Methods of Coping With Social Desirability Bias a Review

Introduction

The majority of inquiry on people's environmental behavior and its antecedents and consequences is conducted using surveys where people self-report their actions, beliefs, attitudes, and other sociopsychological variables (Lange and Dewitte, 2019). For a behavior that is morally relevant, such as proenvironmental behavior, it is not unlikely that people bias their responses to achieve a better social impression of themselves (e.k., Kaiser et al., 1999). This raises the question of how reliable inquiry on ecology behavior and its antecedents is. Being prone to social desirability in answering survey questions may potentially bias people'due south answers to a degree where the accurateness and practical relevance of the findings is threatened.

Consequently, social desirability has been often viewed as a potential confounding variable in ecology psychology enquiry (Kaiser et al., 1999; Bruni and Schultz, 2010; Cerri et al., 2019). On the other paw, there is also bear witness suggesting that social desirability may only play a relatively pocket-sized function (due east.g., Milfont, 2009; O'Brien et al., 2018; see as well McGrath et al., 2010; Paunonen and LeBel, 2012). The chore of the present meta-analyses is therefore to systematically evaluate existing research on the links between social desirability and diverse central measures used in ecology psychology studies, in particular self-reported behavior, intention, and a number of full general attitudinal measures similar the New Ecology Paradigm (Dunlap and Van Liere, 1978; Dunlap et al., 2000) and connectedness to nature (Mayer and Frantz, 2004; Tam, 2013a).

Social desirability can be understood as research participants' tendency to bias their responses in surveys and experiments in order to appear in a more favorable low-cal (Crowne and Marlowe, 1960). A typical example is participants reporting that they regularly sort and recycle household waste product fifty-fifty if this is not in fact true. This type of misreporting may and so in function account for the often observed mismatch betwixt self-reported and observed proenvironmental behavior (see Kormos and Gifford, 2014). The reasons underlying such biased responding primarily include the avoidance of negative social sanctions like disapproval and ostracism and the seeking of social rewards similar approval and higher social condition (Crowne and Marlowe, 1960, 1964; Rasinski et al., 1999). However, since participants' responses are often anonymous, this could in part dispel social desirability bias by eliminating opportunities for subsequent social sanctioning (Paulhus, 1984; Lautenschlager and Flaherty, 1990; Joinson, 1999; Dodou and de Winter, 2014; but see Singer et al., 1992; Fox and Schwartz, 2002). On the other hand, people are implicitly attuned even to subtle cues of ascertainment, then the mere presence of an experimenter or other participants may feasibly trigger some level of socially desirable responding despite explicit assurances of anonymity (encounter Hoffman et al., 1996; Haley and Fessler, 2005).

In that location are several means in which socially desirable responding may potentially bear on findings, such as adding dissonance to information, increasing or decreasing mean scores, constraining the variability of responses, and inflating, suppressing, and moderating correlations betwixt variables (Ganster et al., 1983; Kaiser et al., 2008; Bruni and Schultz, 2010; Paunonen and LeBel, 2012; Zhang W. Z. et al., 2014). Recognizing the potentially serious consequences of social desirability bias, a number of dissimilar methods how to accost information technology have been proposed, but each of them has limitations of their own: Other-reported measures (obtained past gathering information on the target individuals' behavior and characteristics from tertiary-party observers), for example, may endure from the observer not beingness able to properly detect the target's behavior (Chao and Lam, 2011; Grønhøj and Thøgersen, 2012; Matthies et al., 2012; Seebauer et al., 2017). Implicit measures may fail to fully capture conscious attitudes and behavior that also come to play when making actual decisions (see Bruni and Schultz, 2010; Thomas and Walker, 2016; Brick and Lai, 2018). The indirect questioning technique (where participants' beliefs nigh others' behavior are treated every bit a proxy for self-reports of participants' own behavior) can be said to in role tap perceived descriptive norms, rather than to indirectly measure own behavioral tendencies (see, e.g., Lusk and Norwood, 2010; Klaiman et al., 2016). The telescopic of behaviors and behavior that tin be assessed through incentivized and objective measures is restricted (Schultz et al., 2007; Juhl et al., 2017; Vesely and Klöckner, 2018). For boosted approaches of coping with social desirability bias, see, e.1000., Warner (1965); Paulhus (1981); Nederhof (1985); Krumpal (2013); Korndörfer et al. (2014).

