Unskilled, underperforming, or unaware? Testing three accounts of individual differences in metacognitive monitoring.

Many studies show that competence (e.g., skill, expertise, natural ability) influences individuals' capabilities of monitoring their item-level performance. However, debate persists about how best to explain these individual differences in metacognition. The competence-based account ascribes differences in monitoring to individuals' objective ability level, arguing that the same skills necessary to perform a task are required to effectively monitor performance. The performance-based account attributes differences in monitoring to changes in overall task performance - no individual differences in competence required. Finally, the metacognitive awareness account proposes that alignment between an individuals' self-assessed and objective ability leads to differences in monitoring. In this study, 603 participants completed a self-assessment of face recognition ability, a lineup identification task, and an objective assessment of face recognition ability. We manipulated the number of encoding repetitions and delay between encoding and test to produce varying levels of task performance across objective face recognition ability. Following each lineup decision, participants provided both a numeric confidence rating and a written expression of verbal confidence. We transformed verbal confidence into a quantitative value using machine learning techniques. When matched on overall identification accuracy, objectively stronger face recognizers used numeric and verbal confidence that a) better discriminates between correct and filler lineup identifications than weaker recognizers, and b) shows better calibration to accuracy. Participants with greater self-assessed ability used higher levels of confidence, irrespective of trial accuracy. These results support the competence-based account.

The language of accurate and inaccurate eyewitnesses.

This article uses machine-learning techniques to examine people's use of verbal expressions of confidence. Across the field of academic psychology, it is often assumed that such statements reflect the same underlying information as numeric confidence ratings. We show that verbal confidence is not redundant with numeric confidence but instead contributes unique diagnostic value in predicting the accuracy of a response. We use eyewitness confidence in a lineup identification as our model paradigm. There is potentially great applied value in developing a machine-learning algorithm that can predict eyewitness identification accuracy, such as by reducing false convictions. To this end, we applied a machine-learning methodology to investigate the natural language of accurate and inaccurate eyewitnesses. This method revealed that verbal confidence statements provide rich diagnostic information about the likely accuracy of eyewitness identifications. Moreover, verbal confidence statements provide unique diagnostic information that traditional indicators of identification accuracy such as numeric confidence ratings and response times do not provide. However, the diagnostic value of an eyewitness confidence statement depends in part on the face recognition ability of the eyewitness: The natural language of strong face recognizers is more diagnostic than the natural language of weak face recognizers. These results are theoretically interesting but, from an applied perspective, this machine-learning methodology may prove useful to those in the criminal justice system who must evaluate eyewitnesses' verbal confidence statements. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Improving the interpretation of verbal eyewitness confidence statements by distinguishing perceptions of certainty from those of accuracy.

When an eyewitness makes an identification from a lineup, police are also instructed to collect a verbal expression of confidence. This recommendation hinges on the assumption that evaluators will perceive confidence in the manner the witness intended. However, research has consistently shown that these interpretations can be biased by accompanying contextual information. For example, statements that reference facial features (e.g., "I'm very sure. I remember his eyes.") are perceived as less confident than when the statement is presented alone ("I'm very sure.") (featural justification effect). Additionally, perceptions of witness confidence are altered when the witness's identification (mis-)matches the police suspect in a lineup (prior knowledge). We find that the same underlying mechanism explains the bias induced by both featural justification (Experiments 1 and 2) and prior knowledge (Experiment 3) manipulations. Evaluators conflate their own beliefs about the accuracy of an identification with the witness's intended level of confidence. A simple warning that highlights the differences between confidence and accuracy eliminates the featural justification effect, but is less effective for mitigating the influence of prior knowledge. The key takeaway from this paper is that distinguishing perceptions of certainty from those of accuracy improves the interpretation of verbal confidence statements. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

A decision processes account of the differences in the eyewitness confidence-accuracy relationship between strong and weak face recognizers under suboptimal exposure and delay conditions.

