Psychosocial Correlates of Motivation for Abstinence Among People Who Used Drugs After Community Rehabilitation Treatment in China: A Structural Equation Modelling

Introduction

Drug Dependence and Relapse in China and Globally

Drug dependence has been a global public health issue that brings negative impacts on social stability and economic development for centuries.^1,2 While drugs such as opium and heroin are considered “traditional drugs”, there has been an upsurge in new drug use, such as methamphetamine, ketamine and ecstasy.³ According to the World Drug Report,⁴ there were around 275 million people who use drugs worldwide in 2021, a 22% increase from 2010. Furthermore, illicit drug use can be addictive. Drug use relapse after detoxification treatment is common.⁵ Globally, studies in Iran reported almost 90% relapse within a year of rehabilitation.⁶ A study in Norway followed 374 illicit substance users and reported a relapse rate of 37% after inpatient substance use treatment by three-month follow-up.⁷ Drug use caused almost half a million deaths in 2019.⁴ The negative impact caused by the COVID-19 pandemic is also likely to affect global drug use patterns. The crisis has pushed more than 100 million people into extreme poverty and has greatly exacerbated unemployment and inequalities, making more people susceptible to drug use.⁸

In China, the prevalence of drug dependence significantly increased in the late 1980s, spreading into 2102 counties and cities, comprising 76.3% of regions of China by 2004.⁹ Although people who use drugs have decreased for two consecutive years in China, there are still 2.14 million of them nationwide.¹⁰ Drug use relapse rates within the first year after discharge from treatment in China could be as high as 80% to 95%.^11,12

Abstinence Motivation for Drug Use

Abstinence motivation refers to the motivation to engage in and abstain from drug use.¹³ It is a key determinant in the interdiction of psychological addiction.^7,13 Numerous researchers have emphasized the importance of motivation in shaping patterns and outcomes related to substance use and relapse.^14,15 Abstinence motivation is also one of the strongest predictors of positive treatment outcomes of substance use.^13,16 Thus, exploring the psychosocial factors associated with abstinence motivation is important to prevent relapse behaviour. The identified factors can also guide the development of effective treatment services for people who use drugs.

Factors of Abstinence Motivation

Previous studies have found that intrapersonal factors, such as life satisfaction, positive self-concept, and adaptive coping styles, interpersonal factors, such as the number of network members in recovery, and low levels of stigma (eg, self-stigma or public stigma) could enhance abstinence motivation of drug use.^16–18 However, few studies have investigated the roles of impulsivity, social support, and mental health problems in abstinence motivation.

Impulsivity

Impulsivity refers to the inability to inhibit behaviours that may have negative consequences and be inconsiderate of outcomes before acting.¹⁹ High impulsivity is also characterised by a preference for delay reward discounting. Impulsive individuals tend to perform more risk-taking behaviours, be impatient, and have a lack of attention span.¹⁹ Impulsivity is a risk factor of drug use and relapse.²⁰ Abstaining from drugs requires active and sustained response suppression to resist the temptation of rewarding effects and pleasure of drugs.²¹ Thus, impulsivity may enhance one’s craving for drugs and weaken the abstinence motivation after the rehabilitation treatment.

Perceived Social Support

Social support is a well-documented stress buffer and protective factor against drug use and relapse.^6,22 A study conducted in the United States reported that positive interpersonal interactions, such as getting along with family members and helping each other, significantly decreased the chance of relapse among substance abusers at a post-treatment 6-month follow-up.²³ Another study following 535 drug abusers at compulsory rehabilitation treatment for 6 months in China found that greater social support predicted a lower risk of relapse.²⁴ Drug users who perceive social support and warmth especially from family and important others may have more coping resources for stress.²⁵ Thus, they do not need to rely on drugs for stress coping. Perceiving social support may also reduce depression, loneliness and enhance the sense of belongingness and motives of being healthy,^26–28 thus enhancing abstinence motivation of drug use.

