The role of alternative hypotheses in reducing bias in forensic medical experts' decision making.

Medical opinions are often essential evidence in criminal cases but relatively little is known about the factors that impact forensic doctors' decision making. This research examines the role and impact of having an alternative hypothesis while forming a medical opinion. A scenario-based experiment with forensic doctors (n = 20) was conducted. In two out of three scenarios, the existence of alternative hypotheses impacted the actual opinions reached, the confidence in the judgments and the perceived consistency with the plaintiff hypothesis. Investigative and legal actors should be aware of the possibility of biases and importance of having alternative hypotheses when requesting and evaluating medical opinions.

The most consistent finding in forensic science is inconsistency.

The most consistent finding in many forensic science domains is inconsistency (i.e., lack of reliability, reproducibility, repeatability, and replicability). The lack of consistency is a major problem, both from a scientific and a criminal justice point of view. Examining forensic conclusion data, from across many forensic domains, highlights the underlying cognitive issues and offers a better understanding of the issues and challenges. Such insights enable the development of ways to minimize these inconsistencies and move forward. The aim is to highlight the problem, so that it can be minimized and the reliability of forensic science evidence can be improved.

History information management strategy for minimising biases and noise for improved medical diagnosis.

Despite measures for physicians' excellence in diagnosis, the need for improvement of medical history techniques has been pointed out as one of the critical elements for improving diagnosis. Specific and proactive frameworks related to methods of effective history acquisition are needed to minimise bias and optimise decision-making. Therefore, this paper uses Linear Sequential Unmasking- Expanded to develop and propose a structured medical history acquisition strategy. The strength of this lies in its reliance on cognitive psychological processes. Breaking information gatherings and decisions into smaller tasks and ordering them correctly reduces cognitive load as well as minimises noise and bias cascade. Additionally, this approach can help physicians develop diagnostic expertise regardless of specialty.

Measuring base-rate bias error in workplace safety investigators.

INTRODUCTION: This study explored the magnitude of professional industrial investigators' bias to attribute cause to a person more readily than to situational factors (i.e., human error bias). Such biased opinions may relieve companies from responsibilities and liability, as well as compromise efficacy of suggested preventative measures. METHOD: Professional investigators and undergraduate participants were given a summary of a workplace event and asked to allocate cause to the factors they found causal for the event. The summary was crafted to be objectively balanced in its implication of cause equally between two factors: a worker and a tire. Participants then rated their confidence and the objectivity of their judgment. We then conducted an effect size analysis, which supplemented the findings from our experiment with two previously published research studies that used the same event summary. RESULTS: Professionals exhibited a human error bias, but nevertheless believed that they were objective and confident in their conclusions. The lay control group also showed this human error bias. These data, along with previous research data, revealed that, given the equivalent investigative circumstances, this bias was significantly larger with the professional investigators, with an effect size of dunb = 0.97, than the control group with an effect size of only dunb = 0.32. CONCLUSIONS: The direction and strength of the human error bias can be quantified, and is shown to be larger in professional investigators compared to lay people. PRACTICAL APPLICATIONS: Understanding the strength and direction of bias is a crucial step in mitigating the effects of the bias. The results of the current research demonstrate that mitigation strategies such as proper investigator training, a strong investigation culture, and standardized techniques, are potentially promising interventions to mitigate human error bias.

A method to induce stress in human subjects in online research environments.

This paper presents a method to induce stress in human subjects during online participation in research studies without the presence of researchers. In this study, participants in the stress-inducing condition (N = 52, 44%) were asked to answer general knowledge and mathematical questions which people often get wrong, and did so under time pressure as well as receiving feedback. In contrast, participants in the control condition (N = 66, 56%) did not have time pressure or receive feedback. The stress manipulation was found to be effective, as the reported state anxiety and visual analog scale on stress scores were higher for the stress group than for the non-stress group (both findings, p < 0.001). Consistent findings were found when accounting for trait anxiety as a moderator, with the exception of the state anxiety levels in high trait anxiety group. This stressing method combines the established stress conditions of uncontrollability (such as time pressures) and social evaluative threats (such as negative feedback). In addition, the method contains specific measures (such as a commitment statement and attention check questions) to enhance the internal validity by preventing and detecting cheating or random responses. This method can be deployed through any commonly available online software. It offers a simple and cost-effective way to collect data online - which fits the increasing need to carry out research in virtual and online environments.

