<i>Aims. </i>Sleep disturbances are common in addiction and withdrawal. This study examined the course of sleep quality in a population of alcohol dependent patients during qualified detoxification treatment in a psychiatric hospital.<i> Methods. </i>The Pittsburgh Sleep Quality Index (PSQI) was administered to 77 electively admitted alcohol dependent patients hospitalized for qualified detoxification treatment. Sleep quality was measured at admission and at discharge.<i> Results. </i>The prevalence of bad sleep as measured by a PSQI-score &#x3e; 5 was 70.1&#x25; at admission. During detoxification, male and female patients were equally affected by sleep disturbances and improvement of sleep was not significantly different between males and females. The PSQI score at admission predicted the change of the PSQI score during qualified detoxification treatment. After inpatient detoxification, sleep disturbances persisted in 59.7&#x25; of the patients.<i> Conclusions. </i>Contrary to our expectations, the average patient&#x2019;s sleep quality improved in our study after two weeks of detoxification treatment. Sleep disturbances nevertheless persisted in almost two-thirds of the patients. In the view of that finding, patients may require individual evaluation of sleep quality and insomnia-specific treatment in the course of detoxification therapy.

Peter Neu

Yvonne Sofin

Heidi Danker-Hopfe

The Effect of Detoxification on Sleep: How Does Sleep Quality Change during Qualified Detoxification Treatment?

<i>Background</i>. Opioid agonist treatment (OAT), for the treatment of heroin dependence, has been reported to improve overall health and lower mortality. Drug use and retention in treatment have often been used as measures of treatment success. More recently, however, researchers have suggested that measurements of quality of life should be an outcome in substance use treatment evaluations. In a recent randomized controlled trial we demonstrated high rates of successful rapid referral from a needle exchange program (NEP) to OAT. The aim of this study was to see whether an improvement in health related quality of life (HRQoL) could be seen at 3-month follow-up after starting OAT and whether it was associated with any baseline characteristics. We also wanted to compare our sample to a sample from the general population with regard to HRQoL.<i> Methods. </i>This was a 3-month follow-up of 71 patients who started OAT. Measurements of HRQoL with EQ-5D (an instrument developed by the EuroQol group) were made at baseline and at three months.<i> Results.</i> Mean EQ-5D VAS (visual analogue scale) for the study sample at baseline was 47.3, which was lower than a Swedish reference population reporting 83.3. Individuals reporting being prescribed a drug for a psychiatric condition had significantly lower EQ-5D index values. Improvement in EQ-5D index score was significantly less for individuals reporting previous overdoses (-0.10, p=0.025). Individuals reporting previous suicide attempts had significantly lower EQ-5D VAS score at baseline. A significant increase of the EQ-5D VAS difference over time was found with a mean difference of 10.94 (p=0.008) for the total sample.<i> Conclusion</i>. To our knowledge this is the first time HRQoL as an outcome is reported in a population transferred from a NEP to OAT. Our results indicate that OAT can result in increased HRQoL, even with this type of rapid low-threshold referral.

Martin Br&#xe5;b&#xe4;ck

Louise Br&#xe5;dvik

Katja Troberg

Pernilla Isendahl

Suzan Nilsson

Anders H&#xe5;kansson

Health Related Quality of Life in Individuals Transferred from a Needle Exchange Program and Starting Opioid Agonist Treatment

<i>Background</i>. Epidemiological and experimental models have been applied to describe the disproportionately high prevalence of tobacco use in patients with mental illness. This observed association has become a dire public health concern. The main objective of the present study was to examine the provision of tobacco treatment strategies in a community teaching hospital serving a predominantly underserved African American population.<i> Methods</i>. The study was designed as a retrospective review of eight hundred and thirty patients admitted to the inpatient psychiatric units.<i> Results</i>. 52.2&#x25; of the entire cohort described themselves as current smokers. Gender, primary psychiatric diagnosis, and urine toxicology showed significant differences in the tobacco smoking and nontobacco smoking groups (P&#x3c;0.05). Almost all current tobacco smokers (91.9&#x25;) had tobacco cessation counseling during the course of their hospitalization, but only 64&#x25; were offered treatments for tobacco dependence. More than half (57.9&#x25;) of the 680 participants who had urine toxicology reports were positive for any illicit substance with cannabis and cocaine being the most frequently used (32.4&#x25; and 23.2&#x25;). Direct logistic regression revealed gender, psychiatric diagnosis, and substance use as the only significant predictors of tobacco smoking among our cohort (P= 0.021, 0.001, and 0.001, respectively).<i> Conclusions</i>. Tobacco screening, cessation counseling, and treatment continue to be a challenge in community psychiatric hospitals and need increased focus in the comprehensive management of patients with psychiatric disorders. The strong association between tobacco smoking and other substance use lends itself to the hypothesis that tobacco smoking debut prevention may be an effective public health strategy for addressing illicit drug use.

