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Drug Dependence

Drug Dependence is a complex condition characterized by a strong, compulsive desire to use a substance, despite harmful consequences.
It involves physiological and psychological components, leading to tolerance, withdrawal symptoms, and continued use.
Effective treatment often requires a multifaceted approach, including behavioral therapies and medication management.
Reserach into optimizing protocols and identifying the best products for drug dependence can help advance treatment options and improve outcomes for those affected.
Leveraging AI-driven comparisons, as offered by PubCompare.ai, can help locate and evaluate the most promising protocols from literature, preprints, and patents to take drug dependance reserach to the next level.

Most cited protocols related to «Drug Dependence»

Diagnosing Mental Disorders in Adolescents

Cited 51 times

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Publication 2010

Abuse, Alcohol Adolescent Agoraphobia Alcoholic Intoxication, Chronic Anorexia Nervosa Anxiety Disorders Behavior Disorders Bulimia Nervosa Conduct Disorder Diagnosis Disorder, Attention Deficit-Hyperactivity Disorder, Binge-Eating Drug Abuse Drug Dependence Dysthymic Disorder Eating Disorders Emotions Interviewers Major Depressive Disorder Mental Disorders Mood Disorders Oppositional Defiant Disorder Panic Disorder Parent Phobia, Social Phobia, Specific Physical Examination Post-Traumatic Stress Disorder Problem Behavior Separation Anxiety Disorder Substance Use Disorders

Mortality Causes and Prevention Strategies

Cited 48 times

The mortality data were derived from the Inserm-CépiDc database for mainland France for the period 1997–2001. Overall there were 2,650,390 deaths. The commune of residence, which is systematically included in the death record, was used as the spatial location.
The underlying causes of death were analysed and classified using the 17 categories aggregated by Eurostat. An additional category, 'avoidable' causes linked to risk behaviours targeted by primary prevention [41 (link)], was defined for 'premature' deaths occurring before age 65 years only. This category consisted in causes of death related to smoking and alcohol consumption (lung, trachea and bronchus cancers (ICD10 Code: C32–C34), aerodigestive tract cancers (C00–C14), oesophagus cancer (C15), alcohol abuse (F10), chronic liver disease (K70, K73–K74)), drug dependence (F11), AIDS (B20–B24), transport accidents (V01–V99), suicides (X60–X84) and homicides (X85–Y09).

Rey G., Jougla E., Fouillet A, & Hémon D. (2009). Ecological association between a deprivation index and mortality in France over the period 1997 – 2001: variations with spatial scale, degree of urbanicity, age, gender and cause of death. BMC Public Health, 9, 33.

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Publication 2009

Abuse, Alcohol Accidents Acquired Immunodeficiency Syndrome Bronchogenic Carcinoma Disease, Chronic Drug Dependence Esophageal Cancer Liver Liver Diseases Lung Malignant Neoplasms Primary Prevention Trachea