Contextual information in medicolegal death investigation decision-making: Manner of death determination for cases of a single gunshot wound.

To explore the role of contextual information in determining manner of death, four cases involving single gunshot wounds were presented to participants (n = 252) involved in medicolegal death investigation. The participants received identical autopsy information but different contextual information. The data demonstrated that participants tended to rely on contextual information more than autopsy information: In the suicide context, participants across the four cases reached 153 final decisions of suicide (and 25 of homicide), whereas in the homicide context, participants reached only 10 final decisions of suicide (and 181 of homicide) --all while examining identical autopsy information. The impact of the contextual information was so powerful that many participants changed initial autopsy-based conclusions to align with the contextual information. Given the significant role and impact that contextual information has on expert decision making, one must consider what, how, and when contextual information should be used.

Human and machine similarity judgments in forensic firearm comparisons.

It is unclear whether humans assess similarity differently than automated algorithms in firearms comparisons. Human participants (untrained in firearm examination) were asked to assess the similarity of pairs of images (from 0 to 100). A sample of 40 pairs of cartridge casing 2D-images was used. The images were divided into 4 groups according to their similarity as determined by an algorithm. Humans were able to distinguish between matches and non-matches (both when shown the 2 middle groups, as well as when shown all 4 groups). Thus, humans are able to make high-quality similarity judgments in firearm comparisons based on two images. The humans' similarity scores were superior to the algorithms' scores at distinguishing matches and non-matches, but inferior in assessing similarity within groups. This suggests that humans do not have the same group thresholds as the algorithm, and that a hybrid human-machine approach could provide better identification results than humans or algorithms alone.

Statistical feature training improves fingerprint-matching accuracy in novices and professional fingerprint examiners.

Forensic science practitioners compare visual evidence samples (e.g. fingerprints) and decide if they originate from the same person or different people (i.e. fingerprint 'matching'). These tasks are perceptually and cognitively complex-even practising professionals can make errors-and what limited research exists suggests that existing professional training is ineffective. This paper presents three experiments that demonstrate the benefit of perceptual training derived from mathematical theories that suggest statistically rare features have diagnostic utility in visual comparison tasks. Across three studies (N = 551), we demonstrate that a brief module training participants to focus on statistically rare fingerprint features improves fingerprint-matching performance in both novices and experienced fingerprint examiners. These results have applied importance for improving the professional performance of practising fingerprint examiners, and even other domains where this technique may also be helpful (e.g. radiology or banknote security).

A practical tool for information management in forensic decisions: Using Linear Sequential Unmasking-Expanded (LSU-E) in casework.

Forensic analysts often receive information from a multitude of sources. Empirical work clearly demonstrates that biasing information can affect analysts' decisions, and that the order in which task-relevant information is received impacts human cognition and decision-making. Linear Sequential Unmasking (LSU; Dror et al., 2015) and LSU-Expanded (LSU-E; Dror & Kukucka, 2021) are examples of research-based procedural frameworks to guide laboratories' and analysts' consideration and evaluation of case information. These frameworks identify parameters-such as objectivity, relevance, and biasing power-to prioritize and optimally sequence information for forensic analyses. Moreover, the LSU-E framework can be practically incorporated into any forensic discipline to improve decision quality by increasing the repeatability, reproducibility, and transparency of forensic analysts' decisions, as well as reduce bias. Future implementation of LSU and LSU-E in actual forensic casework can be facilitated by concrete guidance. We present here a practical worksheet designed to bridge the gap between research and practice by facilitating the implementation of LSU-E.

Cognitive and human factors in legal layperson decision making: Sources of bias in juror decision making.

