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Alcoholism and Drug Addiction/Alkoholizm i Narkomania
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3/2022
vol. 35
 
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Original paper

The Hazardous Use Scale of psychoactive substances. A pilot study

Robert Modrzyński
1
,
Agnieszka Pisarska
2
,
Anna Maria Mańkowska
3

1.
Chair of Clinical Psychology and Neuropsychology, Institute of Psychology, Faculty of Education and Psychology, The Maria Curie-Skłodowska University, Lublin, Poland
2.
Chair of Educational Psychology and Psychological Diagnosis, Institute of Psychology, Faculty of Education and Psychology, The Maria Curie-Skłodowska University, Lublin, Poland
3.
Chair of Clinical Psychology, Institute of Psychology, Faculty of Social Sciences, The John Paul II Catholic University of Lublin, Poland
Alcohol Drug Addict 2022; 35 (3): 187-204
Online publish date: 2023/02/24
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- AiN_Mankowska.pdf  [0.48 MB]
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INTRODUCTION

The increasing availability and variety of alcohol and psychoactive substances contributes to the development of substance use disorders [1-3]. Research shows that a minimum of 28.9% of European Union citizens aged from 15 to 64 have used drugs at least once in their lifetime. The highest rates, i.e. 16.9%, involve a group of young adults aged 15-34 [4, 5]. In Poland, the percentage for this age group was 10.4% and 5.4% for the entire population [5]. Systematic grow of average alcohol consumption per capita is also observed [6]. Research conducted in Poland shows that approximately 14.2% of the population drinks hazardously including men being 22.3% and women 6.8% [7]. Although the use of non-alcohol psychoactive substances is much less common, drug use patterns are becoming more and more complex and the choice of substances is greater [5].
In view of the increasing number of people using alcohol and other psychoactive substances, including the growing number of addicts, there is a need to identify early symptoms that predict later development into full dependence. Formally, the term “hazardous use” has so far not been included in diagnostic classifications. Therefore there has been a tendency for researchers to capture “hazardous use” differently, referring it mainly to the amount of use of psychoactive substances, including alcohol.
Screening tools are developed in order to identify those at risk of dependence in the population. They are used to identify people who demonstrate alcohol and drug-use disorders. Among them, we can distinguish methods addressed to people who use hazardously, harmfully or are dependent. The tools take into account various symptoms among respondents, some of the presented questionnaires enable self-diagnosis [8-13].
In Poland, the most widespread screening tools for the identification of alcohol use disorders among adults are the Alcohol Use Disorders Identification Test (AUDIT) [14, 15], AUDIT-C (abbreviated version) [16, 17] and CAGE (acronym of words appearing in the questions: cut down, annoyed, guilty, eye-opener) [18-20].
At the initiative of WHO, further scales were constructed for detecting use patterns of psychoactive substances other than alcohol and problems related to their use. These include the ASSIST (Alcohol, Smoking, and Substance Involvement Screening Test) [21, 22] and the DAST-10 (Drug Abuse Screening Test) [23, 24].
The Drug Use Disorders Identification Test (DUDIT) [25], along with an expanded version of the DUDIT-E [26], was constructed with reference to the AUDIT as a complement to it by researchers at Karolinska Institutet.
The conceptualisation of the AUDIT and DUDIT was based on the ICD-10, and the most recent validation of these tests did not capture recent changes in the classification. The design of the Hazardous Use Scale (HUS) is the first method to be based on International Classification of Diseases 11 (ICD-11) criteria. In addition, previous screening methods refer only to alcohol or only to drugs, which may have fostered confusion in the early identification of substance use problems.
The need of developing new screening methods based on the latest standards is justified by changing patterns of alcohol or other psychoactive substance use and the accompanying changes in international classifications of diseases.
The ICD-11 currently operates in Poland introduced changes in the diagnostic process within the identification of dependence [27-29]. These changes resulted in a certain hierarchy in the group of disorders, leaving dependence and the harmful pattern of substance use (defined as harmful drinking in the ICD-10) mutually exclusive. The scope of dependence disorders has been divided into the categories current substance use with its immediate effects and disorders that relate to the health consequences of substance use. The hazardous use of substances, which is an important risk factor among dependence-related disorders, was added in the ICD-11 and has already been included in the DSM classification [29, 30]. In DSM-IV and DSM-5, the understanding of hazardous consumption of substances is limited to the use of substances in physically dangerous situations. In ICD-10, the term “hazardous use of substances” was removed at the final stage of formulation, and in ICD-11 it was reinstated as a health risk factor [29, 31-33]. Due to the changes introduced in the new classification (ICD-11) there are currently no screening methods on the Polish market that would indicate a potential group of hazardous substance use. The answer to this diagnostic gap is the Hazardous Use Scale (HUS).
