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Changes in Sleep With Auricular PointAcupressure for Chronic Low Back PainChao Hsing Yeha, Lorna Kwai-Ping Suenb, Juan Shenc, Lung-ChangChiende, Zhan Lianga, Ronald M. Glickf, Natalia E. Moronegh & EileenR. Chasensa

a School of Nursing, University of Pittsburghb School of Nursing, Hong Kong Polytechnic Universityc School of Nursing, Suzhou Health Colleged Department of Biostatistics, University of Texas School of PublicHealth at San Antonio Regional Campuse Research to Advance Community Health Center, University of TexasHealth Science Center at San Antonio Regional Campusf Departments of Psychiatry, Physical Medicine, and Rehabilitation,University of Pittsburgh, School of Medicineg Department of Medicine, Division of General Internal Medicine,University of Pittsburgh, School of Medicineh Veterans Administration Pittsburgh Healthcare System, GeriatricResearch, Education, and Clinical CenterPublished online: 05 Aug 2015.

To cite this article: Chao Hsing Yeh, Lorna Kwai-Ping Suen, Juan Shen, Lung-Chang Chien,Zhan Liang, Ronald M. Glick, Natalia E. Morone & Eileen R. Chasens (2015): Changes in SleepWith Auricular Point Acupressure for Chronic Low Back Pain, Behavioral Sleep Medicine, DOI:10.1080/15402002.2014.981820

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Behavioral Sleep Medicine, 00:1–16, 2015

Copyright © Taylor & Francis Group, LLC

ISSN: 1540-2002 print/1540-2010 online

DOI: 10.1080/15402002.2014.981820

Changes in Sleep With Auricular PointAcupressure for Chronic Low Back Pain

Chao Hsing YehSchool of Nursing, University of Pittsburgh

Lorna Kwai-Ping SuenSchool of Nursing, Hong Kong Polytechnic University

Juan ShenSchool of Nursing, Suzhou Health College

Lung-Chang ChienDepartment of Biostatistics, University of Texas School of Public Health at San Antonio

Regional Campus

Research to Advance Community Health Center, University of Texas Health Science

Center at San Antonio Regional Campus

Zhan LiangSchool of Nursing, University of Pittsburgh

Ronald M. GlickDepartments of Psychiatry, Physical Medicine, and Rehabilitation, University of

Pittsburgh, School of Medicine

Natalia E. MoroneDepartment of Medicine, Division of General Internal Medicine, University of

Pittsburgh, School of Medicine

Veterans Administration Pittsburgh Healthcare System, Geriatric Research, Education,

and Clinical Center

Eileen R. ChasensSchool of Nursing, University of Pittsburgh

Correspondence should be addressed to Chao Hsing Yeh, RN, PhD, University of Pittsburgh, School of Nursing,

3500 Victoria Street, 440 Victoria Building, Pittsburgh, PA 15261, USA. E-mail: yehc@pitt.edu

Color versions of one or more figures in this article are available online at www.tandfonline.com/hbsm

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2 YEH ET AL.

The purpose of this study was to report sleep quality from 4 weeks of auricular point acupressure

that was designed for chronic low back pain and determine the relationship between pain intensity

and sleep quality. Participants were randomized into the APA group .n =30/ or the sham-APA group

.n =31/. At baseline assessment, 87% of the participants reported poor sleep quality. Participants

who received APA had decreased daytime disturbance and improved global Pittsburgh Sleep Quality

Index scores at end of intervention (EOI) and 1-month follow up compared to participants in the

sham-APA group. For the APA group, both the sleep duration and wake after sleep onset decreased

gradually during the 4-week APA (0.56% and 0.23% daily change, respectively).

With an annual prevalence estimated at 28%, chronic low back pain (CLBP) is the most

common self-reported pain condition in the United States (National Center for Health Statistics,

2014; Waterman, Belmont, & Schoenfeld, 2012). As such, CLBP imposes a significant societal

and economic burden on the U.S. health care system. The estimated cost of CLBP in theUnited States ranges from $84.1 billion (direct—health care) to $624.8 billion (indirect—loss

in productivity) per year (Dagenais, Caro, & Haldeman, 2008; Gore, Sadosky, Stacey, Tai, &

Leslie, 2012; Katz, 2006).

