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. Author manuscript; available in PMC: 2025 Jan 1.
Published in final edited form as: J Psychosoc Nurs Ment Health Serv. 2023 Jul 3;62(1):19–26. doi: 10.3928/02793695-20230622-04

Sleep Health Among Adults in Outpatient Opioid Use Disorder Treatment: A Systematic Review

Estefania Hernandez 1, Stephanie Griggs 2
PMCID: PMC10761602  NIHMSID: NIHMS1942534  PMID: 37379124

Abstract

Introduction.

More than 75% of adults with opioid use disorder (OUD) experience poor sleep health, which is a known risk factor for medication-assisted treatment (MAT) failure and relapse in the United States. The primary aim of this systematic review is to synthesize available original research on objective and self-reported sleep health dimensions among adults in outpatient treatment for OUD (aged 18 to 50 years).

Methods.

A comprehensive search was conducted using multiple electronic databases (PubMed, PsycINFO, CINAHL) followed by screening 2,738 records published in English from the inception of each database to September 14, 2021. Quality was assessed with the Mixed Methods Appraisal Tool (version 2001).

Results.

Fifty-nine studies, 50 descriptive (11 case control, 18 cross sectional, and 21 longitudinal), seven interventional (five non-randomized), and two mixed/multi method designs were included comprising a total of 17,591 adults with mean ages ranging from 23 years to 49 years (mean age, 37.5 ± 5.9 years; 54.4% female) with opioid use disorder and 604 comparison participants without OUD were included in these studies.

Conclusions.

Studies were predominantly observational with various designs with self-report and objective measures with participants at various points in treatment. More work is needed to understand the multidimensional depth of sleep health in adults with OUD. Optimizing sleep health in adults with OUD may improve their addiction trajectory and should be a priority in practice and research.

Keywords: sleep health, opioid use disorder, substance use disorder

A Systematic Review of Sleep Health Among Adults in Outpatient Opioid Use Disorder Treatment

According to Substance Abuse and Mental Health Services (2020), rates of substance use disorders have declined among adolescents and young adults but have remained the same or increased among middle and older aged adults. Opioid use disorder (OUD) affects over 2 million people aged 12 and over (National Center for Drug Abuse Statistics, 2022) in the United States and poor sleep health (satisfaction, alertness, timing, efficiency, and duration) is a primary driver of medication-assisted treatment (MAT) failure and relapse (National Center for Drug Abuse Statistics, 2022). Individuals in therapy for OUD have a high prevalence of sleep problems (>75%) and poorer sleep health compared to individuals without OUD (Mattick et al., 2009). However, sleep health is not routinely assessed in clinical practice (Mattick et al., 2009). Thus, in this systematic review, we examined original studies on sleep health in adults receiving outpatient MAT for OUD.

MAT combined with professional counseling and behavioral therapy is an evidence-informed treatment of OUD however, sleep and other functional outcomes of these therapies remain unclear (SAMHSA, 2020). The US FDA approved medications to treat OUD vary, but common options include Naltrexone (approved 1984; oral pill and injectable), Buprenorphine (approved 1981; implant, injectable, oral pill, sublingual), and Methadone (approved 1972; oral pill) (Mattick et al., 2009). Each of these medications work to target the mu-opioid receptor within the endogenous opioid system to help reduce opioid cravings and better cope with situational triggers; however, each has a distinct mechanism of action based on pharmacological properties (Mancher & Leshner, 2019). The effects of MAT for OUD on functional outcomes based on 40 studies were examined in a previous systematic review, however sleep health dimensions were not included as a functional outcome (Maglione et al., 2018). We exceed prior reviews as we not only synthesize the literature to date on this topic, but also rate the quality of evidence using the Mixed Methods Appraisal tool (version 2011) (Hong et al., 2018).

2. Materials and Methods

The aim of this systematic is to describe sleep health among adults ages 18–50 years in outpatient OUD treatment programs. We followed the Preferred Reporting Items for Systematic Reviews and Meta analyses Statement (Nagendrababu et al., 2019). Our protocol was registered with the PROSPERO registry prior to implementation of the search in the International Prospective Register of Systematic Reviews (Prospero; registration number: CRD42021271701).