Productivity and Health Care Utilization Questionnaire for Psychiatric Patients

Cited 46 times

The TiC-P is questionnaire designed for self-report in patients with a mental disorder. A translation in English of the questionnaire is available at
http://www.imta.nl[15 ]. The TiC-P is a generic questionnaire, meaning that the items are not related to a target disease. Distinguishing between healthcare consumption and production losses as a consequence of the target disease and comorbidity is difficult, especially in psychiatric disorders, as patients also may have physical symptoms that are connected to the psychiatric illness. Moreover, psychiatric comorbidity is a common occurrence in psychiatric illness.
Before the introduction of the TiC-P the questionnaires’ feasibility in daily practice was assessed by interviewing 20 respondents with a psychiatric disorder who were treated in a specialisedcentre for psychiatry. This resulted in a number of textual changes
[16 ].
The TiC-P consists of two parts, both can also be used separately. Additionally, a number of general questions may be added for collecting data on respondents’ demographic characteristics and co-morbidity.
The first part of the TiC-P includes 14 structured no/yes questions on relevant medical resource items each followed by a question on the volume of medical consumption (see Figure
1).
The questions include contacts within the mental healthcare sector (regional mental healthcare organisation, psychiatrist/psychologist or psychotherapist in private practices or outpatient hospital, institutional day-care treatment, Consultation Agency for Alcohol and Drug addiction (CAD), self-help group and contacts with general healthcare providers (general practitioner, paramedical and social worker, alternative practices, outpatients visits to medical specialists, hospital admission and contacts with an occupational practitioner) and the use of medication. The inclusion of questions related to different types of contacts in mental healthcare makes the TiC-P suitable for broad application, i.e. for various psychiatric disorders. Additionally, depending on the relevance for the target population the questionnaire allows adding or leaving out specific items of resource utilisation.
Part two consists of the Short Form-Health and Labour Questionnaire (SF-HLQ), a generic instrument to collect data on productivity losses due to health problems and is based on the HLQ
[17 (link)]. The SF-HLQ aims to measure absence from work and reduced efficiency of paid and unpaid work. Absence from work is measured by two questions related to short-term absence and long-term absence (< 2 weeks and > 2 weeks respectively ) from work, see Figure
2.
Additionally, three questions are included for measuring productivity losses due to reduced efficiency during paid work (see Figure
3).

Bouwmans C., De Jong K., Timman R., Zijlstra-Vlasveld M., Van der Feltz-Cornelis C., Tan S.S, & Hakkaart-van Roijen L. (2013). Feasibility, reliability and validity of a questionnaire on healthcare consumption and productivity loss in patients with a psychiatric disorder (TiC-P). BMC Health Services Research, 13, 217.

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Publication 2013

Day Care, Medical Drug Dependence Ethanol Generic Drugs Health Personnel Mental Disorders Mentally Ill Persons Outpatients Patients Pharmaceutical Preparations Physical Examination Psychiatrist Psychologist Psychotherapists Specialists Target Population Worker, Social

Genetic Basis of Substance Dependence

Cited 38 times

Our GWAS discovery samples (‘GCD sample’) included 2379 EA and 3318 AA subjects. A second identically ascertained GCD sample comprising 1746 EA and 803 AA subjects was used for replication. All subjects were recruited for studies of the genetics of drug (opioid or cocaine) or alcohol dependence.^{1 (link),2} The sample consisted of small nuclear families (SNFs) originally collected for linkage studies and unrelated individuals. Subjects (Table 1) gave written informed consent as approved by the institutional review board at each site, and certificates of confidentiality were obtained from NIDA and NIAAA. Subjects were administered the semi-structured assessment for drug dependence and alcoholism (SSADDA)^{16 (link)} to derive DSM-IV diagnoses¹⁷ of lifetime AD and other major psychiatric traits.
Discovery phase analyses also included publicly available (via application) GWAS data from SAGE (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000092.v1.p1), containing 1311 AA and 2750 EA unrelated individuals (Table 1). It is described in more detail in Supplementary Materials. A German sample of 1806 AD and 1978 control subjects was used for replication.^{9 (link)} Ordinal trait information was not available to us for these subjects, and the controls were not ascertained for exposure to alcohol and may include alcohol abusers.

Gelernter J., Kranzler H., Sherva R., Almasy L., Koesterer R., Smith A., Anton R., Preuss U., Ridinger M., Rujescu D., Wodarz N., Zill P., Zhao H, & Farrer L. (2013). Genome-wide association study of alcohol dependence: significant findings in African- and European-Americans including novel risk loci. Molecular psychiatry, 19(1), 41-49.

