Key Points

Question Are drug cues and craving associated with drug use outcomes?

Findings This systematic review and meta-analysis, including 656 statistics from 237 studies and representing 51 788 participants, yielded a significant association between drug cues and craving and subsequent drug use and relapse.

Meaning Results suggest that drug cues and craving are core mechanisms underlying drug use that are reliably and prospectively associated with drug use.

Introduction

Substance use disorders (SUDs) are the most prevalent and deadly forms of psychopathology.^1-3 Specifically, lifetime prevalence is estimated at approximately 35% and results in 11.8 million deaths annually, or about 1 in 5 deaths.^3,4 Consistently, SUDs incur staggering social costs and economic costs exceeding $740 billion annually in the US.⁵ Further, treatments for SUDs have limited efficacy⁶ with relapse rates of approximately 40% to 60%, comparable with other chronic illnesses.⁷ These sobering statistics underscore the urgent need to identify reliable predictors of drug use and relapse in order to improve diagnosis, tracking, and treatment.⁸

Drug cue reactivity and craving have been suggested as important underlying mechanisms as well as predictors of drug use and relapse.^6,9-11 Cue reactivity includes physiological and neural markers that arise in response to conditioned cues previously paired with drug use. In learning-based models of behavior, drug responses are unconditioned.¹² Cues that are repeatedly present during drug use become linked with drugs (and drug-related actions) and elicit conditioned responses.¹³ Consistently, decades of preclinical work documented that animals respond to drug-associated cues with strong conditioned responses (ie, cue reactivity), including sympathetic activation and dopamine release.^14,15 This work has also suggested that drug-cue exposure increases drug-seeking behavior and use.¹⁶

For humans, conditioned drug cues are typically environmental and can include the sight of drugs, paraphernalia, and interoceptive cues (eg, stress^17,18). Clinical studies have consistently shown that humans respond to such drug-associated cues with craving¹⁹ along with conditioned sympathetic activation, dopamine release, and associated neural activity in regions like the ventral striatum.^9,20-23 Some evidence suggests that cue exposure may lead to drug-seeking in humans, whereas the magnitude of cue reactivity may predict drug use.^6,23

Craving, a complex psychological phenomenon,^24,25 has long been conceptually linked to drug use.^26-28 Recently, drug craving was added as an SUD diagnostic criterion in DSM-5, where it is defined as a “strong desire for drugs.”^29(p491) Importantly, craving is (1) cited by drug users as the cause of relapse in retrospective studies^26,30,31; (2) associated with subsequent drug use in prospective studies^32,33; and (3) linked to drug use in Ecological Momentary Assessment (EMA) studies.^34,35 Craving that arises in response to drug-associated cues (ie, cue-induced craving) has also been shown to predict drug use^36-39 and relapse,^39-42 including in EMA studies.^37,42 Further, craving has been a target of treatment, with studies suggesting that reduction in craving is a mechanism of action in effective treatment.^43,44

Despite this suggestive evidence, the effect of cues and craving on drug use remains controversial^45-47; featured as core components in some models,⁴⁸ their significance is questioned in others.⁴⁹ Some have doubted whether exposure to cues increases use and relapse in humans; others have doubted whether the magnitude of cue reactivity and craving can predict use and relapse.^46,47,50-52 Some have specifically doubted the predictive role of cue-induced craving compared with other forms of craving.⁴⁷

Previously, we conducted a meta-analysis that suggested that food cue reactivity and craving predict eating and weight outcome.⁵³ Given the controversial role of craving and cue reactivity in the context of SUDs, here we evaluated the strength and consistency of evidence across the published literature, asking whether drug cues and craving can predict drug use and relapse. To that end, we conducted a systematic review and meta-analysis to assess and estimate the prospective association (ie, time 1 association with time 2) of 4 cue and craving indicators, including (1) cue exposure, (2) cue reactivity, (3) cue-induced craving, and (4) self-reported craving (without cue exposure), with drug use and relapse. We hypothesized a significant prospective association across cue and craving indicators, different drugs, craving measurements, and cue types, among others.

Methods

Search and Selection

This systematic review and meta-analysis was conducted from May to July 2021. We followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA)⁵⁴ reporting guidelines (Figure 1). We conducted separate literature searches for each drug using Google Scholar (chosen for its full-text search capabilities) up to the end of 2018 (eMethods and eTable 1 in the Supplement). We then reviewed titles and abstracts and selected a subset for full-text review. Next, we read full-text articles and applied final inclusion and exclusion criteria. In addition, we performed forward and backward searches on each included article to identify additional articles. In total, we reviewed 12 105 abstracts and 913 full-text articles.