Patients who suffer from CLBP often report the co-occurrence of sleep disorders (Alsaadi,

McAuley, Hush, & Maher, 2011; Marin, Cyhan, & Miklos, 2006). It is estimated that morethan 50% of CLBP patients report sleep disturbances (Alsaadi et al., 2011; Kelly, Blake, Power,

O’Keeffe, & Fullen, 2011). Sleep-related problems have been suggested as an important element

in evaluating the efficacy and effectiveness of pain management outcomes from not only the

recommendations of experts (Turk et al., 2008), but also patients (Casarett, Karlawish, Sankar,

Hirschman, & Asch, 2001). For example, in a study of 367 older adults with osteoarthritispain and insomnia, the short-term improvement in sleep (i.e., 2 months) can predict long-term

(i.e., 9 and 18 months) chronic pain improvement (Vitiello et al., 2014). Additionally, in a

study of 1,206 patients experiencing difficulty in resuming work, 74% of patients experiencing

moderate/severe sleep disturbance also reported moderate/severe pain problems (Linder, Jansen,

Ekholm, & Ekholm, 2014). Nonetheless, current clinical research generally does not include

sleep disturbance as a pain management outcome (Vickers et al., 2012; Witt et al., 2012).Multiple pharmacologic and nonpharmacologic treatments exist that, when implemented

properly, can provide relief for many who experience CLBP (Chang, Gonzalez, & Akuthota,

2008; Dagenais, Tricco, & Haldeman, 2010; Haldeman & Dagenais, 2008; Rubinstein et al.,

2010; White, Arnold, Norvell, Ecker, & Fehlings, 2011). However, even when pain is ag-

gressively treated according to state-of-the-science recommendations, CLBP pain managementremains suboptimal for many (Dagenais et al., 2008; Katz, 2006). Analgesic use is the most

common strategy to treat CLBP, yet this is associated with a variety of adverse side effects.

In addition, a patient’s needs for pain medication can escalate, resulting in dependence and

the potential for drug addiction (Benyamin et al., 2008; Malanga & Wolff, 2008). Therefore, a

growing number of CLBP patients in the United States have sought nonpharmacological painmanagement. In 2007, American adults spent an estimated $33.9 billion on complementary

and alternative medicine (CAM) and $11.9 billion on visits to CAM practitioners, including

acupuncturists (Nahin, Barnes, Stussman, & Bloom, 2009). In particular, a 2007 government

survey estimated that more than 3 million American adults had used acupuncture for CLBP

in the previous 12 months (Barnes, Bloom, & Nahin, 2008). While acupuncture can be an

effective therapy for pain management (Vickers et al., 2012), use of this approach is limited

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CHANGES IN SLEEP WITH ACUPRESSURE 3

because (a) patients must travel frequently to receive acupuncture treatment (Lu & Rosenthal,

2010), (b) the cost of treatment often is not covered by insurance (Lind et al., 2005), and(c) patients may be afraid of needles (Schapira et al., 2014).

Auricular point acupressure (APA), an alternative to acupuncture, utilizes pressure applied to

botanical seeds (or pellets) taped onto specific ear acupuncture points to produce acupuncture-

like stimulation effects. In this way, APA can treat disease and illness without using needles

(Huang, 2005; Oleson, 2014). APA is based on reflex theory, which posits that the symptomaticbody can induce tenderness in specific ear points, and the treatment of these ear points can

stimulate the brain to correct related pathological reflex centers, which, in turn, will induce

reflex reactions in the body to relieve pathology (Nogier, 1981; Oleson, 2014). The World

Health Organization (WHO) considers APA a form of micro-acupuncture that can affect the

whole body (World Health Organization, 1990).

Our previous publications describe how APA has been used to manage pain in CLBPpatients. These studies provide preliminary evidence of immediate CLBP relief (i.e., a 40%

reduction in pain intensity) after one day of APA (Yeh, Chien, Chiang, & Huang, 2012)

and even greater and lasting effects on CLBP (i.e., 75% pain relief and 45% better physical

function after a four-week APA treatment, which were statistically significant compared to

the sham APA group; Yeh et al., 2013). Participants in the APA treatments exhibited changesin inflammatory cytokines (decreased IL-1ˇ, IL-4, IL-10; increased IL-2; Yeh et al., 2014),

decreased pain catastrophizing (Yeh et al., 2013), and reduced fear avoidance after a four-week

APA intervention, when compared with participants in the sham group (Yeh et al., 2013). This

paper describes the sleep quality results of a four-week APA that was designed for CLBP and

sought to determine whether or not there was any relationship between pain intensity and sleepdisturbance.

METHODS

The complete details of the study design, sample, and data collection are described in our

previous publication (Yeh et al., 2013). In brief, 61 participants with CLBP were enrolled;

30 participants were randomized into the APA group, and 31 into the sham APA group.

