Mental health outcomes associated with the use of amphetamines: A systematic review and meta-analysis

Subst Abuse Treat Prev Policy

Christer

et al. 2020

Background The impact of clinical and sociodemographic factors on fatigue remains unknown among patients with substance use disorders (SUD). This study aims to evaluate fatigue among patients with SUD using a nine-item fatigue severity scale (FSS-9) and identify the impact that clinical and sociodemographic factors – such as injecting substance use, chronic infectious diseases, liver fibrosis, opioid agonist therapy (OAT), debt difficulties, and housing situation – have on fatigue. Methods We used data from a cohort of patients with SUD in Norway with annual health assessments surveying FSS-9 and some clinical and sociodemographic factors. A total of 915 FSS-9 measurements were collected from 654 patients during the period 2016–2020. We defined baseline as the first annual health assessment when the health assessments were listed chronologically. Time was defined as years from baseline. We used a linear mixed model to analyse whether the clinical and sociodemographic factors affected the FSS-9 sum score, presented with beta coefficients (β) with 95% confidence intervals (CI). Results The mean sum score of the FSS-9 was 43 (standard deviation: 16) at baseline. Females compared with males (adjusted mean difference of FSS-9 sum score: 4.1, 95% CI: 1.3–7.0), having debt difficulties compared with having no debt difficulties (2.9;0.4–5.3), and frequent use of benzodiazepines (5.7;3.0–8.4) or amphetamines (-5.0;-8.0– -2.0) compared to less frequent or no use of these substances changed the FSS-9 baseline sum score. The other clinical and sociodemographic factors did not predict any clinically relevant change in the FSS-9 sum score from baseline to the following health assessments. Conclusion Patients with SUD suffer from high levels of fatigue. Female patients, patients with debt difficulties, and those with extensive use of benzodiazepines are at particular risk of being fatigued. This should be taken into consideration when planning health services.

Section: Discussionmentioning

confidence: 99%

Impact of clinical and sociodemographic factors on fatigue among patients with substance use disorder: a cohort study from Norway for the period 2016–2020

Subst Abuse Treat Prev Policy

Christer

et al. 2020

“…Benzodiazepine use is overall associated with lower quality of life, self-reported physical health, and more disability than non-benzodiazepine use in the general population [39,40], which is transferable with the lower fatigue levels shown in the present study. Furthermore, using stimulants, particularly illicit amphetamines, is generally associated with poor mental health and stimulant withdrawal symptoms in the SUD populations [41,42]. A temporary sense of better selfperceived mental health and fewer withdrawal symptoms may arise when consuming stimulant substances, which contributes to a temporary reduction of fatigue compared to the experience without stimulants.…”

Section: Discussionmentioning

confidence: 99%

Impact of Clinical and Sociodemographic Factors on Fatigue Among Patients With Substance Use Disorder: A Cohort Study From Norway for The Period 2016-2020

Christer

et al. 2020

Preprint

Background The impact of clinical and sociodemographic factors on fatigue remains unknown among patients with substance use disorders (SUD). This study aims to evaluate fatigue among patients with SUD using a nine-item fatigue severity scale (FSS-9) and identify the impact that clinical and sociodemographic factors – such as injecting substance use, chronic infectious diseases, liver fibrosis, opioid agonist therapy (OAT), debt difficulties, and housing situation – have on fatigue.Methods We used data from a cohort of patients with SUD in Norway with annual health assessments surveying FSS-9 and some clinical and sociodemographic factors. A total of 915 FSS-9 measurements were collected from 654 patients during the period 2016-2020. We defined baseline as the first annual health assessment when the health assessments were listed chronologically. Time was defined as months from baseline. We used a linear mixed model to analyse whether the clinical and sociodemographic factors affected the FSS-9 sum score, presented with beta coefficients (β) with 95% confidence intervals (CI). Results The mean sum score of the FSS-9 was 43 (standard deviation: 16) at baseline. Being female (change in FSS-9 sum score: 4.1, 95 % CI: 1.3-7.0), having debt difficulties (2.9;0.4-5.3), and using benzodiazepines (5.7;3.0-8.4), amphetamine or cocaine (-5.0;-8.0--2.0) affected the FSS-9 sum score. The other clinical and sociodemographic factors did not predict any clinically relevant change in the FSS-9 sum score from baseline to the following health assessments.Conclusion Patients with SUD suffer from high levels of fatigue. Focusing on closer follow-up of females and reducing debt difficulties and the use of benzodiazepines may mitigate fatigue in the SUD population.

“…Other research indicate that high doses of benzodiazepines reduce social functioning, and that it may also increase psychological distress and worsen mental health [16,40], and misuse of benzodiazepines is seen among both SUD and psychiatric populations alike [41]. Similarly, the use of stimulants, in particular methamphetamine, has been associated with poor mental health outcomes [23]. Selfmedication of attention de cit hyperactivity disorder (ADHD) with stimulants could be one explanation for these ndings.…”

Section: Discussionmentioning

confidence: 99%

“…Opioid dependence is the most severe SUD, and of all illegal drugs, opioids represents the most fatal risk factor, the highest disease burden and most urgent demand for treatment [20,21]. In addition, substance use patterns of cannabis and simulants especially frequent use, are found to be associated with residual cognitive impairment and poor mental health [22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Substance Use and Symptoms of Mental Health Disorders: a Prospective Cohort of Patients With Severe Substance Use Disorders in Norway

Aas¹,

et al. 2020

Preprint

BackgroundThere is high co-occurrence of substance use disorders (SUD) and mental health disorders. We aimed to assess impact of substance use patterns and sociodemographic factors on mental health distress using the ten-item Hopkins Symptom Checklist (SCL-10) over time.MethodsNested prospective cohort study of 707 participants with severe SUD across nine opioid-agonist-therapy outpatient clinics and low-threshold municipality clinics in Norway, during 2017-2020. Descriptive statistics were derived at baseline and reported by means and standard deviation (SD). A linear mixed model analysis was used to assess the impact of substance use patterns and sociodemographic factors on SCL-10 sum score with beta coefficients with 95% confidence intervals (CI).ResultsMean (SD) SCL-10 score was 2.2 (0.8) at baseline with large variations across patients. We observed more symptoms of mental health disorders among people with frequent use of benzodiazepines (beta 3.6, CI:2.4;4.8), cannabis (1.3, CI:0.2;2.5), opioids (2.7, CI:1.1;4.2), and less symptoms among people using frequently stimulants (-2.7, CI:-4.1;-1.4) compared to no or less frequent use. Females (1.8, CI:0.7;3.0) and participants with debt worries (2.2, CI:1.1;3.3) and unstable living conditions (1.7, CI:0.0;3.3) had also higher burden of mental health symptoms. There were large individual variations in SCL-10 score from baseline to follow-up, but no consistent time trends indicating change over time for the whole group. 65 % of the cohort had a mean score >1.85, the standard reference score.ConclusionsPeople with SUD are considerably more likely to have symptoms of mental health disorders compared to the general population. The lack of association between substance use patterns on change in mental health symptoms over time could suggest that the differences observed were indicating flattening of effects or self-medication to larger degree than medication-related decline in mental health. This call for better individualized mental health assessment and patient care.