Included studies met the following criteria: (1) at time 1, participants were exposed to drug cues and/or completed a self-report craving measure; (2) at time 2, at least 1 drug use outcome was reported; (3) time 1 occurred before time 2; (4) at least 1 reported analysis assessed the prospective association between time 1 measures and time 2 outcomes (excluding retrospective/cross-sectional statistics); and (5) statistics could be included in a meta-analysis (eMethods and eTable 1 in the Supplement; Table 1).⁵⁵ Final study inclusion and exclusion were determined independently by the 2 authors, yielding 656 statistics from 237 studies that were included in the omnibus analysis, representing 51 788 participants. Disagreements were discussed until an agreement was reached.

Extraction and Coding

For each included statistic, we extracted N (number of participants represented by that statistic), as well as information about cue type, drug type, outcome, lag from time 1 to time 2, assessment setting, questionnaire type, and participant gender, in order to identify potential moderators of associations (eMethods and eTable 1 in the Supplement; Table 2). Based on the study design, we coded each statistic into cue and craving indicators: (1) cue exposure statistics differentiated between drug use outcomes after exposing participants to drug-related cues vs neutral cues; (2) cue reactivity linked biological measures in response to drug cues (eg, heart rate, neural activity) with subsequent outcomes; (3) cue-induced craving linked self-reported craving in response to drug cues with outcomes; and (4) self-reported craving linked a craving measurement (without cue exposure) with outcome. Within cue-reactivity studies, we only selected functional magnetic resonance imaging statistics for the ventral striatum, which has been consistently implicated in Pavlovian conditioning and cue reactivity.^9,56-59 Within craving and cue-induced craving studies, we specifically coded the measure type as single item or multiple item because it has been argued by some that multiple-item measures would be more predictive, and we wanted to test that hypothesis.^60,61 Outcomes were coded into (1) drug use for direct measures of drug consumption; (2) drug use latency for latency from time 1 to drug use in time 2; (3) drug use proxy for proxy measures of drug consumption (eg, the Alcohol Purchase Task⁶²); (4) relapse for drug use in previously abstinent individuals; and (5) relapse latency for latency from time 1 to relapse in time 2. Hereinafter, we refer to drug use and relapse outcomes as the combination of all 5 outcome types. Each piece of information was extracted and/or coded by 1 of the 2 authors and then checked by the other. Disagreements were discussed until agreement was reached.

Statistical Analyses

All analyses were conducted using Comprehensive Meta-Analysis software, version 3.0 (Biostat),⁶³ following our own and others’ published meta-analyses.^50,53,64 We treated statistics as dependent if they came from the same population (both within and across studies). Within Comprehensive Meta-Analysis software, each statistic was weighted by its sample size; we then used random-effects models to calculate a mean prospective odds ratio (OR) and effect size r with 95% CIs for all analyses. We chose random-effects models to account for the heterogeneity among included studies, and calculated Q statistics that assessed for homogeneity among moderators. The omnibus analysis collapsed across all included statistics (including all cue and craving indicators and all outcomes), whereas other analyses addressed specific moderators. Lastly, we carried out publication bias analyses, including Rosenthal fail-safe N, trim and fill, Egger regression intercept, and a prediction interval for the omnibus results. Rosenthal fail-safe N gives a measure of how many studies with nonsignificant results would need to be published in order to make the meta-analytic results null.⁶⁵ Trim-and-fill analysis identifies and corrects for publication bias by estimating missing studies.⁶⁶ Egger regression intercept inspects asymmetry in a funnel plot of outcome by SE.⁶⁷ Prediction interval is an index of dispersion that indicates how much the true effect size varies.⁶⁸ Statistical analyses were performed from May to July 2021.

Results

As summarized in Figure 1, from a total of 18 205 identified records, 237 studies were included in the omnibus meta-analysis, including 656 statistics, representing 51 788 participants (21 216 with confirmed SUD diagnoses) (eMethods and eTable 1 in the Supplement). This primary analysis yielded an OR of 2.05 (95% CI, 1.94-2.15), indicating that each unit increase of cue and craving indicators was associated with more than double the odds of drug use and relapse (Table 3).