CLBP was defined as low back pain occurring for at least three months with an average pain

intensity score of at least 4 (on a 0 to 10 scale) for one week before the time of enrollment.Every participant received weekly APA treatment for four weeks based on his or her group

assignment. Data were collected at baseline, during each of the four office visits for APA

treatment, after the completion of the four-week APA (i.e., end of intervention [EOI]), and one

month after the last treatment. A daily diary was given to each participant to record his or

her APA practices, analgesic use, and pain intensity. Institutional review board approval was

obtained before conducting the study.

Auricular Point Acupressure Treatment Protocol

The selection of ear points for APA treatment includes (a) corresponding points, (b) points

featuring both disharmony of zang organs and disturbance of meridians, and (c) active points

located at the waist triangle, groove of spinal posterior, and groove of sciatic posterior areas

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4 YEH ET AL.

FIGURE 1 Ear points selection.

of the ear (Huang & Huang, 2007). The Chinese Standard Ear-Acupoints Chart, which is

recognized by the WHO, is used to locate the points (World Health Organization, 1990).

Figure 1 lists the ear points treated for CLBP. In Figure 1, the ear points corresponding to

the lower back are circled in red on the anterior side of the ear and appear as red points on

the posterior side of the ear. The three points for alleviating stress and pain (i.e., shenmen,sympathetic, and nervous subcortex), according to disharmony of zang organs and disturbance

of meridians, are located on the anterior ear. The active ear points corresponding to CLBP

(appearing as the waist triangle cluster) and the grooves of the spinal and sciatic posterior

are all located on the posterior side of the ear. An electrical point finder (Auricular Medicine

International Research & Training Center [AMIRCT], Birmingham, AL) was used to locate thepoints, which is done by detecting decreased electrical resistance. Vaccaria seeds were placed

on the subject’s ears based on the points indicated by the AMIRCT point finder.

Participants in the sham APA group had Vaccaria seeds taped onto the stomach, mouth,

duodenum, and eye acupoints of both ears. Participants were told (a) to press the seeds on each

ear at least three times a day for 3 min each time using the thumb and forefinger and (b) topress the seeds whenever they experienced pain. Participants were instructed to remove the

tape and seeds after five days. Doing so ensured that not only the ear was free of tape two days

each week to minimize the risk of an allergic reaction to the tape, but also the acupoints were

allowed time to recover and restore sensitivity prior to the next treatment. Each participant was

given a diary to monitor his or her adherence to the treatment protocol (i.e., the actual times he

or she pressed the seeds each day and the duration of applied pressure), analgesic use, related

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CHANGES IN SLEEP WITH ACUPRESSURE 5

medication and supplements, and pain intensity. All data were collected by a trained collector

who was blinded to the group assignment of the participants.

Outcome Measures

The Brief Pain Inventory-short form (BPI-sf; Cleeland & Ryan, 1994) was used to measure

pain intensity. The BPI-sf includes two subscales: pain severity/intensity and pain interferencesduring the previous seven days. In the data analysis featured in this paper, only the worst pain

intensity was used. Pain severity/intensity comprises four items (i.e., worst, least, average, and

now) that assess pain on an 11-point scale (i.e., 0 D no pain at all and 10 D pain as bad as

you can imagine). Higher subscale BPI-sf scores indicate more severe pain.

The Pittsburgh Sleep Quality Index (PSQI; Buysse, Reynolds, Monk, Berman, & Kupfer,1989) is a 19-item, self-rated quesionnaire to assess subjective sleep quality and disturbances

during the previous month. The PSQI consistents of seven domain scores that include subjective

sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use

of sleep aid medications, and daytime dysfunction. Scores for these domains are combined

to provide a global sleep quality index score. The global PSQI scores potentially range from0 to 21, with a PSQI score greater than 5 indicating poor sleep quality. In our analysis, the

item pain was removed to avoid possible corrleation with pain intensity. A three-factor scoring

model (i.e., sleep efficiency, perceived sleep quality, and daily disturbance; Cole et al., 2006) is

reflective of how people respond to impaired sleep quality and therefore was used in the final

data analysis. A decrease of three points on the PSQI is considered to be a clinically important

difference (Buysse et al., 2011). The Cronbach’s alpha for the global PSQI was 0.83 in thestudy that we are reporting here.

