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Misplaced Intuitions in Interventions to Reduce Attractiveness-Based Discrimination.

ABSTRACT: Individuals and organizations are increasing efforts to address discrimination. Nonexperts may lack awareness of, or are resistant to, scientifically informed strategies for reducing discrimination, instead relying on intuition. Five studies investigated the accuracy of nonexperts' intuitions about reducing discrimination concerning physical attractiveness. In Studies 1a to 1c (N = 902), participants predicted the effectiveness of six interventions to reduce attractiveness-based favoritism on a judgment task. Studies 2a and 2b (N = 6,292) investigated the effectiveness of these interventions. Although two interventions reduced discrimination, intuitions were poorly aligned with actual results; fewer than 1% of participants identified the combination of interventions that did, versus did not, impact judgment, and responses were more likely to be below than above chance when predicting each intervention's effectiveness. Although follow-up work should investigate the accuracy of intuition in other forms of discrimination, these results further stress the need for greater development and adoption of evidence-based strategies for combating discrimination.

SUBMITTER: Axt JR

PROVIDER: S-EPMC9989229 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature

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Misplaced Intuitions in Interventions to Reduce Attractiveness-Based Discrimination.

Axt Jordan R JR Yang Juanyu J Deshpande Harshadaa H

Personality & social psychology bulletin 20220218 4

Individuals and organizations are increasing efforts to address discrimination. Nonexperts may lack awareness of, or are resistant to, scientifically informed strategies for reducing discrimination, instead relying on intuition. Five studies investigated the accuracy of nonexperts' intuitions about reducing discrimination concerning physical attractiveness. In Studies 1a to 1c (<i>N</i> = 902), participants predicted the effectiveness of six interventions to reduce attractiveness-based favoritis ...[more]

PMID: 35179056

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Project description:BackgroundDespite a publicly funded system, health care in Canada has been shown to be deeply inequitable, particularly toward Indigenous people. Based on research identifying key dimensions of equity-oriented health care as being cultural safety, harm reduction and trauma- and violence-informed care, an intervention to promote equity at the organizational level was tested in primary health care, refined and adapted, and tested in Emergency Departments (EDs).MethodsIn partnership with clinical, community and Indigenous leaders in three diverse EDs in one Canadian province, we supported direct care staff to tailor and implement the intervention. Intervention activities varied in type and intensity at each site. Survey data were collected pre- and post-intervention from every consecutive patient over age 18 presenting to the EDs (n = 4771) with 3315 completing post-visit questions in 4 waves at two sites and 3 waves (due to pandemic constraints) at the third. Administrative data were collected for 12 months pre- and 12 months post-intervention.ResultsThroughout the study period, the participating EDs were dealing with a worsening epidemic of overdoses and deaths related to a toxic drug supply, and the COVID 19 pandemic curtailed both intervention activities and data collection. Despite these constraints, staff at two of the EDs mounted equity-oriented intervention strategies; the other site was experiencing continued, significant staff shortages and leadership changeover. Longitudinal analysis using multiple regression showed non-significant but encouraging trends in patient perceptions of quality of care and patient experiences of discrimination in the ED. Subgroup analysis showed that specific groups of patients experienced care in significantly different ways at each site. An interrupted time series of administrative data showed no significant change in staff sick time, but showed a significant decrease in the percentage of patients who left without care being completed at the site with the most robust intervention activities.ConclusionsThe trends in patient perceptions and the significant decrease in the percentage of patients who left without care being completed suggest potential for impact. Realization of this potential will depend on readiness, commitment and resources at the organizational and systems levels.Trial registrationClinical Trials.gov #NCT03369678 (registration date November 18, 2017).

Project description:ObjectiveOutpatient no-shows have important implications for costs and the quality of care. Predictive models of no-shows could be used to target intervention delivery to reduce no-shows. We reviewed the effectiveness of predictive model-based interventions on outpatient no-shows, intervention costs, acceptability, and equity.Materials and methodsRapid systematic review of randomized controlled trials (RCTs) and non-RCTs. We searched Medline, Cochrane CENTRAL, Embase, IEEE Xplore, and Clinical Trial Registries on March 30, 2022 (updated on July 8, 2022). Two reviewers extracted outcome data and assessed the risk of bias using ROB 2, ROBINS-I, and confidence in the evidence using GRADE. We calculated risk ratios (RRs) for the relationship between the intervention and no-show rates (primary outcome), compared with usual appointment scheduling. Meta-analysis was not possible due to heterogeneity.ResultsWe included 7 RCTs and 1 non-RCT, in dermatology (n = 2), outpatient primary care (n = 2), endoscopy, oncology, mental health, pneumology, and an magnetic resonance imaging clinic. There was high certainty evidence that predictive model-based text message reminders reduced no-shows (1 RCT, median RR 0.91, interquartile range [IQR] 0.90, 0.92). There was moderate certainty evidence that predictive model-based phone call reminders (3 RCTs, median RR 0.61, IQR 0.49, 0.68) and patient navigators reduced no-shows (1 RCT, RR 0.55, 95% confidence interval 0.46, 0.67). The effect of predictive model-based overbooking was uncertain. Limited information was reported on cost-effectiveness, acceptability, and equity.Discussion and conclusionsPredictive modeling plus text message reminders, phone call reminders, and patient navigator calls are probably effective at reducing no-shows. Further research is needed on the comparative effectiveness of predictive model-based interventions addressed to patients at high risk of no-shows versus nontargeted interventions addressed to all patients.

Dataset Information

Misplaced Intuitions in Interventions to Reduce Attractiveness-Based Discrimination.

Publications

Misplaced Intuitions in Interventions to Reduce Attractiveness-Based Discrimination.

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