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Objective <p>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.</p> Results <p>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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月25日

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  • Tomomi Nagasawa,
  • Tsuyoshi Okuhara,
  • Yuriko Nishiie,
  • Hiroko Okada,
  • Takahiro Kiuchi

摘要

Objective

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.

Results

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.