The Daily Sleep Diary (Carney et al., 2012) was used to record self-reported sleep parameters

in addition to daily worst pain intensity, pain medication, and APA practice. These sleep

parameters included time in bed (i.e., the total amount of time in bed at night), nocturnal sleep

time (i.e., the total time the participants slept at night), sleep latency (i.e., the amount of timeit takes to fall asleep after the lights have been turned off), sleep efficiency (i.e., calculated

as self-reported sleep duration divided by time in bed multiplied by 100), wake after sleep

onset (i.e., the amount of time a participant was awake during the night), total sleep time

(i.e., nocturnal sleep time minus sleep latency minus wake after sleep onset), and number of

awakenings (i.e., how many times the participant woke up during the night after sleep onset).

The Demographics and Health History questionnaire designed by the research team queriesage, marital status, education level, living arrangements, ethnicity, disease diagnosis, chronic

condition, related medication, cancer treatment status, and adjunct pain treatments used.

Data Analysis

In order to examine the true effects of the APA, two types of analyses were conducted for

primary outcomes: (a) intent-to-treat (ITT) analysis, which used the data of all participants,

regardless of adherence, treatment received, withdrawal, or devation from protocol (Heritier,

Gebski, & Keech, 2003; Newell, 1992; Wertz, 1995) and (b) per-protocol (PP) analysis, which

included only those participants who adhered to the APA (Heritier et al., 2003; Newell, 1992;

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6 YEH ET AL.

Wertz, 1995). Missing values of the outcome variables were replaced by last observation

carried forward. Descriptive statistics were used to present demographic characteristics andstudy measures. A general linear model with post hoc test (using the GLM Procedure in SAS)

was used to capture the main effects of change scores of outcome measures (i.e., baseline to

EOI and one-month follow-up, modeling covariance across time) and the group comparison

(i.e., APA and sham APA) and their interaction effect (McGullagh & Nelder, 1989). Moreover,

the joinpoint regression modeling approach was used to estimate the linear trend of dailysleep parameters over time (Kim, Fay, Feuer, & Midthune, 2000). The model was constructed

by fitting a linear regression to the score of sleep parameters, using the daily mean score

as a regression outcome and calendar day as a predictor, to characterize the trend of change

from baseline (i.e., day 0) to the completion of the four-week APA treatment (i.e., day 28).

This approach can analyze trends with different plots connected at certain joinpoints, and each

joinpoint represents a significant change in the slope of the trend. A permutation test determinedthe best number of joinpoints in the final model of each measurement in each group (Kim

et al., 2000). The Pearson correlation coefficient was used to examine the relationship between

outcomes. Differences were considered statistically significant at p < :05. All of the data

analyses were performed using SAS software, version 9.2, and Jointpoint software, version

4.1.0.

RESULTS

Demographic Characteristics

Sixty-one participants were randomized into the APA group (n D 30) and the sham APA group(n D 31; Table 1). The retention rate was 83% (n D 25) for the APA group and 68% (n D

21) for the sham group. The mean age of the 61 participants was 63.3 years (SD D 16.70;

range 20–90 years), and they were primarily female (n D 41, 67.2%) and white (n D 51,

83.6%). Four participants took sleep medication at the time of data collection, which included

temazepam (n D 1), melatonin (n D 1), and an over-the-counter sleep aid (n D 2). There

were no statistically significant differences in demographic characteristics between the APAand sham APA groups. In addition, there were no statistically significant differences in pain

intensity (including worst pain, average pain, and current pain) and sleep quality at baseline

assessment between the APA and sham APA groups.

Sleep Quality

The majority of participants displayed poor sleep quality (i.e., the global PSQI score was > 5

for 90% [n D 27] of the APA group and for 84% [n D 26] of the sham APA group). At baseline,there was no statistically significant difference in sleep efficiency, perceived sleep quality, daily

disturbance, or the global PSQI score between the APA and sham APA groups. These findings

are not presented here, but are available upon request. Table 2 presents the change scores in

outcomes measures from baseline to EOI and to one-month follow-up for both ITT and PP.

For ITT, the average score of worst pain in the APA group decreased 3.53 points from baseline

to EOI, which was a statistically significant change compared to the sham APA group, which

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CHANGES IN SLEEP WITH ACUPRESSURE 7

TABLE 1

Demographic Characteristics of the Participants (n D 61)

Mean (SD) or n (%)

Real (n D 30) Sham (n D 31) p-value

Age

Mean (SD) 60.97 (17.44) (20–82) 65.61 (16.04) (21–90) 0.91

Gender, n (%)

Male 10 (33.3%) 10 (32.3%) 0.93

Female 20 (66.7%) 21 (67.7%)

Race/ethnicity, n (%)

White 26 (86.7%) 25 (80.6%) 0.73

Black/African American 4 (13.3%) 6 (19.4%)

Marital status, n (%)

