Are social desirability scales desirable? A meta-analytic test of the validity of social desirability scales in the context of prosocial behavior

On the Utility of Indirect Methods for Detecting Faking

Indirect indices for faking detection in questionnaires make use of a respondent's deviant or unlikely response pattern over the course of the questionnaire to identify them as a faker. Compared with established direct faking indices (i.e., lying and social desirability scales), indirect indices have at least two advantages: First, they cannot be detected by the test taker. Second, their usage does not require changes to the questionnaire. In the last decades, several such indirect indices have been proposed. However, at present, the researcher's choice between different indirect faking detection indices is guided by relatively little information, especially if conceptually different indices are to be used together. Thus, we examined and compared how well indices of a representative selection of 12 conceptionally different indirect indices perform and how well they perform individually and jointly compared with an established direct faking measure or validity scale. We found that, first, the score on the agreement factor of the Likert-type item response process tree model, the proportion of desirable scale endpoint responses, and the covariance index were the best-performing indirect indices. Second, using indirect indices in combination resulted in comparable and in some cases even better detection rates than when using direct faking measures. Third, some effective indirect indices were only minimally correlated with substantive scales and could therefore be used to partial faking variance from response sets without losing substance. We, therefore, encourage researchers to use indirect indices instead of direct faking measures when they aim to detect faking in their data.

Development of a Measure of Anti-Rape Attitudes as a Potential Protective Factor Against Rape Perpetration

The role of attitudes toward women and sexual violence in predicting men's perpetration of rape has been well documented in the literature. While research on rape perpetration has primarily focused on identifying risk factors, the limited understanding of protective factors has hindered the development of psychometric measures to assess attitudinal protective factors. However, comprehending these protective factors is essential for a comprehensive understanding of the risk of rape perpetration and the advancement of strength-based approaches. This research describes the development of a new scale designed to measure anti-rape attitudes (ARA) in young heterosexual men. To generate the initial item pool, relevant information was gathered from sexual violence support service websites and academic literature. This item pool underwent an external expert review for further item generation and cognitive interviews for content validation. This qualitative phase was followed by four quantitative studies for item reduction and scale validation. The resulting 19-item scale demonstrates good internal consistency (Cronbach's α = .84). The ARA scale exhibits strong negative correlations with rape myth acceptance (RMA) and hostile sexism, and strong positive correlations with positive consent attitudes (PCA), supporting the scale's construct validity. We further conducted hierarchical regression analyses to test the unique relationship of ARA with those constructs while controlling for RMA. These showed that ARA have significant, unique associations with PCA and ambivalent sexism. The development of this new scale enables a more comprehensive assessment of the risk of rape perpetration and opens up new avenues for research on protective factors against rape. Ultimately, this study constitutes an important step toward fostering strength-based approaches to combat sexual violence.

Health Workers' Mindfulness-Based Stress Reduction and Resilience During COVID-19 Pandemic

Background

Research indicates that a significant number of healthcare workers accounted for all confirmed Coronavirus disease 2019 (COVID-19) cases, and many of the infected healthcare workers were asymptomatic. During the COVID-19 outbreak, a considerable number of people in Taiwan contracted the disease. Therefore, health workers in Taiwan often experienced lack of medical resources, and this problem is worse for outer island areas. In terms of stress and mental health, this study investigated the effect of poor healthcare capacity and high workload on health workers during the COVID-19 pandemic. This study also explored mindfulness-based stress reduction and resilience in health workers.

Methods

This study conducted an in-depth interview to investigate stress perceived by health workers in a hospital located on an outer island of Taiwan as well as their mental health and stress relieving strategies.

Results

It was found that during the COVID-19 outbreak, some common sources of stress for health workers included exposure to infectious diseases, heavy workloads, facing ethical dilemma in clinical decision-making, and unfamiliar problems from the pandemic. These types of stress cause worries, anxiety, and depression in health workers, which affects their mental and physical health as well as their patient-care performance.

Conclusion

This study proposed that mindfulness-based stress reduction and protecting mental health are important for health workers.

Psychometric assessment of the Runyankole-translated Marlowe-Crowne Social Desirability Scale among persons with HIV in Uganda

BACKGROUND

Social desirability can negatively affect the validity of self-reported measures, including underreporting of stigmatized behaviors like alcohol consumption. The Marlowe-Crowne Social Desirability Scale (SDS) is widely implemented and comprised of Denial and Attribution Domains (i.e., tendencies to deny undesirable traits or attribute socially desirable traits to oneself, respectively). Yet, limited psychometric research has been conducted in sub-Saharan Africa, where the prevalence of unhealthy alcohol consumption is high as well as religiosity and hierarchical social norms. To address this gap, we (a) conducted an exploratory study assessing certain psychometric properties of the 28-item SDS (Runyankole-translated) among persons with HIV (PWH) in Uganda, and (b) examined the relationship between social desirability and self-reported alcohol use.

