries about treatments and self-
(*), 2) after completing a survey, the user is automatically management techniques used in managing their pain,
directed to the main screen without any message to indi- participants shared a variety of actions they take. Some
cate the survey was complete, and 3) the choice of font of these include: “exercises”, “yoga”, “massages”, “stretch-
type and color made visualization difficult. We also no- ing”, and “taking medication”. A more nuanced analysis
ticed technical issues such as 1) users finding it difficult of these is outside the scope of this article.
to select 0 on the 0-10 slider scale, and 2) the keyboard
not disappearing after users have finished typing an an-
swer. These insights were useful in improving the app 5. Results
design and functionality before embarking on the longer
In the following sections, we present our quantitative
deployment.
and qualitative findings, focusing primarily on the effect
of low back pain on the quality of sleep experienced by
4. DATA COLLECTION people living with LBP.
After making modifications to the app based on feedback 5.1. Quantitative Analysis
from the usability testing session, we launched the app
on the Google Play Store and published the study to 5.1.1. Relationship between sleep quality and pain
our campus wide email lists. We did not specify any intensity
reward for participating in the study as we wanted to We analysed the daily surveys (N = 1030) and computed
reach people who really wanted to use the app or were Spearman’s rank correlation to assess the relationship
not motivated by any form of reward but were interested between the collected variables and “well-restedness”. We
in understanding their sleep and LBP. We also reached noticed a negligible negative correlation between pain
out and recommended the study to previous participants intensity and well-restedness (r(1028) = -.12, p < .005)
of studies conducted by co-authors. The study run for a and a negligible correlation between wake up time and
period of seven (7) months, from May to November 2021. well-restedness ( r(1028) = .08, p = .01). Thus, the felt
pain was not strongly associated with how well-rested
participants felt the next morning. We also discovered a
weak negative correlation between sleep time and well-
2
restedness (r(1028) = -.22, p < .005). However, there was a
https://onesignal.com
Table 1
Summary of the multivariate correlation matrix of PSQI component domains using Spearman’s method alongside their
significance values in brackets.
Sleep quality Sleep latency Sleep duration Sleep efficiency Sleep disturbance Use of sleep medication
Sleep latency -0.32 (*)
Sleep duration 0.36 (*) -0.22 (0.18)
Sleep efficiency 0.23 (0.16) 0.11 (0.49) 0.61 (***)
Sleep disturbance -0.17 (0.30) 0.44 (**) -0.08 (0.62) -0.15 (0.35)
Use of sleep medication 0.48 (**) -0.17 (0.29) 0.42 (*) 0.36 (*) 0.01 (0.93)
Daytime dysfunction -0.06 (0.71) 0.21 (0.19) -0.10 (0.53) 0.06 (0.72) 0.34 (*) -0.20 (0.21)
Signif. codes: 0 ‘***’ 0.005 ‘**’ 0.05 ‘*’
strong negative correlation between sleep disruption and 5.2. Qualitative Analysis
well-restedness (r(1028) = -.41, p = < .005). Thus, and as
We analyzed 1030 responses to the open-ended daily
can be expected, sleep disruptions are associated with
questionnaire item (i.e. users’ own elaboration on how
how well-rested people feel in the morning. While these
pain affected sleep or how sleep affected pain) following
findings are not surprising, they are indicative of the
a deductive thematic analysis process [28]. In using this
app’s feasibility in overall data collection.
analytical method, the first author first coded the most
informative responses, generating the coding scheme
5.1.2. PSQI which was then shared with the other co-authors. The
The global PSQI score from the responses (N = 36) of our authors held online meetings to discuss and resolve dis-
study, which is the sum of all seven component scores agreements with the coding. They further identified as-
has a range of 0-21 points with actual scores ranging pects of the responses that would be most interesting to
from 4-16, an overall group mean of 8.4 (SD = 2.83, 𝛼 = present and discuss. In subsequent sections, we present
.68). For the individual components, each with a possible a subset of the findings from the analysis that we believe
range of 0-3, the ranges were 0-3 except sleep disturbance best fits the scope of this article.
which had a range of 0-2. For each component, as well
as the global PSQI score, higher scores are an indication 5.2.1. Pain before, during, and after sleep
of worse sleep quality.
