ORIGINAL ARTICLE |
https://doi.org/10.5005/jp-journals-11001-0074 |
Neuropsychological Functioning in Patients with Opioids Dependence during Early Abstinence: A Comparative Study
1–3Department of Clinical Psychology, Central Institute of Psychiatry, Ranchi, Jharkhand, India
Corresponding Author: Muhammed S TM, Department of Clinical Psychology, Central Institute of Psychiatry, Ranchi, Jharkhand, India, e-mail: sdk.alt@gmail.com
Received: 13 January 2024; Accepted: 02 June 2024; Published on: 08 June 2024
ABSTRACT
Background: People with opioid dependence have various effects, especially in the areas of psychological, physiological, and social functioning.
Aim: To study the improvement in neuropsychological functioning of patients with opioid dependence during early abstinence.
Materials and methods: The study focused on 15 patients with chronic and acute opioid dependence each. Samples were taken after the detoxification period of 2 weeks. The clinical opiate withdrawal scale (COWS) was applied to rule out mild-to-severe withdrawal symptoms, and the severity dependence scale was applied to determine the severity of opioid dependence. Wechsler Adult Intelligence Scale (WAIS)-IV India was administered twice to both groups, just after the detoxification period and at the time of discharge.
Results and discussion: The result indicates that both groups showed a significant difference in neuropsychological functioning from baseline to discharge. Scores on verbal comprehension, perceptual reasoning, working memory, processing speed, and intellectual functioning among acute opioid users improved significantly from baseline to discharge, whereas the chronic users showed a decrease in their perceptual reasoning over time.
Conclusion: Acute opioid users showed significant improvement in neuropsychological functioning over time, whereas chronic users took time to recover their neuropsychological functioning.
How to cite this article: TM MS, Sayeed N, Kumar V. Neuropsychological Functioning in Patients with Opioids Dependence during Early Abstinence: A Comparative Study. East J Psychiatry 2024;24(1):9–15.
Source of support: Nil
Conflict of interest: None
Keywords: Opioid dependence, Perceptual reasoning, Processing speed, Verbal comprehension, Working memory.
INTRODUCTION
Substance use disorders (SUDs) have been defined more and more in the past several years as long-term brain diseases brought on by prolonged exposure to psychoactive drugs.1,2 There is variation in the specific cognitive deficits among substance-using groups, and numerous studies have attempted to examine the neurocognitive functioning of persons with different SUDs.3 It also specifically suggests that impairments are different in chronic opioid use from those seen in acute and subacute users.4
According to research by Grant et al.5 on the neuropsychological deficit in polydrug users, long-term users who use opiates more frequently had worse impairment in many neuropsychological areas. Rapeli et al.6 carried out a similar investigation on cognitive function during the early stages of abstinence from opioid dependence, comparing it to the healthy control group. Critical functions are impaired in adopting a new lifestyle that is incompatible with continued drug use.7
Regarding research on heroin addiction and cognitive functioning, Guerra et al.8 suggested that a key methodological problem was the period of measurement. With continued abstinence, a number of cognitive processes seem to improve, including working memory, sustained attention, episodic memory after methamphetamine dependency, and visuospatial abilities and flexibility following cocaine dependence. According to Davis et al.,9 quitting opiates can lead to recovery, and there is a higher chance of cognitive impairment among opiate abusers. According to others, one reason why addiction is prone to relapses is the cognitive impairment linked to opiate usage.10,11
Need for the Study
A wide range of factors have been found to affect cognitive abilities in numerous research. Neuropsychological functioning has been demonstrated to be impaired in individuals with opioid use. Finding out how opioid abstinence affects cognitive functioning and how to further improve it is the driving force behind this investigation.
Neuropsychological functions are mentioned below.
Verbal Comprehension
It is an ability to process verbal stimuli. It includes one’s access to vocabulary, expressing oneself in a meaningful manner, and applying reasoning skills to verbal information. Chronic opioid users show deficits in verbal fluency.12
Working Memory
It is an ability where information is stored very shortly and temporarily. It also includes the capacity to sustain and manipulate visual and verbal information. Excessive use of opioids leads to deficits in working memory.13,14
Perceptual Reasoning
It is an ability to examine a problem, using visual–spatial skills and to reason with rules, and logical thinking. Findings indicated that long-term exposure to drugs has a great impact on perceptual-motor skills.15,16
Processing Speed
It is a mental ability as the time takes to complete a particular task. Mintzer and Stitzer17 found that excessive use of opioids leads to an impairment in psychomotor functioning.