2.1. Eligibility Criteria

Studies that met the following criteria were included in this systematic review: (1) original research of adults in outpatient treatment for OUD published in English; (2) with a sample mean age from 18 to 50 years; and (3) with sleep characteristics measured using validated self-report questionnaires, wrist actigraphy, or polysomnography (PSG). Studies with a focus on populations that met the following criteria were excluded: (1) people with severe comorbid psychiatric illness (e.g., bipolar disorder, schizophrenia); (2) grey literature (e.g., PhD dissertations, letters to the editor, commentaries); (3) studies that did not report results on primary sleep-related outcomes; and (4) studies in which all intervention groups received pharmacological treatment (e.g., Ambien, Lunesta) for sleep (e.g., drug studies). We included studies with adults between the ages of 18 and 50 years to capture individuals with relatively similar sleep physiology, duration, and architecture (Ohayon et al., 2017).

2.2. Search Strategy

The PubMed search terms are provided in Table 1. The search strategies were adjusted for syntax as appropriate for each database/platform. The search was conducted under the guidance of a health science librarian (VC) with input from the primary (EH) and senior investigator (SG). In addition, an ancestry search was conducted for reference lists of identified articles and earlier systematic reviews, together with a forward search (citation tracking) until no additional relevant articles were found (September 14, 2021).

Table 1.

Database: PubMed Search Strategy

1 sleep wake disorders / diagnosis
2 sleep habit*
3 sleep
4 sleep disturbance
5 reduced sleep
6 sleep loss
7 1 or 2 or 3 or 4 or 5 or 6
8 opiate substitution treatment
9 opioid-related disorders
10 opioid dependence
11 Analgesics, Opioid
12 opioid*
13 8 or 9 or 10 or 11 or 21
14 7 and 13
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2.3. Study Selection

A total of 3,605 references were imported into Covidence (Veritas Health Information) and 864 duplicates were removed. A total of 2,741 references were screened through Covidence. We included 59 studies that were based on 66 articles (some of the studies were reported in more than one record). The titles and abstracts of retrieved articles were screened independently by two reviewers (EH and SG) with 85% agreement. The full texts of all articles deemed potentially relevant were obtained and the two reviewers assessed them for eligibility against the previously mentioned inclusion/exclusion criteria. All disagreements regarding eligibility were discussed by the two reviewers. If there were multiple publications that described the same study, only the study with the largest sample size was included for participant characteristics.

2.4. Quality Assessment

Appraisal of included studies was assessed independently by two reviewers using the Mixed Methods Appraisal Tool (MMAT) through Covidence (Hong et al., 2018). Studies were assessed based on design relevant questions according to the MMAT quality criteria. Methodological quality criteria were rated as yes, no, or unclear and included the following criteria: 1. Research question was clear; 2. Sample represented the target population; 3. Collected data addressed the research question; 4. Appropriate measures were used; 5. If outcome data were complete; and 6. Confounders were addressed in the design and/or analysis.

2.5. Data Extraction and Synthesis

A customized single spreadsheet was used to extract and record data from the papers. Study characteristics, design, location, length, sample size (OUD and case controls), OUD disorder treatment type, sleep health dimensions (satisfaction, alertness, timing, efficiency, duration) along with means and standard deviations of data were extracted. We contacted corresponding authors and one responded with clarification on their data. Two reviewers compared the extracted data and resolved disagreements through discussion and consultation with data in original papers. We started with a preliminary synthesis to organize findings, then calculated pooled mean estimates for common measures across the studies and assessed the robustness of the synthesis to assess generalizability of the findings.

3. Results

3.1. Study Selection

We present the study selection process in Figure 1. We identified 59 original studies (66 articles) that met our inclusion criteria. The results presented are based on the data published in these articles and data in supplemental materials.

Figure 1. PRISMA Flow Diagram.

Figure 1.

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3.2. Characteristics of Included Studies

Fifty-nine original studies were included in this systematic review including 50 descriptive (11 case control, 18 cross sectional, and 21 longitudinal), seven interventional (five non-randomized), and two mixed/multi method designs. A total of 18,195 adults with mean ages ranging from 23 years to 49 years (mean age, 37.5 ± 5.9 years; 54.4% female) were included in these studies. The participants were comprised of 17,591 adults with OUD and 604 comparison participants. The characteristics of the included studies are presented in Table 2 and Table 3. Sleep behavior was measured with validated questionnaires in 48 studies, research grade actigraphy in three studies, PSG or electroencephalography (EEG) in 19 studies, and with an ibutton in one study. The studies were conducted in the following countries including the United States (28), Israel (6), Taiwan (4), Australia (3), China (3), UK (2), Austria (1), Egypt (1), France (1), Germany (2), India (1), Iran (1), Malaysia (1), Netherlands (1), Spain (1), Turkey (1), and Vietnam (1). Study settings included OUD treatment clinic/site (39 studies, 66%), in-lab (e.g., research clinic; 11 studies, 18.6%), in-lab and home (5 studies, 8.4%), psychiatric hospital (3 studies, 5%), and in a federal prison (1 study, 1.7%). Study measurement lengths varied significantly by number of nights, weeks, and years.

