Introduction
Substance dependence disorder is one of the most significant mental health challenges in today’s world, affecting the individual and their family and the broader community (Vujanovic et al., 2020). This disorder is characterized by behavioral, cognitive, and physical symptoms, with its most prominent feature being the continued use of substances despite experiencing negative consequences (American Psychiatric Association, 2022). Reports indicate a growing global prevalence of substance abuse (Saboor et al., 2019), with estimates suggesting that between 162 to 324 million people used substances in the past year (Aryan et al., 2020). In Iran, approximately 4 million individuals are regular or occasional substance users (Drug Control Headquarters, 2019), and the mortality rate resulting from drug overdose is on the rise (Zeledona et al., 2020).
One of the key concepts in the field of substance use is addiction readiness, which refers to a psychological predisposition toward substance use. This concept implies that certain individuals are more likely to develop addiction when specific conditions are present (Sohrabi et al., 2019). Addiction Readiness primarily develops during adolescence and young adulthood (Trifilieff et al., 2017), a period marked by biological, cognitive, and social changes (Karami, 2018). Adolescents are particularly vulnerable to the harms associated with addiction compared to other age groups (Mosalman et al., 2020), and studies have shown a decline in their negative attitudes toward substances along with an increase in high-risk behaviors (Arghabaei et al., 2018).
Addiction readiness is influenced by multiple factors whose interaction contributes to the initiation and continuation of substance use. According to the cognitive-behavioral approach, irrational beliefs or cognitive distortions play a significant role in the development and persistence of maladaptive behaviors and psychological disorders (Ellis, 2005). These distortions, especially in the context of interpersonal cognitive distortions, affect how individuals analyze, interpret, and judge events, leading to inaccurate assessments of situations and poor decision-making (Ciccarelli et al., 2017). Such faulty evaluations are among the key reasons individuals may turn to substance use as a way to regulate emotions or escape problems (Chukwuorji et al., 2021).
Since the 1980s, research has focused on interpersonal cognitive distortions related to beliefs about interpersonal relationships (Stackert & Bursich, 2003). Ellis (2003) defined these beliefs as exaggerated, rigid, irrational, and absolute regarding human relationships. Studies have shown that interpersonal cognitive distortions are associated with negative psychological outcomes, such as anxiety (Yazici-Çelebi & Kaya, 2022), decreased life satisfaction (Şimşek et al., 2021), feelings of loneliness, and problematic internet use (Kuzucu et al., 2020). Additionally, individuals with greater interpersonal cognitive distortions are more susceptible to substance use–related psychological problems than healthy individuals (Zarbakhsh Bahri et al., 2023). In this regard, Ahmadi Tahour and Najafi (2011) emphasized the role of dysfunctional cognitive beliefs as a psychological factor predicting Addiction Readiness. Furthermore, Haji alizadeh et al. (2009) demonstrated that the prevalence of cognitive distortions is higher among substance users than healthy controls.
Another important factor in addiction readiness is co-dependency. Research indicates that social relationships and co-dependency have a significant impact on the tendency toward substance use (Dupree, 2010). Co-dependency refers to a state in which an individual becomes excessively preoccupied with the lives of others, which can lead to maladaptive behaviors (Mendenhall, 1989). Individuals with co-dependency typically neglect their needs due to an excessive focus on the emotions of others and often engage in self-destructive behaviors (Whitfield, 2002). According to findings, co-dependency has a significant relationship with behavioral addiction and can be an influential factor in Addiction Readiness (Diotaiuti et al., 2022). Additionally, co-dependency is associated with psychological problems, low self-esteem (Dear et al., 2005), as well as family stress and substance addiction (Fuller & Warner, 2000).
In contrast to risk factors, resilience is one of the key psychological characteristics that facilitates successful adaptation when facing stress and provides a positive appraisal of stressful events (Gras Pérez et al., 2019; Silk et al., 2007). Resilient individuals can withstand hardships and maintain their bio-psychological balance (Connor & Davidson, 2003), and this characteristic can act as a protective factor against addiction readiness (Mohammadi et al., 2006). Research has shown that both individual and environmental resilience play an effective protective role in reducing the incidence of psychological disorders and other illnesses (Llistosella et al., 2023). Meanwhile, resilience is strongly associated with the mental health of children and adolescents (Mesman et al., 2021) and can predict the psychological well-being of students (Bagheri Sheykhangafshe et al., 2021). Ghanbari Talab and Fooladchang (2015) also found a negative relationship between resilience and Addiction Readiness, indicating its role as a protective factor.
According to global reports, the typical age of onset for substance use is between 16 and 20 years, and this age is gradually decreasing (Eiseman et al., 2019). In Iran as well, addiction remains a serious social challenge, and adolescents, due to their psychological and developmental characteristics, are at greater risk than other age groups for initiating substance use, with many continuing this behavior in subsequent years after initiation (Eyni et al., 2020). Therefore, precise identification of factors influencing Addiction Readiness is a critical focus of psychological research (Sadri Damirchi et al., 2019). Understanding these factors, especially psychological, familial, and social components, is crucial for identifying individuals at risk and designing preventive interventions (Eslamdoost, 2018). Furthermore, awareness of these factors can aid in selecting appropriate treatment methods and providing effective counseling and support services (Oudejans et al., 2019).
Accordingly, simultaneous examination of individual, familial, and social factors within conceptual models featuring mediating roles can provide a deeper understanding of the addiction readiness process. Despite the prominent role of resilience as a protective factor, the mediating role of resilience in the relationship between addiction readiness and variables, such as co-dependency and interpersonal cognitive distortions, has received less attention. This research gap highlights the necessity of designing a predictive model for adolescent addiction readiness with an emphasis on these variables.
Accordingly, the present study examines the relationships between co-dependency, interpersonal cognitive distortions, resilience, and addiction readiness in adolescents. It is hypothesized that co-dependency and interpersonal cognitive distortions are positively related to addiction readiness, while resilience is negatively related. Additionally, the mediating role of resilience in the relationship between Co-dependency and addiction readiness, as well as between interpersonal cognitive distortions and addiction readiness, is also investigated (Figure 1).



