C28. Severity indicators in drug users followed by nurses on a medication-based program

C28. Severity indicators in drug users followed by nurses on a medication-based program

C28. Severity indicators in drug users followed by nurses on a medication-based program

Learner category:

• Intermediate Level

Learning objectives:

• Participants will be aware of the most important consequences severity indicators on a medication based user`s.
• Participants will be aware the most important factor that nurses must attend to help patients to face the drug addiction severity.

Abstract

Severity indicators in drug users followed by nurses on a medication-based program Problem Users of medication-based programs, followed up in nursing consultation, are getting older, with more comorbidities, using different substances, and remain on program for many years(1). Specific indicators of substance addiction consequences (SAC) emerge to which nurses should evaluate at the consultation. Objectives To determine the most severe SAC indicators found on medication-based program users. To determine factors that improve self-management. Methods Cross-sectional, observational, quantitative study. Convenience sampling (n=162). SAC Scale(2) were used. Results Average age 46.96, mostly men, single, unemployed, living on family and social support, some without any profession. They were in different programs: 68.6% on methadone, Alcohol Aversive 26.4% and Buprenorphine 4.4%. They are using different drugs with different impact and had different comorbidities. About SAC, 43.2% users are on severe level. Decreasing order of severity indicators: “Anxiety”, “difficulty in maintaining a job”, “sadness”, “difficulty in maintaining financially” and “problems in family relationships”. Face the different programs there was no difference on SAC outcomes. The main differences were because of using cannabis, cocaine, and having mood disorders, psychotic disorders, HBV and HCV. Conclusions Most severe consequences are related to family relationships and psychological distress. The participants with most severe status was expected to experience a situation of greater social exclusion, more drug use, less family support, more unemployment, older(3-4), however, between the two groups there was homogeneity. Factors that can contribute to better self-management are related with comorbidities management, family support and no drug use.

Author(s)

Paulo Seabra

Post-Doc Researcher, Nursing School of Lisbon; Research and Development Nursing Unit (UI&DE); NursID, CINTESIS – Center for Health Technology and Services Research

Paulo Rosário Carvalho Seabra. Completed PhD in Nursing in 2015 by Universidade Católica Portuguesa, Master in Nursing in 2009 by Universidade Católica Portuguesa, Nursing Bachelor in 1992 by Escola Superior de Enfermagem Calouste Gulbenkian de Lisboa. Is Assistant Teacher in Escola Superior de Enfermagem de Lisboa. Published 28 articles in journals. Organized 4 event(s). Participated in 19 event(s). Supervised 12 MSc dissertation(s). Has received 7 awards and/or honors. Participates and/or participated as Principal investigator in 2 project(s), Researcher in 3 project(s) and Technical development in 1 project(s). Works in the area(s) of Medical and Health Sciences with emphasis on Nursing. In their professional activities interacted with 104 collaborator(s) co-authorship of scientific papers.

Rui Sequeira

RN, Specialist MHN Specialized Technical Treatment Unit of Barreiro, Division of Intervention in Additive Behaviors and Dependencies (DICAD)

Specialist MHN

Ana Sequeira

MSc, RN, Specialist CHN Specialized Technical Treatment Unit of Barreiro, Division of Intervention in Additive Behaviors and Dependencies (DICAD).

Specialist CHN

Carlos Sequeira

PhD, MSc, Rn, Specialist MHN Nursing School of Oporto; NursID, CINTESIS – Center for Health Technology and Services Research

Specialist MHN Coordenator of NursID, CINTESIS, FMUP

Paula Amaral

RN Specialized Technical Treatment Unit of Barreiro, Division of Intervention in Additive Behaviors and Dependencies (DICAD)

RN