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Adverse childhood experiences and craving: Results from an Italian population in outpatient addiction treatment

Subject: Psychology and Psychiatry

Published online by Cambridge University Press:  12 May 2023

Claudio Russo Open the ORCID record for Claudio Russo [Opens in a new window] ,
Natale Salvatore Bonfiglio Open the ORCID record for Natale Salvatore Bonfiglio [Opens in a new window] ,
Eva Orlando Open the ORCID record for Eva Orlando [Opens in a new window] ,
Giuseppe Falcone Open the ORCID record for Giuseppe Falcone [Opens in a new window] ,
Lucia Iuliano ,
Antonietta Grandinetti ,
Carmine Acconcia ,
Adriana Napoletano ,
Giada Conte  and
Barbara Landi
...Show all authors
Claudio Russo*
Affiliation:
Department of Addictions, Azienda Sanitaria Locale Salerno, Salerno, Italy Department of Medicine, Surgery and Dentistry, Salerno Medical School, University of Salerno, Salerno, Italy
Natale Salvatore Bonfiglio
Affiliation:
IRCCS Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
Eva Orlando*
Affiliation:
Department of Addictions, Azienda Sanitaria Locale Salerno, Salerno, Italy
Giuseppe Falcone
Affiliation:
Department of Addictions, Azienda Sanitaria Locale Salerno, Salerno, Italy
Lucia Iuliano
Affiliation:
Department of Addictions, Azienda Sanitaria Locale Salerno, Salerno, Italy
Antonietta Grandinetti
Affiliation:
Department of Addictions, Azienda Sanitaria Locale Salerno, Salerno, Italy
Carmine Acconcia
Affiliation:
Department of Addictions, Azienda Sanitaria Locale Salerno, Salerno, Italy
Adriana Napoletano
Affiliation:
Department of Addictions, Azienda Sanitaria Locale Salerno, Salerno, Italy
Giada Conte
Affiliation:
Department of Addictions, Azienda Sanitaria Locale Salerno, Salerno, Italy
Barbara Landi
Affiliation:
Department of Addictions, Azienda Sanitaria Locale Salerno, Salerno, Italy
Giovanni Truono
Affiliation:
Department of Addictions, Azienda Sanitaria Locale Salerno, Salerno, Italy
Marco D’Alto
Affiliation:
Department of Addictions, Azienda Sanitaria Locale Salerno, Salerno, Italy
Maria Pietronilla Penna
Affiliation:
Department of Pedagogy, Psychological Sciences and Philosophy, University of Cagliari, Cagliari, Italy
Antonio De Luna
Affiliation:
Department of Addictions, Azienda Sanitaria Locale Salerno, Salerno, Italy
*
Corresponding authors: Claudio Russo and Eva Orlando; Emails: clrusso@unisa.it; spec.orlandoe@aslsalerno.it
Corresponding authors: Claudio Russo and Eva Orlando; Emails: clrusso@unisa.it; spec.orlandoe@aslsalerno.it

Abstract

Background

Despite the growing interest in addiction research, which demonstrates the potential predictive role of adverse childhood experiences (ACEs), little is known about their impact on the psychological symptoms of craving.

Methods

After reviewing the relevant diagnostic criteria for addiction and comorbid mental disorders along with routinely collected clinical and service-use data, 208 outpatients were assessed on the study protocol. Following the recruitment phase, nominal and ordinal data were analyzed using nonparametric methods.

Results

Most of the outpatients reported ACEs (89.1%) and experienced cravings (73.4–95.7%). A positive association between ACEs and either intention and preplanning (r = .14, p < .05) or lack of control (r = .15; p < .05) of the craving behavior was found.

Conclusion

Craving behavior in addiction remains a subject of debate. Although correlation analyses showed significant associations between reported ACEs and measures of craving, they were relatively small.

Keywords

addictionchildhood adversitycomorbiditycravingItaly

Information

Type
Research Article
Information
Experimental Results , Volume 4 , 2023 , e11
Result type: Novel result
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press

Introduction

In recent decades, adverse childhood experiences (ACEs) have been associated with negative health outcomes in early adolescence and adulthood (Boullier & Blair, Reference Boullier and Blair2018; Felitti et al., Reference Felitti, Anda, Nordenberg, Williamson, Spitz, Edwards, Koss and Marks1998; Flaherty et al., Reference Flaherty, Thompson, Dubowitz, Harvey, English, Proctor and Runyan2013; Hughes et al., Reference Hughes, Bellis, Hardcastle, Sethi, Butchart, Mikton, Jones and Dunne2017). Further to the developmental impact of ACEs on children’s behavior and their social competence (Clarkson Freeman, Reference Clarkson Freeman2014; Manly et al., Reference Manly, Cicchetti and Barnett1994), a growing literature has found that the lived experience of ACEs can lead to long-term effects on the mental health of adults and the onset of chronic diseases (Boyce et al., Reference Boyce, Sokolowski and Robinson2012; Edwards et al., Reference Edwards, Holden, Felitti and Anda2003; Sonu et al., Reference Sonu, Post and Feinglass2019).