METHODS

We pooled baseline data (N = 1153) from three studies of PWH engaged in alcohol use from 2017 to 2021. We assessed the translated scale's construct validity (via confirmatory factor analysis), internal consistency, item performance, differential item functioning by gender, concurrent validity with the DUREL religiosity index domains, and the association between social desirability and self-reported alcohol use.

RESULTS

Participants had a mean age of 40.42 years, 63% were men, and 91% had an undetectable HIV viral load. The 28-item SDS had satisfactory construct validity (Model fit indices: RMSEA = 0.07, CFI = 0.84, TLI = 0.82) and internal consistency (Denial Domain ΩTotal = 0.82, Attribution Domain ΩTotal = 0.69). We excluded Item 14 ("I never hesitate to help someone in trouble") from the Attribution Domain, which mitigated differential measurement error by gender and slightly improved the construct validity (Model fit indices: RMSEA = 0.06, CFI = 0.86, TLI = 0.85) and reliability (Attribution Domain ΩTotal = 0.72) of the 27-item modified SDS. Using the 27-item SDS, we found that social desirability was weakly correlated with religiosity and inversely associated with self-reported alcohol use after adjusting for biomarker-measured alcohol use and other confounders (β = -0.05, 95% confidence interval: -0.09 to -0.01, p-value = 0.03).

CONCLUSIONS

We detected and mitigated measurement error in the 28-item Runyankole-translated SDS, and found that the modified 27-item scale had satisfactory construct validity and internal consistency in our sample. Future studies should continue to evaluate the psychometric properties of the Runyankole-translated SDS, including retranslating Item 14 and reevaluating its performance.

Can People With Higher Versus Lower Scores on Impression Management or Self-Monitoring Be Identified Through Different Traces Under Faking?

According to faking models, personality variables and faking are related. Most prominently, people's tendency to try to make an appropriate impression (impression management; IM) and their tendency to adjust the impression they make (self-monitoring; SM) have been suggested to be associated with faking. Nevertheless, empirical findings connecting these personality variables to faking have been contradictory, partly because different studies have given individuals different tests to fake and different faking directions (to fake low vs. high scores). Importantly, whereas past research has focused on faking by examining test scores, recent advances have suggested that the faking process could be better understood by analyzing individuals' responses at the item level (response pattern). Using machine learning (elastic net and random forest regression), we reanalyzed a data set (N = 260) to investigate whether individuals' faked response patterns on extraversion (features; i.e., input variables) could reveal their IM and SM scores. We found that individuals had similar response patterns when they faked, irrespective of their IM scores (excluding the faking of high scores when random forest regression was used). Elastic net and random forest regression converged in revealing that individuals higher on SM differed from individuals lower on SM in how they faked. Thus, response patterns were able to reveal individuals' SM, but not IM. Feature importance analyses showed that whereas some items were faked differently by individuals with higher versus lower SM scores, others were faked similarly. Our results imply that analyses of response patterns offer valuable new insights into the faking process.

Connectome-based prediction of decreased trust propensity in older adults with mild cognitive impairment: A resting-state functional magnetic resonance imaging study

Trust propensity (TP) relies more on social than economic rationality to transform the perceived probability of betrayal into positive reciprocity expectations in older adults with normal cognition. While deficits in social rationality have been observed in older adults with mild cognitive impairment (MCI), there is limited research on TP and its associated resting-state functional connectivity (RSFC) mechanisms in this population. To measure TP and related psychological functions (affect, motivation, executive cognition, and social cognition), MCI (n = 42) and normal healthy control (NHC, n = 115) groups completed a one-shot trust game and additional assessments of related psychological functions. RSFC associated with TP was analyzed using connectome-based predictive modeling (CPM) and lesion simulations. Our behavioral results showed that the MCI group trusted less (i.e., had lower TP) than the NHC group, with lower TP associated with higher sensitivity to the probability of betrayal in the MCI group. In the MCI group, only negative CPM models (RSFC negatively correlated with TP) significantly predicted TP, with a high salience network (SN) contribution. In contrast, in the NHC group, positive CPM models (RSFC positively correlated with TP) significantly predicted TP, with a high contribution from the default mode network (DMN). In addition, the total network strength of the NHC-specific positive network was lower in the MCI group than in the NHC group. Our findings demonstrated a decrease in TP in the MCI group compared to the NHC group, which is associated with deficits in social rationality (social cognition, associated with DMN) and increased sensitivity to betrayal (affect, associated with SN) in a trust dilemma. In conclusion, our study contributes to understanding MCI-related alterations in trust and their underlying neural mechanisms.