Another major way of dealing with social desirability bias is to mensurate the tendency a person has for responding in a socially desirable way and use this as a control variable in survey studies to adjust results for the private bias. In this work, we focus specifically on such questionnaire measures of social desirability, for case the seminal scales due to Crowne and Marlowe (1960) and Paulhus (1991). Research in several other domains—for example, personality psychology, piece of work and organizational psychology, and wellness-related enquiry—employs these instruments to find socially desirable responding (e.grand., Ones et al., 1996; Li and Bagger, 2006; van de Mortel, 2008; Bäckström et al., 2009; Davis et al., 2010; Zemore, 2012). An advantage of questionnaire measures is that they tap social desirability straight and allow subsequent partialling out of this variable in statistical analyses (meet, e.yard., Davis et al., 2009; Howell et al., 2011; Tam, 2013b; Cojuharenco et al., 2016). In dissimilarity, when comparing, for example, cocky-reported, other-reported, and observed behaviors (Corral-Verdugo, 1997; Chao and Lam, 2011; Kormos and Gifford, 2014) or incentivized and nonincentivized responses (Camerer and Hogarth, 1999), isolating the effect of social desirability is ofttimes non straightforward, equally other factors, including inattention and imperfect recall, may account for some of the differences betwixt the compared written report variables (see Hough et al., 1990; Oppenheimer et al., 2009; Meade and Craig, 2012).

The inclusion of social desirability measures in environmental psychological research has besides some other reward that we are going to utilize in our study. It allows to quantify if there actually is a confound of measures of proenvironmental behavior or its predictors with social desirability. In other words, we can test if people more prone to social desirability are scoring systematically unlike on the beliefs-related variables than people with lower social desirability scores. Since a growing number of studies of proenvironmental behavior also include social desirability measures (even if the number of studies is still restricted), we deem the time right for testing the hypothesis of a significantly positive relation betwixt social desirability and self-reports of proenvironmental beliefs, attitudes, and intentions in a meta-analytical setting. To our knowledge, such a meta-report has not been conducted before, so we provide valuable noesis on a question of high importance for the interpretation of many studies in environmental psychology.

Method

Inclusion Criteria

The following criteria were practical to select studies for inclusion in our meta-analyses:

(1) The study had to be published in a scientific periodical or in an edited book in English language.

(ii) The study had to include at to the lowest degree 1 of the following measures: (a) environmentally relevant behavior, (b) environmentally relevant behavioral intention, (c) environmentally relevant attitudinal measure (broadly defined), which, for our purposes, encompasses specifically whatsoever of the post-obit measures: environmental mental attitude, environmental concern, environmental or ecological worldview, biospheric values, connexion to nature, and environmental identity. As for our treatment of the "attitudinal measures," nosotros decided to group these conceptually related, albeit distinct, variables together due to limited data availability (for example, only four relevant studies included a connectedness to nature mensurate). We practise non wish to imply that these variables measure the same construct (meet, e.g., Kaiser et al., 2013). The many similarities and substantial empirical associations among these measures may notwithstanding justify grouping them together for the present purposes (see, e.chiliad., Milfont and Duckitt, 2010; Kaiser et al., 2013; Martin and Czellar, 2017).

(3) The study had to include a measure out of social desirability.

(4) Correlation(s) between the respective environmentally relevant measures and the social desirability scale, forth with the associated sample size on which the correlation(due south) were based, had to be reported in the paper or be available upon request from the author(southward) of the respective article.

Literature Search and Selection of Studies

Literature Search

We located papers potentially relevant for our analyses using four search strategies:

(1) The first strategy consisted of searching the Spider web of Science database platform using a combination of search terms such as "social^* desirab^*," "proenvironmental," and "environmentally conscious." The verbal search string nosotros used is reproduced in Appendix. This way, we located 19,141 potentially relevant papers.

(two) Side by side, nosotros scanned full texts of all papers published in Journal of Ecology Psychology and Environment and Behavior between the years 2000 and 2019 and in Frontiers in Psychology: Ecology Psychology between the years 2016 and 2019. This mode, we identified 15 additional potentially relevant papers.

(3) The third search strategy consisted of ancestry and descendancy searches. This yielded 21 additional potentially relevant papers.

(four) Finally, we included eleven additional potentially relevant papers previously known to the authors.

Pick of Studies

In the adjacent stride, nosotros screened the abstracts of all papers located via the above search strategies, retaining those papers that could not be unequivocally excluded based on the inclusion criteria presented in Inclusion Criteria. This resulted in a selection of 211 potentially relevant papers. Full texts of all these papers were then inspected to determine whether they met our inclusion criteria. 20-nine papers did¹.

