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<front>
<journal-meta><journal-id journal-id-type="publisher-id">MISS</journal-id><journal-id journal-id-type="nlm-ta">Meas Instrum Soc Sci</journal-id>
<journal-title-group>
<journal-title>Measurement Instruments for the Social Sciences</journal-title><abbrev-journal-title abbrev-type="pubmed">Meas. Instrum. Soc. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2523-8930</issn>
<publisher><publisher-name>PsychOpen</publisher-name></publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">miss.21977</article-id>
<article-id pub-id-type="doi">10.5964/miss.21977</article-id>
<article-categories>
<subj-group subj-group-type="heading"><subject>New Measurement Instruments</subject></subj-group>

<subj-group subj-group-type="badge">
<subject>Code</subject>
<subject>Materials</subject>
</subj-group>

</article-categories>
<title-group>
<article-title>Short Scale Measurement of Legal Cynicism</article-title>
<alt-title alt-title-type="right-running">Legal Cynicism Measurement</alt-title>
<alt-title specific-use="APA-reference-style" xml:lang="en">Short scale measurement of legal cynicism</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid" authenticated="false">https://orcid.org/0000-0003-1595-6948</contrib-id><name name-style="western"><surname>Seddig</surname><given-names>Daniel</given-names></name><xref ref-type="corresp" rid="cor1">*</xref><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib>
<contrib contrib-type="editor">
<name>
	<surname>Davidov</surname>
<given-names>Eldad</given-names>
</name>
<xref ref-type="aff" rid="aff2"/>
</contrib>
<aff id="aff1"><label>1</label><institution>Criminological Research Institute of Lower Saxony (KFN)</institution>, <addr-line><city>Hannover</city></addr-line>, <country country="DE">Germany</country></aff>
	<aff id="aff2">University of Cologne, Cologne, <country>Germany</country></aff>
</contrib-group>
<author-notes>
<corresp id="cor1"><label>*</label>Lützerodestraße 9, 30161 Hannover, Germany. <email xlink:href="Daniel.Seddig@kfn.de">Daniel.Seddig@kfn.de</email></corresp>
</author-notes>
<pub-date date-type="pub" publication-format="electronic"><day>25</day><month>08</month><year>2026</year></pub-date>
<pub-date pub-type="collection" publication-format="electronic"><year>2026</year></pub-date>
<volume>8</volume>
<elocation-id>e21977</elocation-id>
<history>
<date date-type="received">
<day>28</day>
<month>01</month>
<year>2026</year>
</date>
<date date-type="accepted">
<day>18</day>
<month>05</month>
<year>2026</year>
</date>
</history>
<permissions><copyright-year>2026</copyright-year><copyright-holder>Seddig</copyright-holder><license license-type="open-access" specific-use="CC BY 4.0" xlink:href="https://creativecommons.org/licenses/by/4.0/"><ali:license_ref>https://creativecommons.org/licenses/by/4.0/</ali:license_ref><license-p>This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License, CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p></license></permissions>
<abstract>
<p>Legal cynicism is a key concept in criminology and related social sciences, yet existing measurement instruments are often lengthy or capture only limited aspects of the construct. Building on the current state of theoretical work, which conceptualizes legal cynicism as a multidimensional construct, this study proposes and evaluates two short scales with nine and six items, respectively. Using data from a survey of adolescents and young adults in Germany, confirmatory factor analyses supported a three-factor structure representing legal antipathy, legal corruption, and legal legitimacy for both versions. Measurement invariance across gender and educational groups was largely supported. Both short scales showed acceptable reliability and theoretically consistent associations with personal values, institutional trust, and attitudes toward intimate partner violence, providing support for construct validity. Overall, the proposed short scales offer parsimonious and psychometrically sound instruments for assessing legal cynicism.</p>
</abstract>
<kwd-group kwd-group-type="author"><kwd>legal cynicism</kwd><kwd>measurement</kwd><kwd>confirmatory factor analysis</kwd><kwd>criminology</kwd><kwd>sociology</kwd></kwd-group>

</article-meta>
</front>
<body>
	<sec sec-type="intro"><title/>
<p>The concept of legal cynicism is situated within the broader field of legal socialization research (e.g., <xref ref-type="bibr" rid="r6">Fagan &amp; Tyler, 2005</xref>; <xref ref-type="bibr" rid="r26">Tyler, 2006</xref>), which examines how individuals develop relationships with the law and legal authorities, how these relationships are maintained or eroded over time, and how they shape compliance and criminal behavior across adolescence and adulthood. Within this framework—relevant to criminology, sociology, psychology, and legal studies—legal cynicism refers to the belief that the law and legal institutions are untrustworthy, unfair, corrupt, or ineffective in addressing the needs and concerns of individuals and marginalized communities (<xref ref-type="bibr" rid="r20">Sampson &amp; Bartusch, 1998</xref>). Such beliefs are typically grounded in perceived experiences of mistreatment, discrimination, and structural inequality within the legal system.</p>
<p>Early measurement approaches to legal cynicism relied on a limited number of indicators that often captured only specific facets of the construct and overlapped conceptually with related domains such as anomie or research on police and institutional trust (e.g., <xref ref-type="bibr" rid="r9">Hagan et al., 2020</xref>; <xref ref-type="bibr" rid="r13">Kirk &amp; Papachristos, 2011</xref>; <xref ref-type="bibr" rid="r20">Sampson &amp; Bartusch, 1998</xref>). A more comprehensive conceptualization of legal cynicism was proposed by <xref ref-type="bibr" rid="r7">Gifford and Reisig (2019)</xref>, who advanced a multidimensional framework and introduced a measurement instrument suited for survey research. Initial findings on the reliability and validity of this scale were encouraging and further refined by <xref ref-type="bibr" rid="r23">Seddig (2024)</xref>. However, the current multidimensional legal cynicism scale comprises 17 items, which may be impractical in many survey contexts due to respondent burden and constraints on questionnaire length.</p>
