Feasibility and acceptability of wrist actigraph in assessing sleep quality and sleep quantity: A home-based pilot study in healthy volunteers

Zaswiza Mohamad Noor, Alesha J. Smith, Simon S. Smith, Lisa M. Nissen

Institute for Health and Biomedical Innovation and Centre of Accident Research and Road Safety, Queensland University of Tech-nology, Brisbane, Australia.
School of Pharmacy, Pharmacy Australia Centre of Excellence, University of Queensland, Brisbane, Australia;.

DOI: 10.4236/health.2013.58A2010                

Abstract

Purpose: This study aimed to determine the feasibility and acceptability of actigraphy to monitor sleep quality and quantity in healthy self-rated good sleeper adults at home-based settings. Method: Sixteen healthy volunteers (age > 18) were invited to participate. Each participant was provided with a wrist actigraph device to be worn for 24-hour/day for seven consecutive days to monitor their sleep-wake patterns. Actigraphy data were downloaded using-proprietary software to generate an individual-sleep report. Participants also completed a set of self-reported Health Related Quality of Life (HRQOL) using WHO (five) Well Being Index (WBI) questionnaires. Results: Actigraphy was well accepted by all participants. Only 43.8% of the participants achieved normal total sleep time (TST) and 62.5% had a mean sleep efficiency value below the normal range. Despite a reduced quality of sleep among the participants, the self-reported HRQOL scores produced by the WHO-5 WBI showed a “fair” to “good” among the participants. Conclusions: To maintain healthy well-being, it is vital to have efficient and quality sleep. Insufficient and poor sleep may contribute to various health problems and hazardous outcomes. People often believe they have normal and efficient sleep, not realising they may be developing poor sleep habits. This study found that actigraphy can be easily utilized to monitor sleep-wake patterns at home-based settings. We proposed that actigraphy could be adapted for use in the primary care settings (e.g. community pharmacy) to improve the sleep health management in the community.

Keywords

Actigraphy; Sleep Quality; Sleep Quantity; Home-Based; Good Sleepers

1. INTRODUCTION

Sleep is essential for an individual’s health and wellbeing, thus having a quality sleep is as important as having a good diet and getting regular exercise [1]. Epidemiological data indicate that poor and insufficient sleep may be linked to some chronic diseases such as hypertension, diabetes, depression and obesity. Poor sleep contributes to hazardous outcomes, for instance industrial disasters, medical and occupational errors, difficulty performing daily tasks due to daytime sleepiness, as well as unintentionally falling asleep while driving leading to motor vehicle crashes [2,3]. Irritability, moodiness, impaired memory, and inability to multitask are some of the signs associated with lack of sleep.

In fact, a variety of adverse health behaviours and impairment in health-related quality of life (HRQOL) domains such as general health, frequent physical and mental distress, depression symptoms and anxiety are significantly more likely to be reported as fair/poor in those with poor sleep [4]. It is also important to bear in mind that sleeping too much can possibly indicate the presence of health concerns as well. Thus, the right balance of sleep and wake time including proper sleep hygiene are essential to a healthy lifestyle. Generally, healthy adults need 16 hours of wakefulness and an average of eight hours of sleep at night [5,6]. However, sleep duration and sleep-wake patterns are vastly variable between individuals, cultures and lifestyles [7]. For example, alcohol and caffeine can produce a stimulating effect that increases sleep latency, hence chronic use of alcohol and drinking regular caffeinated drinks such as coffee and soft drinks before going to sleep may cause an individual to have longer sleep onset latency [8,9].

