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Effects of Music Videos on Sleep Quality in Middle-Aged and Older Adults With Chronic Insomnia: A Randomized Controlled Trial Hui-Ling Lai, En-Ting Chang, Yin-Ming Li, Chiung-Yu Huang, Li-Hua Lee and Hsiu-Mei Wang Biol Res Nurs published online 17 September 2014 DOI: 10.1177/1099800414549237 The online version of this article can be found at: http://brn.sagepub.com/content/early/2014/09/17/1099800414549237

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Effects of Music Videos on Sleep Quality in Middle-Aged and Older Adults With Chronic Insomnia: A Randomized Controlled Trial

Biological Research for Nursing 1-8 ª The Author(s) 2014 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/1099800414549237 brn.sagepub.com

Hui-Ling Lai, PhD, RN1,2, En-Ting Chang, MD3, Yin-Ming Li, MS, MD1,4, Chiung-Yu Huang, RN, PhD5, Li-Hua Lee, MSN, RN1, and Hsiu-Mei Wang, BSN, RN3

Abstract Listening to soothing music has been used as a complementary therapy to improve sleep quality. However, there is no empirical evidence for the effects of music videos (MVs) on sleep quality in adults with insomnia as assessed by polysomnography (PSG). In this randomized crossover controlled trial, we compared the effects of a peaceful Buddhist MV intervention to a usual-care control condition before bedtime on subjective and objective sleep quality in middle-aged and older adults with chronic insomnia. The study was conducted in a hospital’s sleep laboratory. We randomly assigned 38 subjects, aged 50–75 years, to an MV/usual-care sequence or a usual-care/MV sequence. After pretest data collection, testing was held on two consecutive nights, with subjects participating in one condition each night according to their assigned sequence. Each intervention lasted 30 min. Sleep was assessed using PSG and self-report questionnaires. After controlling for baseline data, sleep-onset latency was significantly shorter by approximately 2 min in the MV condition than in the usual-care condition (p ¼ .002). The MV intervention had no significant effects relative to the usual care on any other sleep parameters assessed by PSG or self-reported sleep quality. These results suggest that an MV intervention may be effective in promoting sleep. However, the effectiveness of a Buddhist MV on sleep needs further study to develop a culturally specific insomnia intervention. Our findings also suggest that an MV intervention can serve as another option for health care providers to improve sleep onset in people with insomnia. Keywords music video, insomnia, polysomnography, Pittsburgh Sleep Quality Index

Insomnia is broadly defined as subjectively reported difficulty with initiating and/or maintaining sleep, early morning waking, or nonrestorative sleep (Schutte-Rodin, Broch, Buysse, Dorsey, & Sateia, 2008). Estimations of the prevalence of insomnia vary widely due to differences in case definitions (Mai & Buysse, 2009). In one review of sleep studies, Roth (2007) estimated the prevalence of insomnia in a variety of adult samples to be 30%. Insomnia has profound adverse effects on both individuals and society and is a significant growing public health concern (Bartlett, Marshall, Williams, & Grunstein, 2008; Nomura, Yamaok, Nakao, & Yano, 2010). It increases health care costs (Mai & Buysse, 2009), but the full financial burden insomnia places on society is difficult to estimate (Wade, 2011). People with insomnia use diverse sleep aids, such as overthe-counter products, ear plugs, and eye masks, or prescription medications in an attempt to improve their sleep quality (Bertisch, Herzig, Winkelman, & Buettner, 2014). Pharmacological management of sleep problems is frequently accompanied by unwanted side effects (DeMartinis, Kamath, & Winokur, 2009). Further, the efficacy and safety of sleep medications have not been sufficiently established (Buscemi et al., 2007).

Therefore, nonpharmacological management of sleep problems has become a crucial issue for nursing professionals (Su et al., 2013). In a review of mind–body interventions for insomnia, Kozasa et al. (2010) suggest that nonpharmacological methods that promote interactions between the mind and the body to support sleep warrant further examination.

