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. Author manuscript; available in PMC: 2023 Feb 1.
Published in final edited form as: Chronobiol Int. 2021 Nov 3;39(2):221–232. doi: 10.1080/07420528.2021.1992419

Evaluating chronotypically tailored light therapy for breast cancer survivors: Preliminary findings on fatigue and disrupted sleep

Horng-Shiuann Wu a, F Gao b, L Yan c, C Given a
PMCID: PMC8792175  NIHMSID: NIHMS1751733  PMID: 34732099

Abstract

More than one third of cancer survivors experience significant residual symptoms after treatment completion. Fatigue and sleep disruption often co-occur and exacerbate each other. The purpose of this preliminary analysis was to examine the effect of a chronotypically-tailored light therapy on fatigue and sleep disruption in female survivors 1–3 years post-completion of chemotherapy and/or radiation for stage I to III breast cancer. The data for this analysis were collected as part of an on-going two-group randomized controlled trial (NCT03304587). Participants were randomized to receive either bright blue-green light (experimental) or dim red light (control). Light therapy was self-administered using a light visor cap at home. Both groups received 30-min daily light therapy for 14 consecutive days either between 19:00–20:00 h (for morning chronotypes) or within 30 min of waking in the morning (for evening chronotypes). Fatigue and sleep quality were self-reported using the Patient-Reported Outcomes Measurement Information System (PROMIS)-Fatigue, PROMIS-Sleep Disturbance, Pittsburgh Sleep Quality Index, and a daily log before (pre-test) and following the light intervention (post-test). Linear mixed model analysis or generalized estimating equations examined group difference overtime adjusting for pre-test scores. No between-group differences were found. However, after adjusting for the baseline fatigue, the experimental group reported significant decreases in fatigue (p<0.001) and sleep disturbance (p=0.024) overtime. The experimental group also reported significantly better subjective sleep quality after 14 d of light therapy (p=0.017). Positive trends in sleep latency, sleep duration, night-time awakenings, and early morning awakenings were also observed. Unexpectedly, sleep disturbance significantly decreased in the control group (p=0.030). Those who received dim light control reported significantly shorter sleep latency (p=0.002), longer total sleep time (p=0.042), and greater habitual sleep efficiency (p=0.042). These findings suggest that bright light therapy significantly improved post-treatment fatigue and subjective sleep quality in breast cancer survivors. Although it remains to be confirmed, the findings additionally show unexpected benefits of dim light on sleep. Properly timed light exposure may optimize the therapeutic effect and can be the key for successful light therapy. How the administration timing coupled with wavelengths (short vs. long) and intensity of light affecting fatigue and disrupted sleep requires further investigation.

Keywords: light therapy, chronotype, sleep quality, fatigue, cancer survivors

Introduction

Many cancer-related symptoms emerge or are amplified during cancer treatment and persist long after treatment terminates. More than one third of cancer survivors experience significant residual symptoms after treatment completion (Shi et al. 2011). Among those individuals, many report functional limitations and diminished quality of life (Hewitt et al. 2003; Costanzo et al. 2009; Romito et al. 2012; Weaver et al. 2012; Ekwueme et al. 2014). Fatigue and sleep disruption are common symptoms among post-treatment cancer survivors (Wu and Harden 2015). Existing studies show that between 40% and 57% of individuals who completed breast cancer treatment reported disrupted sleep (Janz et al. 2007; Romito et al. 2012; Cheng et al. 2014) and 14% to 83% experienced substantial fatigue (Fu et al. 2009; Andrykowski et al. 2010; Bellury et al. 2012; Berger et al. 2012; Goldstein et al. 2012; Romito et al. 2012; Ness et al. 2013; Cheng et al. 2014). Fatigue and sleep disruption often co-occur and exacerbate each other (Alfano et al. 2011; Berger et al. 2012; Goldstein et al. 2012; Romito et al. 2012; Goedendorp et al. 2013). Despite the debilitating nature of sleep disruption and fatigue, they often continue untreated due to limited treatment options.

Therapeutic bright light is known to be effective in alleviating fatigue and insomnia in non-cancerous conditions, such as seasonal affective disorder, shift work, and jet-lag (Petrie et al. 1989; Meesters and Lambers 1990; Eastman and Martin 1999; Rastad et al. 2011; Tanaka et al. 2011). Therapeutic bright light has also shown promise in curbing fatigue and preventing worsening of quality of life in women with breast cancer undergoing chemotherapy (Ancoli-Israel et al. 2012; Jeste et al. 2013). The therapeutic effect of bright light on cancer-related fatigue is further supported by studies of post-treatment breast or gynecologic cancer survivors (Redd et al. 2014; Johnson et al. 2018). However, in these studies, the effect of bright light on sleep disruption was modest and the mechanism of action by which it occurs remains to be established.

A recent study showed the potential of using bright light to improve disrupted sleep, especially the time to fall asleep, in women undergoing chemotherapy for breast cancer (Wu et al. 2021). Unlike previous studies in which bright light was uniformly delivered in the morning, the timing of the light administration in that study was individually tailored to participants’ chronotype (Wu et al. 2021). The circadian chronotype (known as morningness-eveningness) is an individual’s natural propensity for sleep/wake timing (Duffy et al. 1999; Adan et al. 2012; Jagannath et al. 2017) that stems from the period of endogenous circadian rhythms relative to the 24 h day/night cycle (circadian phase) (Lack et al. 2009). For instance, individuals with endogenous circadian period less than 24 h are likely to have a morningness chronotype. A morningness chronotype demonstrates an earlier diurnal alertness and sleep propensity rhythm (sleep/wake schedule), i.e., phase advanced from the 24 h day/night cycle. On the other hand, individuals with endogenous circadian period longer than 24 hours are likely to have an eveningness chronotype. An eveningness chronotype shows a later sleep/wake schedule, i.e., circadian phase delay (Duffy et al. 1999; Baehr et al. 2000).

It is known that disrupted sleep/wake cycles can be modulated by appropriately timed exposure to bright light, especially by using short wavelength (blue-green) light (Dijk et al. 1995; Terman et al. 1995; Gooley 2008). Coupled with the sufficient amount and duration of bright light, the time of the day of the light exposure determines how the biological clock is reset and therefore either consolidates or disrupts the individual’s sleep/wake cycle (Gooley 2008; Figueiro and Pedler 2020). It is known that light exposure in the morning elicits phase advance of the circadian rhythm, inducing sleep onset at an earlier time. Conversely, light exposure in the evening delays the circadian phase, suppressing sleep onset until a later time. We speculated that customizing the timing of light exposure to conform with differences in individuals’ diurnal preferences can avoid inducing changes in an unwanted direction and worsening already disrupted sleep/wake patterns. This article reports on preliminary findings of an on-going study aimed at examining the efficacy of a chronotypically-tailored light therapy on fatigue and subjective sleep quality in a sample of post-treatment breast cancer survivors. The following hypothesis guided this investigation: compared to the dim light controls, breast cancer survivors who received bright light will report significantly less fatigue and better sleep quality following the completion of 14 d of chronotypically-tailored light therapy.

