A single-item measure of social identification: Reliability, validity, and utility

doi:10.1111/BJSO.12006

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A single-item measure of social identification: Reliability, validity, and utility

Journal Article•DOI•

A single-item measure of social identification: Reliability, validity, and utility

Tom Postmes¹, S. Alexander Haslam², Lise Jans¹•Institutions (2)

University of Groningen¹, University of Exeter²

01 Dec 2013-British Journal of Social Psychology (Wiley-Blackwell)-Vol. 52, Iss: 4, pp 597-617

TL;DR: This paper introduces a single-item social identification measure (SISI) that involves rating one's agreement with the statement 'I identify with my group (or category)' followed by a 7-point scale.

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Abstract: This paper introduces a single-item social identification measure (SISI) that involves rating one's agreement with the statement 'I identify with my group (or category)' followed by a 7-point scale. Three studies provide evidence of the validity (convergent, divergent, and test-retest) of SISI with a broad range of social groups. Overall, the estimated reliability of SISI is good. To address the broader issue of single-item measure reliability, a meta-analysis of 16 widely used single-item measures is reported. The reliability of single-item scales ranges from low to reasonably high. Compared with this field, reliability of the SISI is high. In general, short measures struggle to achieve acceptable reliability because the constructs they assess are broad and heterogeneous. In the case of social identification, however, the construct appears to be sufficiently homogeneous to be adequately operationalized with a single item.

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Journal Article•DOI•

The consequences of perceived discrimination for psychological well-being: A meta-analytic review.

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Michael T. Schmitt, Nyla R. Branscombe¹, Tom Postmes², Amber L. Garcia³•Institutions (3)

University of Kansas¹, University of Groningen², College of Wooster³

17 Feb 2014-Psychological Bulletin

TL;DR: Results support the idea that the pervasiveness of perceived discrimination is fundamental to its harmful effects on psychological well-being.

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Abstract: In 2 meta-analyses, we examined the relationship between perceived discrimination and psychological well-being and tested a number of moderators of that relationship. In Meta-Analysis 1 (328 independent effect sizes, N = 144,246), we examined correlational data measuring both perceived discrimination and psychological well-being (e.g., self-esteem, depression, anxiety, psychological distress, life satisfaction). Using a random-effects model, the mean weighted effect size was significantly negative, indicating harm (r = -.23). Effect sizes were larger for disadvantaged groups (r = -.24) compared to advantaged groups (r = -.10), larger for children compared to adults, larger for perceptions of personal discrimination compared to group discrimination, and weaker for racism and sexism compared to other stigmas. The negative relationship was significant across different operationalizations of well-being but was somewhat weaker for positive outcomes (e.g., self-esteem, positive affect) than for negative outcomes (e.g., depression, anxiety, negative affect). Importantly, the effect size was significantly negative even in longitudinal studies that controlled for prior levels of well-being (r = -.15). In Meta-Analysis 2 (54 independent effect sizes, N = 2,640), we examined experimental data from studies manipulating perceptions of discrimination and measuring well-being. We found that the effect of discrimination on well-being was significantly negative for studies that manipulated general perceptions of discrimination (d = -.25), but effects did not differ from 0 when attributions to discrimination for a specific negative event were compared to personal attributions (d = .06). Overall, results support the idea that the pervasiveness of perceived discrimination is fundamental to its harmful effects on psychological well-being.

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1,167 citations

Journal Article•DOI•

Effects of the COVID-19 pandemic and nationwide lockdown on trust, attitudes toward government, and well-being.

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Chris G. Sibley¹, Lara M. Greaves¹, Nicole Satherley¹, Marc S. Wilson², Nickola C. Overall¹, Carol H. J. Lee¹, Petar Milojev¹, Joseph Bulbulia¹, Danny Osborne¹, Taciano L. Milfont², Carla A. Houkamau¹, Isabelle M. Duck, Raine Vickers-Jones³, Fiona Kate Barlow³ - Show less +10 more•Institutions (3)

University of Auckland¹, Victoria University of Wellington², University of Queensland³

04 Jun 2020-American Psychologist

TL;DR: The study found that people in the pandemic/lockdown group reported higher trust in science, politicians, and police, higher levels of patriotism, and higher rates of mental distress compared to people inThe prelockdown prepandemic group.