Married or living with partner 14 (46.7%) 13 (42.0%) 0.78

Divorced or widowed 10 (33.4%) 11 (35.5%)

Never married 6 (20% ) 5 (16.1%)

Employment situation 0.67

Working (full time) 6 (20%) 4 (12.9%)

Working (part time) 2 (6.7%) 2 (6.5%)

Not employed 4 (13.2%) 6 (19.4%)

Retired 15 (50%) 14 (45.1%)

Others 3 (10%) 5 (16.2%)

Education level

< 11th grade 2 (6.7%) 2 (6.5%) 0.62

High school 5 (16.7%) 4 (12.9%)

Technical or vocational school 2 (6.7%) 2 (6.5%)

College and graduate 21 (70.1%) 21 (67.7%)

Missing 2 (6.5%)

Estimated income before taxes 0.25

Less than $10,000 5 (16.7%) 7 (22.6%)

$10,000 to $19,999 2 (6.7%) 5 (16.1%)

$20,000 to $39,999 8 (26.7%) 2 (6.5%)

$40,000 to $59,000 6 (20%) 7 (22.6%)

$60,000 to $100,000 3 (10%) 5 (16.1%)

More than $100,000 3 (10%) 1 (3.2%)

Missing 3 (10%) 4 (12.9%)

Medical diagnosis related to back pain

Osteoporosis 3 (10%) 4 (12.9%)

Osteoarthritis 9 (30%) 9 (29%)

Scoliosis 4 (13.3%) 5 (16.1%)

Kyphosis 1 (3.3%) 0 (0%)

Discherniation 6 (20%) 7 (22.6%)

Spinal stenosis 8 (26.7%) 13 (41.9%)

Spondylitis 1 (3.3%) 0 (0%)

Spondylosis 3 (10%) 0 (0%)

Current pain medication use

Yes 13 (43.3%) 14 (45.2%)

No 17 (56.7%) 17 (54.8%) 0.89

Current sleep medication use

Yes 1 (3.3%) 3 (9.7%)

No 29 (96.7%) 28 (90.3%) 0.89

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TABLE 2

Outcome Measurement Changes From Baseline to End-of-Intervention and One-Month Follow-Up Between the APA and Sham APA Groups

APA Sham Difference (APA–Sham)

Outcome Duration Mean SD Mean SD Estimate 95% CI p-value Effect

ITT

Worst pain Baseline to End-of-Intervention �3.53 2.66 �0.77 1.41 �2.76 �3.93 �1.59 <.0001 1.30

Baseline to 1-Month Follow-up �3.70 2.78 �0.84 2.22 �2.86 �4.03 �1.69 <.0001 1.14

Perceived sleep quality Baseline to End-of-Intervention �0.24 0.34 �0.08 0.35 �0.16 �0.36 0.05 0.1300 0.46

Baseline to 1-Month Follow-up �0.26 0.52 0.01 0.38 �0.27 �0.47 �0.06 0.0115 0.58

Sleep efficiency Baseline to End-of-Intervention �0.15 0.89 �0.05 0.52 �0.10 �0.52 0.32 0.6348 0.14

Baseline to 1-Month Follow-up �0.08 1.12 0.15 0.69 �0.23 �0.65 0.19 0.2864 0.25

Daytime disturbance Baseline to End-of-Intervention �0.20 0.39 �0.02 0.33 �0.18 �0.39 0.02 0.0776 0.51

Baseline to 1-Month Follow-up �0.13 0.51 �0.05 0.37 �0.08 �0.29 0.12 0.4124 0.19

Global PSQI Baseline to End-of-Intervention �1.42 2.08 �0.37 1.37 �1.05 �2.22 0.13 0.0840 0.60

Baseline to 1-Month Follow-up �1.22 3.55 0.21 1.83 �1.43 �2.60 �0.25 0.0191 0.51

PP

Worst pain Baseline to End-of-Intervention �3.21 2.58 �0.78 1.72 �2.66 �4.04 �1.29 0.0003 1.27

Baseline to 1-Month Follow-up �3.43 2.90 �0.22 2.22 �2.77 �4.14 �1.40 0.0002 1.06

Perceived sleep quality Baseline to End-of-Intervention �0.19 0.31 �0.07 0.40 �0.17 �0.43 0.10 0.2204 0.43

Baseline to 1-Month Follow-up �0.33 0.65 0.26 0.40 �0.32 �0.59 �0.06 0.0202 0.62

Sleep efficiency Baseline to End-of-Intervention �0.11 1.10 �0.11 0.70 �0.11 �0.67 0.45 0.7038 0.13