Participants expressed various degrees of pain felt prior
In Table 1, we examine the correlation of the PSQI
to going to sleep, during sleep hours, and when they
components in our cohort using Spearman rank correla-
woke up in the morning. While there were reported
tion. We found strong correlations between sleep quality
feelings of pain prior to going to bed on some days, pain
and use of sleep medication (r = .48, p < 0.005), sleep effi-
before bed did not always result to a painful sleep. One
ciency and sleep duration (r = .61, p < 0.005), a moderate
participant notes it was “...difficult to fall asleep due to the
correlation between sleep quality and sleep duration (r =
pain but once I did, it didn’t bother my sleep” (Female, 42).
.36, p < 0.05), sleep disturbance and daytime dysfunction
In a similar vein, another participant exclaimed, “...it was
(r = .34, p < 0.05). Sleep quality had little to no effect on
worst when going to bed, it did not bother me during the
daytime dysfunction (r = -.06, p = 0.71) however.
night”(Male, 30).
On the contrary, some participants were quick to high-
5.1.3. PROMIS-10 light the effect their LBP had on their sleep such as forcing
We show the multivariate correlation matrix of the them to stay awake at night for hours. One participant
PROMIS-10 domains of the results (N = 36) of our study notes, “I stayed up two hours at night because of pain in
in Table 2. The mean physical health score of participants my hip” (Male, 49) and “I couldn’t rest well due to pain at
was 13.67 (SD = 3.01) and the physical health T-score of my back” (Male, 30). There were days however where
participants was lower (mean = 44.63, SD = 8.43) relative participants simply reported their LBP not having an ef-
to the standardized mean T-score of 50. Similarly, the fect on their sleep despite the presence of the pain. One
mean mental health score was 11.92 (SD = 3.23) and the participant stating that the “...pain did not disturb my
mental health T-score of participants was lower (mean sleep” (Female, 48).
= 43.33, SD = 8.24) relative to the standard score. Thus It is also worth highlighting that good quality sleep
our participants have significantly lower physical and positively affected participants’ perception of pain in the
mental function compared to the general population. morning, “...sleeping helped pain” (Female, 48). This was
Table 2
Summary of the multivariate correlation matrix of PROMIS-10 domains using Spearman’s method alongside their significance
values in brackets.
Quality of life Physical health Mental health Social activities Physical functioning Emotional problems Fatigue
Physical health 0.74 (***)
Mental health 0.60 (***) 0.33 (*)
Social activities 0.52 (**) 0.45 (*) 0.57 (***)
Physical functioning 0.17 (0.32) 0.31 (0.07) -0.13 (0.45) 0.08 (0.66)
Emotional problems 0.35 (*) 0.21 (0.22) 0.65 (***) 0.45 (*) -0.22 (0.20)
Fatigue 0.55 (***) 0.64 (***) 0.29 (0.08) 0.40 (*) 0.42 (*) 0.25 (0.15)
Pain intensity 0.47 (**) 0.63 (***) 0.12 (0.49) 0.19 (0.26) 0.35 (*) 0.14 (0.42) 0.32 (*)
Signif. codes: 0 ‘***’ 0.005 ‘**’ 0.05 ‘*’
further supported by another who acknowledges to be 5.2.3. Exercises and active lifestyle
“...in a bit less pain this morning because I slept a bit better
Some participants highlight being engaged in an active
than usual” (Female, 67) indicating a potentially positive
lifestyle and sports. To this, we noticed a report of an
effect sleep can have on one’s LBP.
increase in pain or sleeplessness due to pain after an
While we see several instances of sleep affecting pain
intense or strenuous workout, “In the morning I felt some
positively and pain having a negative effect on partici-
lower back pain and stiffness. It could be result from gym
pants’ sleep, we also report that there were days where
exercise” (Male, 38). Interestingly, suffering from LBP
participants were confident that neither sleep nor pain
did not stop participants from indulging in an active
had an effect on the other. One participant sums it all
lifestyle (e.g. cycling, swimming, gardening, etc) or even
up, “I didn’t feel the effect from both sides” (Female, 56).
participating in sports competitions although sometimes
Participants could simply not tell if and how their sleep
they have had to resort to medication to ease the pain
affected their pain or how their pain influenced the qual-
afterwards as one participant notes, “Yesterday I took part
ity of their sleep. As such, experiencing pain did not
in an athletics competition (discus, javelin and hammer
stop them from having a good night’s sleep, neither did
throw) and needed painkillers straight after” (Female, 67).
having good quality sleep improve their perception of
pain.
