Judging experts: Australian magistrates' evaluations of expert opinion quality.

Expert opinions admitted by courts are not always valid and reliable. However, we know little about how indicators of opinion quality affect the persuasiveness of an expert. In this study 25 Australian magistrates and 22 jury-eligible lay people rated the persuasiveness (via credibility, value and weight) of either a high- or a low-quality expert opinion. Opinion quality was determined using attributes specified in the Expert Persuasion Expectancy (ExPEx) framework: Field, Specialty, Ability and Trustworthiness. Both magistrates and jurors were significantly more persuaded by the high- than the low-quality expert opinion. Magistrates were also significantly more sceptical of the expert opinion than lay people, and when given the opportunity sought information that was logically relevant to their decision. These results suggest that magistrates can differentiate between high- and low-quality expert opinions, but it is unclear whether the information they need for the task is actually available for use during trials.

Smoking and finances: baseline characteristics of low income daily smokers in the FISCALS cohort.

BACKGROUND: Financial stress is a barrier to successful smoking cessation and a key predictor of relapse. Little is known about the financial situation of low-income Australian daily smokers. This study aims to describe and investigate associations between the financial functioning, tobacco use and quitting behaviours of low income daily smokers. METHODS: Low-income Australian adult smokers in the 'Financial Intervention for Smoking Cessation Among Low-income Smokers (FISCALS) randomised clinical trial completed a structured telephone questionnaire. RESULTS: The median number of cigarettes typically smoked by the 1047 participants was 23 per day. The median spent on tobacco per week was AU$80. Three quarters (73.0%) reported some financial stress and 43.2% reported smoking-induced deprivation. Financial stress was significantly associated with deprivation (IRR: 1.23, 95% CI 1.21, 1.26, p < 0.001). There were no significant associations either between adjusted financial stress or deprivation and motivation to quit or certainty of quit success. CONCLUSIONS: Financial stress and smoking induced deprivation were prevalent among low-income daily smokers, but they were not associated with motivation to quit. Smoking cessation interventions need to be responsive to the role financial stress plays in reducing quit attempts and increasing relapse. TRIAL REGISTRATION: Australian and New Zealand Clinical trials Registry ACTRN12612000725864 6/07/2012.

On the likelihood of "encapsulating all uncertainty".

The assignment of personal probabilities to form a forensic practitioner's likelihood ratio is a mental operation subject to all the frailties of human memory, perception and judgment. While we agree that beliefs expressed as coherent probabilities are neither 'right' nor 'wrong' we argue that debate over this fact obscures both the requirement for and consideration of the 'helpfulness' of practitioner's opinions. We also question the extent to which a likelihood ratio based on personal probabilities can realistically be expected to 'encapsulate all uncertainty'. Courts cannot rigorously assess a forensic practitioner's bare assertions of belief regarding evidential strength. At a minimum, information regarding the uncertainty both within and between the opinions of practitioners is required.

Associations between behavioural risk factors and smoking, heavy smoking and future smoking among an Australian population-based sample.

INTRODUCTION: Tobacco smoking co-occurs with behavioural risk factors including diet, alcohol use and obesity. However, the association between behavioural risk factors and heavy smoking (>20cig/day) compared to light-moderate smoking is unknown. The link between behavioural risk factors and future smoking for both ex and current smokers is also unknown. This study sought to examine these relationships. It is hypothesised that behavioural risk factors will be more strongly associated with heavy smoking. METHOD: Data from Wave 7 (2007) of the Household and Labour Dynamics in Australia (HILDA) survey was analysed using logistic regression to determine relationships between diet (fruit and vegetable consumption, and unhealthy diet choices), alcohol consumption, obesity and physical activity with light-moderate smoking and heavy smoking. The association between these risk factors and future smoking (2008) was assessed for current and ex-smokers (2007). RESULTS: Obese respondents were less likely to be light/moderate smokers (RRR: 0.53; 95% CI: 0.43, 0.66) but not heavy smokers. Those who consume confectionary weekly were less likely to be light/moderate smokers (RRR: 0.73; 95% CI: 0.61, 0.87), but not heavy smokers. Smokers in 2007 were more likely to continue smoking in 2008 if they consumed 1-4 drinks per occasion (OR: 2.52; 95% CI: 1.13, 5.62). Ex-smokers in 2007 were less likely to relapse in 2008 if they consumed recommended levels of both fruit and vegetables (OR: 0.31; CI: 0.10, 0.91). CONCLUSION: The relationships between heavy smoking and behavioural risk factors differ from moderate-light smoking. Future primary care interventions would benefit from targeting multiple risk factors, particularly for heavy smokers.

