Substance Use and Misuse among Intellectually Disabled Persons

Substance Use and Misuse among Intellectually Disabled Persons - SumID

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

NL-OMON

Registry ID

NL-OMON33047

Enrollment

1000

Registered

2009-07-17

Start date

2009-09-01

Completion date

Unknown

Last updated

2024-05-06

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

gebruik van psychoactieve stoffen addiction Substance use

Interventions

None listed

Eligibility

Age

18 Years to 99 Years

Inclusion criteria

Inclusion criteria: - adults (18+) receiving care (sheltered living intensive or low intensity form, sheltered working, outreaching help, full inpatient care), by professional careproviders (selected from VGN network) - Willing and consenting to participate, and with consent of caregiver or family member

Exclusion criteria

Exclusion criteria: -

Design outcomes

Primary

Measure	Time frame
Validation study Validity of SUMID Self Report and Collateral Report Questionnaire: Sensitivity and specificity of the SUMID Self Report and Collateral Report for detection of substance use will be calculated for each substance (tobacco, cannabis, alcohol, cocaine), and for 2 reference periods (last month, recent use), against positive biomarkers (BAC, hairanalysis, urinalysis, plasteranalysis). Convergent validity between Self Report and Collateral Reports will be calculated using chi-square tests. Test-retest reliability will be assessed calculating kappas. Internal consistency for section 2 (knowledge of and attitudes towards substances) and section 4 (consequences of substance use and motivation to change) will be assessed aiming at a Cronbach*s alpha of at least .80. For dichotomous knowledge items the Kuder-Richardson-20 coefficient (Nunnally 1994) will be calculated. In order to establish construct validity of the knowledge, attitude and consequence scales factor analysis will be calculated. Relationships between knowledge, attitude and consequence subscales and substance use will be assessed by multiple logistic regression methods. Sociodemographic risk factors will be found by comparing sociodemographic differences between non-users, and users using Multivariate Analysis. ROC curves will specify optimal cut off values for the scores on knowledge, attitude and consequences, to differentiate between problematic users, users and non-users. Pearson correlations will be used to establish relations between knowledge, attitude, and consequences scales. ANOVA and GLM will be used to test whether the combined knowledge, attitude and consequence means differ for specific groups depending on for instance living and working arrangements, gender or age groups. Prevalence Study Population prevalence of substance use will be calculated from NISPA SUMID Self Report and Collateral Report Questionnaires. Data will be summarized by producing frequ	—

Measure

Time frame

Validation study Validity of SUMID Self Report and Collateral Report Questionnaire: Sensitivity and specificity of the SUMID Self Report and Collateral Report for detection of substance use will be calculated for each substance (tobacco, cannabis, alcohol, cocaine), and for 2 reference periods (last month, recent use), against positive biomarkers (BAC, hairanalysis, urinalysis, plasteranalysis). Convergent validity between Self Report and Collateral Reports will be calculated using chi-square tests. Test-retest reliability will be assessed calculating kappas. Internal consistency for section 2 (knowledge of and attitudes towards substances) and section 4 (consequences of substance use and motivation to change) will be assessed aiming at a Cronbach*s alpha of at least .80. For dichotomous knowledge items the Kuder-Richardson-20 coefficient (Nunnally 1994) will be calculated. In order to establish construct validity of the knowledge, attitude and consequence scales factor analysis will be calculated. Relationships between knowledge, attitude and consequence subscales and substance use will be assessed by multiple logistic regression methods. Sociodemographic risk factors will be found by comparing sociodemographic differences between non-users, and users using Multivariate Analysis. ROC curves will specify optimal cut off values for the scores on knowledge, attitude and consequences, to differentiate between problematic users, users and non-users. Pearson correlations will be used to establish relations between knowledge, attitude, and consequences scales. ANOVA and GLM will be used to test whether the combined knowledge, attitude and consequence means differ for specific groups depending on for instance living and working arrangements, gender or age groups. Prevalence Study Population prevalence of substance use will be calculated from NISPA SUMID Self Report and Collateral Report Questionnaires. Data will be summarized by producing frequ

—

Secondary

Measure	Time frame
n.a.	—

Countries

Netherlands

Outcome results