Table 2.

Characteristics of case control studies and sleep measures

Authors Country SUD participants Control participants Sleep measure Sleep dimension
N Age (y) ± SD % female N Age (y) ± SD % female
Asaad et al. (2014) Egypt 33 27 ± NR 0 10 27 ± NR 0 PSG Efficiency, Duration
Capella et al. (2018) Spain 114 37.7 ± 1.1 0 103 35.3 ± 0.7 0 iButton and SR Satisfaction, Timing, Efficiency, Duration
Nguyen et al. (2016) Australia 50 35 ± 9.0 50 20 35 ± 9.0 50 PSG/SR Satisfaction, Efficiency, Duration
Oyefesso et al. (1997) UK 27 33 ± 7.5 59.3 26 35 ± 8.0 34.6 SR Satisfaction
Peles et al. (2017) Israel 26 42.2 ± 7.6 100 13 46.9 ± 9.5 100 SR Satisfaction
Peles et al. (2015) Israel 55 51.5 ± 7.7 34.5 99 1 53.5 ± 7.9 19.2 SR Satisfaction
Peles et al. (2009) Israel 31 49.2 ± 9.0 12 92 41.8 ± 8.7 27.8 SR Satisfaction
Teichtahl et al. (2001) Australia 10 33.0 ± 6.0 40 9 32.0 ± 6.0 33.3 PSG Efficiency, Duration
Wang et al. (2008) Australia 50 35.0 ± 9.0 NR 20 35.0 ± 9.0 NR PSG Alertness, Efficiency, Duration
Xiao et al. (2010) China 20 34.2 ± 7.8 0 20 34.0 ± 7.9 0 PSG Alertness, Efficiency, Duration
Zahari et al. (2016) Malaysia 160 37.5 ± 6.8 0 20 37.5 ± 6.8 0 SR Satisfaction
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SR, Self-report; PSG, polysomnography; iButton, wireless peripheral thermometry device for body temperature; NR. not reported. Control participants were drug free but had a history of drug use.

1

Control participants were a low dose methadone group (<80 mg/d) (vs. high dose >150 mg/d).

Table 3.

Characteristics of the remaining studies and sleep measure used

Authors Country Study design Sleep dimension/s Sleep measure Authors Country Study design Sleep dimension/s Sleep measure
Angarita et al. (2014) USA Non-randomized E, D PSG Lydon-Staley et al. (2017) USA Descriptive S SR
Bakyara and Alban (2019) Turkey Non-randomized S SR Mahfoud (2009) USA Descriptive S SR
Bertz et al. (2019) USA Descriptive A, E, D ACT/SR Matuskey et al. (2011) USA Descriptive E, D PSG
Bracken et al. (2021) USA Non-randomized S SR Morse et al. (2014) USA Non-randomized S SR
Burke et al. (2008) USA Descriptive S SR Nkire et al. (2013) Ireland Descriptive S SR
Cao et al. (2019) China Descriptive S SR Nordmann et al. (2016) France RCT S SR
Chen et al. (2017) Taiwan Descriptive S SR Orr and Stahl (1978) USA Descriptive E, D PSG
Chrobok et al. (2020) Germany Descriptive S SR Peles et al. (2018) Israel Descriptive A, S, E, D PSG/SR
Coffey et al. (2000) USA Descriptive S SR Peles et al. (2011) Israel Descriptive A, S, E, D PSG/SR
Dunn et al. (2018) USA Descriptive S SR Peles et al. (2006) Israel Descriptive A, S SR
Dunn et al. (2021) USA Descriptive E, D EEG Pjrek et al. (2012) Austria Descriptive A, E, D ACT
Finan et al. (2020) USA Descriptive E, D PSG Pud et al. (2012) Israel Descriptive S SR
Freeman and Gottfredson (2018) USA Descriptive E, D EEG Rigg and Ibañez (2010) USA Descriptive S SR
Garnaat et al. (2018) USA Descriptive S SR Sharkey et al. (2011) USA Descriptive E, D PSG
Groenewald et al. (2021) USA Descriptive S SR Sharkey et al. (2011) USA Descriptive E, D PSG
Hallinan et al. (2019) USA Descriptive S SR Staedt et al. (1996) Germany Descriptive E, D PSG
Hsu et al. (2012) Taiwan Descriptive S SR Stein et al. (2004) USA Descriptive S SR
Kay D.C. (1975) Netherlands Descriptive A, S, E, D PSG/SR Teeters et al. (2021) USA Descriptive E, D ACT/SR
Khazaie et al. (2018) Iran Descriptive A, S SR Tripathi et al. (2020) India Descriptive A, S SR
Kurth et al. (2009) USA Descriptive S, E, D PSG/SR Wilkerson et al. (2019) USA Descriptive A, S SR
Le et al. (2019) Vietnam Descriptive S SR Winhusen et al. (2019) USA Descriptive A, S SR
Li et al. (2018) Taiwan Descriptive S SR Yu et al. (2020) Taiwan RCT S SR
Liao et al. (2011) China Descriptive S SR Zheng et al. (2016) USA Descriptive S SR
Lukas et al. (1996) USA Non-randomized A, E, D PSG
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SR: self-report; PSG: polysomnography; EEG: Electroencephalography, ACT: actigraphy. RCT: randomized controlled trial; Non-randomized: all participants received same intervention. S: satisfaction, A: alertness, T: timing, E: efficiency, D: duration.

