Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

Keynote webinar | Spotlight on medication adherence

LIVE: Thursday 27th June 2024, 18:00-19:30 (CEST)
Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.
ADVANCED SEARCH
Log in
Top
Substance Abuse Treatment, Prevention, and Policy
Published in: Substance Abuse Treatment, Prevention, and Policy 1/2018

Open Access 01-12-2018 | Research

Development and psychometric properties of the methamphetamine decisional balance scale (METH-DBS) for young adults

Authors: Maryam Khazaee-Pool, Leila Jahangiry, Tahereh Pashaei, Farhad Ramezani-badr, Haidar Nadrian, Koen Ponnet

Published in: Substance Abuse Treatment, Prevention, and Policy | Issue 1/2018

Login to get access

Abstract

Background

Drug misuse is a major problem that has an extreme negative effect on people’s health. Methamphetamine (MA) is frequently used by young adults, despite its harmful consequences. The Transtheoretical Model (TTM) has been known to be very effective in explaining both the achievement and cessation of several health-related behaviors. Therefore, in this study, the TTM was used toward the domain of immoderate MA use among young adults. This study aimed to test the validity and reliability of a decisional balance scale for MA use in young adults.

Methods

A multi-phase scale development approach was used to develop the scale. First, 41 university students enrolled in a qualitative study that generated content for a primary set of a 40-item instrument. In order to produce a pre-final version of the instrument, face and content validity were calculated in the next step. The instrument validation was assessed with a sample of 250 university students. Then, the construct validity (exploratory and confirmatory), convergent validity, discriminate validity, internal consistency applying test-retest reliability, and Cronbach’s alpha of the scale were measured.

Results

Forty items were initially generated from the qualitative data. After content validity, this amount was reduced to 25 items. The exploratory factor analysis revealed four factors (self and other cons, coping and social pros) containing 21 items that jointly accounted for 55.24% of the observed variance. The confirmatory factor analysis indicated a model with appropriate fitness for the data. Cronbach’s alpha coefficient for the dimensions ranged from .74 to .87, and the Intraclass Correlation Coefficient (ICC) ranged from .83 to .91, which is within acceptable ranges.