<p>This article proposes two short versions of the multidimensional legal cynicism scale. Specifically, 9-item and 6-item short forms are assessed regarding their psychometric properties, ability to maintain the multidimensional structure of the original construct, measurement invariance, and meaningful associations with relevant validation criteria. The analyses are based on data from a survey study conducted with adolescents and young adults in Germany, which was not originally designed for the purposes of scale development.</p>
<sec><title>Legal Cynicism: Concept and Measurement</title>
<sec><title>Theoretical Foundations</title>
<p>Legal cynicism was originally conceptualized as “anomie about law” (<xref ref-type="bibr" rid="r20">Sampson &amp; Bartusch, 1998</xref>). This form of normative disintegration was hypothesized to arise from perceived injustice and maltreatment in interactions with legal authorities (e.g., police, courts, and correctional institutions) and from the attribution of unequal and unfair treatment based on social and personal characteristics such as socioeconomic status, race or ethnicity, gender, age, neighborhood disadvantage, or prior contact with the criminal justice system. Such experiences are socially shared and reinforced within families, partnerships, peer groups, and local communities.</p>
<p>Subsequent theoretical refinements in addition emphasized the cultural context in which evaluations of the legal system are formed (<xref ref-type="bibr" rid="r12">Kirk &amp; Matsuda, 2011</xref>). From this perspective, legal cynicism is not solely a product of structural disadvantages or individual predispositions but reflects a cultural response to exclusion and social disintegration. Collective worldviews and value orientations may therefore shape legal cynicism beyond classical indicators of social and economic differentiation, including more abstract and non-personalised conditions such as perceived social decline, cultural insecurity, and fear of crime.</p>
<p>To explicitly address such extensions, <xref ref-type="bibr" rid="r7">Gifford and Reisig (2019)</xref> proposed a multidimensional model of legal cynicism. Extending the anomie-based core conception, this framework explicitly moves beyond both a narrow focus on police encounters and an exclusively norm-oriented interpretation of earlier work. It incorporates dimensions of institutional (dis)trust and perceived legitimacy (see also <xref ref-type="bibr" rid="r10">Jackson, 2018</xref>; <xref ref-type="bibr" rid="r27">Tyler &amp; Huo, 2002</xref>). Legal cynicism thus encompasses not only the rejection of law, but also beliefs about the integrity and motives of legal institutions and the legitimacy of legal authorities to define and enforce norms.</p>
<p>With this conceptualization, the emergence of legal cynicism is no longer attributed solely to direct institutional encounters, but also to broader perceptions of institutional trust, legitimacy, and social order. This broader foundation also incorporates generalized assessments of the integrity and functionality of social institutions, which may shape negative orientations toward law and legal institutions even in the absence of direct contact with legal authorities.</p>
	<p>Gifford and Reisig distinguish three subdimensions. <italic>Legal antipathy</italic> reflects general rejection of law and legal rules. <italic>Legal corruption</italic> captures doubts about the integrity and fairness of legal institutions, including perceptions of selective and self-serving misuse of the law. <italic>Legal legitimacy</italic> refers to a fundamental questioning of the authority and normative claim of the legal system. This multidimensional approach enables a more differentiated understanding of legal cynicism by highlighting a broader range of antecedents and correlates alongside social inequality such as value orientations, cultural insecurity, fear of crime, and general system perceptions (e.g., <xref ref-type="bibr" rid="r1">Adriaenssen et al., 2019</xref>). It also enhances theoretical integration with broader frameworks, such as Situational Action Theory (<xref ref-type="bibr" rid="r29">Wikström et al., 2012</xref>), by positioning legal cynicism as a meta-construct that may shape or precede more specific moral judgments.</p>
<p>From a measurement perspective, this multidimensional structure implies that legal cynicism cannot be adequately captured by single indicators or unidimensional measures. Accordingly, its empirical assessment requires instruments that differentiate between distinct but related subdimensions while remaining suitable for survey-based research. The following section describes the development and operationalization of the legal cynicism scale.</p></sec>
<sec><title>Measurement of Legal Cynicism</title>
<p>Measures of legal cynicism used in seminal studies typically consisted of short scales comprising three to six items. These instruments primarily captured agreement with statements reflecting normlessness, such as “Laws were made to be broken” (<xref ref-type="bibr" rid="r20">Sampson &amp; Bartusch, 1998</xref>), or contextual aspects, for example “The police are not doing a good job in preventing crime in this neighborhood” (<xref ref-type="bibr" rid="r12">Kirk &amp; Matsuda, 2011</xref>). While many studies have employed such measures and reported acceptable psychometric properties and replicability across subgroups (<xref ref-type="bibr" rid="r9">Hagan et al., 2020</xref>), other research has documented inconsistencies in their dimensionality and construct coverage (<xref ref-type="bibr" rid="r7">Gifford &amp; Reisig, 2019</xref>; <xref ref-type="bibr" rid="r17">Reisig et al., 2011</xref>). These findings suggest that existing instruments often fail to adequately multifaceted legal cynicism.</p>
<p>Building on these limitations, <xref ref-type="bibr" rid="r7">Gifford and Reisig (2019)</xref> proposed a measurement instrument corresponding to their theoretically grounded multidimensional conceptualization. After extensive testing and refinement, this scale comprised 17 items representing three correlated dimensions: legal antipathy was reflected by 7 items, legal corruption was measured by 4 items, and legal legitimacy consisted of 6 items. The multidimensional structure was supported by confirmatory factor analyses, including tests of second-order factor models, and construct validity was established through associations (path analysis) with external criteria such as criminal offending, self-control, anger, personal morality, and perceptions of procedural and distributive justice.</p>