Hazardous substance use
The HUS is a proprietary tool based on the concept of hazardous substance use included in the ICD-11. Hazardous substance use is defined there as a pattern of alcohol or other psychoactive substance use that, left without a medical or social intervention, may turn into a harmful pattern of use or dependence. It is therefore not a diagnosis of mental and behavioural disorders caused by using substances and merely draws attention to substance use behaviour. Behaviours related to hazardous substance use concern quantity and frequency of consumption of the substance take into consideration a person’s daily functioning and pay attention to the impact of substance use on the fulfilment of daily duties, interests or interpersonal relationships. The next factor is the harmful route of taking the substance, which concerns, for example, the use of the same needles many times or drinking alcohol from unknown sources. Another is the tendency for hazardous behaviour while intoxicated. These behaviours include working high off the ground, exposure to infections, fines related to consumption in public places, possession of substances in prohibited amounts, accidental sexual contacts and quarrels with relatives or driving under the influence [29, 31-33]. The duration of the substance’s action (usually short-term, immediate) and long-term both mental and physical health effects related to a person’s well-being or consequences suffered after consuming alcohol or other psychoactive substances are also important factors increasing hazardous substance use. Without proper diagnosis and intervention, these factors may lead to harmful consequences for physical and mental health of a person and their environment [17, 29, 31, 34, 35]. The proposed HUS will allow people working in the medical (especially in primary health care), social (e.g. workers of municipal consultation points) or school departments (educators and psychologists working with high school youth) to identify potential risks related to hazardous substance use and implement early interventions designed to stop the development of further consequences. Thus, the purpose of using HUS is to estimate the intensity of alcohol and other psychoactive substance use, which significantly increases the risk of harmful consequences for physical and mental health.
Characteristics of the Hazardous Use Scale
The HUS is a proprietary tool based on the concept of risky substance use according to the ICD-11. The HUS consists of 10 items related to frequency of substance use, harmful behaviour concerning substance use, the context of use and short-term or long-term effects either on health or on physical or mental functioning. As the ICD-11 does not provide for “subtypes” of dependence on a general level, the selection of items for the HUS was such that, although different manifestations of addiction were included, it was assumed that these different manifestations concerned one and the same problem.
A person completing the HUS assesses their own behaviour on a scale from 0 to 4, where 0 means no experience, 1 – occurs less than once a month, 2 – once a month, 3 – once a week and 4 – this behaviour occurs every day or almost every day. For each item, it is possible to receive from 0 to 4 points.
The HUS can be interpreted in quantitative and qualitative terms. The quantitative evaluation is carried out by counting the sum of points connected with each of the answers. The obtained result can be related to the cut-off points, which allow to determine the level of psychoactive substance use. The qualitative analysis, on the other hand, concerns the characteristics of behaviour and probable problems with functioning related to the fulfilment of a given criterion. Anex contains the HUS sheet.
For each question of the HUS, responses are scored in the order of 0-1-2-3-4. Scores are related to the following levels: low-risk use (0-6 points), risky use (7-15 points) and suspected dependence (15-40 points).
The aim of this article is to present the psychometric properties of the HUS, which measures the intensity of alcohol and other psychoactive substances use, conceptualised according to the latest International Classification of Diseases – ICD-11.

MATERIAL AND METHODS

This research used a self-questionnaire, a proprietary tool – the HUS as well as the AUDIT and the screening test that is DUDIT. The self-questionnaire consisted of 8 questions on age, gender, place of residence, marital status, children, education, employment, assessment of financial situation and non-medical use of discharged psychoactive substances over the course of their lives. The question on substance use was the only multiple-choice question.
The WHO AUDIT has been widely recognised as the “golden standard” test for assessing the presence of current alcohol use disorders. The AUDIT psychometric properties from many populations analysed for sociodemographic and cultural factors are very high: Cronbach’s α scores range from 0.80 to 0.94 and the time stability is r = 0.88. The AUDIT score is a good predictor of health and social problems related to alcohol consumption [36]. The tool was designed with intent to be used in many cultural circles. AUDIT has been translated into many languages including Polish. The Polish version of the AUDIT consists of 10 questions and is characterised by its high reliability (r = 0.91) [14, 15, 37, 38].
DUDIT is a screening test of 11 questions designed to identify drug use problems. It complements the AUDIT questionnaire conducted to identify alcohol use problems. DUDIT was developed in 2004 by Swedish specialists from the Karolinska Institutet [39]. The Polish version of the questionnaire is highly reliable and Cronbach’s α was 0.92. Receiver Operator Characteristic (ROC) analysis indicated a cut-off point of 7 with sensitivity of 0.929 and specificity of 0.974 [15, 25].
The authors used the indicated tests in their analyses to assess the validity and reliability of the presented scale. The study used the Polish versions of the AUDIT and DUDIT.
The HUS preparation procedure
In the first stage, the authors of the method, based on the literature and clinical experience, developed 30 statements related to hazardous substance use according to ICD-11.
