Distress Tolerance and Hopelessness as Predictors of Adherence to Treatment among Recovering Drug Users in Recovering Drug Users in Uyo, Akwa Ibom State

Distress Tolerance and Hopelessness as Predictors of Adherence to Treatment among Recovering Drug Users in Recovering Drug Users in Uyo, Akwa Ibom State

Kokoette A. Christopher, Gboyega E. Abikoye

University of Uyo, Akwa Ibom State, Uyo, Akwa Ibom, Nigeria

DOI: https://dx.doi.org/10.47772/IJRISS.2025.917PSY0033

Received: 29 March 2025; Accepted: 11 April 2025; Published: 10 June 2025

ABSTRACT

Drug addiction remains a significant public health concern worldwide, with treatment adherence posing a formidable challenge among recovering drug users. However, several factors such as low distress tolerance and low level of hopelessness are significant issues related to adherence to treatment among recovering drug users. This study aimed to investigate Distress Tolerance and Hopelessness as Predictors of Adherence to Treatment among Recovering Drug Users in Recovering Drug Users in Uyo, Akwa Ibom State. A total of 208 participants (139 males and 69 females), aged 18–42 years (M = 30.2), were purposively selected. They completed the Treatment Adherence Scale (MARS-8), Distress Tolerance Scale and Beck Hopelessness Scale. Data was analyzed using multiple regression statistics. Results revealed that distress tolerance significantly predict adherence to treatment among recovering drug users. Hopelessness significantly predict adherence to treatment among recovering drug users. Additionally, distress tolerance and hopelessness jointly predict adherence to treatment among recovering drug users. Implications of the study and conclusions as well as suggestions for further study were made in line with the findings of this study. It was recommended that drug use patients and the general public should be psycho-educated to maintain high tolerance about their health as no-body can be excluded from negative health outcomes without intentionally adhering to a treatment plan. More health facilities and rehabilitation centers should be created in Uyo with well-equipped facilities to aid and improve the treatment of drug users.

INTRODUCTION

Adherence to treatment is one of the most important factors that impact directly on treatment outcomes. This explains why non-adherence is usually perceived in the light of an invisible epidemic as it is known to cause commotion in the health sector. World Health Organization (2019), considers adherence to treatment as the act of taking medication according to the prescribed dosage and with persistence over time. Difficulties with treatment adherence in patients with schizophrenia due to multiple drug use can lead to relapses, which on average can be five times more likely in young men than in women, thereby increasing the likelihood of hospitalization and healthcare cost (De las Cuevas et al. 2014). Adherence is an active choice of patients to follow through with the recommended treatment plan while taking personal responsibility for their own well-being. Meichenbaum and Turk (1987) defined adherence as an active, voluntary and collaborative involvement by the patient in a mutually acceptable course of behaviour to produce a preventative or therapeutic result.

Drug addiction remains a significant public health concern worldwide, with treatment adherence posing a formidable challenge among recovering drug users. Despite advancements in addiction treatment, a substantial proportion of individuals undergoing recovery exhibit poor treatment adherence, leading to increased risk of relapse and other adverse outcomes (Oene et al, 2007).

The prevalence of adherence and non-adherence to treatment varies across studies. Adewuya et al., (2009) reported that the overall prevalence of medication non-adherence among psychiatric patients in Nigeria ranges from 39.6 percent to 55.7 percent. Specifically, among psychiatric outpatients, 48 percent reported poor adherence, with only 22.2% demonstrating good adherence.  29.3 percent were identified as drug users, and notably, 59 percent of these individuals never reported missing their medications. This suggests that while many substance users may adhere to their treatment regimens, a significant portion did not adhere to their treatment. Another study reported non-adherence rates ranging from 34.2 percent to 55.7 percent among patients with severe mental illnesses across different regions in Nigeria; Southern Nigeria reports rates between 48 percent and 55.5 percent, while rates in Kaduna and Jos are 49.4 percent and 34.2 percent, respectively (Ibrahim et al., 2015)

Studies have shown that a lack of adherence to treatment among drug users negatively influences patient recovery by increasing the likelihood of relapse (Caqueo-Urízar et al., 2021). Studies have also shown that although demographic factors (age, gender, income level, and place of residence) are effective in adhering to treatment; patient perception of the potential benefits of the treatment has also a special importance (National Library of Medicine 2020).

Distress tolerance is a concept with importance across multiple diagnostic categories which plays a crucial role in predicting adherence to treatment among individuals recovering from drug use disorders, for example research has shown that individuals with higher distress tolerance are more likely to adhere to treatment recommendations and engage in recovery efforts effectively, (Bardeen et al., 2013). Distress tolerance may be defined as an individual’s ability to experience and tolerate negative psychological states (Leyro et al., 2010; Simons & Gaher, 2005).