In addiction research, child maltreatment and genetic factors have been linked to cigarette and marijuana use (Azimi & Connolly, Reference Azimi and Connolly2022), and ACEs have accounted for issues with illicit drug use in one-half to two-thirds of cases (Dube et al., Reference Dube, Felitti, Dong, Chapman, Giles and Anda2003). A modeling study showed that more than half of heroin and crack cocaine use was tied to ACEs (Bellis et al., Reference Bellis, Hughes, Leckenby, Perkins and Lowey2014). Another study by Hodgins et al. (Reference Hodgins, Schopflocher, el-Guebaly, Casey, Smith, Williams and Wood2010) tied the experience of childhood maltreatment to the likelihood of experiencing a gambling problem. Furthermore, ACEs have been associated with an increased likelihood of binge drinking among adults (Crouch et al., Reference Crouch, Radcliff, Strompolis and Wilson2018).

Substance craving is a core symptom of substance use disorders (SUDs), namely an uncontrolled desire which may be linked to one’s intentional use of substances, including self-regulation failure, diminished self-efficacy regarding substance abstinence, and affective response patterns (Sayette, Reference Sayette2016). Different models have relied on theoretical and empirical investigations involving in-depth explanations of craving and focusing on the autonomous reactions, or analyzing one’s biological imbalance and brain activity (Danese et al., Reference Danese, Moffitt, Harrington, Milne, Polanczyk, Pariante, Poulton and Caspi2009; Koban et al., Reference Koban, Wager and Kober2023; Skinner & Aubin, Reference Skinner and Aubin2010).

Hence, the appearance of craving can be linked to the severity of addiction, including the comorbid conditions and behaviors (Hormes, Reference Hormes2017). As Stalcup et al. (Reference Stalcup, Christian, Stalcup, Brown and Galloway2006) noted, the clinical management of craving requires four domains of analysis, namely environmental cues, stress-related conditions, mental impairment, and physical withdrawal.

In clinical terms, substance craving may persist over time in patients with SUDs, during either the progression or early remission of the disorder. The timeframe required for detecting an early remission of SUDs ranges from 3 to 12 months, although the symptoms of craving may still be present (Hasin et al., Reference Hasin, O’Brien, Auriacombe, Borges, Bucholz, Budney, Compton, Crowley, Ling, Petry, Schuckit and Grant2013).

Objectives

For this study, we investigated the role of ACEs on craving measures and collected clinical and patient-reported data from a sample of outpatients undertaking routine addiction treatment.

Methods

Sample and procedure

A sample of 208 outpatients ranging from 18 to 65 years old participated in this study. Participants were recruited between the period February and August of 2021 from five distinct addiction service centers that receive public funding from the Italian National Health System and offer free admission and healthcare services in the Salerno area, South Italy. All participants were administered questionnaires by trained psychologists as part of an individualized, routine clinical support plan for addiction and received no compensation for their participation. While the data collection and assessment were undergoing, a total of 125 patients were excluded from the study based on prior medical evaluations or by having already completed their treatment. A group of independent physicians supported the data collection, aiding in cross-referencing the information on diagnosis, comorbidity, and pharmacotherapy.

Measures

The Adverse Childhood Experiences International Questionnaire (ACE-IQ) is a retrospective and self-reported measure of childhood adversities developed by the World Health Organization (WHO, 2018). A set of demographic information is followed by a total of 13 categories concerning adverse or stressful events during the first 18 years of one’s life.

The Substance Craving Questionnaire (SCQ-NOW) is a self-reported measure of craving that has been validated for substance use and gambling disorder, with Cronbach’s alpha ranging from 0.70 to 0.89 (Bonfiglio et al., Reference Bonfiglio, Renati, Agus and Penna2019). Adapted from the original version of a cocaine craving questionnaire by Tiffany et al. (Reference Tiffany, Singleton, Haertzen and Henningfield1993), it is composed of 45 items grouped into five dimensions. Each dimension is the sum of nine items, measuring the following factors: (1) desire to use a substance (DES); (2) intention to use a substance and preplanning (INT); (3) anticipation of positive outcomes (ANP); (4) anticipation of relief from substance withdrawal symptoms, or negative mood (ANR); (5) lack of control over substance use (LCO).

Data analysis

A preliminary data screening was performed to detect missing or invalid data. The patient characteristics were analyzed alongside the collected data from the subscales of the ACE-IQ and the SCQ-NOW. For analytical purposes, the mean and standard deviation of each continuous variable was noted, and the assumption of normality for each variable was examined by visual inspection and the Kolmogorov–Smirnov test.

