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. 2026 Aug 26;21(8):e0356365. doi: 10.1371/journal.pone.0356365

Prevalence of nicotine, alcohol, and cannabis use disorders among adults with chronic pain: Protocol for a systematic review and meta-analysis

Andrew H Rogers 1,2,*, Emily L Zale 3, Jessica M Powers 4,5, Yohannes W Woldeamanuel 6, Nell Aronoff 7, Laurel Mueller 7, Chung Jung Mun 8,9
Editor: Marianna Mazza10
PMCID: PMC13514021  PMID: 42647479

Abstract

Chronic pain is a significant public health problem associated with substantial medical expenditures, decreased quality of life, and physical and mental health comorbidities. Substance use is an important clinical consideration in pain, as substance use has been identified as both an antecedent and consequence of chronic pain. The majority of research on substance use and chronic pain has focused on opioid use, and although commonly used, alcohol, nicotine, and cannabis have received considerably less research attention. While there are empirical studies that examine the impact of non-opioid substance use in the context of chronic pain, the overall prevalence rates of nicotine, alcohol, and cannabis use disorders among adults with chronic pain have not been well-documented. Therefore, a systematic review and meta-analysis that characterizes the prevalence rates of non-opioid substance use disorders among adults with chronic pain is urgently needed. The current paper outlines the protocol for a systematic review and meta-analysis. It will include studies of adults with chronic pain that report on nicotine, alcohol, or cannabis use disorders, as well as problematic use (including co-use where available). The following databases will be searched: PubMed, Embase (Elsevier), Web of Science Core Collection, CINAHL (EBSCO), and PsycINFO (EBSCO). A team of trained research staff will conduct study screening and data extraction. Analyses will focus on pooled prevalence estimates of substance use disorders as primary outcomes and problematic use as secondary outcomes, with planned sub-group analyses and strategies to mitigate potential sources of bias. The results of this review will provide valuable clinical information on the scope of non-opioid substance use disorders, helping to guide future research as well as inform clinical and policy-level decision making.

Introduction

Chronic pain, defined as pain that has been present for ≥3 months [1], negatively impacts a significant proportion of the population worldwide [2–4]. The estimated prevalence of chronic pain differs based on country, definition, and assessment method. Yet, primary and meta-analytic research suggests that between one-fifth and one-third of adults worldwide experience chronic pain [5–8]. These often include chronic overlapping pain conditions, a group of frequently co-occurring pain conditions that include chronic low back pain, irritable bowel syndrome, chronic pelvic pain, fibromyalgia, and migraine, among others [9–12]. Chronic pain is associated with significant medical, psychiatric, and economic costs of upwards of $1 trillion a year [13,14]. The impact of chronic pain extends beyond economic and healthcare, negatively impacting quality of life [15]. Chronic pain is associated with increased rates of mental health symptoms and disorders [16,17], as well as substance use disorders [18,19].

Substance use in the context of chronic pain is of particular clinical importance given pain has been identified as a potent motivator for substance use [20,21]. Substance use often serves a regulatory function for managing multiple facets of pain [22], amplifying negative pain-related outcomes, and contributing to adverse health consequences [19]. Further, substance use disorders (SUDs) have been documented in higher prevalence rates among individuals with chronic pain than those without, conferring risk for poorly managed pain and problematic substance use [23–26]. To date, most attention has been focused on opioids, where prescriptions for pain have been regarded as primary drivers of persistent opioid use, the opioid epidemic, and related consequences [27,28]. Meta-analytic evidence provides support for overall higher rates of opioid use disorder among adults with chronic pain than those without [29–32]. Similarly, nearly half of all individuals receiving treatment for opioid use disorder also meet criteria for chronic pain [33–35], which further hinders opioid use disorder recovery processes [36]. Emerging evidence indicates that most widely used non-opioid substances, specifically nicotine, alcohol, and cannabis use, are frequently used for the self-management of chronic pain. In addition, these substances are often used with opioids, and their chronic or problematic use (i.e., use that engenders increased risks for negative physiological or psychosocial consequences) is similarly linked to negative health outcomes and decreased quality of life [29,37]. Challenges in accurately capturing the extent to which individuals with chronic pain have SUDs involving these non-opioid substances have limited the empirical literature in this area, contributing to the wide variability in estimates of prevalence rates.

Theoretical models of chronic pain and substance use posit a bidirectional association in which pain motivates substance use, while chronic substance use exacerbates pain through several biopsychosocial mechanisms [38–42]. Adults with chronic pain are more likely to use nicotine, alcohol, and cannabis compared to those without chronic pain [43–45], and similarly, high rates of chronic pain are reported among individuals who use these substances [43,44,46,47]. Despite these empirical data, to date, the overall prevalence of nicotine, alcohol, and cannabis use disorders among adults with chronic pain has not been well quantified. A systematic review and meta-analysis published in 2011 found that between 3% and 48% of adults with chronic pain met criteria for any SUD, including opioid use disorder [23]. However, not only was it conducted more than 10 years ago, but the meta-analysis also excluded studies of nicotine use disorder, and the searches could have been more comprehensive.

The current state of knowledge regarding the prevalence rates of nicotine, alcohol, and cannabis use disorders, along with problematic use, among adults with chronic pain is limited in scope and imprecise. There is urgent need for clearer understanding of these prevalence rates, as they can inform the development of both treatment and prevention programs and policy efforts addressing the intersection of chronic pain and non-opioid SUDs. It is also important to quantify the rates of problematic use, as even use that does not meet diagnostic criteria for a SUD can have long term physiological and psychosocial consequences [48]. Accordingly, the proposed systematic review and meta-analysis aims to fill this gap by consolidating existing knowledge and providing estimates of nicotine, alcohol, and cannabis use disorders (primary outcome), as well as estimates of problematic substance use (secondary outcome), among adults chronic pain conditions.

Materials and methods

The protocol was guided by the Preferred Reporting Items for Systematic Review and Meta-Analyses for Protocols (PRISMA-P) checklist (see appendix for checklist; 49). The protocol was pre-registered with the International Prospective Register of Systematic Reviews (PROSPERO) on November 10, 2024 (updated on July 24, 2026 prior to the initiation of the search and data extraction), under registration number CRD42024596125. Currently, the search strategy has been generated and piloted, but the full searches have not been conducted. It is expected that, following the searches, data extraction and results will be available within 12 months.

Eligibility criteria

For full inclusion and exclusion criteria, see S1 Table. Primary study outcomes will focus on nicotine, alcohol, and cannabis use disorders, and secondary outcomes will focus on problematic use of these substances (see S2 Table for definitions). Studies that are focused on exclusively cancer-related pain will be excluded.

Information sources

The following types of studies will be included: original/empirical data, such as cross-sectional studies, cohort studies, and both non-randomized and randomized controlled trials. For longitudinal and interventional studies, only baseline assessments prior to randomization/intervention exposure will be used, rather than mid-treatment, post-treatment or incidence data. The following types of studies will be excluded: literature reviews, systematic reviews, case reports, protocols, commentaries, conference abstracts, opinions, and letters. Additionally, studies that specifically recruit participants based on SUD criteria will be excluded to avoid inflated prevalence estimates.

Search strategy

The following five databases will be searched for potential studies: PubMed, Embase (Elsevier), Web of Science Core Collection, CINAHL (EBSCO), and PsycINFO (EBSCO). The searches were designed by two librarians (NA and LM) to capture papers about adults that experience chronic pain conditions [11,12,49] and report problematic nicotine, alcohol, or cannabis use or use disorders. The searches have the following general structure: chronic pain AND ((substance AND misuse) OR substance misuse). They include broad terms like chronic pain and persistent pain, as well as specific chronic overlapping pain conditions [50]. Keywords and subject headings were employed to help ensure comprehensiveness. Six articles were used as seed articles [51–56]. Seed articles are those the research team anticipates including in the review, and the goal is to design searches that successfully retrieve these articles. One seed article did not come up in any of the searches because it did not contain any misuse-related terms, despite the inclusion of a comprehensive set of synonyms reflecting aspects of problematic use. Publication types will be restricted in Embase (article, article in press, clinical trial), Web of Science Core Collection (article or early access), CINAHL (academic journals), and PsycINFO (academic journals) in accordance with our inclusion and exclusion criteria. The full PubMed search strategy is in S1 Appendix. This search strategy serves as the template for the other four databases.