Mental Health Problems

Depression, anxiety and sleep problem are common mental health problems that can lead to various behavioral problems including drug use and relapse.^29–31 Drug use is often used as a coping behavior to relieve or escape from negative emotions and stress.³² Theories of addiction also suggest that acute and chronic stress could increase vulnerability to drug use and relapse. For example, the stress-coping model of addiction suggests that drug is used as a maladaptive coping strategy to reduce negative affect and increase positive affect.³³ Drug addicts may find relapse to substances a way to deal with their sleep problems and negative feelings. Mental health problems may also affect risk-related expectations and decision-making which would lead to drug use and relapse.³⁴ Sleep and emotional difficulties during abstinence can lead to aggression, irritability, and restlessness.³⁵ In a study with 102 cannabis-dependent patients, those with poor sleep quality had less reduction in cannabis use during the course of a 6-month self-guided cessation attempt compared to those with good sleep quality;³⁶ among 55 patients who finished treatment, poor sleep quality predicted relapse within the first 2 days after treatment.³⁷ However, we have not identified any studies testing whether poor sleep quality would reduce the abstinence motivation of people who use drugs. We only identified one recent study which found that anxiety was negatively associated with drug abstention motivation in Chinese males with substance use disorders.³⁸

The Mediation Model of Abstinence Motivation

Furthermore, mental health problems may play as a proximal mediator that can explain why impulsivity reduces and social support enhances abstinence motivation. The risk effect of impulsivity and the protective effect of social support on mental health problems have been well documented in people who use drugs and general populations.^39,40 Impulsivity is a distinct personality factor that may contribute to stress,⁴¹ suicide,⁴⁰ and the onset of emotional problems,⁴² while social support can provide individuals with a sense of belonging, reduce feelings of isolation and loneliness, and increase coping resources during difficult times which is particularly important for those who are experiencing mental health challenges.⁴³ Thus, it can be expected that impulsivity and social support may affect mental health problems which in turn contribute to abstinence motivation of drug use.

The Present Study

We only identified one study testing the role of anxiety in abstinence motivation of drug use;³⁸ no study tested the roles of depression, sleep problems, impulsivity, and social support in abstinence motivation. We did not find any study testing the mediation effects of mental problems on the relationships from impulsivity and social support to abstinence motivation. To fill these research gaps, the present study aims to investigate the prevalence/levels of depression, anxiety, sleep quality, impulsivity, and social support and their associations with abstinence motivation of drug use among Chinese drug use patients after community-based rehabilitation treatment. It is hypothesized that higher levels of depression, anxiety, poor sleep quality, and impulsivity would be associated with lower abstinence motivation, while greater social support would be associated with higher abstinence motivation.

In China, a 2-year isolated compulsory drug rehabilitation is the most common service for people who use drugs. Since the Anti-Drug Law of the People’s Republic of China was enacted in 2007, local governments have been encouraged to provide residents with community-based drug rehabilitation and recovery programmes. Individuals who register voluntarily are arrested due to illicit drug abuse, or have completed isolated compulsory drug rehabilitation treatment are required to join community-based rehabilitation programs.⁴⁴ The current study included a sample of those who completed such rehabilitation programs.

Materials and Methods

Participants and Data Collection

Participants were recruited from 11 communities located in Wenzhou City, Zhejiang Province, China. The inclusion criteria of this study were: 1) Chinese residents with a history of drug dependence; 2) who completed the community-based drug rehabilitation treatment. The exclusion criteria included: 1) non-Chinese speakers; and 2) being physically and/or cognitively unfit for the interview. The community social workers, who worked for the community-based drug rehabilitation and recovery programmes, invited 254 participants by phone and made an appointment for an individual interview. During the interview, 230 participants completed a structural and anonymous questionnaire in a counselling room in the community and with the assistance of a well-trained research assistant and a social worker. Each participant was informed that their participation was voluntary, and refusal to participate would not result in any negative consequences on their received community service. Data confidentiality was guaranteed, and only the researchers of this study could access the data. The data were collected from April to June 2021. Of the 230 participants who completed the survey, eight (6.5%) were excluded from the data analysis because more than 20% of the data were missing from one or more scales of the key study variables. The remaining 222 (93.5%) were used for the final analysis. No significant differences in socio-demographic characteristics were found between participants included and excluded from the data analysis (P > 0.0.5).

Ethics Approval and Consent to Participate

The study was approved by the Ethics Committee of the affiliated Kangning Hospital, Wenzhou Medical University (Reference No. KNLL-20201011002). Participants signed informed consent. Participation was voluntary and anonymous. The study was conducted according to the Declaration of Helsinki.