Sleep satisfaction was predominantly measured with the Pittsburgh Sleep Quality Index (n = 29 studies, 69%) and less commonly with other multi-item scales (n = 9 studies, 21%) (Medical Outcomes Study, Sleep Quality Questionnaire, St. Mary’s Hospital Sleep Questionnaire, General Sleep Disturbance Scale, and Functional Outcome of Sleep Quality) or a single-item sleep quality question (n = 4 studies, 9%). Alertness was measured mostly with the Epworth Sleepiness Scale (n = 15 studies, 88%), the Standford Sleepiness Scale in one study (5.9%) (Bracken et al., 2012) and the Functional Outcome of Sleep Questionnaire in one study (5.9%) (Nguyen et al., 2016).

Objective and self-report measures of sleep timing, efficiency and duration were used. Timing was measured in various ways through a combination of distal skin temperature and self-report 19-item Composite Scale of Morningness (Capella et al., 2018), and actigraphy (Pjrek et al., 2012). PSG is a multiparametric test measuring sleep efficiency (time in bed to total sleep time, sleep onset latency, wake after sleep onset, and/or sleep stages) (seven studies) (Pandi-Perumal et al., 2014). Wrist actigraphy estimates sleep quantity, efficiency, and duration in the natural environment from motor activity as a surrogate for wakefulness (Ancoli-Israel et al., 2003). Duration was measured via PSG in nine studies, EEG in two studies, Actigraphy in one study, and self-reported questionnaires in two studies.

3.3. Quality Assessment

A graph summarizing the appraisal of the included studies is presented in Figure 2. We determined that most studies were of high quality and provided a clear research question (96%). Research objectives and aims were unclear for three studies, one of which also presented an unclear research question. Most authors reported a comparable and representative sample (96%) and appropriately measured data (90%). Incomplete outcome data were unclear in 10 studies. Confounders were not accounted for in the design and analysis in two studies and were unclear in 13 studies.

Figure 2.

Figure 2.

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Mixed Methods Appraisal Across Studies (Quan Nha Hong et al., 2018)

3.4. Sleep Health in Opioid Use Disorder Compared to Control Participants

Sleep health dimensions were compared between adults with OUD and adults without OUD in 11 case control studies (Asaad et al., 2011; Capella et al., 2018; Nguyen et al., 2016; Oyefeso et al., 1997; Peles et al., 2015; Peles et al., 2006; Teichtahl et al., 2001; Wang et al., 2008; Xiao et al., 2010; Zahari et al., 2016). Compared to adults without OUD, adults with OUD had poorer PSG measured pooled mean sleep health (shorter mean total sleep time 359 ± 58 vs. 404 ± 47 mins; lower mean sleep efficiency 75.6 ± 11.5 vs. 88.7 ± 5.7%; and longer mean sleep onset latency 24.9 ± 8.5 vs. 11.8 ± 6.1 mins) in three studies (Asaad et al., 2011; Teichtahl et al., 2001; Xiao et al., 2010), poorer pooled mean architectural quality (less mean time spent in REM 19.2 ± 6.1 vs. 25.2 ± 12.6 and less slow wave sleep 3.6 ± 3.2 vs. 11.7 ± 5.4 %) in four studies (Asaad et al., 2011; Teichtahl et al., 2001; Wang et al., 2008; Xiao et al., 2010), and poorer pooled mean sleep satisfaction (PSQI 9.75 ± 7.05 vs. 6.9 ± 3.5) in four studies (Peles et al., 2006; Xiao et al., 2010).