Oluwole Jegede

Olawale Ojo

Saad Ahmed

Kodjovi Kodjo

Inderpreet Virk

Dina Rimawi

Cory Mellon

Ayodeji Jolayemi

Tolu Olupona

Tobacco and Substance Use among Psychiatric Inpatients in a Community Hospital: Cessation Counseling, Correlates, and Patterns of Use

The long-term use of opioids leads alternations in both innate-adaptive immune systems and other diagnostic hematologic cells. The purpose of this study is to evaluate the alterations of these parameters in patients with heroin/opioid addictions. Adults, meeting the Fifth Edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria of the American Psychiatric Association regarding opioid use disorder (Heroin Group or HG, n = 51) and healthy controls (Control Group or CG, n = 50), were included in the study. All hematological parameters, inflammation indexes (neutrophil-lymphocyte ratio and platelet-lymphocyte ratio), and iron panel were compared with the controls. Mean corpuscular volume, red blood cell distribution width, mean corpuscular hemoglobin content, unsaturated iron-binding capacity, and total iron-binding capacity were significantly higher in HG compared to CG, while red blood cell count, hemoglobin, hematocrit, and serum iron levels were significantly lower. Additionally, platelet and platelet distribution width were significantly high while mean platelet volume was low in HG. Regarding the parameters related to immunity, white blood cell, neutrophil count, and neutrophil percentage were significantly high while lymphocyte percentage and basophils count were significantly low. Besides, inflammatory indexes were significantly higher in HG compared to CG. Intravenous administration of heroin resulted in lower levels of hemoglobin, hematocrit, and mean corpuscular volume than inhalation and intranasal administration. Our data demonstrated that chronic use of opioids is related to all of the hematologic series. The chronic use of opioid alters the immunologic balance in favor of innate immunity cells and changes the hematometric/morphometric characteristics of erythrocytes. What is more, the route of heroin administration should be taken into consideration as well. This study may lead to a better understanding of the hematological effects of heroin/opioid use in patients with relevant addictions.

Derya Guzel

Ahmet Bulent Yazici

Esra Yazici

Atila Erol

Evaluation of Immunomodulatory and Hematologic Cell Outcome in Heroin/Opioid Addicts

<i>Background</i>. Smoking is the leading cause of preventable death. In Thailand, the prevalence of smoking is about 15-20 times higher among men than women. This study aimed to investigate gender differences among university students concerning smoking behaviors, nicotine dependence, and intention to quit smoking.<i> Methods</i>. A self-administered questionnaire was used to collect information from participants who were current smokers studying at a university in northern Thailand. Snowball sampling was used to recruit participants.<i> Results</i>. Of 364 participants, there were 321 males and 43 females. This study showed higher smoking behaviors among males than females; males were more likely to smoke every day than females (67.0 and 41.9&#x25;, respectively, p value=0.002), and the average number of cigarettes daily was higher among males than females (8.4 and 5.5, respectively, p value=0.006). The sources of cigarettes differed between males and females. The nicotine dependence level, as measured by the Fagerstrom Test for Nicotine Dependence, was quite low in both male and female smokers and did not differ significantly (mean score of 2.3&#xb1;2.2 for males, 1.8&#xb1;1.8 for females; p value=0.123). Females were more likely than males toward intention to quit in the next 30 days (51.2 and 34.0&#x25;, respectively, p value=0.041). The most common reason for intention to quit was awareness of harm to health, for which females were more concerned than males.<i> Conclusion</i>. Male and female university students who smoked differed in smoking behaviors and intention to quit, but not in nicotine dependence level. The university should provide health promotion to help students quit smoking.