Materials and Methods

Type of research and study design
From a purpose perspective, this research is classified as a fundamental (basic) study. Methodologically, it is a descriptive-correlational study conducted to examine the direct and indirect relationships among co-dependency, interpersonal cognitive distortions, resilience, and addiction readiness in adolescents, using structural equation modeling (path analysis).

Participants and sampling methods
The statistical population of the study consisted of all male high school students (grades 10 to 12) in Abadan City, Iran, during the 2022–2023 academic year. A multistage cluster sampling method was employed. Initially, several high schools were randomly selected, and then multiple classes were chosen from each selected school. In total, 220 students participated in the study. After removing incomplete responses, 200 complete questionnaires were used for the final analysis. The age range of participants was between 15 and 18 years. The inclusion criteria were obtaining informed consent, being enrolled in high school, and having no history of diagnosed psychiatric disorders (based on the school counselor’s report). Meanwhile, the exclusion criteria included incomplete questionnaire responses or withdrawal of consent by participants at any stage during data collection.

Study procedure
After obtaining ethical approval from the relevant committee and coordinating with the Abadan County Education Department, the online questionnaire link, designed on the “Porsall” platform, was provided to the counselors of the selected schools. In collaboration with the counselors, the questionnaire link was shared in the official messaging groups of students in grades 10 through 12.
The introduction accompanying the link clearly explained the purpose of the study, the voluntary nature of participation, the confidentiality of the information, and adherence to ethical principles. Additionally, an informed consent form was included at the beginning of the questionnaire, which students were required to read and approve before participating. All data collection procedures were conducted remotely and without in-person contact.

Research instruments

Addiction readiness questionnaire
The addiction readiness questionnaire was developed by Weed and Butcher (1992), and its Persian version was validated by Zargar (2008). This instrument consists of 36 main items and 5 lie-detection items, scored based on a 4-point Likert scale ranging from 0 (“strongly disagree”) to 3 (“strongly agree”). scores above 21 indicate a high level of readiness toward substance use.
The construct validity of this scale was established through its correlation with the symptom checklist-25 scale (r=0.44), and its reliability was reported using the Cronbach α coefficient of 0.90 (Zargar, et al., 2008). Moreover, Sohrabi et al. (2019) reported a Cronbach α of 0.94. In the present study, the reliability coefficient calculated by Cronbach α was 0.86.

Resilience questionnaire
The resilience questionnaire was developed by Connor and Davidson (2003), and its Iranian version was standardized by Mohammadi (2006). The questionnaire includes 25 items scored based on a 5-point Likert scale ranging from 0 (“Completely False”) to 4 (“Completely True”). The total score of the questionnaire ranges from 0 to 100.
In Mohammadi’s study (2006), item-total correlations ranged from 0.41 to 0.64, and the overall Cronbach α coefficient was reported as 0.89. Additionally, Ghanbari Talab and Fooladchang (2015) found the reliability coefficient of this instrument to be 0.74. In the present study, the Cronbach α coefficient was calculated as 0.88, indicating satisfactory reliability of the instrument.

Interpersonal cognitive distortions questionnaire
The interpersonal cognitive distortions questionnaire was developed by Hamamci and Büyüköztürk (2004) and translated into Persian by Bahari (2010). The instrument consists of 19 items scored based on a 5-point Likert scale ranging from 1 (“strongly disagree”) to 5  (“strongly agree”), with total scores ranging from 19 to 95.
In the original study, the construct validity of the tool was confirmed through correlations with the irrational beliefs scale (r=0.45), automatic thoughts questionnaire (r=0.53), and tendency toward interpersonal conflict (r=0.53). In Iran, Esmaeel Poor et al. (2015) confirmed the concurrent validity of the questionnaire using measures of borderline personality traits and immature neurotic defense styles. Bahari (2010) reported the overall reliability of the scale with a Cronbach α coefficient of 0.79. In the present study, the Cronbach α coefficient was calculated at 0.63 for this scale.

