Correlates of Non-Medical Prescription Drug Misuse Among a Treatment-Seeking Population: A Comparison with Illicit Drug Users
Abstract
1. Introduction
2. Materials and Methods
2.1. Participants
2.2. Measurements
2.2.1. Socio Demographic Information (Gender, Ethnicity, Education, Occupation and Marital Status)
2.2.2. Diagnosis of Substance Use Disorder
2.2.3. Co-Morbidity
2.2.4. Severity of Substance Use: Addiction Severity Index-Lite (ASI-Lite)
2.2.5. Quality of Life: Personal Well-Being Index (PWI)
2.3. Procedure
2.4. Analyses
3. Results
3.1. Demographics
3.2. Severity of Addictions
3.3. Quality of Life
3.4. Co-Morbidities: Psychiatric and Physical
3.5. Predictors of Drug Use
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
Illegal Drugs | Prescription Drugs |
---|---|
Methamphetamine (Ice, Yaba, etc.) Heroin Cannabis Cocaine Ecstasy New Psychoactive Substances (NPS, synthetic cannabinoids, synthetic cathinone, etc.) * | CNS depressants Barbiturates Phenobarbital Benzodiazepines Alprazolam Lorazepam Diazepam Clonazepam Nitrazepam Medazolam Z-hypnotics Zopiclone Zolpidem Amitriptyline Antihistamines Chlorpheniramine Promethazine Diphenhydramine |
Stimulants Methylphenidate Modafinil Amphetamine | |
Centrally acting appetite suppressant Phentermine | |
Anticholinergics Benzhexol Benztropine | |
Opioid agonist Codeine Tramadol Morphine Oxycodone Hydromorphone Meperidine Methadone Buprenorphine | |
Over the counter Preparations Decongestants Ephedrine Pseudoephedrine Anti-diarrhea Loperamide Diphenoxylate Cough preparations Containing Codeine, Dextromethophan | |
Others Ketamine Steroids Propofol |
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PDUD Alone n (%) | IDUD Alone n (%) | PDUD+IDUD n (%) | |
---|---|---|---|
Gender | |||
Male | 243 (82.4) | 727 (89.6) | 234 (89) |
Female | 52 (17.6) | 84 (10.4) | 29 (11) |
Ethnicity | |||
Chinese | 164 (71.3) | 277 (41.3) | 128 (60.4) |
Malay | 42 (18.2) | 266 (39.6) | 61 (28.8) |
Indian | 16 (7) | 95 (14.2) | 17 (8) |
Others | 8 (3.5) | 33 (4.9) | 6 (2.8) |
Marital status | |||
Single | 111 (39.5) | 412 (53) | 106 (43.1) |
Married | 111 (39.5) | 226 (29) | 70 (28.5) |
Separated | 6 (2) | 16 (2.1) | 7 (2.8) |
Divorced | 50 (17.8) | 119 (15.3) | 62 (25.2) |
Widowed | 3 (1.1) | 5 (0.6) | 1 (0.41) |
Education | |||
No Formal Education | 3 (1.4) | 5 (0.8) | 2 (1) |
Primary | 57 (27.5) | 214 (33.5) | 74 (36.8) |
Secondary | 96 (46.4) | 297 (46.6) | 112 (55.7) |
* Tertiary | 51 (24.6) | 122 (19) | 13 (6.5) |
Occupation | |||
Clerical/Secretary | 2 (0.7) | 2 (0.3) | 2 (0.8) |
Labourer | 20 (7.2) | 67 (8.7) | 18 (7.2) |
Manager/Administrator | 9 (3.2) | 5 (0.6) | 2 (0.8) |
Others | 60 (21.5) | 211 (27.3) | 54 (21.5) |
Professional | 9 (3.2) | 2 (0.3) | 1 (0.4) |
Services/Sales | 17 (6.1) | 51 (6.6) | 6 (2.4) |
Technical/Vocational | 9 (3.2) | 35 (4.5) | 24 (9.6) |
Unemployed | 153 (54.8) | 399 (51.7) | 144 (57.4) |
Comorbidities | |||
Psychiatric comorbidity | 142 (48.1) | 157 (19.4) | 94 (35.7) |
Anxiety disorder | 20 (6.8) | 6 (0.7) | 6 (2.3) |
Mood disorder | 59 (20) | 83 (10.2) | 38 (14.5) |
Adjustment disorder | 31 (10.5) | 43 (5.3) | 17 (6.5) |
Physical co-morbidity | 63 (21.4) | 237 (29.2) | 65 (24.7) |
Mean (SD) | Mean (SD) | Mean (SD) | |
Personal wellbeing index | 48.52 (18.58) | 50.27 (21.27) | 46.53 (20.76) |