The cut-off score or mean value of the SCQ-NOW referred to the validation results as reported by Bonfiglio et al. (Reference Bonfiglio, Renati, Agus and Penna2019). The scores were presented as the average of the summed items and dichotomized. A score below the mean value on each subscale was referred to as “absent craving.” Conversely, a score equal to or above the mean value was referred to as “experienced craving.” Likewise, two dimensions of exposure, namely experience of childhood adversity vs. no experience of childhood adversity, were dichotomized from the ACE-IQ subscales.

Chi-square tests, Fisher’s exact method, and Spearman rank correlations were used to analyze categorical variables. A bivariate regression analysis was used to establish the strength of the association between the subscales of the SCQ-NOW and the ACE-IQ. The demographic characteristics and other clinical information were expressed by covariates and examined with the counts and percentages across the SCQ-NOW subscales and the ACE-IQ total score.

After adjusting for potential confounding variables, all variables with a p-value less than .05 were combined from the bivariate analysis and entered a multivariate logistic regression model (Kirkwood & Sterne, Reference Kirkwood and Sterne2010). The final model was assessed using the Hosmer–Lemeshow goodness-of-fit test. Lastly, the adjusted odds ratios (aOR) were used to estimate the occurrence of experienced craving with a 95% confidence interval, given the exposure to at least one experience of childhood adversity.

Data analysis was performed using the IBM SPSS Statistics software, Version 24 (IBM Corp., Armonk, NY, USA) and Jasp 0.15 (Jasp Team, 2020).

Results

The patient characteristics are presented in Table 1.

Table 1.

Patient Characteristics

Note. DSM-5: Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5).

a The percentage is calculated within the subgroup on pharmacological treatment of addiction.

b Familiarity equals clinical information or individual’s awareness of relatives/significant others with addiction or mental disorders.

A consistent amount of exposure to ACEs and craving (89.1% and between 73.4 and 95.7%, respectively) was reported (Table 2).

Table 2.

Observed range, mean and standard deviation (SD) for ACE-IQ and SCQ-NOW

Specifically, 56% of outpatients met the ANR threshold and presented no familiarity with mental disorders, while 57.2% reported ACEs and no familiarity with addiction. Among those reporting ACEs, 59.2% were not presenting comorbid mental disorders, including 20.4% of outpatients that were below the ANR threshold and 47.8% that were above it. The identification of this clinical subgroup indicated that when comorbid mental disorders were absent, ANR was more experienced.

In Figure 1, statistically significant correlations between the ACE-IQ total score and the SCQ-NOW subscales are shown, including significant associations across the demographic and clinical characteristics.

Figure 1.

Adverse childhood experience and craving

In terms of service use, significant negative correlations between either the number of sessions of psychological intervention or psychotherapy (r = −.23; p = .02) or the duration of psychological therapies in days (r = −.18; p = .017) and the ACE-IQ total score were found. Furthermore, statistically significant negative correlations were found between either the number of sessions of psychological intervention or psychotherapy (r = −.26; p = .001) or the duration of psychological therapies in days (r = −.27; p = .001) and the ANR subscale. A statistically significant negative correlation was also found between the number of months individuals were enrolled in addiction services and the ANR subscale score (r = −.20; p = .004).

The group of outpatients for which the severity of addiction was either moderate (aOR = 2.47; 95% CI: 0.89, 6.82) or severe (aOR = 5.05; 95% CI: 1.06 16.1) were, respectively, 2.47 and 5.05 times more likely to report high ANR scores compared to the group of outpatients with a low severity addiction. Additionally, the ANR score was 1.15 times higher for the group of outpatients reporting ACEs (aOR = 1.15; 95% CI: 0.98, 1.33). The final model (X2 = 13.03; p = .005) indicated a high sensitivity (.96) and low specificity (.11).

Discussion

Previous research evidence has suggested that the occurrence of childhood adversities is a potential source of toxic stress (Oral et al., Reference Oral, Ramirez, Coohey, Nakada, Walz, Kuntz, Benoit and Peek-Asa2016), in which stress reactivity (Groh et al., Reference Groh, Rhein, Roy, Gessner, Lichtinghagen, Heberlein, Hillemacher, Bleich, Walter and Frieling2020) and a prolonged state of exposure may trigger the toxic effects later in life (Shonkoff et al., Reference Shonkoff and Garner2012).

The ACE-IQ total score (Mean: 3.01; SD: 2.32) revealed distinctive features that were consistent with previous findings (Garland et al., Reference Garland, Reese, Bedford and Baker2019), as shown in the pioneering study of Felitti et al. (Reference Felitti, Anda, Nordenberg, Williamson, Spitz, Edwards, Koss and Marks1998).