Co-dependency questionnaire
This instrument was developed by Spann and Fischer (1990), and its Persian version was validated by Ashraf (2010). The questionnaire consists of 16 items rated based on a 6-point Likert scale ranging from 1 (“strongly disagree”) to 6 (“strongly agree”). two items (items 5 and 7) are scored inversely.
In Ashraf’s (2010) study, the construct, convergent, and criterion validity of this instrument were confirmed, demonstrating its ability to distinguish between co-dependent and non-co-dependent groups, as well as between individuals with addicted and non-addicted parents. Additionally, a significant positive correlation with Wilson’s co-dependency questionnaire was reported. The Cronbach α coefficient of this instrument was reported as 0.87 in Ashraf’s study and 0.79 in Khosravi et al. (2013) for the Iranian population. In the present study, the Cronbach α coefficient was calculated at 0.67.

Data analysis
Before conducting the main analyses, statistical assumptions, including data normality, absence of multicollinearity, and sample size adequacy, were examined and confirmed. Data collection was performed remotely via online questionnaires with the cooperation of school counselors.
For data analysis, descriptive statistics, the Pearson correlation coefficients, and structural equation modeling (path analysis) were employed using the AMOS software, version 24. To assess the significance of indirect effects, the bootstrap method with 5000 resamples was applied.

Results

Descriptive analysis of data
This section presents descriptive statistics related to the demographic characteristics (grade level and age) and the main variables of the study.
A total of 200 students participated in the study. Among them, 87 students (43.5%) were in the 10th grade, 54 students (27%) in the 11th grade, and 59 students (29.5%) in the 12th grade. The mean age of the participants was 16.52 years with a standard deviation of 0.90. The age range of the sample was between 15 and 18 years.
The data presented in Table 1 indicate that the distribution of scores for the study variables falls within an acceptable range in terms of skewness and kurtosis indices; therefore, the assumption of data normality is confirmed.
Based on the results of Pearson’s correlation coefficient, a significant relationship was observed between addiction readiness and all three independent variables of the study. Specifically, interpersonal cognitive distortions (r=0.396, P<0.01) and co-dependency (r=0.470, P<0.01) have a positive and significant relationship with addiction readiness, whereas resilience (r=-0.371, P<0.01) shows a significant negative relationship with addiction readiness.
Accordingly, with the increase in co-dependency and interpersonal cognitive distortions, readiness for substance use also increases; meanwhile, higher levels of resilience are associated with a decrease in addiction readiness.



Path analysis and model fit indices
To examine the fit of the model predicting addiction readiness based on co-dependency and interpersonal cognitive distortions with the mediating role of resilience, path analysis was conducted using the Maximum Likelihood Estimation method.
Before performing the path analysis, the following statistical assumptions were assessed: univariate normality was evaluated using skewness and kurtosis indices (Table 1); multivariate normality was confirmed through the standardized Mardia’s coefficient with a value of 0.927; the absence of multicollinearity was examined by reviewing the Pearson correlation matrix (Table 1), which indicated no extremely high correlations among the predictor variables. Table 2 presents the model fit indices.



As shown in Table 2, all model fit indices are within acceptable ranges. These results indicate a good fit of the proposed model to the research data.
The standardized path coefficients are presented in Figure 2, which illustrates the direct and indirect relationships among the variables.



Analysis of direct effects in the path model
Table 3 presents the standardized and unstandardized coefficients of the direct paths between the study variables along with their statistical significance.
The results of Table 3 indicate that all direct paths in the model, except for the path between interpersonal cognitive distortions and resilience, are statistically significant. Specifically, co-dependency has a positive and significant effect on addiction readiness; resilience plays a significant negative role in reducing addiction readiness; interpersonal cognitive distortions have a direct and positive impact on addiction readiness; however, their effect on resilience was not significant. Additionally, the model was able to explain 36% of the variance in addiction readiness through the variables included.



Analysis of indirect effects (mediation)
To examine the mediating role of resilience in the relationship between co-dependency and interpersonal cognitive distortions with addiction readiness, the bootstrap method with 5000 resamples was used. The results of the bootstrap test are presented in Table 4.
According to Table 4, the indirect effect of co-dependency on addiction readiness through resilience is significant (P=0.018), as the 95% confidence interval for this effect does not include zero. Therefore, resilience plays a significant mediating role in the relationship between co-dependency and addiction readiness. In contrast, the indirect effect of interpersonal cognitive distortions on addiction readiness through resilience is not significant (P=0.725), since the confidence interval includes zero. Hence, resilience does not mediate this relationship.



