Keywords
pain, sleep disturbances, assessment tools
-
Views
-
Downloads
How to cite this article
Tanaka K, Isaji Y, Suzuki K et al. Imbalances in the Content of Sleep and Pain Assessments in Patients with Chronic Pain: A Scoping Review [version 3; peer review: 2 approved with reservations]. F1000Research 2025, 14:605 (https://doi.org/10.12688/f1000research.166110.3)
NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article.
Export Citation
Sciwheel
EndNote
Ref. Manager
Bibtex
ProCite
Sente
▬
✚
Systematic Review
Revised
Imbalances in the Content of Sleep and Pain Assessments in Patients with Chronic Pain: A Scoping Review
[version 3; peer review: 2 approved with reservations]
PUBLISHED 12 Dec 2025
OPEN PEER REVIEW
REVIEWER STATUS
This article is included in the Circadian Clocks in Health and Disease collection.
Abstract
Corresponding author:
Katsuyoshi Tanaka
Competing interests:
No competing interests were disclosed.
Grant information:
The author(s) declared that no grants were involved in supporting this work.
Copyright:
© 2025 Tanaka K et al.
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
How to cite: Tanaka K, Isaji Y, Suzuki K et al. Imbalances in the Content of Sleep and Pain Assessments in Patients with Chronic Pain: A Scoping Review [version 3; peer review: 2 approved with reservations]. F1000Research 2025, 14:605 (https://doi.org/10.12688/f1000research.166110.3)
First published: 20 Jun 2025, 14:605 (https://doi.org/10.12688/f1000research.166110.1)
Latest published: 12 Dec 2025, 14:605 (https://doi.org/10.12688/f1000research.166110.3)
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.
See the authors' detailed response to the review by Yuri Chaves Martins and Peyton Murin
See the authors' detailed response to the review by Brett D Neilson
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%) |
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%) |
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.
Download
Export To
metrics
| Views | Downloads | |
|---|---|---|
| F1000Research | - | - |
|
PubMed Central
Data from PMC are received and updated monthly.
|
- | - |
Citations
CITE
how to cite this article
Tanaka K, Isaji Y, Suzuki K et al. Imbalances in the Content of Sleep and Pain Assessments in Patients with Chronic Pain: A Scoping Review [version 3; peer review: 2 approved with reservations]. F1000Research 2025, 14:605 (https://doi.org/10.12688/f1000research.166110.3)
NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article.
track
receive updates on this article
Track an article to receive email alerts on any updates to this article.
Open Peer Review
Current Reviewer Status:
Key to Reviewer Statuses
VIEW
HIDE
ApprovedThe paper is scientifically sound in its current form and only minor, if any, improvements are suggested
Approved with reservations
A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.
Not approvedFundamental flaws in the paper seriously undermine the findings and conclusions
Version 2
VERSION 2
PUBLISHED 15 Sep 2025
Revised
Views
16
How to cite this report:
Martins YC and Murin P. Reviewer Report For: Imbalances in the Content of Sleep and Pain Assessments in Patients with Chronic Pain: A Scoping Review [version 3; peer review: 2 approved with reservations]. F1000Research 2025, 14:605 (https://doi.org/10.5256/f1000research.188083.r421813)
The direct URL for this report is:
https://f1000research.com/articles/14-605/v2#referee-response-421813
https://f1000research.com/articles/14-605/v2#referee-response-421813
NOTE: it is important to ensure the information in square brackets after the title is included in this citation.
Reviewer Report 06 Nov 2025
Yuri Chaves Martins,
Anesthesiology, Saint Louis University School of Medicine (Ringgold ID: 12274), St. Louis, Missouri, USA
Peyton Murin,
Neurology, Saint Louis University School of Medicine (Ringgold ID: 12274), St. Louis, Missouri, USA
Approved with Reservations
VIEWS 16
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
... Continue reading
CITE
HOW TO CITE THIS REPORT
Martins YC and Murin P. Reviewer Report For: Imbalances in the Content of Sleep and Pain Assessments in Patients with Chronic Pain: A Scoping Review [version 3; peer review: 2 approved with reservations]. F1000Research 2025, 14:605 (https://doi.org/10.5256/f1000research.188083.r421813)
The direct URL for this report is:
https://f1000research.com/articles/14-605/v2#referee-response-421813
https://f1000research.com/articles/14-605/v2#referee-response-421813
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
-
Author Response 12 Dec 2025Katsuyoshi Tanaka, Department of Physical Therapy, School of Health Sciences, Bukkyo University, Kyoto, 604-8418, Japan12 Dec 2025Author ResponseResponse 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 ... Continue reading
COMMENTS ON THIS REPORT
-
Author Response 12 Dec 2025Katsuyoshi Tanaka, Department of Physical Therapy, School of Health Sciences, Bukkyo University, Kyoto, 604-8418, Japan12 Dec 2025Author ResponseResponse 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 ... Continue reading
Version 1
VERSION 1
PUBLISHED 20 Jun 2025
Views
18
How to cite this report:
Neilson BD. Reviewer Report For: Imbalances in the Content of Sleep and Pain Assessments in Patients with Chronic Pain: A Scoping Review [version 3; peer review: 2 approved with reservations]. F1000Research 2025, 14:605 (https://doi.org/10.5256/f1000research.182981.r399708)
The direct URL for this report is:
https://f1000research.com/articles/14-605/v1#referee-response-399708
https://f1000research.com/articles/14-605/v1#referee-response-399708
NOTE: it is important to ensure the information in square brackets after the title is included in this citation.
Reviewer Report 27 Aug 2025
Approved with Reservations
VIEWS 18
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 ... Continue reading
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 ... Continue reading
CITE
HOW TO CITE THIS REPORT
Neilson BD. Reviewer Report For: Imbalances in the Content of Sleep and Pain Assessments in Patients with Chronic Pain: A Scoping Review [version 3; peer review: 2 approved with reservations]. F1000Research 2025, 14:605 (https://doi.org/10.5256/f1000research.182981.r399708)
The direct URL for this report is:
https://f1000research.com/articles/14-605/v1#referee-response-399708
https://f1000research.com/articles/14-605/v1#referee-response-399708
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
-
Author Response 23 Sep 2025Katsuyoshi Tanaka, Department of Physical Therapy, School of Health Sciences, Bukkyo University, Kyoto, 604-8418, Japan23 Sep 2025Author ResponseResponse 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 ... Continue reading
COMMENTS ON THIS REPORT
-
Author Response 23 Sep 2025Katsuyoshi Tanaka, Department of Physical Therapy, School of Health Sciences, Bukkyo University, Kyoto, 604-8418, Japan23 Sep 2025Author ResponseResponse 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 ... Continue reading
Comments on this article Comments (0)