In the present study, we found small and positive associations between either the LCO or the INT and the ACE-IQ total score, along with a small and negative association between the ACE-IQ total score and the age of first child’s birth. As a significant association between the ANR and the severity of addiction emerged, the results from the final model were collateral to previous evidence on the intergenerational transmission of behavioral risks resulting from ACEs (Schickedanz et al., Reference Schickedanz, Halfon, Sastry and Chung2018). Not surprisingly, a significant association between the familiarity with mental disorders and the ANR was also tied to the severity of addiction.

Following the recruitment of 208 study participants, we analyzed a larger population of outpatients in routine addiction treatment at different levels of morbidity, chronicity, and severity, even when the criteria for exploratory and confirmatory factor analyses were not met. The main study limitation is that data analyses were performed on a limited sample with statistical significance that was determined at p < .05. Incidentally, we used retrospective estimates of ACEs which were tied to single self-reported measures of current craving. Therefore, the occurrence of overlapping physical or mental health issues will be a necessary step to validate our results with the ones from different socio-cultural settings and therapeutic contexts, as well as to benefit from the analysis of dissimilar measures for ACEs and craving at multiple points in time.

Conclusions

The main results extended the measures of craving in relation to the experience of ACEs and provided new evidence on cognitive, emotional, and automatic cravings in addiction (cf. Flaudias et al., Reference Flaudias, Heeren, Brousse and Maurage2019). Our pattern of analysis was consistent with the most recent findings from Romero-Sanchiz et al. (Reference Romero-Sanchiz, Mahu, Barrett, Salmon, Al-Hamdani, Swansburg and Stewart2022), in which urge and desire for cannabis were linked to craving following experimental exposure to trauma reminders. In particular, the duration of addiction treatment and the self-reported childhood adversities (Hughes et al., Reference Hughes, Bellis, Hardcastle, Sethi, Butchart, Mikton, Jones and Dunne2017; Kelly-Irving & Delpierre, Reference Kelly-Irving and Delpierre2019) contributed to explore the underlying mechanisms of ANR and more generally of psychological craving, compared to the self-medication attempts (Khantzian, Reference Khantzian1997), biological imbalance (Wise, Reference Wise1988), cue reactivity (Limbrick-Oldfield et al., Reference Limbrick-Oldfield, Mick, Cocks, McGonigle, Sharman, Goldstone, Stokes, Waldman, Erritzoe, Bowden-Jones, Nutt, Lingford-Hughes and Clark2017), and emotional states (Wilson, Reference Wilson2022). Drawing on findings from the craving literature, the lack of control or pre-planning, the intention to use substances, the occurrence of multiple addictions, a variable employment status, or familiarity with addiction were found significantly associated with the experience of childhood adversities.

Open peer review

To view the open peer review materials for this article, please visit http://doi.org/10.1017/exp.2023.12.

Data availability statement

Data are available upon reasonable request due to privacy or other restrictions.

Authorship contribution

Conceptualization, Methodology, Investigation, Data Curation, Project administration, Writing—Original Draft, Writing—Review and Editing (C.R. and E.O.; equally contributed). Conceptualization, Formal analysis, Writing—Original Draft, Writing—Review and Editing (N.S.B.). Conceptualization, Data Curation, Visualization (G.F., L.I., A.G., C.A, and A.N.; equally contributed). Data Curation, Project administration (G.C., B.L., G.T., and M.D.; equally contributed). Conceptualization, Writing—Original Draft (M.P.P.). Visualization, Supervision (A.D.L.).

Funding statement

This work received partial financial support from the Campania regional plan for addiction prevention and recovery (grant number 86/2016).

Competing interest

The authors have no conflict of interest to declare that is relevant to the content of this article.

Ethical standard

The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. Informed consent was obtained from all patients for being included in the study.