Publication 2013

Alcoholic Intoxication, Chronic Cocaine DNA Replication Drug Dependence Ethanol Ethics Committees, Research Genome-Wide Association Study N-nitrosoiminodiacetic acid Opioids

Longitudinal Assessment of Mental Disorders

Cited 30 times

The Dunedin Study longitudinally ascertains mental disorders using a strategy akin to experience sampling: Every 2 to 6 years, we interview participants about past-year symptoms. Past-year reports maximize reliability and validity because recall of symptoms over longer periods has been shown to be inaccurate. It is possible that past-year reports separated by 1 to 5 years miss episodes of mental disorder occurring only in gaps between assessments. We tested for this possibility by using life-history calendar interviews to ascertain indicators of mental disorder occurring in the gaps between assessments, including inpatient treatment, outpatient treatment, or spells taking prescribed psychiatric medication (indicators that are salient and recalled more reliably than individual symptoms). Life-history calendar data indicated that virtually all participants having a disorder consequential enough to be associated with treatment have been detected in our net of past-year diagnoses made at ages 18, 21, 26, 32, and 38. Specifically, we identified only 11 people who reported treatment but had not been captured in our net of diagnoses from ages 18 to 38 (many of whom had a brief postnatal depression).
Symptom counts for the examined disorders were assessed via private structured interviews using the Diagnostic Interview Schedule (Robins, Cottler, Bucholz, & Compton, 1995 ) at ages 18, 21, 26, 32, and 38. Interviewers are health professionals, not lay interviewers. We studied DSM-defined symptoms of the following disorders that were repeatedly assessed in our longitudinal study (see Table S1 in the Supplemental Material available online): alcohol dependence, cannabis dependence, dependence on hard drugs, tobacco dependence (assessed with the Fagerström Test for Nicotine Dependence; Heatherton, Kozlowski, Frecker, & Fagerström, 1991 (link)), conduct disorder, MDE, GAD, fears/phobias, obsessive-compulsive disorder (OCD), mania, and positive and negative schizophrenia symptoms. Ordinal measures represented the number of the 7 (e.g., mania and GAD) to 10 (e.g., alcohol dependence and cannabis dependence) observed DSM-defined symptoms associated with each disorder (see Table S1 in the Supplemental Material). Fears/phobias were assessed as the count of diagnoses for simple phobia, social phobia, agoraphobia, and panic disorder that a study member reported at each assessment. Symptoms were assessed without regard for hierarchical exclusionary rules to facilitate the examination of comorbidity. Of the 11 disorders, 4 were not assessed at every occasion, but each disorder was measured at least three times (see Fig. 1 for the structure of psychopathology models and see Table S1 in the Supplemental Material).
Elsewhere we have shown that the past-year prevalence rates of psychiatric disorders in the Dunedin cohort are similar to prevalence rates in nationwide surveys of the United States and New Zealand (Moffitt et al., 2010 (link)). Of the original 1,037 study members, we included 1.000 study members who had symptom count assessments for at least one age (871 study members had present symptom counts for all five assessment ages, 955 for four, 974 for three, and 989 for two). The 37 excluded study members comprised those who died or left the study before age 18 or who had such severe developmental disabilities that they could not be interviewed with the Diagnostic Interview Schedule.

Caspi A., Houts R.M., Belsky D.W., Goldman-Mellor S.J., Harrington H., Israel S., Meier M.H., Ramrakha S., Shalev I., Poulton R, & Moffitt T.E. (2014). The p Factor: One General Psychopathology Factor in the Structure of Psychiatric Disorders?. Clinical psychological science : a journal of the Association for Psychological Science, 2(2), 119-137.

Publication 2013

Agoraphobia Alcoholic Intoxication, Chronic Cannabis Dependence Care, Ambulatory Conduct Disorder Depression, Postpartum Developmental Disabilities Diagnosis Drug Dependence Fear Health Personnel Hospitalization Interviewers Mania Mental Disorders Nicotine Dependence Obsessive-Compulsive Disorder Panic Disorder Pharmaceutical Preparations Phobia, Social Phobia, Specific Phobias Robins Schizophrenia Symptom Assessment Tobacco Dependence

Most recents protocols related to «Drug Dependence»