Overview of Analysis

Several studies, for example O'Brien et al. (2018), contained multiple relevant "outcome variables" (i.e., ecology beliefs, ecology intention, or ecology mental attitude, see Inclusion Criteria) or multiple measures of social desirability (east.g., Haws et al., 2014). To ensure independence of observations included in a meta-analysis (Hunter and Schmidt, 1990), we therefore conducted three dissever meta-analyses, with each of the outcome variables (intention, behavior, and mental attitude) studied separately. Furthermore, when a study contained multiple outcome variables of the aforementioned type (such equally two dissimilar intention measures) or multiple social desirability measures, we aggregated the respective correlations following the shifting unit of analysis method proposed past Cooper (1998).

Post-obit these procedures, we arrived at the prepare of correlations extracted from primary studies, which are listed in Table ane in Results. There, nosotros also report correlations corrected for measurement error attenuation (Spearman, 1904). When reliabilities were not reported or when unmarried-item scales were used, we assigned a reliability value of ane in order to compute the corrected correlation (Manning, 2009).

Table 1. Overview of studies included in the meta-analyses.

Before estimating the population effect size, nosotros converted the correlations from chief studies to a standard normal metric using Fisher r-to-Z transformation (Hedges and Olkin, 1985). The population Z scores that nosotros obtained were then transformed back to r. We obtained the estimate of the correlation size in the population from which the observations (here, correlations extracted from primary studies) were drawn by estimating a random effects model. Random effects models assume the presence of unidentified sources of variance that are randomly distributed across studies (due east.chiliad., due to different procedures used to collect data). This supposition was supported by a series of highly significant Q tests (reported in Table ii below), which refuse homogeneity in correlations across studies included in a given meta-analysis. Pooled correlations were estimated by weighing the observations past the inverse of a variance term including both their inside- and between-report variance components (DerSimonian and Laird, 1986; Hedges and Vevea, 1998).

Table 2. Pooled correlations with social desirability.

Results

For each of our three meta-analyses (with proenvironmental beliefs, proenvironmental intention, and proenvironmental mental attitude, respectively, serving as the outcome variable), Tabular array i lists the number of correlations from primary studies included in the meta-analysis (k), along with a more detailed information on the actual studies included, the correlations with social desirability extracted from each report (r), the correlations with social desirability corrected for measurement mistake attenuation (r _c, computed co-ordinate to Spearman, 1904), and the number of participants on which the corresponding within-study correlations are based (due north)^two.

Table ii presents the master results. In the upper half of the table, we report calculations based on correlations not corrected for measurement error attenuation, while the lower part of the table presents calculations based on correlations corrected for measurement error attenuation (which are more often than not slightly larger). In the tertiary cavalcade, we report population estimates of the size of the correlation betwixt social desirability and the respective upshot variable (listed in the second column), with 95% conviction intervals in brackets. As i can run across, the pooled correlations are all small. All correlations are withal statistically significantly larger than nothing.

In the concluding cavalcade of Tabular array 2, nosotros report Cochran'due south Q. A meaning Q statistic suggests the presence of heterogeneity in upshot sizes beyond studies within a given meta-analysis. This might indicate the influence of moderator variables that render the effects relatively more pronounced in sure cases. However, due to the relatively pocket-sized number of studies included in each meta-analysis, we decided against performing moderator analyses.

Conclusions

Our meta-analyses of existing testify on the links betwixt social desirability and proenvironmental behaviors, intentions, and (broadly defined) attitudes prove the furnishings of social desirability to be pocket-sized (Cohen, 1988; Richard et al., 2003). Information technology does not follow, however, that environmental psychologists should simply ignore social desirability issues as a result. Commencement of all, the evidence available up to appointment is somewhat sparse, and futurity studies incorporating social desirability scales would be valuable in social club to gain more than robust and refined insights. The scarcity of available evidence, for example, does not allow us to draw any firm conclusions with respect to the blazon of self-reported ecology behaviors that may be comparatively more prone to socially desirable responding. Presumably, this might business peculiarly behaviors, the operation of which is more strongly associated with social sanctions and social status (Griskevicius et al., 2010; Brooks and Wilson, 2015).

A 2nd important indicate to make is that social desirability may bias responses obtained from dissimilar people in reverse directions, which could in turn attenuate the overall correlation that nosotros observe. For case, people holding proenvironmental beliefs may bias their self-reported behavior upwards, while people holding less proenvironmental or even antienvironmental convictions may underreport their sustainable behaviors (Brick et al., 2017). To shed more than light on this hypothesis of social desirability steering responses of dissimilar types of people in opposite directions, future studies can include social and personal norms (eastward.one thousand., Thøgersen, 2006) and identity variables (e.chiliad., Whitmarsh and O'Neill, 2010) every bit potential moderators of the links between social desirability and relevant cocky-reported measures.