Dujrudee Chinwong

Ngamtip Mookmanee

Jongkonnee Chongpornchai

Surarong Chinwong

A Comparison of Gender Differences in Smoking Behaviors, Intention to Quit, and Nicotine Dependence among Thai University Students

<i>Background</i>. Rates of cigarette smoking among the public and individuals with mental illness have been well documented. Studies have demonstrated that prevalence of smoking among individuals with mental illness remains elevated compared to the general population and as a distinct subgroup, individuals with mental illness consume more than a third of cigarettes sold in the U.S. However, information on rates of smoking among patients presenting to a psychiatric emergency room (ER) is lacking. This study assesses this understudied population for smoking prevalence and associated factors.<i> Methods</i>. A retrospective chart review of 203 distinct psychiatric ER patients was conducted. Demographics, tobacco use, substance use, psychiatric diagnoses, and family history were noted and analyzed with SPSS.<i> Result</i>. Tobacco use rates were noted to be nearly fifty percent and significant associations were found with active suicidal ideation, alcohol use disorders, illicit drug use disorders, and history of prior psychiatric hospitalization.<i> Conclusion</i>. Tobacco use among psychiatric ER patients is much higher than that of the general population and associated with active suicidal ideations, alcohol use disorders, and illicit substance use disorders. These findings should be considered in the evaluation and expectant management of these patients by their clinicians and healthcare providers.

Ashely Collins

Oluwadamilare Ajayi

Savannah Diamond

William Diamond

Suzanne Holroyd

Tobacco Use and Associated Factors in Patients Presenting to a Psychiatric Emergency Room

<i>Background. </i>This study aimed to map differences between male and female offenders with substance abuse, with respect to descriptive characteristics and risk factors for mortality and criminal recidivism.<i> Methods.</i> Criminal justice clients with substance abuse problems <span class="inline_break"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="22.287pt" style="vertical-align:-2.26807pt" id="M1" height="11.5564pt" version="1.1" viewBox="-0.0498162 -9.28833 22.287 11.5564"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g113-41" d="M300 -147C201 -63 143 98 143 270S200 602 300 686L282 710C136 610 70 450 70 271V270C70 89 136 -72 282 -170L300 -147Z"/></g><g transform="matrix(.013,0,0,-0.013,4.498,0)"><path id="g113-111" d="M495 86L479 114C446 82 419 66 409 66C401 66 401 72 406 97C420 166 436 231 453 297C489 435 454 448 428 448C406 448 384 439 354 422C305 394 222 327 161 247H159L183 345C200 415 194 448 173 448C143 448 82 410 23 351L38 325C64 349 95 371 105 371C111 371 116 365 109 336L25 -4L31 -12C50 -4 77 3 107 9C119 69 132 122 145 168C197 254 321 381 370 381C387 381 393 374 378 305L329 95C309 17 320 -12 345 -12C372 -12 430 19 495 86Z"/></g><g transform="matrix(.013,0,0,-0.013,14.656,0)"><path id="g117-34" d="M535 323V373H52V323H535ZM535 138V188H52V138H535Z"/></g></svg><span class="irelop"/><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="29.738pt" style="vertical-align:-2.26807pt" height="11.5564pt" version="1.1" viewBox="25.869183800000002 -9.28833 29.738 11.5564"><g transform="matrix(.013,0,0,-0.013,25.919,0)"><path id="g113-56" d="M447 623H65C61 580 56 530 47 475H76C100 541 106 550 172 550H388C308 376 196 170 91 -1L98 -12L172 -2C268 204 360 408 455 611L447 623Z"/></g><g transform="matrix(.013,0,0,-0.013,32.161,0)"><path id="g113-49" d="M241 635C89 635 35 457 35 312C35 153 89 -12 240 -12C390 -12 443 166 443 312C443 466 390 635 241 635ZM238 602C329 602 354 454 354 312C354 172 330 22 240 22C152 22 124 173 124 313S148 602 238 602Z"/></g><g transform="matrix(.013,0,0,-0.013,38.401,0)"><path id="g113-57" d="M249 635C141 635 70 555 70 471C70 401 114 353 179 316C143 294 106 267 90 252C68 231 45 202 45 157C45 50 130 -12 237 -12C322 -12 435 52 435 169C435 256 372 304 303 343C349 374 375 398 383 407C401 429 411 458 411 487C411 569 344 635 249 635ZM238 603C285 603 337 567 337 482C337 422 310 385 276 358C205 393 145 426 145 500C145 552 179 603 238 603ZM248 20C183 20 125 70 125 163C125 218 158 268 206 300C284 261 355 217 355 143C355 66 308 20 248 20Z"/></g><g transform="matrix(.013,0,0,-0.013,44.641,0)"><path id="g113-54" d="M153 550H386L412 615L406 623H120L82 318C104 327 142 338 184 338C294 338 347 275 347 187C347 112 305 39 221 39C160 39 119 71 97 89C88 97 80 96 71 90C59 80 50 67 49 57C48 45 52 36 66 23C80 9 123 -12 169 -12C221 -11 288 15 342 59C403 109 431 165 431 225C431 308 366 395 238 395C212 395 165 379 127 364L153 550Z"/></g><g transform="matrix(.013,0,0,-0.013,50.881,0)"><path id="g113-42" d="M275 270C275 450 212 609 64 710L45 686C145 604 203 442 203 270S147 -63 45 -147L64 -170C213 -68 275 89 275 270Z"/></g></svg></span> were interviewed with the Addiction Severity Index. Mortality and data on return to criminal justice were retrieved from national registers.<i> Results. </i>Female offenders reported heavier substance use patterns, more psychiatric symptoms, and more often a partner with substance abuse, but had lower mortality (2% versus 4%) and criminal recidivism (62% versus 71%) during follow-up. Having a substance-abusing partner was associated with criminal recidivism among females.<i> Conclusions. </i>Female offenders with substance abuse differ from their male counterparts. Males and females had different risk factors for criminal recidivism.