Methods

Chronotypically Tailored Light Therapy

In this two-group randomized controlled trial (NCT03304587) with pre- and post-tests, participants were randomly assigned to receive either bright blue-green light (~500nm peak; 12,000 lux) (experimental group) or dim red light (~620nm peak; 5 lux) (control group) for 30 min once a day for 14 consecutive days. Light therapy was self-administered using a light visor cap (Physician Engineered Products, Fryeburg, ME) at the participant’s home. Both experimental and control groups followed the same study protocol.

The timing of the bright and dim light administration was prescribed according to the individual’s circadian chronotype. Based on the total score of the Horne-Ostberg Morningness-Eveningness Questionnaire (MEQ) (Horne and Ostberg 1976; Smith et al. 1989), participants who self-reported as evening types (MEQ score ≤ 41) applied the light within 30 min of waking in the morning. Participants who self-reported as morning types (MEQ score ≥ 59) applied the light between 1900–2000 h in the evening. Individuals who identified as intermediate circadian types (MEQ scores 42–58) were excluded. The two timepoints for the light administration were based on the evidence supporting that light exposure near the time (within 30 mins) of awakening alleviates difficulty in initiating sleep (Buysse et al. 2010; Lewy et al. 1985). Evening bright light exposure (between 2000 to 2400 h) effectively alleviates symptoms of insomniacs suffering from sleep maintenance problems or early morning awakenings (Lack and Wright 1993; Campbell et al. 1993). To minimize the possible alerting effect of light affecting subsequent sleep, the evening bright light was administered between 1900–2000 h.

Sample and Settings

Data collection took place at sites within the Greater Lansing area in Michigan and within the St. Louis bi-state metropolitan area in Missouri and Illinois. Eligible participants were females, 21 y of age or older, 1–3 y post-completion of chemotherapy and/or radiation therapy for stage I-III breast cancer, symptomatic (experiencing ≥ 2 concurrent symptoms of fatigue, sleep disruption, depressive symptoms, and/or cognitive dysfunction), with either morning or evening chronotypes (MEQ ≥59 or ≤41), and were sighted, mentally competent to consent, and able to understand English. Individuals were excluded if they exhibited any of the following: were undergoing cancer treatment for another malignancy; had metastatic cancer; engaged in shift work or traveled across more than three time zones within two weeks prior to the study; had current diagnosis of seasonal affective disorder, substance abuse, major Axis I psychiatric disorders, neurological impairments, or muscular dystrophies; reported severe depressive mood (Center for Epidemiological Studies Depression Scale score >24); took prescribed steroid or sedative hypnotics; had eye conditions (glaucoma or retinal disease) or problems triggered by bright light (e.g., migraine); or took photosensitizing medications (e.g., some porphyrin drugs, antipsychotics, antiarrhythmic agents). The study was approved by the Institutional Review Boards at Michigan State University in East Lansing, Michigan and Washington University in St. Louis, Missouri. The study protocol conformed to international ethical standards for human chronobiology research (Portaluppi et al. 2010).

Variables and Measures

Fatigue

In order to capture the trend with different time frame (within past seven days vs. 24 hours), fatigue was measured by the Patient-Reported Outcomes Measurement Information System (PROMIS)-Fatigue Short Form 8a (v1.0) (Garcia et al. 2007) and a single-item numeric rating scale. The PROMIS-Fatigue Short Form 8a consists of eight items with a five-point rating scale (1 = not at all or never, 5 = very much or always) measuring fatigue experience (frequency, duration, and intensity) and fatigue impact (physical, mental, and social activities) during the past seven days. Higher scores indicate greater fatigue. The PROMIS-Fatigue 8a was developed based on item response theory (Cella et al. 2007) and has been tested across chronic illnesses, including cancer (Garcia et al. 2007).

Fatigue was also measured by an 11-point rating scale, ranging from 0 (no fatigue) to 10 (worst fatigue) that asked individuals to indicate the average level of fatigue in the last 24 hours. Descriptive numeric rating scales have been used and proven efficient in measuring symptoms in patients with cancer and pose minimal burden (Richardson et al. 1978; Miaskowski et al. 2004; Wu et al. 2008).

Disrupted sleep patterns

Subjective sleep quality

To assess overall sleep quality as well as specific sleep parameters, over a period of time as well as daily, sleep quality was self-reported by the PROMIS-Sleep Disturbance Short Form 8a (v1.0), the Pittsburgh Sleep Quality Index (PSQI) (Buysse et al. 1989), and a daily sleep log.

The PROMIS- Sleep Disturbance Short Form 8a (v1.0) consists of eight items with five-point rating scales measuring overall sleep (1 = very good, 5 = very poor) and sleep-related impairments (1 = not at all, 5 = very much) during the past seven days. Higher scores indicate greater sleep disturbances. Validity was supported by moderate to high correlations with the existing scales, e.g., PSQI, Epworth Sleepiness Scale. The scores significantly differed among participants with and without sleep disorders (Buysse et al. 2010).

The PSQI contains 19 self-report items measuring seven sleep characteristics, including sleep quality, latency, duration, efficiency, disturbance, medication use, and daytime dysfunction, during the past month. The total global PSQI score ranges from 0–21; a higher score suggests worse sleep quality. The cut-off score of five was found to have a sensitivity of 89.6% and a specificity of 86.5% in differentiating good and poor sleepers (Buysse et al. 1989). In a sample of cancer patients, internal consistency reliability was α=0.81 for the global sleep quality score (Berger et al. 2005).

The daily sleep log contained three questions measuring sleep disturbance during the prior night including “I had difficulty falling asleep,” “I kept waking up during the night,” and “I woke up too early and couldn’t get back to sleep.” Each question was assessed using a five-point rating scale (1 = not at all to 5 = very much). A sleep diary is commonly used in sleep research (Buysse et al. 2006).

Procedure

Potential subjects were recruited via mail and email invitations using patient registries, referrals by oncologists or clinic nurses, and recruitment materials posted on social media and within public areas. Once an individual showed interest, the principal investigator (first author) or a research assistant contacted the person by telephone followed by an in-person meeting at a location convenient to the individual. Please see Figure 1 for the study flow chart.

Figure 1.

Figure 1.

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Study Flow Diagram

After giving informed consent, the individuals were screened for the eligibility criteria using a standardized checklist. During the screening, participants first completed the demographic information and then a battery of self-reported screening measures. After the screening interview, eligible participants were scheduled for subsequent study activities that included the baseline/pre-test data collection, the 14-day daily light therapy, and the post-test data collection.

During the baseline data collection, participants were instructed to complete a battery of self-reported instruments the day before starting the light therapy, including the PROMIS-Fatigue, PROMIS-Sleep Disturbance, PSQI, and the daily sleep log that contained one fatigue and three sleep questions. Throughout the 14-day light therapy period, the participants were instructed to record the time of the beginning and the end of each light treatment on a daily log. The post-test data collection took place on the day following the completion of 14-day light therapy. Each participant in the two groups was instructed to complete the same battery of self-reported instruments administered during the baseline data collection.

