Substance use, sleep and intervention design: insights from qualitative data.

Background: Alcohol and other drug use is associated with poor sleep quality and quantity, but there is limited qualitative research exploring substance users' experiences of sleep and few psychosocial sleep interventions for them. Aim: To inform the development of psychosocial interventions to improve sleep amongst people reporting drug/alcohol problems. Method: Qualitative data were collected during a sleep survey. Of the 549 drug/alcohol users completing the survey, 188 (34%) provided additional information about their sleep using a free text box. Responses were analysed via Iterative Categorisation. Findings were reviewed with reference to the Behaviour Change Wheel (BCW). Results: All data were categorised inductively under five headings: (i) sleep quality; (ii) nature of sleep problems; (iii) sleep and substances; (iv) factors improving sleep quality; (v) factors undermining sleep quality. Substance use undermined sleep, but poor sleep often persisted after substance use had ceased. Sleep problems were diverse; as were the causes of, and strategies for dealing with, those problems. Causes and strategies had biological, psychological, social and environmental roots. Conclusions: The BCW facilitated the identification of intervention components that might improve the sleep of people who use substances. These components relate to education, training, enablement, modelling, service provision, guidelines and environment.

Development and early validation of a patient-reported outcome measure to assess sleep amongst people experiencing problems with alcohol or other drugs.

Study Objectives: To develop a patient-reported outcome measure to assess sleep amongst people experiencing problems with alcohol or other drugs. Methods: Item development included secondary analyses of qualitative interviews with drug or alcohol users in residential treatment, a review of validated sleep measures, focus groups with drug or alcohol users in residential treatment, and feedback from drug or alcohol users recruited from community and residential settings. An initial version of the measure was completed by 549 current and former drug or alcohol users (442 in person and 107 online). Analyses comprised classical test theory methods, exploratory and confirmatory factor analysis, measurement invariance assessment, and item response theory (IRT). Results: The initial measure (30 items) had good content and face validity and was named the Substance Use Sleep Scale (SUSS) by addiction service users. After seven items were removed due to low item-factor loadings, two factors were retained and labeled: "Mind and Body Sleep Problems" (14 items) and "Substance-Related Sleep Problems" (nine items). Measurement invariance was confirmed with respect to gender, age, and administration format. IRT (information) and classical test theory (internal consistency and stability) indicated measure reliability. Standard parametric and nonparametric techniques supported convergent and discriminant validity. Conclusions: SUSS is an easy-to-complete patient-reported outcome measure of sleep for people with drug or alcohol problems. It can be used by those concerned about their own sleep, and by treatment providers and researchers seeking to better understand, assess, and potentially treat sleep difficulties amongst this population. Further validity testing with larger and more diverse samples is now required.

DEVELOPMENT AND VALIDATION OF 'SURE': A PATIENT REPORTED OUTCOME MEASURE (PROM) FOR RECOVERY FROM DRUG AND ALCOHOL DEPENDENCE.

BACKGROUND: Patient Reported Outcome Measures (PROMs) assess health status and health-related quality of life from the patient/service user perspective. Our study aimed to: i. develop a PROM for recovery from drug and alcohol dependence that has good face and content validity, acceptability and usability for people in recovery; ii. evaluate the psychometric properties and factorial structure of the new PROM ('SURE'). METHODS: Item development included Delphi groups, focus groups, and service user feedback on draft versions of the new measure. A 30-item beta version was completed by 575 service users (461 in person [IP] and 114 online [OL]). Analyses comprised rating scale evaluation, assessment of psychometric properties, factorial structure, and differential item functioning. RESULTS: The beta measure had good face and content validity. Nine items were removed due to low stability, low factor loading, low construct validity or high complexity. The remaining 21 items were re-scaled (Rasch model analyses). Exploratory and confirmatory factor analyses revealed 5 factors: substance use, material resources, outlook on life, self-care, and relationships. The MIMIC model indicated 95% metric invariance across the IP and OL samples, and 100% metric invariance for gender. Internal consistency and test-retest reliability were granted. The 5 factors correlated positively with the corresponding WHOQOL-BREF and ARC subscales and score differences between participant sub-groups confirmed discriminative validity. CONCLUSION: 'SURE' is a psychometrically valid, quick and easy-to-complete outcome measure, developed with unprecedented input from people in recovery. It can be used alongside, or instead of, existing outcome tools.

Personal support networks, social capital, and risk of relapse among individuals treated for substance use issues.

BACKGROUND: The success of treatment for substance use issues varies with personal and social factors, including the composition and structure of the individual's personal support network. This paper describes the personal support networks and social capital of a sample of Italian adults after long-term residential therapeutic treatment for substance use issues, and analyses network correlates of post-treatment substance use (relapse). METHODS: Using a social network analysis approach, data were obtained from structured interviews (90-120 min long) with 80 former clients of a large non-governmental therapeutic treatment agency in Italy providing voluntary residential treatments and rehabilitation services for substance use issues. Participants had concluded the program at least six months prior. Data were collected on socio-demographic variables, addiction history, current drug use status (drug-free or relapsed), and the composition and structure of personal support networks. Factors related to risk of relapse were assessed using bivariate and multivariate logistic regression models. RESULTS: A main goal of this study was to identify differences between the support network profiles of drug free and relapsed participants. Drug free participants had larger, less dense, more heterogeneous and reciprocal support networks, and more brokerage social capital than relapsed participants. Additionally, a lower risk of relapse was associated with higher socio-economic status, being married/cohabiting, and having network members with higher socio-economic status, who have greater occupational heterogeneity, and reciprocate support. CONCLUSIONS: Post-treatment relapse was found to be negatively associated with the socioeconomic status and occupational heterogeneity of ego's support network, reciprocity in the ties between ego and network members, and a support network in which the members are relatively loosely connected with one another (i.e., ego possesses "brokerage social capital"). These findings suggest the incorporation into therapeutic programming of interventions that address those aspects of clients' personal support networks.