Primary keyword: qualitative analysis of hyperphagia. Researchers studying eating behaviours in rare genetic conditions face measurement gaps: questionnaires can miss severity that expert-led interviews reveal. The 2026 mixed-methods study of adults with Bardet-Biedl Syndrome (BBS) offers a clear example of this measurement gap and a practical model for integrating interviews with structured tools to produce defensible severity ratings.
Key Takeaways
According to the European Journal of Endocrinology abstract deposited on 18 August 2026, expert-led interviews classified far more adults with Bardet-Biedl Syndrome as having severe hyperphagia than a 14-item self-report questionnaire.
- Sample: Mossman et al., 2026 analysed 39 adult patients with BBS and obesity in a non-interventional cross-sectional study deposited 18 August 2026.
- Interview result: Mossman et al., 2026 reported that 9 of 13 interviewed participants (69%) were rated as having severe hyperphagia in August 2026.
- Questionnaire discordance: Mossman et al., 2026 found only 8% of the full sample were classified as severe by questionnaire in 2026, and 92% (12/13) of interviewed patients were assigned a higher severity level via interviews than by questionnaire.
- Conclusion: Mossman et al., 2026 explicitly state there is "substantial underreporting with self-reported questionnaires, " supporting the addition of expert-led interviews to better capture true burden.
What Happened and How the Study Worked
What happened: Mossman et al., 2026 conducted a mixed-methods cross-sectional sub-analysis to assess hyperphagia severity in adults with Bardet-Biedl Syndrome in the United Kingdom.
Mossman et al., 2026 enrolled 39 adults with BBS and obesity, excluding patients with BMI <30 kg/m2 or prior/current setmelanotide treatment, and deposited the abstract on 18 August 2026.
Mossman et al., 2026 used a 14-item hyperphagia questionnaire for all 39 participants and conducted semi-structured follow-up interviews with a subset of 13 participants to provide contextualised assessment.
Mossman et al., 2026 report that interview transcripts were systematically coded by a qualitative researcher and jointly reviewed with a BBS clinical expert to assign severity ratings, a method intended to address known limitations of self-report in this population.
Definition quoted in the study: Mossman et al., 2026 describe hyperphagia as an "insatiable feeling of hunger, persistent food-seeking behaviours and abnormal food intake, " and they used interviews to capture behavioural and social context not present in questionnaire responses.
Findings Snapshot
| Date | Metric | Value | Implication |
|---|---|---|---|
| 18 August 2026 | Total participants | 39 adults with BBS and obesity | Sample basis for questionnaire prevalence estimates |
| 18 August 2026 | Interview subset | 13 participants | Provided contextualised clinical ratings beyond self-report |
| 18 August 2026 | Interview-rated severe | 9/13 (69%) | Majority classified as severe when assessed via interview |
| 18 August 2026 | Questionnaire-rated severe/moderate/mild | 8% severe, 51% moderate, 41% mild | Questionnaire produced far lower severe prevalence |
| 18 August 2026 | Cross-method discordance | 12/13 (92%) rated higher severity via interview | Strong evidence of questionnaire underestimation |
Implications for Qualitative Researchers
Implications for qualitative researchers: Mossman et al., 2026 show that integrating expert-led interviews with questionnaires materially changes severity estimates and should inform study design in BBS and similar conditions.
Mossman et al., 2026 demonstrate three operational decisions researchers should consider: recruit for an interview subsample to validate self-reports, code interviews with clinical expert input to assign clinically meaningful severity labels, and explicitly adjust prevalence estimates when relying solely on questionnaires.
Mossman et al., 2026 also identify practical constraints: cognitive differences, stigma, and the disability paradox can depress self-report scores, so qualitative context is essential for accurate measurement.
How Evidano Helps: from Interviews to Accurate Severity Ratings
Problem: Questionnaires underreport severity
Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.
Solution: Use Evidano to ingest interview transcripts and questionnaire responses together to create unified thematic and cross-segment analyses, reducing the risk of underestimating severity.
Feature link: Learn more about relevant capabilities on the Evidano Features page.
Problem: Manual coding is slow and inconsistent
Solution: Evidano accelerates coding with AI-assisted thematic and hierarchical code generation, enabling a qualitative researcher to focus on clinical adjudication rather than repetitive tagging.
Practical outcome: Rapid, reproducible coding lets teams iterate on severity definitions and produce the expert-reviewed ratings Mossman et al., 2026 used.
Problem: Integrating interview context with numeric questionnaires
Solution: Evidano supports side-by-side analyses of free text and structured data, producing co-occurrence networks and cross-segment frequency reports that clarify when interviews diverge from questionnaires.
Practical outcome: Researchers can quantify discordance like the 92% higher-severity shift reported by Mossman et al., 2026 and present evidence-based adjustments for prevalence claims.
FAQ: qualitative analysis of hyperphagia
Why did interviews find more severe hyperphagia than questionnaires in the 2026 study?
Direct answer: Expert-led interviews captured behavioural and contextual detail that questionnaires missed.
Supporting detail: Mossman et al., 2026 report that interview coding with clinical review reclassified 9/13 (69%) as severe versus 8% by questionnaire, and they attribute this gap to factors such as stigma, cognitive differences, and the disability paradox affecting self-report.
How should I design a mixed-methods study of hyperphagia in rare disease?
Direct answer: Combine a structured questionnaire for breadth with purposive interviews for depth, and use clinical adjudication to assign severity.
Supporting detail: Mossman et al., 2026 implemented a 14-item questionnaire for 39 participants and semi-structured interviews for a 13-person subset, then used joint qualitative coding with a clinical expert to produce robust severity ratings.
Can AI tools reliably assist coding of interview transcripts for severity ratings?
Direct answer: AI tools can speed and standardise initial coding, but human clinical review remains essential for final severity assignment.
Supporting detail: Product workflows such as those offered by Evidano combine AI-generated thematic coding with expert review to replicate the mixed-method rigour used by Mossman et al., 2026 while reducing manual workload.
Is the 2026 finding generalisable beyond the UK BBS sample?
Direct answer: The Mossman et al., 2026 sample is small and context-specific, so generalisation requires caution.
Supporting detail: Mossman et al., 2026 analysed 39 adults with BBS and obesity and interviewed 13; these sample sizes support strong internal conclusions about measurement discordance but external validation in larger, more diverse samples is needed.
Conclusion & Next Steps
Mossman et al., 2026 provide concrete evidence that expert-led interviews reveal substantially more severe hyperphagia in adults with Bardet-Biedl Syndrome than questionnaires alone.
Researchers designing studies of eating behaviour should plan for mixed-methods validation and document discordance with clear numbers, as Mossman et al., 2026 did with 39 participants and a 13-person interview subset.
If your team needs to combine transcripts, questionnaires, and expert adjudication with faster, reproducible workflows, Try Evidano for free to prototype an AI-enabled qualitative pipeline.
Topics
- qualitative analysis of hyperphagia
- Bardet-Biedl Syndrome qualitative research
- AI qualitative analysis
- mixed-methods interviews
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