Measures

Depressive Symptoms

The 20-item Self-rating Depression Scale (SDS)⁴⁵ was used to assess depression over the past week. It is rated on a 4-point Likert scale (1 = never to 4 = always), with a higher score implying higher levels of depression. The standard raw total score (raw total score * 1.25) was used to calculate the prevalence of depression, and the cut-off points of 53, 63, and 73 represent the thresholds for mild, moderate, and major depression, respectively.⁴⁶ The scale has been validated in Chinese populations.⁴⁷ (Cronbach’s α=0.86 in the current sample)

Anxious Symptoms

The 20-item Self-rating Anxiety Scale (SAS)⁴⁸ was used to assess anxiety. It has been validated among the Chinese population.⁴⁷ Items were rated on a 4-point Likert scale (1 = never to 4 = always). A higher score implies a higher level of anxiety. The standard raw total score was used to calculate the prevalence of anxiety; the cut-off points of 50, 60, and 70 represent the thresholds for mild, moderate, and severe anxiety, respectively.⁴⁷ (Cronbach’s α=0.86 in the current sample)

Quality of Sleep

The 18-item Pittsburgh Sleep Quality Index was used to evaluate sleep quality in the past month.⁴⁹ Items are rated on a 4-point Likert scale (0 = Not during the past month to 3 = Three or more times a week). The total score ranges from 0 to 21, with higher scores representing lower sleep quality. The cut-off points of 5 and 7 represent the thresholds for the general and poor sleep quality, respectively. This scale has been used in Chinese populations.⁵⁰ (Cronbach’s α=0.93 in the current sample)

Impulsivity

Impulsivity was assessed by the 30-item Chinese-version Barratt impulsivity Scale.⁵¹ It is rated on a 5-point Likert scale (1 = never to 5 = always). The total score ranges from 30 to 150, with higher scores representing a higher level of impulsivity. (Cronbach’s α=0.89 in the current sample)

Perceived Social Support

Perceived social support was measured by the 12-item Perceived Social Support Scale, which contains three subscales, including social support from family, friends, and significant others.⁵² The scale is rated on a 7-point response scale (1 = strongly disagree to 7 = strongly agree), with a higher total score indicating a higher level of perceived social support. This scale showed good reliability in Chinese populations.⁵³ (Cronbach’s α=0.92 for Family Support, 0.92 for Friends Support, and 0.91 for Significant Others Support in the current sample)

Abstinence Motivation to Drugs

The 36-item Abstinence Motivation Scale was used to measure participants’ abstinence motivation to drugs.⁵⁴ Items are rated on a 5-point Likert scale (1 = totally disagree to 5 = totally agree). Total scores range from 36 to 180. A higher score indicates higher levels of internal and external motivation and confidence for abstinence. The scale has been validated among the Chinese population.⁵⁴ (Cronbach’s α=0.99 in the current sample)

Statistical Analysis

Descriptive statistics were conducted for all the variables. Univariate linear regression models were used to examine the association between each background factor and abstinence motivation. Univariable and multivariable linear regression models were applied to investigate the associations between psychosocial factors (ie, depressive symptoms, anxious symptoms, quality of sleep, impulsivity and perceived social support) and abstinence motivation after adjusting for the significant background factors.

Structural equation modelling (SEM) was conducted to test the proposed mediation model. Scores of depression, anxiety, and poor sleep quality were used as indicators for mental problems (latent variable). The items of impulsivity and abstinence motivation to drugs were randomly bundled into three parcels for the latent variables, respectively. The measurement model was tested using confirmatory factor analysis (CFA). The structural model was tested by SEM. χ²/df ≤3, the Comparative Fit Index (CFI) >0.95, the Tucker-Lewis Index (TLI) >0.95, the Root Means Square Error of Approximation (RMSEA) and the Standardized Root Mean Square Residual (SRMR)<0.08 were considered as good model fit.^55,56 The 95% confidence interval (CI) of the indirect effects was based on 5000 bias-corrected bootstrap samples. The magnitude of the effect sizes was assessed by the standardized coefficients (β). β = 0.10, 0.30 and 0.50 were considered as small, medium, and large effect sizes for direct path coefficients,⁵⁷ and β = 0.01, 0.09 and 0.25 as small, medium, and large effect sizes for indirect path coefficients.⁵⁸ According to 10 observations per indicator variable in setting a lower bound of an adequate sample size for SEM,⁵⁹ our sample size was sufficient for these analyses. The analyses were conducted by SPSS 23.0 and Mplus 7.4. The significance level was set at p < 0.05.

Results

Descriptive Characteristics

Participants were primarily male (89.2%), without a family history of mental disorder (96.8%) or physical disease (88.0%). Around 16.7% of the participants were 35 years old or younger, and 44.1% were between 36 and 45 years. The whole sample’s average years of school attainment were 7.61 (SD = 2.89). Nearly half (53.2%) of the participants were married. About 23.3% of participants were gamblers, and 94.3% were tobacco users (Table 1).