Conclusion

The findings showed that the Methamphetamine Decisional Balance Scale is a valid and reliable scale that increases our ability to study motivational factors related to MA use among young adult. Consequently, the instrument could be applied in both practice and future studies.
Appendix
Available only for authorised users
Literature
1.
2.
Chauhan H, Killinger BA, Miller CV, Moszczynska A. Single and binge methamphetamine administrations have different effects on the levels of dopamine D2 autoreceptor and dopamine transporter in rat striatum. Int J Mol Sci. 2014;15(4):5884–906.CrossRefPubMedCentral
3.
United Nations Office on Drugs and Crime (UNODC). World Drug Report, vol. 2015. Vienna: United Nations; 2015.
4.
Marshall JF, O'Dell SJ. Methamphetamine influences on brain and behavior: unsafe at any speed? Trends Neurosci. 2012;35(9):536–45.CrossRefPubMedCentral
5.
Brackins T, Brahm NC, Kissack JC. Treatments for methamphetamine abuse: a literature review for the clinician. J Pharm Pract. 2011;24(6):541–50.CrossRefPubMedCentral
6.
Sobieraj JC, Kim A, Fannon MJ, Mandyam CD. Chronic wheel running-induced reduction of extinction and reinstatement of methamphetamine seeking in methamphetamine dependent rats is associated with reduced number of periaqueductal gray dopamine neurons. Brain Struct Funct. 2016;221(1):261–76.CrossRefPubMedCentral
7.
Norberg MM, Kezelman S, Lim-Howe N. Primary prevention of cannabis use: a systematic review of randomized controlled trials. PloS one. 2013;11(8):e53187.CrossRefPubMedCentral
8.
Glasner-Edwards S, Mooney LJ, Marinelli-Casey P, Hillhouse M, Ang A, Rawson RA. Methamphetamine treatment project corporate authors. Psychopathology in methamphetamine-dependent adults 3 years after treatment. Drug Alcohol Rev. 2010;29(1):12–20.CrossRefPubMedCentral
9.
McKetin R, Lubman DI, Najman JM, Dawe S, Butterworth P, Baker AL. Does methamphetamine use increase violent behaviour? Evidence from a prospective longitudinal study. Addiction. 2014;109(5):798–806.CrossRefPubMedCentral
10.
Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. 2006;3(2):77–101.CrossRef
11.
Karrari P, Mehrpour O, Balali-Mood M. Iranian crystal: a misunderstanding of the crystal-meth. J Res Med Sci. 2012 Feb;17(2):203–4.PubMedPubMedCentral
12.
Shariatirad S, Maarefvand M, Ekhtiari H. Emergence of a methamphetamine crisis in Iran. Drug Alcohol Rev. 2013;32(2):223–4.CrossRef
13.
Ishaak F, de Vries NK, van der Wolf K. Design of study without drugs--a Surinamese school-based drug-prevention program for adolescents. BMC Public Health. 2015;15:1046.CrossRefPubMedCentral
14.
Faggiano F, Minozzi S, Versino E, Buscemi D. Universal school-based prevention for illicit drug use. Cochrane Database Syst Rev. 2014;12:CD003020.
15.
Porath-Waller AJ, Beasley E, Beirness DJ. A meta-analytic review of school-based prevention for cannabis use. Health Educ Behav. 2010;37(5):709–23.CrossRef
16.
Janis IL, Mann L. Decision making: a psychological analysis of conflict, choice, and commitment. 1st ed. New York: Free Press; 1977.
17.
Apodaca TR, Longabaugh R. Mechanisms of change in motivational interviewing: a review and preliminary evaluation of the evidence. Addiction. 2009;104(5):705–15.CrossRefPubMedCentral
18.
Prochaska JO, Velicer WF. The transtheoretical model of health behavior change. Am J Health Promot. 1997;12(1):38–48.CrossRef
19.
Prochaska JO. A stage paradigm for integrating clinical and public health approaches to smoking cessation. Addict Behav. 1996;21(6):721–32.CrossRef
20.
Girma E, Assefa T, Deribew A. Cigarette smokers' intention to quit smoking in Dire Dawa town Ethiopia: an assessment using the Transtheoretical model. BMC Public Health. 2010;10:320.CrossRefPubMedCentral
21.
Khazaee-Pool M, Pashaei T, Ponnet K, Jafari F, Alizadeh R. Correction to: decisional balance inventory (DBI) adolescent form for smoking: psychometric properties of the Persian version. BMC Public Health. 2017;17(1):919.CrossRefPubMedCentral
22.
Velicer WF, DiClemente CC, Prochaska JO, Brandenburg N. Decisional balance measure for assessing and predicting smoking status. J Pers Soc Psychol. 1985;48(5):1279–89.CrossRefPubMedCentral
23.
Lea T, Kolstee J, Lambert S, Ness R, Hannan S, Holt M. Methamphetamine treatment outcomes among gay men attending a LGBTI-specific treatment service in Sydney, Australia. PLoS One. 2017;12(2):e0172560.CrossRefPubMedCentral
24.
Braun V, Clarke V. What can “thematic analysis” offer health and wellbeing researchers? Int J Qual Stud Health Well-being. 2014;9:26152.CrossRefPubMedCentral
25.
Khazaee-Pool M, Majlessi F, Montazeri A, Pashaei T, Gholami A, Ponnet K. Development and psychometric testing of a new instrument to measure factors influencing women's breast cancer prevention behaviors (ASSISTS). BMC Womens Health. 2016;16:40.CrossRefPubMedCentral
26.
Waltz CF, Bausell BR. Nursing research: design statistics and computer analysis. First ed. Davis FA; 1981.
27.