Sofa Surfing: A Dangerous Gateway to Exclusion

Typically, women had repeatedly experienced several different types of homelessness. But sofa surfing was by far the most long lasting and repeatedly found. Women had wide networks which enabled them to sofa surf for considerable periods of time without exhausting their options. This was often linked with substance misuse and needing access to drugs “I was just sofa surfing. From drug house to drug house to drug house. Me drug addiction got worse and I looked terrible. And I met me baby’s dad through drugs… Met him quite early didn’t fancy him but it was just the drugs, I was there for the drugs (Gillian).
Underlining the importance of understanding sofa surfing as a gateway to exclusion many women detailed the inherent danger and vulnerability in needing to rely on others to find a place to stay:

You get to know people the wrong way sometimes. It’s really sad when you need, you know you’re doing a very dangerous thing... it also exposes the anger. Men who hate women. I always forget the word, misogynist. You become a needy woman, you meet a misogynist (Tracy).

Survival sex is understood as “the exchange of sex for material support” [20 (link)], and has previously found to be common amongst young homeless women [66 ]. Moore’s study, in Australia noted that issues of consent and coercion were obscured within this context [66 ]. The expectation of sex was hinted at by several women and explicitly expressed by Tracy:

I was couch surfing but there was many a night where I’d have to get out of there because they assume that means sex in bed and rock and roll, you know ... Because you owe something. And once you owe something, they can take anything. It’s dirty. It’s a really ugly, you know the word rape is um, is so misunderstood even as a victim of it because if you’re doing it for a place to stay, am I being raped? Or am I f****** him so I can have somewhere to sleep. You know what I mean? Excuse my language. It’s a horrendous place to be.

The routine violence and victimisation associated with sofa surfing is less well evidenced in the literature but well known by the women in this study. In particular sexual exploitation was understood to be prevalent: “I was thinking, “Shall I mention it [sexual exploitation] and I thought well I’m not going to be the only one am I?”(Sienna). That the women in this study were still sofa surfing despite being aware of the inherent dangers highlights the paucity of other options available to them.

McGrath J., Crossley S., Lhussier M, & Forster N. (2023). Social capital and women’s narratives of homelessness and multiple exclusion in northern England. International Journal for Equity in Health, 22, 41.

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Publication 2023

Anger BAD protein, human Brassica rapa Drug Dependence Drugs, Non-Prescription Infant Persons, Homeless Pharmaceutical Preparations Sleep Victimization Woman

Lifetime History of Mental Disorders

Classic mental health disorder is defined as a lifetime history of any of the following 22 diagnoses as indicated by administrative ICD‐9 codes: ADHD, adjustment disorder, alcohol, anxiety, bipolar, conduct/ODD, minor depression, MDD, eating disorders, non‐affective psychosis, organic mental disorders, other disorders, other impulse‐control disorders, personality disorders, sex disorders, sleep disorders, somatoform/dissociative disorders, traumatic stress, PTSD, drug‐induced mental illness, drug abuse without dependence, or drug dependence.

Dempsey C.L., Benedek D.M., Zuromski K.L., Nock M.K., Brent D.A., Ao J., Georg M.W., Haller K., Aliaga P.A., Heeringa S.G., Kessler R.C., Stein M.B, & Ursano R.J. (2023). Recent Stressful Experiences and Suicide Risk: Implications for Suicide Prevention and Intervention in U.S. Army Soldiers. Psychiatric Research and Clinical Practice, 5(1), 24-36.

Publication 2023

Adjustment Disorders Affective Disorders, Psychotic Anxiety Disorders Delirium, Dementia, Amnestic, Cognitive Disorders Diagnosis Disorder, Attention Deficit-Hyperactivity Disorder, Dissociative Disruptive, Impulse Control, and Conduct Disorders Drug Abuse Drug Dependence Eating Disorders Ethanol Mental Disorders Personality Disorders Pharmaceutical Preparations Physiological Sexual Disorders Post-Traumatic Stress Disorder Sleep Disorders

Shame and Guilt in Obsessive-Compulsive Disorder

A total of 62 participants (38 women and 24 men) were examined in this study. Of these, 31 patients fulfilled the criteria of OCD [ICD-10 F42.X: mean age 35.2 (SD = 10.7) years] and 31 subjects formed the healthy control group [mean age 39.1 (SD = 15.0) years]. A detailed description of the groups can be found in Table 1.Table 1

