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10.12688/f1000research.166110.3

Systematic Review

Articles

Imbalances in the Content of Sleep and Pain Assessments in Patients with Chronic Pain: A Scoping Review

[version 3; peer review: 2 approved]

Tanaka

Katsuyoshi

Conceptualization Data Curation Formal Analysis Investigation Methodology Project Administration Visualization Writing – Original Draft Preparation Writing – Review & Editing https://orcid.org/0000-0003-2322-0287 a 1 Isaji

Yuichi

Investigation Writing – Review & Editing https://orcid.org/0000-0003-1190-6652 1 Suzuki

Kosuke

Investigation Writing – Review & Editing https://orcid.org/0009-0004-2344-6029 2 Okuyama

Kohei

Investigation Writing – Review & Editing https://orcid.org/0000-0001-9876-1307 1 Kurasawa

Yasuyuki

Investigation Writing – Review & Editing https://orcid.org/0000-0001-9966-5261 3 Hayashi

Masateru

Investigation Writing – Review & Editing 4 Kitagawa

Takashi

Investigation Supervision Writing – Review & Editing https://orcid.org/0000-0002-8596-8381 5 1Department of Physical Therapy, School of Health Sciences, Bukkyo University, Kyoto, Kyoto, 604-8418, Japan 2Department of Rehabilitation, Yamagata Saisei Hospital, Yamagata, Yamagata, Japan 3Department of Rehabilitation, Faculty of Health Science, Nagano University of Health and Medicine, Nagano, Nagano, Japan 4Department of Rehabilitation, Matsuoka Orthopedic Surgery and Internal Medicine Rehabilitation, Gifu, Gifu, Japan 5Department of Physical Therapy, School of Health Sciences, Shinshu University, Matsumoto, Nagano, Japan

a katsutanaka7@gmail.com

No competing interests were disclosed.

12 12 2025

2025

605

3 12 2025

2025

This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Background

Sleep disturbances frequently occur in concomitance with chronic pain, exacerbating its detrimental effects and diminishing patients’ quality of life. Although various studies have explored the relationship between chronic pain and sleep disturbances, comprehensive evidence on detailed assessment methods and their bidirectional interactions remains limited. This scoping review aimed to examine the characteristics and prevalence of assessment methods for sleep and pain-related outcomes in individuals with chronic pain.

Methods

A comprehensive search of nine databases identified observational and interventional studies examining the relationship between sleep disturbances/disorders and chronic pain in adults. A literature search was conducted in MEDLINE, the Cochrane Central Register of Controlled Trials, Embase, PsycINFO, Web of Science, Cumulative Index to Nursing and Allied Health Literature (CINAHL) as well as gray literature sources, Open Grey. In addition, the following trial registries were searched for ongoing or unpublished trials: the World Health Organization International Clinical Trials Registry Platform and ClinicalTrials.gov.

Results

This review included 81 of 3,513 studies. Approximately 90.1% of studies relied on self-report sleep assessments, whereas only 9.9% incorporated objective measures. Additionally, 7.4% of studies used a combination of self-report and objective sleep assessments. The visual analog and numeric rating scales were the most frequently used methods for assessing pain-related outcomes (59.3%). Despite extensive research on sleep and chronic pain, critical gaps persist, particularly in the integration of multidimensional assessment tools.

Conclusions

This scoping review discovered imbalances in the content of both sleep and pain assessments. Future studies should integrate both objective and self-report assessment tools to provide a more comprehensive understanding of this interaction.

pain sleep disturbances assessment tools

The author(s) declared that no grants were involved in supporting this work.

Revised Amendments from Version 2

In this revised version, we have addressed the reviewer's comments by strengthening the synthesis of our findings and deepening the discussion. The Introduction and Methods sections have been revised to clarify the study rationale and detail the categorization process for the assessment tools. In the Results, we added a narrative summary describing the associations between sleep and pain outcomes, highlighting the discrepancy between patient-reported correlations and objective measures. A new table has been included to systematically map the identified assessment tools to specific pain domains (e.g., intensity, interference, psychosocial factors), providing a clear overview of the usage frequencies. Furthermore, the Discussion section has been expanded to elaborate on the bidirectional nature of the sleep-pain relationship, incorporating recent evidence on sleep deprivation and hypothesize neurobiological mechanisms. The reference list has been updated to support these additions.

Abbreviations

BPI

Brief Pain Inventory

ISI

Insomnia Severity Index

NRS

Numeric Rating Scale

PSQI

Pittsburgh Sleep Quality Index

PRO

Patient-Reported Outcome

QOL

Quality Of Life

RCT

Randomized Controlled Trial

ScR

Scoping Review

VAS

Visual Analog Scale

1. Introduction

Pain is a fundamental human experience that functions as a protective mechanism, however, when it persists beyond the expected period of tissue healing, it is regarded as a pathological condition known as chronic pain. The World Health Organization recognizes chronic pain as a disease, making it one of the most prevalent conditions worldwide. ¹ Chronic pain results in significant disability and imposes a substantial economic strain on society. ² In addition to persistent pain, individuals with chronic pain experience various consequences, including deterioration in the quality of life (QOL), higher prevalence of depressive symptoms, and greater levels of disability compared with those without pain. ³ The financial impact of chronic pain, including healthcare expenses and reduced work efficiency, is substantial. ⁴ This underlines the extensive influence of pain on the individual and the community as a whole. Furthermore, chronic pain often coexists with sleep disturbances, which exacerbate the adverse effects of pain, adding to the overall strain on individuals and society. ^{5,
6}

Patients with chronic pain frequently develop sleep disturbances. ^{7–
10} Sleep disturbance including inadequate sleep, insomnia and obstructive sleep apnea, represent significant and widespread health concerns. ^{11,
12} Notably, the prevalence of sleep disturbance is high among patients with chronic musculoskeletal pain, affecting approximately 75% and 44% of such individuals, respectively. ^{9,
13} Previous studies have suggested a correlation between compromised sleep and reduced QOL, adverse general health outcomes, elevated levels of depression, and diminished physical function. ¹⁴ Additionally, the concomitance of chronic pain and sleep disturbances leads to further deterioration in overall health and QOL. A bidirectional association has also been suggested, wherein pain negatively affects sleep, and sleep disturbances contribute to increased pain. ¹⁵

Polysomnography, which is considered the gold standard for the objective assessment of sleep, has been used in various chronic pain conditions, such as fibromyalgia, rheumatoid arthritis, osteoarthritis, and temporomandibular pain. ^{7,
16} In addition to polysomnography, sleep assessment, encompassing sleep duration and quality, has been conducted using several tools, such as actigraphy, questionnaires, and wearable devices. ^{17,
18} Moreover, although several studies have investigated the relationship between sleep and chronic pain, most existing reviews have focused on specific populations, such as those with postsurgical pain, pediatric pain, or low back pain. ^{19–
21} Thus, comprehensive evidence on detailed methods for assessing the relationship between chronic pain and sleep disturbance remains scarce.