<p><xref ref-type="bibr" rid="r23">Seddig (2024)</xref> introduced a German-language version of the Gifford and Reisig legal cynicism scale and empirically confirmed its three-dimensional structure using data from two independent German samples. Importantly, these findings indicate that the multidimensional structure of legal cynicism matters for empirical interpretation and that a single overall scale score is insufficient to capture the construct adequately.</p></sec></sec>
<sec><title>Legal Cynicism Short Scale-9 (LCS-9) and Legal Cynicism Short Scale-6 (LCS-6)</title>
<p>A reduced set of items was selected to construct two short forms of the scale: the Legal Cynicism Short Scale-9 (LCS-9) and the Legal Cynicism Short Scale-6 (LCS-6). For each subdimension of legal cynicism, three (LCS-9) or two (LCS-6) items were selected, prioritizing those with the highest standardized factor loadings in the analyses reported by <xref ref-type="bibr" rid="r23">Seddig (2024)</xref>. Importantly, the same items emerged as the strongest indicators of their respective subdimensions across both samples analyzed in <xref ref-type="bibr" rid="r23">Seddig (2024)</xref>, lending support to the stability and generalizability of the item selection. In the first sample, standardized factor loadings of the selected items ranged from .75 to .88, while in the second sample they ranged from .69 to .90. The resulting item selection also partially aligns with the empirical findings reported by <xref ref-type="bibr" rid="r7">Gifford and Reisig (2019)</xref>. The original English item wordings of the selected items are presented in <xref ref-type="table" rid="t1">Table 1</xref>.</p>
<table-wrap id="t1" position="anchor" orientation="landscape"><?pagebreak-before?>
<label>Table 1</label><caption><title>Items and Descriptive Statistics</title></caption>
	<table frame="hsides" rules="groups" style="striped-#f3f3f3">
<col width="6%" align="left"/>
<col width="26%"/>
<col width="6%"/>
<col width="8%"/>
<col width="11%"/>
<col width="9%"/>
<col width="6%"/>
<col width="8%"/>
<col width="11%"/>
<col width="9%"/>
<thead>
<tr>
<th rowspan="2" valign="bottom">Item</th>
	<th rowspan="2" valign="bottom" align="left">Label</th>
<th colspan="4" scope="colgroup">LCS-9<hr/></th>
<th colspan="4" scope="colgroup">LCS-6<hr/></th>
</tr>
<tr>
	<th valign="bottom" scope="colgroup"><italic>n</italic></th>
	<th valign="bottom">Mean (<italic>SD</italic>)</th>
	<th valign="bottom">Skewness (SE)</th>
	<th valign="bottom">Kurtosis</th>
	<th valign="bottom"><italic>n</italic></th>
	<th valign="bottom">Mean (<italic>SD</italic>)</th>
	<th valign="bottom">Skewness (SE)</th>
	<th valign="bottom">Kurtosis</th>
</tr>
</thead>
<tbody>
<tr>
<td>LA1</td>
	<td align="left">Sometimes you need to ignore the law and do what you want to.</td>
<td>386</td>
<td>2.88 (1.35)</td>
<td>0.24 (0.12)</td>
<td align="char" char=".">-0.85</td>
<td/>
<td/>
<td/>
<td/>
</tr>
<tr>
<td>LA2</td>
	<td align="left">It’s alright to break the law if you don’t get caught.</td>
<td>385</td>
<td>2.62 (1.38)</td>
<td>0.57 (0.12)</td>
<td align="char" char=".">-0.52</td>
<td>387</td>
<td>2.49 (1.45)</td>
<td>0.70 (0.12)</td>
<td align="char" char=".">-0.47</td>
</tr>
<tr>
<td>LA3</td>
	<td align="left">It is alright to get around the law if you can get away with it.</td>
<td>385</td>
<td>2.73 (1.37)</td>
<td>0.33 (0.12)</td>
<td align="char" char=".">-0.96</td>
<td>385</td>
<td>2.60 (1.40)</td>
<td>0.54 (0.12)</td>
<td align="char" char=".">-0.65</td>
</tr>
<tr>
<td>LC1</td>
	<td align="left">The law does not protect my interests.</td>
<td>373</td>
<td>3.07 (1.42)</td>
<td>0.33 (0.13)</td>
<td align="char" char=".">-0.73</td>
<td/>
<td/>
<td/>
<td/>
</tr>
<tr>
<td>LC2</td>
	<td align="left">Laws are usually bad.</td>
<td>388</td>
<td>2.30 (1.30)</td>
<td>0.85 (0.12)</td>
<td align="char" char=".">-0.17</td>
<td>392</td>
<td>2.30 (1.40)</td>
<td>0.93 (0.12)</td>
<td align="char" char=".">-0.05</td>
</tr>
<tr>
<td>LC3</td>
	<td align="left">The law is rotten to the core.</td>
<td>383</td>
<td>2.62 (1.45)</td>
<td>0.60 (0.12)</td>
<td align="char" char=".">-0.58</td>
<td>375</td>
<td>2.59 (1.47)</td>
<td>0.50 (0.13)</td>
<td align="char" char=".">-0.86</td>
</tr>
<tr>
<td>LL1</td>
	<td align="left">People should always obey the law even if it interferes with their personal ambition.*</td>
<td>380</td>
<td>2.72 (1.19)</td>
<td>0.59 (0.13)</td>
<td align="char" char=".">0.20</td>
<td/>
<td/>
<td/>
<td/>
</tr>
<tr>
<td>LL2</td>
	<td align="left">I try to obey the law, even if it goes against what I think is right.*</td>
<td>381</td>
<td>2.72 (1.09)</td>
<td>0.60 (0.13)</td>
<td align="char" char=".">0.42</td>
<td>380</td>
<td>2.74 (1.20)</td>
<td>0.67 (0.13)</td>
<td align="char" char=".">0.36</td>
</tr>
<tr>
<td>LL3</td>
	<td align="left">People should obey the law, even if they disagree with it.*</td>
<td>380</td>
<td>2.76 (1.12)</td>
<td>0.49 (0.13)</td>
<td align="char" char=".">0.41</td>
<td>387</td>
<td>2.64 (1.18)</td>
<td>0.62 (0.12)</td>
<td align="char" char=".">0.31</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p><italic>Note</italic>. <italic>SD</italic> = standard deviation; SE = standard error; LA = Legal Antipathy; LC = Legal Corruption; LL = Legal Legitimacy. Response options: 1 = “fully disagree,” 2 = “disagree,” 3 = “rather disagree,” 4 = “rather agree,” 5 = “agree,” 6 = “fully agree.” Items marked with * were reverse-coded so that higher scores indicate greater legal cynicism.</p>
</table-wrap-foot>
</table-wrap>
<sec><title>Data</title>
<p>The data for this study were drawn from a project aimed at evaluating a social media campaign designed to intervene in intimate partner violence among adolescents and young adults in Germany (<xref ref-type="bibr" rid="r25">Seddig et al., 2026</xref>). The study employed a survey-experimental design with two measurement waves. Legal cynicism was not among the primary study objectives. However, both short scale versions were implemented in their German-language forms in the second wave of data collection.</p>