Schulte et al.’s research18 examined the therapeutic implications and the restoration of neurocognitive abilities after long-term abstinence from drugs. Future neurocognitive therapies and treatments must take neurocognitive recovery assessment into account.
MATERIALS AND METHODS
This comparative study was approved by the institutional ethics committee in September 2015, and the study was completed in April 2017. Written informed consent was taken from all the participants before enrolling them for the study.
Design
This was a comparative study examining the differences in neuropsychological functioning in patients with opioid dependence during early abstinence. In this study, purposive sampling was used to select the sample.
Aim of the Study
To study the improvement in neuropsychological functioning of patients with opioid dependence.
Participants
All the participants were taken from the S S Raju Centre for Addiction Psychiatry (inpatients) at Central Institute of Psychiatry, Ranchi, after obtaining consent. Using purposive sampling, the participants of the study included 30 individuals with opioid dependence from a clinical population diagnosed with recent onset as per the World Health Organization’s 10th Revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10) Diagnostic Criteria for Research.19 They were divided into two groups—15 patients with the diagnosis of chronic opioid dependence (use of opioids for >2 years) and acute opioid dependence (use of opioids for <2 years) each. Additionally, all the participants required a minimum of 5 years of formal education, male gender, and the age-group of 18–50 years. Exclusion criteria were a history of neurological illness, significant head injury, and other psychiatric disorders.
Tools Used
A consent form was used to obtain consent for participation in the current research. The sociodemographic and clinical datasheet was designed to collect all details regarding age, sex, education, occupation, marital status, religion, caste, family income, and duration of illness of the patient. Additional information about the patient was obtained with the help of the institute’s case record file of the patient. The clinical opiate withdrawal scale (COWS) was developed by Wesson and Ling20 in 2003, which was used to assess a patient’s level of opiate withdrawal and to make inferences about their level of physical dependence on opioids. The severity of dependence scale (SDS) was developed by Gossop et al.11 in 1995 and used to assess the severity of dependence on opioids. The Wechsler Adult Intelligence Scale (WAIS) was developed by Wechsler21 in 1955..The current version of the test, WAIS-IV India, which was released in 2013, is composed of 10 core subtests with four indexes—verbal comprehension index (VCI), perceptual reasoning index (PRI), working memory index (WMI), and processing speed index (PSI). With these subtests comprising the full-scale intelligence quotient (FSIQ), WAIS-IV India was used to assess neuropsychological functioning.
Procedure
Patients with acute and chronic opioid dependence have been selected for the study. All patients, including chronic and acute opioid-dependent, provided written informed consent. SDS was used on the patients in groups one and two at the time of admission to determine the degree of dependence. When the detoxification phase ended, the COWS was used to measure the intensity of the withdrawal symptoms. Following the resolution of their withdrawal symptoms, the patients in both groups underwent their first administration of the WAIS-IV India to assess their neuropsychological functioning. WAIS-IV India was then readministered at the time of discharge.
Statistical Analysis
The results obtained were analyzed using the computer software program Statistical Package for the Social Sciences (version 22.0 for Windows). Different parametric measures were used. Description of sample characteristics was done with descriptive statistics like percentage, means, and standard deviation (SD). Group differences for sample characteristics and experimental variables were examined with one-way analysis of variance (ANOVA) and Chi-squared test wherever applicable. For correlation between the variables, Pearson correlation was used (Tables 1 to 8).
