Joanneke E L VanDerNagel1, Marion Kiewik2, Marike van Dijk3, Robert Didden4, Hubert P L M Korzilius5, Job van der Palen6, Jan K Buitelaar7, Donald R A Uges8, Remco A Koster8, Cor A J de Jong9. 1. Nijmegen Institute for Scientist-Practitioners in Addiction, Radboud University, P.O. Box 6909, 6503 GK Nijmegen, The Netherlands; Tactus Addiction Treatment, Raiffeisenstraat 75, 7514 AM Enschede, The Netherlands; Aveleijn, Grotestraat 260, 7622 GW Borne, The Netherlands. Electronic address: j.vandernagel@tactus.nl. 2. Nijmegen Institute for Scientist-Practitioners in Addiction, Radboud University, P.O. Box 6909, 6503 GK Nijmegen, The Netherlands; Aveleijn, Grotestraat 260, 7622 GW Borne, The Netherlands. 3. Nijmegen Institute for Scientist-Practitioners in Addiction, Radboud University, P.O. Box 6909, 6503 GK Nijmegen, The Netherlands; Tactus Addiction Treatment, Raiffeisenstraat 75, 7514 AM Enschede, The Netherlands. 4. Behavioural Science Institute, Radboud University, P.O. Box 9104, 6500 HE Nijmegen, The Netherlands; Trajectum, P.O. Box 40012, 8004 DA Zwolle, The Netherlands. 5. Institute for Management Research, Radboud University, Thomas van Aquinostraat 5, 6525 GD Nijmegen, The Netherlands. 6. Department of Research Methodology, Measurement and Data Analysis, Faculty of Behavioral Sciences, University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands; Medical School Twente, Medisch Spectrum Twente, Ariënsplein 1, 7511 JX Enschede, The Netherlands. 7. Department of Cognitive Neuroscience, Radboud University Medical Centre, P.O. Box 9101 (204), 6500HB Nijmegen, The Netherlands. 8. University of Groningen, University Medical Center Groningen, Department of Clinical Pharmacy and Pharmacology, Clinical Pharmaceutical and Toxicological Laboratory, P.O. Box 30.001, 9700 RB Groningen, University of Groningen, The Netherlands. 9. Nijmegen Institute for Scientist-Practitioners in Addiction, Radboud University, P.O. Box 6909, 6503 GK Nijmegen, The Netherlands; Behavioural Science Institute, Radboud University, P.O. Box 9104, 6500 HE Nijmegen, The Netherlands.
Abstract
BACKGROUND AND AIMS: Individuals with mild or borderline intellectual disability (MBID) are at risk of substance use (SU). At present, it is unclear which strategy is the best for assessing SU in individuals with MBID. This study compares three strategies, namely self-report, collateral-report, and biomarker analysis. METHODS AND PROCEDURES: In a sample of 112 participants with MBID from six Dutch facilities providing care to individuals with intellectual disabilities, willingness to participate, SU rates, and agreement between the three strategies were explored. The Substance use and misuse in Intellectual Disability - Questionnaire (SumID-Q; self-report) assesses lifetime use, use in the previous month, and recent use of tobacco, alcohol, cannabis, and stimulants. The Substance use and misuse in Intellectual Disability - Collateral-report questionnaire (SumID-CR; collateral-report) assesses staff members' report of participants' SU over the same reference periods as the SumID-Q. Biomarkers for SU, such as cotinine (metabolite of nicotine), ethanol, tetrahydrocannabinol (THC), and its metabolite THCCOOH, benzoylecgonine (metabolite of cocaine), and amphetamines were assessed in urine, hair, and sweat patches. RESULTS: Willingness to provide biomarker samples was significantly lower compared to willingness to complete the SumID-Q (p<0.001). Most participants reported smoking, drinking alcohol, and using cannabis at least once in their lives, and about a fifth had ever used stimulants. Collateralreported lifetime use was significantly lower. However, self-reported past month and recent SU rates did not differ significantly from the rates from collateral-reports or biomarkers, with the exception of lower alcohol use rates found in biomarker analysis. The agreement between self-report and biomarker analysis was substantial (kappas 0.60-0.89), except for alcohol use (kappa 0.06). Disagreement between SumID-Q and biomarkers concerned mainly over-reporting of the SumID-Q. The agreement between SumID-CR and biomarker analysis was moderate to substantial (kappas 0.48 - 0.88), again with the exception of alcohol (kappa 0.02). CONCLUSIONS AND IMPLICATIONS: In this study, the three strategies that were used to assess SU in individuals with MBID differed significantly in participation rates, but not in SU rates. Several explanations for the better-than-expected performance of self- and collateral-reports are presented. We conclude that for individuals with MBID, self-report combined with collateralreport can be used to assess current SU, and this combination may contribute to collaborative, early intervention efforts to reduce SU and its related harms in this vulnerable group.
BACKGROUND AND AIMS: Individuals with mild or borderline intellectual disability (MBID) are at risk of substance use (SU). At present, it is unclear which strategy is the best for assessing SU in individuals with MBID. This study compares three strategies, namely self-report, collateral-report, and biomarker analysis. METHODS AND PROCEDURES: In a sample of 112 participants with MBID from six Dutch facilities providing care to individuals with intellectual disabilities, willingness to participate, SU rates, and agreement between the three strategies were explored. The Substance use and misuse in Intellectual Disability - Questionnaire (SumID-Q; self-report) assesses lifetime use, use in the previous month, and recent use of tobacco, alcohol, cannabis, and stimulants. The Substance use and misuse in Intellectual Disability - Collateral-report questionnaire (SumID-CR; collateral-report) assesses staff members' report of participants' SU over the same reference periods as the SumID-Q. Biomarkers for SU, such as cotinine (metabolite of nicotine), ethanol, tetrahydrocannabinol (THC), and its metabolite THCCOOH, benzoylecgonine (metabolite of cocaine), and amphetamines were assessed in urine, hair, and sweat patches. RESULTS: Willingness to provide biomarker samples was significantly lower compared to willingness to complete the SumID-Q (p<0.001). Most participants reported smoking, drinking alcohol, and using cannabis at least once in their lives, and about a fifth had ever used stimulants. Collateralreported lifetime use was significantly lower. However, self-reported past month and recent SU rates did not differ significantly from the rates from collateral-reports or biomarkers, with the exception of lower alcohol use rates found in biomarker analysis. The agreement between self-report and biomarker analysis was substantial (kappas 0.60-0.89), except for alcohol use (kappa 0.06). Disagreement between SumID-Q and biomarkers concerned mainly over-reporting of the SumID-Q. The agreement between SumID-CR and biomarker analysis was moderate to substantial (kappas 0.48 - 0.88), again with the exception of alcohol (kappa 0.02). CONCLUSIONS AND IMPLICATIONS: In this study, the three strategies that were used to assess SU in individuals with MBID differed significantly in participation rates, but not in SU rates. Several explanations for the better-than-expected performance of self- and collateral-reports are presented. We conclude that for individuals with MBID, self-report combined with collateralreport can be used to assess current SU, and this combination may contribute to collaborative, early intervention efforts to reduce SU and its related harms in this vulnerable group.
Authors: Sharon L Nichols; Sean Brummel; Kathleen M Malee; Claude A Mellins; Anna-Barbara Moscicki; Renee Smith; Anai M Cuadra; Kendall Bryant; Cheryl Anne Boyce; Katherine K Tassiopoulos Journal: AIDS Behav Date: 2021-02-22