<p>Participants were recruited from an ongoing German online access panel provided by the market research institute Bilendi (<ext-link ext-link-type="uri" xlink:href="https://www.bilendi.us/">https://www.bilendi.us/</ext-link>). Thus, the sample is a convenience sample without claims to representativeness and without the application of additional quota restrictions. After data cleaning, out of the 2,000 respondents who had participated in the first wave, 800 responses could be used from participants that remained in the second wave. The final sample comprised 74.3% female respondents, with a mean age of 22.2 years (<italic>SD</italic> = 2.5; range = 16–25).</p>
<p>Participants were randomly assigned to one of the two short scale versions within the online questionnaire, such that 403 respondents completed the LCS-9 version and 397 respondents completed the LCS-6 version. Respondents were asked to rate their agreement with the statements implying legal cynicism on a six-point response scale with fully labeled categories. The response options were 1 = “fully disagree,” 2 = “disagree,” 3 = “rather disagree,” 4 = “rather agree,” 5 = “agree,” 6 = “fully agree.” The item frequency plots in <xref ref-type="fig" rid="f1">Figure 1</xref> and the descriptive statistics in <xref ref-type="table" rid="t1">Table 1</xref> indicated positive skewness and mixed kurtosis of the item distributions, with responses concentrated at the lower end of the scale and right-tailed distributions reflecting generally low levels of legal cynicism across items.</p>
	
	<fig id="f1" position="anchor" fig-type="figure" orientation="portrait"><label>Figure 1</label><caption>
<title>Item Frequencies</title></caption><graphic xlink:href="miss.21977-f1" position="anchor" orientation="portrait"/></fig>

</sec>
<sec><title>Analytical Plan</title>
<p>The short scales were evaluated using confirmatory factor analysis (CFA; <xref ref-type="bibr" rid="r3">Brown, 2015</xref>). Legal cynicism was modeled as three correlated latent factors representing legal antipathy, legal corruption, and legal legitimacy. Due to the categorical and nonnormal nature of the data, diagonally weighted least squares estimation with robust standard errors was applied (<xref ref-type="bibr" rid="r14">Koziol, 2023</xref>), with pairwise deletion used in the computation of polychoric correlations. Thus, a threshold model was specified for the item responses, allowing for estimation of latent response variables underlying the observed categories.</p>
<p>Measurement invariance was examined to determine whether factor loadings, thresholds, and residual variances function equivalently across groups. Measurement invariance can help determine whether comparisons of mean scores or regression coefficients can be considered unbiased across groups (<xref ref-type="bibr" rid="r15">Leitgöb et al., 2023</xref>). Configural invariance assumes the same factor structure across groups. Metric invariance adds equality constraints on factor loadings. Scalar invariance further constrains item thresholds. Strict invariance additionally constrains residual variances. More restrictive models were accepted if fit did not deteriorate substantially. Group comparisons were conducted for gender (female, <italic>n</italic> = 574, 75%; male, <italic>n</italic> = 191, 25%; cases with missing gender information, <italic>n</italic> = 30, and five respondents identifying as diverse were excluded) and educational level (high education: Gymnasium, <italic>n</italic> = 537, 70%; lower education, <italic>n</italic> = 232, 30%), whereas other demographic comparisons were not feasible due to unavailable information, restricted variability, or small group sizes.</p>
<p>To assess the validity of the short scales, multiple complementary variables were examined in relation to legal antipathy, legal corruption, and legal legitimacy. Construct validity was assessed through associations with selected personal values (<xref ref-type="bibr" rid="r22">Schwartz, 1994</xref>). The legal cynicism subdimensions were expected to correlate positively with power values and negatively with security and universalism values, indicating that legal cynicism is value-driven and supporting its conceptualization as a meta-construct rather than situational or context-dependent norm acceptance. Personal values were assessed as single items using the German version of the Short Schwartz’s Value Survey (<xref ref-type="bibr" rid="r2">Boer, 2013</xref>) on a 6-point rating scale. Convergent validity was examined through associations with trust in police, trust in the justice system, and trust in politicians as well as attitudes toward intimate partner violence (assault on a partner). The legal cynicism subdimensions were expected to correlate negatively with trust and positively with permissive attitudes toward intimate partner violence, demonstrating relevance to perceptions of institutions and normatively charged behaviors. Trust and attitudes were assessed as single items on 6-point rating scales.</p>
<p>Model fit was evaluated using the scaled chi-square (χ<sup>2</sup>) test and alternative indices including the comparative fit index (CFI), root mean square error of approximation (RMSEA), and standardized root mean residual (SRMR), with acceptable thresholds of CFI ≥ 0.95, RMSEA ≤ 0.08, and SRMR ≤ 0.08 (<xref ref-type="bibr" rid="r28">West et al., 2012</xref>). Measurement invariance in the present study was evaluated by testing chi-square differences and assessing differences in alternative fit indices, interpreted on a case-by-case basis rather than relying on strict cutoff rules. Many commonly cited guidelines (e.g., <xref ref-type="bibr" rid="r4">Chen, 2007</xref>) were developed under normal-theory maximum likelihood estimation and may not directly generalize to models estimated with weighted least squares approaches. Other studies indicate that changes in alternative fit indices (e.g., ΔCFI, ΔRMSEA, ΔSRMR) can be sensitive to model misspecification and scale length (<xref ref-type="bibr" rid="r21">Sass et al., 2014</xref>; <xref ref-type="bibr" rid="r5">D’Urso et al., 2022</xref>). All analyses were conducted in R (<xref ref-type="bibr" rid="r16">R Core Team, 2025</xref>) using lavaan (<xref ref-type="bibr" rid="r19">Rosseel, 2012</xref>) and semTools (<xref ref-type="bibr" rid="r11">Jorgensen et al., 2025</xref>). A documentation of the analyses is presented in an online appendix. The data are available from the author upon request.</p></sec></sec></sec>
<sec sec-type="results"><title>Results</title>
<sec><title>Confirmatory Factor Analysis</title>