Time to level up: A systematic review of interventions aiming to reduce stigma toward autistic people

LAY ABSTRACT

How non-autistic people think about autistic people impacts autistic people negatively. Many studies developed trainings to reduce autism stigma. The existing trainings vary a lot in terms of study design, content, and reported effectiveness. This means that a review studying how the studies have been conducted is needed. We also looked at the quality of these studies. We collected and studied 26 studies that tried to reduce stigma toward autistic people. The studies often targeted White K-12 students and college students. Most trainings were implemented once. Trainings frequently used video or computer. Especially, recent studies tended to use online platforms. The study quality was poor for most studies. Some studies made inaccurate claims about the intervention effectiveness. Studies did not sufficiently address study limitations. Future trainings should aim to figure out why and how interventions work. How intervention changes people's behavior and thoughts should be studied. Researchers should study whether the training can change the societal stigma. Also, researchers should use a better study design.

Public acceptance of default nudges to promote healthy and sustainable food choices

BACKGROUND

Default nudges are an increasingly prominent tool for promoting healthy and sustainable food choices; however, questions of acceptance remain. While default nudges are more acceptable to the public than traditionally paternalistic tools that aim to restrict choice, they are also the least acceptable amongst nudging strategies. Little research has investigated the aspects of default nudge design that can be leveraged to better uphold freedom of choice, increase public acceptance, and therefore heighten legitimacy of default nudges. Consequently, this study examines public acceptance of five food choice default nudges with demonstrated precedent of effectiveness, as drawn from research studies and/or real-world policies, along with a design variation of each anticipated to increase acceptance. Three drivers of acceptance - perceived intrusiveness, perceived effectiveness, and own behavior - are examined.

METHODS

An online survey was administered in Germany (N = 451) to a sample representative of the adult population on quotas of age, gender and income. Acceptance and drivers were measured using seven-point Likert scales. Significant differences in median acceptance of the nudge were determined and displayed graphically. Ten proportional odds ordered logit models were applied and estimated using a maximum likelihood approach to investigate the mechanisms of nudge acceptance.

RESULTS

Examined changes in nudge design, particularly decreasing costliness of opting out and increasing transparency, increased the acceptance of three of the five nudges (N2.2: p = 0.000; N3.2: p = 0.000; N4.2: p = 0.008). Perceived intrusiveness emerged as the most prominent driver of acceptance (negative relationship), followed by perceived effectiveness (positive relationship). Own engagement in the target behavior of the nudge and socio-demographic variables demonstrated negligible impact on acceptance.

CONCLUSIONS

Mitigating the costliness of opting out and improving nudge transparency emerge as key opportunities for choice architects to improve public acceptance, and thereby potentially identify 'sweet spots' in designing default nudges that are both effective and acceptable. The protection of individual freedom of choice and effectiveness are key aspects for choice architects to communicate to increase acceptance.

The effect of survey administration mode on youth mental health measures: Social desirability bias and sensitive questions

Aim

Research on trends in youth mental health is used to inform government policy and service funding decisions. It often uses interviewer-administered surveys, which may be affected by mode effects related to social desirability bias. This study sought to determine the impact of survey administration mode on mental health measures, comparing mode effects for sensitive mental health measures (psychological distress and wellbeing) and non-sensitive (physical activity) measures.

Methods

Data were from two large national community samples of young Australians aged 12-25 years conducted in 2020 (N = 6238) and 2022 (N = 4122), which used both interviewer-administered and self-report modes of data collection.

Results

Results showed participants reported lower psychological distress and higher wellbeing in the interviewer-assisted compared with the self-report mode. No mode effects were found for the non-sensitive physical activity measures. No interaction between mode and gender was found, but an age group by mode interaction revealed that those in the 18-21 and 22-25-year age groups were more strongly affected than younger adolescents.

Conclusions

These findings suggest underestimates of mental health issues from interview survey formats, particularly for young adults. The results show how even a weak mode effect can have a large impact on mental health prevalence indicators. Researchers and policy makers need to be aware of the impact social desirability bias can have on mental health measures and consider taking steps to mitigate this effect.