Data Analysis

The analyses were completed based on the intention-to-treat principle (i.e., all participants were analyzed based on their group assignment). The distributions of baseline demographic and clinical characteristics between experimental and control groups were compared using t-test, Mann-Whitney rank-sum test, Chi-square, or Fisher’s exact test as appropriate. The pre- and post-test endpoints of fatigue and sleep disruption in each group were summarized using mean, standard deviation (SD), median, and interquartile range for continuous outcomes or using counts and frequencies for ordinal outcomes. Linear mixed models (for continuous outcomes) or generalized estimating equations (GEE) with cumulative log link function (for ordinal outcomes) were fitted to examine between-group differences, while adjusting for correlation among repeated measures taken from the same participant. Three significance tests were performed simultaneously in each model, including pre-post change in the control group, pre-post change in the experimental group, and the difference in over-time changes between groups.

Data transformation was conducted as necessary for continuous variables to better satisfy assumptions of normality and homoscedasticity for mixed models. To inform future studies, treatment effects were also estimated in addition to the significance tests. For continuous outcomes, the effect size was calculated as Cohen’s d where the between-group difference was scaled by the corresponding standard deviation in the control group. For ordinal outcomes, the effect size was expressed as the cumulative odds ratio (OR) of 1-unit increase in outcomes. Since higher scores indicate worse fatigue or sleep disturbance, an OR<1 represented a beneficial treatment effect.

All data analyses were performed using SAS 9.4 (SAS Institutes. Cary, NC) and statistical significance was defined as a two-tailed p-value of <0.05 for all analyses.

Results

The data from a convenience sample of 21 female survivors of breast cancer were included in this analysis. Among those, 19 completed both pre- and post-tests with 11 in the experimental and eight in the control group. The mean age of the 21 women was 52.8 ± 9.0 y (ranged 35–72 y). The average time since last cancer treatment was 24.9 ± 10.1 months at the time of study enrollment. The majority were White/Caucasian (90.5%), had completed some college or more (90.5%), and had been treated for stage I or II breast cancer (85.7%). About three quarters (76.2%) of the women were morning type. Table 1 summarizes the demographics of the study participants. There were no significant differences in the demographic characteristics between the experimental and control groups, with the exception of tumor stages. Stage I cancer was significantly more prevalent among women in the control group than in the experimental group (88.9% vs. 41.7%, respectively; p = 0.039).

Table 1.

Characteristics of Participants (N = 21)

Experimental (n = 12) Control (n = 9)
Mean (SD) Number (valid %) Mean (SD) Number (valid %) Non-Parametric p-value
Age (years) 50.8 (±8.7) 55.6 (±9.1) .50
Race
 White 11 (92) 8 (89) 1.00
 Black 1 (8) 1 (11)
Education (years) 16 (±2.9) 16 (±1.7) .27
Marital Status
 Single 1 (8) 0 (0) .88
 Married/Partnered 8 (67) 5 (56)
 Divorced 3 (25) 3 (33)
 Widowed 0 (0) 1 (11)
Employment
 Full-time 7 (58) 4 (44) .59
 Part-time 1 (8) 1 (11)
 Self-employed 3 (25) 1 (11)
 Retired 1 (8) 3 (33)
Living Arrangement
 Live alone 1 (8) 0 (0) 1.0
 Live with others 11 (92) 9 (100)
Tumor Stage
 Stage I 5 (42) 8 (89) .04
 Stage II 5 (42) 0 (0)
 Stage III 2 (16) 1 (11)
Previous Treatment
 Chemotherapy 1 (8) 1 (11) .66
 Radiation 7 (58) 7 (78)
 Both 4 (33) 1 (11)
Numbers of Co-morbidities
 0 5 (42) 4 (44) .91
 1 5 (42) 3 (33)
 2 2 (16) 1 (11)
 4 0 1 (11)
Chronotype
 Eveningness 3 (25) 2 (22) 1.0
 Morningness 9 (75) 7 (78)
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Among those who completed the study, the experimental group (n=11) completed a total of 138 intervention sessions (mean=12.6±3.1 sessions; 154 possible sessions) and the control group (n=8) completed a total of 108 sessions (mean=13.5±1.2 sessions; 112 possible sessions). All participants except one completed 11–14 intervention sessions; one participant in the experimental group only completed four intervention sessions due to headaches exaggerated by light.

Fatigue

The PROMIS-Fatigue Short Form 8a was scored using item-level calibrations by the HealthMeasures Scoring Service (HealthMeasures 2020). The PROMIS-Fatigue measure was scored on a T-score metric with mean = 50 and standard deviation (SD) = 10 (HealthMeasures 2019). A higher PROMIS T-score represented more severe fatigue.

After adjusting for the baseline fatigue, fatigue severity significantly decreased in the experimental group after 14 d of light therapy. Levels of fatigue reported by the participants who received bright light were significantly lower, on average, by 8.1 points at the post-test than at pre-test (p<0.001). Levels of fatigue reported by the participants who received dim light were also lower by 5.1 points at the post-test but the decreases were only marginally significant (p=0.051). Please see Table 2 for the observed treatment effects. Although the experimental group showed larger decreases in fatigue severity, the overtime changes did not differ by group (p=0.200). It is worth noting that after the 14-day light therapy, levels of fatigue reported by experimental and control groups were both below the general population mean of 50.0 (median=48.1 and median= 46.4, respectively).

Table 2.

Observed Treatment Effects (Pre-Post Changes) and Effect Size for Continuous Outcomes (N=21)

Observed Treatment Effects Effect Size P-values
Mean Median Lower Quartile Upper Quartile Cohen’s d Within-group Between-group
PROMIS-Fatigue T: −8.05
C: −5.12		 T: −5.60
C: −6.15		 T: −14.30
C: −10.80		 T: −4.50
C: −0.20		 0.37 <0.001
0.051		 0.198
PROMIS-Sleep Disturbance T: −7.12
C: −7.29		 T: −5.20
C: −5.60		 T: −14.90
C: −10.40		 T: −0.10
C: 0.30		 0.02 0.024
0.030		 0.860
Global PSQI Score T: −1.36
C: −4.13		 T: −2.00
C: −3.50		 T: −3.00
C: −7.50		 T: 0.00
C: −1.00		 0.75 0.178
0.004		 0.120
Sleep Efficiency (%) T: 0.02
C: 0.05		 T: 0.04
C: 0.05		 T: −0.04
C: −0.05		 T: 0.10
C: 0.14		 0.18 0.580
0.138		 0.426
Sleep Latency (min) T: −3.64
C: −17.75		 T: 0.00
C: −15.00		 T: −10.00
C: −30.00		 T: 0.00
C: −5.00		 0.65 0.407
0.002		 0.034
Total Sleep Time (h) T: 0.00
C: 0.69		 T: 0.00
C: 0.75		 T: −1.00
C: −0.25		 T: 1.00
C: 1.50		 0.59 0.989
0.042		 0.115
Daily Fatigue T: −1.60
C: −1.38		 T: −1.00
C: −1.00		 T: −5.00
C: −2.00		 T: −0.50
C: 1.00		 0.16 0.030
0.112		 0.764
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Annotations: T=treatment group; C=control

Note. Changes were calculated as post-test values minus pre-test values

The analysis of the single item daily fatigue measure shows similar findings. On the 0–10 rating scale, the participants who received bright light reported a significant improvement in fatigue levels, from median of 4.0 at pre-test to median of 1.5 at post-test (p=0.030). The participants who received dim light also reported decreases in fatigue levels, but the changes were not statistically significant (median of 3.5 at pre-test vs. median of 1.5 at post-test, p=0.112).