References

Azimi, A. M., & Connolly, E. J. (2022). Child maltreatment and substance use: A behavior genetic analysis. Child Maltreatment, 27(2), 279–289. https://doi.org/10.1177/10775595211064207.CrossRefGoogle ScholarPubMed
Bellis, M. A., Hughes, K., Leckenby, N., Perkins, C., & Lowey, H. (2014). National household survey of adverse childhood experiences and their relationship with resilience to health-harming behaviors in England. BMC Medicine, 12(1), 72. https://doi.org/10.1186/1741-7015-12-72.CrossRefGoogle ScholarPubMed
Bonfiglio, N. S., Renati, R., Agus, M., & Penna, M. P. (2019). Validation of a substance craving questionnaire (SCQ) in Italian population. Addictive Behaviors Reports, 9, 100172. https://doi.org/10.1016/j.abrep.2019.100172.CrossRefGoogle ScholarPubMed
Boullier, M., & Blair, M. (2018). Adverse childhood experiences. Paediatrics and Child Health, 28(3), 132–137. https://doi.org/10.1016/j.paed.2017.12.008.CrossRefGoogle Scholar
Boyce, W. T., Sokolowski, M. B., & Robinson, G. E. (2012). Toward a new biology of social adversity. Proceedings of the National Academy of Sciences, 109(suppl. 2), 17143–17148. https://doi.org/10.1073/pnas.1121264109CrossRefGoogle Scholar
Clarkson Freeman, P. A. (2014). Prevalence and relationship between adverse childhood experiences and child behavior among young children: Adverse childhood experiences and young children in child welfare. Infant Mental Health Journal, 35(6), 544–554. https://doi.org/10.1002/imhj.21460.CrossRefGoogle Scholar
Crouch, E., Radcliff, E., Strompolis, M., & Wilson, A. (2018). Adverse childhood experiences (ACEs) and alcohol abuse among South Carolina adults. Substance Use & Misuse, 53(7), 1212–1220. https://doi.org/10.1080/10826084.2017.1400568.CrossRefGoogle ScholarPubMed
Danese, A., Moffitt, T. E., Harrington, H., Milne, B. J., Polanczyk, G., Pariante, C. M., Poulton, R., & Caspi, A. (2009). Adverse childhood experiences and adult risk factors for age-related disease: Depression, inflammation, and clustering of metabolic risk markers. Archives of Pediatrics & Adolescent Medicine, 163(12). https://doi.org/10.1001/archpediatrics.2009.214.CrossRefGoogle ScholarPubMed
Dube, S. R., Felitti, V. J., Dong, M., Chapman, D. P., Giles, W. H., & Anda, R. F. (2003). Childhood abuse, neglect, and household dysfunction and the risk of illicit drug use: The adverse childhood experiences study. Pediatrics, 111(3), 564–572. https://doi.org/10.1542/peds.111.3.564.CrossRefGoogle ScholarPubMed
Edwards, V. J., Holden, G. W., Felitti, V. J., & Anda, R. F. (2003). Relationship between multiple forms of childhood maltreatment and adult mental health in community respondents: Results from the adverse childhood experiences study. American Journal of Psychiatry, 160(8), 1453–1460. https://doi.org/10.1176/appi.ajp.160.8.1453.CrossRefGoogle ScholarPubMed
Felitti, V. J., Anda, R. F., Nordenberg, D., Williamson, D. F., Spitz, A. M., Edwards, V., Koss, M. P., & Marks, J. S. (1998). Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults. American Journal of Preventive Medicine, 14(4), 245–258. https://doi.org/10.1016/S0749-3797(98)00017-8.CrossRefGoogle ScholarPubMed
Flaherty, E. G., Thompson, R., Dubowitz, H., Harvey, E. M., English, D. J., Proctor, L. J., & Runyan, D. K. (2013). Adverse childhood experiences and child health in early adolescence. JAMA Pediatrics, 167(7), 622. https://doi.org/10.1001/jamapediatrics.2013.22.CrossRefGoogle ScholarPubMed
Flaudias, V., Heeren, A., Brousse, G., & Maurage, P. (2019). Toward a triadic approach to craving in addictive disorders: The metacognitive hub model. Harvard Review of Psychiatry, 27(5), 326–331. https://doi.org/10.1097/HRP.0000000000000225.CrossRefGoogle Scholar
Garland, E. L., Reese, S. E., Bedford, C. E., & Baker, A. K. (2019). Adverse childhood experiences predict autonomic indices of emotion dysregulation and negative emotional cue-elicited craving among female opioid-treated chronic pain patients. Development and Psychopathology, 31(3), 1101–1110. https://doi.org/10.1017/S0954579419000622.CrossRefGoogle ScholarPubMed
Groh, A., Rhein, M., Roy, M., Gessner, C., Lichtinghagen, R., Heberlein, A., Hillemacher, T., Bleich, S., Walter, M., & Frieling, H. (2020). Trauma severity in early childhood correlates with stress and satiety hormone levels in a pilot cohort receiving diamorphine maintenance treatment. European Addiction Research, 26(2), 103–108. https://doi.org/10.1159/000505293.CrossRefGoogle Scholar
Hasin, D. S., O’Brien, C. P., Auriacombe, M., Borges, G., Bucholz, K., Budney, A., Compton, W. M., Crowley, T., Ling, W., Petry, N. M., Schuckit, M., & Grant, B. F. (2013). DSM-5 criteria for substance use disorders: Recommendations and rationale. American Journal of Psychiatry, 170(8), 834–851. https://doi.org/10.1176/appi.ajp.2013.12060782.CrossRefGoogle ScholarPubMed
Hodgins, D. C., Schopflocher, D. P., el-Guebaly, N., Casey, D. M., Smith, G. J., Williams, R. J., & Wood, R. T. (2010). The association between childhood maltreatment and gambling problems in a community sample of adult men and women. Psychology of Addictive Behaviors, 24(3), 548–554. https://doi.org/10.1037/a0019946.CrossRefGoogle Scholar