| Group I (chronic) n = 15 | Group II (acute) n = 15 | |||
|---|---|---|---|---|
| Variables | Mean ± SD | t (df = 28) | p | |
| Age (in years) | 29.066 ± 6.681 | 26.267 ± 5.403 | 1.255 | 0.220 |
| Education (in years) | 11.533 ± 2.38 | 9.866 ± 2.133 | 2.016 | 0.53 |
| Family income (in rupees) | 12266.66 ± 3881.5 | 9866.66 ± 3481.92 | 1.227 | 0.230 |
df, Degree of freedom; SD, standard deviation
| Group I (chronic) | Group II (acute) | ||||
|---|---|---|---|---|---|
| Variables | N (%) n = 15 | N (%) n = 15 | χ2 | p | |
| Marital status | Married | 10 (66.7%) | 8 (53.3%) | 0.556 | 0.710 |
| Unmarried | 5 (33.3%) | 7 (46.7%) | |||
| Religion | Hindu | 12 (80%) | 9 (60%) | 1.49 | 0.427 |
| Others | 3 (20%) | 6 (40%) | |||
| Occupation | Employed | 14 (93.3%) | 12 (80%) | 1.154 | 0.598 |
| Unemployed | 1 (6.7%) | 3 (20%) | |||
| Residence | Rural | 6 (40%) | 6 (40%) | 1.200 | 0.466 |
| Urban | 9 (60%) | 9 (60%) | |||
| Family type | Joint | 6 (40%) | 11 (66.7%) | 3.257 | 0.196 |
| Nuclear | 9 (60%) | 19 (33.3%) |
| Group I (chronic) n = 15 | Group II (acute) n = 15 | ||||
|---|---|---|---|---|---|
| Variables | Mean ± SD/N (%) | t/χ2 | p | ||
| Duration of illness (in years) | 5.933 ± 3.172 | 1.566 ± 0.495 | 5.267 | 0.001 | |
| Age of onset (in years) | 23.733 ± 6.125 | 24.7 ± 5.463 | 0.452 | 0.654 | |
| Past history of medical illness | Absent | 15 (100%) | 15 (100%) | – | – |
| Present | 0 (0%) | 0 (0%) | |||
| Past history of psychiatric Illness | Absent | 15 (100%) | 15 (100%) | – | – |
| Present | 0 (0%) | 0 (0%) | |||
SD, Standard deviation
| Group I (chronic) | Group II (acute) | |||
|---|---|---|---|---|
| Variables | Mean ± SD | t (df = 28) | p | |
| COWS | 3.446 ± 0.639 | 3.6 ± 0.507 | −0.632 | 0.532 |
| SDS | 12.866 ± 0.990 | 12.646 ± 1.187 | 1.002 | 0.325 |
COWS, Clinical opiate withdrawal scale; SDS, severity of dependence scale
| Baseline | Discharge | |||
|---|---|---|---|---|
| Variables | Mean ± SD | t (df = 14) | p | |
| VCI | 84.533 ± 8.830 | 88.666 ± 12.321 | −3.569 | 0.003 |
| PRI | 67.00 ± 9.388 | 64.600 ± 10.384 | 3.235 | 0.006 |
| WMI | 75.80 ± 10.107 | 77.733 ± 10.937 | −1.599 | 0.141 |
| PSI | 74.66 ± 13.449 | 74.133 ± 15.136 | 0.377 | 0.712 |
| FSIQ | 71.933 ± 8.387 | 72.333 ± 9.360 | −0.549 | 0.592 |
df: Degree of freedom; FSIQ, full scale intellectual quotient; PRI, perceptual reasoning index; PSI: processing speed index; SD: standard deviation, VCI: verbal comprehension index, WMI: working memory index
| Baseline | Discharge | |||
|---|---|---|---|---|
| Variables | Mean ± SD | t (df =14) | p | |
| VCI | 77.600 ± 8.270 | 81.466 ± 10.350 | −3.965 | 0.001 |
| PRI | 60.800 ± 6.710 | 63.933 ± 7.156 | 3.246 | 0.006 |
| WMI | 66.866 ± 7.945 | 72.200 ± 6.405 | −6.123 | 0.001 |
| PSI | 63.866 ± 9.898 | 71.66 6 ± 10.847 | −8.107 | 0.001 |
| FSIQ | 63.33 ± 6.54 | 68.066 ± 8.004 | −7.040 | 0.001 |
df, Degree of freedom; FSIQ, full scale intellectual quotient; PRI, perceptual reasoning index; PSI, processing speed index; SD, standard deviation; VCI, verbal comprehension index; WMI, working memory index
| Mean ± SD | |||
|---|---|---|---|
| Variables | Chronic | Acute | |
| VCI | Baseline | 84.533 ± 8.830 | 77.600 ± 8.270 |
| Discharge | 88.666± 12.321 | 81.466 ± 10.350 | |
| PRI | Baseline | 67.00 ± 9.388 | 60.800 ± 6.710 |
| Discharge | 64.600 ± 10.384 | 63.933 ± 7.156 | |
| WMI | Baseline | 75.80 ± 10.107 | 66.866 ± 7.945 |
| Discharge | 77.733 ± 10.937 | 72.200± 6.405 | |
| PSI | Baseline | 74.66 ± 13.449 | 63.866 ± 9.898 |
| Discharge | 74.133 ± 15.136 | 71.66 6± 10. 847 | |
| FSIQ | Baseline | 71.933 ± 8.387 | 63.33 ± 6.54 |
| Discharge | 72.333 ± 9.363 | 68.066 ± 8.004 | |
FSIQ, Full scale intellectual quotient; PRI, perceptual reasoning index; PSI, processing speed index; SD, standard deviation; VCI, verbal comprehension index; WAIS, Wechsler adult intelligence scale; WMI, working memory index
| Variables | Time and group | F | p | Partial eta squared | Observed power |
|---|---|---|---|---|---|
| VCI | Time | 27.915 | 0.001 | 0.499 | 0.999 |
| Time and group | 0.31 | 0.861 | 0.001 | 0.053 | |
| PRI | Time | 0.363 | 0.552 | 0.013 | 0.090 |
| Time and group | 20.652 | 0.001 | 0.424 | 0.992 | |
| WMI | Time | 22.993 | 0.001 | 0.451 | 0.996 |
| Time and group | 5.034 | 0.033 | 0.152 | 0.582 | |
| PSI | Time | 18.056 | 0.001 | 0.392 | 0.984 |