In the second stage, 48 competent judges rated each claim on a scale from 1 to 6, where 1 meant that the item did not relate at all to the conceptualisation of the criterion and 6 meant it related fully. The competent judges were specialists in dependence psychotherapy. Thus 10 items were distinguished, obtaining the highest marks in terms of compliance with the adopted criterion description.
In the third stage, pilot studies were carried out using the HUS, AUDIT and DUDIT on a group of 70 adults with average age 30.85 (SD = 13.21, age range: 18-63) – 40 were outpatient addiction treatment patients, while the remaining 30 were the control group. The control group consisted of abstainers. The respondents were asked for comments on the formulated HUS items.
In the fourth stage, the comments were analysed and the HUS items were clarified in terms of content and language.
Stage five was the main survey. The sampling procedure mirrored the earlier pilot.
The respondents
The research was carried out in a group of 508 adults, 281 of whom were women (55.42%). Average respondents’ age was 30.8 years (SD = 12.32, range: 18-66 years). It was shown that women were statistically significantly younger (t = –9.56, p < 0.001), were more often part of younger age groups than men (up to 30 years of age) and less frequently in older ones (χ2 (5) = 79.98, p < 0.001). Almost 61% of the respondents were in the 18-30 age group, 15% in the 31-40 year-old group and 15% in the 41-50 year-old group while 9% were people over the age of 51. The respondents’ places of residence were mainly a city of over 100,000 inhabitants (35%) and villages (28.46%). Women lived in cities over 100,000 more often than men (χ2(5) = 11.31, p = 0.045). More than half of the respondents (57.25%) were married or in a partnership and 35% were divorced. Regarding marital status, women were less often married than men (χ2(4) = 48.73, p < 0.001) and preferred to remain in a partnership. Significant differences between the two genders also concern education and employment. Men more often had primary, lower secondary, vocational and higher vocational education (χ2(7) = 82.79, p < 0.001) than women and they were more often employed or on a pension/retirement pension. The vast majority of women were still in education (χ2(3) = 83.75, p < 0.001). Detailed data are presented in Tables I and II.
When asked about psychoactive substances, almost 98% of the respondents reported they drink alcohol, 37.7% use sedatives and 39.5% smoke marijuana. In the area of stimulants, men more often than women take cannabis (χ2 = 5.14, p < 0.001), cocaine (χ2 = 22.03, p < 0.001), amphetamines (χ2 = 22.47, p < 0.001), hallucinogens (χ2 = 15.77, p = 0.023) and opioids (χ2 = 21.43, p < 0.001). The distribution of psychoactive substances used by gender is presented in Figure 1.
While taking into account the gender differences visible in demographic data, all of the analyses for the HUS were performed separately for each gender.
The research procedure
Recruitment of respondents was carried out in two ways. The first was inviting people being treated for substance use disorders to participate in the project. The second method of recruitment assumed using the “snowball” method. After the survey was completed, the authors of the method asked the respondents to indicate more people who could complete the questionnaire. This sampling model was decided upon because of difficult access to a group like hazardous users. The starting point were people of different sociodemographic characteristics. The assumed exclusion criterion was the lack of consent to participate in the research or withdrawal of consent in the process of research.
The research was a one-off, fully anonymous event. Respondents from various backgrounds obtained information about its purpose and the possibility of cancelling their participation. After giving their consent, the respondents filled in the questionnaires. The study was conducted by the authors of the method. The test took up to 20 minutes to complete. The respondents completed the questionnaires at any time convenient for them with the opportunity to take breaks. The research was exploratory and did not bear any risk of experiencing adverse reactions among respondents, who also did not derive any material benefits from participating in the study. They could ask the researcher to present the result if they wished. Then the results were entered into the database and subjected to appropriate analyses.
Pearson’s r correlation coefficient was used in the statistical analysis for AUDIT and DUDIT. Cronbach’s α and inter-item reliability coefficients were used to measure scale reliability. Adjusted inter-item correlation coefficients and alpha at item removal were used to determine the discriminatory power of individual HUS items. Receiver Operating Characteristics (ROC) analysis, including determination of the area under the curve (AUC) were used to determine the diagnostic cut-offs of the HUS. Principal component factor analysis was used to examine the factor structure of the HUS. SPSS PS IMAGO 8.0 was used for statistical analyses.

RESULTS

After the research was completed, the construct validity was performed first. Exploratory factor analysis was conducted to discover the structure of the HUS. The obtained results clearly stated that the HUS is univariate. The Kaiser-Meyer-Olkin coefficient (KMO) was 0.95, which indicates a very high sampling adequacy for each variable. The research assumption was confirmed, according to which the included items of the HUS are correlated with each other and measure one factor of hazardous psychoactive substances use. The analysis detected only one factor with an eigen value of 6.73. Factor loadings were not provided because with only one factor revealed, the solution cannot be rotated and factor loadings cannot be calculated. To further ascertain whether the factor structure of the HUS is unidimensional, a confirmatory factor analysis (CFA) was conducted. The results confirmed an unifactor structure in three out of four indicators: comparative fit index (CFI) 0.93, Tucker-Lewis Index (TLI) 0.91, standardized root mean square residual (SRMR) 0.04 and slightly too high root mean square error of approximation (RMSEA) 0.15.