Therefore, this scoping review (ScR) aimed to examine the characteristics and prevalence of methods used to assess sleep and pain-related outcomes in individuals with chronic pain and to identify gaps in the evidence, with the objective of guiding future studies.

2. Methods

This ScR was conducted according to the Joanna Briggs Institute methodology for scoping reviews, following all eight recommended steps without deviation. ²² The study was registered with the Open Science Framework ( https://doi.org/10.17605/OSF.IO/5JK63) on March 29, 2024. This review also adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping reviews (PRISMA-ScR) checklist. The inclusion criteria were established based on the participants, concept, and context of the study.

2.1 Eligibility criteria

This ScR included studies on individuals with chronic pain lasting for >3 months. Studies on individuals with malignancy-related or cancer-related pain or acute pain conditions, such as postoperative pain, were excluded. Moreover, studies that included children (≤18 years) and/or participants with other conditions besides chronic pain were excluded. No restrictions were imposed with respect to the sex, location, race, country, or language of the participants. This review evaluated the measurement tools used for sleep assessment in individuals with chronic pain conditions, including polysomnography, wearable devices, and questionnaires. Additionally, we identified various types of pain-related assessments, including pain intensity, severity, disability, catastrophizing, threshold, and tolerance. In other words, we included studies that involved sleep assessments in individuals with chronic pain conditions.

This ScR included randomized controlled trials (RCTs), crossover trials, quasi-RCTs, non-RCTs, cross-sectional studies, and prospective and retrospective cohort studies, encompassing both observational and interventional designs. Protocols and conference abstracts were included in the initial screening, with a secondary screening conducted to verify the existence of published articles. Case reports, case-control studies, systematic reviews, meta-analyses, and narrative reviews were excluded.

2.2 Search strategy

The search strategy was designed to identify both published and unpublished studies. A literature search was conducted in MEDLINE, the Cochrane Central Register of Controlled Trials, Embase, PsycINFO, Web of Science, Cumulative Index to Nursing and Allied Health Literature (CINAHL) as well as gray literature sources, Open Grey. In addition, the following trial registries were searched for ongoing or unpublished trials: the World Health Organization International Clinical Trials Registry Platform and ClinicalTrials.gov.

The text words found in the titles and abstracts of relevant articles, along with the index terms used to describe the articles, were used to develop a comprehensive search strategy across nine databases (the complete PubMed search strategy is provided in Table S1). Previous studies were also referenced. ^{19,
23,
24} Studies published in any language were included, with no restrictions on the publication date. The final comprehensive search was conducted on March 29, 2024.

2.3 Study selection and source of evidence

All identified citations were collated and uploaded into Rayyan (Qatar Computing Research Institute, Ar Rayyan, Qatar, https://www.rayyan.ai/), and duplicates were removed. Following a pilot test, two or more independent reviewers (K.T. and Y.I.) screened the study titles and abstracts based on the eligibility criteria. The full text of relevant sources was retrieved, and their citation details were imported into Rayyan. Two or more independent reviewers (K.T., Y.I., K.S., M.H., K.O., and Y.K.) assessed the full text of the selected studies based on the eligibility criteria. The reasons for excluding sources that did not meet the eligibility criteria were documented and reported in this ScR. Any disagreements between reviewers at each stage of selection were resolved through discussion or by consulting additional reviewers.

The results of the search and study inclusion process were comprehensively reported in the final ScR and illustrated in a Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for ScR flow diagram. ²⁵

2.4 Data extraction

Data were extracted from the included studies using Microsoft Excel (Microsoft Corp., Redmond, WA, USA) by the first author (K.T.), with the assistance of ChatGPT-4o (San Francisco, CA, USA) and NotebookLM (Mountain View, CA, USA). ^{26,
27} These AI tools were used to facilitate the extraction and preliminary organization of information from the included studies. All outputs generated by AI were reviewed and verified against the original sources by the first author (K.T.) to ensure accuracy, and all final decisions were made by the research team. No dedicated systematic review software (e.g., Covidence) was used for data extraction. The extracted data included the first author’s name, country of origin, study design, sample size, participant characteristics (age, sex, and diagnosis), and tools used for assessing sleep disturbance and pain-related outcomes. The draft data extraction tool was modified and refined as necessary throughout the data extraction process. Where necessary, the authors of the included studies were contacted to obtain any missing or additional data.

To enhance reproducibility, the exact data extraction template has been made publicly available in the Open Science Framework repository ( https://doi.org/10.17605/OSF.IO/5JK63). The column headings include, for example, “Title”, “Author”, “Year of publication”, “Country”, “Study design”, “Diagnosis/Conditions”, “Sample size”, “Age”, “Sleep assessment tool”, and “Assessment tools of pain-related factor”. Verification checks included double-checking the counts of sleep and pain assessment tools extracted by AI against both the full-text tables and textual descriptions, and cross-referencing the extracted sample characteristics with the methods sections of the original papers.

2.5 Sensitivity statement on search recency

The literature search was last conducted on March 29, 2024. To contextualize the recency of the review, an updated search was performed in PubMed using the same search strategy, limited to publications from 2024 to 2025, on November 7, 2025. This additional search identified 131 new records. Although this increase indicates an ongoing rise in research activity, particularly in wearable-based sleep assessments, the number of new studies remains modest relative to the total volume of literature included in the present review. Therefore, the findings of this review are considered broadly representative of the current evidence base, while future updates should incorporate these recent studies to capture emerging trends.

3. Results 3.1 Study selection

A total of 3,513 articles were retrieved during the database search. After eliminating 1,296 duplicates, the titles and abstracts of 2,217 articles were screened. Thereafter, the full texts of the remaining 415 articles were assessed for eligibility. Ultimately, only 81 studies that met the eligibility criteria were included in the analysis ( Figure 1).