| Time and group | 23.746 | 0.001 | 0.459 | 0.997 | |
| FSIQ | Time | 26.793 | 0.001 | 0.489 | 0.999 |
| Time and group | 19.093 | 0.001 | 0.405 | 0.988 |
FSIQ, full scale intellectual quotient; PRI, perceptual reasoning index; PSI, processing speed index; VCI, verbal comprehension index; WAIS, Wechsler adult intelligence scale; WMI, working memory index
RESULTS
Analysis Exploring the Sociodemographic and Clinical Variables (Both Continuous and Categorical)
Tables 1 and 2 provide comparative information about the sociodemographic characteristics of acute and chronic groups. Continuous variables were compared using the t-test, whereas categorical variables were analyzed using Pearson Chi-squared or Fisher’s exact test, wherever applicable, such as religion, marital status, education, occupation, income, family type, and habitat. No significant differences were found between the two groups across these variables.
Tables 3 and 4 present the comparison of both groups on various clinical variables such as age of onset, duration of illness, and history of psychiatric and medical illness. As indicated by the p-values, no significant differences were found between the groups in the age of onset, presence of family history of psychiatric and medical illness, SDS, and COWS.
Comparison of Neuropsychological Functioning among Acute and Chronic Groups with Opioids Dependence
Table 5 shows the comparison of scores obtained on WAIS-IV India between baseline and discharge assessment of the chronic group of opioid dependence. It was found that there is a statistically significant difference between baseline and discharge in the VCI (p = 0.003) and the PRI (p = 0.006). However, there is no statistically significant difference in the WMI, the PSI, and the FSIQ.
Table 6 shows the comparison of scores obtained on WAIS-IV India between baseline and discharge assessment of the acute group of opioid dependence. It was found that there is a statistically significant difference between baseline and discharge in VCI (p = 0.001), PRI (p = 0.006), WMI (p = 0.001), PSI (p = 0.001), and FSIQ (p = 0.001).
Tables 7 and 8 show that there was a significant change (p < 0.05) in WAIS scores in the domains of VCI, PRI, WMI, PSI, and FSIQ over time in both groups.
A substantial shift in VCI scores was seen over time in both groups, as shown by a partial eta squared value of 0.499 and a p-value of 0.001. Wilks’s λ had a value of 27.915. However, there was no discernible time and group interaction for the VCI scores, and the groups did not differ from one another in terms of scores at any point in time (p-values and partial eta squared values of 0.861, 0.41, and 0.001, 0.31). With a p-value of 0.866 and a partial eta squared value of 0.001, it was seen that there was no significant change in the PRI scores over time for either group. On the contrary, the PRI score showed statistically significant group and time interaction with a p-value of 0.001, Wilks’s λ of 20.652, and partial eta squared of 0.424. A statistically significant change in WMI scores over time was observed in both groups, as indicated by a partial eta squared value of 0.451 and a p-value of 0.00. Wilks’s λ had a value of 22.993. Furthermore, significant group interaction and time effect were seen for the WMI scores (Wilks’s partial eta squared value, p-value, and λ were 0.033, 5.034, and 0.152, respectively). It was observed that both groups’ PSI scores had significantly changed over time as seen with a p-value of 0.001 and a partial eta-squared value of 0.392. Wilks’s λ had a value of 18.056. Additionally, a significant group interaction and time relationship were seen, as indicated by the partial eta squared value of 0.459, Wilks’s λ of 23.746, and a p-value of 0.001. A significant change in FSIQ scores over time was observed in both groups, as shown by a partial eta squared value of 0.489 and a p-value of <0.001. Wilks’s λ had a value of 26.793. Additionally, a significant group interaction and time relationship were seen, as indicated by the partial eta squared value of 0.405, Wilks’s λ of 19.093, and a p-value of 0.001. Ultimately, these results indicated that there have been distinct changes over time in both the acute and chronic groups. The acute group has shown highly significant changes when compared to the chronic group.