Adults receiving methadone maintenance treatment reported higher daytime sleepiness and lower daytime function when compared with control participants without OUD (ESS 7.1 ± 5 vs 2.05 ± 1.76 (Functional Outcomes of Sleep Questionnaire 15.47 ± 3.19 vs 19.4 ± 0.47) (Wang et al., 2008). For adults on buprenorphine/naloxone treatment, the Medical Outcomes Study Sleep Scale reported significant improvements after 90 days of treatment (Zheng et al., 2016). In a study where sleep profile differences in adults with OUD compared to healthy controls were explored, those with OUD had higher difficulty initiating sleep (5.42 min vs 1.43 min), maintaining sleep (16.50 min vs. 3.81 min), and achieving adequate quality (8.56 min vs. 2.04 min) and quantity of sleep (9.00 min vs. 2.49 min) (Oyefeso et al., 1997). For instance, higher rates of initial insomnia interrupted sleep, and excessive daytime sleepiness were significantly higher among 10 individuals using heroin and tramadol as opposed to the control group (Asaad et al., 2011). No differences between methadone, diacetylmorphine, and buprenorphine on sleep were found across five studies (Bertz et al., 2019; Chrobok et al., 2020; Finan et al., 2020; Hallinan et al., 2019; Pjrek et al., 2012). However, in one study, adults on methadone treatment reported feeling drowsier throughout the day than those on buprenorphine treatment (Dunn et al., 2018). Participants in the methadone group reported 11% lower activity and were 24 minutes phase delayed whereas those in the buprenorphine group had 2.5% lower sleep efficiency and 9% shorter actual sleep time (N = 42 participants) (Pjrek et al., 2012). Conversely, findings from a sample of 44 individuals formerly using heroin and currently on methadone treatment had poorer sleep (both perceived and objective) regardless of methadone dosage (Peles et al., 2009).

3.5. Sleep Health Dimensions

3.5.1. Satisfaction

Sleep satisfaction was assessed in a majority of the studies (n = 42 studies, 67.7%). Overall, participants with OUD reported poor sleep satisfaction across the different studies and measures. Participants with OUD reported poor global sleep satisfaction (mean PSQI 4.7 – 12.9, 58 – 100% of PSQI > 5) (Peles et al., 2009; Teeters et al., 2021; Winhusen et al., 2019), poor sleep quality measured by a 4-item questionnaire (Matuskey et al., 2011) or single item question (Finan et al., 2020; Freeman & Gottfredson, 2018; Garnaat et al., 2017).

3.5.2. Alertness

Self-reported alertness was assessed in 14 studies (23.7%). Most participants with OUD across the studies reported low daytime alertness (excessive daytime sleepiness, Epworth Sleepiness Scale >7) with mean scores ranging from 6.6 (Wilkerson et al., 2021) to 13.4 (Peles et al., 2015) and an overall mean of 9.5 ± 2.8 on the Epworth Sleepiness Scale and poor sleep daytime function (mean of 15.5 on the Functional Outcome of Sleep Questionnaire (Nguyen et al., 2016), mean Medical Outcome Study Scores ranging from 59 – 62.4) (Burke et al., 2008; Zheng et al., 2016). The mean was not reported in the study where the Standford Sleepiness Scale was used (Bracken et al., 2012).

3.5.3. Timing

Sleep timing (circadian rhythm or typology) was only reported in three studies (5%). A majority participants with OUD in the case control study (n = 114, mean age 35.3 ± 0.7) classified as a morning-type (64%), followed by neither type (referred to as intermediate type) (30%), and evening type (5% (Capella et al., 2018). Control group typologies were not reported in the one study where chronotype was reported (Capella et al., 2018). Chronotypes in the general population have been reported as 50.7% intermediate, 30.5% morning, and 18.8% evening (Urbán et al., 2011). In an actigraphy-based study of 42 individuals with OUD, the cosine peak was 13:59 ± 0:05, amplitude was 9594 ± 176.3, relative amplitude was 0.83 ± .006, interdaily stability was 0.76 ± .01, and intradaily variability was 1.02 ± .01 (Pjrek et al., 2012), and these numbers are comparable to the general population without OUD.