Information technology is also possible that popular social desirability scales (Crowne and Marlowe, 1960; Paulhus, 1991) are too general in their focus to fully capture socially desirable response tendencies specific to contexts studied in environmental psychology and related disciplines. A promising arroyo to help address this issue may be the development of social desirability scales tailor-fabricated for the specific context at hand (encounter Ewert and Galloway, 2009 for an initial step in this direction).

Even so another subtle fashion in which social desirability may operate is by influencing the level of consistency among different elicited responses (Ganster et al., 1983; Hough et al., 1990; Milfont, 2009; Oerke and Bogner, 2013). Merely looking at the correlation between an result variable and social desirability would not pick up this blazon of bias: one needs to look at the manner in which social desirability may interact with a predictor in determining the dependent variable (cf. Milfont, 2009; Oerke and Bogner, 2013).

Our results suggest that it is unlikely that controlling for social desirability lone would be plenty to obtain entirely unbiased attitudinal and behavioral measures. Futurity research in environmental psychology should therefore pay increased attention also to other so far often neglected sources of measurement fault, such as imperfect recollect, lack of comprehension, and careless responding (for examples of studies attempting to address some of these issues, see Bissing-Olson et al., 2016; Brick and Lewis, 2016; Cojuharenco et al., 2016; Gorissen and Weijters, 2016; Hahnel and Brosch, 2018).

In conclusion, the present meta-analyses provide a reliable assessment of available testify on social desirability effects in environmental psychology. The effects are minor, but we recommend including social desirability scales as control variables in ecology psychology studies to enhance internal validity and to generate more information that can be later used to evaluate likewise possible subtle effects of social desirability discussed earlier in this department (e.grand., social desirability concerns leading some people to overreport, but others to underreport their ecology behavior, cf. Brick et al., 2017).

Data Availability Statement

All datasets presented in this study are included in the commodity/supplementary material.

Author Contributions

Both authors contributed to all aspects of this piece of work (pattern, assay, and writing).

Funding

Open access fees for this article are covered by Norwegian University of Science and Technology's Publishing Fund.

Disharmonize of Interest

The authors declare that the research was conducted in the absenteeism of any commercial or financial relationships that could be construed as a potential conflict of interest.

Footnotes

1. ^To avoid double counting, nosotros dropped the paper by Hartig et al. (2001) from the analysis, despite coming together our inclusion criteria, since the same data were likewise reported in Kaiser et al. (1999), a newspaper that we include.

ii. ^In a few instances when additional data non reported in the original article was requested from the authors, the data we obtained differed slightly from what the data would have looked liked if it was possible to reproduce the analyses exactly every bit they were performed in the original article. For case, data on the exact data cleaning procedures used in the original commodity may have been no longer available to the authors of the original article, and thus, the additional analyses they sent us may take been based on a slightly larger or smaller sample than the analyses reported in their original commodity. All the same, it seems unlikely that this could bias our results.

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Appendix

Search String Used to Search the Web of Science Database

TS = (("social* desirab*" OR desirab* OR charade OR deceive OR misreport* OR overreport* OR misrepresent* OR distort* OR denial OR acquiesc* OR "impression direction" OR self-disclosure OR disclos* OR self-enhancement OR Edwards OR Marlowe-Crowne OR Crowne-Marlowe OR Paulhus OR Wiggins OR MCSD OR MC-SD OR MCSDS OR MC-SDS OR BIDR OR RD-16) AND (saving OR save OR conserv* OR preserv* OR consum* OR proenvironmental OR environment* friendly OR "environmentally conscious" OR "environmentally responsible" OR ecological OR sustain* OR reuse OR greenish OR renewable OR PEB OR GEB OR recycl* OR waste OR energy OR electricity OR h2o OR purchas* OR travel OR send* OR "organic nutrient" OR "local food" OR meat OR mobility OR "car use" OR activis* OR "climate modify" OR "global warming" OR mitigat* OR value-belief-norm OR "value belief norm" OR VBN OR "comprehensive action determination model" OR CADM)) Refined by: Spider web OF SCIENCE CATEGORIES: (Management OR ECOLOGY OR ENVIRONMENTAL SCIENCES OR Dark-green SUSTAINABLE Science Engineering OR Economics OR MULTIDISCIPLINARY SCIENCES OR PSYCHOLOGY MULTIDISCIPLINARY OR BUSINESS OR SOCIAL SCIENCES INTERDISCIPLINARY OR ENVIRONMENTAL STUDIES OR Nutrition DIETETICS) Timespan: All years. Indexes: SCI-EXPANDED, SSCI, A&HCI, CPCI-Southward, CPCI-SSH, ESCI.

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Source: https://www.frontiersin.org/articles/10.3389/fpsyg.2020.01395/full

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