DISCUSSION
Neuropsychological Profile in Opioids Dependence Syndrome
In various studies, it has been discovered that opioid dependence affects cognitive functioning while a person is abstaining. Our goal was to determine whether patients with opioid dependence had improved cognitive functioning. Both the chronic and the acute groups with opioid dependence showed improvement, although the chronic group required more time than the acute group. Studies on the neuropsychology of long-term opioid users have revealed similarly erratic deficiencies on measures of executive function.22,23
Working Memory in Opioids Dependence Syndrome
Alertness, attention, encoding, mental manipulation, visual–spatial imaging, concentration, numerical reasoning ability, and quantitative knowledge are all included in working memory. Research revealed that the aforementioned working memory functions are significantly impaired.12,24,25 A significant portion of working memory function is determined by biological variables. Alhola and Polo-Kantola, for instance,26 found that sleep deprivation affects how well working memory functions. In the present study, it was found that there was a statistically significant difference in both groups regarding this functioning. It has been found that the mean value of WMI during baseline was 75.803 ± 10.107 for chronic opioid dependence and 66.866 ± 7.945 for acute opioid dependence. In a similar study,6 it had studied that early abstinent opioids dependent patients performed statistically significantly worse than controls in tests measuring complex working memory.
Improvement of Working Memory in Opioids Dependence
In the present study, there was a statistically significant improvement in both chronic and acute groups with opioid dependence. Both have shown improvement in the period from baseline to discharge. The baseline and discharge mean value of the chronic group with opioid dependence were 75.80 ± 10.107 and 77.733 ± 10.937, and for the acute group with opioid dependence were 66.866 ± 7.945 and 72.200 ± 6.405. The acute group with opioid dependence shows a highly significant improvement in working memory compared to the chronic group with opioid dependence. The chronic group had taken more time to improve in working memory functioning than the acute group with opioid dependence. Similar to this, Guerra et al.8 did neuropsychological performance in opiate addicts after rapid detoxification where neuropsychological performances were carried out before and after a rapid (1 week) detoxification treatment. At reevaluation, the participants showed improvement in most measures, especially in working memory.
Verbal Comprehension in Opioid Dependence
Lower scores were found on verbal fluency in opiate-dependent subjects compared to controls.27 This could be seen in patients who have chronic substance abuse. It may lead them to be socially isolated and having difficulty in making new friends as they cannot communicate effectively through language. Over time, it was seen in the present study, there was a statistically significant difference between both groups. However, the groups did not differ with each other in terms of the scores at any time points, and also there was no significant improvement over time and group interaction. It could be due to not being sensitive to the illness easily (hold test). While attention and mental flexibility/abstract reasoning skills remain unaffected, an earlier study28 found that heroin addiction negatively impacts impulse control. Brown and Partington29 also discovered that there are no appreciable variations on the verbal scale.
Improvement of Verbal Comprehension in Opioids Dependence
Additionally, it was discovered that both groups of people with acute and chronic opioid dependence showed improvements over time in verbal idea generation, factual knowledge, long-term memory, and abstract reasoning. Compared to the acute opioid dependence group, the chronic opioid dependence group performed poorly. On batteries of standard neuropsychological tests like the Halstead–Reitan neuropsychological test battery (HRNB), WAIS, and Aphasia tests, early research found some evidence that chronic opiate abusers are more likely to be impaired. However, Hill and Mikhael30 found evidence of impairment in some memory measures but relatively few impairments in tasks involving abstraction and reasoning.31
Processing Speed in Opioid Dependence
Processing speed involves visuomotor coordination, psychomotor speed, speed of mental operation, attention, concentration, cognitive flexibility, and perceptual speed. In the present study, processing speed was assessed by WAIS-IV India. The chronic group had performed poorly compared to the acute group with opioid dependence. This finding has been consistent with previous studies that long-term opiate use was associated with decrements in attention, concentration, and psychomotor functioning.4,24
Improvement of Processing Speed in Opioids Dependence
As we have seen, many other factors also influence the processing speed of individuals. Franken et al.32 studied that reaction time on heroin cues was significantly predicted by heroin craving levels. Results indicated that selective processing may be related to motivational-induced states in general. While the acute group exhibited very significant improvement over time, the chronic group with opioid dependence has taken a lengthy time to improve in the function of processing speed. Significantly worse psychomotor/cognitive speed performance was observed by Mintzer and Stitze.17 The results of a study by Davis et al.9 support the idea that some recovery of functioning may occur during abstinence. The findings that the performance of the abstinent abusers was intermediate between that of the methadone maintenance patients and controls, and did not differ significantly from that of the controls on most measures.