Perception problems of the verbal scale: A reanalysis and application of a membership function approach.

Verbal conclusion scales provide a standardized vocabulary that forensic scientists can adopt to describe the amount of support offered by a set of observations with regard to two competing hypotheses. The extent to which these verbal scales can efficiently and accurately communicate strength of support to lay evaluators is, however, an empirical matter of considerable importance. The aim of this paper was to reexamine the results of a recent study measuring lay interpretations of expert verbal phrases (Mullen et al., 2014) and to further improve upon those estimates through the utilization of a membership function approach. Across both the reexamination (n=400) and the new experiment (n=134) 534 participants provided translations of expert verbal conclusion scales used by forensic scientists. Overall, there is compelling evidence that the correspondence between expert intentions and lay interpretations is low, while the potential for miscommunication is high. Consequently, further attention is required to facilitate the development of valid and reliable verbal conclusion scales which clearly communicate expert evaluative opinions.

Use of smoking cessation and quit support services by socioeconomic status over 10 years of the national drug strategy household survey.

OBJECTIVES: The aim of this research was to examine the use of quit smoking services and support options in Australia with national survey data to determine whether use of quit smoking services and pharmacotherapy contributes to socioeconomic status (SES) differences in smoking. METHODS: Analyses were performed with data from 4 waves of the Australian National Drug Strategy Household Survey between 2001 and 2010. The primary outcomes were the use of quit smoking services or pharmacotherapy. The main predictor variables used were measures of SES including the Socio-Economic Indexes for Areas, income, and education. Other sociodemographic variables were also examined. RESULTS: There was no systematic SES difference in the use of services or support options, with some used more by high SES and some used more by low SES. Those with university education (odds ratio [OR] = 0.72; 95% CI = 0.56-0.93) were less likely to use prescription medication. Conversely, those with higher incomes were more likely to use patches, gum, or an inhaler (OR = 1.13; 95% CI = 1.01-1.27). Prescription medication was significantly associated with increased odds for recent cessation, although only among those with lower levels of education (OR = 2.50; 95% CI = 1.94-3.23). Those with higher SES had the greatest odds for recent cessation. CONCLUSIONS: The evidence suggests that low-SES smokers use quit services and support options equally compared with high-SES smokers; thus, access does not drive the SES differential in smoking. However, the findings are positive, suggesting that increasing the uptake of prescription medication may help increase cessation rates among low-SES smokers.

EXPRESS: Individual differences in distributional statistical learning: better frequency 'discriminators' are better 'estimators'.

People can easily extract and encode statistical information from their environment. However, research has primarily focused on conditional statistical learning (i.e. the ability to learn joint and conditional relationships between stimuli) and has largely neglected distributional statistical learning (i.e. the ability to learn the frequency and variability of distributions). For example, learning that 'E' is more common in the English alphabet than 'Z.' In this paper, we investigate how distributional learning can be measured by exploring the relationship between, and psychometric properties of, four different measures of distributional learning - from the ability to discriminate relative frequencies to the ability to estimate frequencies. We identified moderate relationships between four distributional learning measures and these tasks accounted for a substantial portion of the variance in performance across tasks (44.3%). A measure of divergent validity (intrinsic motivation) did not significantly correlate with any statistical learning measure and accounted for a separate portion of the variance across tasks. More complex measures also showed better reliability and internal consistency. Our results suggest that distributional statistical learning encompasses both the ability to discriminate between relative frequencies and directly estimating them.

Jack of all trades, master of one: domain-specific and domain-general contributions to perceptual expertise in visual comparison.

Perceptual expertise is typically domain-specific and rarely generalises beyond an expert's domain of experience. Forensic feature-comparison examiners outperform the norm in domain-specific visual comparison, but emerging research suggests that they show advantages on other similar tasks outside their domain of expertise. For example, fingerprint examiners not only outperform novices in fingerprint comparison, but also in face comparison. Yet, the extent to which their skills generalise is poorly understood. In this study, we investigated the generalisability of perceptual expertise amongst forensic examiners by comparing their performance to novices and other examiners within and outside their area of expertise. We recruited 85 experts from three forensic disciplines (face, fingerprint, and firearms) and asked them to complete four different visual comparison tasks: faces, fingerprints, firearms, and novel-objects. Examiners displayed domain-specific expertise: they outperformed novices and other examiners within their domain of visual comparison expertise. Yet, some of their skill also generalised: examiners also outperformed novices outside their area of expertise. However, while individual differences in examiners' performance within their domain of experience were associated with their performance in a novel comparison task, they were not related to their performance on tasks outside their expert domain. These results provide key insight into the domain-specific and domain-general contributions of forensic examiners' perceptual expertise. Forensic expertise lends some generalisable skill to other visual comparison tasks, but best performance is still seen within examiners' domain of expertise.