Juries in adversarial courts are tasked with several responsibilities. They are asked to: 1) assess the credibility and reliability of the evidence presented; 2) deliberate; 3) and then reach a decision. Jurors are expected to evaluate said evidence in a rational/impartial manner, thus allowing the defendant their right to a fair trial. However, psychological research has shown that jurors are not rational and can reach inaccurate decisions by being biased by certain factors. The aim of the current review was to explore the potential sources from which biases are introduced into the jury. Three main sources of bias were focussed upon: 1) pre-trial bias; 2) cognitive bias; 3) bias from external legal actors (expert witnesses). Legal scholars commonly cite deliberations as a method of attenuating individual juror bias, this claim is evaluated in the review. The review concludes that bias is a multifaceted phenomenon introduced from many different elements, and that several sources of bias may interact with one another during a jury trial to cause the effects of bias to snowball. Four recommendations are made: 1) juror selection should be utilised to create heterogenous juries that challenge problematic biases from individual jurors; 2) increase the quality of expert testimony through training; 3) procedures such as Linear Sequential Unmasking should be adopted by expert witnesses to filter out some sources of bias; 4) legal professionals and jurors should be educated about the effects that biases may have on decision making; 5) more research into bias in jurors is needed.

Metric forensic anthropology decisions: Reliability and biasability of sectioning-point-based sex estimates.

Subjective decisions make human cognitive processes more susceptible to bias and error. Specifically, research indicates that additional context biases forensic anthropologists' morphological analyses. To address whether metric analyses are also subject to bias, we conducted a pilot study in which 52 experienced osteologists measured a difficult-to-classify human femur, with or without additional contextual information. Using a metric sectioning-point sex-estimation method, participants provided a sex estimate for individual skeletal element(s) and, when given multiple elements, the combined skeletal assemblage. Control group participants (n = 24) measured only the femur. In addition to the femur, bias group participants (n = 28) either measured a female humerus and viewed a female-biasing photograph (n = 14) or measured a male humerus and viewed a male-biasing photograph (n = 14). We explored whether the experts in the different groups would differ in: (1) femoral measurements; (2) femoral sex-estimation conclusions; and (3) final sex-estimation conclusions for the skeletal assemblage. Although the femoral measurements and femoral sex estimates were comparable across groups, the overall sex estimates in the female-biased group were impacted by contextual information-differing from both the control and male-biased groups (p < 0.001). Our results demonstrate that cognitive bias can occur even in metric sex-estimation conclusions. Specifically, this occurred when the metric data and single-element sex estimates were synthesized into an overall estimate. Thus, our results suggest that metric methods are most vulnerable to bias when data are synthesized into an overall conclusion, highlighting the need for bias countermeasures and comprehensive statistical frameworks for synthesizing metric data to mitigate the effects of cognitive bias.

The biasing impact of irrelevant contextual information on forensic odontology radiograph matching decisions.

The potential biasing effect of irrelevant context information on the forensic odontology method of radiograph-based identification has never been empirically investigated despite being a recognized problem in other forensic science disciplines. This study examines the effect of irrelevant context information on the probability judgment of match (JOM) of practicing forensic odontologist and dentist participants who were asked to match pairs of dental radiographs supplemented with irrelevant case information. The irrelevant case information contained domain task-irrelevant context information which varied in strength (strong or weak). It suggested either supportive or contradictory bias relative to the actual match status of the radiograph pairs. The dental radiographs consisted of verified match and non-match radiographs pairs sampled and de-identified from actual forensic cases. Changes in accuracy and JOM between supportive and contradictory contexts conditions revealed a contextual bias. Mixed model analysis showed that strong supportive context increased the odds ratio of correct decisions by a factor of 2.4 [1.23, 4.46]; p = 0.0097. Consistent with the biasing effect, the JOM score differences between strong supportive and contradictory irrelevant context information were 1.03 and 0.43 respectively for the non-match and match decisions. The direction of context suggestion (p = 0.0067), the radiograph match status (p = 0.014), and their interactions (p = 0.0061), were all found to impact the participants' decision. The weak context information was not strong enough to have a significant effect on accuracy or JOM scores. This study demonstrates that radiograph match judgment is affected and can be biased by strong irrelevant contextual information.