Hormes, J. M. (2017). The clinical significance of craving across the addictive behaviors: A review. Current Addiction Reports, 4(2), 132–141. https://doi.org/10.1007/s40429-017-0138-y.CrossRefGoogle Scholar
Hughes, K., Bellis, M. A., Hardcastle, K. A., Sethi, D., Butchart, A., Mikton, C., Jones, L., & Dunne, M. P. (2017). The effect of multiple adverse childhood experiences on health: A systematic review and meta-analysis. The Lancet Public Health, 2(8), e356–e366. https://doi.org/10.1016/S2468-2667(17)30118-4.CrossRefGoogle Scholar
JASP Team (2020). JASP (Version 0.15) [Computer software]. https://jasp-stats.org/.Google Scholar
Kelly-Irving, M., & Delpierre, C. (2019). A critique of the adverse childhood experiences framework in epidemiology and public health: Uses and misuses. Social Policy and Society, 18(3), 445–456. https://doi.org/10.1017/S1474746419000101.CrossRefGoogle Scholar
Khantzian, E. J. (1997). The self-medication hypothesis of substance use disorders: A reconsideration and recent applications. Harvard Review of Psychiatry, 4(5), 231–244. https://doi.org/10.3109/10673229709030550.CrossRefGoogle ScholarPubMed
Kirkwood, B. R., & Sterne, J. A. C. (2010). Essential medical statistics (2nd ed.). Blackwell Science.Google Scholar
Koban, L., Wager, T. D., & Kober, H. (2023). A neuromarker for drug and food craving distinguishes drug users from non-users. Nature Neuroscience, 26(2), 316–325. https://doi.org/10.1038/s41593-022-01228-w.CrossRefGoogle ScholarPubMed
Limbrick-Oldfield, E. H., Mick, I., Cocks, R. E., McGonigle, J., Sharman, S. P., Goldstone, A. P., Stokes, P. R. A., Waldman, A., Erritzoe, D., Bowden-Jones, H., Nutt, D., Lingford-Hughes, A., & Clark, L. (2017). Neural substrates of cue reactivity and craving in gambling disorder. Translational Psychiatry, 7(1), e992–e992. https://doi.org/10.1038/tp.2016.256.CrossRefGoogle ScholarPubMed
Manly, J. T., Cicchetti, D., & Barnett, D. (1994). The impact of subtype, frequency, chronicity, and severity of child maltreatment on social competence and behavior problems. Development and Psychopathology, 6(1), 121–143. https://doi.org/10.1017/S0954579400005915.CrossRefGoogle Scholar
Oral, R., Ramirez, M., Coohey, C., Nakada, S., Walz, A., Kuntz, A., Benoit, J., & Peek-Asa, C. (2016). Adverse childhood experiences and trauma informed care: The future of health care. Pediatric Research, 79(1–2), 227–233. https://doi.org/10.1038/pr.2015.197.CrossRefGoogle ScholarPubMed
Romero-Sanchiz, P., Mahu, I. T., Barrett, S. P., Salmon, J. P., Al-Hamdani, M., Swansburg, J. E., & Stewart, S. H. (2022). Craving and emotional responses to trauma and cannabis cues in trauma-exposed cannabis users: Influence of PTSD symptom severity. Addictive Behaviors, 125, 107126. https://doi.org/10.1016/j.addbeh.2021.107126.CrossRefGoogle ScholarPubMed
Sayette, M. A. (2016). The role of craving in substance use disorders: Theoretical and methodological issues. Annual Review of Clinical Psychology, 12(1), 407–433. https://doi.org/10.1146/annurev-clinpsy-021815-093351.CrossRefGoogle ScholarPubMed
Schickedanz, A., Halfon, N., Sastry, N., & Chung, P. J. (2018). Parents’ adverse childhood experiences and their children’s behavioral health problems. Pediatrics, 142(2), e20180023. https://doi.org/10.1542/peds.2018-0023.CrossRefGoogle ScholarPubMed
Shonkoff, J. P., Garner, A. S., & Committee on Psychosocial Aspects of Child and Family Health, Committee on Early Childhood, Adoption, and Dependent Care, & Section on Developmental and Behavioral Pediatrics. (2012). The lifelong effects of early childhood adversity and toxic stress. Pediatrics, 129(1), e232–e246. https://doi.org/10.1542/peds.2011-2663.CrossRefGoogle ScholarPubMed
Skinner, M. D., & Aubin, H.-J. (2010). Craving’s place in addiction theory: Contributions of the major models. Neuroscience & Biobehavioral Reviews, 34(4), 606–623. https://doi.org/10.1016/j.neubiorev.2009.11.024.CrossRefGoogle ScholarPubMed
Sonu, S., Post, S., & Feinglass, J. (2019). Adverse childhood experiences and the onset of chronic disease in young adulthood. Preventive Medicine, 123, 163–170. https://doi.org/10.1016/j.ypmed.2019.03.032.CrossRefGoogle ScholarPubMed
Stalcup, S. A., Christian, D., Stalcup, J., Brown, M., & Galloway, G. P. (2006). A treatment model for craving identification and management. Journal of Psychoactive Drugs, 38(2), 189–202. https://doi.org/10.1080/02791072.2006.10399843.CrossRefGoogle ScholarPubMed
Tiffany, S. T., Singleton, E., Haertzen, C. A., & Henningfield, J. E. (1993). The development of a cocaine craving questionnaire. Drug and Alcohol Dependence, 34(1), 19–28. https://doi.org/10.1016/0376-8716(93)90042-O.CrossRefGoogle ScholarPubMed
Wilson, S. J. (2022). Constructing craving: Applying the theory of constructed emotion to urge states. Current Directions in Psychological Science, 31(4), 347–354. https://doi.org/ 10.1177/09637214221098055.CrossRefGoogle ScholarPubMed
Wise, R. A. (1988). The neurobiology of craving: Implications for the understanding and treatment of addiction. Journal of Abnormal Psychology, 97(2), 118–132. https://doi.org/10.1037/0021-843X.97.2.118.CrossRefGoogle ScholarPubMed
World Health Organization (2018). Adverse Childhood Experiences International Questionnaire (ACE-IQ). https://www.who.int/publications/m/item/adverse-childhood-experiences-international-questionnaire-(ace-iq).Google Scholar
Figure 0