Discussion
The present study examined the mediating role of resilience in the relationship between co-dependency and interpersonal cognitive distortions with addiction readiness in adolescents. The results of the path analysis supported the study hypotheses, except for the mediating role of resilience in the relationship between Interpersonal cognitive distortions and addiction readiness.
Firstly, the findings indicated a significant positive relationship between co-dependency and addiction readiness. This result aligns with the findings of Karapet (2024), Salonia et al. (2021), and Bortolon et al. (2016), who introduced co-dependency as a maladaptive pattern in interpersonal relationships, which can pave the way for self-harming behaviors, including addiction readiness. From a theoretical perspective, Cermak (1986) posits that co-dependency stems from a lack of differentiation of the “self” in interpersonal relationships, and a co-dependent individual may engage in risky behaviors, such as substance use, to gain a sense of worth, acceptance, or approval from others. The present study’s findings also demonstrate that adolescents with co-dependency, due to excessive emotional reliance on others, are at greater risk of engaging in risky behaviors.
Secondly, a significant positive relationship between interpersonal cognitive distortions and addiction readiness was also confirmed. This finding aligns with the results of studies by Zarbakhsh Bahri et al. (2023), Su Topbaş et al. (2024), and Ahmadi Tahour and Najafi (2011). Interpersonal cognitive distortions, especially in adolescents with weaker communication skills and emotional regulation, can lead to misinterpretations of others’ intentions or behaviors, feelings of rejection, social isolation, and increased psychological distress, conditions that may drive the individual toward maladaptive strategies such as substance use.
Thirdly, the findings indicated a significant negative relationship between resilience and addiction readiness. This result is consistent with research by Boron et al. (2023), Qutb and Abedi (2024), and Vinayak and Judge (2018), who introduced resilience as a protective factor against various psychological harms and risky behaviors, including addiction. Adolescents with higher levels of resilience have a greater ability to regulate negative emotions, resist peer pressure, and cope adaptively with life challenges; consequently, their likelihood of engaging in substance use decreases.
Overall, the results of the present study indicate that co-dependency and interpersonal cognitive distortions are factors that increase addiction readiness in adolescents. In contrast, having a high level of resilience can play a protective role and mitigate the negative effects of these variables. Next, the mediating role of resilience in these relationships is examined.

Examining the mediating role of resilience
The results showed that resilience has a significant mediating role in the relationship between co-dependency and addiction readiness. This finding is consistent with the study by Kaya et al. (2024), which demonstrated that resilience can reduce the negative effects of dependent and maladaptive relationships. In other words, co-dependent adolescents who possess a high level of resilience, despite having maladaptive emotional dependencies, are less likely to engage in high-risk behaviors, such as substance use. In such cases, resilience acts as an internal and supportive resource, protecting the individual against the negative consequences of co-dependency.
However, contrary to expectations, the mediating role of resilience in the relationship between interpersonal cognitive distortions and addiction readiness was not confirmed. This finding can be explained by the deep, persistent, and ingrained nature of cognitive distortions. These distortions typically develop in early life within the family context, upbringing, and initial relationships, gradually becoming part of the individual’s cognitive structure. Therefore, changing them requires specialized and targeted cognitive interventions. Even with a high level of resilience, an individual may still be entangled in misinterpretations, perceived threats, or feelings of rejection in interpersonal relationships, factors that can weaken or neutralize the protective effect of resilience.
Overall, the findings of this study suggest that focusing on cognitive, emotional components, such as co-dependency and resilience, can be effective in preventing addiction readiness in adolescents. However, when dealing with interpersonal cognitive distortions, merely strengthening resilience is insufficient, and the use of more structured cognitive–behavioral interventions such as cognitive behavioral therapy or schema therapy appears necessary to fundamentally modify these maladaptive patterns.

Conclusion
To identify the underlying factors contributing to behavioral disorders, a precise examination of the proximal and influential components affecting these behaviors is of special importance. One such component is psychological resilience, defined as an individual’s ability to cope with challenges and adapt to difficult and stressful conditions. Resilience is a flexible and dynamic trait shaped by the interaction between individual and environmental factors. Among environmental factors, emotional and interpersonal relationships play a prominent role, especially during adolescence, when the individual is seeking to define social identity and gain acceptance within peer groups.
In this context, co-dependency, as a form of maladaptive emotional attachment to others, can steer adolescents toward high-risk behaviors, such as substance use, particularly when these behaviors are performed to gain approval and acceptance from peers. However, the findings of the present study showed that resilience can serve as an effective mediator in this relationship. Adolescents with co-dependency who possess high levels of resilience demonstrate greater resistance to social pressure, make more independent decisions, and consequently show a lower readiness for substance use.
On the other hand, interpersonal cognitive distortions were also identified as important factors influencing addiction readiness in adolescents. These distortions, which include inaccurate and irrational beliefs about others and social relationships, can lead to misinterpretations, feelings of rejection, and ultimately a tendency toward maladaptive coping strategies such as substance use. Although resilience has a protective role against many psychological harms, its effect alone is not sufficient when facing cognitive distortions. This is because these distortions have deep roots in early life experiences and are not easily modified by protective factors.
Accordingly, the findings of this study suggest that enhancing resilience in adolescents can be an effective strategy for reducing addiction readiness, especially in the context of co-dependency. However, regarding interpersonal cognitive distortions, structured cognitive interventions, such as cognitive-behavioral therapy or schema therapy, are necessary to fundamentally modify these maladaptive patterns.
Overall, this research emphasizes the necessity of simultaneously addressing cognitive, emotional, and interpersonal factors in designing preventive programs and psychological interventions for adolescents. Focusing on resilience and restructuring maladaptive cognitions can lead to a reduction in risky behaviors and promote mental health in this age group.