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Abstract: The contagiousness and deadliness of COVID-19 have necessitated drastic social management to halt transmission. The immediate effects of a nationwide lockdown were investigated by comparing matched samples of New Zealanders assessed before (Nprelockdown = 1,003) and during the first 18 days of lockdown (Nlockdown = 1,003). Two categories of outcomes were examined: (a) institutional trust and attitudes toward the nation and government and (b) health and well-being. Applying propensity score matching to approximate the conditions of a randomized controlled experiment, the study found that people in the pandemic/lockdown group reported higher trust in science, politicians, and police, higher levels of patriotism, and higher rates of mental distress compared to people in the prelockdown prepandemic group. Results were confirmed in within-subjects analyses. The study highlights social connectedness, resilience, and vulnerability in the face of adversity and has applied implications for how countries face this global challenge. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

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484 citations

Cites background from "A single-item measure of social ide..."

...…2019), in the early stages of the nationwide lockdown in New Zealand, people reported increased trust in politicians and police, increased satisfaction with the government’s performance, and increased patriotism, as well as within-person increases in national identification (Postmes et al., 2013)....
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..., 2006), and access to health care (Lee & Sibley, 2017); level of identification with New Zealand (Postmes et al., 2013); and patriotism (Kosterman & Feshbach, 1989)....
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...external threats motivate people to band together (Greenaway & Cruwys, 2019), in the early stages of the nationwide lockdown in New Zealand, people reported increased trust in politicians and police, increased satisfaction with the government’s performance, and increased patriotism, as well as within-person increases in national identification (Postmes et al., 2013)....
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...Participants also rated their satisfaction with the economy, business, social conditions, the current government (Tiliouine et al., 2006), and access to health care (Lee & Sibley, 2017); level of identification with New Zealand (Postmes et al., 2013); and patriotism (Kosterman & Feshbach, 1989)....
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Journal Article•DOI•

Social group memberships protect against future depression, alleviate depression symptoms and prevent depression relapse

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Tegan Cruwys¹, Genevieve A. Dingle¹, Catherine Haslam¹, S. Alexander Haslam¹, Jolanda Jetten¹, Thomas A. Morton² - Show less +2 more•Institutions (2)

University of Queensland¹, University of Exeter²

01 Dec 2013-Social Science & Medicine

TL;DR: It is demonstrated that the number of groups that a person belongs to is a strong predictor of subsequent depression, and that the unfolding benefits of social group memberships are stronger among individuals who are depressed than among those who are non-depressed.

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374 citations

Journal Article•DOI•

Depression and Social Identity An Integrative Review

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Tegan Cruwys¹, S. Alexander Haslam¹, Genevieve A. Dingle¹, Catherine Haslam¹, Jolanda Jetten¹ - Show less +1 more•Institutions (1)

University of Queensland¹

12 Apr 2014-Personality and Social Psychology Review

TL;DR: Evidence that social connectedness is key to understanding the development and resolution of clinical depression is presented, and an agenda for future research is presented to advance theoretical and empirical understanding of the link between social identity and depression.

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Abstract: Social relationships play a key role in depression. This is apparent in its etiology, symptomatology, and effective treatment. However, there has been little consensus about the best way to conceptualize the link between depression and social relationships. Furthermore, the extensive social-psychological literature on the nature of social relationships, and in particular, research on social identity, has not been integrated with depression research. This review presents evidence that social connectedness is key to understanding the development and resolution of clinical depression. The social identity approach is then used as a basis for conceptualizing the role of social relationships in depression, operationalized in terms of six central hypotheses. Research relevant to these hypotheses is then reviewed. Finally, we present an agenda for future research to advance theoretical and empirical understanding of the link between social identity and depression, and to translate the insights of this approach into clinical practice.