Behaviors which have been linked with low distress tolerance include substance use and poor adherence to treatment. Consistent with negative reinforcement models of the development of mental disorders, lower levels of distress tolerance of individuals who are treated for substance use, the more likely to manage their emotions using some maladaptive coping strategies to avoid negative emotional status, such as substance use problems resulting in poor adherence to treatment (Leyro et al. 2010). On the other hand, when an individual is distressed due to specific negative events, he or she will be seeking mitigation and reduction of distress through performing specific tasks, for addicts, a significant distress improving behavior is to take drugs, and doing this will help the individual to avoid the distressing situation which could interfere with treatment adherence (Han et al., 2015).

Studies have highlighted the importance of distress tolerance in predicting treatment outcomes among individuals with drug use disorders. For example, a study by Daughters et al. (2005) found that individuals with higher distress tolerance were more likely to complete treatment programs and maintain abstinence from drugs compared to those with lower distress tolerance levels. This suggests that individuals who are better able to tolerate emotional distress are more likely to adhere to treatment recommendations and achieve positive outcomes in their recovery journey, also, by improving individuals’ ability to tolerate distress, treatment providers can help enhance treatment adherence and reduce the risk of relapse among recovery drug users.

Ali et al., (2017) also reported that at higher level of distress tolerance, favorable external circumstances, higher internal motivation, and greater readiness to treatment are important indicators of substance abuse treatment retention.  Kumar and Ram (2015) found a significant correlation between social burden and occupation, distress tolerance with decision and knowledge about treatment and medication adherence with knowledge about treatment.

Hopelessness is a phenomenon that is associated with a variety of negative cognitions and emotions, such as sadness, lack of positive emotions, low self-esteem, demoralization, and suicidal ideation (Klonsky et al., 2016), which makes this phenomenon highly relevant for both clinicians and researchers. It also describes the state of someone who does not see the possibility that life will increase and maintain that no one could help or do anything for himself (Carpenito, 2013). Meanwhile, hopelessness is a condition that causes stress, the inability of an individual to think about his future, do something meaningful in his life and empower himself (Davison & Kring, 2013).

On the other hand, helplessness is defined as the expectation that a given outcome is independent of one’s actions (Seligman, 1975). In other words, hopeless people feel they have no power or ability to change the problems they are currently facing and feel that attaining positive outcomes is outside of their control. In line with this, there is evidence that hopelessness is associated with perceived ineffective problem solving, namely the individual’s appraisal that their problem-solving skills will be insufficient or inadequate to deal with life’s problems (Heppner et al., 2004). Both healthy and depressed individuals with high levels of hopelessness lack confidence in their skills to solve problems and such impairments predict interaction with stress and future levels of hopelessness (Priester & Clum, 2006).

Hopelessness is of paramount importance in the field of addiction treatment, as adherence to treatment is crucial for successful recovery and long-term sobriety (Maral et al. 2021). Research conducted by Smith et al., (2018) highlighted the impact of hopelessness on treatment outcomes among recovery substance users. The study found that individuals with higher levels of hopelessness were less likely to adhere to treatment recommendations, leading to poorer recovery outcomes and increased risk of relapse.

One of the key mechanisms through which hopelessness predicts treatment adherence is its effect on motivation and efficacy. Individuals experiencing high levels of hopelessness may struggle to maintain motivation to engage in treatment activities or adhere to prescribed interventions. This can result in a lack of commitment to the recovery process and increased susceptibility to relapse (Johnson et al., 2019). Moreover, feelings of hopelessness can undermine an individual’s belief in their ability to overcome challenges and achieve positive outcomes, leading to decreased self-confidence in their ability to stay sober, this can also contribute to negative emotional states which further hinder treatment adherence among recovery drug users (Mohamed et al., 2020). Studies have shown that a significant negative relationship between substance use duration, age and total medication adherence score (Kargın et al., 2020). Base on this backdrop, the following hypotheses were posited in this study: Distress tolerance will significantly predict adherence to treatment among recovering drug users. Hopelessness will significantly predict adherence to treatment among recovering drug users. Distress tolerance and hopelessness will jointly predict adherence to treatment among recovering drug users

METHOD

Research Design and Research Area

This study adopted a cross-sectional survey design. This is because data was collected from a larger population at a given time.