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Department of Nursing, Tzu Chi University, Hualien, Taiwan, Republic of China 2 Department of Nursing, Buddhist Tzu Chi General Hospital, Hualien, Taiwan, Republic of China 3 Department of Internal Medicine, Buddhist Tzu Chi General Hospital, Hualien, Taiwan, Republic of China 4 Department of Family Medicine, Buddhist Tzu Chi General Hospital, Hualien, Taiwan, Republic of China 5 Department of Nursing, I-Shou University, Kaohsiung, Taiwan, Republic of China Corresponding Author: Hui-Ling Lai, PhD, RN, Department of Nursing, Tzu Chi University, 707, Section 3, Chung Yang Road, Hualien 970, Taiwan, Republic of China. Email: [email protected]

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Music therapy, a mind–body domain within complementary and alternative medicine (National Center for Complementary and Alternative Medicine, 2012), is one of the strategies nurses use most frequently to help their patients to relax (Chu & Wallis, 2007). Authors of a nationwide survey among adults in Japan estimated the prevalence of using music as a self-help strategy to improve sleep to be 40–50% (Furihata et al., 2011). In one recent study, investigators verified the beneficial effects of music on sleep quality in patients in the intensive care unit (Su et al., 2013). In another study, researchers used polysomnography (PSG) to verify these beneficial effects in communitydwelling adults with insomnia (Chang, Lai, Chen, Hsieh, & Lee, 2012). Empirical research on the effectiveness of music for relaxation and improved sleep is based on psychophysiological theory (Lai & Good, 2002) and examines patients’ responses to music alone and in combination with other relaxation techniques. Using different mind–body relaxation techniques involving music, investigators have produced evidence of differing strength suggesting that soothing music has causal links with relaxation and have relied on a variety of theories to explain these links (Joanna Briggs Institute, 2011). In a meta-analysis of 10 randomized studies of the use of music therapy in sleep disorders, Wang, Sun, and Zhang, 2014) found evidence that music therapy does improve sleep quality. A more recent form of music therapy involves the use of music videos (MVs). The earliest form of MV was developed in 1890 (Allen, 2010). MVs have increasingly become one of the most popular forms of daily entertainment. An MV may present strong images to stimulate the viewers’ emotions, thus making them feel more involved in the music and the depicted scenes than they might be were they only listening to a recording. The field of MV cognition has expanded as multimedia has become an increasingly prominent aspect of life in the 21st century. A recent study suggested that a peaceful MV decreased anxiety levels and pain severity in cancer patients (Chi et al., 2011). Lai, Li, and Lee (2012) found that caregivers of cancer patients preferred an intervention involving a combination of auditory and visual stimulation to one using music, alone, to relieve stress. Therefore, MV therapy might improve sleep by alleviating anxiety. To date, however, no study has tested the general effects of an MV intervention on sleep quality. In this study, we hypothesized that watching a peaceful religious MV would have effects on sleep quality similar to those of listening to soothing music. Our assumption was that a calm MV would promote a peaceful inner state in the viewer, resulting in relaxation, drowsiness, and improved sleep quality. We chose to use Buddhist MVs in this study because 62% of the Taiwanese population identifies as Buddhistor Taoist (Executive Yuan, Taiwan, 2014) and the peaceful images and soothing music used in these videos are suitable for a relaxation intervention (Chi et al., 2011). The purpose of this randomized crossover trial, therefore, was to compare the effects of a peaceful religious MV intervention and those of usual care before bedtime on subjective and objective sleep quality in middle-aged and older adults with chronic insomnia.

Material and Method Study Design We conducted this randomized controlled crossover trial at a sleep center in a hospital in eastern Taiwan to compare the effects on objective and subjective sleep quality of watching a peaceful Buddhist MV before bedtime to usual care among middle-aged and older adults with chronic insomnia. Previous sleep-intervention research has shown that interventions performed in sleep clinics have no first-night effect on insomnia in adults because of the participants’ need to acclimatize to the environment (Chang et al., 2012). Therefore, we collected baseline data on the first night and began the testing on the second night. After the first night, participants were randomly assigned to a two-night sequence that involved (1) viewing/listening to an MV intervention on the second night followed by usual care on the third night or (2) usual care on the second night followed by the MV intervention on the third night.