<sec><title>LCS-9</title>
<p>The theorized three-factor model showed good global fit to the data: χ<sup>2</sup>(24) = 42.64, <italic>p</italic> = .01; CFI = .99; RMSEA = .05; SRMR = .03. The fit was substantially better than for a one-factor model, in which all items reflect a unique latent legal cynicism factor: Δχ<sup>2</sup>(3) = 310.96, <italic>p</italic> &lt; .01. Standardized factor loadings in the three-factor model were all ≥ .70, except for item LL2, which showed a more moderate loading (λ = .52; see <xref ref-type="fig" rid="f2">Figure 2</xref>). McDonald’s omega reliability coefficients indicated good internal consistency for legal antipathy (ω = .87) and legal corruption (ω = .82), and acceptable reliability for legal legitimacy (ω = .73). The correlation between the legal antipathy and legal corruption factors was high (<italic>r</italic> = .86), indicating a substantial overlap between these subdimensions. However, collapsing the three-factor structure into a two-factor model, in which legal antipathy and legal corruption were combined, resulted in a significant deterioration in fit, Δχ<sup>2</sup>(2) = 49.78, <italic>p</italic> &lt; .01, suggesting that the separated factors capture conceptually distinct aspects of legal cynicism, each reflecting a specific substantive core, which justifies their separate consideration. Legal antipathy and legal corruption showed moderate to moderately high correlations with legal legitimacy.</p>
	
	<fig id="f2" position="anchor" fig-type="figure" orientation="portrait"><label>Figure 2</label><caption>
			<title>Standardized Factor Loadings, Residuals, and Factor Correlations of the LCS-9 (n = 397; Upper Panel) and LCS-6 (n = 393, Lower Panel) Models</title><p>*<italic>p</italic> &lt; .01</p></caption><graphic xlink:href="miss.21977-f2" position="anchor" orientation="portrait"/></fig>

	
<p>A model with parallel parameter constraints (i.e., factor loadings and residual variances constrained to equality within dimensions) does not fit the data well: χ<sup>2</sup>(30) = 173.92, <italic>p</italic> &lt; .01; CFI = .94; RMSEA = .10; SRMR = .06. However, excluding item LL2 resulted in acceptable model fit: χ<sup>2</sup>(22) = 72.88, <italic>p</italic> &lt; .01; CFI = .97; RMSEA = .08; SRMR = .04. Based on this finding, the eight remaining items may be used to compute separate sum or mean scores for each dimension in substantive analyses. It should be noted, however, that sum or mean scores do not account for measurement error, which may lead to attenuation of regression or path coefficients in subsequent analyses (<xref ref-type="bibr" rid="r8">Gilbert, 2025</xref>). Moreover, bifactor analyses (<xref ref-type="bibr" rid="r23">Seddig, 2024</xref>) showed that a total scale score would not represent a meaningful general construct.</p>
<p>Higher-order CFA models were not specified. A second-order legal cynicism factor model is statistically equivalent to the three-factor model when only three first-order factors are included and therefore does not provide additional information. Bifactor models resulted in negative estimated latent variances, indicating that the models were not properly identified.</p>
<p>To assess robustness to estimation method and missing-data handling, we re-estimated the preferred three-factor model using three alternative specifications: DWLS with listwise deletion, pairwise maximum-likelihood (PML) as a categorical alternative using pairwise available data, and robust maximum likelihood (MLR) treating indicators as approximately continuous with FIML handling of missing data. Across all specifications, factor loadings and latent correlations showed strong convergence. Minor attenuation of parameters was observed under MLR, consistent with differences found between models for ordinal and continuous indicators (e.g., <xref ref-type="bibr" rid="r18">Rhemtulla et al., 2012</xref>). The overall pattern and magnitude of relationships, however, remained highly stable. These results indicate that the measurement structure and substantive conclusions are robust across estimation frameworks and missing data treatments.</p></sec>
<sec><title>LCS-6</title>
<p>The three-factor model showed acceptable global fit to the data: χ<sup>2</sup>(6) = 15.74, <italic>p</italic> = .02; CFI = .99; RMSEA = .08; and SRMR = .02. Model fit was substantially better than that of a one-factor model: Δχ<sup>2</sup>(3) = 206.93, <italic>p</italic> &lt; .01. Standardized factor loadings in the three-factor model were all ≥ .83, except for item LL2, which again showed a more moderate loading (λ = .56). McDonald’s omega reliability coefficients indicated good internal consistency for legal antipathy (ω = .83) and legal corruption (ω = .83), but comparatively weak reliability for legal legitimacy (ω = .63). This lower reliability is due to the reduced scale length, which comprises only two items, one of which exhibits a weaker factor loading. The correlation between the legal antipathy and legal corruption factors was high (r = .82), whereas correlations involving legal legitimacy were weak to moderately high. A two-factor model combining legal antipathy and legal corruption fit the data significantly worse than the three-factor model: Δχ<sup>2</sup>(2) = 57.02, <italic>p</italic> &lt; .01.</p>
<p>A model with parallel parameter constraints showed acceptable fit to the data: χ<sup>2</sup>(9) = 30.38, <italic>p</italic> &lt; .01; CFI = .98; RMSEA = .08; and SRMR = .04. Accordingly, separate sum or mean scores may be computed for each dimension in substantive analyses. However, measurement error and the reduced reliability of the legal legitimacy scale should be considered when interpreting results.</p></sec></sec>
<sec><title>Measurement Invariance</title>
<sec><title>LCS-9</title>
<p>Increasing model restrictions across the gender groups did not lead to statistically significant χ<sup>2</sup> difference tests (<xref ref-type="table" rid="t2">Table 2</xref>). Moreover, changes in alternative fit indices were minimal, indicating negligible impact of added constraints and, in some cases, even slight improvements in model fit. The maximum decrease in CFI was 0.006, the maximum increase in RMSEA was 0.01, and the maximum increase in SRMR was 0.005.</p>
<table-wrap id="t2" position="anchor" orientation="landscape">
<label>Table 2</label><caption><title>Measurement Invariance Model Fit Statistics</title></caption>