Figure 1. PRISMA flow diagram illustrating the structure of the search and screening process. 3.2 Study and participant characteristics

Of the 81 included studies, 26 (32.1%) were RCTs, ^{28–
53} while the remaining studies were non-RCTs. ^{54–
108} The included studies were published between 1998 and 2024, with nearly half (45.7%, 37 of 81) published within the last 5 years. ^{30–
32,
34–
36,
40,
41,
43,
48,
51–
54,
58,
59,
63,
67,
68,
73,
76,
78–
82,
85–
87,
90–
93,
95,
96,
101,
106} The distribution of participants varied across studies: 31 studies (38.3%) focused on examining patients with chronic pain, irrespective of pain type, accounting for 40.5% of the total participants (7,413 out of 18,316). ^{32,
38,
42,
47,
51,
52,
54,
57,
58,
65,
67,
69–
73,
76,
79,
80,
82,
85,
88,
89,
91,
92,
94,
97,
99,
101,
103,
106} Eleven studies (13.6%) investigated patients with chronic low back pain, accounting for 12.4% of the total participants (2,266 participants). ^{33,
36,
46,
48,
56,
81,
90,
95,
98,
107,
108} Eight studies (9.9%) examined patients with chronic musculoskeletal pain, irrespective of location, accounting for 9.1% of the total participants (1,667 individuals). ^{41,
62–
64,
77,
78,
86,
105} Six studies (7.4%) assessed patients with chronic neck pain, comprising 5.2% of the total participants (950 participants). ^{34,
40,
60,
61,
96,
100}

To provide an overview of demographic and clinical characteristics of the study populations, Table 1 summarizes the participant characteristics across the included studies, while detailed study-level information is available in Supplementary Table S2.

Table 1. Summary of included studies and participant characteristics.

Category	N (%) or Median (IQR)
Study design
RCTs	26 (32.1%)
non-RCTs	55 (67.9%)
Publication period	1998–2024 (45.7% after 2019)
Age (years)	48.1 (44.0-54.1) *
Female participants (%)	61.4 (53.4-72.5) **
Pain type
Chronic pain	31 (38.3%)
CLBP	11 (13.6%)
Chronic musculoskeletal pain	8 (9.9%)
CNP	6 (7.4%)
Chronic pain and insomnia	3 (3.7%)
CTTH	2 (2.5%)
PHN	2 (2.5%)
Fibromyalgia or CLBP	1 (1.2%)
Idiopathic chronic pain	1 (1.2%)
Chronic spinal degenerative disease	1 (1.2%)
Traumatic SCI	1 (1.2%)
ICONP and MMP	1 (1.2%)
Chronic Migraine	1 (1.2%)
CLBP, and unspecified back pain	1 (1.2%)
Orofacial pain	1 (1.2%)
Chronic back pain	1 (1.2%)
Insomnia, chronic musculoskeletal pain	1 (1.2%)
TMD	1 (1.2%)
Chronic pain with insomnia	1 (1.2%)
Chronic pain after SCI	1 (1.2%)
Osteoarthritis of the knee	1 (1.2%)
CNP, CLBP, and/or generalized pain	1 (1.2%)
NSCNP	1 (1.2%)
NSCSP and comorbid insomnia	1 (1.2%)
Masticatory/cervical muscle pain or temporomandibular joint pain	1 (1.2%)

Reported in 79 studies.

^**

Reported in 74 studies.

3.3 Outcome measurements

An overview of the included studies is presented in supplemental materials (Table S2, S3). Various methods have been used to assess sleep disturbances and pain-related outcomes, with patient-reported outcomes (PROs) being the most frequently utilized.

The Pittsburgh Sleep Quality Index (PSQI) (45 of 81 studies, 55.6%) and Insomnia Severity Index (ISI) (21 of 81 studies, 25.9%) were the most commonly used tools for the assessment of sleep problems ( Figure 2). Other self-reported sleep assessment methods used included the Athens Insomnia Scale and sleep diaries. Sleep problems were predominantly assessed based on the participant’s entries in sleep diaries. In terms of study methodology, 73 of 81 studies (90.1%) relied solely on PROs (90.1% [73/81]). ^{30–
53,
60–
108} Only 2 of 81 studies (2.5%) relied solely objective assessments, ^{58,
59} such as actigraphy, whereas 6 of 81 studies (7.4%) used a combination of PROs and objective assessments. ^{28,
29,
54–
57} Other objective sleep assessment methods used included polysomnography and electroencephalography.

Figure 2. Percentage of the combined use of sleep problem and pain-related outcome assessments.

For PRO assessments, the outcomes were frequently evaluated using the numeric rating scale (NRS) or visual analog scale (VAS) (59.3% [48/81]). ^{32,
34–
41,
44,
45,
49,
50,
52,
53,
55–
62,
64–
66,
70–
72,
77,
79,
81,
85,
87,
88,
90,
91,
94–
98,
100,
103,
105,
107,
108} The Brief Pain Inventory (BPI) was the second most frequently used pain assessment tool (28.4% [23/81]). ^{28,
30,
31,
33,
42–
44,
46,
47,
51,
57,
63,
67–
69,
73,
76,
78,
80,
82,
86,
89,
99} Additional pain-related outcome measures included the Multidimensional Pain Inventory and Pain Disability Questionnaire. Psychometric factors were evaluated in more than half of the included studies (60.5% [49/81]). ^{30,
32,
35–
38,
41,
42,
44,
47,
49,
50,
52,
54,
55,
58,
60–
63,
69–
79,
83–
85,
87,
90–
95,
97–
99,
102,
103,
105,
106,
108} Objective pain assessment was rarely performed, with only one study utilizing quantitative sensory testing. ⁹⁸

Figure 2 presents the detailed percentages of the combined use of sleep problems and pain-related outcome assessments. The NRS/VAS was frequently used in combination with the PSQI (31.4%), followed by combination of the NRS/VAS with the ISI (15.6%). The simultaneous use of both self-report and objective sleep assessments, along with the NRS or VAS and the BPI, was extremely rare, occurring in only 0.6% of studies ( Figure 2, Table 2).

Table 2. Mapping of pain domains to assessment tools idendified in the included studies.

Pain domains	Assessment tools	Frequency, n (%)
Pain Intensity	Total studies assessing this domains	71 (87.7%)
	Numeric Rating Scale (NRS)	33 (40.8%)
	Visual Analog Scale (VAS)	15 (18.5%)
	Brief Pain Inventory (BPI) *	23 (28.4%)
Interference/Disability	Total Studies assessing this domain	46 (56.8%)
	Brief Pain Inventory (BPI) *	23 (28.4%)
	Pain Disability Questionnaire (PDQ)	10 (12.3%)
	Multidimensional Pain Inventory (MPI)	7 (8.6%)
	Region-specific (ODI, RMDQ, NDI, etc.)	6 (7.4%)
Pain Quality	McGill Pain Questionnaire (MPQ, SF-MPQ)	5 (6.2%)
Psychosocial Factors	Total Studies assessing this domain	49 (60.5%)
	Depression/Anxiety Scales (HADS, BDI, PHQ, PASS, etc.)	44 (54.3%)
	Pain Catastrophizing Scale (PCS)	18 (19.8)
	Tampa Scale for Kinesiophobia (TSK)	6 (6.6%)
	Self-Efficacy/Acceptance (PSEQ, CPAQ)	2 (2.5%)
Quantitative Sensory Testing (QST)	Pressure Pain Threshold (PPT)	1 (1.2%)

BPI was mapped to both “Pain Intensity” and “Pain Interference” domains as it assesses both pain severity and its impact on daily functions.