Study Participants We used flyers and word of mouth to recruit 38 eligible subjects. By power analysis, we determined the necessary sample size for each sequence to be 38 based on a power of .80, α of .05, a correlation between the repeated measures (Stevens, 1996, p. 511), and an effect size of .35, which was the effect of music on sleep quality in adults with sleep disturbances in previous randomized clinical trials (Chang et al., 2012; Lai & Good, 2005; Su et al., 2013). The inclusion criteria were as follows: (1) had experienced insomnia (Pittsburgh Sleep Quality Index [PSQI] score > 5 at screening; Buysse, Reynolds, Monk, Berman, & Kupfer, 1989) for at least 1 month; (2) 50–75 years old; (3) Taiwanese; and (4) had a usual-care routine before bedtime (Johnson, 1991). The exclusion criteria were as follows: self-reported (1) psychiatric or neurological problems, (2) sleep apnea, or (3) history of alcohol/drug abuse. Over a 10-month period, we contacted 49 middle-aged and elderly adults, disqualifying 11 because they were too young to participate in the study. The remaining 38 completed the study assessments and were compensated for their participation (New Taiwan (NT)$1,000, or, approximately US$34.00).

Experimental Intervention The MV intervention consisted of a 30-min set of MVs that was shown to patients at bedtime in a room in the sleep center. The seven peaceful religious videos that comprised the 30-min intervention showed nature scenes along with text comprising Buddha’s teaching and words of wisdom while the peaceful music was being played (Jing Si Publication, Taipei, Taiwan): Petition of Vow, To Ask Ourselves, There Is Love in This World, Thoughts and Feelings of Compassion, Path, Kneeling Sheep, and Prayer. We adjusted MV volume to a comfortable listening level before the session, as determined by each participant, and left the participants alone to watch the MV. We selected a video length of

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30 min because previous research demonstrated that heart rate, mean arterial pressure, and finger temperature were reduced after listening to relaxing music for 5 (Lai, Li, & Lee, 2012) and 30 min (Su et al., 2013). In addition, Chang, Lai, Chen, Hsieh, and Lee (2012) reported that sleep onset, as assessed by PSG in adults with insomnia, occurred 13–30 min after the start of the music intervention. Our selection of these particular MVs was based on psychophysiological theory and focused on helping participants achieve a relaxed psychophysiological state (Lai & Good, 2002). The sequential arrangement of these musical image pieces was standardized and predetermined by the investigators. All of the videos had peaceful Buddhist characteristics with no sudden changes in volume. The musical tempos ranged from 60 to 85 beats/min (slow), and the music used minor tonalities and smooth melodies to achieve a relaxing effect (Nilsson, 2010).

Measures and Instruments Chronic insomnia. For this study, chronic insomnia was defined as the subjective report of difficulty in initiating/maintaining sleep and/or nonrestorative sleep accompanied by decreased daytime functioning (American Academy of Sleep Medicine, 2005) that persisted for at least 4 weeks (Schutte-Rodin et al., 2008). We used the PSQI (Buysse et al., 1989), a Visual Analog Scale (VAS), and PSG to assess insomnia. PSQI. The PSQI was administered 1 week before the night of PSG. The PSQI is a self-report questionnaire that assesses sleeping habits during the previous month. Its 19 self-rating items are grouped into seven component scores. The sum is a sleep quality score ranging from 0 to 21 to yield a global PSQI score, with higher scores indicating worse sleep quality. A PSQI score >5 identifies subjects suffering from poor sleep quality (Buysse et al., 1989) and was the cutoff that we used to determine eligibility for participation in the present study. Cronbach’s α for the seven components was .83. The Chinese version of the PSQI with scores >5 had a sensitivity and specificity of 98% and 55%, respectively, for people with insomnia (Tsai et al., 2005). The definitions of the seven components of PSQI are presented in Table 1. VAS. We used an investigator-designed VAS to assess four aspects of sleep: ease of getting to sleep, perceived quality of sleep, ease of awakening from sleep, and daytime function. The VAS is more sensitive than a Likert-type scale for assessing subjective experiences (Gift, 1989). The scale consisted of a horizontal 10-cm line with an affixed scale and was administered at baseline after each intervention. Higher values indicate better sleep quality. PSG. PSG included a standard 16-channel montage for scoring sleep parameters. The international 10–20 system was used to mark the standard electrode sites. Sleep recordings were scored at 30-s intervals for each stage of sleep using standard criteria (Iber, Ancoli-Israel, Chesson, & Quant, 2007). PSG data were