We tested several specific hypotheses regarding the association of each cue and craving indicator with drug use and relapse. Unless specified for a particular analysis (eg, study type, outcome type), we ran moderator analyses across all cue and craving indicators and/or across all outcome types to preserve power (eMethods, eTable 1, and eFigure in the Supplement). As hypothesized, cue exposure was associated with increased drug use and relapse across studies (OR, 2.28; 95% CI, 1.88-2.76). Further, the magnitude of cue-induced craving (OR, 3.01; 95% CI, 2.5-3.63), craving (OR, 2.16; 95% CI, 1.98-2.37), and cue reactivity (OR, 2.15; 95% CI, 1.62-2.86) was prospectively associated with increased odds of drug use and/or relapse. Cue-induced craving produced the strongest effect size (Q₃ = 10.08; P = .02).

All cue types were significantly associated with drug use and relapse (images OR, 3.42; 95% CI, 2.51-4.66; real OR, 2.59; 95% CI, 2.25-2.98; stress OR, 2.11; 95% CI, 1.55-2.88; mixed OR, 1.76; 95% CI, 1.31-2.37; imagery OR, 1.67; 95% CI, 1.04-2.67; media OR, 1.35; 95% CI, 1.02-1.8). Images and real cues showed the greatest effect (Q₅ = 27.46; images-real z test = 1.6; P = .12) (eFigure, eResults, and eTable 2 in the Supplement).

All cue and craving indicators were prospectively associated with outcomes across all categories of drug use and relapse (use OR, 2.56; 95% CI, 2.36-2.78; use latency OR, 2.2; 95% CI, 1.8-2.68; use proxy OR, 3.17; 95% CI, 2.25-4.46; relapse OR, 1.72; 95% CI, 1.59-1.86; relapse latency OR, 1.66; 95% CI, 1.32-2.09). Drug use outcomes were associated with stronger effect sizes compared with relapse (Q₄ = 58.18; P < .001). Importantly, we found the strongest associations for studies in which participants had confirmed SUD diagnoses (eTable 2 and eTable 3 Supplement).

Cue and craving indicators were prospectively associated with drug use and relapse across drug types. The 3 types representing the majority of included statistics were alcohol (OR, 2.47; 95% CI, 2.21-2.75), cocaine (OR, 1.98; 95% CI, 1.61-2.44), and nicotine (OR, 1.87; 95% CI, 1.73-2.02). The following 3 drug types represent a smaller subsample of statistics: cannabis (OR, 3.54; 95% CI, 2.1-5.98), opioids (OR, 1.91; 95% CI, 1.43-2.56), and other (OR, 3; 95% CI, 2.27-3.98), which includes polydrug use and other drugs (eg, methamphetamine).

To assess whether cue and craving indicators were prospectively associated with drug use and relapse across time lags, we coded statistics as reflecting drug use with the following time lags: same day, short term (1 day to 1 month), medium term (1-6 months), and long term (longer than 6 months). Cue and craving indicators were significantly associated with drug use and relapse across all time lags (same-day OR, 2.37; 95% CI, 2.18-2.57; short-term OR, 1.63; 95% CI, 1.54-1.73; medium-term OR, 1.64; 95% CI, 1.54-1.74; long-term OR, 1.73; 95% CI, 1.59-1.88). Although there was a significant association with time lags over 1 year, same day results showed the strongest association (Q₆ = 47.32; P < .001) (eResults and eTable 2 in the Supplement).

In a moderation analysis, we further evaluated the assessment setting, comparing studies in which (1) both measurements pertained to everyday life outside of laboratory settings (clinical OR, 1.47; 95% CI, 1.40-1.54); (2) studies that used EMA (OR, 2.05; 95% CI, 1.90-2.23); (3) both time 1 and time 2 were in the laboratory (OR, 2.18; 95% CI, 2.00-2.37); and (4) studies wherein time 1 pertained to measurements in the laboratory and time 2 to drug use and relapse in everyday life (OR, 1.82; 95% CI, 1.68-1.97). Across all methods, cue and craving indicators were prospectively associated with drug use and relapse, with the strongest association shown in laboratory and EMA studies (Q₃ = 94.79; P < .001).