Table 1 Description of Background Characteristics, Psychosocial Factors, and Abstinence Motivation of the Participants (N = 222)

Before the treatment, Methamphetamine was the most popular type of drug (60.4%), followed by Heroin (20.7%) in this sample. The methods of drug use were smoking (67.0%), snorting (11.5%), injection (10.4%) and ingestion (7.1%). On average, the participants had used the drugs for 10 years (SD = 7.74). And the mean of years abstaining from the drugs was 2.85 (SD = 1.71). The mean score of abstinence motivation was 20.42 (SD = 5.92).

Among 222 participants, 57 (25.7%) of them reported a mild level of depressive symptoms while 29 (13.1%) of them reported a moderate level of symptoms. In addition, the number of participants with mild, moderate, and severe anxious symptoms were 27 (12.2%), 13 (5.9%) and 3 (1.4%), respectively. It was also shown that 47 (21.2%) participants had poor sleep quality.

Background Factors Associated with Abstinence Motivation

Age was negatively associated with abstinence motivation (β_u=−0.20, p < 0.01). Having a family history of physical disease was positively associated with motivation for abstaining from drugs (β_u=0.14 p < 0.05). Other background factors did not significantly affect abstinence motivation.

Psychosocial Factors Associated with Abstinence Motivation

Depressive symptoms (β_a=−0.28, p < 0.001), anxiety symptoms (β_a=−0.24, p < 0.001), poor sleep quality (β_a=−0.23, p < 0.01), impulsivity (β_a=−0.29, p < 0.001) were negatively associated with abstinence motivation, respectively. Perceived family support (β_a=0.17, p < 0.05) and perceived important others support (β_a=0.16, p < 0.05) were positively associated with abstinence motivation, respectively. When adjusting for other psychosocial factors, only impulsivity was still significantly associated with abstinence motivation (β_a=−0.19, p < 0.001; Table 2).

Table 2 Associations Between Psychosocial Factors and Abstinence Motivation (N = 222)

Structural Equation Modelling

The measurement model yielded a good fit: χ²/df = 1.78, CFI = 0.98, TLI = 0.97, RMSEA = 0.06 (95% CI = 0.04, 0.08), SRMR = 0.04. All the parcel indicators were significantly loaded on the latent variables, with standardized factor loading ranging from 0.50 to 0.99 (all p < 0.001). The structural model fitted the data well: χ²/df=1.75, CFI = 0.98, TLI = 0.97, RMSEA = 0.06 (95% CI = 0.04, 0.08), SRMR = 0.05. As shown in Figure 1, the direct effect of impulsivity (β= −0.21, 95% CI = −0.35, −0.06) on abstinence motivation was significant. Mental problems significantly mediated the associations between impulsivity (β_indirect = −0.08, 95% CI = −0.16, −0.02)/perceived social support (β_indirect = 0.04, 95% CI = 0.01, 0.11) and abstinence motivation.

Figure 1 A structural equation modeling model explaining the mediating role of mental health problems in the associations between impulsivity, perceived social support and abstinence motivation. Notes: The standardized path coefficients were shown in the figure. The background variables having associations with abstinence motivation with p < 0.05 (ie, age and having a family history of physical disease) were controlled for. **p < 0.01, ***p < 0.001. The dashed arrow means p ≥ 0.05; the solid arrow means p <0.05.

Discussion

This study is the first attempt to investigate multiple psychosocial factors of abstinence motivation in ex-drug use patients who have completed community rehabilitation treatments in China. The results generally support our hypotheses, while unexpected findings were also identified.

Our results showed that, after the community-based drug rehabilitation treatment, the prevalence of depression, anxiety and poor sleep quality among the participants were 38.8%, 19.5%, and 21.2%, respectively. With the same assessment tools, the prevalence of depression and anxiety was higher than those reported in general Chinese population (depression ranged from 16.3% to 31%; anxiety ranged from 1.5% to 8.7%),^60–63 while the prevalence of poor sleep quality was comparable with those reported in the general Chinese population (26.4%).⁶⁴

Furthermore, we demonstrated that these mental health problems were negatively associated with abstinence motivation of drug use and mediated the effects of impulsivity and social support on abstinence motivation. Drug use has been a well-documented maladaptive coping behaviour to stress and mental difficulties.⁶⁵ Individuals who rely on drugs as a means of coping with these emotional and mental problems would be less likely to have motivation to abstain from drugs. The findings suggest that effective treatment (eg, cognitive behavioural treatment (CBT)) and follow-up service targeting mental health problems for people who used drugs should be helpful for reinforcing their abstinence motivation and preventing relapse of drug use.