Speaker identification in courtroom contexts - Part III: Groups of collaborating listeners compared to forensic voice comparison based on automatic-speaker-recognition technology.

Expert testimony is only admissible in common-law systems if it will potentially assist the trier of fact. In order for a forensic-voice-comparison expert's testimony to assist a trier of fact, the expert's forensic voice comparison should be more accurate than the trier of fact's speaker identification. "Speaker identification in courtroom contexts - Part I" addressed the question of whether speaker identification by an individual lay listener (such as a judge) would be more or less accurate than the output of a forensic-voice-comparison system that is based on state-of-the-art automatic-speaker-recognition technology. The present paper addresses the question of whether speaker identification by a group of collaborating lay listeners (such as a jury) would be more or less accurate than the output of such a forensic-voice-comparison system. As members of collaborating groups, participants listen to pairs of recordings reflecting the conditions of the questioned- and known-speaker recordings in an actual case, confer, and make a probabilistic consensus judgement on each pair of recordings. The present paper also compares group-consensus responses with "wisdom of the crowd" which uses the average of the responses from multiple independent individual listeners.

Understanding 'error' in the forensic sciences: A primer.

This paper distils seven key lessons about 'error' from a collaborative webinar series between practitioners at Victoria Police Forensic Services Department and academics. It aims to provide the common understanding of error necessary to foster interdisciplinary dialogue, collaboration and research. The lessons underscore the inevitability, complexity and subjectivity of error, as well as opportunities for learning and growth. Ultimately, we argue that error can be a potent tool for continuous improvement and accountability, enhancing the reliability of forensic sciences and public trust. It is hoped the shared understanding provided by this paper will support future initiatives and funding for collaborative developments in this vital domain.

The expression and interpretation of uncertain forensic science evidence: verbal equivalence, evidence strength, and the weak evidence effect.

Standards published by the Association of Forensic Science Providers (2009, Standards for the formulation of evaluative forensic science expert opinion, Science & Justice, Vol. 49, pp. 161-164) encourage forensic scientists to express their conclusions in the form of a likelihood ratio (LR), in which the value of the evidence is conveyed verbally or numerically. In this article, we report two experiments (using undergraduates and Mechanical Turk recruits) designed to investigate how much decision makers change their beliefs when presented with evidence in the form of verbal or numeric LRs. In Experiment 1 (N = 494), participants read a summary of a larceny trial containing inculpatory expert testimony in which evidence strength (low, moderate, high) and presentation method (verbal, numerical) varied. In Experiment 2 (N = 411), participants read the same larceny trial, this time including either exculpatory or inculpatory expert evidence that varied in strength (low, high) and presentation method (verbal, numerical). Both studies found a reasonable degree of correspondence in observed belief change resulting from verbal and numeric formats. However, belief change was considerably smaller than Bayesian calculations would predict. In addition, participants presented with evidence weakly supporting guilt tended to "invert" the evidence, thereby counterintuitively reducing their belief in the guilt of the accused. This "weak evidence effect" was most apparent in the verbal presentation conditions of both experiments, but only when the evidence was inculpatory. These findings raise questions about the interpretability of LRs by jurors and appear to support an expectancy-based account of the weak evidence effect.

Thinking false and slow: Implausible beliefs and the Cognitive Reflection Test.

Why do people believe implausible claims like conspiracy theories, pseudoscience, and fake news? Past studies using the Cognitive Reflection Test (CRT) suggest that implausible beliefs may result from an unwillingness to effortfully process information (i.e., cognitive miserliness). Our analysis (N = 664) tests this account by comparing CRT performance (total score, number and proportion of incorrect intuitive responses, and completion time) for endorsers and non-endorsers of implausible claims. Our results show that endorsers performed worse than non-endorsers on the CRT, but they took significantly longer to answer the questions and did not make proportionally more intuitive mistakes. Endorsers therefore appear to process information effortfully but nonetheless score lower on the CRT. Poorer overall CRT performance may not necessarily indicate that those who endorse implausible beliefs have a more reflexive, intuitive, or non-analytical cognitive style than non-endorsers.