Table 1. Patient Characteristics

Figure 1

Table 2. Observed range, mean and standard deviation (SD) for ACE-IQ and SCQ-NOW

Figure 2

Figure 1. Adverse childhood experience and craving

Review 1: Adverse childhood experiences and craving: results from an Italian population in outpatient addiction treatment

Published online by Cambridge University Press:  12 May 2023
DOI: https://doi.org/10.1017/exp.2023.12.pr1 [Opens in a new window]
Robert Lundin [Opens in a new window] Deakin University, Burwood, Australia, 3125
Date of review:  18 April 2023
Role: reviewer
Recommendation/decision: accept

Conflict of interest statement

Reviewer declares none.

Comments

Comments to the Author: Thank you for addressing the requested changes. I am satisfied this has been completed.

Presentation

Overall score 4 out of 5
Is the article written in clear and proper English? (30%)
4 out of 5
Is the data presented in the most useful manner? (40%)
4 out of 5
Does the paper cite relevant and related articles appropriately? (30%)
4 out of 5

Context

Overall score 4 out of 5
Does the title suitably represent the article? (25%)
4 out of 5
Does the abstract correctly embody the content of the article? (25%)
4 out of 5
Does the introduction give appropriate context? (25%)
4 out of 5
Is the objective of the experiment clearly defined? (25%)
4 out of 5

Analysis

Overall score 4 out of 5
Does the discussion adequately interpret the results presented? (40%)
4 out of 5
Is the conclusion consistent with the results and discussion? (40%)
4 out of 5
Are the limitations of the experiment as well as the contributions of the experiment clearly outlined? (20%)
4 out of 5

Review 2: Adverse childhood experiences and craving: results from an Italian population in outpatient addiction treatment

Published online by Cambridge University Press:  12 May 2023
DOI: https://doi.org/10.1017/exp.2023.12.pr2 [Opens in a new window]
Varun Thirayan [Opens in a new window] Waikato DHB Laboratory, Hamilton, New Zealand, 3240
Date of review:  21 April 2023
Role: reviewer

Conflict of interest statement

Reviewer declares none.

Comments

Comments to the Author: EXP-23-0016

22.4.23

Abstract “Most of the outpatients reported ACEs and experienced cravings.” Recommend include percentage in brackets.

ACE-IQ – this is used in the abstract but the acronym should be written in full when first used. Perhaps include what survey you used in the methods part of abstract.

“A positive association between the ACE-IQ total score and either intention and pre-planning (INT) or lack of control (LCO) of the craving behaviour was found.” - was this finding statistically significant? If so mention this e.g. p<0.05.

“Craving behaviour in addiction remains a subject of debate. “ – I don’t believe this can be written in your conclusion as nothing in your results suggests this.

“Although correlation analyses showed significant associations between reported ACEs and craving, they were relatively small. “ – to say this, you need to quantify how small in your results.

--

The introduction still does not explain why you want to investigate the link between ACE and cravings. Lines 34-37 you mention different models have been used to explain cravings – but you do not say what they found or if there is controversy e.g. in the abstract you mention it is a subject of debate, but your introduction does not highlight the aspects of this debate which is important for the reader to be aware of to justify your objective.

In summary your intro is conveying to me: ACE is related to mental health problems. ACE is associated with substance use. Craving is associated to substance use and severity of addiction. Craving has various domains. Craving can persist even after substance use stops. – why does this justify your objective?