Baseline to 1-Month Follow-up �0.18 1.54 0.11 0.99 �0.31 �0.87 0.24 0.2725 0.29

Daytime disturbance Baseline to End-of-Intervention �0.39 0.45 0.17 0.43 �0.22 �0.48 0.05 0.1177 0.53

Baseline to 1-Month Follow-up �0.32 0.61 0.11 0.60 �0.09 �0.36 0.18 0.5191 0.17

Global PSQI Baseline to End-of-Intervention �1.57 2.41 �0.11 1.45 �1.15 �2.70 0.39 0.1474 0.59

Baseline to 1-Month Follow-up �2.00 4.76 1.22 1.64 �1.77 �3.31 �0.22 0.0273 0.55

Note. ITT: intention-to-treat; PP: per-protocol; SD D standard deviation; PSQI: Pittsburgh Sleep Quality Index; CI D confidence interval.

Worst pain: higher scores higher pain intensity. Perceived sleep quality factor, sleep efficiency factor, daytime disturbance factor: higher scores indicate poorer

sleep quality.

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CHANGES IN SLEEP WITH ACUPRESSURE 9

only displayed 0.77 points of decrement (p value < .0001). The APA group also displayed

a statistically significant 2.86-point (p value < .0001) decrement compared to the sham APAgroup from baseline to one-month follow-up. For sleep quality outcomes, participants in the

APA group displayed statistically significant, decreased scores in perceived sleep quality and

the global PSQI score from baseline to one-month follow-up compared to participants in the

sham APA group. Similar findings were also obtained for PP.

In terms of sleep disturbance, 27 participants in the APA group reported sleep disturbance(global PSQI score > 5) at baseline, but 3 of them (11%) had no sleep disturbance at EOI,

and 4 of them (15%) improved their sleep disturbance at one-month follow-up. However, 26

participants in the sham APA group reported sleep disturbance at baseline, and one of them

(4%) had no sleep disturbance at EOI, and there was no sleep improvement at one-month

follow-up. There was no statistically significant improvement in sleep disturbance between the

APA and the sham groups.We further examined whether or not the participants who completed the four-week APA

experienced clinically significant improvement of PSQI—defined as a three-point decrease in

the global PSQI score. Only participants who completed the entire study assessment were

examined. Twenty-four percent of participants who completed the four-week APA (n D 6

of 25 total) at EOI and 28% of participants at one-month follow-up (n D 7 of 21 total)experienced clinically significant improvement in the global PSQI score. The difference in two

proportions (from baseline to EOI and baseline to one-month follow-up) is �4 (95% CI D

�28, 20), which indicates there is no statistically significant difference between the change at

EOI and the change at one-month follow-up in the APA group. Additionally, only 10% (n D

2) of participants in the sham APA group at EOI and 5% (n D 1) at one-month follow-uphad changes in scores of three or greater points, but there were no within-groups differences

in the sham group (95% CI D �12, 20). For the between-group differences, the proportional

difference between the APA group and the sham group is not statistically significant (95% CI D

�6, 35) from baseline to EOI; however, the proportional difference was 23% from baseline to

one-month follow-up (95% CI D 2, 43), which suggests that the proportion of the participants

in the APA group who exhibited an improved PSQI score is, statistically, significantly highercompared to the participants in the sham group at one-month follow-up.

Daily Worst Pain and Sleep Diary

Table 3 lists the trends of worst pain, sleep efficiency, sleep latency, time awake after sleep

onset, sleep awakenings, and sleep duration, and these trends are shown in Figure 2. We

observed that both the APA and sham APA groups displayed the same statistically significant

decrease in the time trend of worst pain on day 2, which caused a statistically significant daily

decrease of 1.22 points (p value D 0.0001; 95% CI D �1.71, �0.74) in the APA group and0.60 points (p value D 0.0151; 95% CI D �1.05, �0.15) in the sham APA group from baseline.

After day 2, the worst pain score increased; however, only the sham APA group displayed a

statistically significant daily increase of 0.02 points (p value D 0.0033; 95% CI D 0.01, 0.03)

until day 28. The APA group had an additionally statistically significant bent on day 9, which

lead to a statistically significant decrease of 0.06 points (p value < .0001; 95% CI D �0.08,

�0.04) until day 28.