Study selection/article screening

Study citations will be exported to Covidence. After duplicates have been removed in Covidence, titles and abstracts will be screened by two independent reviewers. Any disagreements on article inclusion will be resolved by a third reviewer. Once the potentially relevant articles are identified, full texts will be retrieved and compared to the full inclusion and exclusion criteria by two independent reviewers. For papers in languages other than English, the abstracts will be reviewed using machine translation tools (e.g., Google Translate) for usable data during the full-text screening stage. Due to restrictions in funding for formal translation services, articles that appear to meet inclusion criteria that the team is unable to translate will be excluded. For these articles, we will 1) indicate in the PRISMA flow diagram how many of these articles were identified, and 2) provide a summary table in the appendix that includes, when available from the abstract, the study country, pain condition, substance type, and reported prevalence (excluding non-English full texts may be a source of language and regional bias. If a clear pattern is identified from these non-English articles, we will note this in the main text.). A table of these articles will be included in the appendix. Discrepancies will be resolved by a third reviewer. Any studies that do not meet the inclusion criteria will be excluded, and exclusion reasons will be documented in a PRIMSA flow diagram according to PRISMA 2020 reporting guidelines [57]. If the searches are older than 12 months, they will be re-run.

Data extraction and management

Once the list of included articles has been finalized, data will be extracted from each study by two independent coders. For each study, extracted data will include study details (author, year of publication), study characteristics (study location; sample size; sampling method; study design; study setting; demographics), pain characteristics (pain condition, intensity, duration, frequency), substance use characteristics (frequency and quantity of alcohol, nicotine, and/or cannabis use; prevalence rates of nicotine, alcohol, or cannabis use disorders; prevalence of problematic substance use, types of products for nicotine and cannabis; routes of administration for nicotine and cannabis; and method of assessment). Prevalence estimates for problematic substance use will only be derived from validated screening instruments with established cutoffs (e.g., AUDIT) and will also include the specific construct being assessed (e.g., hazardous use, misuse, etc.); studies that rely solely on author-defined thresholds for problematic substance use will not contribute to pooled prevalence estimates. Additionally, specific estimates of co-use (i.e., concurrent use disorders or problematic use involving multiple substances) will be extracted. Where sufficient data are available, co-use will also be examined in exploratory analyses; however, co-use estimates will not be included in the primary pooled prevalence analyses for individual substances.

Risk of bias assessment

Utilizing the Joanna Briggs Institute (JBI)’s Critical Appraisal Checklist for Studies Reporting Prevalence Data, two independent reviewers will evaluate the methodological quality of each study and assessing the risk of bias [58]. Any disagreements between the reviewers will be resolved through discussion and, when necessary, consultation with a third reviewer. However, risk of bias will not be interpreted solely on the basis of an overall summary score. In additional to conducting sensitivity analyses excluding studies judged to be at high risk of bias, we will report the individual JBI domain rating for each study included in the supplementary materials. This approach will assist with interpretation of the findings. In addition, to investigate the presence of small study publication bias, we will use the funnel plot and contoured funnel plot for a visual inspection of study bias [59], and Egger’s regression test for a statistical test of small study bias [60]. When Egger’s test is significant, suggesting the presence of small study publication bias, we will employ Duval and Tweedie’s trim and fill procedure [61], which calculates how many studies are missing, imputes effect sizes from the missing studies, and estimates what the effect size would have been if the missing studies had been included.

Data analysis and synthesis

Data analyses will be conducted using R to calculate the pooled prevalence point estimates (with 95% confidence intervals) of nicotine, alcohol, and cannabis use disorders (primary outcome) and problematic nicotine, alcohol, and cannabis use (secondary outcome) among individuals with chronic pain. To address assumptions of independence of each study, only one prevalence rate per substance will be included in the pooled analysis. When studies provide a total sample estimate, no additional subgroup prevalence rates will be extracted. If studies report multiple prevalence rates (e.g., subgroups) for the same substance, a single study-level prevalence estimate will be derived by aggregating subgroup data using sample size weighted estimates (i.e., total number of cases divided by the total sample size). This retains within-study information while minimizing bias associated with unweighted average of prevalence rates and ensures each study contributes only one independent estimate per substance [62]. This approach is in line with existing meta-analytic prevalence research [63–67]. We will also consider conducting sensitivity analyses using alternative strategies, including selecting the largest subgroup, as well as serially excluding each study to determine the influence of individual studies on the overall prevalence estimates. When studies report multiple thresholds (e.g., different severity cutoffs), we will prioritize estimates based on standard validated thresholds (e.g., AUDIT ≥8) or the threshold identified by the authors as primary. In terms of the time frame, where sufficient data are available, we will prioritize past year (or current) estimates for both SUD diagnoses and problematic use, given their greater clinical relevance and comparability across studies. Lifetime estimates will be analyzed separately and not pooled with past-year estimates.

Where sufficient data are available, co-use will also be examined in exploratory analyses; however, co-use estimates will not be included in the primary pooled prevalence analyses for individual substances. Because analyses focus on substance-specific prevalence, individuals who report multiple substances may contribute to more than one substance-specific analysis (e.g., both alcohol and nicotine). Importantly, individuals will not be counted more than once. We will descriptively report how co-use was defined in each of the estimates used. Further, in an effort to eliminate potentially duplicate study prevalence estimates, studies will be screened according to published recommendations [68], including examining the same first author, corresponding author, sample size, study year, study measures/prevalence rates, cohort or database name (when applicable), recruitment period, and other relevant study characteristics (e.g., geographic location). For studies that have been determined to be from the same sample and reporting the same prevalence outcome, only one independent estimate will be included in the meta-analysis, with preference given to the study with the largest eligible sample and/or the most comprehensive prevalence data relevant to the planned analysis.

Several sensitivity and moderator subgroup analyses will be examined based on available data. Specifically, point prevalence estimates will be examined as a function of study setting, pain characteristics, biological sex, study location, type of product (for nicotine and cannabis), route of administration (for nicotine and cannabis), medical vs. non-medical use and legal status (for cannabis where sufficient information is available), screening instrument for problematic use, study quality (utilizing the Joanna Briggs Institute Critical Appraisal Checklist for Studies Reporting Prevalence Data sum score), study type (e.g., cross-sectional, longitudinal), and age [58]. Additionally, we will include risk of bias scores in sensitivity analyses along with descriptive reporting.

For the meta-analysis, a random-effects model, using the restricted maximum likelihood (REML) estimator for between-study heterogeneity, will be used first to estimate the pooled prevalence rates for each outcome using generalized linear mixed models (GLMMs) with a binomial distribution and logit link [69,70]. Because this relies on a binomial distribution, variance-stabilizing transformations are not required [71]. To test the homogeneity assumption for meta-analyses, I² and τ2 will be examined. Based on prior research and recommendation, I² will not be interpreted using rigid thresholds, as very high I² values (e.g., > 90%) are common in prevalence meta-analyses and may not meaningfully distinguish heterogeneity [72]. Rather, I² will be interpreted in conjunction with τ2, prediction intervals, and the clinical and methodological comparability of included studies [72]. Quantitative synthesis will be undertaken only when studies are judged to be sufficiently comparable with respect to key conceptual characteristics, including the chronic pain population, substance definitions, measurement approach, and study designs [73–75]. If studies are judged to be too conceptually heterogeneous for a pooled prevalence estimate (determined by study team consensus), we will instead provide a narrative synthesis and visual presentation with the range of prevalence rates across studies. With substantial heterogeneity, we will interpret descriptive summaries rather than single estimates, emphasizing prediction intervals, subgroup patterns, and the limits of generalizability

To examine the effect of potential moderators on study heterogeneity, two types of moderator analyses will be conducted. First, for categorical moderators, sub-group analyses allowed for individual pooled random-effects correlations for each group studied, as well as a statistical test of between-study variability [65]. For continuous moderators, a meta-regression analysis will be conducted [76]. Pooled estimates will be presented using random-effects models even in the presence of substantial heterogeneity, but will be interpreted cautiously, as average prevalence across diverse contexts rather than precise summary values, including prediction intervals. If there is significant variability in the number of studies that include each moderator variable, not all studies will be included in each moderator analysis. While past research suggests that a minimum of two studies is needed to conduct a meta-analysis [77], we will adopt a more conservative threshold of five studies [78], given the random-effects model and the potential for significant within- and between-study heterogeneity. All subgroup and meta-regression analyses will be conducted based on a priori hypotheses to explore potential sources of heterogeneity. If heterogeneity is judged to be too substantial to support meaningful pooled estimates, we will supplement or replace pooled estimates with a narrative synthesis focused on the distribution and range of estimates across studies Fig 1.