Sociodemographic and clinical characteristics

Trait	OCDN = 31	HCN = 31	p-value*
Age, mean (SD), years	38,7 (11,9)	39,6 (13,1)	n. s
Gender
Female n,	19 (61,3%)	19 (61,3%)	n. s
Male n,	12 (38,7%)	12 (38,7%)
Marital status
Single, n	17 (54,8%)	12(38,7%)
Married, n	9 (29,0%)	19 (61,3%)	p = 0.009
Divorced, n	5 (16,1%)	0
Current Partnership
- No	13 (41,9%)	7 (22,6%)	n. s
- Yes	18 (58,1%)	24 (77,4%)
Graduation
High school, n	25 (80,7%)	24 (77,4)
Junior high school, n	3 (9,7%)	5 (16,1%)	n. s
Low school., n	3 (9,7%)	2 (6,5%)
Occupational status
Current employment (Including be a student), n	22 (71,0%)	27 (87,1%)	n. s
No current Job,	9 (29,0%)	4 (12,9%)
Diagnosis (ICD-10)
F42.0, n	5 (16,1%)	/
F42.2, n	26 (83,9%)
Age of onset
mean (SD), years	23,2 (9,1)	/
Duration of illness
mean (SD), years	15,8 (10,8)	/

^*x²-Test/ t-Test; n. s. non-significant, OCD Obsessive–compulsive disorder, HC Healthy controls

All OCD patients were recruited and examined during their treatment at the Department of Psychiatry (LWL-University Hospital of the Medical Faculty of Ruhr-University Bochum, special outpatient clinic for OCDs). Examination of the healthy volunteers also took place at the LWL-University Hospital Bochum and recruitment was via notices and flyers.
Patients and healthy volunteers aged 18–67 years were included. Further inclusion criteria were a verbal IQ > 70, sufficient German language skills and the ability to give informed consent according to the Helsinki and ICH-GCP declarations. Exclusion criteria for the study were: severe somatic diseases; other mental diseases, such as reduced intelligence (ICD10 F70–F70.9), schizophrenia (ICD10 F20–F20.9) or organic brain disorders (ICD10 F06–F06.9, dependence on illegal drugs); acute suicidal tendencies or behaviour endangering others; and lack of informed consent to participate in the study.
Furthermore, psychopharmacotherapy was not an exclusion criterion for patients with OCD. In this respect, 96.8% of the patients (n = 30) received monotherapy, whereby antidepressants from the selective serotonin reuptake inhibitor group [e.g. sertraline (n = 21), escitalopram, paroxetine, fluoxetine] but also clomipramine (a tricyclic antidepressant) were predominantly used. Moreover, seven of the patients received a combination treatment (mainly a sedating antipsychotic medication, e.g. promethazine or quetiapine). At the time of inclusion in the study, 12 patients were receiving psychotherapeutic treatment (validation therapy: n = 9; deep psychology: n = 3). Only five of the patients (16.1%) with OCD had not received psychotherapy at the time of study inclusion, either currently or in the past. A detailed anamnesis was taken from all OCD patients and healthy volunteers in a semi-structured interview (duration 45–60 min). The psychometric characteristics, including shame and guilty proneness, were gathered using various questionnaires.
The study was approved by the local Ethics Committee (No. 20–6883) of the Medical Faculty of Ruhr-University Bochum.

Mavrogiorgou P., Becker S., Lee-Grimm S.I, & Juckel G. (2023). Embitterment and metacognition in obsessive–compulsive disorder. BMC Psychiatry, 23, 146.