6. Discussion
5.2.2. Weather, mattress, and sleep position
In this short report, we wish to introduce a simple mobile
It was clear from the responses that other factors beside application along with some preliminary evidence speak-
LBP affected participants’ sleep. We noted that finding ing in favour of people being able to use it for providing
a “...good position to sleep” (Male, 40), a good support data about sleep, LBP and their relationship.
from the bed or mattress, and the need to “...turn during The exploratory nature of our study is aimed at shed-
sleep” (Male, 38) were some of the concerns of a lot of ding more light on the LBP and sleep relationship co-
participants. Participants also noted that the weather nundrum. Sleep Better with Back Pain helps capture
affected their sleep. This was particularly noticeable important self-reports on sleep and LBP that provides re-
during the summer months where participants expressed searchers with data and insights on this important health
a lack of or poor sleep due to hot weather. To some, issue. The long term plan is to build a community pow-
the weather rather than their LBP affected their sleep, ered application for improving the lifestyles of people
“...my sleep last night was affected by the humid weather living with LBP through timely reminders, recommenda-
but not by the back pain” (Female, 56). Another drew tions, and coaching to motivate people to make healthier
a connection between the weather and their felt pain, life choices that could improve both their low back pain
outlining how the heat could possibly be exacerbating and sleep quality.
the intensity of the felt pain, “...it’s mainly the heat that
is making other things harder to deal with” (Female, 67).
Thus, to effectively manage one’s pain, environmental 6.1. Heterogeneity of Poor Sleep Factors
factors must also be considered. Overall, our results indicate the existence of a negligi-
ble relationship between felt pain and how well-rested
participants felt in the morning. Indeed, this result is
interesting as it could be an indication that people liv-
ing with LBP have become so accustomed to their pain
such that it does not matter anymore. It is also an in- source treatments for LBP and people suffering from LBP
dication that the precise mechanisms that underpin the can suggest and view common LBP treatments used by
sleep and pain relationship remain unclear but are likely community members. We envision the app to become an
to involve multiple contributors such as depression [20], enabler of various studies with real users.
physical discomfort, neurotropic factors [29], as well as
psychological factors [19] among others. Despite the
pain felt prior to or during sleep, participants on average 7. Conclusion
sleep well. On the contrary, we notice the emergence
Our results show that the well-restedness of people liv-
of factors such as “sleep distruption”, “weather”, “active
ing with LBP is influenced not only by pain at night but
lifestyle”, “medication”, and “sleep position” all having an
other factors such as sleep time, wake up time, and sleep
effect on how well-rested people felt in the morning. One
disruptions. We also indicate that people are willing to
such factor worth expounding on is “sleep distruption”.
donate their data toward sleep and LBP related research
Sleep disruption affected significantly how well-rested
purposes. This study introduces a preliminary investi-
participants felt in the morning despite the intensity of
gation into sleep tracking and low back pain using the
their pain during the previous night. Thus, while partic-
“Sleep Better with Back Pain” app and communicates our
ipants’ perceived sleep quality was not affected by the
initial results to the academic community in hopes to
intensity of their pain at night, it was affected by the
spark interest and discussion within the community.
disruption of their sleep, disruptions which they identify
to be caused non-exhaustively by e.g. sleep movements,
bed or mattress, and environmental factors such as the Acknowledgments
weather.