3.4 Association between sleep and pain outcomes

Although a meta-analysis was not conducted, a narrative summary of the included studies reveals distinct patterns in the relationship between sleep and pain.

Studies relying on patient-reported outcomes consistently demonstrated a significant positive correlation, where higher score on sleep questionnaires (e.g., PSQI, ISI) were associated with greater pain intensity or interference.

In contrast, findings from objective assessments varied depending on the measurement modality. Studies utilizing movement-based devises, such as actigraphy, generally did not show a clear association with pain intensity or other pain-related outcomes. However, objective measures based on physiological parameters, such as heart rate or electroencephalography (EEG), tended to exhibit significant associations with pain outcomes.

4. Discussion

This ScR highlighted the use of various measurement tools for assessing sleep and pain. The review emphasized the diversity of assessment tools used to evaluate sleep and pain, revealing substantial inconsistencies and the lack of standardization. Despite the large body of research on this topic, critical gaps persist, particularly the absence of generalizable objective measurements for sleep assessment, which may hinder the reliability and applicability of the current findings.

A key finding of this review is the predominant reliance on self-report measures for evaluating sleep disturbances. Over 90% of the included studies utilized PROs, such as the PSQI or the ISI. Although these tools provide practical and accessible methods of assessing perceived sleep quality, they are inherently limited by individual biases and self-reported variability. ^{109,
110} In contrast, objective measures such as actigraphy and polysomnography provide precise and quantifiable data on sleep architecture, including sleep stages, latency, and fragmentation. ^{111,
112} However, these tools were employed by only a small portion of the included studies, with objective methods utilized by 9.9% (8/81) of studies. This imbalance likely stems from the challenges, which traditionally include cost and other constraints, hindering the use of objective measures, thereby complicating the comprehensive assessment of sleep disturbances. ^{113,
114} Furthermore, our review identified a discrepancy in the results derived from different objective modalities. While movement-based assessment (e.g., actigraphy) often failed to correlate with pain, physiological measures (e.g., EEG, heart rate) consistently showed significant associations. This suggests that while pain may not always disrupt gross body movements during sleep, it likely impacts physiological sleep architecture and autonomic regulation. Future research should prioritize the integration of these objective tools to provide a more robust understanding of sleep disturbances in individuals with chronic pain.

Beyond sleep assessment, this review also identified variability and potential bias in the pain-related outcome evaluations. Most studies focused primarily on examining pain intensity, often measured using the NRS or the VAS. Although these tools are widely used and validated, ^{115,
116} they only capture one aspect of the complex pain experience. ^{117–
119} Approximately half of the studies assessed the psychological factors associated with pain, but other important domains, such as pain-related disability and sensitization, were less frequently explored. Notably, only one study included in this review utilized quantitative sensory testing. ⁹⁸ This limited focus restricts the understanding of pain mechanisms and hinders the development of targeted treatment strategies. More comprehensive pain assessment protocols that incorporate these additional dimensions are necessary to produce clinically relevant evidence. ¹²⁰

The complex relationship between sleep disturbances and chronic pain necessitates a multidimensional research approach. Current evidence emphasizes a strong bidirectional relationship between sleep and pain, with sleep disturbances often predicting future pain severity more robustly than pain predicts sleep problems. ⁶ Experimental studies have further demonstrated that sleep deprivation directly exacerbates pain perception, lowering pain thresholds and increasing hyperalgesia. ¹²¹ ^, ¹²² These interactions are hypothesized to be mediated by shared neurobiological mechanisms, particularly central sensitization and impairments in descending pain inhibitory pathways, which nociceptive signaling. ^{123,
124} Incorporating objective sleep assessments and multidimensional pain measures into research and practice will enhance the quality of evidence and support the development of precision medicine approaches tailored to individual patient needs. Furthermore, interdisciplinary collaboration that brings together experts in neurology, psychology, and bioinformatics could facilitate the development of innovative assessment tools and therapeutic interventions.

This review has some limitations. The lack of synthesis of the findings restricted our ability to evaluate methodological rigor and the overall reliability of the evidence. Additionally, the possibility of overlooking relevant studies cannot be completely excluded, which may have introduced selection bias. However, this review included gray literature and non-English studies to mitigate this potential bias. A further limitation is that the literature search was last conducted in March 2024, and more recent studies may not have been captured.

5. Conclusions

This ScR highlights the imbalance in the characteristics of sleep and pain assessments, indicating the need for a more comprehensive evaluation of sleep disturbances and pain-related outcomes. Addressing the gaps in objective and multidimensional assessments could facilitate the development of personalized interventions that improve patient outcomes and overall quality of care.

Ethics and consent

This scoping review did not involve human participants directly, and therefore ethical approval was not required.

Data availability

All data underlying the results are available in the Open Science Framework repository: ( https://doi.org/10.17605/OSF.IO/5JK63), licensed under CC0 1.0 Universal. ¹²⁵

This includes the PRISMA-ScR checklist, flowchart, data for figure and supplementary tables.

Acknowledgements

The authors utilized artificial intelligence tools for data extraction and the preparation of preliminary drafts. Data interpretation and final manuscript revisions were solely performed by human researchers.

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Reviewer response for version 3

Martins

Yuri Chaves

1 Referee https://orcid.org/0000-0003-4220-4979 Murin

Peyton

2 2 Co-referee 1Anesthesiology, Saint Louis University School of Medicine (Ringgold ID: 12274), St. Louis, Missouri, USA 2Neurology, Saint Louis University School of Medicine (Ringgold ID: 12274), St. Louis, Missouri, USA

Competing interests: No competing interests were disclosed.

2 1 2026

2026

This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

recommendation

approve

Response to Yuri Chaves Martins and Peyton J. Murin

We greatly appreciate the reviewer’s insightful comments. Our responses to your comments are given below.

Introduction

Comment: The transition between pain to chronic pain could be smoother. Would recommend rewording to allow for better flow/cohesion.

Responses:

We appreciate the reviewer’s helpful suggestion. To improve the logical flow from pain to chronic pain, we have revised the beginning of the Introduction. Specifically, we added a sentence to clarify the conceptual transition from pain as a protective mechanism to chronic pain as a pathological condition. The following text was added:

“Pain is a fundamental human experience that functions as a protective mechanism, however, when it persists beyond the expected period of tissue healing, it is regarded as a pathological condition known as chronic pain.”

2 ^nd review: The change in wording improved the flow of the introduction.

Methods

Comment: You transparently describe using ChatGPT-4o and NotebookLM with human verification. To enhance reproducibility, please (i) provide the exact extraction template (e.g., the Excel column headings) in the OSF repository and (ii) add one or two concrete examples of verification checks you performed (e.g., double-checking instrument counts against full texts).