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Publication 2023

Antidepressive Agents Antipsychotic Agents Brain Diseases Clomipramine Diagnosis Diploid Cell Drug Dependence Escitalopram Faculty, Medical Fluoxetine Guilt Healthy Volunteers Immunologic Memory Males Paroxetine Patients Promethazine Psychometrics Psychotherapy Psychotic Disorders Psychotropic Drugs Quetiapine Regional Ethics Committees Schizophrenia Selective Serotonin Reuptake Inhibitors Sertraline Shame Student Therapeutics Tricyclic Antidepressive Agents Woman

Methamphetamine Use Disorder and Brain Structural Changes

We recruited the study participants from the Compulsory Detoxification Center of Changsha Public Security Bureau in Changsha, Hunan, China, between October 2018 and October 2019. All the study subjects had used MA within the previous 12 months. We recruited two groups of participants – one with MCU and the other with MUD. According to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM‐5), MUD participants fulfilled at least 2 of 11 DSM-5 MUD diagnostic criteria, whereas MCU participants fulfilled 0 or 1 and could also control MA use. We assessed the participants using the Semi-Structured Assessment for Drug Dependence and Alcoholism (SSADDA), Chinese Version (Ma et al., 2021 (link)). The exclusion criteria of participants were as follows: 1) medical condition related to intestinal dysbacteriosis such as gastrointestinal disease, liver disease, or infection; 2) current neurological and psychiatric disorders not due to MA use; 3) antibiotics use in the previous three months; 4) other illicit substances used in the previous 12 months other than MA. The participants were given a complete explanation of the study before their invitation to participate. All participants signed written informed consent. The study was approved by the Ethics Committee of the Second Xiangya Hospital of Central South University.
Sixty-six participants (21 MCU and 45 MUD (42 males and 3 females)) were recruited for this study. None of the participants reported using antipsychotic medication or other prescription medications. We excluded the three female MUDs to avoid the confounding effect of sex and retained only the male participants in the subsequent investigation. To avoid the effects of age and obesity on GM, we conducted a propensity-matched analysis of the eligible participants by age and body mass index (BMI). To this end, 42 age- and BMI-matched participants (21 MCU and 21 MUD) were included in the current study.

He L., Yang B.Z., Ma Y.J., Wen L., Liu F., Zhang X.J, & Liu T.Q. (2023). Differences in clinical features and gut microbiota between individuals with methamphetamine casual use and methamphetamine use disorder. Frontiers in Cellular and Infection Microbiology, 13, 1103919.

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Publication 2023

Alcoholic Intoxication, Chronic Antibiotics Antipsychotic Agents Chinese Compulsive Behavior Diagnosis Drug Dependence Dysbacteriosis Ethics Committees, Clinical Females Gastrointestinal Diseases Index, Body Mass Infection Intestines Liver Diseases MA 12 Males Mental Disorders Metabolic Detoxication, Drug Obesity Prescription Drugs Secure resin cement

Amnestic Mild Cognitive Impairment Study

This study was ethically approved by the institutional review board at Shandong Provincial Hospital, and all participants provided written informed consent. Patients with aMCI enrolled in this study met the following criteria: (1) between 50 and 80 years of age; (2) fulfilling the clinical features proposed by the 2011 revised National Institute on Aging–Alzheimer's Association (NIA-AA) criteria for MCI (Albert et al., 2011 (link)) and current patients with aMCI (MCI with memory impairments); and (3) having a score of 20 or higher on the Minimum Mental State Examination (MMSE) for elementary school and >24 in the middle school and above group, with Clinical Dementia Rating (CDR) of 0.5. The exclusion criteria for participants included: (1) seizure disorders; (2) serious mental illness; (3) serious cerebrovascular diseases, traumatic brain injury, hydrocephalus, brain tumor, and white matter lesions (Fazekas ≥3); (4) alcohol or drug dependence; and (5) patients with MRI contraindications. The healthy controls were evaluated using the MMSE and CDR, and none of the controls had noticeable cognitive impairment. The diagnosis of aMCI was made by a neurologist with 8 years of experience. The MMSE and CDR evaluations were performed by a neuropsychologist with 5 years of experience blinded to the clinical information of all the participants. From December 2020 to March 2022, 20 patients with aMCI from the neurology outpatient clinic of Shandong Provincial Hospital in Jinan were recruited in our study. Twenty age- and gender-matched healthy controls (HCs) were recruited from the communities in Jinan. The patients' screening information is presented in the Supplementary Figure 1. All participants were right-handed. This is a cross-sectional study that followed the STROBE Guideline.