Many people believe that they have a normal sleep quality, thus may not be concerned about their sleep even though they may display poor sleep quality. A Swiss study which screened pharmacy customers to detect the likelihood of any sleep problem or daytime sleepiness based on the answers from online questionnaires found that 32% customers were suspected of having a disorder in at least one category of sleep disorders and 20.7% were suspected of having excessive daytime sleepiness [10]. Kashyap et al. (2012) screened 241 community pharmacy customers in a survey over a 4-week period and found that among the participants, 50.2% were regular snorers and 30.7%, 10.7% and 7.9% were at risk of insomnia, daytime sleepiness and obstructive sleep apnoea respectively [11]. Even though sleep disorders are highly prevalent in the community, they still remain under-diagnosed and inadequately treated [10]. Assessing and monitoring sleep [10,11] is the first step in preventing and treating the condition therefore appropriate validated measuring tools are essential. Assessment is also required to assess the quality and quantity of sleep following any treatment, particularly at home.

Polysomnography (PSG) is accepted as the gold standard assessment methodology for sleep in research and hospital settings [12,13]. However, in non-laboratory and community settings, such as home, where sleep assessment entails monitoring over many consecutive nights, PSG is impractical as it requires professional handling and expensive equipment [14-16]. At present, many different objective methods to assess sleep in home-based settings, such as sensitive bed sensors, non-contact biomotion sensors and wrist-worn Peripheral Arterial Tonometry (PAT), have been developed and used [17,18]. However, the literature suggests that methods which are less invasive, less expensive and more convenient in providing a 24-hour/day record of sleep should be considered as more appropriate for the home environment [18]. Still, there are limited studies on the acceptability of 24-hour home-based monitoring.

Actigraphy is a reliable alternative to PSG for measurement of habitual sleep-wake behaviour [19,20]. It can provide an accurate estimation of sleep-wake patterns in normal and healthy adult populations, and also in patients suspected of certain sleep disorders [21,22] which are related to disturbances of the circadian rhythm [23]. Actigraphy can conveniently record sleep-wake activities 24-hour/day over a period of one week or longer, and can generate automated sleep-wake scores based on validated scoring algorithms [24]. An actigraph is usually worn on the non-dominant wrist. An accelerometer in the actigraph has the ability to detect movement; therefore, it can be used as a proxy measure of activity levels [21,25]. Hence, certain sleep parameters such as percentage of sleep efficiency (SE%), total sleep time (TST), number of nocturnal awakenings (NWAK), wake after sleep onset (WASO), and sleep onset latency (SOL) [26,27] can be calculated from the actigraphy data to generate indices of sleep quality, sleep quantity and sleep-wake timing.

This paper describes a study intended to identify the feasibility and acceptability of utilizing actigraphy to assess sleep-wake patterns in healthy adults in a homebased setting. The outcomes of this study will support the development of an intervention for community pharmacies which utilizes actigraphy and the knowledge of pharmacists to improve sleep health management in primary care settings.

2. METHODS

2.1. Study Participants

Participants were a convenient sample of 16 healthy volunteers (five females and 11 males; mean age 28.25 ± 6.68 years) who were selected among university students and individuals working standard hours (Table 1). Recruitment was conducted from April to May, 2012. Exclusion criteria were diagnosed sleep disorders and/or associated symptoms, serious or acute illness and the use of sleep and psychotropic medicines. This study received ethical approval from the University of Queensland, School of Pharmacy Human Research Ethics Committee (ref: number 2012/04). Each participant involved in the study provided informed consent. Participation in this study was entirely voluntary and no monetary incentive was provided.

2.2. Instrumentation

2.2.1. Actigraph

We used the SBV2 Readiband™ (Fatigue Science, Honolulu, USA) wrist-worn actigraph to record participant’s sleep-wake patterns over seven days [28]. The hardware consisted of an accelerometer with the sensitivity to continuously track wrist movement and stores these data for later analysis. Devices were initialized to collect data in 1-minute epochs. The collected data was then wirelessly downloaded to a study computer for analysis using a Nordic 2.4 GHz ANT transceiver. Data

Table 1. Baseline demographic characteristics of the participants.

were analysed using software [28] and individualised reports were generated for each participant.