3.5.4. Efficiency and Objective Architectural Quality

Sleep efficiency is defined as the ratio between percentage of time in bed to total sleep time as well as the ease of falling asleep (onset latency) and staying asleep (wake after sleep onset) (Buysse, 2014). Higher sleep efficiency percentages >85% along with onset latency and wake after sleep onset < 30 minutes are desirable (Ohayon et al., 2017). PSG measured sleep efficiency was reported in seven studies with sleep efficiency percentages ranging from 42.7% to 88.2% with a pooled mean of 75.6% ± 11.5%. PSG measured wake after sleep onset and sleep onset latency was reported in five and ten studies respectively. PSG measured wake after sleep onset ranged from 45 to 106 minutes (pooled mean 76.8 ± 45.3 minutes) and sleep onset latency ranged from 7.7 to 108 minutes (pooled mean 35.3 ± 24.3 minutes). Self-reported wake after sleep onset and sleep onset latency were measured in two studies (Asaad et al., 2011; Oyefeso et al., 1997). Self-reported mean wake after sleep onset (86.4 minutes) and sleep onset latency (45 minutes) was reported in one study (N = 33 participants) (Oyefeso et al., 1997).

For architectural quality, recommended sleep staging includes (REM ≤ 41%, N1 ≤ 5%, N2 ≤ 20%, N3 > 5%) (Ohayon et al., 2017). In eleven studies where PSG was used, rapid eye movement (REM) and Non-REM sleep stages (N1, N2, N3) were reported. REM ranged from 5.3 to 29.2% (pooled mean 14.1 ± 7.2%), Non-REM N1 ranged from 9.4 to 39.8% (pooled mean 16.8 ± 9.1 %), Non-REM N2 ranged from 5.5 to 75.7% (pooled mean 53.6 ± 12.2%), and Non-REM N3 ranged from 2.2–16.6% (pooled mean 9 ± 9.9%).

3.5.5. Duration

Recommended sleep duration is seven to nine hours (420 to 540 minutes) (Ohayon et al., 2017). Sleep duration was reported in 13 studies (59%). The PSG/EEG measured sleep duration ranged from 249 to 399 minutes (4 hours 9 minutes to 6 hours 39 minutes) with a pooled mean of 331.6 ± 80.5 (5 hours 31 minutes ± 1 hour 20 minutes) for PSG/EEG studies. Mean actigraphy-derived sleep duration was 366 ± 51.0 minutes (6.3 ± 1.5 hours) in the no stress condition (n = 20) and 353.2 ± 68.4 minutes (6.6 ± 1.9 hours) in the stress condition (n = 19) (Teeters et al., 2021). Self-reported sleep duration ranged from 320 to 378 with a pooled mean of 366.8 ± 126.6 in two studies (Burke et al., 2008; Ohayon et al., 2017).

4. Discussion

4.1. Summary of Findings

We systematically examined fifty-nine studies of sleep health among adults ages 18–50 years in outpatient OUD treatment. We found that adults with OUD had poorer sleep health across multiple dimensions (poorer satisfaction, lower daytime alertness, poorer timing, poorer efficiency, and shorter duration) compared to matched control participants without OUD, national recommendations, and national samples without OUD (Ohayon et al., 2017). Future researchers should address how medication type and dosage impacts sleep-wake cycles among adults with OUD to best improve their quality of sleep and overall treatment trajectory.