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329 citations

Journal Article•DOI•

Groups 4 Health: Evidence that a social-identity intervention that builds and strengthens social group membership improves mental health

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Catherine Haslam¹, Tegan Cruwys¹, S. Alexander Haslam¹, Genevieve A. Dingle¹, Melissa Xue-Ling Chang¹ - Show less +1 more•Institutions (1)

University of Queensland¹

01 Apr 2016-Journal of Affective Disorders

TL;DR: G4H was found to significantly improve mental health, well-being, and social connectedness on all measures, both on program completion and 6-month follow-up, and showed that improvements in depression, anxiety, stress, loneliness, and life satisfaction were underpinned by participants' increased identification both with their G4H group and with multiple groups.

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303 citations

Cites methods from "A single-item measure of social ide..."

...The Four-Item measure of Social Identification (FISI; Postmes et al., 2013) was used to index participants' sense of connectedness with their G4H group (e....
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...The Four-Item measure of Social Identification (FISI; Postmes et al., 2013) was used to index participants' sense of connectedness with their G4H group (e.g., “I feel committed to this G4H group”) – G4H being the one group common to all participants and the means via which the intervention was delivered....
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...The Four-Item measure of Social Identification (FISI; Postmes et al., 2013) was used to index participants' sense of connectedness with their G4H group (e.g., “I feel committed to this G4H group”) – G4H being the one group common to all participants and the means via which the intervention was…...
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References

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Journal Article•DOI•

Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives

[...]

Li-tze Hu, Peter M. Bentler¹•Institutions (1)

University of California, Los Angeles¹

01 Jan 1999-Structural Equation Modeling

TL;DR: In this article, the adequacy of the conventional cutoff criteria and several new alternatives for various fit indexes used to evaluate model fit in practice were examined, and the results suggest that, for the ML method, a cutoff value close to.95 for TLI, BL89, CFI, RNI, and G...

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Abstract: This article examines the adequacy of the “rules of thumb” conventional cutoff criteria and several new alternatives for various fit indexes used to evaluate model fit in practice. Using a 2‐index presentation strategy, which includes using the maximum likelihood (ML)‐based standardized root mean squared residual (SRMR) and supplementing it with either Tucker‐Lewis Index (TLI), Bollen's (1989) Fit Index (BL89), Relative Noncentrality Index (RNI), Comparative Fit Index (CFI), Gamma Hat, McDonald's Centrality Index (Mc), or root mean squared error of approximation (RMSEA), various combinations of cutoff values from selected ranges of cutoff criteria for the ML‐based SRMR and a given supplemental fit index were used to calculate rejection rates for various types of true‐population and misspecified models; that is, models with misspecified factor covariance(s) and models with misspecified factor loading(s). The results suggest that, for the ML method, a cutoff value close to .95 for TLI, BL89, CFI, RNI, and G...

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76,383 citations

"A single-item measure of social ide..." refers background in this paper

...Rules of thumb concerning cut-off criteria suggest that TLI andCFI should not be above .95, RMSEAbelow .06, and SRMR below .08 (Hu & Bentler, 1999)....
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Book•

Using multivariate statistics

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Barbara G. Tabachnick, Linda S. Fidell

01 Jan 1983

TL;DR: In this Section: 1. Multivariate Statistics: Why? and 2. A Guide to Statistical Techniques: Using the Book Research Questions and Associated Techniques.