We then assessed whether single-item measures of both craving and cue-induced craving were as effective as multiple-item measures. We found that for both self-reported and cue-induced craving, single-item measures were as prospectively associated with drug use and relapse as multiple-item measures. Specifically, for cue-induced craving (multiple-item OR, 3.42; 95% CI, 2.39-4.9; single-item OR, 3.02; 95% CI, 2.33-3.91; Q₁ = 0.31; P = .58) and for self-reported craving (multiple-item OR, 1.97; 95% CI, 1.78-2.19; single-item OR, 2.17; 95% CI, 1.96-2.42; Q₁ = 1.64; P = .20).

Lastly, another moderation analysis also evaluated sex and gender within the small subset of studies that included separate statistics for male and female participants (both sexes/genders OR, 2.05; 95% CI, 1.94-2.18; male OR, 2.61; 95% CI, 2.1-3.25; female OR, 1.82; 95% CI, 1.5-2.22). Statistics representing male participants showed the stronger association (Q₃ = 6.01; P = .05; male vs female z test = 2.39; P = .02 (eResults; eTable 2 in the Supplement).

To determine publication bias, Rosenthal fail-safe N revealed that 180 092 null studies would need to be published to nullify the meta-analytic results. Kendal τ did not indicate a risk of publication bias (τ = 0.03; zτ = 0.596; P = .55); Egger regression intercept detected some publication bias (intercept = 2.12; SE = 0.52; t₂₅₁ = 4.25; P < .001). Trim-and-fill analysis added 114 studies left of the mean and zero studies right of the mean (Figure 2), which brought the adjusted effect size to an OR of 1.31 (95% CI, 1.25-1.38). The prediction interval for the omnibus analysis was 1.21 to 3.44.

Discussion

To our knowledge, this was the first and most comprehensive systematic review and meta-analysis on the association of multiple types of cue and craving indicators with drug use and relapse for all drug types. These cue and craving indicators were included: cue exposure, physiological cue reactivity, cue-induced craving, and self-reported craving (without cue exposure). The primary analysis revealed, across all studies and all 4 cue and craving indicators, a significant prospective association with drug use and relapse outcomes (OR, 2.05; 95% CI, 1.94-2.15), such that a 1-unit increase in cue and craving indicators was associated with more than double the odds of future drug use and relapse. Moreover, each of the 4 cue and craving indicators was prospectively associated with more than double the odds of drug use/relapse. This association held across cue types, drug types, outcome, time lags, assessment settings, questionnaire types, and gender. To our knowledge, these consistent and significant prospective associations provide the strongest evidence to date that cues and craving may reliably predict drug use and relapse outcomes and may be core mechanisms underlying drug use.^48,69,70

Notably and contrary to doubts raised about the degree to which cue-induced craving can influence drug use outcomes,⁴⁷ the results demonstrate that cue-induced craving has the strongest meta-analytic effect size. Specifically, a 1-point increase in cue-induced craving more than tripled the odds of drug use and/or relapse. Interestingly, although learning-based models suggest that craving responses to real-life cues (eg, cigarettes, pipes) would be the best estimators of drug use and relapse outcomes, results indicate that responses to drug images are as strongly associated with drug use outcomes as real-life cues. This suggests that laboratory models that use such images may be particularly useful in estimating drug use and relapse outcomes.

Among assessment settings, we found that EMA and laboratory settings produced the strongest associations between cues and craving indicators and drug use and relapse outcomes.⁷¹ Given that EMA methods capture real-life behaviors in vivo, results from such studies may better represent the true effect size for the association of cue and craving indicators with drug use and relapse compared with studies that rely on retrospective reports.⁷² Thus, it is possible that this meta-analysis, which includes 84% non-EMA statistics, may, in fact, be underestimating the size of the true effect size for the association between cue and craving indicators with drug taking and relapse in everyday life.

Importantly, although we have so far not used predictive language to describe the results, the meta-analysis is composed of prospective studies with statistical analyses of associations between variables/risk factors at time 1 and a subsequent, prospective, and clinical outcome at time 2. Additionally, 60% of the included studies, representing 77% of the included participants, came from analyses of the type that some describe as prediction models, such as logistic and linear regressions. Indeed, an analysis isolating these statistics (representing 144 studies, 384 statistics, and 40 109 participants) suggests that the aggregate effect size was significant (eFigure in the Supplement). This is consistent with the idea that cue and craving indicators may predict drug use and relapse and are not only prospectively associated with them.