Fig 1. Protocol Overview: Prevalence of Substance Use Disorders in Chronic Pain.

Fig 1

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Flow chart for meta analysis, guiding through steps to determine eligibility criteria, outcomes, analytic workflow, and individual analyses. Moderator and sensitivity analyses represent currently identified moderators. It is possible there will be additional moderators identified upon completion of the search and data extraction.

Ethics

Ethics approval is not required, as the study will rely on published data.

Discussion

The proposed study will address an important gap by providing a clearer and more accurate picture of nicotine, alcohol, and cannabis use disorders, as well as problematic use among adults with chronic pain. Although non-opioid substance use in this population is quite common, the prevalence of each corresponding use disorder remains poorly understood. The lack of research on prevalence of SUDs in chronic pain can detrimentally impact clinical care if providers underestimate or overlook substance use in the context of chronic pain management, or lack sufficient understanding of the underlying mechanisms, treatment options, and preventative approaches. The goal of this meta-analysis is to provide much-needed data for patients, providers, and policy makers, and to guide future research inquiries, as well as development of intervention and prevention strategies for individuals with chronic pain and SUDs.

There are, however, several limitations to the proposed meta-analysis which are important to acknowledge. First, we plan to restrict the articles to peer-reviewed studies and do not have the resources to translate full length articles written in languages other than English. This may introduce potential bias into prevalence estimates, with potential underrepresentation of estimates from low- and middle-income countries, as well as not fully reflecting the global epidemiology of substance use disorders among individuals with chronic pain. Additionally, we expect that there will be substantial heterogeneity in how SUDs and problematic substance use are assessed and reported across studies, including variability in diagnostic criteria, screening measures, and chronic pain characteristics. These variabilities may limit our understanding of observed differences and interpretability of pooled findings. Although we do plan to conduct sub-group analyses to address these potential sources of heterogeneity, our ability to disentangle these factors is limited by how they are reported in existing literature. The expected heterogeneity may further impact the generalizability of the findings, and interpreting the prevalence estimates with caution will be warranted. The proposed meta-analysis has the potential to significantly advance the literature by providing more accurate understanding of the scope of nicotine, alcohol, and cannabis use disorders among adults with chronic pain. These findings can inform several actionable next steps for key stakeholders. For clinicians, the results may support the routine implementation of validated screening tools for SUDs in chronic pain treatment settings and the integration of brief interventions or referrals when necessary. For researchers, the findings may help identify some gaps in measurements and reporting practices, guiding the development of more standardized assessments. At the policy level, the results may inform resource allocation and the development of integrated care models that address co-occurring chronic pain and SUDs. Collectively, this meta-analysis will contribute to the development of more targeted and effective prevention and treatment for this potentially prevalent and a burdensome public health challenge.

Supporting information

S1 Table. Inclusion and Exclusion Criteria for Reviewed Studies.

Mixed cancer-pain and non-cancer pain populations will be included only if specific data on non-cancer pain can be extracted from the article. Nicotine-related outcomes may include combustible tobacco, electronic cigarettes/vaping products, smokeless tobacco, and other nicotine-containing products when assessed as part of nicotine use disorder or problematic nicotine use. Cannabis-related outcomes may include synthetic cannabinoids.

(DOCX)

pone.0356365.s001.docx (15.8KB, docx)
S2 Table. Terminology referring to problematic substance use.

The list of terms above identified possible terms that indicate problematic substance use [79–85]. Following the full article search and data extraction, and updated table will be included in the published manuscript.

(DOCX)

pone.0356365.s002.docx (14.5KB, docx)
S1 File. Inclusion and Exclusion Criteria for Reviewed Studies.

(DOC)

pone.0356365.s003.doc (82KB, doc)
S1 Appendix. PubMed Search Strategy.

(DOCX)

pone.0356365.s004.docx (16.5KB, docx)

Data Availability

No datasets were generated or analyzed during the current study. All relevant data from this study will be made available upon study completion, and analytic code will be shared on Open Science Framework.

Funding Statement

The author(s) received no specific funding for this work.

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Decision Letter 0

Marianna Mazza

17 Feb 2026

Dear Dr.  Rogers,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that carefully addresses the points raised by the three reviewers.

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Reviewer's Responses to Questions

Comments to the Author

1. Does the manuscript provide a valid rationale for the proposed study, with clearly identified and justified research questions?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Partly

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2. Is the protocol technically sound and planned in a manner that will lead to a meaningful outcome and allow testing the stated hypotheses??>

Reviewer #1: Partly

Reviewer #2: Yes

Reviewer #3: Partly

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3. Is the methodology feasible and described in sufficient detail to allow the work to be replicable??>

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No

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4. Have the authors described where all data underlying the findings will be made available when the study is complete??>

The PLOS Data policy

Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Please use the space provided to explain your answers to the questions above and, if applicable, provide comments about issues authors must address before this protocol can be accepted for publication. You may also include additional comments for the author, including concerns about research or publication ethics.

You may also provide optional suggestions and comments to authors that they might find helpful in planning their study.

Reviewer #1: Comments to the Authors

Major Comments

1. Conceptual Clarity of “Problematic Substance Use”

The protocol appropriately acknowledges heterogeneity in how problematic substance use is defined; however, the current operationalization remains overly broad.

The inclusion criteria combine:

Hazardous/problematic use (screening-based),

Diagnosed substance use disorders (DSM/ICD),

Past-year and lifetime measures.

These constructs reflect distinct clinical severities and time frames, yet are pooled under a single analytic framework.

Suggestions:

Explicitly predefine tiers or categories of problematic use (e.g., hazardous use vs. diagnosed disorder).

Clarify whether pooled estimates will be stratified by:

Diagnostic vs. screening-based definitions,

Past-year vs. lifetime prevalence.

Consider whether combining these constructs risks inflating or obscuring clinically meaningful prevalence estimates.

2. Decision to Average Multiple Prevalence Estimates Within Studies

The protocol states that when studies report multiple prevalence estimates for the same substance, a mean prevalence rate will be calculated.

This approach is methodologically concerning, as it:

Violates assumptions of independence,

Masks subgroup variability,

May introduce bias depending on subgroup sizes.

Suggestions:

Justify this approach more explicitly with citations from prevalence meta-analysis methodology.

Consider alternative strategies, such as:

Selecting the most clinically relevant estimate (e.g., total sample),

Conducting sensitivity analyses,

Using multilevel or robust variance meta-analytic approaches.

3. Anticipated Heterogeneity and Its Implications

Given the wide range of:

Chronic pain definitions,

Pain conditions,

Substance types, products, and routes of administration,

Measurement tools,

very high heterogeneity is likely.

Suggestions:

Elaborate on how extreme heterogeneity (e.g., I² > 90%) will be handled in interpretation.

Clarify whether pooled estimates will still be presented under such conditions, or whether narrative synthesis thresholds will be applied.

Consider pre-specifying criteria for when meta-analysis may be deemed inappropriate.

4. Exclusion of Non-English Full-Text Articles

While resource constraints are understandable, excluding non-English full texts may bias prevalence estimates, particularly given global variation in chronic pain and substance use.

Suggestions:

Explicitly acknowledge this as a source of language and regional bias in both the Methods and Discussion.