The study area covered drug users who were treated for drug addiction. However, the study participants were drawn from two health facilities (University of Uyo Teaching Hospital and Mobile Manna Foundation) in Uyo, Akwa Ibom State. Uyo is the capital of Akwa Ibom state, south-south Nigeria. Uyo which is the capital city of the state lies between latitudes 4°58’N and 5°04’N and longitudes 7°51’E and 8°01’E.  It is one of the most well-known local government areas in Akwa Ibom. As mentioned earlier, it is the state’s capital and arguably the biggest of them all. Uyo is also host to one of the Nigeria’s federal University of Uyo. Uyo has a number of primary, secondary and tertiary health facilities

Research population

This study adopted a purposive sampling technique to select a total of two hundred and eight (208) recovering drug users. The research was specifically carried out on recovery drug users who were currently on therapeutic interventions such as medication, psychotherapy, dietary, occupational therapy and health check-up. All the participants were drawn from two (2) health facilities in Uyo, Akwa Ibom State. The health facilities are: University of Uyo Teaching Hospital and Mobile Manna Foundation. The participants were between the age range from 18-42 years. 139 (66.8%) of the participants were male while 69 (33.2) of the participants were female. In terms of duration of treatment, 83 (39.9%) participants were treated from 1-2 years, 88 (42.3%) were treated from 2-4 years and 37 (17.8%) participants were treated from 5-6 years.

Instrument

Three instruments were used to collect data for this study. They are: Treatment Adherence Scale (MARS-8), Distress Tolerance Scale and Beck Hopelessness Scale. The instruments were stapled together and arranged in five sections: A, B and C.

Section A was demographic variables including age, gender, current marital status, duration of treatment, highest education, place of residence and type of home born into.

Section B was Treatment Adherence Scale [MARS-8] (Morisky et al., 1986): Treatment Adherence Scale is a modified adherence scale. This scale consists of 8-items in a 5-point Likert type response format, 1= always, 2= often, 3 = sometimes 4= rarely, 5= never. Score for each item were summed to give a total score, with higher scores indicating higher levels of reported adherence. It is an effective self-report tool for measuring patients’ reports of medication use across a range of health conditions. It facilitates the recognition of barriers to the behaviors associated with adherence to chronic medications such as psychiatric drugs. It provides information on behaviors related to medication use that may be unintentional (such as forgetfulness) and intentional (such as not taking medications because of side effect). The medication adherence report scale (MARS-8) was evaluated in terms of its reliability (internal consistency and test-retest reliability) and validity (criterion-related and construct validity. The internal consistency of the Treatment Adherence Scale showed a good internal consistency with Cronbach alpha coefficient reliability of .75 Treatment Adherence Scale [MARS-8] was subjected to a pilot study to assess its reliability. All eight items were reliable having met the cut off coefficient alpha of 0.92. Item-total correlation analysis was used to determine the validity of the instrument. Total correlation co-efficient ranged between 0.36 to 0.58 indicating the validity of the instrument. The mean for the scale is 32.03. Scores higher than the mean indicates greater tendency to adhere to treatment while scores below the mean indicates greater tendency not to adhere.

Section C was the Distress Tolerance Scale (Simons & Gaher, 2005): The Distress Tolerance Scale is a 15-item questionnaire that is structured in a 5- point likert 1 = strongly agree, 2= mildly agree, 3= agree or disagree equally, 4- mildly disagree, 5= strongly disagree. It is designed to measure measures an individual’s ability to tolerate negative emotional state. The scale is made up of four subscales: Tolerance (the individual’s perceived ability to tolerate distress), Absorption (the degree to which an individual is consumed by negative emotions), Appraisal (the individual’s subjective assessment of the distress as tolerable or intolerable), and Regulation (the degree of urgency an individual feels to do something to alleviate the negative emotion). The reliability of distress tolerance was obtained in three phases: finding the construct validity, concurrent validity, criterion validity and discriminant validity with the initial set of items. The higher order distress tolerance scale is formed from the mean of the four subscales. Reliabilities for the subscales of distress tolerance are: 0.81 for tolerance, 0.85 for absorption, 0.81 for appraisal, and 0.80 for regulation. All 15 items on the scale were reliable after being subjected to a pilot study and meeting the cut off coefficient of 0.28 to 0.56 in item-total correlation and coefficient alpha of 0.93. The mean for the scale is 52.57. Scores higher than the mean indicates high distress tolerance and shows tendency to adhere to treatment while scores below the mean indicates low distress tolerance and shows tendency not to adhere to treatment