The HUS criterion validity
The criterion validity of the HUS was estimated by using the Pearson r-statistic and correlating the data obtained in the HUS with the results of the AUDIT and DUDIT questionnaires (Table III).
Correlations with AUDIT appear to be very high both in the group of women (r = 0.91) and men (r = 0.82). The strength of the relationship between the HUS and DUDIT scores fluctuates on the verge of a moderate correlation for both men (r = 0.47) and women (r = 0.52).
The HUS reliability
Reliability describes the accuracy with which the scale measures a phenomenon. From among many methods of assessing reliability, the authors chose the internal consistency measures of reliability analysis which examines the compliance of the respondents’ answers to particular questions of the tool. Assessment is performed by designating the so-called Cronbach’s α coefficient. It was assumed that the scale is reliable when it obtains Cronbach’s α properties above 0.70. The reliability was assumed high when the index exceeds 0.80. The tools used for validation show the following reliability: AUDIT = 0.94, DUDIT = 0.97 in the study sample.
The coefficients of internal reliability (Cronbach’s α) and indicators of split-half reliability (with Spearman-Brown correction) for the HUS shown by gender are presented in Table IV.
The obtained data show that the overall HUS split-half reliability index is 0.90 for women and 0.94 for men. The expected correlation of the randomly divided scale into two halves is confirmed.
The consistency of items included in the HUS, which was obtained by the Cronbach’s α indicator, is 0.94 for women and 0.94 for men. Items included in the composition of the univariate HUS are highly correlated with each other. This means that there is a high similarity between the answers. The respondents provided answers to particular questions in a similar way. It can therefore be assumed that items on the scale investigate the same phenomenon, which is hazardous substance use.
Then the discriminant power (α at item removal) for each question and the reliability of the scale after item removal (adjusted inter-item correlation coefficients) were calculated. The discriminant power of each question, calculated as the correlation of a given question with the overall score minus that question, is high. Detailed data is presented in Table V.
Cut-off points for initial diagnosis in HUS
ROC analyses were performed for the HUS score, according to the cut-off points for AUDIT (0-7 – low-risk drinking, 8-15 – hazardous alcohol consumption, 16-19 – harmful alcohol consumption, 20 and more – suspected dependence) and for DUDIT (0-6 – low risk or abstinence, 7-25 – existence of risk factors, 26 and more – possible development of dependence).
The cut-off points for HUS were located according to a compromise between sensitivity and specificity. The area under the curve (AUC) was calculated in each case in order to determine the goodness of pre-diagnosis together with analysis of statistical significance for the AUC (Table VI).
The area under the curve (AUC) indicate very good initial diagnosis differentiation according to AUDIT and slightly weaker but still satisfactory according to DUDIT.
The cut-off points were calculated according to the ROC curves modelled on the AUDIT and DUDIT tests. The measures of test validity were used, which are sensitivity, i.e. the ability to diagnose ill people and specificity to detect healthy people. According to the analysis of obtained results, the authors proposed the following cut-off points (Table VII). With the proposed cut-off points, the sensitivity of the scale is satisfactory in all cases. In the range of raw scores for HUS from 7 to 14 points, 81% (by AUDIT) and 91% (by DUDIT) of hazardous users were accurately detected. In case of suspicion of dependence (15-40 points), as many as 93% of people were correctly diagnosed.
The specificity of HUS, i.e. the ability to detect people who use low-risk substances, is high in relation to alcohol use (AUDIT) and slightly lower for the initial diagnosis of hazardous drug use, calculated according to the DUDIT. This means that among 100 people who drink alcohol or use drugs with a low risk of harm to health, 7 persons (according to AUDIT) and 35 (according to DUDIT) have received an initial diagnosis of hazardous use. Dependence refers to 8 (according to AUDIT) and 22 (according to DUDIT) persons.

DISCUSSION

The aim of the article was to present and describe the psychometric properties of the proprietary HUS designed to measure alcohol and other psychoactive substance hazardous use among adults. The tool was developed in response to the introduction of new diagnostic criteria in the ICD-11 connected with alcohol and other psychoactive substances use disorders. In order to adjust the preventive interventions, there is a need to identify early symptoms that predict their later development into a full dependence syndrome. The presented scale was developed because of the lack of screening tools in health practice, e.g. primary health care (PHC).