Speaker identification in courtroom contexts - Part II: Investigation of bias in individual listeners' responses.

In "Speaker identification in courtroom contexts - Part I" individual listeners made speaker-identification judgements on pairs of recordings which reflected the conditions of the questioned-speaker and known-speaker recordings in a real case. The recording conditions were poor, and there was a mismatch between the questioned-speaker condition and the known-speaker condition. No contextual information that could potentially bias listeners' responses was included in the experiment condition - it was decontextualized with respect to case circumstances and with respect to other evidence that could be presented in the context of a case. Listeners' responses exhibited a bias in favour of the different-speaker hypothesis. It was hypothesized that the bias was due to the poor and mismatched recording conditions. The present research compares speaker-identification performance between: (1) listeners under the original Part I experiment condition, (2) listeners who were informed ahead of time that the recording conditions would make the recordings sound more different from one another than had they both been high-quality recordings, and (3) listeners who were presented with high-quality versions of the recordings. Under all experiment conditions, there was a substantial bias in favour of the different-speaker hypothesis. The bias in favour of the different-speaker hypothesis therefore appears not to be due to the poor and mismatched recording conditions.

Finding the perfect match: Fingerprint expertise facilitates statistical learning and visual comparison decision-making.

Forensic feature-comparison examiners compare-or "match"-evidence samples (e.g., fingerprints) to provide judgments about the source of the evidence. Research demonstrates that examiners in select disciplines possess expertise in this task by outperforming novices-yet the psychological mechanisms underpinning this expertise are unclear. This article investigates one implicated mechanism: statistical learning, the ability to learn how often things occur in the environment. This ability is likely important in forensic decision-making as samples sharing rarer statistical information are more likely to come from the same source than those sharing more common information. We investigated 46 fingerprint examiners' and 52 novices' statistical learning of fingerprint categories and application of this knowledge in a source-likelihood judgment task. Participants completed four measures of their statistical learning (frequency discrimination judgments, bounded and unbounded frequency estimates, and source-likelihood judgments) before and after familiarization to the "ground-truth" category frequencies. Compared to novices, fingerprint examiners had superior domain-specific statistical learning across all measures-both before and after familiarization. This suggests that fingerprint expertise facilitates domain-specific statistical learning-something that has important theoretical and applied implications for the development of training programs and statistical databases in forensic science. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Speaker identification in courtroom contexts - Part I: Individual listeners compared to forensic voice comparison based on automatic-speaker-recognition technology.

Expert testimony is only admissible in common law if it will potentially assist the trier of fact to make a decision that they would not be able to make unaided. The present paper addresses the question of whether speaker identification by an individual lay listener (such as a judge) would be more or less accurate than the output of a forensic-voice-comparison system that is based on state-of-the-art automatic-speaker-recognition technology. Listeners listen to and make probabilistic judgements on pairs of recordings reflecting the conditions of the questioned- and known-speaker recordings in an actual case. Reflecting different courtroom contexts, listeners with different language backgrounds are tested: Some are familiar with the language and accent spoken, some are familiar with the language but less familiar with the accent, and others are less familiar with the language. Also reflecting different courtroom contexts: In one condition listeners make judgements based only on listening, and in another condition listeners make judgements based on both listening to the recordings and considering the likelihood-ratio values output by the forensic-voice-comparison system.

Likeability and Expert Persuasion: Dislikeability Reduces the Perceived Persuasiveness of Expert Evidence.

With the use of expert evidence increasing in civil and criminal trials, there is concern jurors' decisions are affected by factors that are irrelevant to the quality of the expert opinion. Past research suggests that the likeability of an expert significantly affects juror attributions of credibility and merit. However, we know little about the effects of expert likeability when detailed information about expertise is provided. Two studies examined the effect of an expert's likeability on the persuasiveness judgments and sentencing decisions of 456 jury-eligible respondents. Participants viewed and/or read an expert's testimony (lower vs. higher quality) before rating expert persuasiveness (via credibility, value, and weight), and making a sentencing decision in a Capitol murder case (death penalty vs. life in prison). Lower quality evidence was significantly less persuasive than higher quality evidence. Less likeable experts were also significantly less persuasive than either neutral or more likeable experts. This "penalty" for less likeable experts was observed irrespective of evidence quality. However, only perceptions of the foundational validity of the expert's discipline, the expert's trustworthiness and the clarity and conservativeness of the expert opinion significantly predicted sentencing decisions. Thus, the present study demonstrates that while likeability does influence persuasiveness, it does not necessarily affect sentencing outcomes.