Study limitations
Like other studies, this research had several limitations that should be considered when interpreting the results. The type of substance or addictive behavior was examined in a general manner without differentiation, which may reduce the precision of the findings. Additionally, the data were collected through self-report measures, which may be subject to biases such as social desirability. Also, important contextual variables such as socio-economic status, ethnicity, and cultural background were not controlled; therefore, generalizing the results to other groups should be done with caution.

Future research suggestions
Based on the findings and limitations of the study, the following recommendations are made for future research: Conducting similar studies with female adolescent samples and comparing the results by gender to gain a more accurate understanding of differences in factors influencing addiction readiness; examining cognitive and emotional components of addiction readiness separately using more precise and multi-source tools such as self-assessment, observer reports, and parental reports; employing experimental or quasi-experimental designs to evaluate the effects of intervention programs aimed at enhancing resilience and reducing addiction readiness; studying integrative models including family, educational, social, and cultural factors alongside psychological components for a more comprehensive explanation of addiction readiness.

Practical study recommendations
Based on the research findings, the following recommendations are offered to policymakers, psychologists, parents, and educators: designing and implementing school-based programs to strengthen adolescents’ resilience to enhance coping skills and emotion regulation; developing cognitive-based therapeutic interventions to identify and modify interpersonal cognitive distortions in vulnerable adolescents; training parents and educational staff to recognize signs of co-dependency and interpersonal cognitive distortions in adolescents and to refer them to psychological specialists at early stages; forming emphasize group and family-centered interventions to reinforce healthy and balanced relationships between adolescents and their social environment, aiming to prevent the development of maladaptive dependency patterns.

Ethical Considerations

Compliance with ethical guidelines
This study was approved by the Ethics Committee of Roudehen Branch, Islamic Azad University, Roudehen, Iran (Code: IR.IAU.R.REC.1401.022). Participation in the study was voluntary, confidential, and conducted with informed consent obtained from the students.

Funding
This paper was extracted from the doctoral dissertation of Vali Tavakoli Nia, approved by Roudehen Branch, Islamic Azad University, Roudehen, Tehran, Iran.

Authors' contributions
All authors contributed equally to the conception and design of the study, data collection and analysis, interpretation of the results, and drafting of the manuscript. Each author approved the final version of the manuscript for submission.

Conflict of interest
The authors declared no conflict of interest.

Acknowledgments
Hereby, sincere thanks are extended to all adolescents who participated in this study. Their cooperation and support played a crucial role in the conduct and validation of this research. Appreciation is also expressed to the families and affiliated centers whose support and collaboration made this study possible.




References

Ahmadi Tahour Soultani, M., & Najafi, M. (2011). [The comparison of metacognitive beliefs and ambiguity tolerance among addicted, smokers, and normal individuals (Persian)]. Journal of Clinical Psychology, 3(4), 59-67. [DOI:10.22075/jcp.2017.2071]

American Psychiatric Association. (2022). Diagnostic and statistical manual of mental disorders (DSM-5-TR). Washington: American Psychiatric Publishing. [DOI:10.1176/appi.books.9780890425787]

Arghabaei, M., Soleimanian, A. A., & Mohammadipour, M. (2018). The role of family emotional atmosphere, sense of coherence, and affects in the prediction of tendency toward substance use among university students. Iranian Journal of Psychiatry and Clinical Psychology, 24(3), 310-323. [DOI:10.32598/ijpcp.24.3.310]

Aryan, N., Banafshe, H. R., Farnia, V., Shakeri, J., Alikhani, M., & Rahimi, H., et al. (2020). The therapeutic effects of methylphenidate and matrix-methylphenidate on addiction severity, craving, relapse and mental health in the methamphetamine use disorder. Substance Abuse Treatment, Prevention, and Policy, 15(1), 1-9. [DOI:10.1186/s13011-020-00317-y] [PMID]

Ashraf, S. M. H. (2010). Codependency and validating Spann-Fischer in the women of Mashhad. Etiadpajohi, 4(15), 49-62. [Link]