Waltz CF, Strickland OL, Lenz ER. Measurement in nursing and health research. 4rd ed. New York: Springer; 2005. 
28.
Polit DF, Beck CT. The content validity index: are you sure you know what's being reported? Critique and recommendations. Res Nurs Health. 2006;29(5):489–97.CrossRefPubMedCentral
29.
Lawshe CH. A quantitative approach to content validity. Pers Psychol. 1975;28(4):563–75.CrossRef
30.
Khazaee-Pool M, Pashaei T, Ponnet K, Jafari F, Alizadeh R. Decisional balance inventory (DBI) adolescent form for smoking: psychometric properties of the Persian version. BMC Public Health. 2017;17(1):507.CrossRefPubMedCentral
31.
Khazaee-Pool M, Arefi Z, Roshani D, Pashaei T. Development and psychometric properties of a questionnaire to measure drug users' attitudes toward methadone maintenance treatment (DUAMMT) in Iran. BMC Public Health. 2017;17(1):906.CrossRefPubMedCentral
32.
Lacasse Y, Godbout C, Sériès F. Health-related quality of life in obstructive sleep apnoea. Eur Respir J. 2002;19(3):499–503.CrossRef
33.
Pallonen UE, Prochaska JO, Velicer WF, Prokhorov AV, Smith NF. Stages of acquisition and cessation for adolescent smoking: an empirical integration. Addict Behav. 1998;23(3):303–24.CrossRef
34.
Grant JS, Davis LL. Selection and use of content experts for instrument development. Res Nurs Health. 1997;20(3):269–74.CrossRef
35.
McCoach DB, Gable RK, Madura JP. Instrument development in the affective domain. New York, NY: Springer 2013;10:978–971.CrossRef
36.
Ferguson E, Cox T. Exploratory factor analysis: a users’ guide. Int J Sel Assess. 1993;1:84–94.CrossRef
37.
Norris M, Lecavalier L. Evaluating the use of exploratory factor analysis in developmental disability psychological research. J Autism Dev Disord. 2010;40(1):8–20.CrossRef
38.
Harrington D. Confirmatory factor analysis. 2nd ed. New York: Oxford University Press; 2009.
39.
Kline RB. Principles and practice of structural equation modeling. 3rd ed. New York: Guilford publications; 1998.
40.
Schumacker RE, Lomax RG. A beginner's guide to structural equation modeling. 3rd ed. New York, NY: Routledge; 2010.
41.
Nunnally J, Bernstein I. Psychometric theory. 3rd ed. New York: MacGraw-Hill; 1994.
42.
Fayers PM, Machin D. Quality of life: the assessment, analysis and interpretation of patient-reported outcomes. 2nd ed: Wiley; 2013.
43.
Cronbach LJ. Coefficient alpha and the internal structure of tests. Psychometrika. 1951;16(3):297–334.CrossRef
44.
Munro BH. Statistical methods for health care research. 5th ed. Philadelphia: Wolters Kluwer health/Lippincott Williams & Wilkins Publisher; 1986.
45.
Corp I. IBM SPSS statistics for windows, version 22.0. Armonk, NY: IBM Corp. 2013.
46.
Arbuckle J. SPSS Amos (version 22.0) [computer program]. Chicago, IL: SPSS. 2006.
47.
Berry T, Naylor PJ, Wharf-Higgins J. Stages of change in adolescents: an examination of self-efficacy, decisional balance, and reasons for relapse. J Adolesc Health. 2005;37(6):452–9.CrossRefPubMedCentral
48.
Kelly BC, Liu T, Yang XY, Zhang G, Hao W, Wang J. Perceived risk of methamphetamine among Chinese methamphetamine users. Int J Drug Policy. 2014;25(6):1076–83.CrossRefPubMedCentral
49.
Noar SM, Laforge RG, Maddock JE, Wood MD. Rethinking positive and negative aspects of alcohol use: suggestions from a comparison of alcohol expectancies and decisional balance. J Stud Alcohol. 2003;64(1):60–9.CrossRefPubMedCentral
50.
51.
Hendershot CS, Witkiewitz K, George WH, Marlatt GA. Relapse prevention for addictive behaviors. Subst Abuse Treat Prev Policy. 2011;6:17.CrossRefPubMedCentral
Metadata
Title
Development and psychometric properties of the methamphetamine decisional balance scale (METH-DBS) for young adults
Authors
Maryam Khazaee-Pool
Leila Jahangiry
Tahereh Pashaei
Farhad Ramezani-badr
Haidar Nadrian
Koen Ponnet
Publication date
01-12-2018
Publisher
BioMed Central
Published in
Substance Abuse Treatment, Prevention, and Policy / Issue 1/2018
Electronic ISSN: 1747-597X
DOI
https://doi.org/10.1186/s13011-018-0175-0

Other articles of this Issue 1/2018

Substance Abuse Treatment, Prevention, and Policy 1/2018 Go to the issue

Research

Psychometric properties of the Alcohol Use Disorders Identification Test (AUDIT) and prevalence of alcohol use among Iranian psychiatric outpatients

Research

Narrating the journey of sustained recovery from substance use disorder

Research

Pharmacological neuroenhancement and the ability to recover from stress – a representative cross-sectional survey among the German population

Research

Strategies to control HIV and HCV in methadone maintenance treatment in Guangdong Province, China: a system dynamic modeling study

Research

Perceived driving safety and estimated blood alcohol concentration (BAC) the morning after drinking amongst young Australians attending a music festival: a cross-sectional survey

Research

“Freshman’s week”: characteristics associated with participation and experiencing adverse effects