Addiction Severity index | 0.19 (0.13) | 0.21 (0.13) | 0.26 (0.15) |
Baseline Mean (SD) | 3 Months Mean (SD) | Repeated Measure ANOVA Test | ||||||
---|---|---|---|---|---|---|---|---|
PDUD Alone | IDUD Alone | PDUD+IDUD | PDUD Alone | IDUD Alone | PDUD+IDUD | F (df) | p | |
PWI | 48.5 (18.6) | 50.3 (21.3) | 46.5 (20.8) | 59.2 (17.5) | 58.4 (21.0) | 57.2 (21.5) | 0.95 (2) | 0.39 |
ASI | 0.19 (0.1) | 0.21 (0.1) | 0.25 (0.2) | 0.07 (0.1) | 0.06 (0.1) | 0.08 (0.1) | 0.04 (2) | 0.96 |
PDUD+IDUD vs. IDUD Alone | PDUD Alone vs. IDUD Alone | |||||
---|---|---|---|---|---|---|
Characteristic (Referent) | OR | p | 95% CI | OR | p | 95% CI |
Age | 1.03 | 0.003 * | (1.0,1.0) | 1 | 0.201 | (1.0, 1.0) |
Gender Male vs. Female | 1.2 | 0.651 | (0.6, 2.1) | 1.4 | 0.208 | (0.8, 2.4) |
Ethnicity (Chinese) | ||||||
Malay | 0.6 | 0.015 * | (0.4, 0.9) | 0.3 | 0.000 * | (0. 2, 0.4) |
Indian | 0.4 | 0.003 * | (0.2, 0.7) | 0.3 | 0.000 * | (0.2, 0.5) |
Others | 0.4 | 0.058 | (0.2, 1.0) | 0.4 | 0.026 * | (0.2, 0.9) |
Marital Status (Married) | ||||||
Single | 1.2 | 0.481 | (0.8, 1.8) | 0.4 | 0.000 * | (0.3, 0.7) |
Separated | 1.5 | 0.496 | (0.5, 4.6) | 0.8 | 0.676 | (0.3, 2.4) |
Divorced | 1.8 | 0.025 * | (1.1, 2.9) | 0.8 | 0.360 | (0.5, 1.3) |
Widowed | 1.4 | 0.794 | (0.1, 15.1) | 1. 5 | 0.713 | (0.2, 10.6) |
Education (Tertiary) | ||||||
No Formal Education | 0.7 | 0.788 | (0.1, 7.6) | 0.8 | 0.793 | (0.2, 4.2) |
Primary | 2.1 | 0.047 * | (1.0, 4.3) | 0.6 | 0.106 | (0.4, 1.1) |
Secondary | 2.9 | 0.002 * | (1.5, 5.7) | 0.8 | 0.411 | (0.5, 1.3) |
Occupation (Unemployed) | ||||||
Manager/Administrator | 2.5 | 0.347 | (0.4, 16.5) | 4.4 | 0.047 * | (1.0, 18.6) |
Professional | 2.4 | 0.485 | (0.2, 28.2) | 7.4 | 0.020 * | (1.4, 39.4) |
Technical/Vocational | 2.4 | 0.013 * | (1.2, 4.6) | 0.7 | 0.454 | (0.3, 1.7) |
Services/Sales | 0.3 | 0.048 * | (0.1, 1) | 0.8 | 0.539 | (0.3, 1.8) |
Labourer | 0.6 | 0.097 | (0.3, 1.1) | 0.9 | 0.723 | (0. 5, 1.7) |
Others | 0.8 | 0.205 | (0.5, 1.2) | 0.7 | 0.114 | (0. 5, 1.1) |
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PV, A.; Abdin, E.; Jun Wen, T.; Subramaniam, M.; Cheok, C.; Song, G. Correlates of Non-Medical Prescription Drug Misuse Among a Treatment-Seeking Population: A Comparison with Illicit Drug Users. Int. J. Environ. Res. Public Health 2018, 15, 1978. https://doi.org/10.3390/ijerph15091978
PV A, Abdin E, Jun Wen T, Subramaniam M, Cheok C, Song G. Correlates of Non-Medical Prescription Drug Misuse Among a Treatment-Seeking Population: A Comparison with Illicit Drug Users. International Journal of Environmental Research and Public Health. 2018; 15(9):1978. https://doi.org/10.3390/ijerph15091978
Chicago/Turabian StylePV, Asharani, Edimansyah Abdin, Tan Jun Wen, Mythily Subramaniam, Christopher Cheok, and Guo Song. 2018. "Correlates of Non-Medical Prescription Drug Misuse Among a Treatment-Seeking Population: A Comparison with Illicit Drug Users" International Journal of Environmental Research and Public Health 15, no. 9: 1978. https://doi.org/10.3390/ijerph15091978
APA StylePV, A., Abdin, E., Jun Wen, T., Subramaniam, M., Cheok, C., & Song, G. (2018). Correlates of Non-Medical Prescription Drug Misuse Among a Treatment-Seeking Population: A Comparison with Illicit Drug Users. International Journal of Environmental Research and Public Health, 15(9), 1978. https://doi.org/10.3390/ijerph15091978