Coding Client Language in Motivational Interviewing for HIV Medication Adherence Using Self-Determination Theory.
Coding Client Language in Motivational Interviewing for HIV Medication Adherence Using Self-Determination Theory.
复制标题
使用自我决定理论对艾滋病毒药物依从性动机访谈中的客户语言进行编码。
DOI:
10.1007/s12529-018-09766-z
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发表时间:
2019
影响因子:
2.7
通讯作者:
Evangeli,Michael
中科院分区:
文献类型:
--
作者:
Hogan,Ailbhe;Catley,Delwyn;Goggin,Kathy;Evangeli,Michael
BackgroundBoth motivational interviewing (MI) and self-determination theory (SDT) emphasise the importance of an individual’s autonomy. SDT proposes that motivation is on a continuum with autonomous motivation (AM) at the self-determined end of the spectrum. Whether client speech reflects AM is not coded in MI process studies, however, as it is subsumed under the broader category of change talk (CT). We aimed to code naturalistic speech within MI sessions for HIV medication (antiretroviral) adherence according to whether expressed motivation was autonomous or controlled. We then assessed relationships between adherence and both autonomous/controlled motivational speech (AM/CM) and CT.MethodsWe developed a new coding tool (the SDT coding system: SDTCS) to measure naturally occurring AM speech and CM speech expressed during an MI session targeting antiretroviral (ART) adherence with 62 adults living with HIV (16 female; mean age 40 years). We coded the same sessions using the motivational interviewing skills code (MISC) 2.5 and then examined relationships with on-time ART adherence.ResultsThe SDTCS was developed using a combined inductive and deductive approach. Adequate reliability estimates were achieved and the measure possessed good content validity. Naturally occurring AM speech had a stronger relationship to ART adherence in the week after the MI session than CM speech. There was also some evidence that the relationship between AM speech and adherence was stronger than between CT and adherence.ConclusionFuture refinement and extension of the SDTCS could allow for a more nuanced understanding of client motivational speech that is currently provided by existing coding tools.