These results may support a potential causal inference for the role of cues and/or craving with drug use and relapse. Specifically, they satisfy multiple dimensions of potential causal inference.^73,74 Indeed, we report a significant association between cues and craving and drug use, as well as consistency of results across types of cue and craving indicators and numerous study- and participant-related factors. Additionally, the prospective nature of all included statistics provides support for the temporal sequence of these associations. Further, biological rationale and coherence have been previously demonstrated for cue and craving indicators as a core mechanism in SUDs. Notably, the effect sizes for the cue exposure indicator type specifically support the experimental evidence dimension of the criteria; however, craving is a subjective experience that can be provoked—not directly manipulated experimentally—and therefore does not fulfill this criterion. Nevertheless, together, these factors suggest a potential causative role for drug cues as well as craving in drug use and relapse, with the evidence being particularly strong for cue exposure owing to the subjective and nonexperimental nature of craving.

Although significant overall, the results also suggest some variability between studies, as the effect sizes ranged from 1.21 to 3.44. Accordingly, the results indicate that a unit increase in cues and craving was associated with 3 times higher likelihoods of drug use or relapse for some populations and a lesser likelihood for other subpopulations. The observed heterogeneity also affects the interpretation of publication bias analyses.⁷⁵ For example, the trim-and-fill method produced an adjusted effect size of 1.03. Although trim and fill is an informative method for assessing the presence of bias in a meta-analysis, its interpretive utility is limited in the presence of high variability.⁷⁶

The variability observed in this meta-analysis was likely attributable to individual differences, whereby certain SUD phenotypes could differentially show these associations. Indeed, it has been argued the heterogeneity of response to SUD treatments could stem from a lack of granular understanding of individual differences.⁷⁷ Consistently, in personalized-medicine approaches, the identification of different mechanisms of action is considered crucial for addressing the onset and maintenance of SUDs and for identifying treatment targets that are based on individual needs.⁷⁸ We expect future work can elucidate these mechanisms further, which in turn may aid in risk assessment and selection of targeted treatments.

The results have important potential implications for public health interventions and clinical treatment of SUDs. First, identification of empirically supported, variables and risk factors associated with drug use and relapse are essential tools in managing disease. In line with recommendations to use science-based action to limit the rise of SUDs,⁷⁹ the current results support the use of craving as a clinical estimator of drug use and SUDs, including strong recommendations to incorporate assessment of craving into clinical practice across settings. Furthermore, the lack of difference in predictive power between single- and multiple-item measures of craving is especially important in this context, as it suggests that a relatively simple and easy-to-collect single-item measure of craving could be used as early as primary care and emergency medicine, to estimate drug use and relapse. Importantly, cue and craving indicators remained significantly associated with drug use outcomes not only in the short term, as would be expected, but also in the long term—6 months and even years afterward. This suggests that repeated measures of cue and craving indicators (in particular cue-induced craving) during care and treatment could be used to educate patients and to assess treatment adherence and efficacy.

Second, the results support the removal or avoidance of drug cues as a treatment target. Indeed, many effective SUD treatments already include management of cues (eg, avoidance of high-risk situations⁸⁰) especially in early recovery. One classic example is the adage “people, places, and things” that may trigger drug use. Similarly, the results support craving—and the regulation of craving—as treatment targets.⁵¹ Again, many effective treatments already include training in strategies to regulate or cope with craving (eg, cognitive-behavioral^81,82 and mindfulness-based^83,84 treatments), and brief trainings that focus on regulation of craving reduce substance use.^85,86 Indeed, behavioral and pharmacological studies have both suggested that reduction of craving is one key mechanism of action of SUD treatment.^43,44 The results of this meta-analysis further support developing interventions that target craving directly.⁸⁶

Third, the results support the use of craving as an outcomes measure in SUD treatment studies—alongside drug use—as it satisfies multiple proposed criteria,⁸⁷ including clinical significance, ease of assessment using a variety of psychometrically validated measures, being altered by treatment, and predicting drug use across substances. Consistently, craving can be used during and after treatment to monitor treatment adherence, serve as an early warning sign during recovery, and estimate the risk of relapse in individuals who are already abstinent.