Clarify whether non-English abstracts will contribute to any descriptive mapping of excluded studies (beyond listing in an appendix).

5. Co-use of Substances

The protocol states that studies reporting co-use will be included, but the analytic handling of co-use is unclear.

Suggestions:

Clarify whether co-use prevalence will be:

Reported descriptively,

Analyzed separately,

Or excluded from pooled estimates.

Explicitly state whether individuals may be counted multiple times across substance-specific analyses.

Minor Comments

Terminology consistency

The manuscript alternates between “problematic use,” “misuse,” “hazardous use,” and “use disorder.”

Recommend standardizing terminology and providing a brief definitional table.

Grammar and clarity

Minor typographical issues (e.g., duplicated phrases such as “full the full searches”) should be corrected.

Some long sentences in the Introduction could be tightened for clarity.

Data Availability Statement

While acceptable for a protocol, the statement could be strengthened by briefly outlining where and how extracted data and analytic code will be shared upon completion (e.g., OSF, GitHub).

Table 1

Consider explicitly stating whether mixed pain populations (e.g., cancer + non-cancer pain) are excluded or handled separately.

Overall Recommendation

This is a well-motivated and potentially impactful protocol, addressing an important and understudied area at the intersection of chronic pain and non-opioid substance use. With clearer conceptual definitions, stronger justification for analytic decisions, and improved handling of heterogeneity, the manuscript would meet high methodological standards and provide a solid foundation for the planned review.

Recommendation: Major revision

Reviewer #2: This protocol addresses a critical and timely gap in the literature regarding the prevalence of problematic nicotine, alcohol, and cannabis use among adults with chronic pain. While opioid use has been extensively characterized, the scope of non-opioid substance use in this population remains less precisely defined. The protocol is methodologically strong overall, adheres to PRISMA-P guidance, and outlines a thoughtful statistical plan. The study aims are well aligned with the stated need to better quantify prevalence estimates in this area.

That said, some technical aspects related to the search strategy and data synthesis would benefit from additional clarification to ensure the highest standards of transparency and reproducibility.

1. Search Strategy Refinement – Seed Article Omission

The protocol notes that one seed article was not retrieved because it lacked “misuse” terminology. This raises the possibility that the current search string may be overly restrictive. It would be helpful to clarify whether the search strategy was subsequently modified to incorporate broader terminology (e.g., high-risk use, heavy use, or consumption-level descriptors), or whether the decision reflects an intentional prioritization of specificity over sensitivity.

2. Database Translation and Language Bias

The protocol indicates that articles may be excluded if translation is not feasible due to funding limitations. This introduces the potential for language and geographic bias. It would strengthen the protocol to explicitly state how this limitation will be reported in the final manuscript and whether machine translation tools will be used for preliminary screening or data extraction feasibility assessment.

3. Operationalization of “Problematic Use”

The protocol plans to estimate prevalence for both “problematic use” and “use disorders.” Given the variability in how problematic use is defined across studies (for example, frequency-based thresholds versus consequence-based definitions), it would be valuable to provide a predefined hierarchical or decision framework for categorizing heterogeneous measures during data extraction. This would help ensure consistency across studies and improve interpretability of pooled estimates.

4. Statistical Rigor and Handling of Heterogeneity

The requirement of at least five studies to conduct random-effects meta-analysis is a commendably conservative decision. The approach of averaging prevalence rates derived from the same sample is also appropriate. For subgroup and moderator analyses, additional clarification would be helpful regarding how studies reporting multiple substances or co-use within the same population will be handled to avoid unit-of-analysis issues.

5. Risk of Bias Integration

The use of the Joanna Briggs Institute checklist for prevalence data is well justified. It would further strengthen the analytic plan to specify whether risk-of-bias scores will be incorporated as moderators or sensitivity analyses, rather than used solely for descriptive reporting.

6. Inclusion Criteria Clarification (Table 1)

The inclusion of self-reported pain ≥3 months is appropriate and consistent with standard chronic pain definitions. It may be helpful to explicitly state in the text (not only in the table) whether studies focused exclusively on cancer-related pain will be excluded, to reinforce the focus on chronic non-cancer pain.

7. Terminology in the Introduction

In the sentence stating that a systematic review and meta-analysis “conducted in 2011” reported prevalence estimates, it may be more precise to use “published in 2011,” since the cited year reflects publication rather than study conduct.

8. Minor Editorial Issue

In the Materials and Methods section, the phrase “full the full searches” appears to contain a duplicated word and should be corrected for clarity.

Overall, this is a well-conceived and clinically important protocol. Addressing the points above would further strengthen methodological transparency and reproducibility and improve clarity for readers and future replication efforts.

Reviewer #3: The manuscript needs the following clarifications:

1. The title ‘use disorders’ is creating confusion. How does it matter if this term is deleted?

2. It would be much better to show the entire research question into a PICO format.

3. Line 159: “cohort studies (both non-randomized and randomized controlled trials)” – RCT and NRCT are not part of a cohort study – please correct.

4. Objective is to find out the ‘estimate’ – does it include only prevalence? Since, the term prevalence has been used in the introduction section. Then, cohort studies might not be needed. If incidence is also there, then the rationality of cohort studies is justified. Moreover, RCT and NRCT will not provide any estimate of any of the use. So, please correct or clarify the entire manuscript.

5. Scopus, being the largest database, is not considered – why?

6. Line 174: For the same reason as mentioned earlier, clinical trials might not be suited.

7. Whether sensitivity analysis will be done?

8. It would be very helpful to the readers if the authors could highlight the high heterogeneity, how it would influence the interpretation of pooled prevalence estimates and mention what could be the possible reasons for the high heterogeneity.

9. Please mention potential confounding variables that may influence the findings.

10. Conclusion: The conclusion can be strengthened by adding 1 or 2 actionable steps for the stakeholders.

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: Yes: Indranil Saha

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PLoS One. 2026 Aug 26;21(8):e0356365. doi: 10.1371/journal.pone.0356365.r002

Author response to Decision Letter 1

8 May 2026

Response Letter to Reviewers

We appreciate the thoughtful review and the opportunity to revise and resubmit this manuscript. We believe the suggested revisions have significantly strengthened the manuscript. In this letter, we outline how we addressed the feedback provided by reviewers. For ease of review, we have highlighted the corresponding changes in the manuscript in yellow.

Reviewer #1

Major Comments

1. Conceptual Clarity of “Problematic Substance Use”: The protocol appropriately acknowledges heterogeneity in how problematic substance use is defined; however, the current operationalization remains overly broad. The inclusion criteria combine: Hazardous/problematic use (screening-based), Diagnosed substance use disorders (DSM/ICD), Past-year and lifetime measures. These constructs reflect distinct clinical severities and time frames yet are pooled under a single analytic framework.

Suggestions:

• Explicitly predefine tiers or categories of problematic use (e.g., hazardous use vs. diagnosed disorder).

• Clarify whether pooled estimates will be stratified by:

Diagnostic vs. screening-based definitions, Past-year vs. lifetime prevalence.

• Consider whether combining these constructs risks inflating or obscuring clinically meaningful prevalence estimates.

Response: We thank the reviewer for pointing out the conceptual heterogeneity in how problematic substance use is defined, particularly with respect to differences in clinical severity (e.g., problematic use vs. diagnosable disorder) and time frame (e.g., past year vs. lifetime). We agree that pooling these constructs without distinction may obscure clinically meaningful differences.

In response (as well as other reviewer comments), we have refined our analytic framework to more clearly distinguish between levels of severity and assessment approaches. Specifically, Substance Use Disorder (SUD) status is now designated as the primary outcome, defined based on DSM or ICD diagnostic criteria. Problematic use, as identified by validated screening instruments (e.g., AUDIT, CUDIT), as the secondary outcome (see below for how this will be identified; see Table 1).

In terms of the time frame, where sufficient data are available, we will prioritize past year (or current) estimates for both SUD diagnoses and problematic use, given their greater clinical relevance and comparability across studies. Lifetime estimates will be analyzed separately and not pooled with past-year estimates. We have updated our planned stratification analyses in line with reviewer feedback (see pp. 10-11).