The search was last run on March 29, 2024. You acknowledge that newer studies may be missing (page 7). Given the rapid growth in wearable-based sleep assessments, a short sensitivity statement (e.g., how many additional records a quick 2024–2025 update might add based on pilot scoping) would contextualize recency without requiring a full rerun.

Responses:

We sincerely thank the reviewer for these valuable and constructive comments.

(i) To improve transparence and reproducibility, we have updated the Excel data extraction template (showing the column headings used for data collection) to our Open Science Framework (OSF) repository ( https://doi.org/10.17605/OSF.IO/5JK63). The revised Methods section has showed the major data fields extracted (eg., author country, study design, and tools used for sleep and pain assessment). The following sentence was added:

“To enhance reproducibility, the exact data extraction template has been made publicly available in the Open Science Framework repository ( https://doi.org/10.17605/OSF.IO/5JK63 ). The column headings include, for example, “Title”, “Author”, “Year of publication”, “Country”, “Study design”, “Diagnosis/Conditions”, “Sample size”, “Age”, “Sleep assessment tool”, and “Assessment tools of pain-related factor”.”

(ii) We have also added specific examples of verification procedures used during data validation. These included double-checking the counts of sleep and pain assessment tools extracted by AI against both the full-text tables and textual descriptions, and cross-referencing the extracted sample characteristics with the methods section. The following sentence was added:

“Verification checks included double-checking the counts of sleep and pain assessment tools extracted by AI against both the full-text tables and textual descriptions, and cross-referencing the extracted sample characteristics with the methods sections of the original papers.”

(iii) To contextualize the recency of our research, we performed an updated PubMed search using the same search strategy as in the original review, limited to publications from 2024 to 2025, on November 7, 2025. This updated search identified 131 new records, reflecting a moderate increase in studies related to wearable-based sleep assessments. We have added a corresponding sensitivity statement to the Methods section, clarifying that the findings of the present review remain broadly representative of the current evidence base, while future updates should incorporate these recent studies. The following sentences were added:

“The literature search was last conducted on March 29, 2024. To contextualize the recency of the review, an updated search was performed in PubMed using the same search strategy, limited to publications from 2024 to 2025, on November 7, 2025. This additional search identified 131 new records. Although this increase indicates an ongoing rise in research activity, particularly in wearable-based sleep assessments, the number of new studies remains modest relative to the total volume of literature included in the present review. Therefore, the findings of this review are considered broadly representative of the current evidence base, while future updates should incorporate these recent studies to capture emerging trends.”

2 ^nd Review: The above changes increased reproducibility of the methodology. These changes sufficiently addressed our concerns.

Results

Comment: 3.2: Would recommend including more robust analysis on the gender distribution, age, pain type. Would recommend adding a table to summarize this data.

Response:

Thank you for this helpful suggestion. In response, we strengthened the description of participant characteristics by providing an aggregated summary of age distribution, sex distribution, and pain diagnoses in the main text. The following sentence was added:

“To provide an overview of demographic and clinical characteristics of the study populations, Table 1 summarizes the participant characteristics across the included studies, while detailed study-level information is available in Supplementary Table S2.”

2 ^nd Review: This is sufficiently addressed

Comment: 3.3: While this is not a meta-analysis (and as such, there is not a need for formal analysis), it would strengthen the results to have a summary of findings in the studies (i.e. did pain scores and sleep scores correlate)? In addition, for pain outcomes, you note the predominance of NRS/VAS and BPI. Consider adding a summary matrix (main text or supplement) mapping pain domains (intensity, interference/disability, psychosocial, sensitization, QST) to the instruments encountered, indicating frequencies (some of this is described narratively on page 6)

Response:

Thank you for this constructive suggestion. We agree that providing a summary of the associations and a structured mapping of assessment tools significantly strengthens the manuscript.

Regarding the summary of findings, we have added a new section in the Results (3.4 Association between sleep and pain outcomes) to narratively describe the trends identified in the included studies. We reported that while patient-reported outcomes consistently demonstrated positive correlations between sleep and pain, objective measures showed distinct patterns: movement-based assessments (e.g., actigraphy) often lacked clear associations, whereas physiological measures (e.g., EEG) tended to correlate with pain outcomes. We have also added an interpretation of this discrepance to the Discussion section. The following sentences was added:

“3.4 Association between sleep and pain outcomes

Although a meta-analysis was not conducted, a narrative summary of the included studies reveals distinct patterns in the relationship between sleep and pain.

“Furthermore, our review identified a discrepancy in the results derived from different objective modalities. While movement-based assessment (e.g., actigraphy) often failed to correlate with pain, physiological measures (e.g., EEG, heart rate) consistently showed significant associations. This suggests that while pain may not always disrupt gross body movements during sleep, it likely impacts physiological sleep architecture and autonomic regulation.”

Regarding the summary matrix, we have created a new table (Table 2) that maps the identified assessment tools to specific pain domains: Pain Intensity, Interference/Disability, Pain Quality, Psychosocial Factors, and Quantitative Sensory Testing. As suggested, this table presents the frequencies of use for each instrument within these domains. Please note that the Brief Pain Inventory (BPI) was categorized into both “Pain Intensity” and “Interference” domains, as it assesses both severity and impact on daily function.

2 ^nd Review: The addition of section 3.4 adds important context to the manuscript. Our concerns are sufficiently addressed here.

Discussion

Comment: The authors do well to highlight the heterogeneity in approach and the need for more standardized study design combining objective and subjective measures. However, I would like to see more discussion of what we do know about the relationship between sleep and pain [Reference 1], the potential impact of sleep deprivation on pain scores (PMID: 36334461) and hypothesize on mechanisms that may link the disorders [Reference 2].

References

1. Haack M, Simpson N, Sethna N, Kaur S, et al.: Sleep deficiency and chronic pain: potential underlying mechanisms and clinical implications. Neuropsychopharmacology. 2020; 45 (1): 205-216 Publisher Full Text

2. Chang J, Fu S, Li X, Li S, et al.: The differential effects of sleep deprivation on pain perception in individuals with or without chronic pain: A systematic review and meta-analysis. Sleep Medicine Reviews. 2022; 66. Publisher Full Text

Response:

Thank you for your valuable feedback. We agree that elaborating on the established relationship and underlying mechanisms provides crucial context for our findings. We have revised the Discussion section to incorporate the suggested references. Specifically, we have expanded the paragraph discussing the sleep-pain interaction to explicitly address:

The bidirectional nature of the relationship (Finan et al., 2013)

Experimental evidence showing that sleep deprivation significantly increases pain sensitivity (Chang et al., 2022)

Hypothesized neurobiological mechanisms, such as central sensitization and impaired descending pain inhibition (Haack et al., 2020; Nijs et al., 2018)

In accordance with these revisions, we have updated the reference list. The following sentences and references were added:

“Current evidence emphasizes a strong bidirectional relationship between sleep and pain, with sleep disturbances often predicting future pain severity more robustly than pain predicts sleep problems. ⁶ Experimental studies have further demonstrated that sleep deprivation directly exacerbates pain perception, lowering pain thresholds and increasing hyperalgesia ¹²¹ (new ref). These interactions are hypothesized to be mediated by shared neurobiological mechanisms, particularly central sensitization and impairments in descending pain inhibitory pathways, which nociceptive signaling. ^122,123 Incorporating objective sleep assessments and multidimensional pain measures into research and practice will enhance the quality of evidence and support the development of precision medicine approaches tailored to individual patient needs.”