Section D was the Beck Hopelessness Scale (Beck, 1974): The Beck Hopelessness Scale (BHS) is a 20 item self-assessment instrument for the measurement of hopelessness that is structured in first choice response format 0 = True, 1= False. It measures an individual feeling about the future, loss of motivation, and expectations or negative expectations about the future. The scale has a strong internal consistency (Cronbach alpha reliability) of 0.87. A pilot study was conducted on the scale for validation and reliability. Cronbach alpha coefficient of 0.82 was achieved for the scale, indicating that the scale is reliable. Total correlation co-efficient ranged between 0.004 to 0.41 in item total correlation, indicating that the scale is valid. The scale has a mean score of 14.17. Scores higher than the mean indicates high level of hopelessness and shows tendency not to adhere to treatment while scores below the mean indicates low level of hopelessness and shows tendency to adhere to treatment

Procedure

Participants were individually approached and administered the instrument, which is the use of questionnaires. Participants were given informed consent to participate in the exercise voluntarily and it’s met for academic research purposes. Some of the participants were a bit reluctant to fill the questionnaires initially, but complied after they were assured that their identity would be anonymous in the participatory exercise. The researcher was present to guide participants through the instructions and items of the questionnaire. A total of 220 copies of questionnaire were distributed to the participants. However, only 208 copies were retrieved for data analysis.

Statistics

The data collected for the study were analyzed using Pearson correlation coefficient and multiple regression in SPSS. Descriptive statistics, including frequency, mean and standard deviation, were used to summarize the data. Pearson correlation coefficient was used to assessed the direct relationships among the study variables. Multiple regression was used to assessed the joint prediction between distress tolerance and hopelessness on adherence to treatment

Ethical consideration

Ethical concerns revolve around confidentiality and anonymity of data. These concerns were mitigated as participants were asked for informed consent and the data was handled confidentially using appropriate protocols including anonymization of data and results. To achieve this, the university google shared drive system was used to store the data. Also, ethical approval for the study was obtained from the Health Research Ethics Committee of the University of Uyo Teaching Hospital.

RESULT

The result of the findings of this study are presented in this chapter. The demographic features of participants are presented in Table 1. The correlations of the demographic variables and study variables are shown in Table 2. Multiple regression results for testing the hypotheses are in Tables 3.

Table 1: Summary of demographic features of participants

Descriptive statistics

Results in table 1 display the demographic features of 208 participants, including age, gender, duration of treatment, highest educational qualification, place of residence, current marital status and type of home.

The frequency distribution revealed that 139 (66.8%) of the participants were male while 69 (33.2) of the participants were female. Frequency distribution also revealed that 40 (19.2%) were participants whose age range between 18-22 years, 67 (32.2%) participants were between the age range from 23 – 27 years, 75 (36.1%) participants were between the age range from 28 -32 years, 23 (11.1) participants were between the age range from 23 – 37 years and 3 (1.4%) participants were between the age range from 38 -42 years.

In terms of duration of treatment, 83 (39.9%) participants were treated from 1-2 years, 88 (42.3%) were treated from 2-4 years and 37 (17.8%) participants were treated from 5-6 years.

In terms of highest educational qualification, 27 (13.0%) participants were first school leaving certificate (FSLC) holder, 80 (38.5%) participants were senior secondary school certificate education (SSCE) holder, 26 (12.5%) participants were national diploma (ND) holder, 16 (7.5%) participants were higher national diploma (HND) holder, 30 (14.4%) participants were bachelor of science degree (B.Sc.) holder, 22 (10.6%) participants were bachelor of art (BA) holder and 7 (3.4%) participants were master of science degree (M.Sc.) holder.

In terms of current marital status, 87 (41.8%) participants were single, 107 (51.4%) participants were married, 5 (2.4%) participants were divorced, 4 (1.9%) participants were separated and 5 (2.4%) participants were widowed.

In terms of place of residence, 137 (65.9%) participants reside in Uyo and 71 (34.1%) resides in Eket, finally, 33 (15.9%) participants were from a polygamous home and 175 (84.1%) participants were from a monogamous home.

Table 1: Zero-order correlation matrix showing inter-correlations of age, duration of treatment, distress tolerance, hopelessness and adherence to treatment

**Correlation is significant at the .01 level

*Correlation is significant at the .05 level

Table 2 revealed that age was positively correlated with adherence to treatment. Furthermore, duration of treatment was negatively correlated with distress tolerance and hopelessness but positively correlated with adherence to treatment. Similarly, distress tolerance was negatively correlated with hopelessness but positively correlated with adherence to treatment.