The HUS is a one-way tool designed to measure the intensity of alcohol and other psychoactive substances use. The development of the scale revealed that it is possible to identify hazardous users and those suspected of being dependent. However, it should be pointed out that the HUS does not differentiate alcohol use from other psychoactive substances. The detailed analyses, which were carried out throughout the research reveal that HUS has very good psychometric properties as a method. The adequacy measure for the selection of the analysis variables is satisfactory (KMO = 0.95). The criterion validity of the AUDIT is high for both women (r = 0.91) and men (r = 0.82). Regarding the DUDIT, the correlations are moderate in both groups (women: r = 0.52, men: r = 0.47). The HUS shows a better diagnostic index for alcohol use than for drug use. This result may have been influenced by the diversity of the group in terms of substance use. Most respondents admitted to using alcohol more often than other psychoactive substances.
Referring to the scale reliability, it can be confirmed that it is high for the group of women (r = 0.94) and men (r = 0.96), which makes possible to measure a given phenomenon accurately and repeatedly. Similar properties are reported by the AUDIT (r = 0.91) and DUDIT (r = 0.92), which indicates that the HUS is a tool of satisfactory reliability and can be compared with the methods commonly used so far. It is also worth noting that compared to other, less popular methods of measuring alcohol use intensity like the Alcohol Use Scale (r = 0.94), the HUS is relatively high [15, 25, 40].
The discriminant power and its high properties indicate a significant diagnostic value for the HUS and allow the tool to be used in a wide range of clinical practice, mainly by professionals in contact with people who abuse alcohol and other psychoactive substances. The proposed cut-off points were based on the AUDIT and DUDIT after taking into account the scale’s sensitivity and specificity. The results of analyses are satisfactory in terms of sensitivity. The HUS accurately indicted hazardous substance use in 81% (according to AUDIT) and 91% (according to DUDIT). The HUS also accurately indicated suspicion of alcohol or other psychoactive substances dependence in 93% referring to both the AUDIT and DUDIT. Analyses concerning the dimension of specificity assumed higher properties for the AUDIT than for the DUDIT. This means there is little risk of misdiagnosis in the initial diagnosis of drug users in terms of hazardous use of psychoactive substances. Therefore, diagnostic caution is recommended. This may be related to the diversity of the study group in terms of psychoactive substance use as individuals were more likely to choose alcohol as a psychoactive substance. However, it is worth adding that the HUS identifies alcohol-related problems more accurately than the CAGE questionnaire, which indicates only 53% of disorders for the elderly [41].
The strength of the presented scale is the enabling of initial diagnosis of hazardous users of alcohol and/or other psychoactive substances with a one tool. The conceptual separation of alcohol from other psychoactive substances in questions, corresponds to the common tendency of respondents to assign the name “psychoactive substance” to the so-called drugs and rather than alcohol in this category. Thus, the questions’ structure is transparent. The five-point response scale allows positioning subjects with different patterns of alcohol and psychoactive substance use on a continuum, which corresponds to the current trend to define use by assessing severity in the ICD-11 and DSM-5 classifications [31, 32, 42].
Research indicates that it is possible to avoid serious consequences related to dependence if people in the high-risk, hazardous users’ group are covered by appropriate support measures (i.e., for whom justified interventions have been undertaken). Patient treatment at the stage of hazardous use gives noticeable results and health benefits are possible compared to the no-treatment stage. In addition, treating hazardous drug users before dependence symptoms develop is more effective than treating drug addicts. This type of impact lowers financial and social costs connected with psychoactive substances dependence [31-33, 43-48]. The presented Hazardous Use Scale is a helpful screening tool for identifying patterns of hazardous alcohol or other psychoactive substances use.
Limitations. The presented scale also has its limitations. The scale’s conceptual framework is ICD-11, but the tools used to validate it were created based on the ICD-10. The authors are considering using additional methods in further studies to obtain more reliable cut-off points like semi-structured interviews based on ICD-11. The scale shows a much better diagnostic index for alcohol use than drug use. This may have to do with the specifics of the pilot study and the diversity of the study group in terms of specific substance use. Analysis of the characteristics of the study population also indicated uneven numbers in age groups. The most numerous group is made up of people aged 21-30. Young adults differ in terms of specifics of alcohol and other psychoactive substance use as they use much more often, which may have translated into HUS analyses [49]. In further studies, the authors will supplement the results with data from other age groups.
Another limitation of the present study as regards study of its factorial structure is that the Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were applied on the same sample.

CONCLUSIONS

The analysis of test results showed very good HUS statistical parameters: 1) very high internal reliability was obtained and 2) high correlations of HUS results with AUDIT and DUDIT were obtained, which proves high validity.
The analysis of the obtained results allows the use of HUS a wide range of clinical practice by professionals in contact with alcohol and other psychoactive substance abusers.
Conflict of interest/Konflikt interesów
None declared./Nie występuje.