Chen X., Gong T., Chen T., Xu C., Li Y., Song Q., Lin L., Oeltzschner G., Edden R.A., Xia Z, & Wang G. (2023). Altered glutamate–glutamine and amide proton transfer-weighted values in the hippocampus of patients with amnestic mild cognitive impairment: A novel combined imaging diagnostic marker. Frontiers in Neuroscience, 17, 1089300.

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Publication 2023

Brain Neoplasms Cerebrovascular Disorders Diagnosis Disorders, Cognitive Drug Dependence Epilepsy Ethanol Ethics Committees, Research Gender Hydrocephalus Memory Deficits Mental Disorders Neurologists Patients Respiratory Diaphragm Traumatic Brain Injury White Matter

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What are the different types of drug dependence?

Drug dependence can take many forms, including dependence on opioids, stimulants, depressants, and other substances. Each type of drug dependence has its own unique physiological and psychological characteristics, leading to different withdrawal symptoms and treatment approaches. Understanding the specific type of drug dependence is crucial for developing an effective, personalized treatment plan.

How does drug dependence affect daily life?

Drug dependence can have a profound impact on an individual's daily life, leading to changes in behavior, mood, and physical health. Those struggling with drug dependence may experience difficulty maintaining relationships, performing at work or school, and engaging in hobbies and activities they once enjoyed. The compulsive nature of drug dependence can make it challenging to fulfill responsibilities and maintain a healthy lifestyle.

What are some common treatment options for drug dependence?

Effective treatment for drug dependence often requires a multifaceted approach, including behavioral therapies, medication management, and supportive care. Commonly used treatments include cognitive-behavioral therapy, contingency management, medication-assisted treatment (such as methadone or buprenorphine), and residential or outpatient rehabilitation programs. The specific treatment plan should be tailored to the individual's needs and the type of drug dependence they are experiencing.

How can PubCompare.ai help with drug dependence research?

PubCompare.ai is a powerful tool that can assist researchers in optimizing their protocols for drug dependence research. The platform allows you to efficiently screen the protocol literature, leveraging AI to pinpoint critical insights. By comparing the effectiveness of different protocols related to drug dependence, PubCompare.ai can help you identify the most promising approaches and make informed decisions about your research direction. This can lead to more reproducible and accurate results, ultimately advancing the understanding and treatment of drug dependence.

What are some common challenges faced in drug dependence treatment?

One of the key challenges in treating drug dependence is the high risk of relapse. Maintaining long-term sobriety can be dificult, as the brain's reward system becomes dysregulated, and cravings can persist even after detoxification. Additionally, co-occurring mental health conditions, such as depression or anxiety, can complicate treatment and require a comprehensive approach. Overcoming the social stigma associated with drug dependence and ensuring access to affordable, high-quality care are also ongoing challenges in the field.

More about "Drug Dependence"

Drug addiction, substance use disorder, and chemical dependency are all terms used to describe the complex condition of drug dependence.
This compulsive desire to use a substance, despite harmful consequences, involves both physiological and psychological components.
Individuals with drug dependence often develop tolerance, experience withdrawal symptoms, and continue using the substance even when it negatively impacts their lives.
Effective treatment for drug dependence often requires a multifaceted approach, including behavioral therapies and medication management.
Researchers are constantly working to optimize treatment protocols and identify the best products for managing drug dependence.
Techniques like the PURExpress transcription-translation coupled system, LeadProfilingScreen, and CompuSyn software can be valuable tools in this research process.
Leveraging AI-driven comparisons, as offered by PubCompare.ai, can help researchers locate and evaluate the most promising protocols from literature, preprints, and patents.
This can be particularly useful for advancing drug dependence research and improving outcomes for those affected.
By exploring PubCompare.ai, researchers can take their work on drug dependence to the next level, utilizing the latest technologies and insights to develop more effective treatment options.