However, the connection of some of these factors to This research is connected to the GenZ strategic profil-
pain is evident, e.g. sleep movements or uncomfortable ing project at the University of Oulu, supported by the
sleep positions lead to sleep disruptions because partici- Academy of Finland (project number 318930), and CRIT-
pants’ express feeling pain while moving in bed or laying ICAL (Academy of Finland Strategic Research, 335729).
in a particular position. Although participants often refer Part of the work was also carried out with the support of
to a factor such as sleep disruption as a major cause of Biocenter Oulu, spearhead project ICON.
their poor quality sleep, one possible underlying reason
for this disruption is their pain. The existence of and
possibly, interconnection of these heterogeneous factors References
in assessing the sleep and pain relationship calls for a
[1] M. Chaudhary, Y. Selvamani, Association between
more holistic approach to investigating this issue.
back pain and subjective health, wellbeing and sleep
problems among older adults in six middle-income
6.2. Limitations countries: a cross-sectional study, Journal of Public
We acknowledge limitations in our initial exploration. We Health (2021) 1–10.
did not provide any form of reports, analytics, etc. nor [2] P. K. Morelhão, R. Z. Pinto, S. Tufik, M. L. Andersen,
incentives for participation to participants of the study, a Sleep disturbance and low back pain in older adults:
possible reason for the low number of participants. Our A bidirectional relationship?, Pain Medicine 21
focus in this study is to ascertain the feasibility of the (2020) 1303–1304.
core features of the app, and our results confirm that. [3] A. L. Dutmer, H. R. S. Preuper, R. Soer, S. Brouwer,
While this affects the generalizability of our results, we U. Bültmann, P. U. Dijkstra, M. H. Coppes, P. Stege-
argue that people have clear interest in LBP and sleep man, E. Buskens, A. D. van Asselt, et al., Personal
and are willing to contribute their data towards research and societal impact of low back pain: the groningen
in this sphere even when all they do is donate their data spine cohort, Spine 44 (2019) E1443–E1451.
without getting any insights in return. [4] L. C. Lambeek, M. W. van Tulder, I. C. Swinkels, L. L.
Koppes, J. R. Anema, W. van Mechelen, The trend
in total cost of back pain in the netherlands in the
6.3. Towards a Future with LBP period 2002 to 2007, Spine 36 (2011) 1050–1058.
Work is currently underway with the “Sleep Better with [5] A. H. Babiloni, B. P. De Koninck, G. Beetz,
Back Pain” app, with new features and user-interface (UI) L. De Beaumont, M. O. Martel, G. J. Lavigne, Sleep
redesign. One such feature is the integration of daily, and pain: recent insights, mechanisms, and future
weekly, and monthly analytics for all survey items (daily, directions in the investigation of this relationship,
sleep, and quality of life surveys). We also foresee other Journal of neural transmission 127 (2020) 647–660.
features like an in-app community where we could crowd-
[6] J. Vinstrup, M. D. Jakobsen, L. L. Andersen, Poor and sleep disorders in adults living with chronic
sleep is a risk factor for low-back pain among pain: a meta-analysis, Sleep medicine 52 (2018)
healthcare workers: Prospective cohort study, In- 198–210.
ternational Journal of Environmental Research and [20] K. Harman, R. Pivik, J. L. D’Eon, K. G. Wilson,
Public Health 17 (2020) 996. J. Swenson, L. Matsunaga, Sleep in depressed and
[7] J. M. Siegel, Clues to the functions of mammalian nondepressed participants with chronic low back
sleep, Nature 437 (2005) 1264–1271. pain: electroencephalographic and behaviour find-
[8] J. McBeth, R. Wilkie, J. Bedson, C. Chew-Graham, ings, Sleep 25 (2002) 47–55.
R. J. Lacey, Sleep disturbance and chronic [21] M. T. Smith, J. A. Haythornthwaite, How do sleep
widespread pain, Current rheumatology reports disturbance and chronic pain inter-relate? insights
17 (2015) 1. from the longitudinal and cognitive-behavioral clin-
[9] L. Shi, S.-J. Chen, M.-Y. Ma, Y.-P. Bao, Y. Han, Y.-M. ical trials literature, Sleep medicine reviews 8 (2004)
Wang, J. Shi, M. V. Vitiello, L. Lu, Sleep disturbances 119–132.
increase the risk of dementia: a systematic review [22] T. A. Roehrs, Does effective management of sleep
and meta-analysis, Sleep medicine reviews 40 (2018) disorders improve pain symptoms?, Drugs 69 (2009)
4–16. 5–11.