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TABLE 3

Trends of Worst Pain Score and Sleep Factors

APA Sham APA

Period

(Days) Estimate 95% CI p-value

Period

(Days) Estimate 95% CI p-value

Worst pain 0–2 �1.22 �1.71 �0.74 0.0001 0–2 �0.60 �1.05 �0.15 0.0151

2–9 0.07 �0.03 0.17 0.2004 2–28 0.02 0.01 0.03 0.0033

9–28 �0.06 �0.08 �0.04 <.0001

Sleep duration 0–28 �0.55 �1.01 �0.08 0.0300 0–10 2.80 0.85 4.75 0.0097

10–28 �0.89 �1.75 �0.02 0.0557

Sleep efficiency 0–28 0.0001 �0.0001 0.0004 0.3244 0–9 0.0019 0.0001 0.0036 0.0476

9–28 �0.0002 �0.0007 0.0003 0.4233

Sleep latency 0–28 0.03 �0.02 0.07 0.2611 0–28 0.03 �0.02 0.07 0.2611

Sleep awakenings 0–12 �0.04 �0.06 �0.02 0.0019 0–7 �0.06 �0.13 0.01 0.0939

12–15 0.13 �0.29 0.54 0.5523 7–28 0.0022 �0.0072 0.0117 0.6477

15–28 �0.05 �0.07 �0.03 0.0001

Time awake after sleep onset 0–28 �0.23 �0.32 �0.14 <.0001 0–28 �0.09 �0.19 �0.02 0.1337

Note. CI: confidence interval. Worst pain: negative trend means improvement; positive trend means worsening. Sleep efficiency, sleep latency, sleep awakenings,

time awake after sleep onset: negative trends mean worsening, positive trend means improvement.

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FIGURE 2 The daily change patterns of worst pain intensity and sleep quality.

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12 YEH ET AL.

TABLE 4

Pearson Correlation Between Pain Intensity and Sleep Quality

Worst Pain

Perceived

Sleep Quality

Sleep

Efficiency

Daytime

Disturbance

Global

PSQI

Baseline .33* .11 .22 .31*

End-of-intervention .51** .17 .46** .53**

One-month follow-up .44** .34** .45** .58**

*Correlation is significant at the 0.05 level (2-tailed). **Correlation is significant at the

0.01 level (2-tailed).

Note. PSQI: Pittsburgh Sleep Quality Index.

For the other five sleep parameters, there was no statistically significant bent in the APA

group, except for sleep awakenings, which had two statistically significant bents on day 12

and day 15, causing two statistically significantly declining trends: �0.04 times (p value D

0.0019; 95% CI D �0.06, �0.02) per day from baseline to day 12 and �0.05 times (p value D

0.0001; 95% CI D �0.07, �0.03) per day from day 15 to day 28. Even though there was no

statistically significant bent for the other four sleep parameters in the APA group, we examined

significant declinations in sleep duration and time awake after sleep onset. In the sham APA

group, there were three statistically significant bents for sleep duration, sleep efficacy, andsleep awakenings. The statistically significant bent in sleep duration in the sham APA group

reflects a statistically significantly daily elevation by 2.80 min (p value D 0.0097; 95% CI D

0.85, 4.75) from baseline to day 10; however, there was no statistically significant trend after

day 10. The same situation emerged for sleep efficiency in the sham APA group-a statistically

significant bent was observed on day 9, which produced a statistically significant incrementfrom baseline to day 9 (p value D 0.0476) but no statistically significant trend after day 9. For

the other two sleep factors without statistically significant bents (i.e., sleep latency and time

awake after sleep onset), we did not observe significant time trends during the study period in

the sham APA group.

Relationship Between Sleep Quality and Worst Pain

The relationships between sleep quality and pain intensity are displayed in Table 4. At baseline,worst pain had a moderate, positive relationship with worse perceived sleep quality (Pearson’s

r D 0.33, p < 0.05) and the global PSQI score (Pearson’s r D 0.31, p < .05). Simultaneously,

worst pain had a weak positive relationship with the daytime disturbance factor score (Pearson’s

r D 0.22, p D 0.06). Worst pain intensity had a strong positive relationship with worse scores

on the perceived sleep quality factor, the daytime disturbance factor, and the global PSQI score(Table 4).

DISCUSSION

This is the first study to report the change patterns of sleep quality and sleep parameters in a

four-week APA treatment protocol that was designed to reduce CLBP. The findings indicate

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CHANGES IN SLEEP WITH ACUPRESSURE 13

that participants who received APA designed for CLBP had statistically significant reduced

perceived sleep quality and global PSQI scores (lower scores indicate improved sleep) atone-month follow-up compared to participants in the sham APA group. Additionally, strong

positive relationships were found among more severe pain intensity, worse perceived sleep

quality, increased daytime disturbance, and increased global PSQI scores. For the APA group,

both sleep duration and time awake after sleep onset decreased gradually during the four-week

APA (0.56% and 0.23% daily change, respectively). Sleep efficiency and sleep awakeningsremained relatively constant throughout the four-week APA.

