Qualitative Analysis of Hyperphagia in BBS

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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