Subjective Sleep Quality

PROMIS-Sleep Disturbance.

The PROMIS-Sleep Disturbance Short Form 8a was scored using item-level calibrations by the HealthMeasures Scoring Service (HealthMeasures 2020). The PROMIS-Sleep Disturbance 8a was scored on a T-score metric with mean = 50 and standard deviation (SD) = 10 (HealthMeasures 2019). A higher PROMIS T-score represented more disrupted sleep.

After adjusting for the baseline value, sleep disturbance significantly decreased in not only the experimental but also the control group after 14 d of light therapy. Levels of sleep disturbance reported by the participants who received bright light were significantly lower, on average, by 7.1 points at the post-test than at pre-test (p=0.024). Unexpectedly, levels of sleep disturbance reported by the participants who received dim light were also significantly lower by 7.3 points (p=0.030). The observed treatment effects were compatible between the experimental and control groups (p= 0.860). Please see Table 2 for the observed treatment effects.

Pittsburgh Sleep Quality Index (PSQI).

The analyses of PSQI data were in favor of dim light, which is unexpected. Although positive changes were observed among the participants who received bright light, most improvement was non-significant, except for subjective sleep quality. The analysis of seven PSQI components showed that subjective sleep quality significantly improved among the participants who received bright light (p=0.017) (see Table 3). Although the time it takes to fall asleep (sleep latency) slightly shortened in the experimental group, the change was trivial (median of 25 mins at pre-test vs. median of 20 mins at post-test, p=0.407). Similarly, those who received bright light reported better global sleep quality (sum of seven component scores) overtime, but the change was not statistically significant (global PSQI median score of 10 at pre-test vs. 8 at post-test, p=0.178).

Table 3.

Treatment Effects (Pre-Post Changes) and Effect Size for Ordinal Outcomes (N=21)

95% CI P-values
Mean* OR** Lower Upper Within-group Between-group
PSQI Components:
Subjective sleep quality T: −0.36
C: −0.50		 T: 0.240
C: 0.157		 T: 0.074
C: 0.014		 T: 0.778
C: 1.779		 0.017
0.135		 0.764
Sleep latency T: −0.45
C: −1.13		 T: 0.300
C: 0.066		 T: 0.089
C: 0.012		 T: 1.008
C: 0.367		 0.052
0.003		 0.136
Sleep duration T: 0.00
C: −0.63		 T: 1.021
C: 0.177		 T: 0.374
C: 0.063		 T: 2.786
C: 0.503		 0.967
0.001		 0.016
Habitual sleep efficiency T: −0.09
C: −0.50		 T: 0.851
C: 0.363		 T: 0.483
C: 0.136		 T: 1.500
C: 0.966		 0.576
0.042		 0.143
Sleep disturbances T: −0.09
C: −0.63		 T: 0.520
C: 0.178		 T: 0.148
C: 0.023		 T: 1.823
C: 1.367		 0.307
0.097		 0.350
Use of sleeping medication T: −0.09
C: −0.50		 T: 0.545
C: 0.473		 T: 0.246
C: 0.181		 T: 1.205
C: 1.241		 0.134
0.128		 0.828
Daytime dysfunction T: −0.27
C: −0.25		 T: 0.566
C: 0.415		 T: 0.201
C: 0.111		 T: 1.595
C: 1.548		 0.282
0.191		 0.704
Sleep Log:
Difficulty falling asleep T: −0.82
C: −1.00		 T: 0.882
C: 0.134		 T: 0.313
C: 0.023		 T: 2.487
C: 0.766		 0.812
0.024		 0.067
Nighttime awakening T: −0.55
C: −1.25		 T: 0.729
C: 0.470		 T: 0.148
C: 0.126		 T: 3.589
C: 1.755		 0.697
0.261		 0.686
Wake up too early T: −1.18
C: −1.25		 T: 0.237
C: 0.527		 T: 0.053
C: 0.074		 T: 1.066
C: 3.738		 0.061
0.522		 0.527
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Annotations: T=treatment group; C=control

Note.

*

Average of over-time changes, calculated as post-test values minus pre-test values

**

Cumulative odds ratio (OR) for 1-unit increase in the ordinal outcome

Unexpectedly, the control group demonstrated significant and beneficial changes in several sleep parameters. For example, global sleep quality (global PSQI score) reported by the participants who received dim light significantly improved by 4.1 points overtime (p=0.004) (see Table 2). A significant improvement was also demonstrated among three PSQI components, including sleep latency (p=0.002), sleep duration (p=0.001), and habitual sleep efficiency (p=0.042) (see Table 3). Participants who received dim light control reported significantly shorter sleep latency, from median of 45 mins at pre-test to median of 20 mins at post-test (p=0.002).

There was a significant interaction between group (experimental vs. control) and time (pre- and post-test) for sleep duration (P=0.024). Sleep duration lengthened in both groups after the completion of the 14-day light therapy, but the control group demonstrated a greater overtime change (p=0.016). The participants who received dim light reported more than an hour increases in total sleep time, from median of 6.00 hrs at pre-test to median of 7.25 hrs at post-test (p=0.042).

Sleep Diary.

The analysis of the sleep log revealed that both experimental and control groups experienced improvement in difficulty falling asleep, night-time awakenings, and early morning awakenings after the completion of the 14-day light therapy (see Table 3). However, only those who received dim light reported significant decreases in difficulty falling asleep (p=0.024). This finding is consistent with the findings of PSQI in which numeric value of sleep latency (in mins) was reported.

Discussion

Despite the small sample size, the women who received bright light reported significant decline in fatigue severity and sleep disturbance (based on the analysis of the PROMIS measures) and subjective sleep quality (based on the analysis of PSQI) after adjusting for their baseline levels. Positive trends were also observed in sleep latency, total sleep time, and global sleep quality. Although this preliminary analysis supports the potential of using bright blue-green light in managing post-treatment sleep disturbance and fatigue among breast cancer survivors, some findings revealed unexpected effects of dim red light on sleep.

In contrast to our hypothesis, global sleep quality alone with other sleep parameters, including sleep latency, sleep duration, and habitual sleep efficiency, were significantly improved among the women who received dim red light. Although those findings were unexpected, some effect sizes were relatively large and therefore not negligible. For example, a large effect size of d=0.75 for global sleep quality is substantial (Cohen 1998; Sawilowsky 2009). The effect size of d=0.65 for the time it takes to fall asleep (sleep latency) was also noticeable. Compared to the time it took to fall asleep at baseline (45 min), it took those participants only half of the time to fall asleep (20 min) after the 14-day light therapy. In addition to taking less time to fall asleep, those who received dim red light reported gaining about 75 min (1.25 h) of sleep at night. Once again, a large effect size of d=0.59 for sleep duration was observed. Moreover, although the improvement in fatigue severity among the control group was marginal, the post-intervention fatigue level fell below the upper limit of the norm in general population (HealthMeasures 2021), indicating a desirable relief after using dim red light. These improvements were unexpected as dim red light in this study was intended to overcome placebo effects for those who were in the control group.