Financial support/Finansowanie
Ministry of Health provided financial support for this research in the programme framework: Implementation of the alcohol dependence prevention programme and other psychoactive substances in adolescents and young adults in the Eastern Macroregion./Ministerstwo Zdrowia wsparło finansowo to badanie w ramach tematu: Wdrożenie programu profilaktyki uzależnień od alkoholu i innych substancji psychoaktywnych u młodzieży i młodych dorosłych na terenie makroregionu wschodniego; POWR.05.01.00-IP.05-00-015/19.
Ethics/Etyka
The research project was conducted with the approval of the research ethics committee of the John Paul II Catholic University of Lublin. The decision number is: KEBN_7/2022.
Badanie uzyskało zgodę Komisji Bioetycznej Katolickiego Uniwersytetu Lubelskiego Jana Pawła II w Lublinie, nr KEBN_7/2022.
The work described in this article has been carried out in accordance with the Code of Ethics of the World Medical Association (Declaration of Helsinki) on medical research involving human subjects, Uniform Requirements for manuscripts submitted to biomedical journals and the ethical principles defined in the Farmington Consensus of 1997.
Treści przedstawione w pracy są zgodne z zasadami Deklaracji Helsińskiej odnoszącymi się do badań z udziałem ludzi, ujednoliconymi wymaganiami dla czasopism biomedycznych oraz z zasadami etycznymi określonymi w Porozumieniu z Farmington w 1997 roku.
References/Piśmiennictwo
1. Komro KA, Maldonado-Molina MM, Tobler AL, Bonds JR, Muller KE. Effects of home access and availability of alcohol on young adolescents’ alcohol use. Addiction 2007; 102(10): 1597-608. DOI: 10.1111/j.1360-0443.2007.01941.x.
2. Villatoro Velazquez JA, Bustos Gamiño MN, Fregoso Ito DA, Bautista CF, López MDLG, Buenabad NGA, et al. Contextual factors associated with marijuana use in school population. Salud Mental 2017; 40(3): 93-102. DOI: 10.17711/SM.0185-3325.2017.012.
3. World Health Organization. Status report on alcohol consumption, harm and policy responses in 30 European countries 2019; 2019. https://www.euro.who.int/__data/assets/pdf_file/0019/411418/Alcohol-consumption-harm-policy-responses-30-European-countries-2019.pdf (Accessed: 07.07.2022).
4. Krajowe Biuro do Spraw Przeciwdziałania Narkomanii. Raport o stanie narkomanii w Polsce 2020. https://www.cinn.gov.pl/portal?id=105923 (Accessed: 04.02.2022).
5. Europejskie Centrum Monitorowania Narkotyków i Narkomanii [EMCDDA]. Europejski raport narkotykowy 2021: Tendencje i osiągnięcia. Luxemburg: Urząd Publikacji Unii Europejskiej; 2020. https://www.emcdda.europa.eu/system/files/publications/13838/2021.2256_PL_03.pdf (Accessed: 04.02.2022).
6. Statistic Poland. A picture of Poland. Statistics for SDGs 2018. https://sdg.gov.pl/o_sdg/#publ (Accessed: 07.07.2022).
7. Rowicka M, Postek S, Zin-Sędek M. Wzory konsumpcji alkoholu w Polsce. Raport z badań kwestionariuszowych 2020 r. Warszawa: PARPA; 2021. https://www.parpa.pl/images/wzory_konsumpcji_2020.pdf (Accessed: 04.02.2022).
8. Campbell EM, Strickland JC. Reliability and validity of the Brief DSM-5 Alcohol Use Disorder Diagnostic Assessment: a systematic replication in a crowdsourced sample. Addict Behav 2019; 92: 194-8. DOI: 10.1016/j.addbeh.2019.01.007.
9. Kelly SM, Gryczyński J, Mitchell SG, Kirk A, O’Grady KE, Schwartz RP. Validity of brief screening instrument for adolescent tobacco, alcohol, and drug use. Pediatrics 2014; 133(5): 819-26. DOI: 10.1542/peds.2013-2346.
10. Armenta BE, Cooper ML. The Rutgers Alcohol Problem Index: Measurement equivalence among college students in the US and Mexico. Psychol Assess 2019; 31(1): 1-14. DOI: 10.1037/pas0000608.
11. Touquet R, Brown A. PAT (2009) – Revisions to the Paddington Alcohol Test for early identification of alcohol misuse and brief advice to reduce Emergency Department re-attendance. Alcohol Alcohol 2009; 44(3): 284-6. DOI: 10.1093/alcalc/agp016.
12. Murad HAS, AlHarthi NA, Bakarman MA, Gazzaz ZJ. Development and validation of an Arabic version of the Drug Abuse Screening Test-10 (DAST-10) among Saudi drug abusers. J Psychoactive Drugs 2022; 54: 482-9. DOI: 10.1080/02791072.2021.2013580.
13. Zamboanga BL, Wickham RE, George AM, Olthuis JV, Pilatti A, Madson MB, et al. The Brief Young Adult Alcohol Consequences Questionnaire: A cross-country examination among university students in Australia, New Zealand, Canada, Argentina, and the United States. Drug Alcohol Depend 2021; 227(1): 108975. DOI: 10.1016/j.drugalcdep.2021.108975.