“121 Chang JR, Fu SN, Li X, et al. The differential effects of sleep deprivation on pain perception in individuals with or without chronic pain: A systematic review and meta-analysis. Sleep Med Rev. 2022;66:101695. 36334461 10.1016/j.smrv.2022.101695”

“123 Nijs J, Mairesse O, Neu D, et al.: Sleep Disturbances in Chronic Pain: Neurobiology, Assessment, and Treatment in Physical Therapist Practice. Phys. Ther.2018;98:325–335. 29425327 10.1093/ptj/pzy020”

2 ^nd Review: We appreciate the addition of a mechanistic discussion of the b-directional. While it would be possible to have more depth, in the context of this manuscript, the above description sufficiently describes the underlying pathophysiology.

These revisions improve the clarity, methodological transparency, and interpretability of our review.

Overall 2 ^nd Review: The authors have sufficiently addressed our concerns regarding the methodology, description of the results, and the depth of the discussion. We believe the manuscript is now suitable for Indexing.

Are the rationale for, and objectives of, the Systematic Review clearly stated?

Yes

Is the statistical analysis and its interpretation appropriate?

Yes

If this is a Living Systematic Review, is the ‘living’ method appropriate and is the search schedule clearly defined and justified? (‘Living Systematic Review’ or a variation of this term should be included in the title.)

Not applicable

Are sufficient details of the methods and analysis provided to allow replication by others?

Yes

Are the conclusions drawn adequately supported by the results presented in the review?

Partly

Reviewer Expertise:

Sleep medicine, chronic pain, anesthesiology

We confirm that we have read this submission and believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

10.5256/f1000research.192814.r414411

Reviewer response for version 3

Neilson

Brett D

1 Referee https://orcid.org/0000-0002-3904-0160 1Hawai'i Pacific University, Hawaii, USA

Competing interests: No competing interests were disclosed.

2 1 2026

2026

recommendation

approve

Thank you to the authors for addressing my prior concerns and recommendations. No further feedback is required at this stage.

Are the rationale for, and objectives of, the Systematic Review clearly stated?

Yes

Is the statistical analysis and its interpretation appropriate?

Yes

Not applicable

Are sufficient details of the methods and analysis provided to allow replication by others?

Yes

Are the conclusions drawn adequately supported by the results presented in the review?

Yes

Reviewer Expertise:

Physical therapy researcher whose scholarly agenda is focused on the intersection of sleep and pain. I believe I am well qualified to review and approve this manuscript.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

10.5256/f1000research.188083.r421813

Reviewer response for version 2

Martins

Yuri Chaves

1 Referee https://orcid.org/0000-0003-4220-4979 Murin

Peyton

Competing interests: No competing interests were disclosed.

6 11 2025

2025

recommendation

approve-with-reservations

The authors provide a systematic review looking at the relationship between sleep and chronic pain. The study follows JBI guidance, is OSF-registered, adheres to PRISMA-ScR, and synthesizes 81 studies from a multi-database search (finalized March 29, 2024). They use a robust AI assisted approach to identify articles meeting all screening, inclusion, and exclusion criteria. They find significant heterogeneity in measures for both pain and sleep disorders, highlighting a need for more consistency in study design/approach, a well-documented problem within chronic pain.

Introduction:

The authors summarize the background transitioning from chronic pain to sleep disorders. Identify the high prevalence of sleep disorders and chronic pain. Address the relationship between sleep and other comorbidities including pain and identify a gap in the literature.

Minor: The transition between pain to chronic pain could be smoother. Would recommend rewording to allow for better flow/cohesion.

Methods:

Approach is appropriate. Inclusion and exclusion criteria are appropriate. Use of AI is appropriate and documented.

You transparently describe using ChatGPT-4o and NotebookLM with human verification. To enhance reproducibility, please (i) provide the exact extraction template (e.g., the Excel column headings) in the OSF repository and (ii) add one or two concrete examples of verification checks you performed (e.g., double-checking instrument counts against full texts).

Results:

3.1 : No concerns

3.2: Would recommend including more robust analysis on the gender distribution, age, pain type. Would recommend adding a table to summarize this data.

3.3: While this is not a meta-analysis (and as such, there is not a need for formal analysis), it would strengthen the results to have a summary of findings in the studies (i.e. did pain scores and sleep scores correlate)? In addition, for pain outcomes, you note the predominance of NRS/VAS and BPI. Consider adding a summary matrix (main text or supplement) mapping pain domains (intensity, interference/disability, psychosocial, sensitization, QST) to the instruments encountered, indicating frequencies (some of this is described narratively on page 6)

Discussion:

The authors do well to highlight the heterogeneity in approach and the need for more standardized study design combining objective and subjective measures. However, I would like to see more discussion of what we do know about the relationship between sleep and pain [Reference 1], the potential impact of sleep deprivation on pain scores (PMID: 36334461) and hypothesize on mechanisms that may link the disorders [Reference 2].

Are the rationale for, and objectives of, the Systematic Review clearly stated?

Yes

Is the statistical analysis and its interpretation appropriate?

Yes

Not applicable

Are sufficient details of the methods and analysis provided to allow replication by others?

Yes

Are the conclusions drawn adequately supported by the results presented in the review?

Partly

Reviewer Expertise:

Sleep medicine, chronic pain, anesthesiology

We confirm that we have read this submission and believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however we have significant reservations, as outlined above.

References 1

: Sleep deficiency and chronic pain: potential underlying mechanisms and clinical implications. Neuropsychopharmacology .2020;45(1) : 10.1038/s41386-019-0439-z 205-216

10.1038/s41386-019-0439-z

: The differential effects of sleep deprivation on pain perception in individuals with or without chronic pain: A systematic review and meta-analysis. Sleep Medicine Reviews .2022;66: 10.1016/j.smrv.2022.101695

10.1016/j.smrv.2022.101695

Tanaka

Katsuyoshi

Competing interests: No competing interests were disclosed.