Dim red light is commonly used as the control in studies involving bright light therapy (Golden et al. 2005; Redd et al. 2014). It is thought that intrinsically photosensitive retinal ganglion cells (ipRGCs) are insensitive to long wavelength (red) light (Lockley et al. 2003; Newman et al. 2003; Brainard et al. 2008). For this reason, animal studies involving nocturnal behaviour experiments are usually performed under the red-light environment. However, unexpected findings demonstrating that red light affects sleep/wake behavior have also been reported in animal studies. The exposure to red light (≥20 lux) during the dark cycle was found to significantly increase rapid eye movement (REM) and non-REM sleep in mice (Zhang et al. 2017). Another study reported that 2-week long night-time exposure to dim red light (>620 nm, 8.1 lux) disrupted circadian rhythms in Sprague-Dawley rats (Dauchy et al. 2015).

The effect of night-time long wavelength (red) light exposure on sleep/wake patterns and melatonin secretion in humans is inconclusive. Red light was found to positively affect sleep quality, especially in sleep duration and sleep latency in a group of female athletes (Zhao et al. 2012). In that study, increased serum melatonin level was observed after receiving 30 mins of whole-body red-light irradiation every night for 14 days and was inferred as the contributor to the improved sleep quality (Zhao et al. 2012). Although the study used a different method of delivery, the administration timing of red light and the observed effects on sleep were similar to this study. Other studies have showed that red light exposures at night promoted nocturnal alertness in adults (Figueiro et al. 2009; Figueiro and Pedler 2020). In those studies, red light (λmax=630 nm) exerted similar effects on alertness as blue light (λmax=470 nm) (Figueiro et al. 2009; Figueiro and Pedler 2020). However, unlike blue light, red light did not affect melatonin levels (Figueiro et al. 2009; Figueiro and Rea 2010; Figueiro and Pedler 2020).

Although it is plausible that red light contributed to the observed beneficial effects in this study, alternative explanations were explored. First, it is possible that the observed effects from the control group were the result of light leak from the red-tinted visor. Some animal studies show that even a small light leak (as little as 0.2 lux) has the potential to elicit a circadian rhythm disruption (Dauchy et al. 1999; Dauchy et al. 2010; Dauchy et al. 2011; Dauchy et al. 2013; Wren et al. 2014). Second, the seemingly beneficial effects observed in the dim red light controls could be due to diminished exposure or darkness. The visor caps likely blocked the light from other sources reaching to the eyes of participants. A dark pulse has been shown to regulate circadian rhythms and sleep in human subjects (Van Cauter et al. 1998; Buxton et al. 2000; Burgess et al. 2002; Duffy and Czeisler 2009).

The small sample size is a major limitation. Since the study participants all resided at home, they were exposed to other light sources which could affect the outcomes. Also, there were more women in the control group with Stage I cancer. Another major weakness is the limited generalizability. Because the samples were selected based on the strict criteria such as being female, presenting multiple pre-selected symptoms, either morning or evening chronotypes etc., the findings may not be applicable to males, with other symptoms, and/or neither chronotypes. The women in our sample were all post-menopausal. Sleep disturbance is a common symptom in estrogen deficient women and therefore it is difficult to rule out the effect of cancer and/or cancer treatment. Future studies comparing female breast cancer survivors and healthy post-menopausal women can further the understanding of disrupted sleep patterns in breast cancer. In addition, the participants completed PSQI at the post-test. As the PSQI measures subject sleep quality during the past month, the assessment may not be sensitive in reflecting the changes immediately following the 14 d of light treatment. A daily sleep measure can better capture the fluctuation and, therefore, is recommended for future studies.

Furthermore, although the light administration timing in this study was tailored to the individuals’ chronotypes, 78% of the participants in the control group were morning chronotypes and were therefore exposed to red light in the evening. Although it is conceivable that the timing of light administration coupled with the wavelength enhanced the effects, the explanation of the observed effect of dim light conditions remains open and in need of further research. Examining the effect of the light treatment based on chronotypes is underway. The interaction between administration timing and the wavelength, as well as the optimal intensity of the light, demands further study.

Together, these preliminary findings provide some evidence to support bright light as a promising non-pharmacological intervention for fatigue and disrupted sleep in post-treatment breast cancer survivors. Unlike previous studies, chronotypically tailored bright light therapy demonstrated the beneficial effects on not only fatigue but also sleep. Unexpectedly, we found that the participants in the control group benefited even more from the dim red light. The unexpected findings remain unexplained, but nonetheless indicate the potential of using long wavelength (red) light as an alternative option to blue light. If used at the proper time, even with lower intensity, light may promote advantageous changes in sleep/wake patterns. These results suggest the importance of individualizing the administration of light therapy. Properly timed light exposure may optimize the therapeutic effects. In sum, tailoring light administration timing based on individuals’ differences has been overlooked but could be crucial for the efficacy of light therapy on managing fatigue and sleep disruption in post-treatment breast cancer survivors.

Funding details:

This study was supported by NIH NINR under Grant #R15NR016828

Footnotes

Disclosure statement.

The authors report no conflict of interest.

