---
_id: '13880'
abstract:
- lang: eng
  text: "<jats:title>ABSTRACT</jats:title>\r\n                  <jats:sec>\r\n                    <jats:title>Objective</jats:title>\r\n
    \                   <jats:p>Epidemiological evidence on muscle dysmorphia (MD)
    remains limited, and self‐report algorithm‐defined estimates may depend on sampling
    and case definitions. We examined how algorithm‐defined MD estimates and exploratory
    correlates varied across weighting and case‐definition scenarios in a gender‐balanced
    German online sample.</jats:p>\r\n                  </jats:sec>\r\n                  <jats:sec>\r\n
    \                   <jats:title>Method</jats:title>\r\n                    <jats:p>In
    this cross‐sectional web‐based study, 1468 adults from Germany completed self‐report
    measures: 739 (50.3%) men, 706 (48.1%) women, 21 (1.4%) nonbinary/diverse participants,
    and 2 (0.1%) who preferred not to disclose their gender. Algorithm‐defined MD
    was estimated using a self‐report algorithm derived from prior epidemiological
    work. Estimates were compared across four scenarios combining unweighted versus
    age‐ and gender‐weighted analyses with global versus gender‐specific criterion
    A cutoffs. Logistic regression models examined correlates across weighted and
    unweighted analytic specifications.</jats:p>\r\n                  </jats:sec>\r\n
    \                 <jats:sec>\r\n                    <jats:title>Results</jats:title>\r\n
    \                   <jats:p>Algorithm‐defined estimates varied substantially across
    operationalizations. The unweighted global algorithm yielded an estimate of 6.2%
    overall and 11.0% in men. The weighted gender‐specific scenario yielded 2.6% overall,
    3.5% in men, and 1.7% in women. Across regression specifications, lower BMI and
    higher identity disturbance were the most consistent correlates of algorithm‐defined
    MD. Female gender showed lower odds in pooled models, particularly under the global
    cutoff, but this finding should be interpreted cautiously.</jats:p>\r\n                  </jats:sec>\r\n
    \                 <jats:sec>\r\n                    <jats:title>Discussion</jats:title>\r\n
    \                   <jats:p>Self‐report algorithm‐defined MD may affect a meaningful
    minority of adults, but estimates depend strongly on weighting strategy and case
    definition. These findings highlight the need for transparent reporting of algorithmic
    operationalizations.</jats:p>\r\n                  </jats:sec>"
article_number: eat.70170
author:
- first_name: Christopher
  full_name: Zaiser, Christopher
  last_name: Zaiser
- first_name: Nora M.
  full_name: Laskowski, Nora M.
  last_name: Laskowski
- first_name: Georg
  full_name: Halbeisen, Georg
  id: '85780'
  last_name: Halbeisen
  orcid: 0000-0002-9529-2215
- first_name: Marietta
  full_name: Lieb, Marietta
  last_name: Lieb
- first_name: Georgios
  full_name: Paslakis, Georgios
  last_name: Paslakis
citation:
  ama: Zaiser C, Laskowski NM, Halbeisen G, Lieb M, Paslakis G. Algorithm‐Defined
    Muscle Dysmorphia Estimates Across Weighting and Case‐Definition Strategies in
    a Gender‐Balanced Adult Online Sample. <i>International Journal of Eating Disorders</i>.
    Published online 2026. doi:<a href="https://doi.org/10.1002/eat.70170">10.1002/eat.70170</a>
  apa: Zaiser, C., Laskowski, N. M., Halbeisen, G., Lieb, M., &#38; Paslakis, G. (2026).
    Algorithm‐Defined Muscle Dysmorphia Estimates Across Weighting and Case‐Definition
    Strategies in a Gender‐Balanced Adult Online Sample. <i>International Journal
    of Eating Disorders</i>, Article eat. 70170. <a href="https://doi.org/10.1002/eat.70170">https://doi.org/10.1002/eat.70170</a>
  bjps: <b>Zaiser C <i>et al.</i></b> (2026) Algorithm‐Defined Muscle Dysmorphia Estimates
    Across Weighting and Case‐Definition Strategies in a Gender‐Balanced Adult Online
    Sample. <i>International Journal of Eating Disorders</i>.