<table frame="hsides" rules="groups">
<col width="10%" align="left"/>
<col width="9%"/>
<col width="12%"/>
<col width="8%"/>
<col width="8%"/>
<col width="8%"/>
<col width="9%"/>
<col width="12%"/>
<col width="8%"/>
<col width="8%"/>
<col width="8%"/>
<thead>
<tr>
<th rowspan="2"/>
<th colspan="5" scope="colgroup">LCS-9<hr/></th>
<th colspan="5" scope="colgroup">LCS-6<hr/></th>
</tr>
<tr>
<th scope="colgroup">χ<sup>2</sup> (<italic>df</italic>)</th>
<th>Δχ<sup>2</sup> (Δ<italic>df</italic>)</th>
<th>CFI</th>
<th>RMSEA</th>
<th>SRMR</th>
<th>χ<sup>2</sup> (<italic>df</italic>)</th>
<th>Δχ<sup>2</sup> (Δ<italic>df</italic>)</th>
<th>CFI</th>
<th>RMSEA</th>
<th>SRMR</th>
</tr>
</thead>
<tbody>
<tr>
<th colspan="11">Gender</th>
</tr>
<tr>
<td style="indent">Configural</td>
<td>100.56 (48)</td>
<td/>
<td align="char" char=".">0.99</td>
<td align="char" char=".">0.08</td>
<td align="char" char=".">0.04</td>
<td>24.98 (12)</td>
<td/>
<td align="char" char=".">0.99</td>
<td align="char" char=".">0.08</td>
<td align="char" char=".">0.03</td>
</tr>
<tr>
	<td style="indent">Metric</td>
<td>101.46 (53)</td>
<td>2.90 (5),<break/><italic>p</italic> = .72 </td>
<td align="char" char=".">0.99</td>
<td align="char" char=".">0.07</td>
<td align="char" char=".">0.04</td>
<td>25.32 (14)</td>
<td>0.79 (2),<break/><italic>p</italic> = .67 </td>
<td align="char" char=".">1.00</td>
<td align="char" char=".">0.07</td>
<td align="char" char=".">0.03</td>
</tr>
<tr>
	<td style="indent">Scalar</td>
<td>129.16 (86)</td>
<td>35.69 (33),<break/><italic>p</italic> = .34 </td>
<td align="char" char=".">0.99</td>
<td align="char" char=".">0.05</td>
<td align="char" char=".">0.04</td>
<td>43.85 (35)</td>
<td>22.64 (21),<break/><italic>p</italic> = .36 </td>
<td align="char" char=".">1.00</td>
<td align="char" char=".">0.04</td>
<td align="char" char=".">0.03</td>
</tr>
<tr>
	<td style="indent">Strict</td>
<td>142.38 (95)</td>
<td>16.12 (9),<break/><italic>p</italic> = .06 </td>
<td align="char" char=".">0.99</td>
<td align="char" char=".">0.05</td>
<td align="char" char=".">0.04</td>
<td>63.17 (41)</td>
<td>19.45 (6),<break/><italic>p</italic> &lt; .01 </td>
<td align="char" char=".">0.99</td>
<td align="char" char=".">0.05</td>
<td align="char" char=".">0.03</td>
</tr>
<tr>
<th colspan="11">Education</th>
</tr>
<tr>
	<td style="indent">Configural</td>
<td>84.90 (48)</td>
<td/>
<td align="char" char=".">0.99</td>
<td align="char" char=".">0.07</td>
<td align="char" char=".">0.04</td>
<td>25.35 (12)</td>
<td/>
<td align="char" char=".">1.00</td>
<td align="char" char=".">0.08</td>
<td align="char" char=".">0.02</td>
</tr>
<tr>
	<td style="indent">Metric</td>
<td>94.48 (53)</td>
<td>12.70 (5),<break/><italic>p</italic> = .03 </td>
<td align="char" char=".">0.99</td>
<td align="char" char=".">0.07</td>
<td align="char" char=".">0.04</td>
<td>25.65 (14)</td>
<td>0.89 (2),<break/><italic>p</italic> = .64 </td>
<td align="char" char=".">1.00</td>
<td align="char" char=".">0.07</td>
<td align="char" char=".">0.02</td>
</tr>
<tr>
	<td style="indent">Scalar</td>
<td>127.82 (86)</td>
<td>37.54 (33),<break/><italic>p</italic> = .27 </td>
<td align="char" char=".">0.99</td>
<td align="char" char=".">0.05</td>
<td align="char" char=".">0.04</td>
<td>54.94 (35)</td>
<td>32.21 (21),<break/><italic>p</italic> = .06 </td>
<td align="char" char=".">0.99</td>
<td align="char" char=".">0.06</td>
<td align="char" char=".">0.03</td>
</tr>
<tr>
	<td style="indent">Strict</td>
<td>159.86 (95)</td>
<td>36.53 (9),<break/><italic>p</italic> &lt; .01 </td>
<td align="char" char=".">0.98</td>
<td align="char" char=".">0.06</td>
<td align="char" char=".">0.04</td>
<td>66.13 (41)</td>
<td>12.28 (6),<break/><italic>p</italic> = .06 </td>
<td align="char" char=".">0.99</td>
<td align="char" char=".">0.05</td>
<td align="char" char=".">0.03</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p><italic>Note</italic>. Sample sizes LCS-9: female (<italic>n</italic> = 290) vs. male (<italic>n</italic> = 90), high education (<italic>n</italic> = 239) vs. low education (<italic>n</italic> = 94). Sample sizes LCS-6: female (<italic>n</italic> = 277) vs. male (<italic>n</italic> = 100), high education (<italic>n</italic> = 263) vs. low education (<italic>n</italic> = 116).</p>
</table-wrap-foot>
</table-wrap>
<p>For education, using DWLS estimation with pairwise missing data handling resulted in non-convergence for the configural and metric invariance models. Therefore, DWLS with listwise deletion was used. The χ<sup>2</sup> difference test indicated significant deterioration from the configural to the metric invariance model (<italic>p</italic> = .03) and from the scalar to the strict invariance model (<italic>p</italic> &lt; .01). However, changes across successive invariance models were minimal, indicating that adding equality constraints had a negligible impact on model fit. The maximum decrease in CFI was 0.006, the maximum increase in RMSEA was 0.015, and the maximum increase in SRMR was 0.005.</p>

<?table t2?>

</sec>
<sec><title>LCS-6</title>
<p>For the gender invariance tests, the residual variance of item LL2 was fixed to zero to avoid negative variance estimates in the configural and metric models. The χ<sup>2</sup> difference test indicated a significant deterioration from the scalar to the strict invariance model (<italic>p</italic> &lt; .01). However, changes in alternative fit indices across successive invariance models were small. The maximum decrease in CFI was 0.005, the maximum increase in RMSEA was 0.017, and the maximum increase in SRMR was 0.009. Thus, adding equality constraints had a negligible impact on model fit. Regarding educational level, neither the χ<sup>2</sup> difference tests or changes in alterative fit indices indicated significant deterioration in model fit across successive invariance models.</p>
<p>Based on these findings, strict measurement invariance indicates that factor loadings, thresholds, and residual variances are equivalent across gender and educational groups, implying that differences in latent or manifest scores from both the LCS-9 and LCS-6 reflect true differences in the underlying constructs rather than measurement artifacts. However, comparisons of other groups require separate new invariance tests in each case.</p></sec></sec>
<sec><title>Validation</title>