Public attitudes towards the use of automatic facial recognition technology in criminal justice systems around the world.

Automatic facial recognition technology (AFR) is increasingly used in criminal justice systems around the world, yet to date there has not been an international survey of public attitudes toward its use. In Study 1, we ran focus groups in the UK, Australia and China (countries at different stages of adopting AFR) and in Study 2 we collected data from over 3,000 participants in the UK, Australia and the USA using a questionnaire investigating attitudes towards AFR use in criminal justice systems. Our results showed that although overall participants were aligned in their attitudes and reasoning behind them, there were some key differences across countries. People in the USA were more accepting of tracking citizens, more accepting of private companies' use of AFR, and less trusting of the police using AFR than people in the UK and Australia. Our results showed that support for the use of AFR depends greatly on what the technology is used for and who it is used by. We recommend vendors and users do more to explain AFR use, including details around accuracy and data protection. We also recommend that governments should set legal boundaries around the use of AFR in investigative and criminal justice settings.

Forensic feature-comparison expertise: Statistical learning facilitates visual comparison performance.

Forensic feature-comparison examiners in select disciplines are more accurate than novices when comparing samples of visual evidence. This article examines a key cognitive mechanism that may contribute to this superior visual comparison performance: the ability to learn how often stimuli occur in the environment (distributional statistical learning). We examined the relationship between distributional learning and visual comparison performance and the impact of training on the diagnosticity of distributional information in visual comparison tasks. We compared performance between novices given no training (uninformed novices; n = 32), accurate training (informed novices; n = 32), or inaccurate training (misinformed novices; n = 32) in Experiment 1 and between forensic examiners (n = 26), informed novices (n = 29), and uninformed novices (n = 27) in Experiment 2. Across both experiments, forensic examiners and novices performed significantly above chance in a visual comparison task in which distributional learning was required for high performance. However, informed novices outperformed all participants, and only their visual comparison performance was significantly associated with their distributional learning. It is likely that forensic examiners' expertise is domain specific and doesn't generalize to novel visual comparison tasks. Nevertheless, diagnosticity training could be critical to the relationship between distributional learning and visual comparison performance. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Human factors in forensic science: The cognitive mechanisms that underlie forensic feature-comparison expertise.

After a decade of critique from leading scientific bodies, forensic science research is at a crossroads. Whilst emerging research has shown that some forensic feature-comparison disciplines are not foundationally valid, others are moving towards establishing reliability and validity. Forensic examiners in fingerprint, face and handwriting comparison disciplines have skills and knowledge that distinguish them from novices. Yet our understanding of the basis of this expertise is only beginning to emerge. In this paper, we review evidence on the psychological mechanisms contributing to forensic feature-comparison expertise, with a focus on one mechanism: statistical learning, or the ability to learn how often things occur in the environment. Research is beginning to emphasise the importance of statistical learning in forensic feature-comparison expertise. Ultimately, this research and broader cognitive science research has an important role to play in informing the development of training programs and selection tools for forensic feature-comparison examiners.

The multi-faceted nature of visual statistical learning: Individual differences in learning conditional and distributional regularities across time and space.

Emerging research has demonstrated that statistical learning is a modality-specific ability governed by domain-general principles. Yet limited research has investigated different forms of statistical learning within modality. This paper explores whether there is one unified statistical learning mechanism within the visual modality, or separate task-specific abilities. To do so, we examined individual differences in spatial and nonspatial conditional and distributional statistical learning. Participants completed four visual statistical learning tasks: conditional spatial, conditional nonspatial, distributional spatial, and distributional nonspatial. Performance on all four tasks significantly correlated with each other, and performance on all tasks accounted for a large portion of the variance across tasks (57%). Interestingly, a portion of the variance of task performance (between 11% and 18%) was also accounted for by performance on each of the individual tasks. Our results suggest that visual statistical learning is the result of the interplay between a unified mechanism for extracting conditional and distributional statistical regularities across time and space, and an individual's ability to extract specific types of regularities.