  chicago: Zaiser, Christopher, Nora M. Laskowski, Georg Halbeisen, Marietta Lieb,
    and Georgios Paslakis. “Algorithm‐Defined Muscle Dysmorphia Estimates Across Weighting
    and Case‐Definition Strategies in a Gender‐Balanced Adult Online Sample.” <i>International
    Journal of Eating Disorders</i>, 2026. <a href="https://doi.org/10.1002/eat.70170">https://doi.org/10.1002/eat.70170</a>.
  chicago-de: Zaiser, Christopher, Nora M. Laskowski, Georg Halbeisen, Marietta Lieb
    und Georgios Paslakis. 2026. Algorithm‐Defined Muscle Dysmorphia Estimates Across
    Weighting and Case‐Definition Strategies in a Gender‐Balanced Adult Online Sample.
    <i>International Journal of Eating Disorders</i>. doi:<a href="https://doi.org/10.1002/eat.70170">10.1002/eat.70170</a>,
    .
  din1505-2-1: '<span style="font-variant:small-caps;">Zaiser, Christopher</span>
    ; <span style="font-variant:small-caps;">Laskowski, Nora M.</span> ; <span style="font-variant:small-caps;">Halbeisen,
    Georg</span> ; <span style="font-variant:small-caps;">Lieb, Marietta</span> ;
    <span style="font-variant:small-caps;">Paslakis, Georgios</span>: Algorithm‐Defined
    Muscle Dysmorphia Estimates Across Weighting and Case‐Definition Strategies in
    a Gender‐Balanced Adult Online Sample. In: <i>International Journal of Eating
    Disorders</i>, Wiley (2026)'
  havard: C. Zaiser, N.M. Laskowski, G. Halbeisen, M. Lieb, G. Paslakis, Algorithm‐Defined
    Muscle Dysmorphia Estimates Across Weighting and Case‐Definition Strategies in
    a Gender‐Balanced Adult Online Sample, International Journal of Eating Disorders.
    (2026).
  ieee: 'C. Zaiser, N. M. Laskowski, G. Halbeisen, M. Lieb, and G. Paslakis, “Algorithm‐Defined
    Muscle Dysmorphia Estimates Across Weighting and Case‐Definition Strategies in
    a Gender‐Balanced Adult Online Sample,” <i>International Journal of Eating Disorders</i>,
    Art. no. eat. 70170, 2026, doi: <a href="https://doi.org/10.1002/eat.70170">10.1002/eat.70170</a>.'
  mla: Zaiser, Christopher, et al. “Algorithm‐Defined Muscle Dysmorphia Estimates
    Across Weighting and Case‐Definition Strategies in a Gender‐Balanced Adult Online
    Sample.” <i>International Journal of Eating Disorders</i>, eat. 70170, 2026, <a
    href="https://doi.org/10.1002/eat.70170">https://doi.org/10.1002/eat.70170</a>.
  short: C. Zaiser, N.M. Laskowski, G. Halbeisen, M. Lieb, G. Paslakis, International
    Journal of Eating Disorders (2026).
  ufg: '<b>Zaiser, Christopher u. a.</b>: Algorithm‐Defined Muscle Dysmorphia Estimates
    Across Weighting and Case‐Definition Strategies in a Gender‐Balanced Adult Online
    Sample, in: <i>International Journal of Eating Disorders</i> (2026).'
  van: Zaiser C, Laskowski NM, Halbeisen G, Lieb M, Paslakis G. Algorithm‐Defined
    Muscle Dysmorphia Estimates Across Weighting and Case‐Definition Strategies in
    a Gender‐Balanced Adult Online Sample. International Journal of Eating Disorders.
    2026;
date_created: 2026-07-28T08:39:30Z
date_updated: 2026-07-28T08:40:00Z
department:
- _id: DEP1500
doi: 10.1002/eat.70170
language:
- iso: eng
publication: International Journal of Eating Disorders
publication_identifier:
  issn:
  - 0276-3478
  - 1098-108X
publication_status: published
publisher: Wiley
quality_controlled: '1'
status: public
title: Algorithm‐Defined Muscle Dysmorphia Estimates Across Weighting and Case‐Definition
  Strategies in a Gender‐Balanced Adult Online Sample
type: scientific_journal_article
user_id: '85780'
year: '2026'
...