References

  1. Adan A, Archer SN, Hidalgo MP, Di Milia L, Natale V, Randler C. 2012. Circadian typology: a comprehensive review. Chronobiol Int. 29(9):1153–1175 doi: 10.3109/07420528.2012.719971 [DOI] [PubMed] [Google Scholar]
  2. Alfano CM, Lichstein KL, Vander Wal GS, Smith AW, Reeve BB, McTiernan A, Bernstein L, Baumgartner KB, Ballard-Barbash R. 2011. Sleep duration change across breast cancer survivorship: associations with symptoms and health-related quality of life. Breast Cancer Res Treat. 130(1):243–254 doi: 10.1007/s10549-011-1530-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Ancoli-Israel S, Rissling M, Neikrug A, Trofimenko V, Natarajan L, Parker BA, Lawton S, Desan P, Liu L. 2012. Light treatment prevents fatigue in women undergoing chemotherapy for breast cancer. Support Care Cancer. 20(6):1211–1219 doi: 10.1007/s00520-011-1203-z [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Andrykowski MA, Donovan KA, Laronga C, Jacobsen PB. 2010. Prevalence, predictors, and characteristics of off-treatment fatigue in breast cancer survivors. Cancer. 116(24):5740–5748 doi: 10.1002/cncr.25294 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Baehr EK, Revelle W, Eastman CI. 2000. Individual differences in the phase and amplitude of the human circadian temperature rhythm: with an emphasis on morningness-eveningness. J Sleep Res. 9(2):117–127 doi: 10.1046/j.1365-2869.2000.00196.x [DOI] [PubMed] [Google Scholar]
  6. Bellury L, Pett MA, Ellington L, Beck SL, Clark JC, Stein KD. 2012. The effect of aging and cancer on the symptom experience and physical function of elderly breast cancer survivors. Cancer. 118(24):6171–6178 doi: 10.1002/cncr.27656 [DOI] [PubMed] [Google Scholar]
  7. Berger AM, Parker KP, Young-McCaughan S, Mallory GA, Barsevick AM, Beck SL, Carpenter JS, Carter PA, Farr LA, Hinds PS et al. 2005. Sleep wake disturbances in people with cancer and their caregivers: state of the science. Oncol Nurs Forum. 32(6):E98–126 doi: 10.1188/04.ONF.E98-E126 [DOI] [PubMed] [Google Scholar]
  8. Berger AM, Visovsky C, Hertzog M, Holtz S, Loberiza FR. 2012. Usual and worst symptom severity and interference with function in breast cancer survivors. J Support Oncol. 10(3):112–118 doi: 10.1016/j.suponc.2011.11.001 [DOI] [PubMed] [Google Scholar]
  9. Brainard GC, Sliney D, Hanifin JP, Glickman G, Byrne B, Greeson JM, Jasser S, Gerner E, Rollag MD. 2008. Sensitivity of the human circadian system to short-wavelength (420-nm) light. J Biol Rhythms. 23(5):379–386 doi: 10.1177/0748730408323089 [DOI] [PubMed] [Google Scholar]
  10. Burgess HJ, Sharkey KM, Eastman CI. 2002. Bright light, dark and melatonin can promote circadian adaptation in night shift workers. Sleep medicine reviews. 6(5):407–420 [PubMed] [Google Scholar]
  11. Buxton OM, L’Hermite-Balériaux M, Turek FW, van Cauter E. 2000. Daytime naps in darkness phase shift the human circadian rhythms of melatonin and thyrotropin secretion. American journal of physiology Regulatory, integrative and comparative physiology. 278(2):R373–382 doi: 10.1152/ajpregu.2000.278.2.R373 [DOI] [PubMed] [Google Scholar]
  12. Buysse DJ, Ancoli-Israel S, Edinger JD, Lichstein KL, Morin CM. 2006. Recommendations for a standard research assessment of insomnia. Sleep. 29(9):1155–1173 doi: 10.1093/sleep/29.9.1155 [DOI] [PubMed] [Google Scholar]
  13. Buysse DJ, Reynolds CF 3rd, Monk TH, Berman SR, Kupfer DJ. 1989. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 28(2):193–213 doi: 10.1016/0165-1781(89)90047-4 [DOI] [PubMed] [Google Scholar]
  14. Buysse DJ, Yu L, Moul DE, Germain A, Stover A, Dodds NE, Johnston KL, Shablesky-Cade MA, Pilkonis PA. 2010. Development and validation of patient-reported outcome measures for sleep disturbance and sleep-related impairments. Sleep. 33(6):781–792 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Campbell SS, Dawson D, Anderson MW. 1993. Alleviation of sleep maintenance insomnia with timed exposure to bright light. J Am Geriatr Soc. 41(8): 829–836 doi: 10.1111/j.1532-5415.1993.tb06179.x [DOI] [PubMed] [Google Scholar]
  16. Cella D, Yount S, Rothrock N, Gershon R, Cook K, Reeve B, Ader D, Fries JF, Bruce B, Rose M et al. 2007. The Patient-Reported Outcomes Measurement Information System (PROMIS): progress of an NIH Roadmap cooperative group during its first two years. Med Care. 45(5 Suppl 1):S3–S11 doi: 10.1097/01.mlr.0000258615.42478.55 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Cheng KK, Darshini Devi R, Wong WH, Koh C. 2014. Perceived symptoms and the supportive care needs of breast cancer survivors six months to five years post-treatment period. Eur J Oncol Nurs. 18(1):3–9 doi: 10.1016/j.ejon.2013.10.005 [DOI] [PubMed] [Google Scholar]
  18. Cohen. 1998. Statistical power analysis for the behavioral sciences. Hillsdale NJ: Lawrence Erlbaum Associates. [Google Scholar]
  19. Costanzo ES, Ryff CD, Singer BH. 2009. Psychosocial adjustment among cancer survivors: findings from a national survey of health and well-being. Health Psychol. 28(2):147–156 doi: 10.1037/a0013221 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Dauchy RT, Blask DE, Sauer LA, Brainard GC, Krause JA. 1999. Dim light during darkness stimulates tumor progression by enhancing tumor fatty acid uptake and metabolism. Cancer Lett. 144(2):131–136 doi: 10.1016/s0304-3835(99)00207-4 [DOI] [PubMed] [Google Scholar]
  21. Dauchy RT, Dauchy EM, Hanifin JP, Gauthreaux SL, Mao L, Belancio VP, Ooms TG, Dupepe LM, Jablonski MR, Warfield B et al. 2013. Effects of spectral transmittance through standard laboratory cages on circadian metabolism and physiology in nude rats. J Am Assoc Lab Anim Sci. 52(2):146–156 [PMC free article] [PubMed] [Google Scholar]
  22. Dauchy RT, Dauchy EM, Tirrell RP, Hill CR, Davidson LK, Greene MW, Tirrell PC, Wu J, Sauer LA, Blask DE. 2010. Dark-phase light contamination disrupts circadian rhythms in plasma measures of endocrine physiology and metabolism in rats. Comp Med. 60(5):348–356 [PMC free article] [PubMed] [Google Scholar]
  23. Dauchy RT, Dupepe LM, Ooms TG, Dauchy EM, Hill CR, Mao L, Belancio VP, Slakey LM, Hill SM, Blask DE. 2011. Eliminating animal facility light-at-night contamination and its effect on circadian regulation of rodent physiology, tumor growth, and metabolism: a challenge in the relocation of a cancer research laboratory. J Am Assoc Lab Anim Sci. 50(3):326–336 [PMC free article] [PubMed] [Google Scholar]