[10] P. H. Finan, B. R. Goodin, M. T. Smith, The asso- [23] R. M. Benca, S. Ancoli-Israel, H. Moldofsky, Special
ciation of sleep and pain: an update and a path considerations in insomnia diagnosis and manage-
forward, The Journal of Pain 14 (2013) 1539–1552. ment: depressed, elderly, and chronic pain popu-
[11] M. L. Andersen, P. Araujo, C. Frange, S. Tufik, Sleep lations., Journal of Clinical psychiatry 65 (2004)
disturbance and pain: a tale of two common prob- 26–35.
lems, Chest 154 (2018) 1249–1259. [24] T. Roth, Challenges in the comorbid condition,
[12] R. Przkora, M. S. Wallace, L. Doan, A. D. Wasan, Sleep medicine 8 (2007) S1–S2.
M. A. Ashburn, J. Mao, A major step to improve [25] T. Roehrs, T. Roth, Sleep and pain: interaction
pain research infrastructure: The nih early phase of two vital functions, in: Seminars in neurology,
pain investigation clinical network (eppic-net), ASA volume 25, Copyright© 2005 by Thieme Medical
Monitor 84 (2020) 38–39. Publishers, Inc., 333 Seventh Avenue, New . . . , 2005,
[13] T. Vos, C. Allen, M. Arora, R. M. Barber, Z. A. Bhutta, pp. 106–116.
A. Brown, A. Carter, D. C. Casey, F. J. Charlson, [26] D. J. Buysse, C. F. Reynolds III, T. H. Monk, S. R.
A. Z. Chen, et al., Global, regional, and national in- Berman, D. J. Kupfer, The pittsburgh sleep quality
cidence, prevalence, and years lived with disability index: a new instrument for psychiatric practice
for 310 diseases and injuries, 1990–2015: a system- and research, Psychiatry research 28 (1989) 193–
atic analysis for the global burden of disease study 213.
2015, The lancet 388 (2016) 1545–1602. [27] R. D. Hays, J. B. Bjorner, D. A. Revicki, K. L.
[14] D. R. Hillman, L. C. Lack, Public health implica- Spritzer, D. Cella, Development of physical and
tions of sleep loss: the community burden, Medical mental health summary scores from the patient-
Journal of Australia 199 (2013) S7–S10. reported outcomes measurement information sys-
[15] W. D. Killgore, T. J. Balkin, N. J. Wesensten, Im- tem (promis) global items, Quality of Life Research
paired decision making following 49h of sleep de- 18 (2009) 873–880.
privation, Journal of sleep research 15 (2006) 7–13. [28] V. Braun, V. Clarke, Using thematic analysis in
[16] J. Yin, X. Jin, Z. Shan, S. Li, H. Huang, P. Li, X. Peng, psychology, Qualitative research in psychology 3
Z. Peng, K. Yu, W. Bao, et al., Relationship of sleep (2006) 77–101.
duration with all-cause mortality and cardiovascu- [29] P. A. Boakye, C. Olechowski, S. Rashiq, M. J. Verrier,
lar events: a systematic review and dose-response B. Kerr, M. Witmans, G. Baker, A. Joyce, B. D. Dick,
meta-analysis of prospective cohort studies, Journal A critical review of neurobiological factors involved
of the American Heart Association 6 (2017) e005947. in the interactions between chronic pain, depres-
[17] E. F. Afolalu, F. Ramlee, N. K. Tang, Effects of sleep sion, and sleep disruption, The Clinical Journal of
changes on pain-related health outcomes in the Pain 32 (2016) 327–336.
general population: a systematic review of longitu-
dinal studies with exploratory meta-analysis, Sleep
medicine reviews 39 (2018) 82–97.
[18] D. Hillman, S. Mitchell, J. Streatfeild, C. Burns,
D. Bruck, L. Pezzullo, The economic cost of in-
adequate sleep, Sleep 41 (2018) zsy083.
[19] J. Mathias, M. Cant, A. Burke, Sleep disturbances