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Abstract: In this Section: 1. Brief Table of Contents 2. Full Table of Contents 1. BRIEF TABLE OF CONTENTS Chapter 1 Introduction Chapter 2 A Guide to Statistical Techniques: Using the Book Chapter 3 Review of Univariate and Bivariate Statistics Chapter 4 Cleaning Up Your Act: Screening Data Prior to Analysis Chapter 5 Multiple Regression Chapter 6 Analysis of Covariance Chapter 7 Multivariate Analysis of Variance and Covariance Chapter 8 Profile Analysis: The Multivariate Approach to Repeated Measures Chapter 9 Discriminant Analysis Chapter 10 Logistic Regression Chapter 11 Survival/Failure Analysis Chapter 12 Canonical Correlation Chapter 13 Principal Components and Factor Analysis Chapter 14 Structural Equation Modeling Chapter 15 Multilevel Linear Modeling Chapter 16 Multiway Frequency Analysis 2. FULL TABLE OF CONTENTS Chapter 1: Introduction Multivariate Statistics: Why? Some Useful Definitions Linear Combinations of Variables Number and Nature of Variables to Include Statistical Power Data Appropriate for Multivariate Statistics Organization of the Book Chapter 2: A Guide to Statistical Techniques: Using the Book Research Questions and Associated Techniques Some Further Comparisons A Decision Tree Technique Chapters Preliminary Check of the Data Chapter 3: Review of Univariate and Bivariate Statistics Hypothesis Testing Analysis of Variance Parameter Estimation Effect Size Bivariate Statistics: Correlation and Regression. Chi-Square Analysis Chapter 4: Cleaning Up Your Act: Screening Data Prior to Analysis Important Issues in Data Screening Complete Examples of Data Screening Chapter 5: Multiple Regression General Purpose and Description Kinds of Research Questions Limitations to Regression Analyses Fundamental Equations for Multiple Regression Major Types of Multiple Regression Some Important Issues. Complete Examples of Regression Analysis Comparison of Programs Chapter 6: Analysis of Covariance General Purpose and Description Kinds of Research Questions Limitations to Analysis of Covariance Fundamental Equations for Analysis of Covariance Some Important Issues Complete Example of Analysis of Covariance Comparison of Programs Chapter 7: Multivariate Analysis of Variance and Covariance General Purpose and Description Kinds of Research Questions Limitations to Multivariate Analysis of Variance and Covariance Fundamental Equations for Multivariate Analysis of Variance and Covariance Some Important Issues Complete Examples of Multivariate Analysis of Variance and Covariance Comparison of Programs Chapter 8: Profile Analysis: The Multivariate Approach to Repeated Measures General Purpose and Description Kinds of Research Questions Limitations to Profile Analysis Fundamental Equations for Profile Analysis Some Important Issues Complete Examples of Profile Analysis Comparison of Programs Chapter 9: Discriminant Analysis General Purpose and Description Kinds of Research Questions Limitations to Discriminant Analysis Fundamental Equations for Discriminant Analysis Types of Discriminant Analysis Some Important Issues Comparison of Programs Chapter 10: Logistic Regression General Purpose and Description Kinds of Research Questions Limitations to Logistic Regression Analysis Fundamental Equations for Logistic Regression Types of Logistic Regression Some Important Issues Complete Examples of Logistic Regression Comparison of Programs Chapter 11: Survival/Failure Analysis General Purpose and Description Kinds of Research Questions Limitations to Survival Analysis Fundamental Equations for Survival Analysis Types of Survival Analysis Some Important Issues Complete Example of Survival Analysis Comparison of Programs Chapter 12: Canonical Correlation General Purpose and Description Kinds of Research Questions Limitations Fundamental Equations for Canonical Correlation Some Important Issues Complete Example of Canonical Correlation Comparison of Programs Chapter 13: Principal Components and Factor Analysis General Purpose and Description Kinds of Research Questions Limitations Fundamental Equations for Factor Analysis Major Types of Factor Analysis Some Important Issues Complete Example of FA Comparison of Programs Chapter 14: Structural Equation Modeling General Purpose and Description Kinds of Research Questions Limitations to Structural Equation Modeling Fundamental Equations for Structural Equations Modeling Some Important Issues Complete Examples of Structural Equation Modeling Analysis. Comparison of Programs Chapter 15: Multilevel Linear Modeling General Purpose and Description Kinds of Research Questions Limitations to Multilevel Linear Modeling Fundamental Equations Types of MLM Some Important Issues Complete Example of MLM Comparison of Programs Chapter 16: Multiway Frequency Analysis General Purpose and Description Kinds of Research Questions Limitations to Multiway Frequency Analysis Fundamental Equations for Multiway Frequency Analysis Some Important Issues Complete Example of Multiway Frequency Analysis Comparison of Programs