Limitations

There was heterogeneity among studies, and we carried out moderator analyses to parse out potential causes of this variability. Study type, assessment setting, lag from time 1 to time 2, drug type, and gender, among others, were factors that moderated the meta-analytic results. However, some moderator analyses were underpowered. For example, within drug type, cannabis and opioids were represented by only 6 and 9 statistics, respectively. Consequently, the ORs estimated for these drug types must be cautiously interpreted. Indeed, the main limitation of this meta-analysis results from the nature of the literature itself. Specifically, we found great variability in statistical reporting (eg, which statistics were reported), and most studies did not parse out statistics by crucial moderators, such as gender.⁸⁸ Indeed, the higher prevalence of SUDs in male participants,⁸⁹ coupled with the finding of stronger meta-analytic outcome in male participants compared with their female counterparts, makes differentiating across such moderators imperative, with important consequences for treatment and outcome (eResults in the Supplement). Overall, this curtailed our ability to assess the roots of this variability. Relatedly, we found a substantial number of studies with poor statistical reporting practices. Examples include studies reporting betas without specifying if they were standardized, reporting means without SDs, or reporting results without test statistics. With this, we call on researchers to adhere to best practice reporting guidelines^90,91 to allow for more studies to be included in future meta-analyses in this and other fields.

Conclusions

Taken together, the results of this systematic review and meta-analysis may be used as a methodological blueprint for future studies aiming to better elucidate the role and mechanism of action of cues and craving in SUDs. Results of this systematic review and meta-analysis suggest the use of craving as a measurable variable to estimate risk of drug use or relapse across assessment and clinical settings to aid in assessment and treatment.

Article Information

Accepted for Publication: January 19, 2022.

Published Online: June 1, 2022. doi:10.1001/jamapsychiatry.2022.1240

Corresponding Author: Hedy Kober, PhD, Department of Psychiatry, Yale School of Medicine, One Church St, Ste 701, New Haven, CT 06510 (hedy.kober@yale.edu).

Author Contributions: Ms Vafaie and Dr Kober had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: All authors.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: All authors.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Vafaie.

Obtained funding: Kober.

Administrative, technical, or material support: Kober.

Supervision: Kober.

Conflict of Interest Disclosures: Dr Kober reported receiving personal fees from Indivior Inc outside the submitted work. No other disclosures were reported.

Funding/Support: This work was funded by grant R01 DA043690 from the National Institute on Drug Abuse (Dr Kober).

Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: We thank Yale’s CANLab staff for their help with searches, preliminary screening, and prior versions of the meta-analytic database; Rebecca Boswell, PhD, Yale University, for her work on an earlier version of the meta-analysis, Ralitza Gueorguieva, PhD, Yale University, for statistical consultation, and Corey Roos, PhD, Yale University, for helpful comments on the manuscript. We thank 4 anonymous reviewers and the editors for their helpful comments. No one was financially compensated for their contribution.

Summary

This systematic review and meta-analysis investigated the predictive relationship between drug cues, craving, and subsequent drug use or relapse. A significant prospective association was identified, indicating that drug cues and craving are reliably associated with future drug use, suggesting these factors are core mechanisms in substance use disorders.

Introduction

Substance use disorders (SUDs) represent a significant global health concern, characterized by high prevalence, mortality rates, and substantial economic burden. Existing treatments demonstrate limited efficacy, with high relapse rates. Drug cue reactivity and craving are posited as key underlying mechanisms and potential predictors of relapse. Cue reactivity encompasses physiological and neural responses to stimuli associated with drug use, while craving represents a strong desire for the substance. Preclinical and clinical research consistently demonstrates the association of these factors with drug-seeking behavior and relapse. However, the strength and consistency of this association within the human SUD literature remains a subject of ongoing debate. This study aimed to comprehensively evaluate the prospective association between various cue and craving indicators and drug use/relapse outcomes through a systematic review and meta-analysis.

Methods

A systematic review and meta-analysis adhering to PRISMA guidelines was conducted. A comprehensive literature search identified studies meeting specific inclusion criteria, focusing on the prospective association between time 1 cue/craving measures and time 2 drug use outcomes. Data extraction involved detailed coding of various parameters, including cue type, drug type, outcome measures, and time lag. Random-effects models were employed for meta-analysis, accounting for heterogeneity across studies. Publication bias analyses were also conducted.

Results

The meta-analysis encompassed 656 statistics from 237 studies, representing 51,788 participants. The omnibus analysis revealed a significant prospective association between cue and craving indicators and drug use/relapse (OR = 2.05). Further analyses demonstrated significant associations for each cue and craving indicator (cue exposure, cue reactivity, cue-induced craving, self-reported craving). Cue-induced craving showed the strongest effect size. Associations were consistent across various drug types, outcome measures, time lags, assessment settings (with EMA and laboratory settings showing the strongest effects), and questionnaire types. While a significant association was observed across genders, the effect size was stronger for male participants. Publication bias analyses yielded mixed results.