14. Babor TF, Higgins-Biddle JC, Saunders JB, Monteiro MG. AUDIT: The Alcohol Use Disorders Identification Test Guidelines for Use in Primary Care. Geneva: WHO; 2001. https://apps.who.int/iris/bitstream/handle/10665/67205/WHO_MSD_MSB_01.6a-eng.pdf?sequence=1&isAllowed=y (Accessed: 04.02.2022).
15. Klimkiewicz A, Jakubczyk A, Mach A, Abramowska M, Szczypiński J, Berent D, et al. Psychometric properties of the Polish version of the Alcohol Use Disorders Identification Test (AUDIT). Drug Alcohol Depend 2021; 218(1): 108427. DOI: 10.1016/j.drugalcdep.2020.108427.
16. Higgins-Biddle JC, Babor TF. A review of the Alcohol Use Disorders Identification Test (AUDIT), AUDIT-C, and USAUDIT for screening in the United States: Past issues and future directions. Am J Drug Alcohol Abuse 2018; 44(6): 578-86. DOI: 0.1080/00952990.2018.1456545.
17. Verhoog S, Dopmeijer JM, de Jonge JM, van der Heijde CM, Vonk P, Bovens RH, et al. The use of the alcohol use disorders identification test–Consumption as an indicator of hazardous alcohol use among university students. Eur Addict Res 2020; 26(1): 1-9. DOI: 10.1159/000503342.
18. Mayfield D, McLeod G, Hall P. The CAGE questionnaire: validation of a new alcoholism screening instrument. Am J Psychiatry 1974; 131(10): 1121-3. DOI: 10.1176/ajp.131.10.1121.
19. Ewing JA. Detecting alcoholism: The CAGE questionnaire. JAMA 1984; 252(14): 1905-7. DOI: 10.1001/jama.252.14.1905.
20. Morawski J, Świątkiewicz G. Polska wersja testu uzależnienia od alkoholu CAGE. Problemy Alkoholizmu 1985; 32(1): 9-10.
21. WHO ASSIST Working Group. The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST): development, reliability and feasibility. Addiction 2002; 97(9): 1183-94. DOI: 10.1046/j.1360-0443.2002.00185.x.
22. Humeniuk R, Ali R, Babor TF, Farrell M, Formigoni ML, Jittiwutikam J, et al. Validation of the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST). Addiction 2008; 103(6): 1039-7. DOI: 10.1111/j.1360-0443.2007.02114.x.
23. Skinner HA. The Drug Abuse Screening Test. Addict Behav 1982; 7(4): 363-71. DOI: 10.3389/fpsyt.2013.00179.
24. Yudko E, Lozhkina O, Fouts A. A comprehensive review of the psychometric properties of the Drug Abuse Screening Test. J Subst Abuse Treat 2007; 32(2): 189-98. DOI: 10.1016/j.jsat.2006.08.002.
25. Klimkiewicz A, Jakubczyk A, Mach A, Abramowska M, Serafin P, Szczypiński J, et al. Psychometric Properties of the Polish version of the Drug-Use Disorders Identification Test. Eur Addict Res 2020; 26(3): 131-40. DOI: 10.1159/000506156.
26. Berman AH, Palmstierna T, Källmén H, Bergman H. The self-report Drug Use Disorders Identification Test: Extended (DUDIT-E): reliability, validity, and motivational index. J Subst Abuse Treat 2007; 32(4): 357-69. DOI: 10.1016/j.jsat.2006.10.001.
27. Grant JE, Chamberlain SR. Expanding the definition of addiction: DSM-5 vs. ICD-11. CNS Spectrums 2016; 21(4): 300-3. DOI: 10.1017/S1092852916000183.
28. Gaebel W, Zielasek J, Reed GM. Mental and behavioural disorders in the ICD-11: concepts, methodologies, and current status. Psychiatria Polska 2017; 51(2): 169-95. DOI: 10.12740/PP/69660.
29. Modrzyński R. Zaburzenia związane z używaniem alkoholu – propozycje zmian w klasyfikacji ICD-11. Polskie Forum Psychologiczne 2019; 24(3): 324-33. DOI: 10.14656/PFP20190304.
30. Saunders JB. Substance use and addictive disorders in DSM-5 and ICD 10 and the draft ICD 11. Curr Opin Psychiatry 2017; 30(4): 227-37. DOI: 10.1097/YCO.0000000000000332.
31. Poznyak V, Reed GM, Medina-Mora ME. Aligning the ICD-11 classification of disorders due to substance use with global service needs. Epidemiol Psychiatr Sci 2018; 27(3): 212-8. DOI: 10.1017/S2045796017000622.