<p>For both the LCS-9 and LCS-6, associations between the legal cynicism subdimensions and the validation criteria were estimated within a CFA model as correlations between latent and observed constructs. Across both scale versions, the correlations followed a consistent and theoretically meaningful pattern, providing support for the validity of the short scales (<xref ref-type="table" rid="t3">Table 3</xref>). Power values were positively associated with legal antipathy and legal corruption, but not with legal legitimacy. This suggests that an emphasis on control or dominance over people and resources is linked to dismissive views of the law and perceptions of legal corruption, but not to generalized beliefs about whether laws should be obeyed. Security and universalism values were negatively correlated with all three dimensions, indicating that striving for personal and societal safety and stability, as well as concern for the welfare of others and nature, is associated with lower levels of legal cynicism. The observed pattern of associations across subdimensions is theoretically coherent and lends support to the construct validity of the scales.</p>
<table-wrap id="t3" position="anchor" orientation="portrait">
<label>Table 3</label><caption><title>Model-Based Correlations of Legal Cynicism Subdimensions and Validation Criteria</title></caption>
<table frame="hsides" rules="groups">
<col width="26%" align="left"/>
<col width="12%"/>
<col width="12.5%"/>
<col width="12.5%"/>
<col width="12%"/>
<col width="12.5%"/>
<col width="12.5%"/>
<thead>
<tr>
<th rowspan="2"/>
<th colspan="3" scope="colgroup">LCS-9 (<italic>n</italic> = 403)<hr/></th>
<th colspan="3" scope="colgroup">LCS-6 (<italic>n</italic> = 397)<hr/></th>
</tr>
<tr>
<th scope="colgroup">Legal Antipathy </th>
<th>Legal Corruption</th>
<th>Legal Legitimacy</th>
<th>Legal Antipathy </th>
<th>Legal Corruption</th>
<th>Legal Legitimacy</th>
</tr>
</thead>
<tbody>
<tr>
<td>Power</td>
<td align="char" char=".">0.31*</td>
<td align="char" char=".">0.42*</td>
<td align="char" char=".">-0.05</td>
<td align="char" char=".">0.51*</td>
<td align="char" char=".">0.44*</td>
<td align="char" char=".">0.07</td>
</tr>
<tr>
<td>Security</td>
<td align="char" char=".">-0.33*</td>
<td align="char" char=".">-0.33*</td>
<td align="char" char=".">-0.38*</td>
<td align="char" char=".">-0.47*</td>
<td align="char" char=".">-0.42*</td>
<td align="char" char=".">-0.31*</td>
</tr>
<tr>
<td>Universalism</td>
<td align="char" char=".">-0.22*</td>
<td align="char" char=".">-0.26*</td>
<td align="char" char=".">-0.20*</td>
<td align="char" char=".">-0.33*</td>
<td align="char" char=".">-0.28*</td>
<td align="char" char=".">-0.21*</td>
</tr>
<tr>
<td>Trust in police</td>
<td align="char" char=".">-0.26*</td>
<td align="char" char=".">-0.33*</td>
<td align="char" char=".">-0.33*</td>
<td align="char" char=".">-0.24*</td>
<td align="char" char=".">-0.25*</td>
<td align="char" char=".">-0.20*</td>
</tr>
<tr>
<td>Trust in the justice system </td>
<td align="char" char=".">-0.28*</td>
<td align="char" char=".">-0.43*</td>
<td align="char" char=".">-0.36*</td>
<td align="char" char=".">-0.24*</td>
<td align="char" char=".">-0.34*</td>
<td align="char" char=".">-0.16*</td>
</tr>
<tr>
<td>Trust in politicians</td>
<td align="char" char=".">0.04</td>
<td align="char" char=".">-0.08</td>
<td align="char" char=".">-0.21*</td>
<td align="char" char=".">0.01</td>
<td align="char" char=".">-0.07</td>
<td align="char" char=".">-0.04</td>
</tr>
<tr>
<td>Attitude toward IPV</td>
<td align="char" char=".">0.44*</td>
<td align="char" char=".">0.50*</td>
<td align="char" char=".">0.24*</td>
<td align="char" char=".">0.51*</td>
<td align="char" char=".">0.56*</td>
<td align="char" char=".">0.30*</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>*<italic>p</italic> &lt; .01.</p>
</table-wrap-foot>
</table-wrap>
<p>Trust in the police and trust in the justice system were consistently and negatively related to all dimensions of legal cynicism, with particularly strong associations for legal corruption and legal legitimacy. Trust in politicians showed weaker and less consistent associations, reaching statistical significance only for legal legitimacy in the LCS-9 version. Together, these findings highlight the close relationship especially between the non-anomic dimensions of legal cynicism and institutional trust.</p>
<p>Finally, all dimensions of legal cynicism were positively correlated with more permissive attitudes toward intimate partner violence, demonstrating that legal cynicism is meaningfully related to normatively and legally charged attitudes and behaviors. This indicates the construct’s substantive relevance beyond general evaluations of legal or political institutions.</p>

<?table t3?>

</sec></sec>
<sec sec-type="discussion"><title>Discussion</title>
<p>Legal cynicism has attracted attention as an important concept in the social sciences, particularly in criminology and sociology, where it is used to explain attitudes toward deviant behavior and norm compliance. Originally conceptualized as a form of normative disintegration or anomie, legal cynicism emphasizes a generalized skepticism toward the law, which is linked to experiences of injustice and exclusion. Theoretical developments have moved toward a more differentiated understanding of legal cynicism as a multidimensional construct encompassing distinct but related orientations toward the law and legal institutions.</p>
<p>Initial measurement approaches reflected the anomie-based conception and were typically limited to a small number of items capturing normlessness or distrust in legal authorities. Although these measures proved useful in many empirical applications, they were often unable to capture the full conceptual range of legal cynicism. The multidimensional instrument proposed by <xref ref-type="bibr" rid="r7">Gifford and Reisig (2019)</xref> represents an important theoretical and measurement advance by integrating perspectives on institutional trust, perceived fairness, and legitimacy into one concept of legal cynicism. By distinguishing legal antipathy, legal corruption, and legal legitimacy, the framework extends earlier norm-oriented and police-focused approaches toward a broader understanding of skeptical orientations toward law and legal institutions. Perceptions of lacking fairness and integrity provide an important theoretical link to behavior, as a fundamental questioning of the legitimacy and authority of the legal system may weaken normative obligations toward legal compliance and reduce adherence to law beyond purely instrumental considerations. However, with 17 items, the full scale may be impractical for many survey contexts due to respondent burden and space constraints.</p>