When pristine testing conditions are used, an eyewitness's high-confidence identification from a lineup can be a reliable predictor of their identification accuracy (Wixted & Wells, 2017). Further, Grabman, Dobolyi, Berelovich, and Dodson (2019) found that high-confidence identifications are more predictive of accuracy for individuals with stronger than weaker face recognition ability. We extend this research by investigating why strong face recognizers make more informative confidence judgments and fewer high-confidence errors through the framework of two different accounts: the optimality account (Deffenbacher, 1980) and the decision processes account (e.g., Kruger & Dunning, 1999). The optimality account holds that differences in the predictive value of confidence ratings made by strong versus weak face recognizers are a result of differences in the quality of their memory representations for faces, indicating that confidence-accuracy calibration would be equated between these two groups when overall accuracy is equated, whereas the decision processes account attributes differences in calibration to strong face recognizers' superior metacognitive skills, which allow them to better evaluate their performance in the domain of face recognition. Therefore, to distinguish between these accounts, we manipulated exposure and retention interval to create conditions that produced comparable levels of identification accuracy between stronger and weaker face recognizers, and then examined their confidence-accuracy calibration. The decision processes account was supported, as differences in calibration between stronger and weaker face recognizers persisted even when overall identification accuracy was equated. Stronger face recognizers are better able to regulate their use of the confidence scale points with changes in identification accuracy. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Body Mass Index Effect on Differing Responses to Psychological Stress in Blood Glucose Dynamics in Patients With Type 1 Diabetes.

OBJECTIVE: The objective was to investigate the relationship of body mass index (BMI) to differing glycemic responses to psychological stress in patients with type 1 diabetes. METHODS: Continuous blood glucose monitor (CGM) data were collected for 1 week from a total of 37 patients with BMI ranging from 21.5-39.4 kg/m2 (mean = 28.2 ± 4.9). Patients reported daily stress levels (5-point Likert-type scale, 0 = none, 4 = extreme), physical activity, carbohydrate intake, insulin boluses and basal rates. Daily reported carbohydrates, total insulin bolus, and average blood glucose (BG from CGM) were compared among patients based on their BMI levels on days with different stress levels. In addition, daily averages of a model-based "effectiveness index" (quantifying the combined impact of insulin and carbohydrate on glucose levels) were defined and compared across stress levels to capture meal and insulin independent glycemic changes. RESULTS: Analyses showed that patient BMI likely moderated stress related glycemic changes. Linear mixed effect model results were significant for the stress-BMI interaction on both behavioral and behavior-independent glycemic changes. Across participants, under stress, an increase was observed in daily carbohydrate intake and effectiveness index at higher BMI. There was no significant interactive effect on daily insulin or average BG. CONCLUSION: Findings suggest that (1) stress has both behavioral and nonbehavioral glycemic effects on T1D patients and (2) the direction and magnitude of these effects are potentially influenced by level of stress and patient BMI. Possibly responsible for these observed effects are T1D/BMI related alterations in endocrine response.

Diabetes Alert Dogs (DADs): An assessment of accuracy and implications.

AIMS: To test the accuracy of Diabetes Alert Dogs (DADs) by comparing recorded alerts to continuous glucose monitoring (CGM) device readings during waking and sleeping hours. METHODS: 14 individuals (7 adults with type 1 diabetes and 7 youth with type 1 diabetes/parents) who owned DADs for ≥6 mos wore masked CGM devices over a several-week period while recording DAD alerts electronically and in paper diaries. RESULTS: During waking hours, sensitivity scores across participants were 35.9% for low BG events and 26.2% for high BG events. DAD accuracy was highly variable with 3/14 individual dogs performing statistically higher than chance. Sensitivity scores were lower during sleep hours of the person with diabetes (22.2% for low BG events and 8.4% for high BG events). DAD accuracy during sleeping hours was also highly variable, with 1/11 individual dogs performing statistically better than chance. Rate of change analyses indicated that DADs were responding to absolute BG level, rather than rapid shifts in glucose levels. CONCLUSIONS: In this study the majority of DADs did not demonstrate accurate detection of low and high BG events. However, performance varied greatly across DADs and additional studies are needed to examine factors contributing to this variability. Additionally, more research is needed to investigate the significant gap between the positive experiences and clinical outcomes reported by DAD owners and the mixed research findings on DAD accuracy.