Table 3: Showing Multiple Regression of Distress Tolerance and Hopelessness as Predictors of Treatment Adherence in Recovering Drug Users in Uyo, Akwa Ibom State

The results presented in table 3 revealed that distress tolerance and hopelessness yielded a coefficient of multiple correlation (R) of 0.36 and multiple correlation square (R²) of 0.35. In order words, only 36.0 of adherence to treatment accounted for by the combined effect of distress tolerance and hopelessness

Distress tolerance was an independent predictor of adherence to treatment (β= 0.20; t= 2.92; p= <0.01). The t value indicates that there is a significant positive relationship between distress tolerance and adherence to treatment, indicating that as distress tolerance increases, adherence to treatment also increases. This finding supported hypothesis 1, which posited that distress tolerance will significantly predict adherence to treatment among recovery drug users.

Hopelessness was an independent predictor of adherence to treatment (β= -0.54; t= -7.93; p= <0.01). The t value indicates that there is a significant negative relationship between hopelessness and adherence to treatment, indicating that as hopelessness increases, adherence to treatment decreases. This finding supported hypothesis 2, which posited that hopelessness will significantly predict adherence to treatment among recovery drug users

The joint prediction between distress tolerance and hopelessness on adherence to treatment among recovery drug users was significant (F= (2,146) = 39.90; p<0.01). This finding supported hypothesis 3, which stated that distress tolerance and hopelessness will jointly predict adherence to treatment among recovery drug users

DISCUSSION

This study aimed to examine Distress Tolerance and Hopelessness as Predictors of Adherence to Treatment among Recovering Drug Users in Uyo, Akwa Ibom State. The first hypothesis which stated that distress tolerance will significantly predict adherence to treatment among recovering drug users was supported. This finding is consistent with the study conducted by Ali et al., (2017), Kumar and Ram (2015) and Daughters et al., (2005) who reported that individuals with higher distress tolerance were more likely to complete treatment programs and maintain abstinence from drugs compared to those with lower distress tolerance levels. Also, a significant correlation between social burden and occupation, distress tolerance with decision and knowledge about treatment and medication adherence with knowledge about treatment.

The second hypothesis which stated that hopelessness will significantly predict adherence to treatment among recovering drug users was supported. This finding is in line with the study conducted by Kargın et al., (2020), Smith et al., (2018) and Johnson et al., (2019) who reported that that individuals experiencing high levels of hopelessness may struggle to maintain motivation to engage in treatment activities or adhere to prescribed interventions. Similarly, a who revealed a significantly negative relationship between substance use duration, age and total medication adherence score and that medication adherence decreased with increasing hopelessness.

RECOMMENDATIONS

The following recommendations were made:

Holistic Treatment Approaches: Policymakers and treatment facilities are encouraged to adopt holistic approaches that recognize the interconnectedness of psychosocial factors. Drug use treatment programs should not only address the psychological factors of addiction such as distress tolerance and hopelessness but also incorporate components that focus on improving overall well-being.

More health facilities and rehabilitation centers should be created in Uyo with well-equipped facilities to aid and improve the treatment of drug users.

Health professionals should implement adherence enhancement strategies such as counseling, support groups, therapeutic education, mindfulness, Acceptance and Commitment Therapy (ACT)-based techniques to help patients improve distress tolerance, accept discomfort while pursuing treatment goals, reduce their addiction and urge to use drug.

Limitations of the study and suggestions for further studies

This study had several limitations that should be addressed in future research. First, the cross-sectional design used in this study limits the ability to establish joint prediction between distress tolerance, hopelessness and adherence to treatment. Future research could benefit from adopting longitudinal designs to explore the temporal and joint prediction among these variables more comprehensively.

The study excluded patients from other health facilities outside Akwa Ibom State and only focused on patients in Akwa Ibom State.

The participants felt worn out from the brief amount of time it took to complete the questionnaire.

The study relied on self-report measures to collect data, which may be subject to response bias and may not fully capture the complexity of treatment adherence and its predictive role. To address this limitation, future studies could adopt a multi-method approach, incorporating behavioral assessments, clinical observations to provide a more nuanced understanding of these associations.

The sample was drawn solely from patient who were treated for drug use in Uyo which may limit the generalizability of the findings to other populations or cultural contexts. Future studies should aim to replicate these findings in more diverse populations, including individuals from different geographic regions and socio-economic backgrounds. Collecting more detailed demographic data—such as income level, occupational status, and health conditions— could also provide valuable insights into additional factors that predict adherence to treatment.

Lastly, while distress tolerance and hopelessness were identified as significant predictors in this study, future research could explore additional predictors, such as social support, resilience and emotional regulation to further clarify the pathways that link adherence to treatment.

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