<p>The present study contributes to the literature by proposing two short versions of the multidimensional legal cynicism scale that retain the theoretical core of the construct while substantially reducing scale length. The LCS-9 short scale demonstrated good psychometric properties, including acceptable to good reliability, clear differentiation of the three subdimensions, and measurement invariance across gender and educational levels, indicating that the scale functions comparably across key demographic groups. However, item LL2 (“I try to obey the law, even if it goes against what I think is right”) showed the lowest, though still moderate, factor loading. Excluding this item and defining legal legitimacy with two items did not improve model fit or reliability. Moreover, meaningful associations were shown with external validation criteria. While the associations with power, security, and universalism values highlight that legal cynicism can be embedded in broader socio-cultural orientations, the associations with trust in police and the legal systems raise questions about the extent to which general trust measures capture the same underlying constructs as legal cynicism. Empirically, correlations remain moderate (up to <italic>r</italic> = −.33 for police trust and <italic>r</italic> = −.43 or the justice system), indicating that institutional trust is not simply the inverse of legal cynicism. As global evaluative trust indicators, they remain widely used but are conceptually underspecified, as they do not distinguish between different facets of institutional evaluation such as competence, fairness, integrity, or legitimacy.</p>
<p>The LCS-6 performed largely comparably to the LCS-9 in terms of overall psychometric quality and meaningful associations with external validation criteria. However, the legal legitimacy subscale is largely driven by one stronger indicator, as item LL2 showed a lower factor loading, which is reflected in reduced internal consistency. As a result, this subscale should be interpreted with appropriate caution, as it may be less suitable for applications requiring high reliability, such as individual-level assessment or analyses based on small samples.</p>
<p>The scales provide opportunities to examine how legal cynicism is embedded within broader cultural and social contexts. Although the present study focused on individual-level measurement, future research may investigate the distribution and prevalence of cynical orientations across contextual units such as neighborhoods, social milieus, or other social groups, as well as explore distinct patterns of legal cynicism using person-centered approaches. In this way, the proposed framework may help bridge individual cognitive orientations and broader cultural manifestations of legal cynicism (<xref ref-type="bibr" rid="r24">Seddig, 2026</xref>).</p>
<p>This study has limitations. First, the data were drawn from a convenience sample, which precludes any inference to the German population and may have introduced systematic bias in the estimation of psychometric parameters. Second, the sample was restricted to adolescents and young adults, with a pronounced overrepresentation of female respondents due to attrition between survey waves, limiting the generalizability of the measurement properties across age groups and gender distributions. Third, sample sizes, especially for group comparisons, were relatively small, constraining the stability of more complex models and the precision of parameter estimates. Fourth, the availability of external validation criteria was limited, restricting the scope of construct validation. Moreover, external validation measures exclusively relied on single items, which may have limited the precision and reliability of the validation analyses. Consequently, further research based on larger, more diverse, and preferably probability-based samples is needed to replicate the factor structure, test measurement invariance more rigorously, and extend the nomological network of the short legal cynicism scales.</p>
	<p>Finally, the proposed short versions should be understood as recommended rather than definitive versions of the scale. They were developed to provide efficient measurement while preserving broad coverage of the underlying dimensions. Depending on the specific research question, items from the original full scale may be retained where they provide additional conceptual value. For example, researchers interested in a broader institutional focus within the legal corruption dimension may consider including the item “When you are well connected, the law doesn’t really apply to you,” as it may also refer to actors outside of the legal system. Likewise, if legal legitimacy is intended to capture not only personal acceptance of the law but also beliefs regarding the social enforcement of laws, the item “Society would be a better place if all laws were enforced” may be retained. Viewed in this way, the short forms represent flexible instruments that can be adapted to specific theoretical or empirical objectives while maintaining the conceptual framework of the full scale.</p>
</sec>
</body>
<back><fn-group><fn fn-type="financial-disclosure">
<p>The parent study’s data collection was funded by ProPK (‘Programm Polizeiliche Kriminalprävention der Länder und des Bundes’).</p></fn></fn-group>
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	<sec sec-type="data-availability" id="das"><title>Data Availability</title>
		<p>The data used in the study can be obtained by the author upon reasonable request.</p>
	</sec>	

	
	
	
	<sec sec-type="supplementary-material" id="sp1"><title>Supplementary Materials</title>
		<p>The supplementary materials include a description of the data and items, as well as the R code (lavaan) and output (see <xref ref-type="bibr" rid="sp1_r1">Seddig, 2026</xref>).</p>
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<fn-group>
<fn fn-type="conflict"><p>The author has declared that no competing interests exist.</p></fn>
</fn-group>
<ack>
<p>The author has no additional (i.e., non-financial) support to report.</p>
</ack>
</back>
</article>