Caroline Mannerfelt

Substance Use, Criminal Recidivism, and Mortality in Criminal Justice Clients: A Comparison between Men and Women

<i>Introduction</i>. A substantial proportion of cancer patients continue to smoke after their diagnosis but few studies have evaluated correlates of nicotine dependence and smoking rate in this population, which could help guide smoking cessation interventions.<i> Aim</i>. This study evaluated correlates of smoking rate and nicotine dependence among 207 cancer patients.<i> Methods</i>. A cross-sectional analysis using multiple linear regression evaluated disease, demographic, affective, and tobacco-seeking correlates of smoking rate and nicotine dependence. Smoking rate was assessed using a timeline follow-back method. The Fagerström Test for Nicotine Dependence measured levels of nicotine dependence.<i> Results</i>. A multiple linear regression predicting nicotine dependence showed an association with smoking to alleviate a sense of addiction from the Reasons for Smoking scale and tobacco-seeking behavior from the concurrent choice task (<span class="inline_break"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="18.973pt" style="vertical-align:-3.42938pt" id="M1" height="11.7782pt" version="1.1" viewBox="-0.0498162 -8.34882 18.973 11.7782"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g113-113" d="M570 304C570 398 525 448 414 448C385 448 343 445 312 434L329 511L321 518C297 504 262 482 244 460L233 411C195 397 159 381 128 358L135 332C160 347 189 360 224 373L111 -147C97 -210 84 -218 17 -231L13 -257L254 -247L259 -218L233 -216C183 -212 177 -202 189 -142L218 -1C238 -10 266 -12 283 -12C351 3 429 48 483 105C543 168 570 242 570 304ZM482 289C482 161 380 33 304 33C278 33 248 51 233 69L303 396C326 400 352 403 369 403C428 403 482 380 482 289Z"/></g><g transform="matrix(.013,0,0,-0.013,11.342,0)"><path id="g117-91" d="M512 -3V55L134 254V256L512 456V514L75 281V230L512 -3Z"/></g></svg><span class="irelop"/><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="15.658pt" style="vertical-align:-3.42938pt" height="11.7782pt" version="1.1" viewBox="22.555183800000002 -8.34882 15.658 11.7782"><g transform="matrix(.013,0,0,-0.013,22.605,0)"><path id="g113-47" d="M113 -12C146 -12 170 11 170 46C170 78 146 103 114 103S58 78 58 46C58 11 82 -12 113 -12Z"/></g><g transform="matrix(.013,0,0,-0.013,25.569,0)"><path id="g113-49" d="M241 635C89 635 35 457 35 312C35 153 89 -12 240 -12C390 -12 443 166 443 312C443 466 390 635 241 635ZM238 602C329 602 354 454 354 312C354 172 330 22 240 22C152 22 124 173 124 313S148 602 238 602Z"/></g><g transform="matrix(.013,0,0,-0.013,31.809,0)"><path id="g113-54" d="M153 550H386L412 615L406 623H120L82 318C104 327 142 338 184 338C294 338 347 275 347 187C347 112 305 39 221 39C160 39 119 71 97 89C88 97 80 96 71 90C59 80 50 67 49 57C48 45 52 36 66 23C80 9 123 -12 169 -12C221 -11 288 15 342 59C403 109 431 165 