2 12 2025

Response to Yuri Chaves Martins

We greatly appreciate the reviewer’s insightful comments. Our responses to your comments are given below.

Introduction

Comment: The transition between pain to chronic pain could be smoother. Would recommend rewording to allow for better flow/cohesion.

Responses:

Methods

Responses:

We sincerely thank the reviewer for these valuable and constructive comments.

Results

Comment: 3.2: Would recommend including more robust analysis on the gender distribution, age, pain type. Would recommend adding a table to summarize this data.

Response:

Thank you for this constructive suggestion. We agree that providing a summary of the associations and a structured mapping of assessment tools significantly strengthens the manuscript.

“3.4 Association between sleep and pain outcomes

Although a meta-analysis was not conducted, a narrative summary of the included studies reveals distinct patterns in the relationship between sleep and pain.

Discussion

References

Response:

The bidirectional nature of the relationship (Finan et al., 2013)

Experimental evidence showing that sleep deprivation significantly increases pain sensitivity (Chang et al., 2022)

Hypothesized neurobiological mechanisms, such as central sensitization and impaired descending pain inhibition (Haack et al., 2020; Nijs et al., 2018)

In accordance with these revisions, we have updated the reference list. The following sentences and references were added:

These revisions improve the clarity, methodological transparency, and interpretability of our review.

10.5256/f1000research.182981.r399708

Reviewer response for version 1

Neilson

Brett D

1 Referee https://orcid.org/0000-0002-3904-0160 1Hawai'i Pacific University, Hawaii, USA

Competing interests: No competing interests were disclosed.

27 8 2025

2025

recommendation

approve-with-reservations

General Comments

This is a well-organized and clearly written scoping review (ScR) that addresses an important topic: the methods used to assess sleep and pain-related outcomes in individuals with chronic pain. The authors articulate a clear aim, follow a structured methodology, and present their findings with clarity. The manuscript would benefit from some clarifications and adjustments, particularly regarding terminology, methodological rigor, and reporting of results.

Abstract

The abstract is clear and concisely conveys the purpose and scope of the review.

The aim is well articulated.

No major revisions are needed for the abstract.

Introduction

The introduction is generally well written and provides appropriate context for the review. However, the use of inconsistent terminology for sleep-related issues may create confusion for the reader.

Recommendations:

Consider defining or consistently using terms such as “sleep problems,” “sleep disorders,” “compromised sleep,” and “sleep disturbances.”

Reference standardized definitions or diagnostic criteria where appropriate.

The statement: “The financial impact of chronic pain, including healthcare expenses and reduced work efficiency, is substantial.” should be supported with a citation. There is robust literature available on this topic.

Methods

The methodology appears rigorous, with an extensive search strategy across nine databases and inclusion of grey literature. However, a few clarifications and enhancements are suggested.

Recommendations:

Clarify adherence to all eight JBI steps, or note deviations.

Consider referencing the PRISMA-ScR checklist.

Search was completed in March 2024; consider updating if required by the journal.

Describe how ChatGPT-4o outputs were validated to ensure data accuracy.

Mention if data extraction software (e.g., Covidence) was used.

Include a sample search strategy for at least one database to enhance reproducibility of the review process.

Results

The results are clearly reported, with appropriate use of tables and figures.

Recommendation:

Provide percentages or refer to Figure 2 when discussing the use of PSQI and ISI.

Discussion

The discussion section is well constructed and effectively summarizes the key findings of the review.

Recommendations:

Use consistent and defined terminology for sleep-related terms.

Discuss how inadequate sleep assessment may affect intervention outcomes, given the bidirectional relationship between sleep and pain.

Conclusions

The conclusions are appropriate and do not overreach.

Recommendation:

Replace the term “content” with “characteristics” or “types” where appropriate.

Summary of Key Revisions for Authors

Ensure consistent and defined terminology for sleep-related dysfunction.

Add citation(s) to support claims regarding the financial impact of chronic pain.

Clarify adherence to JBI methodology and consider referencing PRISMA-ScR.

Provide detail on how ChatGPT-4o was used and how its outputs were validated.

Include numerical data or clear reference to figures for key result statements.

Explore how measurement inconsistencies could impact intervention outcomes.

Replace the term “content” with “characteristics” or “types” where appropriate.

Acknowledge that the PRISMA-ScR checklist was used, as mentioned in the Data Availability section. Consider integrating this earlier in the Methods to emphasize adherence to reporting standards.

Include a sample search strategy for at least one database to enhance reproducibility of the review process.

Are the rationale for, and objectives of, the Systematic Review clearly stated?

Yes

Is the statistical analysis and its interpretation appropriate?

Yes

Not applicable

Are sufficient details of the methods and analysis provided to allow replication by others?

Yes

Are the conclusions drawn adequately supported by the results presented in the review?

Yes

Reviewer Expertise:

I am a physical therapist educator in the Hawai‘i Pacific University Doctor of Physical Therapy Program. My research focuses on the intersection of sleep and pain, with several publications in this area. I have previously published two ScRs on a similar topic: Feda J, Miller T, Young JL, Neilson B, Rhon DI. Measures of sleep are not routinely captured in trials assessing treatment outcomes in knee osteoarthritis - A scoping systematic review and call to action. Osteoarthr Cartil Open. 2023;(100400):100400. Neilson BD, Dickerson C, Young JL, Shepherd MH, Rhon DI. Measures of sleep disturbance are not routinely captured in trials for chronic low back pain: a systematic scoping review of 282 trials. J Clin Sleep Med. 2023;19(11):1961–1970.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

Tanaka

Katsuyoshi

Competing interests: No competing interests were disclosed.

12 9 2025

Response to Brett D Neilson

We greatly appreciate the reviewer’s insightful comments. Our responses to your comments are given below.

Introduction

Comment: The introduction is generally well written and provides appropriate context for the review. However, the use of inconsistent terminology for sleep-related issues may create confusion for the reader.

Recommendations:

Consider defining or consistently using terms such as “sleep problems,” “sleep disorders,” “compromised sleep,” and “sleep disturbances.”

Reference standardized definitions or diagnostic criteria where appropriate.

Responses:

We appreciate the reviewer’s suggestion. To avoid confusion, we have revised the manuscript to use the term “sleep disturbances” consistently when referring to general sleep-related dysfunction. In the Introduction, we also added a clarifying statement with references to the International Classification of Sleep Disorders, Third Edition (ICSD-3).

Additionally, as recommended, we have added a citation to support the statement regarding the financial impact of chronic pain.