Objectification decreases prosociality: the mediating role of relative deprivation

Objectification denies individuals' personhood and renders them as tools for facilitating others' goal achievement. With two studies (N = 446), the present investigation aimed to contribute to the literature by testing whether and how objectification impacts prosociality, including prosocial intention and prosocial behavior. Study 1, with a correlational design, aimed to test whether participants with greater experience of objectification would report lower levels of prosociality, and to test whether participants' relative deprivation could account for the proposed association between objectification and prosociality. To further test these associations and provide causal evidence, in Study 2, we manipulated objectification by asking participants to imagine future objectification experiences. These studies converged in support of the negative relationship between objectification and prosocial intention, as well as the mediating role of relative deprivation. Regarding prosocial behavior, our findings support a mediating mechanism between objectification and prosocial behavior, although the evidence for the effect of objectification on prosocial behavior is not sufficient. These findings enrich our understanding of the consequences of objectification, while highlighting interpersonal processes' contribution to prosocial intention and behavior. The limitations and potential future directions were discussed.

Individual differences in self-reported lie detection abilities

Previous literature on lie detection abilities bears an interesting paradox. On the group level, people detect others' lies at guessing level. However, when asked to evaluate their own abilities, people report being able to detect lies (i.e., self-reported lie detection). Understanding this paradox is important because decisions which rely on credibility assessment and deception detection can have serious implications (e.g., trust in others, legal issues). In two online studies, we tested whether individual differences account for variance in self-reported lie detection abilities. We assessed personality traits (Big-Six personality traits, Dark Triad), empathy, emotional intelligence, cultural values, trust level, social desirability, and belief in one's own lie detection abilities. In both studies, mean self-reported lie detection abilities were above chance level. Then, lower out-group trust and higher social desirability levels predicted higher self-reported lie detection abilities. These results suggest that social trust and norms shape our beliefs about our own lie detection abilities.

Antibiotic Misuse Behaviours of Older People: Confirmation of the Factor Structure of the Antibiotic Use Questionnaire

Antibacterial resistance (AR) is responsible for steadily rising numbers of untreatable bacterial infections, most prevalently found in the older adult (OA) population due to age-related physical and cognitive deterioration, more frequent and long-lasting hospital visits, and reduced immunity. There are currently no established measures of antibiotic use behaviours for older adults, and theory-informed approaches to identifying the drivers of antibiotic use in older adults are lacking in the literature. The objective of this study was to identify predictors of antibiotic use and misuse in older adults using the Antibiotic Use Questionnaire (AUQ), a measure informed by the factors of the Theory of Planned Behaviour (TPB): attitudes and beliefs, social norms, perceived behavioural control, behaviour, and a covariate-knowledge. A measure of social desirability was included, and participants scoring highly were excluded to control for social desirability bias. Confirmatory Factor Analyses and regression analyses were conducted to test the hypotheses in a cross-sectional, anonymous survey. A total of 211 participants completed the survey, 47 of which were excluded due to incompletion and high social desirability scores (≥5). Results of the factor analysis confirmed that some (but not all) factors from previous research in the general population were confirmed in the OA sample. No factors were found to be significant predictors of antibiotic use behaviour. Several suggestions for the variance in results from that of the first study are suggested, including challenges with meeting requirement for statistical power. The paper concludes that further research is required to determine the validity of the AUQ in an older adult population.

Lying on the Dissection Table: Anatomizing Faked Responses

Research has shown that even experts cannot detect faking above chance, but recent studies have suggested that machine learning may help in this endeavor. However, faking differs between faking conditions, previous efforts have not taken these differences into account, and faking indices have yet to be integrated into such approaches. We reanalyzed seven data sets (N = 1,039) with various faking conditions (high and low scores, different constructs, naïve and informed faking, faking with and without practice, different measures [self-reports vs. implicit association tests; IATs]). We investigated the extent to which and how machine learning classifiers could detect faking under these conditions and compared different input data (response patterns, scores, faking indices) and different classifiers (logistic regression, random forest, XGBoost). We also explored the features that classifiers used for detection. Our results show that machine learning has the potential to detect faking, but detection success varies between conditions from chance levels to 100%. There were differences in detection (e.g., detecting low-score faking was better than detecting high-score faking). For self-reports, response patterns and scores were comparable with regard to faking detection, whereas for IATs, faking indices and response patterns were superior to scores. Logistic regression and random forest worked about equally well and outperformed XGBoost. In most cases, classifiers used more than one feature (faking occurred over different pathways), and the features varied in their relevance. Our research supports the assumption of different faking processes and explains why detecting faking is a complex endeavor.

Only the good cry: Investigating the relationship between crying proneness and moral judgments and behavior