2. Decision to Average Multiple Prevalence Estimates Within Studies. The protocol states that when studies report multiple prevalence estimates for the same substance, a mean prevalence rate will be calculated. This approach is methodologically concerning, as it: Violates assumptions of independence, masks subgroup variability, may introduce bias depending on subgroup sizes.

Suggestions:

• Justify this approach more explicitly with citations from prevalence meta-analysis methodology.

• Consider alternative strategies, such as:

o Selecting the most clinically relevant estimate (e.g., total sample), conducting sensitivity analyses, using multilevel or robust variance meta-analytic approaches.

Response: We thank the reviewer for this helpful comment and suggestion. First, when studies provide a total sample estimate, we will extract that estimate (even if subgroups are also identified). When studies report multiple subgroup-specific prevalence estimates (e.g., by sex, age group, or different pain conditions), we will derive a single study-level prevalence by aggregating subgroup data using sample size-weighted estimates (i.e., total number of cases divided by the total sample size, where available; see pp. 10). This approach retains within-study information while minimizing bias associated with unweighted averaging of prevalence rate and ensures that each study contributes only one independent estimate per substance. To assess the robustness of this approach, following the reviewer’s recommendation, we will also conduct sensitivity analyses using alternative strategies, such as selecting the largest subgroup, as well as serially excluding each study to determine the influence of individual studies on the overall prevalence estimates. Although multilevel and robust variance estimation methods can account for dependent effect sizes, we will prioritize a single aggregated estimate per study to enhance interpretability and maintain comparability across studies, which is common practice in prevalence meta-analyses (see citations below for examples).

• Barendregt, J. J., Doi, S. A., Lee, Y. Y., Norman, R. E., & Vos, T. (2013). Meta-analysis of prevalence. J epidemiol community health, 67(11), 974-978.

• Rotenstein LS, Ramos MA, Torre M, et al. Prevalence of Depression, Depressive Symptoms, and Suicidal Ideation Among Medical Students: A Systematic Review and Meta-Analysis. JAMA. 2016;316(21):2214–2236. doi:10.1001/jama.2016.17324

• Borenstein, M., Hedges, L. V., Higgins, J. P., & Rothstein, H. R. (2010). A basic introduction to fixed‐effect and random‐effects models for meta‐analysis. Research synthesis methods, 1(2), 97-111.

• Sterne, J. A., Jüni, P., Schulz, K. F., Altman, D. G., Bartlett, C., & Egger, M. (2002). Statistical methods for assessing the influence of study characteristics on treatment effects in ‘meta‐epidemiological’research. Statistics in medicine, 21(11), 1513-1524.

• Van Houwelingen, H. C., Arends, L. R., & Stijnen, T. (2002). Advanced methods in meta‐analysis: multivariate approach and meta‐regression. Statistics in medicine, 21(4), 589-624.

3. Anticipated Heterogeneity and Its Implications

Given the wide range of: Chronic pain definitions, pain conditions, substance types, products, and routes of administration, measurement tools, very high heterogeneity is likely.

Suggestions:

• Elaborate on how extreme heterogeneity (e.g., I² > 90%) will be handled in interpretation.

• Clarify whether pooled estimates will still be presented under such conditions, or whether narrative synthesis thresholds will be applied.

• Consider pre-specifying criteria for when meta-analysis may be deemed inappropriate.

Response: We thank the reviewer for this important comment and agree that substantial heterogeneity is likely given the diversity of chronic pain populations, substances, and measurement approaches included in this review.

We have revised the protocol to clarify our approach to the assessment and interpretation of heterogeneity. Specifically, we now emphasize that I² will not be interpreted using rigid thresholds, as recent methodological work (Migliavaca et al., 2022) demonstrates that very high I² values (e.g., >90%) are common in prevalence meta-analyses and may not be discriminative of meaningful heterogeneity. Instead, we will interpret I² in conjunction with τ², prediction intervals, and the clinical and methodological comparability of included studies (Migliavaca et al., 2022; see pp. 11-12).

We further clarify that pooled estimates will be presented using random-effects models even in the presence of substantial heterogeneity but will be interpreted cautiously as average prevalence across diverse contexts rather than precise summary values. To enhance interpretability, we will report prediction intervals to reflect the expected range of true prevalence estimates across settings (see p. 12).

In addition, we have specified that subgroup and, where feasible, meta-regression analyses will be conducted based on a priori hypotheses to explore potential sources of heterogeneity. Importantly, we now explicitly state that decisions regarding the appropriateness of meta-analysis will not be based solely on I². If heterogeneity is judged to be too substantial to support a meaningful pooled estimate (e.g., due to extreme variability that cannot be explained or limited conceptual comparability across studies), we will supplement or replace pooled estimates with a narrative synthesis, focusing on the distribution and range of estimates across studies (see p. 12).

• Migliavaca, C.B., Stein, C., Colpani, V., Barker, T.H., Ziegelmann, P.K., Munn, Z., & Falavigna, M. (2022). Meta-analysis of prevalence: I² statistic and how to deal with heterogeneity. Research Synthesis Methods, 13(3), 363–367. https://doi.org/10.1002/jrsm.1547

4. Exclusion of Non-English Full-Text Articles: While resource constraints are understandable, excluding non-English full texts may bias prevalence estimates, particularly given global variation in chronic pain and substance use.

Suggestions:

• Explicitly acknowledge this as a source of language and regional bias in both the Methods and Discussion.

• Clarify whether non-English abstracts will contribute to any descriptive mapping of excluded studies (beyond listing in an appendix).

Response: We have explicitly acknowledged that excluding non-English full texts may be a source of language and regional bias (see p. 8). For all identified non-English papers, we will 1) indicate in the PRISMA flow diagram under a dedicated exclusion category of "unable to obtain full translation," distinct from other exclusion reasons, to allow readers to gauge the potential scope of this bias, and 2) provide a summary table in the appendix that includes, where extractable from the abstract alone, the study country, pain condition, substance type examined, and reported prevalence if clearly stated in the abstract. Importantly, if there is a clear pattern that is identified from these non-English articles, we will note this in text.

5. Co-use of Substances

The protocol states that studies reporting co-use will be included, but the analytic handling of co-use is unclear.

Suggestions:

• Clarify whether co-use prevalence will be: Reported descriptively, analyzed separately, or excluded from pooled estimates.

• Explicitly state whether individuals may be counted multiple times across substance-specific analyses.

Response: We agree that the handling of co-use requires clarification. We have revised the protocol (see p. 9) to specify that prevalence estimates of co-use (i.e., concurrent problematic use or use disorders involving multiple substances) will be extracted and reported descriptively. Where sufficient data are available, co-use will also be examined in exploratory analyses; however, co-use estimates will not be included in the primary pooled prevalence analyses for individual substances.

Our primary analyses focus on estimating substance-specific prevalence (i.e., use disorders for nicotine, alcohol, and cannabis separately) and secondary analyses for problematic use. Accordingly, each study will contribute at most one prevalence estimate per substance to the pooled analyses. For example, if a study reports that 30% of participants meet criteria for alcohol use disorder, 40% for nicotine dependence, and 15% for co-occurring alcohol and nicotine use disorder, the alcohol (30%) and nicotine (40%) estimates would be included in their respective meta-analyses, while the co-use estimate (15%) would be summarized descriptively or examined in secondary analyses.

Because the analyses focus on substance-specific prevalence, each substance will be examined separately. As a result, individuals who use multiple substances may contribute to more than one substance-specific analysis (e.g., both alcohol and nicotine). However, within each substance-specific meta-analysis, each study will contribute only one estimate, and individuals will not be counted more than once. We will also descriptively report how co-use was defined in each of the estimates used. We have clarified this approach on pp. 10-11 to improve transparency.

Minor Comments

6. Terminology consistency

The manuscript alternates between “problematic use,” “misuse,” “hazardous use,” and “use disorder.”

Recommend standardizing terminology and providing a brief definitional table.

Response: We have added a table to help with clarity and standardization of terminology (see Table 2), and have clarified that the primary outcomes now focus on use disorders, with secondary outcomes focused on problematic use.