Table 1. Definitions of the components of the Pittsburgh Sleep Quality Index (PSQI). Component

Definition/calculations

Sleep latency

Reported number of minutes needed to fall asleep and number of times during the previous month there was difficulty getting to sleep Sleep duration Reported number of hours of sleep per night Perceived sleep Subjective rating of sleep quality over the previous quality month on a 4-point scale Sleep efficiency Number of hours slept divided by the number of hours spent in bed expressed as a percentage by multiplying by 100 Sleep disturbance Frequency of 10 ways of awakening on a 4-point scale. The sum of the ratings for the 10 ways serves as the score Use of sleep How often subject has taken medicine to help medication sleep coded on a 4-point scale Daytime Frequency of staying awake and difficulty of dysfunction maintaining enthusiasm during the daytime, which are summed to calculate a score

analyzed using Somnologica Studio 3.3.2 software (Somnologica, Flaga hf, Medical Devices, Iceland). Total sleep time (TST), sleep efficiency (SE; TST/total recording time expressed as a percentage), sleep-onset latency (SOL), wake after sleep onset (WASO), number of awakenings, percentages of time in stages N1, N2, N3 and in rapid eye movement (REM) sleep (Iber et al., 2007), and arousal index (number of electroencephalographic arousals per hour of sleep) were automatically recorded with a laboratory-based PSG system (Embla, Denver, CO) using electroencephalography (including O1-A2, O2-A1, C3-A2, and C4-A1), electromyography (submental), and right and left electrooculography during the study nights. Anxiety. We used the State-Trait Anxiety Inventory (STAI; Spielberger, 1983) to evaluate how anxious participants feel “right now.” This inventory uses a 4-point Likert-type scale response format in which a score of 20 indicates the absence of anxiety and a score of 80 indicates high anxiety. Self-reported anxiety levels correlate well with objective measures of anxiety levels based on vital signs among Taiwanese populations (Lai et al., 2008). The state of anxiety was assessed at baseline only and was treated as a potential confounder. Cronbach’s α for the Chinese version of the STAI used in our study was .79. Depression. For the purposes of the present study, we defined depression as sadness, melancholy, or a feeling of hopelessness which could vary in duration and degree and could produce physiological and other psychological manifestations. Depression was assessed using the Chinese version of the short-form Geriatric Depression Scale (Lee et al., 1993). In the instrument, respondents report their usual feelings over the previous week (Yesavage et al., 1983) using a yes/no response format, with 0 = no and 1 = yes. Scores range from 0 to 15, with higher scores indicating more severe depression. Lee et al. (1993) reported an optimal cutoff score of 8 to identify depression in a Chinese

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population. This cutoff score had a sensitivity of 96.3% and a specificity of 87.5%. In our study, the α coefficient was .84. Depression was assessed at baseline only and was treated as a potential confounder.

using a VAS, which had been sent home with the patients from the sleep laboratory.

Subjective experience of the MV intervention. We used a VAS to evaluate the participants’ subjective experiences associated with the MV. This VAS used a horizontal 10-cm line with an affixed scale; the left end of the scale represented not at all and the right end of the scale represented very much. A score of 10 indicated the most positive experience of the MV intervention

Data were analyzed using PASW 18.0 for Windows (SPSS Inc., Chicago, IL). Descriptive statistics were used to summarize the data. Generalized estimating equation (GEE) analysis was used to control baseline values to compare differences between the groups (Liang & Zeger, 1986). Baseline outcome measurements were used as covariates in the data analysis (Cook & Campbell, 1979). Wilcoxon’s signed rank test was used to assess the carryover effect. A p-value of