We have added the references as follow:

“ Rikard SM, Strahan AE, Schmit KM, Guy GP Jr. Chronic pain among adults - United States, 2019-2021. MMWR Morb Mortal Wkly Rep. 2023;72:379-385. ”

“ Sateia MJ. International classification of sleep disorders-third edition: highlights and modifications. Chest. 2014;146:1387-1394. ”

Methods

Comment: The methodology appears rigorous, with an extensive search strategy across nine databases and inclusion of grey literature. However, a few clarifications and enhancements are suggested.

Recommendations:

Clarify adherence to all eight JBI steps, or note deviations.

Consider referencing the PRISMA-ScR checklist.

Search was completed in March 2024; consider updating if required by the journal.

Describe how ChatGPT-4o outputs were validated to ensure data accuracy.

Mention if data extraction software (e.g., Covidence) was used.

Include a sample search strategy for at least one database to enhance reproducibility of the review process.

Responses:

We appreciate the reviewer’s suggestions. We have responded to each recommendation as below:

1. Adherence to JBI steps

We clarified that our review followed all eight steps of the Joanna Briggs Institute (JBI) methodology for scoping review without deviation. We revised the sentence as below:

“This ScR was conducted according to the Joanna Briggs Institute methodology for scoping reviews, following all eight recommended steps without deviation.”

2. PRISMA-ScR checklist

We appreciate the reviewer’s recommendation. In addition to noting in the Data Availability section that the completed PRISMA-ScR checklist is provided, we have now explicitly stated in the Methods section that the review adhered to the PRISMA-ScR checklist. The following sentence was added:

“This review also adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping reviews (PRISMA-ScR) checklist.”

3. Search update

We appreciate the reviewer’s suggestion. The final comprehensive search was conducted on March 29, 2024, as already noted in the Methods section. Given the publication model of F1000Research, the Version 1 preprint of this review was made publicly available shortly after submission, and thus the search reflects the literature available at that time. As the journal does not require an updated search for scoping reviews, we have not repeated the search. Nevertheless, we have noted in the Discussion that more recent studies may not have been captured. The following sentence was added:

“A limitation of this review is that the literature search was last conducted in March 2024, and more recent studies may not have been capture.”

4. Use of ChatGPT-4o

We thank the reviewer for this important comment. In the revised manuscript, we have clarified how ChatGPT-4o and NotebookLM were used during data extraction. These AI tools were used to facilitate the extraction and preliminary organization of information from the included studies. All outputs were reviewed and verified against the original studies by the first author (K.T.) to ensure accuracy. Thus, while AI was utilized as part of the data extraction process, no information was included without human verification, and all final decisions were made by the research team. The following sentence was added:

“These AI tools were used to facilitate the extraction and preliminary organization of information from the included studies. All outputs generated by AI were reviewed and verified against the original sources by the first author (K.T.) to ensure accuracy, and all final decisions were made by the research team.”

5. Data extraction software

We thank the reviewer’s helpful comment. In the revised manuscript, we have clarified that no dedicated systematic review software such as Covidence was used for data extraction. Instead, data were extracted using Microsoft Excel, supported by ChatGPT-4o and NotebookLM, with all outputs reviewed and verified by the first author (K.T.) to ensure accuracy. The following sentence was added:

“No dedicated systematic review software (e.g., Covidence) was used for data extraction.”

6. Sample search strategy

We thank the reviewer’s valuable suggestion. To ensure reproducibility, we have clarified in the Methods section that the full PubMed search strategy is provided as Supplementary Table S1. The sentence was revised as follow:

“The text words found in the titles and abstracts of relevant articles, along with the index terms used to describe the articles, were used to develop a comprehensive search strategy across nine databases (the complete PubMed search strategy is provided in Table S1).”

Results

Comment: The results are clearly reported, with appropriate use of tables and figures.

Recommendation:

Provide percentages or refer to Figure 2 when discussing the use of PSQI and ISI.

Response:

We appreciate the reviewer’s suggestion. To improve clarity, we have added the frequencies and percentages of studies that used the PSQI and ISI, and we now reference Figure 2 in the text. We revised the sentences as follow:

“ The Pittsburgh Sleep Quality Index (PSQI) (45 of 81 studies, 55.6%) and Insomnia Severity Index (ISI) (21 of 81 studies, 25.9%) were the most commonly used tools for the assessment of sleep problems (Figure 2).”

Discussion

Comment: The discussion section is well constructed and effectively summarizes the key findings of the review.

Recommendations:

Use consistent and defined terminology for sleep-related terms.

Discuss how inadequate sleep assessment may affect intervention outcomes, given the bidirectional relationship between sleep and pain.

Responses:

We appreciate the reviewer’s comments. In the revised manuscript, we have ensured consistent use of the term “sleep disturbances” in the Discussion section. We have also added text to highlight how inadequate or inconsistent sleep assessment may influence the interpretation of intervention outcomes, given the bidirectional relationship between sleep and pain. The following sentences were added:

“Given the bidirectional relationship between sleep and pain, inadequate or inconsistent assessment of sleep disturbances may obscure the true effects of intervention for chronic pain. This limitation could lead to underestimation or misinterpretation of treatment efficacy and reduce the comparability of results across studies. Addressing this issue is essential for developing effective multimodal interventions and advancing precision medicine.”

Conclusions

Comment: The conclusions are appropriate and do not overreach.

Recommendation:

Replace the term “content” with “characteristics” or “types” where appropriate.

Response:

We appreciate the reviewer’s suggestion. In the revised manuscript, we have replaced the term content with characteristics in the Conclusions section to improve clarity as follows:

“This ScR highlights the imbalance in the characteristics of sleep and pain assessments, indicating the need for a more comprehensive evaluation of sleep disturbances and pain-related outcomes.”

Summary of Key Revisions

We sincerely thank the reviewer for the thorough and constructive feedback. In response to the comments, we have made the following key revisions to the manuscript:

Terminology: We ensured consistent use of the term sleep disturbances across the Introduction and Discussion, and provided standardized definitions with citations to the ICSD-3.

Introduction: We added a citation to support the statement regarding the financial impact of chronic pain.

Methods:

Clarified adherence to all eight JBI steps.

Explicitly stated adherence to the PRISMA-ScR checklist.

Explained that the final search was conducted in March 2024 and noted this as a limitation.

Clarified how ChatGPT-4o and NotebookLM were used to facilitate data extraction, and described human verification procedures.

Stated that no dedicated systematic review software (e.g., Covidence) was used.

Specified that the complete PubMed search strategy is provided in Supplementary Table S1.

Results: Added the frequencies and percentages of studies using the PSQI and ISI, with reference to Figure 2.

Discussion: Ensured consistent terminology and added a statement on how inadequate sleep assessment may affect the interpretation of intervention outcomes, given the bidirectional relationship between sleep and pain.

Conclusions: Replaced the term content with characteristics for improved clarity.

These revisions improve the clarity, methodological transparency, and interpretability of our review.