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53,113 citations

"A single-item measure of social ide..." refers background in this paper

...We conclude with a practical recommendation for measuring identification (in a Tajfelian sense) where a single dimension suffices. As noted above, such a single dimension is best captured by self-investment. There aremany cases inwhich researchers have the opportunity to include a small number of items. Leach et al. (2008) and the above studies confirm that a specific combination of itemsmeasured byDoosje et al. (1998) and SISI would be a good predictor of the components of self-investment: I feel committed to [In-group] (Doosje et al....
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...We conclude with a practical recommendation for measuring identification (in a Tajfelian sense) where a single dimension suffices. As noted above, such a single dimension is best captured by self-investment. There aremany cases inwhich researchers have the opportunity to include a small number of items. Leach et al. (2008) and the above studies confirm that a specific combination of itemsmeasured byDoosje et al....
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Journal Article•DOI•

A power primer.

[...]

Jacob Cohen¹•Institutions (1)

York University¹

01 Jul 1992-Psychological Bulletin

TL;DR: A convenient, although not comprehensive, presentation of required sample sizes is providedHere the sample sizes necessary for .80 power to detect effects at these levels are tabled for eight standard statistical tests.

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Abstract: One possible reason for the continued neglect of statistical power analysis in research in the behavioral sciences is the inaccessibility of or difficulty with the standard material. A convenient, although not comprehensive, presentation of required sample sizes is provided here. Effect-size indexes and conventional values for these are given for operationally defined small, medium, and large effects. The sample sizes necessary for .80 power to detect effects at these levels are tabled for eight standard statistical tests: (a) the difference between independent means, (b) the significance of a product-moment correlation, (c) the difference between independent rs, (d) the sign test, (e) the difference between independent proportions, (f) chi-square tests for goodness of fit and contingency tables, (g) one-way analysis of variance, and (h) the significance of a multiple or multiple partial correlation.

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38,291 citations

Journal Article•DOI•

lavaan: An R Package for Structural Equation Modeling

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Yves Rosseel

24 May 2012-Journal of Statistical Software

TL;DR: The aims behind the development of the lavaan package are explained, an overview of its most important features are given, and some examples to illustrate how lavaan works in practice are provided.

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Abstract: Structural equation modeling (SEM) is a vast field and widely used by many applied researchers in the social and behavioral sciences. Over the years, many software packages for structural equation modeling have been developed, both free and commercial. However, perhaps the best state-of-the-art software packages in this field are still closed-source and/or commercial. The R package lavaan has been developed to provide applied researchers, teachers, and statisticians, a free, fully open-source, but commercial-quality package for latent variable modeling. This paper explains the aims behind the development of the package, gives an overview of its most important features, and provides some examples to illustrate how lavaan works in practice.

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14,401 citations

"A single-item measure of social ide..." refers methods in this paper

...A series of confirmatory factor analyses were conducted with the package Lavaan (Rosseel, 2012), using maximum likelihood estimation with robust standard errors and Satorra-Bentler scaled test statistics appropriate for smaller samples....
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An integrative theory of intergroup conflict

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Henri Tajfel, John C. Turner¹•Institutions (1)

Australian National University¹

01 Jan 2001

14,106 citations

"A single-item measure of social ide..." refers background in this paper

...Haslam, Oakes, Reynolds, and Turner (1999) use the single-item measure ‘this group is important to me’ as a manipulation check to assess the efficacy of a manipulation of social identity salience....
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...The construct of social identification pertains to a range of topics and issues addressed within social identity theory (Tajfel, 1978; Tajfel & Turner, 1979) and selfcategorization theory (Turner, 1985; Turner, Hogg, Oakes, Reicher & Wetherell, 1987), with adjoining disciplinesmaking considerable…...
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