7. Grammar and clarity

Minor typographical issues (e.g., duplicated phrases such as “full the full searches”) should be corrected.

Some long sentences in the Introduction could be tightened for clarity.

Response: We have thoroughly reviewed the manuscript for typographical and grammar errors (see revised manuscript).

8. Data Availability Statement

While acceptable for a protocol, the statement could be strengthened by briefly outlining where and how extracted data and analytic code will be shared upon completion (e.g., OSF, GitHub).

Response: We have added additional details on where the data and code will be shared (see p. Data Availability Statement). Specifically, the extracted data and analytic code will be shared on OSF upon completion.

9. Table 1

Consider explicitly stating whether mixed pain populations (e.g., cancer + non-cancer pain) are excluded or handled separately.

Response: We have revised the protocol to specify that studies including mixed pain populations (e.g., cancer and non-cancer pain) will be included only if data specific to individuals with chronic non-cancer pain can be extracted separately (see Table 1 note).

Reviewer #2

Overall Recommendation

This is a well-motivated and potentially impactful protocol, addressing an important and understudied area at the intersection of chronic pain and non-opioid substance use. With clearer conceptual definitions, stronger justification for analytic decisions, and improved handling of heterogeneity, the manuscript would meet high methodological standards and provide a solid foundation for the planned review.

Recommendation: Major revision

This protocol addresses a critical and timely gap in the literature regarding the prevalence of problematic nicotine, alcohol, and cannabis use among adults with chronic pain. While opioid use has been extensively characterized, the scope of non-opioid substance use in this population remains less precisely defined. The protocol is methodologically strong overall, adheres to PRISMA-P guidance, and outlines a thoughtful statistical plan. The study aims are well aligned with the stated need to better quantify prevalence estimates in this area. That said, some technical aspects related to the search strategy and data synthesis would benefit from additional clarification to ensure the highest standards of transparency and reproducibility.

1. Search Strategy Refinement – Seed Article Omission

The protocol notes that one seed article was not retrieved because it lacked “misuse” terminology. This raises the possibility that the current search string may be overly restrictive. It would be helpful to clarify whether the search strategy was subsequently modified to incorporate broader terminology (e.g., high-risk use, heavy use, or consumption-level descriptors), or whether the decision reflects an intentional prioritization of specificity over sensitivity.

Response: Thank you for this helpful comment. As noted, one seed article was not retrieved because the paper did not include any misuse-related terms in the title, abstract, or indexed subject headings. Following this observation, we reviewed and refined the search strategy to ensure broader coverage of relevant terminology. Specifically, we incorporated a comprehensive set of synonyms reflecting problematic use, including terms related to abuse, addiction, dependence, and overconsumption, as well as high-risk patterns of use (e.g., binge, daily, harmful, heavy, problematic, and risky use). We also include terms for alcoholism and specific database headings for alcohol and tobacco use disorders and marijuana abuse. Yet, the specific seed article was still not identified (see pp. 7-8).

2. Database Translation and Language Bias

The protocol indicates that articles may be excluded if translation is not feasible due to funding limitations. This introduces the potential for language and geographic bias. It would strengthen the protocol to explicitly state how this limitation will be rep

Decision Letter 1

Marianna Mazza

27 May 2026

Dear Dr. Rogers,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please follow with particular attention reviewer's 1 requests.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Does the manuscript provide a valid rationale for the proposed study, with clearly identified and justified research questions?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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2. Is the protocol technically sound and planned in a manner that will lead to a meaningful outcome and allow testing the stated hypotheses??>

Reviewer #1: Partly

Reviewer #2: Yes

Reviewer #3: Yes

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3. Is the methodology feasible and described in sufficient detail to allow the work to be replicable??>

Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Have the authors described where all data underlying the findings will be made available when the study is complete??>

The PLOS Data policy

Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: Yes

**********

Please use the space provided to explain your answers to the questions above and, if applicable, provide comments about issues authors must address before this protocol can be accepted for publication. You may also include additional comments for the author, including concerns about research or publication ethics.

You may also provide optional suggestions and comments to authors that they might find helpful in planning their study.

Reviewer #1: Major Comments

Persistent conceptual heterogeneity in “problematic use”

Although the revised protocol distinguishes substance use disorders from problematic use, the operationalization of “problematic use” remains broad and somewhat conceptually unstable. Terms such as “hazardous,” “risky,” “harmful,” “misuse,” and “unhealthy use” are grouped together, yet these constructs differ clinically, behaviorally, and diagnostically. Table 2 improves transparency but may still permit substantial conceptual heterogeneity.

Consider:

Explicitly prioritizing validated screening tools with established cutoffs,

Clarifying whether studies using author-defined thresholds without validation will be excluded,

Providing a more hierarchical framework for categorizing severity.

Pooling prevalence across highly heterogeneous populations

The planned pooling strategy may still yield prevalence estimates of questionable interpretability due to anticipated extreme heterogeneity across:

Pain conditions,

Clinical versus community settings,

Substance definitions,

Measurement tools,

Geographic contexts,

Timeframes,

Study designs.

Although the manuscript appropriately discusses heterogeneity and prediction intervals, the protocol should more explicitly define:

What level of conceptual heterogeneity would preclude meta-analysis,

Whether narrative synthesis would replace pooling under certain circumstances,

How interpretability of pooled prevalence will be communicated to readers when heterogeneity remains extreme despite subgroup analyses.

Inclusion of interventional studies requires stronger justification

The inclusion of randomized and non-randomized trials remains somewhat problematic for a prevalence-focused review. Even if only baseline data are extracted, trial populations are often highly selected and may not represent underlying chronic pain populations. This could introduce selection bias and inflate prevalence estimates.

The authors should:

More clearly justify inclusion of clinical trial samples,

Consider conducting separate subgroup analyses by study design,

Discuss the potential effect of enriched clinical samples on pooled prevalence estimates.

Potential duplication of populations

The strategy for identifying duplicate samples is appreciated but may still be insufficient. Reliance on author names, sample sizes, and study years may fail to identify overlapping cohorts from large longitudinal databases or multicenter studies.

The protocol would benefit from:

More explicit criteria for identifying overlapping samples,

Clarification on how partially overlapping datasets will be handled,

Whether preference will be given to larger or more comprehensive datasets.

Language bias remains a significant limitation

The revised discussion acknowledges exclusion of non-English full texts; however, the practical implications may be larger than described given global variation in chronic pain and substance use epidemiology.

The authors should discuss:

Whether machine translation tools (e.g., DeepL or Google Translate) will be used for feasibility screening,

Potential underrepresentation of studies from low- and middle-income countries,

How this may affect generalizability of prevalence estimates.

Potential confounding by medical cannabis legalization contexts

Cannabis use prevalence may vary dramatically across regions depending on legal status, medical prescribing frameworks, and recreational availability. This is particularly important because cannabis use in chronic pain populations may reflect therapeutic use rather than problematic use in some jurisdictions.

Consider including:

Legal status or region-specific cannabis policy as a moderator,

Distinction between prescribed medical cannabis and non-medical use where possible.

Risk-of-bias integration could be stronger

The addition of sensitivity analyses using risk-of-bias scores is valuable. However, reliance on JBI sum scores may oversimplify methodological quality. Some items may contribute differently to prevalence bias.

Consider:

Presenting domain-level assessments,

Exploring whether high-risk studies disproportionately influence pooled estimates,

Clarifying how disagreements in quality ratings will be resolved.

Minor Comments

The abstract is generally clear, but the sentence:

“Therefore, a systematic review and meta-analysis, characterizing the prevalence rates… are urgently needed”

should be grammatically revised for clarity.

Several sentences in the introduction are lengthy and could be condensed for readability, particularly in the sections discussing theoretical models and chronic overlapping pain conditions.

The protocol should clarify whether nicotine includes:

combustible tobacco,

vaping/e-cigarettes,

smokeless tobacco,

mixed nicotine products.

Similarly, cannabis terminology should clarify whether synthetic cannabinoids are included or excluded.