Bagheri Sheykhangafshe, F., Alizadeh, D., Savabi Niri, V., Asgari, F., & Ghodrat, G. (2021). The role of internet addiction, mindfulness and resilience in predicting students’ mental health during the coronavirus 2019 pandemic. Journal of Child Mental Health, 8(3), 1-14. [DOI:10.52547/jcmh.8.3.2]

Bahari, F., Fatehizadeh, M., Ahmadi, S. A., Molavi, H., & Bahrami, F. (2010). The effect of hope, forgiveness, and combined marital counseling on interpersonal cognitive distortions of divorcing couples. Research in Behavioral Sciences, 8(1), 25-33. [DOI:10.1037/e537902012-137]

Boron, Z., Dokaneei Fard, F., & Fattahi Andabil, A. (2023). [The effectiveness of a resilience-based curriculum on impulsivity and psychological flexibility in addiction-prone adolescents (Persian)]. Journal of Applied Psychological Research, 14(1), 31-47. [DOI:10.22059/japr.2023.330047.643979]

Bortolon, C. B., Signor, L., Moreira, T. D. C., Figueiró, L. R., Benchaya, M. C., Machado, C. A., et al. (2016). Family functioning and health issues associated with codependency in families of drug users. Ciencia & Saude Coletiva, 21(1), 101-107. [DOI:10.1590/1413-81232015211.20662014] [PMID]

Cermak, T. L. (1986). Diagnosing and treating co-dependence: A guide for professionals who work with chemical dependents, their spouses and children. Minneapolis: Johnson Institute Books. [Link]

Chukwuorji, J. C., Nweke, A., Iorfa, S. K., Lloyd, C. J., Effiong, J. E., & Ndukaihe, I. L. (2021). Distorted cognitions, substance use and suicide ideation among gamblers: A moderated mediation approach. International Journal of Mental Health and Addiction, 19(4), 1398-1409. [DOI:10.1007/s11469-020-00232-0]

Ciccarelli, M., Griffiths, M. D., Nigro, G., & Cosenza. (2017). Decision making, cognitive distortions and emotional distress: A comparison between pathological gamblers and healthy controls. Journal of Behavior Therapy and Experimental Psychiatry, 54, 204-210. [DOI:10.1016/j.jbtep.2016.08.012] [PMID]

Connor, K. M., & Davidson, J. R. (2003). Development of a new resilience scale: The Connor-Davidson resilience scale (CD-RISC). Depression and Anxiety, 18(2), 76-82. [DOI:10.1002/da.10113]

Dear, G. E., Roberts, C. M., & Lange, L. (2005). Defining codependency: A thematic analysis of published definitions. In S. P. Shohov (Ed.), Advances in psychology research (pp. 189-205). Hauppauge, New York: Nova Science. [Link]

Diotaiuti, P., Mancone, S., Corrado, S., De Risio, A., Cavicchiolo, E., Girelli, L., & Chirico, A. (2022). Internet addiction in young adults: The role of impulsivity and codependency. Frontiers in Psychiatry, 13, 893861. [DOI:10.3389/fpsyt.2022.893861] [PMID]

Drug Control Headquarters. (2019). Annual report of the Islamic Republic of Iran’s drug control activities in 2019. Tehran: Drug Control Headquarters Secretariat Publication. [Link]

Dupree, A. T. W. (2010). The impact of parental codependency on children with mental health conditions [master thesis]. Long Beach: California State University. [Link]

Eiseman, S., Wingard, J., & Huba, G. (2019). Drug abuse: Foundation for a psychosocial approach. New York: Routledge. [DOI:10.4324/9781315224695]

Ellis, A. (2003). The nature of disturbed marital interaction. Journal of Rational-Emotive & Cognitive Behavior Therapy, 21, 147-153. [DOI:10.1023/A:1025825725522]

Ellis, A., MacLaren, C. (2005). Rational emotive behavior therapy: A therapist’s guide (2nd ed., with Catharine Maclaren). Atascadero: Impact Publishers. [Link]

EslamDoost, S. (2018). [Addiction etiology and treatment (Persian)]. Tehran: Payam Noor. [Link]

EsmaeelPoor, K., Bakhshi Poor Rodsari, A., & Mohammadzadegan, R. (2015). [Determining factor structure, validity, and reliability of interpersonal cognitive distortions scale among students of Tabriz University (Persian)]. Journal of Cognitive Strategies in Learning, 2(3), 53-72. [Link]

Eyni, S., Torabi, N., Ebadi, M., & Kermani, A. (2020). [Predicting tendency to drug abuse based on academic alienation, negative academic emotions, and general self-efficacy in students (Persian)]. Etiadpajohi, 14(56), 79-100. [DOI:10.29252/etiadpajohi.14.56.79]

Fuller, J. A., & Warner, R. M. (2000). Family stressors as predictors of codependency. Genetic, Social, and General Psychology Monographs, 126(1), 5-22. [PMID]