Discussion

This study provides robust evidence supporting the prospective association of drug cues and craving with drug use and relapse across various SUDs. Cue-induced craving demonstrated a particularly strong predictive effect. The findings highlight the importance of cues and craving as core mechanisms underlying SUDs and underscore the potential of targeting these factors in prevention and treatment strategies. The study also emphasizes the value of EMA and laboratory settings in capturing this association. Although limitations related to heterogeneity and inconsistent statistical reporting exist, the study's comprehensive approach provides valuable insights. Further research should focus on identifying individual differences that influence the strength of this relationship.

Limitations

Heterogeneity across studies, limited power in some moderator analyses (particularly for specific drug types), and inconsistent statistical reporting in the included studies limited the analysis. The relatively small number of studies reporting data disaggregated by gender also affected the interpretability of gender-specific results. These limitations necessitate cautious interpretation of some findings and highlight the need for improved methodological rigor in future research.

Conclusions

This meta-analysis provides strong evidence for the prospective association of drug cues and craving with drug use and relapse. The findings support the incorporation of craving assessment into clinical practice, the development of interventions targeting cue exposure and craving regulation, and the use of craving as an outcome measure in treatment studies. The methodological approach of this study serves as a template for future investigations to further elucidate the intricate relationship between cues, craving, and SUDs.

Summary

A meta-analysis of 237 studies (656 statistics, 51,788 participants) reveals a strong association between drug cues, craving, and subsequent drug use/relapse. This suggests that these factors are central mechanisms in substance use disorders.

Introduction

Substance use disorders (SUDs) represent a significant public health crisis, characterized by high prevalence, mortality rates, and substantial economic burden. Existing treatments demonstrate limited efficacy, with relapse rates mirroring those of other chronic illnesses. Drug cue reactivity (physiological and neural responses to drug-related stimuli) and craving are posited as key predictors of relapse and continued drug use. Preclinical and clinical research supports the notion that conditioned responses to drug cues, including craving and physiological arousal, significantly influence drug-seeking behavior. However, the precise predictive power of these factors remains debated. This study aims to systematically evaluate the evidence linking drug cues and craving to drug use outcomes.

Methods

A systematic review and meta-analysis, adhering to PRISMA guidelines, was conducted. A comprehensive literature search across multiple databases yielded 237 studies meeting pre-defined inclusion criteria. Data extraction focused on cue type, drug type, outcome measures (drug use, relapse, latency), assessment methods, and participant characteristics to explore potential moderating effects. Statistical analyses, utilizing random-effects models, assessed the prospective association between cue/craving indicators (cue exposure, cue reactivity, cue-induced craving, and self-reported craving) and drug use/relapse outcomes. Publication bias analyses were also conducted.

Results

The primary analysis indicated a significant prospective association between cue/craving indicators and drug use/relapse (OR = 2.05). This association held robustly across various moderators including: cue type (images, real cues, stress, etc.), drug type (alcohol, cocaine, nicotine, etc.), outcome measure, time lag, assessment setting (laboratory, EMA, clinical), and gender. Cue-induced craving exhibited the strongest effect size. While some publication bias was detected, the overall findings remained significant.

Discussion

This comprehensive meta-analysis provides robust evidence supporting a strong prospective association between drug cues, craving, and drug use/relapse outcomes. The findings highlight the importance of cue-induced craving as a particularly potent predictor, and underscore the potential of both cue avoidance and craving regulation as treatment targets. The study’s limitations include heterogeneity among studies and potential underpowering of some moderator analyses. Future research should focus on addressing these limitations and further investigating individual differences influencing the cue-craving-drug use relationship.

Limitations

Study heterogeneity and underpowered moderator analyses limited the ability to fully explore sources of variability. Inconsistent statistical reporting practices across studies also hindered the analysis. The authors call for improved reporting standards to facilitate more comprehensive future meta-analyses.

Conclusions

This meta-analysis strongly suggests the value of incorporating craving assessment into clinical practice for SUDs. The findings support interventions targeting both cue avoidance and craving regulation, and suggest that craving may serve as a valuable outcome measure in treatment studies.