Perceptual Reasoning Opioid Dependence
Nonverbal concept generation and reasoning, fluid intelligence, broad visual intelligence, visual perception and organization, spatial ability and classification, and part-whole relationship knowledge are all included in perceptual reasoning. Our goal was to determine how much better off the acute and chronic opioid-dependent groups were from one another. It was discovered that there was progress in both groups. Compared to the chronic group with opioid dependence, the acute group fared better. Kar and Jain report impairment in specific neuropsychological domains.33 Alcohol and psychostimulants have comparatively stronger effects on impulsive behavior and cognitive flexibility. Similar effects on perceptual speed, spatial processing, and selective attention are seen when alcohol and 3,4-methylenedioxy-N-methamphetamine (MDMA) are combined. In a similar vein, cannabis and MDMA have more of an impact on processing speed and intricate planning than do cannabis and methamphetamine.34 Subtle adverse effects of cocaine on perception are seen.35,36
Improvement of Perceptual Reasoning in Opioids Dependence
It was discovered that over time, the acute group with opioid dependence performed better than the chronic group with opioid dependence. Long-term high-dosage heroin use and its effects on neuropsychological functioning in the domains of verbal recognition memory and perceptual-motor speed were examined by Strang and Gurling.37 Emotional processing deficits have been noted in human studies on the acute administration of opioids.38 The results of Fishbein et al.39 indicating heroin addicts typically perform worse than healthy individuals on a variety of prefrontal functions, such as working memory, attention, learning, and pattern recognition, further reinforced this idea. These results lead to deficiencies in reasoning, which could result in poor decision-making skills. Following 3 weeks of abstinence, drug addicts’ and users’ cognitive performance was assessed. Heroin users performed less well while making decisions. The acute group with opioid dependence showed a significant improvement in perceptual reasoning, according to the current study. When these patients maintained long-term abstinence, they displayed cognitive recovery. The persistence of some disabilities implied good behavior and effective management.
Intellectual Functioning in Opioids Dependence
Both chronic and acute groups with opioid dependence differed in terms of intellectual functioning. Scores of chronic groups with opioid dependence were low compared to the acute group. Findings indicate more decline in the group of chronic opioid dependence. A study by Rapeli et al.6 found that early abstinent opioids dependent individuals performed worse than normal controls in intellectual functioning. Isbell et al.40 also studied that methadone might have a detrimental effect on intelligence.
Improvement of Intellectual Functioning in Opioids Dependence
We also found that the acute group with opioid dependence had highly improved over time period in intellectual functioning, whereas the chronic group with opioid dependence showed gradual improvement in intellectual functioning. Similar to this finding, Gordon and Lipset41 found that over a period of time, there was a gain in intellectual functioning in those who received methadone.
CONCLUSION
Performance on verbal comprehension, perceptual reasoning, working memory, processing speed, and intellectual functioning among acute opioid users improved significantly from baseline to discharge. Findings indicate that chronic opioid users showed significant improvement in verbal comprehension, but there was a decrease in their perceptual reasoning. This might lead to difficulties in decision-making abilities, which will have to be focused on in management. Otherwise, this may result in repeated substance use among those patients.
Limitations
There are always going to be limitations to research, and this study is no different. However, due to the use of purposive sampling in this study, it was not possible to completely eliminate the sources of the inadequacies found in the research. The tiny sample size of this study was one of its main drawbacks. Over time, more subtle alterations can be found with bigger samples. Purposive sampling was used; randomized sampling would have resulted in more generalizability. The postassessment was completed following a 15-day detoxification period; if it had been completed sooner, the influence of time would have been more evident. Gender differences were not examined in this study because it did not include any female participants.
FUTURE DIRECTIONS
In order to increase generalizability, randomized sampling should be performed. To see how neuropsychological functioning improves over time, longer follow-up investigations are required. It is necessary to conduct more large-scale, controlled investigations. Experience should have little to no influence on neuropsychological tests. It is important to evaluate gender disparities by including female patients in the study.
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