The manuscript alternates between “use disorders,” “dependence,” and “problematic use.” While improved from the prior version, terminology consistency could still be enhanced throughout the text.

Consider adding a schematic figure summarizing:

eligibility criteria,

outcome hierarchy,

analytic workflow,

subgroup analyses.

This would improve protocol clarity for readers.

The rationale for selecting the Sidik–Jonkman estimator over alternative estimators (e.g., REML or DerSimonian-Laird) could be briefly justified.

The manuscript should specify whether prevalence estimates will undergo variance-stabilizing transformation (e.g., Freeman–Tukey double arcsine transformation), which is commonly used in prevalence meta-analyses.

The statement:

“individuals will only be counted in one estimate and not be counted more than once”

is somewhat unclear because individuals may contribute to multiple substance-specific analyses. This wording should be revised for precision.

The discussion appropriately outlines implications for clinicians and policymakers; however, it may overstate the certainty of pooled estimates given anticipated heterogeneity. A slightly more cautious tone is recommended

Reviewer #2: The authors responded appropriately to the comments.

Reviewer #3: The authors have satisfactorily addressed all the previous queries. But I have one objection. Authors have mentioned, if prevalence data is available from the baseline from cohort or experimental study, then these studies will also be taken into consideration. But for the baseline information, how the methodological rigour of those studies will be judged? Moreover, in experimental studies, one group will be having intervention having the disease and control group will be having placebo having the disease. Then how prevalence will be estimated from experimental studies? Moreover, if baseline findings are taken, then again the same problem of judging the article in methodological rigour in addition to non-availability of some basic findings that are need for SRMA.

**********

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: Yes: Dr. Indranil Saha

**********

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PLoS One. 2026 Aug 26;21(8):e0356365. doi: 10.1371/journal.pone.0356365.r004

Author response to Decision Letter 2

31 Jul 2026

Response Letter to Reviewers

We appreciate the thoughtful review and the opportunity to revise and resubmit this manuscript. We believe the suggested revisions have significantly strengthened the manuscript. In this letter, we outline how we addressed the feedback provided by reviewers. For ease of review, we have highlighted the corresponding changes in the manuscript in yellow.

Reviewer #1: Major Comments

Persistent conceptual heterogeneity in “problematic use”

Although the revised protocol distinguishes substance use disorders from problematic use, the operationalization of “problematic use” remains broad and somewhat conceptually unstable. Terms such as “hazardous,” “risky,” “harmful,” “misuse,” and “unhealthy use” are grouped together, yet these constructs differ clinically, behaviorally, and diagnostically. Table 2 improves transparency but may still permit substantial conceptual heterogeneity.

Consider:

Explicitly prioritizing validated screening tools with established cutoffs,

Clarifying whether studies using author-defined thresholds without validation will be excluded,

Providing a more hierarchical framework for categorizing severity.

Pooling prevalence across highly heterogeneous populations

Response: We thank the reviewer for their thoughtful comment. We agree that the operationalization of problematic use is broad and encompasses a heterogeneous group of constructs (e.g., hazardous, risky, harmful use, and misuse), and this variability reflects an important limitation of the existing literature. As noted in our revised protocol (see p. 6), the primary outcome of this review is now the prevalence of nicotine, alcohol, and cannabis use disorders, while problematic use is examined as a secondary outcome. This change was made specifically to distinguish clinically diagnosed substance use disorders from broader screening-based indicators of problematic use.

For the secondary analyses of problematic use, we have further clarified our approach following the reviewer’s suggestion. Specifically, we will include only prevalence estimates derived from validated screening instruments using established cutoffs (e.g., AUDIT, CUDIT, FTND). Studies relying solely on author-defined thresholds without evidence of validation will not contribute to the pooled prevalence estimates of problematic use (see p. 9). During data extraction, we will also document the specific construct assessed (e.g., hazardous use, harmful use, misuse) and the corresponding instrument used. Where sufficient data are available, we will conduct subgroup or moderator analyses by screening instrument or measure type to examine whether prevalence estimates differ across these measures (see p. 12). These revisions are intended to improve transparency while acknowledging that some conceptual heterogeneity will inevitably remain because of differences in how problematic use has been operationalized across the published literature.

The planned pooling strategy may still yield prevalence estimates of questionable interpretability due to anticipated extreme heterogeneity across:

Pain conditions,

Clinical versus community settings,

Substance definitions,

Measurement tools,

Geographic contexts,

Timeframes,

Study designs.

Although the manuscript appropriately discusses heterogeneity and prediction intervals, the protocol should more explicitly define:

What level of conceptual heterogeneity would preclude meta-analysis,

Whether narrative synthesis would replace pooling under certain circumstances,

How interpretability of pooled prevalence will be communicated to readers when heterogeneity remains extreme despite subgroup analyses.

Response: We thank the reviewer for this thoughtful comment and agree that conceptual heterogeneity is an important consideration in prevalence meta-analyses.

First, regarding what level of conceptual heterogeneity would preclude meta-analysis, there is no universally accepted threshold for conceptual heterogeneity. Accordingly, we elected not to rely on a rigid criterion. Instead, quantitative synthesis will be undertaken only when studies are judged to be sufficiently comparable with respect to key conceptual characteristics, including the chronic pain population, substance definitions, measurement approach, and study designs. This approach is consistent with guidelines that suggest that studies should be grouped for meta-analytic synthesis based on pre-defined conceptual comparable characteristics and not use meta-analysis as a default when summary estimates would be misleading.

Lin, L. (2020). Comparison of four heterogeneity measures for meta‐analysis. Journal of Evaluation in Clinical Practice, 26(1), 376-384.

Melsen, W. G., Bootsma, M. C. J., Rovers, M. M., & Bonten, M. J. M. (2014). The effects of clinical and statistical heterogeneity on the predictive values of results from meta-analyses. Clinical Microbiology and Infection, 20(2), 123-129.

Campbell, M., McKenzie, J. E., Sowden, A., Katikireddi, S. V., Brennan, S. E., Ellis, S., ... & Thomson, H. (2020). Synthesis without meta-analysis (SWiM) in systematic reviews: Reporting guideline. BMJ, 368.

Second, if the included studies are judged to be too conceptually heterogenous for a pooled prevalence estimate to provide a meaningful summary of the evidence (determined by expert consensus from the study team), we will instead provide a narrative synthesis with additional transparent reporting and visual presentation and range of prevalence rates across studies.

Third, we clarified that, when meta-analysis is conducted despite substantial heterogeneity, prevalence estimates will be interpreted as descriptive summaries rather than single generalizable estimates. We will emphasize prediction intervals, subgroup patterns, and the limits of generalizability in the Results and Discussion (see p. 12).

Inclusion of interventional studies requires stronger justification

The inclusion of randomized and non-randomized trials remains somewhat problematic for a prevalence-focused review. Even if only baseline data are extracted, trial populations are often highly selected and may not represent underlying chronic pain populations. This could introduce selection bias and inflate prevalence estimates.

The authors should:

More clearly justify inclusion of clinical trial samples,

Consider conducting separate subgroup analyses by study design,

Discuss the potential effect of enriched clinical samples on pooled prevalence estimates.

Response: We agree that participants enrolled in randomized and non-randomized trials may differ from the broader population of individuals with chronic pain because of trial-specific eligibility criteria and treatment-seeking status. However, we believe these studies remain informative for the current review because many report baseline prevalence estimates that reflect clinically relevant chronic pain populations represented in the published literature.

To address this concern, we have further clarified that these interventional studies will contribute only baseline (pre-intervention) prevalence data (see p. 7). Mid- and post-intervention, as well as follow-up data will NOT be included in the prevalence analyses. These data will be treated as observational prevalence estimates and will not be combined with any post-treatment data. We will also conduct separate subgroup analyses by study design whenever sufficient studies are available (see pp. 11-12). This will allow us to evaluate whether prevalence estimates differ systematically between cross-sectional, cohort, and interventional studies. In addition, we will discuss the findings from these subgroup analysis, as well as the potential impact of including these clinical trial samples on pooled prevalence estimates and their generalizability, in the Discussion.