Ghanbari-Talab, M., & Fooladchang, M. (2015). [On the relationship of resilience and mental vitality with addiction potential among students (Persian)]. Research on Addiction, 9(34), 9-22. [Link]

Gras Pérez, M. E., Font-Mayolas, S., Baltasar Bagué, A., Patiño Masó, J., Sullman, M. J., & Planes Pedra, M. (2019). The connor-davidson resilience scale (CD-RISC) amongst young. Clinical and Health, 30(2), 73-79. [DOI:10.5093/clysa2019a11]

Haji Alizadeh, K., Bahreinian, A., Naziri, G., & Modares Gharavi, M. (2009). [The role of cognitive variables, metacognitive dimensions and emotions in substance abuse behaviors (Persian)]. Advances in Cognitive Sciences, 11(3), 1-12. [Link]

Hamamci, Z., & Büyüköztürk, S. (2004). The interpersonal cognitive distortions scale: Development of the scale and investigation of its psychometric characteristics. Psychological Reports, 95(1), 291-303. [DOI:10.2466/pr0.95.1.291-303] [PMID]

Karami, A. (2018). [The effect of negative automatic thoughts and self-esteem on the addiction potential in male students. Rooyesh-e-Ravanshenasi Journal, 7(7), 51-62. [Link]

Karapet, R. (2024). The relationship between substance use, codependency, and self-esteem [doctoral dissertation], San Diego: Alliant International University. [Link]

Kaya, Z., Kale, K., Yağan, F., & Kaya, Ş. (2024). The mediating role of resilience in the relationship between childhood emotional abuse and emotional neglect and codependency. Children and Youth Services Review, 161, 107670. [DOI:10.1016/j.childyouth.2024.107670]

Khosravi, N., Panaghi, L., Ahmad Abadi, Z., & Sadeghi, M. S. (2013). [Relationship between inefficiency of origin family and the interdependence of women: Interfering role of university education (Persian)]. Journal of Applied Psychology, 7(1), 85-100. [Link]

Kuzucu, Y., Sariot Ertürk, Ö., Şimşek, Ö. F., & Gökdaş, İ. (2020). Cognitive distortions and problematic Internet use connection: Examining the mediator roles of loneliness and social anxiety by partialling out the effects of social desirability. Journal of Evidence-Based Psychotherapies, 20(1), 51-76. [DOI:10.24193/jebp.2020.1.4]

Llistosella, M., Goni-Fuste, B., Martín-Delgado, L., Miranda-Mendizabal, A., Franch Martinez, B., &Pérez-Ventana, C., et al. (2023). Effectiveness of resilience-based interventions in schools for adolescents: A systematic review and meta-analysis. Frontiers in Psychology, 14, 1211113. [DOI:10.3389/fpsyg.2023.1211113] [PMID]

Mendenhall, W. (1989). Co-dependency definitions and dynamics. In B. Carruth & W. Mendenhall (Eds.), Co-dependency: Issues in treatment and recovery (pp. 3-17). Philadelphia: The Haworth Press. [DOI:10.1300/J020V06N01_02]

Mesman, E., Vreeker, A., & Hillegers, M. (2021). Resilience and mental health in children and adolescents: An update of the recent literature and future directions. Current Opinion in Psychiatry, 34(6), 586–592. [DOI:10.1097/YCO.0000000000000741] [PMID]

Mohammadi, M., Jazayeri, A. R., Rafie, A. H., Joukar, B., & Pourshahbaz, A. (2006). [Resilience factors in individuals at risk for substance abuse (Persian)]. Journal of Psychology, 1(2-3), 203-224. [Link]

Mosalman, M., Narimani, M., & Atadokht, A. (2020). Predicting readiness for substance dependence based on positive psychological states of university students. Research on Addiction, 14(56), 133-152. [DOI:10.29252/etiadpajohi.14.56.133]

Oudejans, S., De Weert-van, O., Spits, M., Wildt, W., Merkx, M., & Dekker, J., et al. (2019). A self-reported version of the measurements in the addictions for triage and evaluation-q: concurrent validity with the MATE 2.1. European Addiction Research, 26(1), 20-27. [DOI:10.1159/000503625] [PMID]

Qutb, S. A., & Abedi, A. (2024). [The mediating role of coronavirus anxiety in the relationship between resilience, social media addiction, and death distress (Persian)]. Recent Advances in Psychology, Educational Sciences, and Education, 68(6), 70-83. [Link]

Saboor, Z., Rahimi Pordanjani, T., & Mohammadzadeh Ebrahimi, A. (2019). Effect of hope therapy on general self-efficacy among substance abusers. Journal of Research & Health, 9(4), 302-308. [DOI:10.29252/jrh.9.4.302]

Sadri Damirchi, E., Esrafili Tazeh Kand Mohammadieh, H., & Mesbahi, S. F. (2019). [Addiction potential pattern based on dark triad traits of personality and schema modes (Persian)]. Research on Addiction, 13(53), 119-138. [Link]

