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Exploring client messages in a therapist-guided internet intervention for alcohol use disorders – A content analysis

ABSTRACT:

Background

There is a growing interest in offering therapist-guided internet interventions for alcohol use disorders (AUD) in regular addiction services. Elucidating the therapeutic processes during these interventions may help improve clinical delivery. The aim of this paper was to investigate written messages from client to therapist in a therapist-guided internet intervention for AUD.

Methods

Data was extracted from the therapist-guided arm (n = 57) of a randomized trial of internet interventions for AUD. Qualitative content analysis was used to identify distinct categories of client behaviors in written messages to therapists. Coding was deductive (applying categories from past literature) as well as inductive (identifying new categories from the data). Subsequently, exploratory correlational and regression analyses were conducted to investigate whether identified client behaviors predicted module completion and drinking outcomes. Also, client questions posed in messages to therapists were categorized separately.

Results

Eleven distinct behavior categories were identified, of which the two most common were alliance (26.6% of total categorizations) and identifying patterns and problem behaviors (22.8%). Confrontational alliance rupture was the least common category (0.4%). One new behavior category was identified inductively – alcohol-related setback (4.1%). In the exploratory analyses, no categories consistently predicted module completion or drinking outcomes. Client questions were most commonly posed to improve understanding or use of program content or skills.

Discussion

The behavior categories, although not predictive of module completion or outcomes, may be of use for therapists, treatment developers and health care providers as a tool for understanding therapeutic processes in internet interventions for AUD. Highlights • Interest in internet interventions for alcohol use disorder is growing.• Content analysis was applied to messages from clients to therapists in a therapist-guided intervention.• Eleven distinct behavior categories were identified.• The most common client behavior category was alliance.• Categorizations may be of use for digital health care providers.

SUBMITTER: Kraepelien M

PROVIDER: S-EPMC8605073 | biostudies-literature |

REPOSITORIES: biostudies-literature

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