Is it important to be aware that more severe ACE could potentially be a predictor for greater cravings when attempting to stop SUD and the need for more support to be put in place? Is there controversy in the literature about this? Has this not been investigated before? This is important to discuss in your intro in my opinion.

Line 102 – I would not give a range % for the craving, give one % instead of 73.4-95.7 since you already mentioned you dichotomised the data.

Table 2 – are there missing values in the ACE-IQ section of Kolmogorov-smirnov? I see a large empty part of the table. If values are not relevant to ACE-IQ, may be worth putting a dash or n/a?

Line 105 to 110: The SCQNOW mean for each variable is found and shown in table 2. This is to help you say whether the person scored positive or negative in that particular variable. Yet, you only talk about INR? What about results from DES ANP LCO and INT? If nothing is relevant, state this.

e.g. Are you trying to say: Of the patients with no familiarity with mental disorders, SCQ-NOW threshold was met for ANR (56%), DES (%), ANP (%), LCO (%), and INT (%). Of patients with no familiarity with addiction, threshold was met for …. Etc.

Line 107, you say “among those reporting ACEs”. – in the methods you do not mention what the cut off for this is. Does scoring for 1 variable in ACE mean it is positive for ACE? Please make this clear in methods.

It would be useful if you could show results that a greater number of positive variables in ACE may increase scores in ANR DES ANP LCO or INT (Please check with your statistician about this).

Are you focusing only on ANR because you are looking at craving? If so you may want to mention in your methods that this is what you are looking at and specify why only ANR? However, consider that all factors of SQCNOW are a measure of cravin so you need to justify clearly why only ANR is discussed.

For my knowledge: Does “familiarity with addiction” mean, the patient is aware and has insight that they have an addiction?

In methods, line 52. What is the inclusion criteria for participant inclusion from the addiction service centres? Anyone receiving any form of treatment at the service centre? Are all participants assumed to an addiction as per DSM? I would make this clear in the methods since in the results you have said some are “not familiar with addiction” suggesting the participant did not think they had an addiction, yet to the service we are identifying they have an addiction based on ?DSM criteria.

Line 116: does this mean the more sessions of therapy and longer duration in therapy, the lower the ACE-IQ score? Does this mean, people with less ACE engaged better in services? If so, consider revision of the sentence structure e.g. there was a positive correlation between ACE and therapy duration etc. Currently it reads backwards i.e. the more therapy a person has the lower their ACE (yet ACE occurred historically).

Line 119: consider sentence revision. Are you trying to convey greater frequency of therapy and greater duration were associated with lower ANR?

Line 134: quote the ACEIQ scores from the other studies to show the comparison.

Line 139: avoid using the word “small”. What does this mean? That the p value is <0.05?

Line 139: do you mean “maternal” age of first child’s birth ? i.e. older the mother when first child is born, the less ACE? Consider sentence structure.

Line 124 and 140: in the methods you did not say how “severity of addiction” was found.

Line 144: unclear what this sentence means

Line 147-8: p<0.05 is considered statistically significant, remove this as a limitation.

Line 149-152: unclear what this sentence means or why it is relevant to your results. Are you trying to say a limitation is that your study did not consider physical health comorbidities or cultural contexts? Table 1 has 30.8% comorbid mental health issues so you did record this.

Line 154: In your conclusion, why are you referencing Flaudias 2019 paper? It is meant to be your conclusion based on your own findings, not Flaudias.

Line 156-158 put in your discussion, not conclusion. This referenced paper talked about urge and desire but you made limited note of DES variable in your findings.

Your whole “conclusion” section should be revised. Some of what you mention could go in your “discussion” but your conclusion section should have your overall summary and conclusion of your results and key take home message.

There are 14 authors mentioned on this paper. I would suggest you collaborate to improve this manuscript. The results are important but significant revision of manuscript is required in my opinion.

Note to editor: does a statistician need to check if the appropriate tests have been used? E.g. In the methods the Kolmogorov-smirnov test was used to assess normality for each variable. Is this appropriately used in table 2 for the ACE-IQ?

Presentation

Overall score 2 out of 5
Is the article written in clear and proper English? (30%)
2 out of 5
Is the data presented in the most useful manner? (40%)
2 out of 5
Does the paper cite relevant and related articles appropriately? (30%)
2 out of 5

Context

Overall score 2.5 out of 5
Does the title suitably represent the article? (25%)
5 out of 5
Does the abstract correctly embody the content of the article? (25%)
2 out of 5
Does the introduction give appropriate context? (25%)
1 out of 5
Is the objective of the experiment clearly defined? (25%)
2 out of 5

Analysis

Overall score 1 out of 5
Does the discussion adequately interpret the results presented? (40%)
1 out of 5
Is the conclusion consistent with the results and discussion? (40%)
1 out of 5
Are the limitations of the experiment as well as the contributions of the experiment clearly outlined? (20%)
1 out of 5