Salonia, G., Mahajan, R., & Mahajan, N. S. (2021). Codependency and coping strategies in the spouses of substance abusers. Scholars Journal of Applied Medical Sciences, 9(7), 1130-1138. [DOI:10.36347/sjams.2021.v09i07.002]

Silk, J. S., Vanderbilt-Adriance, E., Shaw, D. S., Forbes, E. E., Whalen, D. J., & Ryan, N. D., et al. (2007). Resilience among children and adolescents at risk for depression: Mediation and moderation across social and neurobiological contexts. Development and Psychopathology, 19(3), 841-865. [DOI:10.1017/S0954579407000417] [PMID]

Şimşek, O. M., Koçak, O., & Younis, M. Z. (2021). The impact of interpersonal cognitive distortions on satisfaction with life and the mediating role of loneliness. Sustainability, 13(16), 9293. [DOI:10.3390/su13169293]

Sohrabi, F., Mamsharifi, P., Rafezi, Z., & Azami, Y. (2019). Predicting addiction potential based on mental health, social support, and neuroticism and agreeableness personality traits. Iranian Journal of Psychiatric Nursing, 6(6), 58-66. [DOI:10.21859/ijpn-06067]

Spann, L., & Fischer, J. L. (1990). Identifying codependency. The Counselor, 8(27), 27-31. [Link]

Stackert, R., & Bursich, K. (2003). Why am I unsatisfied? Adult attachment style, gendered irrational relationship beliefs, and young adult romantic relationship satisfaction. Personality and Individual Differences, 34(8), 1419-1429. [DOI:10.1016/S0191-8869(02)00124-1]

Su Topbaş, Z., Evli, M., Şimşek, N., İpekten, F., Işıkgöz, M., & Öztürk, H. İ. (2024). The relationship between anxious attachment and social networking site addiction in adolescents: The mediating role of interpersonal cognitive distortions, self-esteem, and the desire to be liked. International Journal of Mental Health and Addiction, 1-15. [DOI:10.1007/s11469-024-01163-z]

Trifilieff, P., Ducrocq, F., Vander Velldt, S., & Martinea, D. (2017). Blunted dopamine transmission in addiction: Potential mechanisms and implications for behavior. Seminars in Nuclear Medicine, 47(1), 64-74. [DOI:10.1053/j.semnuclmed.2016.09.006] [PMID]

Vinayak, S., & Judge, J. (2018). Resilience and empathy as predictors of psychological well-being among adolescents. International Journal of Health Sciences and Research, 8(4), 192-200. [Link]

Vujanovic, A. A., Smith, L. J., Green, C., Lane, S. D., & Schmitz, J. M. (2020). Mindfulness as a predictor of cognitive-behavioral therapy outcomes in inner-city adults with posttraumatic stress and substance dependence. Addictive Behaviors, 104, 106283. [DOI:10.1016/j.addbeh.2019.106283] [PMID]

Weed, N. C., Butcher, J. N., McKenna, T., & Ben-Porath, Y. S. (1992). New measures for assessing alcohol and drug abuse with the MMPI-2: The APS and AAS. Journal of Personality Assessment, 58(2), 389–404. [DOI:10.1207/s15327752jpa5802_15] [PMID]

Whitfield, C. (2002). Co-dependence: Healing the human condition [H. Masoomian Sharghi, Persian trans]. Tehran: Farabi Hakim Publishing. 

Yazici-Çelebi, G., & Kaya, F. (2022). Interpersonal cognitive distortions and anxiety: The mediating role of emotional intelligence. International Journal of Psychology and Educational Studies, 9(3), 741-753. [DOI:10.52380/ijpes.2022.9.3.769]

Zarbakhsh Bahri, M. R. , Rahmani, M. A. and Rastgoo, F. (2023). [Structural equation modeling of the relationship between ego-strength, defense styles and object relations in cluster b personality disorders with the mediating role of cognitive emotion regulation (Persian)]. Islamic Lifestyle With a Focus on Health, 7(4), 19-34. [Link]

Zargar, Y., Najarian, B., & Naami, A. Z. (2008). [The relationship of some personality variables, religious attitudes, and marital satisfaction with addiction potential in personnel of an industrial factory in Ahvaz (Persian)]. Journal of Education and Psychology, 15(1), 99-120. [Link]

Zeledon, I., West, A., Antony, V., Telles, V., Begay, C., Henderson, B., Unger, J. B., & Soto, C. (2020). Statewide collaborative partnerships among American Indian and Alaska Native (AI/AN) communities in California to target the opioid epidemic: Preliminary results of the Tribal Medication Assisted Treatment (MAT) key informant needs assessment. Journal of Substance Abuse Treatment, 108, 9–19. [DOI:10.1016/j.jsat.2019.04.003] [PMID]