  24. Dauchy RT, Wren MA, Dauchy EM, Hoffman AE, Hanifin JP, Warfield B, Jablonski MR, Brainard GC, Hill SM, Mao L et al. 2015. The influence of red light exposure at night on circadian metabolism and physiology in Sprague-Dawley rats. J Am Assoc Lab Anim Sci. 54(1):40–50 [PMC free article] [PubMed] [Google Scholar]
  25. Dijk DJ, Boulos Z, Eastman CI, Lewy AJ, Campbell SS, Terman M. 1995. Light treatment for sleep disorders: consensus report. II. Basic properties of circadian physiology and sleep regulation. J Biol Rhythms. 10(2):113–125 [DOI] [PubMed] [Google Scholar]
  26. Duffy JF, Czeisler CA. 2009. Effect of Light on Human Circadian Physiology. Sleep medicine clinics. 4(2):165–177 doi: 10.1016/j.jsmc.2009.01.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Duffy JF, Dijk DJ, Hall EF, Czeisler CA. 1999. Relationship of endogenous circadian melatonin and temperature rhythms to self-reported preference for morning or evening activity in young and older people. J Investig Med. 47(3):141–150 [PMC free article] [PubMed] [Google Scholar]
  28. Eastman CI, Martin SK. 1999. How to use light and dark to produce circadian adaptation to night shift work. Ann Med. 31(2):87–98 [DOI] [PubMed] [Google Scholar]
  29. Ekwueme DU, Yabroff KR, Guy GP Jr., Banegas MP, de Moor JS, Li C, Han X, Zheng Z, Soni A, Davidoff A et al. 2014. Medical costs and productivity losses of cancer survivors--United States, 2008–2011. MMWR Morb Mortal Wkly Rep. 63(23):505–510 [PMC free article] [PubMed] [Google Scholar]
  30. Figueiro MG, Bierman A, Plitnick B, Rea MS. 2009. Preliminary evidence that both blue and red light can induce alertness at night. BMC Neurosci. 10:105 doi: 10.1186/1471-2202-10-105 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Figueiro MG, Pedler D. 2020. Red light: A novel, non-pharmacological intervention to promote alertness in shift workers. J Safety Res. 74:169–177 doi: 10.1016/j.jsr.2020.06.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Figueiro MG, Rea MS. 2010. The effects of red and blue lights on circadian variations in cortisol, alpha amylase, and melatonin. Int J Endocrinol. 2010:829351 doi: 10.1155/2010/829351 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Fu OS, Crew KD, Jacobson JS, Greenlee H, Yu G, Campbell J, Ortiz Y, Hershman DL. 2009. Ethnicity and persistent symptom burden in breast cancer survivors. J Cancer Surviv. 3(4):241–250 doi: 10.1007/s11764-009-0100-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Garcia SF, Cella D, Clauser SB, Flynn KE, Lad T, Lai JS, Reeve BB, Smith AW, Stone AA, Weinfurt K. 2007. Standardizing patient-reported outcomes assessment in cancer clinical trials: a patient-reported outcomes measurement information system initiative. J Clin Oncol. 25(32):5106–5112 doi: 10.1200/JCO.2007.12.2341 [DOI] [PubMed] [Google Scholar]
  35. Goedendorp MM, Gielissen MF, Verhagen CA, Bleijenberg G. 2013. Development of fatigue in cancer survivors: a prospective follow-up study from diagnosis into the year after treatment. J Pain Symptom Manage. 45(2):213–222 doi: 10.1016/j.jpainsymman.2012.02.009 [DOI] [PubMed] [Google Scholar]
  36. Golden RN, Gaynes BN, Ekstrom RD, Hamer RM, Jacobsen FM, Suppes T, Wisner KL, Nemeroff CB. 2005. The efficacy of light therapy in the treatment of mood disorders: a review and meta-analysis of the evidence. Am J Psychiatry. 162(4):656–662 doi: 10.1176/appi.ajp.162.4.656 [DOI] [PubMed] [Google Scholar]
  37. Goldstein D, Bennett BK, Webber K, Boyle F, de Souza PL, Wilcken NR, Scott EM, Toppler R, Murie P, O’Malley L et al. 2012. Cancer-related fatigue in women with breast cancer: outcomes of a 5-year prospective cohort study. J Clin Oncol. 30(15):1805–1812 doi: 10.1200/JCO.2011.34.6148 [DOI] [PubMed] [Google Scholar]
  38. Gooley JJ. 2008. Treatment of circadian rhythm sleep disorders with light. Ann Acad Med Singapore. 37(8):669–676 [PubMed] [Google Scholar]
  39. HealthMeasures. 2020. HealthMeasures Scoring Service powered by Assessment Center; [accessed 2021 September 16]. https://www.assessmentcenter.net/ac_scoringservice.
  40. HealthMeasures. 2021. PROMIS® Score Cut Points. [accessed 2021 September 16]. https://www.healthmeasures.net/score-and-interpret/interpret-scores/promis/promis-score-cut-points.
  41. HealthMeasures. 2019. PROMIS fatigue scoring manual. [accessed 2021 September 16]. http://www.healthmeasures.net/images/PROMIS/manuals/PROMIS_Fatigue_Scoring_Manual.pdf.
  42. Hewitt M, Rowland JH, Yancik R. 2003. Cancer survivors in the United States: age, health, and disability. J Gerontol A Biol Sci Med Sci. 58(1):82–91 doi: 10.1093/gerona/58.1.m82 [DOI] [PubMed] [Google Scholar]
  43. Horne JA, Ostberg O. 1976. A self-assessment questionnaire to determine morningness-eveningness in human circadian rhythms. Int J Chronobiol. 4(2):97–110 [PubMed] [Google Scholar]
  44. Jagannath A, Taylor L, Wakaf Z, Vasudevan SR, Foster RG. 2017. The genetics of circadian rhythms, sleep and health. Hum Mol Genet. 26(R2):R128–R138 doi: 10.1093/hmg/ddx240 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Janz NK, Mujahid M, Chung LK, Lantz PM, Hawley ST, Morrow M, Schwartz K, Katz SJ. 2007. Symptom experience and quality of life of women following breast cancer treatment. J Womens Health. 16(9):1348–1361 doi: 10.1089/jwh.2006.0255 [DOI] [PubMed] [Google Scholar]
  46. Jeste N, Liu L, Rissling M, Trofimenko V, Natarajan L, Parker BA, Ancoli-Israel S. 2013. Prevention of quality-of-life deterioration with light therapy is associated with changes in fatigue in women with breast cancer undergoing chemotherapy. Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation. 22(6):1239–1244 doi: 10.1007/s11136-012-0243-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Johnson JA, Garland SN, Carlson LE, Savard J, Simpson JSA, Ancoli-Israel S, Campbell TS. 2018. Bright light therapy improves cancer-related fatigue in cancer survivors: a randomized controlled trial. J Cancer Surviv. 12(2):206–215 doi: 10.1007/s11764-017-0659-3 [DOI] [PubMed] [Google Scholar]
  48. Lack L, Bailey M, Lovato N, Wright H. 2009. Chronotype differences in circadian rhythms of temperature, melatonin, and sleepiness as measured in a modified constant routine protocol. Nat Sci Sleep. 1:1–8 doi: 10.2147/nss.s6234 [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Lack L, Wright H. 1993. The effect of evening bright light in delaying the circadian rhythms and lengthening the sleep of early morning awakening insomniacs. Sleep. 16(5): 436–443 doi: 10.1093/sleep/16.5.436 [DOI] [PubMed] [Google Scholar]
