139
Views
16
CrossRef citations to date
0
Altmetric
ORIGINAL ARTICLES

Prediction of adherence to antiretroviral therapy: can patients’ gender play some role? An Italian pilot study

, , , , , & show all
Pages 571-575 | Received 20 Aug 2007, Published online: 16 May 2008
 

Abstract

Recent literature has shown that adherence to HAART is a multi-faceted phenomenon, which involves both behavioural and psychological features. Therefore, the results obtained so far, though promising, have not yet unambiguously identified the factors that could predict non-adherence. Since any support for strengthening the adherence should take into account the HIV+ patients’ perception of both their state of health and their relational style, this study tried to identify some psychological characteristics involved in the adherence phenomenon. A self-administered battery of tests including the Attachment Style Questionnaire (ASQ) and the Multidimensional Health Locus of Control Form-C (MHLC-C) was administered to an Italian sample. Results showed significant gender differences between non-adherent and adherent subjects. Specifically, the psychological profile of non-adherent males seemed focused less on relational aspects and perceived relevance of physicians and of ‘significant other people’, whilst that of non-adherent females seemed more ‘relationshiporiented’. This study means to encourage clinicians to plan specific, gender-focused support for enhancing adherence.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 464.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.