431 225C431 308 366 395 238 395C212 395 165 379 127 364L153 550Z"/></g></svg></span>), but not with affect measured by the HADS and PANAS (<span class="inline_break"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="18.973pt" style="vertical-align:-3.42938pt" id="M2" height="11.7782pt" version="1.1" viewBox="-0.0498162 -8.34882 18.973 11.7782"><g transform="matrix(.013,0,0,-0.013,0,0)"><use xlink:href="#g113-113"/></g><g transform="matrix(.013,0,0,-0.013,11.342,0)"><path id="g117-92" d="M512 230V281L75 514V456L453 256V254L75 55V-3L512 230Z"/></g></svg><span class="irelop"/><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="15.658pt" style="vertical-align:-3.42938pt" height="11.7782pt" version="1.1" viewBox="22.555183800000002 -8.34882 15.658 11.7782"><g transform="matrix(.013,0,0,-0.013,22.605,0)"><use xlink:href="#g113-47"/></g><g transform="matrix(.013,0,0,-0.013,25.569,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,31.809,0)"><use xlink:href="#g113-54"/></g></svg></span>). Multiple linear regression predicting prequit showed an association with smoking to alleviate addiction (<span class="inline_break"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="18.973pt" style="vertical-align:-3.42938pt" id="M3" height="11.7782pt" version="1.1" viewBox="-0.0498162 -8.34882 18.973 11.7782"><g transform="matrix(.013,0,0,-0.013,0,0)"><use xlink:href="#g113-113"/></g><g transform="matrix(.013,0,0,-0.013,11.342,0)"><use xlink:href="#g117-91"/></g></svg><span class="irelop"/><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="15.658pt" style="vertical-align:-3.42938pt" height="11.7782pt" version="1.1" viewBox="22.555183800000002 -8.34882 15.658 11.7782"><g transform="matrix(.013,0,0,-0.013,22.605,0)"><use xlink:href="#g113-47"/></g><g transform="matrix(.013,0,0,-0.013,25.569,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,31.809,0)"><use xlink:href="#g113-54"/></g></svg></span>). ANOVA showed that Caucasian participants reported greater rates of smoking compared to other races.<i> Conclusions</i>. The results suggest that behavioral smoking cessation interventions that focus on helping patients to manage tobacco-seeking behavior, rather than mood management interventions, could help cancer patients quit smoking.

Andrew Miele

Morgan Thompson

Nancy C. Jao

Ravi Kalhan

Frank Leone

Lee Hogarth

Brian Hitsman

Robert Schnoll

Cancer Patients Enrolled in a Smoking Cessation Clinical Trial: Characteristics and Correlates of Smoking Rate and Nicotine Dependence

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<p><em>Journal of Addiction</em> publishes original research articles and&nbsp;review articles&nbsp;related to all aspects of addiction.</p>


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Journal of Addiction publishes original research articles and review articles related to all aspects of addiction.

Journal of Addiction