4.2. Limitations

There are some limitations that should be considered regarding this systematic review. First, to isolate sleep health dimensions among adults with OUD, the focus of the synthesized studies was on individuals generally free of medical, psychiatric, and sleep disorders, and of a healthy weight, limiting the generalizability the findings. Second, although all selected studies addressed sleep health, only one to two dimensions were addressed in each study (satisfaction in 42 studies, alertness in 17 studies, timing in three studies, efficiency in 14 studies, and duration in 16 studies). Although common scales were used to address satisfaction (e.g., PSQI used in 69%), sleepiness (e.g., ESS used in 88%), efficiency/duration (e.g., PSG in 80%), the ways in which data were reported varied in important ways. For instance, sleep stage percentages were reported in some studies (Asaad et al., 2011; Dunn et al., 2018; Finan et al., 2020; Freeman & Gottfredson, 2018; Lukas, 1996; Sharkey et al., 2009; Teichtahl et al., 2001; Xiao et al., 2010) and sleep stage minutes in others (Angarita et al., 2014; Staedt et al., 1996; Wang et al., 2008) and thus were not comparable. Also means for various values were not consistently reported. We recommend more transparent reporting in the future to allow more results to be pooled across studies for comparison to move the field forward. Though the focus of this systematic review was on OUD, several studies included samples with OUD and other substances making it difficult to appreciate the confounding effects of these other substances. Lastly, there were limited interventional studies making it difficult to consider the confounding effect of treatment, biological sex, race, and socioeconomic factors on the findings. Randomized controlled trials are needed to determine whether promoting one or more sleep health dimensions will have an effect on MAT outcomes in this population. This would be consistent with the national priority to address sleep health in individuals with OUD (National Institutes of Health, Helping to End Addition Long-Term or NIH HEAL initiative ®).

4.3. Clinical Implications for Nursing Practice

The findings from this review support that sleep health (e.g., sleep disturbance and deficiency) is an important factor to consider in risk relapse for people with OUD. Psychiatric nurses as well as nurses working with individuals with OUD in other settings can assess for potential modifiable challenges specific to OUD and strategies specific to OUD to promote sleep, such as timing of medication, and managing both OUD and emotional/physical effects of the opioid use disorder. Various types of opioids have been monitored in addiction-related sleep health research. However, the inconsistent patterns of polysubstance use and heterogeneity in treatment populations make assessing the association between one or more dimensions of sleep health challenging. To best understand the mechanisms that link sleep and addiction, future nurses and clinical researchers should 1) incorporate a combination of measures such as actigraphy, sleep logs, and self-report instruments, 2) examine the individual effects of opioid medication type and dosing on sleep, 3) reframe the current dialogue between patients and their providers regarding normal and expected sleep adjustments during treatment through motivational interviewing, and 4) systematically assess all dimensions of sleep (e.g., satisfaction, alertness, timing, efficiency, and duration).

It was difficult to draw conclusions about the study results included in this review due to the various sleep measurements used. While polysomnography is the gold-standard to measure sleep objectively, it has a high degree of subject burden and cost thus limits the recruitment phase and sample size and increases the chance of selection bias. Using PSG for a subsample alongside self-reported and actigraphy-derived sleep measures can help improve the understanding of e sleep health dimensions (timing, efficiency, and duration).

5. Conclusions

This research provides a better understanding of how sleep health may impact addictive behaviors and recovery and vice versa. While many of the included studies had a degree of limitation, each demonstrated innovative and potentially cost-effective strategies to provide insight into a population often understudied and stigmatized for their condition. Sleep and opioid use research ought to be navigated through a combination of both subjective and objective measures. People experiencing addiction should not only be made aware of the pharmacological explications but also the importance of promoting healthy behaviors such as sleep. The effects of medication-type and -dose on multiple sleep health dimensions and the outcomes of treatment (e.g., relapse, cognitive, physical, occupational, social/behavioral, and neurological function) remain unclear. This systematic review highlights the need to explore whether promoting sleep health may improve recovery outcomes in persons with OUD.

Highlights.

  • Adults with opioid use disorder have poor sleep health.

  • Adults with substance use disorder have difficulty initiating/maintaining sleep.

  • High methadone doses are associated with poor sleep (less slow wave sleep).

  • More daytime drowsiness in methadone vs. buprenorphine use.

  • Effects of medication type and dose on sleep architecture research are limited.

Funding:

American Academy of Sleep Medicine (AASM, 220-BS-19) provided funding for this work (E. Hernandez and S. Griggs). Stephanie Griggs is also funded by the National Institute of Nursing Research (R00NR018886, Griggs PI). Its contents are solely the responsibility of the authors and do not necessarily represent the official view of NIH or AASM.

Footnotes

Conflicts of interest: The authors declare no conflicts of interest.

Contributor Information

Estefania Hernandez, Case Western Reserve University, Frances Payne Bolton School of Nursing, Department of Anthropology.

Stephanie Griggs, Case Western Reserve University, Frances Payne Bolton School of Nursing, Cleveland, Ohio, 44106.

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