Capturing goal content from free text in weight loss: an exploratory pilot on feasibility, reliability, and early outcomes

Understanding patients’ self-articulated weight-loss goals may support tailored weight-management interventions; however, reproducible methods to capture and classify free-text goal content are limited. This pilot study aimed to develop and preliminarily evaluate a laddering-informed free-text elicitation and classification protocol, and to explore its associations with motivational quality and short-term weight change. Adults with a body mass index ≥ 25 kg/m² enrolled in a 3-month digital behavioral weight-management program completed two free-text prompts. Responses were coded by two trained raters, using rules mapped to the Aspiration Index (AI) and the Goal Content for Weight Maintenance Scale (GCWMS). Inter-rater agreement was excellent (Cohen’s κ = 0.91 for both frameworks). The protocol yielded analyzable data. AI showed better operational fit than GCWMS, with fewer unclassified (“Other”) responses (2.1% vs. 19.1%). Differences in motivational quality across goal-content categories were small (partial η² = 0.005–0.032). In exploratory models, engagement was positively associated with weight loss, whereas autonomous motivation showed a negative association over the short observation period.