  50. Lewy AJ, Sack RL, Singer CM. 1985. Treating phase typed chronobiologic sleep and mood disorders using appropriately timed bright artificial light. Psychopharmcol Bull. 21(3): 368–372. [PubMed] [Google Scholar]
  51. Lockley SW, Brainard GC, Czeisler CA. 2003. High sensitivity of the human circadian melatonin rhythm to resetting by short wavelength light. J Clin Endocrinol Metab. 88(9):4502–4505 doi: 10.1210/jc.2003-030570 [DOI] [PubMed] [Google Scholar]
  52. Meesters Y, Lambers PA. 1990. Light therapy in patient with seasonal fatigue. Lancet. 336(8717):745. [DOI] [PubMed] [Google Scholar]
  53. Miaskowski C, Dodd M, West C, Schumacher K, Paul SM, Tripathy D, Koo P. 2004. Randomized clinical trial of the effectiveness of a self-care intervention to improve cancer pain management. J Clin Oncol. 22(9):1713–1720 doi: 10.1200/JCO.2004.06.140 [DOI] [PubMed] [Google Scholar]
  54. Ness S, Kokal J, Fee-Schroeder K, Novotny P, Satele D, Barton D. 2013. Concerns across the survivorship trajectory: results from a survey of cancer survivors. Oncol Nurs Forum. 40(1):35–42 doi: 10.1188/13.ONF.35-42 [DOI] [PubMed] [Google Scholar]
  55. Newman LA, Walker MT, Brown RL, Cronin TW, Robinson PR. 2003. Melanopsin forms a functional short-wavelength photopigment. Biochemistry. 42(44):12734–12738 doi: 10.1021/bi035418z [DOI] [PubMed] [Google Scholar]
  56. Petrie K, Conaglen JV, Thompson L, Chamberlain K. 1989. Effect of melatonin on jet lag after long haul flights. BMJ. 298(6675):705–707 [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Portaluppi F, Smolensky MH, Touitou Y. 2010. Ethics and methods for biological rhythm research on animals and human beings. Chronobiol Int. 27(9–10):1911–1929 doi: 10.3109/07420528.2010.516381 [DOI] [PubMed] [Google Scholar]
  58. Rastad C, Ulfberg J, Lindberg P. 2011. Improvement in Fatigue, Sleepiness, and Health-Related Quality of Life with Bright Light Treatment in Persons with Seasonal Affective Disorder and Subsyndromal SAD. Depress Res Treat. 2011:543906 doi: 10.1155/2011/543906 [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Redd WH, Valdimarsdottir H, Wu LM, Winkel G, Byrne EE, Beltre MA, Liebman ES, Erazo T, Hayes JA, Isola L et al. 2014. Systematic light exposure in the treatment of cancer-related fatigue: a preliminary study. Psycho-oncology. 23(12):1431–1434 doi: 10.1002/pon.3553 [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Richardson GS, Carskadon MA, Flagg W, Van den Hoed J, Dement WC, Mitler MM. 1978. Excessive daytime sleepiness in man: multiple sleep latency measurement in narcoleptic and control subjects. Electroencephalography and clinical neurophysiology. 45(5):621–627 [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Romito F, Cormio C, Giotta F, Colucci G, Mattioli V. 2012. Quality of life, fatigue and depression in Italian long-term breast cancer survivors. Support Care Cancer. 20(11):2941–2948 doi: 10.1007/s00520-012-1424-9 [DOI] [PubMed] [Google Scholar]
  62. Sawilowsky. 2009. New Effect Size Rules of Thumb. J Mod Appl Stat Meth. 8(2):597–599 doi: 10.22237/jmasm/1257035100 [DOI] [Google Scholar]
  63. Shi Q, Smith TG, Michonski JD, Stein KD, Kaw C, Cleeland CS. 2011. Symptom burden in cancer survivors 1 year after diagnosis: a report from the American Cancer Society’s Studies of Cancer Survivors. Cancer. 117(12):2779–2790 doi: 10.1002/cncr.26146 [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Smith CS, Reilly C, Midkiff K. 1989. Evaluation of three circadian rhythm questionnaires with suggestions for an improved measure of morningness. J Appl Psychol. 74(5):728–738 [DOI] [PubMed] [Google Scholar]
  65. Tanaka K, Takahashi M, Tanaka M, Takanao T, Nishinoue N, Kaku A, Kato N, Tagaya H, Miyaoka H. 2011. Brief morning exposure to bright light improves subjective symptoms and performance in nurses with rapidly rotating shifts. J Occup Health. 53(4):258–266 [DOI] [PubMed] [Google Scholar]
  66. Terman M, Lewy AJ, Dijk DJ, Boulos Z, Eastman CI, Campbell SS. 1995. Light treatment for sleep disorders: consensus report. IV. Sleep phase and duration disturbances. J Biol Rhythms. 10(2):135–147 [DOI] [PubMed] [Google Scholar]
  67. Van Cauter E, Moreno-Reyes R, Akseki E, L’Hermite-Balériaux M, Hirschfeld U, Leproult R, Copinschi G. 1998. Rapid phase advance of the 24-h melatonin profile in response to afternoon dark exposure. The American journal of physiology. 275(1):E48–54 doi: 10.1152/ajpendo.1998.275.1.E48 [DOI] [PubMed] [Google Scholar]
  68. Weaver KE, Forsythe LP, Reeve BB, Alfano CM, Rodriguez JL, Sabatino SA, Hawkins NA, Rowland JH. 2012. Mental and physical health-related quality of life among U.S. cancer survivors: population estimates from the 2010 National Health Interview Survey. Cancer Epidemiol Biomarkers Prev. 21(11):2108–2117 doi: 10.1158/1055-9965.EPI-12-0740 [DOI] [PMC free article] [PubMed] [Google Scholar]
  69. Wren MA, Dauchy RT, Hanifin JP, Jablonski MR, Warfield B, Brainard GC, Blask DE, Hill SM, Ooms TG, Bohm RP Jr., 2014. Effect of different spectral transmittances through tinted animal cages on circadian metabolism and physiology in Sprague-Dawley rats. J Am Assoc Lab Anim Sci. 53(1):44–51 [PMC free article] [PubMed] [Google Scholar]
  70. Wu HS, Davis JE, Chen L. 2021. Bright light shows promise in improving sleep, depression, and quality of life in women with breast cancer during chemotherapy: findings of a pilot study. Chronobiol Int. 38(5):694–704 doi: 10.1080/07420528.2021.1871914 [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. Wu HS, Dodd M, Cho MH. 2008. Patterns of fatigue and effect of exercise in breast cancer patients receiving chemotherapy. Oncol Nurs Forum. 35(5):E90–E99 doi: 10.1188/08.ONF.E90-E99 [DOI] [Google Scholar]
  72. Wu HS, Harden JK. 2015. Symptom burden and quality of life in survivorship: a review of the literature. Cancer nursing. 38(1):E29–54 doi: 10.1097/NCC.0000000000000135 [DOI] [PubMed] [Google Scholar]
  73. Zhang Z, Wang HJ, Wang DR, Qu WM, Huang ZL. 2017. Red light at intensities above 10 lx alters sleep-wake behavior in mice. Light Sci Appl. 6(5):e16231 doi: 10.1038/lsa.2016.231 [DOI] [PMC free article] [PubMed] [Google Scholar]
  74. Zhao J, Tian Y, Nie J, Xu J, Liu D. 2012. Red light and the sleep quality and endurance performance of Chinese female basketball players. J Athl Train. 47(6):673–678 doi: 10.4085/1062-6050-47.6.08 [DOI] [PMC free article] [PubMed] [Google Scholar]

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