2.2.2. Questionnaires

A self-report questionnaire was used to collect baseline demographic information. At the end of the study, participants were asked to complete the validated World Health Organization (five) (WHO-5) Well-being Index 1998 version [29] to assess Health-Related Quality of Life (HRQOL) and a questionnaire consisting of questions on the utilization of actigraphy (e.g. appropriateness of the duration, difficulties and acceptability), plus questions on lifestyle modification from a validated survey [30]; smoking status (yes or no), number of cigarettes smoked (if any) and, alcoholic and caffeinated drinks consumption per day.

2.3. Study Protocol

At baseline, individuals who identified themselves as healthy self-rated “good sleepers” were invited to participate in the study, giving informed consent and completing the demographic questionnaire. Each participant was provided with an actigraph to be worn for 24-hour/day for seven consecutive days to record the sleep-wake patterns.

2.4. Sleep Statistics and Data Analysis

Figures 1 and 2 (from a participant’s sleep report and reproduced with permission from Fatigue Science [28]) show examples of an actigraphy plot and sleep parameters data from an individual sleep report, which also can be used for consultation purposes. Figure 1 shows the actigraphy 24-hour sleep-wake plot for seven consecutive days in a sleep report. In this model, these data were converted into information about sleep through the use of scientifically-validated algorithms [31,32]. The vertical black lines represent motion or activity. In this plot, the more activities (showed as black lines in Figure 1) recorded during sleep, the lower the quantity and quality of sleep [33].

Sleep statistics, i.e. data on sleep parameters such as mean (average) values for total sleep time (TST) per 24- hour period, number of nocturnal awakenings (NWAK), the percentage of sleep efficiency (SE%), and the median of sleep onset latency (SOL) were summarized in the sleep report to indicate whether or not sleep is within the normal ranges (as in Figure 2) during the study period. The normal ranges for each sleep parameter in the report are determined by the software.

For analysis, data from the sleep report and information from the questionnaire were entered into an SPSS 20.0 [34] data file. Details of the measured sleep parameters (e.g. time spent in bed (minutes), time spent for sleep (minutes) and sleep efficiency (%)) for each day were also automatically downloaded as a Microsoft Office value file and data were entered into SPSS data file for further analysis.

3. RESULTS

All participants agreed that the use of the actigraph was feasible and acceptable by answering “No” to questions “Issue with actigraph: not comfortable?” and “Issue with actigraph: felt awkward?” No disturbance to daily tasks or movement was reported and no one requested to remove the actigraph before the seven-day duration ended. Whilst no specific question was asked regarding the willingness to wear the actigraph for an extended period, all participants agreed that the duration of seven days was acceptable and reasonable. The details of the findings for each participant are summarized in Table 2.

With regards to the mean total sleep time (TST), only seven out of 16 participants (43.8%) achieved a TST

Figure 1. Example of a plot of actigraphy data from an individual sleep report (33). This seven-day recording is a 24-hour sleepwake pattern from a participant and shows a pattern of normal sleep-wake for a healthy adult with no reported sleep disturbance. Sleep onset time, wake after sleep onset (WASO), and duration of sleep (total sleep time per day) can be obtained from this plot.

value within the normal range. By definition, sleep efficiency is the ratio of time actually spent asleep (i.e. TST) to the amount of time spent in bed (time in bed; TIB) including resting [35]. However in this study we could obtain the SE% values directly from the software. Although the software considers SE% values within 80% - 95% to be normal, the literature suggested that SE% values greater than 85% are considered normal [36,37]. In this study, our preference was to adapt normal SE% values based on the literature. Hence, using this definition, 10 participants (62.5%) were found to have mean SE% below the normal range.

Alcohol was consumed only by two participants, however caffeinated drinks, mostly tea and coffee, were consumed by 75% (n = 13) of the participants. Of that, 50% (n = 8) consumed 2 - 3 cups per day of caffeinated drinks.

Table 3 show details of night-by-night TST, SE%,

Conflicts of Interest

The authors declare no conflicts of interest.

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