Summary

A large-scale study examined the link between drug cues (sights, smells, etc., associated with drug use) and cravings, and the likelihood of future drug use or relapse. The analysis of data from many studies strongly suggests a significant relationship: exposure to drug cues and experiencing cravings significantly increase the chances of someone using drugs again or relapsing. This highlights the importance of these factors in understanding and treating substance use disorders.

Introduction

Substance use disorders (SUDs) are a major public health problem, causing many deaths and immense economic costs. Current treatments are not always effective, and relapse is common. Researchers have focused on drug cue reactivity (physical and mental responses to drug-related stimuli) and craving as potential key factors in predicting relapse. Animal studies have shown that cues associated with drug use trigger strong responses, increasing drug-seeking behavior. Similarly, human studies show that exposure to drug cues leads to cravings and physiological changes, potentially predicting future drug use. However, the overall impact of cues and cravings on drug use has been debated. This study aimed to analyze existing research to definitively determine the predictive strength of these factors.

Methods

Researchers conducted a comprehensive review and analysis of studies published up to 2018, focusing on the prospective association between drug cues/cravings and subsequent drug use. They included studies that met specific criteria, focusing on data that could be used in a meta-analysis. The data collected included information on the type of cue (images, real objects, stress), the type of drug, the type of outcome measure, and other participant details. Statistical analyses were performed using specialized software, accounting for potential biases and variations among studies.

Results

The analysis included data from 237 studies and over 51,000 participants. The overall finding was a strong and consistent link between drug cues/cravings and future drug use or relapse. Specifically, increased cue exposure, cue reactivity, cue-induced craving, and general craving were all associated with a substantially higher chance of subsequent drug use. Cue-induced craving showed the strongest effect. These associations held true across different drug types, time periods, and study settings. While men showed a stronger association than women, both showed statistically significant results. There was some evidence of publication bias, but the main findings remained significant.

Discussion

This study provides strong evidence that drug cues and cravings are important predictors of drug use and relapse. Cue-induced craving was especially influential. The findings support the inclusion of craving assessment in clinical practice, as it could assist in predicting relapse risk and monitoring treatment success. Furthermore, the study supports targeting cues and craving management in treatment strategies.

Limitations

The study acknowledges limitations such as heterogeneity between studies and underpowered analyses for certain subgroups. Variability in statistical reporting across studies also limited the scope of the analysis. The researchers recommend that future studies adhere to better reporting practices for more thorough meta-analyses.

Conclusions

This study confirms the importance of drug cues and cravings in predicting drug use and relapse. The findings have implications for both clinical practice and public health initiatives. The use of craving as a measurable risk factor is recommended for clinical settings.

Summary

Scientists studied if thoughts about drugs and cravings were linked to people using drugs again. They looked at lots of studies and found a strong link. This means that strong cravings and seeing things that remind people of drugs are important reasons why people start using drugs again.

Introduction

Drug addiction is a really big problem. Many people struggle with it, and it causes many deaths each year. Sadly, treatments don't always work well, and many people start using drugs again. Scientists are trying to figure out what makes people use drugs again so they can make better treatments.

One thing scientists think is important is how people react to things that remind them of drugs (like seeing a cigarette). These reminders can cause strong cravings, which make it hard to stay away from drugs. Studies in animals and people show that these reminders and cravings are strongly connected to using drugs again.

Methods

Researchers looked at lots of studies to see if things that reminded people of drugs or their cravings led to drug use. They carefully chose studies that followed people over time to see what happened. They looked at different kinds of studies, including ones that used brain scans and questionnaires. They combined the results of all these studies to see the overall picture.

Results

The scientists found a strong link between things reminding people of drugs, cravings, and using drugs again. People who had stronger cravings or were exposed to drug cues were much more likely to use drugs again. This was true for many different types of drugs and different ways of measuring cravings. The strongest link was for cravings caused by seeing things that remind them of drugs.

Discussion

This study showed a very strong link between thoughts about drugs, cravings, and using drugs again. This is important because it can help doctors and researchers understand drug addiction better. Knowing this can help develop better ways to treat addiction by helping people avoid things that remind them of drugs and learn to cope with their cravings. However, there were differences among the studies, showing that not everyone reacts the same way. More research is needed to understand those differences.

Limitations

The researchers point out that not all studies were exactly the same and some had different ways of collecting information. Also, some types of drugs weren't studied as much as others.

Conclusions

This large study showed a clear link between drug reminders, cravings, and using drugs again. This information is really helpful for creating better treatments and helping people stay away from drugs.