Our interpretation of the study findings is limited by the small sample size, the unblinding of

the therapist and the primary investigator, the lack of inclusion/exclusion criteria related to sleep

disorders, upper age limits, and the lack of comorbidities data, which may affect sleep quality.

Moreover, the sleep of the participants, according to their diaries, was not greatly impaired,

which might have limited the possible effects of the intervention. These shortcomings shouldbe addressed in a future study. Additionally, the dropout rate (39%) was higher in the sham

APA group, which limits the comparisons that can be made between the two APA groups.

To address this issue, strategies will need to be implemented in any future study to improve

participant retention that could include (a) calling the participants when a treatment session is

missed to discern the cause and (b) providing participant transportation.Another limitation of the study was that sleep was evaluated with only self-report measures.

No objective measurement of sleep disorders, such as obstructive sleep apnea or restless leg

syndrome, was made. Future research evaluating the effect of auricular therapy for treatment

of insomnia would benefit by the objective evaluation of sleep—possibly with actigraphy.

There was an 87% prevalence of poor sleep quality among participants (90% in the APAgroup and 84% in the sham APA group; PSQI global score > 5) at baseline assessment,

which is much higher than the 50% sleep disturbance reported in the literature (Alsaadi et al.,

2011; Kelly et al., 2011). Although there were no statistically significant differences in sleep

efficiency factor scores between the APA and sham APA groups, the daytime disturbance

factor scores and global PSQI scores improved significantly at EOI and one-month follow

up, which provides evidence that APA treatment designed for CLBP can also improve sleepquality. In the literature, the causal relationship between sleep disturbance and pain intensity

remains unclear (Tang, Goodchild, Sanborn, Howard, & Salkovskis, 2012), but bidirectional

relationships appear to exist between pain intensity and sleep disturbance (Bernardy et al.,

2013; Lew et al., 2010), which suggests that any approach to pain management should take

sleep disturbance into consideration because it likely contributes to pain intensity.Auricular therapy has shown promising potential for treating insomnia (Suen, Wong, &

Leung, 2002; Suen, Wong, Leung, & Ip, 2003). In a study conducted in Hong Kong that

provided auricular therapy to older adults to help relieve insomnia, patients who received

a three-week APA treatment displayed a significant improvement in nocturnal sleep time

(F2:30;29:90 D 3:63, p < 0.05) and marginal improvements in sleep efficiency (F4;52 D 2:52,p D 0.05) at baseline, immediately after therapy, and in three follow-up measurements at

one, three, and six months (Suen et al., 2003). In addition to the self-reported data to assess

sleep quality, objective measures of sleep quality assessment can be included. For example,

polysomnography was used to examine the APA effects for 45 patients with sleep apnea

syndrome (Wang, Yuan, & Wang, 2003). Patients who received 10 days of APA displayed a

significantly reduced apnea-hypopnea index, apnea index, and hyponea index as well as an

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14 YEH ET AL.

increased blood oxygen saturation compared to a control group who took vitamin C (100 mg/3

times/daily, p < 0.001; Wang et al., 2003). Additionally, the ear acupuncture points selectedto treat insomnia included shenmen (often used in treating various conditions, including pain,

sedation, addiction treatment, and inflammation; Frank & Soliman, 1999), heart, kidney, liver,

spleen, occiput, and subcortex (Suen et al., 2003; Wang et al., 2003). Borrowing from these

results, a future APA treatment protocol should add the heart, kidney, liver, spleen, and occiput

points so that both CLBP and insomnia can be treated simultaneously in a clinical setting.

CONCLUSION

In our APA intervention for CLBP, almost all participants (i.e., 86%) with CLBP reported

sleep problems, which indicates that CLBP and sleep disturbance coexist. The trends in sleepimprovement displayed among our study’s participants suggest that sleep quality should be

considered as an important outcome in the management of CLBP. Moreover, ear acupuncture

points to treat sleep disturbances can be included in the APA treatment designed for CLBP to

increase the maximum treatment effects of APA in a future study.

ACKNOWLEDGMENTS

The authors wish to thank Brian Greene in the Center for Research and Evaluation at the

University of Pittsburgh, School of Nursing for editorial support.

FUNDING

This study was supported by a grant to Dr. Yeh from the Aging Institute of the University of

Pittsburgh Medical Center (UPMC), Senior Services, and the University of Pittsburgh.

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