Potential duplication of populations

The strategy for identifying duplicate samples is appreciated but may still be insufficient. Reliance on author names, sample sizes, and study years may fail to identify overlapping cohorts from large longitudinal databases or multicenter studies.

The protocol would benefit from:

More explicit criteria for identifying overlapping samples,

Clarification on how partially overlapping datasets will be handled,

Whether preference will be given to larger or more comprehensive datasets.

Response: We agree that identifying overlapping study populations can be challenging, particularly for large publicly available longitudinal cohorts and multicenter studies. We have therefore expanded our protocol to further clarify how potential duplicate samples will be identified and handled. Specifically, in addition to study authors, sample size, publication year, and study measures, we will also examine the cohort or database name (when applicable), recruitment period, and other relevant study characteristics (e.g., geographical locations) to identify potentially overlapping samples (see p. 11).

When multiple publications report the same prevalence outcome from overlapping samples, only one independent estimate will be included in the corresponding meta-analysis. Preference will be given to the report with the largest eligible sample and/or the most comprehensive prevalence data relevant to the planned analysis. We have clarified these procedures in the Methods (p. 11).

Language bias remains a significant limitation

The revised discussion acknowledges exclusion of non-English full texts; however, the practical implications may be larger than described given global variation in chronic pain and substance use epidemiology.

The authors should discuss:

Whether machine translation tools (e.g., DeepL or Google Translate) will be used for feasibility screening,

Potential underrepresentation of studies from low- and middle-income countries,

How this may affect generalizability of prevalence estimates.

Response: We appreciate the reviewer’s concerns regarding the exclusion of non-English full text articles. We have clarified that machine translation tools (e.g., Google Translate) will be used during feasibility screening to help determine whether non-English studies appear to meet the eligibility criteria and whether sufficient information can be extracted (see p. 8). However, because formal translation of full-text articles is beyond the scope of the current review, studies that cannot be adequately translated will be excluded. We have also expanded the Discussion to acknowledge that there is potential underrepresentation of prevalence estimates from low- and middle-income countries, where publication in languages other than English may be more common. Consequently, the pooled prevalence estimates may not fully reflect the global epidemiology of substance use disorders among individuals with chronic pain (see p. 14).

Potential confounding by medical cannabis legalization contexts

Cannabis use prevalence may vary dramatically across regions depending on legal status, medical prescribing frameworks, and recreational availability. This is particularly important because cannabis use in chronic pain populations may reflect therapeutic use rather than problematic use in some jurisdictions.

Consider including:

Legal status or region-specific cannabis policy as a moderator,

Distinction between prescribed medical cannabis and non-medical use where possible.

Response: Our protocol already included planned subgroup analyses comparing medical versus non-medical cannabis use where sufficient data are available (see p. 12). To further address the reviewer's concern, we have additionally included jurisdiction-specific cannabis legal status as a planned moderator, where sufficient information is available, and clarified these analyses in the Methods (p. 12).

Risk-of-bias integration could be stronger

The addition of sensitivity analyses using risk-of-bias scores is valuable. However, reliance on JBI sum scores may oversimplify methodological quality. Some items may contribute differently to prevalence bias.

Consider:

Presenting domain-level assessments,

Exploring whether high-risk studies disproportionately influence pooled estimates,

Clarifying how disagreements in quality ratings will be resolved.

Response: We thank the reviewer for this thoughtful comment. In response, we have clarified that the JBI Critical Appraisal Checklist will continue to be used because it is specifically designed and widely recommended for prevalence studies. However, risk of bias will not be interpreted solely on the basis of an overall summary score. In addition to conducting sensitivity analyses excluding studies judged to be at high risk of bias, we will report the individual JBI domain ratings for each included study in the supplementary materials to improve transparency. Finally, we have clarified that risk-of-bias assessments will be conducted independently by two reviewers, with any disagreements resolved through discussion and, when necessary, consultation with a third reviewer. We have revised the Methods accordingly (pp. 9-10).

Minor Comments

The abstract is generally clear, but the sentence:

“Therefore, a systematic review and meta-analysis, characterizing the prevalence rates… are urgently needed”

should be grammatically revised for clarity.

Response: We have revised the sentence accordingly in the Abstract.

Several sentences in the introduction are lengthy and could be condensed for readability, particularly in the sections discussing theoretical models and chronic overlapping pain conditions.

Response: We have reviewed and revised the Introduction section accordingly.

The protocol should clarify whether nicotine includes:

combustible tobacco,

vaping/e-cigarettes,

smokeless tobacco,

mixed nicotine products.

Similarly, cannabis terminology should clarify whether synthetic cannabinoids are included or excluded.

The manuscript alternates between “use disorders,” “dependence,” and “problematic use.” While improved from the prior version, terminology consistency could still be enhanced throughout the text.

Consider adding a schematic figure summarizing:

eligibility criteria,

outcome hierarchy,

analytic workflow,

subgroup analyses.

This would improve protocol clarity for readers.

Response: We appreciate the reviewer comments, and we have clarified the scope of nicotine and cannabis products included in the review. Specifically, nicotine-related outcomes may include combustible tobacco, electronic cigarettes/vaping products, smokeless tobacco, and other nicotine-containing products when assessed as part of nicotine use disorder or problematic nicotine use. Similarly, we have clarified the eligibility criteria for cannabis-related outcomes, including whether studies of synthetic cannabinoids will be eligible (see Table 1).

Following the previous revision, the protocol now clearly distinguishes substance use disorders as the primary outcome from problematic use as the secondary outcome. The term dependence is retained only when referring to historical diagnostic terminology (e.g., DSM-IV or ICD definitions) or the terminology used in the original studies. We are electing to keep this language to be consistent with clinically applicable terminology.

We appreciate the suggestion to include a schematic summarizing the study design and analytic workflow, and have included this to improve transparency (see Figure 1).

The rationale for selecting the Sidik–Jonkman estimator over alternative estimators (e.g., REML or DerSimonian-Laird) could be briefly justified.

Response: We thank the reviewer for this helpful suggestion. Upon further consideration, we agree that restricted maximum likelihood (REML) is a more appropriate choice for the planned analyses (see p. 12). Accordingly, we have revised the statistical analysis plan to use REML estimation rather than the previously proposed Sidik-Jonkman estimator. REML is a widely used estimator for random-effects meta-analysis and generally provides stable estimation of between-study variance, particularly when substantial heterogeneity is anticipated.

The manuscript should specify whether prevalence estimates will undergo variance-stabilizing transformation (e.g.

Decision Letter 2

Marianna Mazza

3 Aug 2026

Prevalence of Nicotine, Alcohol, and Cannabis Use Disorders Among Adults with Chronic Pain: Protocol for a Systematic Review and Meta-Analysis

PONE-D-25-57476R2

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PLOS One

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Marianna Mazza

PONE-D-25-57476R2

PLOS One

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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Table. Inclusion and Exclusion Criteria for Reviewed Studies.

    Mixed cancer-pain and non-cancer pain populations will be included only if specific data on non-cancer pain can be extracted from the article. Nicotine-related outcomes may include combustible tobacco, electronic cigarettes/vaping products, smokeless tobacco, and other nicotine-containing products when assessed as part of nicotine use disorder or problematic nicotine use. Cannabis-related outcomes may include synthetic cannabinoids.

    (DOCX)

    pone.0356365.s001.docx (15.8KB, docx)
    S2 Table. Terminology referring to problematic substance use.

    The list of terms above identified possible terms that indicate problematic substance use [79–85]. Following the full article search and data extraction, and updated table will be included in the published manuscript.

    (DOCX)

    pone.0356365.s002.docx (14.5KB, docx)
    S1 File. Inclusion and Exclusion Criteria for Reviewed Studies.

    (DOC)

    pone.0356365.s003.doc (82KB, doc)
    S1 Appendix. PubMed Search Strategy.

    (DOCX)

    pone.0356365.s004.docx (16.5KB, docx)

    Data Availability Statement

    No datasets were generated or analyzed during the current study. All relevant data from this study will be made available upon study completion, and analytic code will be shared on Open Science Framework.

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