32. Rehm J, Heilig M, Gual A. ICD-11 for Alcohol Use Disorders: Not a Convincing Answer to the Challenges. Alcohol Clin Exp Res 2019; 43(11): 2296-300. DOI: 10.1111/acer.14182.
33. Saunders JB, Degenhardt L, Reed GM, Poznyak V. Alcohol use disorders in ICD-11: Past, present, and future. Alcohol Clin Exp Res 2019; 43(8): 1617-31. DOI: 10.1111/acer.14128.
34. Subramaniam M, Mahesh MV, Peh CX, Tan J, Fauziana R, Satghare P, et al. Hazardous alcohol use among patients with schizophrenia and depression. Alcohol 2017; 65: 63-9. DOI: 10.1016/j.alcohol.2017.07.008.
35. Wawrzyniak S. Rola współczesnej szkoły w zakresie profilaktyki uzależnień od substancji szkodliwych. Studia Edukacyjne 2020; 59: 151-72. DOI: 10.14746/se.2020.59.11.
36. Deady M. A Review of Screening, Assessment and Outcome Measures for Drug and Alcohol Settings. NADA 2009. https://www.drugsandalcohol.ie/18266/1/NADA_A_Review_of_Screening%2C_Assessment_and_Outcome_Measures_for_Drug_and_Alcohol_Settings.pdf (Accessed: 28.12.2021).
37. Moehring A, Rumpf HJ, Hapke U, Bischof G, John U, Meyer C. Diagnostic performance of the Alcohol Use Disorders Identification Test (AUDIT) in detecting DSM-5 alcohol use disorders in the general population. Drug Alcohol Depend 2019; 204: 107530. DOI: 10.1016/j.drugalcdep.2019.06.032.
38. Noorbakhsh S, Shams J, Faghihimohamadi M, Zahiroddin H, Hallgren M, Kallmen H. Psychometric properties of the Alcohol Use Disorders Identification Test (AUDIT) and prevalence of alcohol use among Iranian psychiatric outpatients. Subst Abuse Treat Prev Policy 2018; 13(1): 5. DOI: 10.1186/s13011-018-0141-x.
39. Berman AH, Bergman H, Palmstierna T, Schlyter F. Evaluation of the Drug Use Disorders Identification Test (DUDIT) in criminal justice and detoxification settings and in a Swedish population sample. Eur Addict Res 2005; 11(1): 22-31. DOI: 10.1159/000081413.
40. Poprawa R. Pomiar stopnia zaangażowania w używanie alkoholu. Badania właściwości psychometrycznych Skali Używania Alkoholu. In: Chodkiewicz J, Gąsior K (eds.). Wybrane zagadnienia z psychologii alkoholizmu. Warszawa: Difin; 2013, p. 13-41.
41. Suwała M, Gerstenkorn A. Rozpoznawanie problemów alkoholowych u osób w wieku powyżej 65 lat. Gerontologia Polska 2006; 14(4): 172-78.
42. Noël X, Brevers D, Bechara A. A triadic neurocognitive approach to addiction for clinical interventions. Front Psychiatry 2013; 4: 179. DOI: 10.3389/fpsyt.2013.00179.
43. Stewart SH, Connors GJ. Screening for Alcohol Problems, What Makes a Test Effective? Alcohol Res Health 2004; 28(1): 5-16.
44. Prokop M. Krótka interwencja. Instytut Psychologii Zdrowia Polskiego Towarzystwa Psychologicznego; 2005. https://psychologia.edu.pl/czytelnia/51-alkohol-i-nauka/961-krotka-interwencja.html (Accessed: 09.11.2021).
45. Pilowsky DJ, Wu LT. Screening for alcohol and drug use disorders among adults in primary care: a review. Subst Abuse Rehabil 2012; 3(1): 25-34. DOI: 10.2147/SAR.S30057.
46. Cherpitel CJ, Ye Y, Moskalewicz J, Świątkiewicz G. Does brief intervention work for heavy episodic drinking? A comparison of emergency department patients in two cultures. Alcohol Drug Addict 2015; 28(3): 145-62. DOI: 10.1016/j.alkona.2015.05.001. 
47. Carvalho AF, Heilig M, Perez A, Probst C, Rehm J. Zaburzenia związane z używaniem alkoholu. Lancet 2019; 394: 781-92. DOI: 10.1016/S0140-6736(19)31775-1.
48. King DL, Billieux J, Mueller K, Delfabbro PH. Clinical interventions for technology-based problems. In: Stein DJ, Fineberg NA, Chamberlain SR (eds.). Mental Health in a Digital World. London: Elsevier; 2022, p. 435-57. DOI: https://doi.org/10.1016/B978-0-12-822201-0.00016-2.
49. Centrum Badania Opinii Społecznej [CBOS]. Konsumpcja alkoholu w Polsce 2019. https://www.cbos.pl/SPISKOM.POL/2019/K_151_19.PDF (Accessed: 23.07.2022).
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