Individuals with high impulsivity and low social support would be more vulnerable to mental health problems. We found that social support was positively associated with abstinence motivation in regression and indirectly via mental health problems in SEM. Enhancing social support is an effective strategy in addiction treatment.⁶⁶ It is also a well-documented protective factor of help-seeking and treatment adherence for addictive behaviors (eg,^67,68). Proper emotional and instrumental support, encouragement, and help, especially from family members and other significant others (eg, healthcare professionals), could give patients a sense of inclusion, security and belongingness, which aids them in coping with distress and difficulties, and develop positive prospect in life⁶⁹ and thus enhances drug abstinence self-efficacy and commitment. Our findings corroborate previous studies on drug use treatment¹¹ and suggest that rehabilitation services should enhance proper interpersonal social support of people who used drugs and provide a supportive interpersonal system to enhance their abstinence motivation and maintain the treatment effect. However, friend support was not significantly correlated with abstinence motivation in this sample. Previous studies have discussed the complex role of friends and peers in drug use and relapse. For example, a longitudinal study with 206 males testing the relationship between adolescence and adulthood’s peer influence and substance use reported that adulthood substance use was affected by peers in adolescence, specifically deviant friendships.⁷⁰ The number of network members in recovery was positively associated with abstinence motivation.¹⁷ Hence, it is important to further explore which kinds of friends provided support and what types of support they provided to understand the role of friend support better.

It is worth noting that impulsivity showed robust associations with abstinence motivation in both univariate and multivariate models and SEM (both directly and indirectly). It is theorised that impulsivity leads to risk-taking and poor decisions, making it a major risk for drug use and relapse under conditions that impair an individual’s inhibition responses, such as stressful events or cues to substance use.^71–73 It has been documented that people with higher impulsivity are more likely to engage in drug use behaviours.⁷⁴ This study is the first to further extend our understanding of the effect of impulsivity on abstinence motivation which may affect one’s treatment intention and adherence and future relapse. The significant direct effect of impulsivity in SEM suggests that in addition to mental health problems, there may exist other mediators between impulsivity and abstinence motivation, such as sensation-seeking and craving for drugs. Future studies may explore these potential mediators. Rehabilitation interventions should take this intrapersonal factor into account and teach them skills to cope with patients’ rash-spontaneous behaviours, enhance their self-control, and guide them to explore alternative rewards that are healthier (eg, physical activity). Mindfulness-based interventions have been found to effectively redress impulsive patterns derived from inhibitory motor control or planning capacity deficits and benefit mental health. Cognitive behavioral therapy that provides training for patients’ self-regulation skills and motivational interviewing that aims to enhance patients’ self-change motivation may also be helpful.

The participants who were older and had no family history of physical disease had lower levels of abstinence motivation and should be paid particular attention. However, it is inconsistent with the previous finding that younger people are more likely to relapse than older people.⁷⁵ One plausible reason is that the survey was conducted during COVID-19, which might increase the risk of relapse among older people because they experienced more stress (eg, worrying about health, finance and job and social isolation), were more difficult to adjust, and had fewer coping resources than younger people.⁷⁶ In addition, older people may have a longer history of drug use and heavier dependence on drugs, which would also reduce their abstinence motivation. People with a family history of physical disease may concern more about their health and have greater motivation to adopt healthy lifestyles,⁷⁷ which, in turn, motivates them to abstain from drugs.

The study had several limitations. First, the cross-sectional design could not demonstrate the causal relationships between the psychosocial variables and the outcome. Their relationships can be reciprocal. For example, low abstinence motivation to drugs may lead to relapse and aggravate emotional problems. Longitudinal study design and cross-lagged model to comprehensively investigate their longitudinal relationships are warranted. Future studies should also monitor during and post-treatment changes in the study variables. This would help quantify the impact of rehabilitation services on these areas and inform future service development. Also, the study sample was recruited in one city in China, ensuring the homogeneity of the rehabilitation program the participants attended. However, our findings may not be applicable to people in other geographical locations. Last but not least, we did not include drug use relapse as a variable or confounder although it is closely related to our outcome. It is because it is a sensitive question and almost all the participants chose not to disclose this status.

Conclusions

The high prevalence of mental health problems in people who completed community rehabilitation treatments should be paid attention to and well addressed. Significant risk factors of abstinence motivation included older age, no family history of physical disease, mental health problems, impulsivity, and low perceived social support from family and significant others. Impulsivity was directly and indirectly associated with abstinence motivation via mental health problems, while the indirect effect of social support was significant. Rehabilitation programs and follow-up services should consistently monitor the prevalence of mental health problems and drug use relapse, and address the modifiable psychosocial factors to enhance the abstinence motivation of people who used drugs and the long-term effectiveness of the treatment.