Variability of Diabetes Alert Dog Accuracy in a Real-World Setting.

BACKGROUND: Diabetes alert dogs (DADs) are growing in popularity as an alternative method of glucose monitoring for individuals with type 1 diabetes (T1D). Only a few empirical studies have assessed DAD accuracy, with inconsistent results. The present study examined DAD accuracy and variability in performance in real-world conditions using a convenience sample of owner-report diaries. METHOD: Eighteen DAD owners (44.4% female; 77.8% youth) with T1D completed diaries of DAD alerts during the first year after placement. Diary entries included daily BG readings and DAD alerts. For each DAD, percentage hits (alert with BG ≤ 5.0 or ≥ 11.1 mmol/L; ≤90 or ≥200 mg/dl), percentage misses (no alert with BG out of range), and percentage false alarms (alert with BG in range) were computed. Sensitivity, specificity, positive likelihood ratio (PLR), and true positive rates were also calculated. RESULTS: Overall comparison of DAD Hits to Misses yielded significantly more Hits for both low and high BG. Total sensitivity was 57.0%, with increased sensitivity to low BG (59.2%) compared to high BG (56.1%). Total specificity was 49.3% and PLR = 1.12. However, high variability in accuracy was observed across DADs, with low BG sensitivity ranging from 33% to 100%. Number of DADs achieving ≥ 60%, 65% and 70% true positive rates was 71%, 50% and 44%, respectively. CONCLUSIONS: DADs may be able to detect out-of-range BG, but variability across DADs is evident. Larger trials are needed to further assess DAD accuracy and to identify factors influencing the complexity of DAD accuracy in BG detection.

Predicting and Reducing Driving Mishaps Among Drivers With Type 1 Diabetes.

OBJECTIVE: Two aims of this study were to develop and validate A) a metric to identify drivers with type 1 diabetes at high risk of future driving mishaps and B) an online intervention to reduce mishaps among high-risk drivers. RESEARCH DESIGN AND METHODS: To achieve aim A, in study 1, 371 drivers with type 1 diabetes from three U.S. regions completed a series of established questionnaires about diabetes and driving. They recorded their driving mishaps over the next 12 months. Questionnaire items that uniquely discriminated drivers who did and did not have subsequent driving mishaps were assembled into the Risk Assessment of Diabetic Drivers (RADD) scale. In study 2, 1,737 drivers with type 1 diabetes from all 50 states completed the RADD online. Among these, 118 low-risk (LR) and 372 high-risk (HR) drivers qualified for and consented to participate in a 2-month treatment period followed by 12 monthly recordings of driving mishaps. To address aim B, HR participants were randomized to receive either routine care (RC) or the online intervention "DiabetesDriving.com" (DD.com). Half of the DD.com participants received a motivational interview (MI) at the beginning and end of the treatment period to boost participation and efficacy. All of the LR participants were assigned to RC. In both studies, the primary outcome variable was driving mishaps. RESULTS: Related to aim A, in study 1, the RADD demonstrated 61% sensitivity and 75% specificity. Participants in the upper third of the RADD distribution (HR), compared with those in the lower third (LR), reported 3.03 vs. 0.87 mishaps/driver/year, respectively (P < 0.001). In study 2, HR and LR participants receiving RC reported 4.3 and 1.6 mishaps/driver/year, respectively (P < 0.001). Related to aim B, in study 2, MIs did not enhance participation or efficacy, so the DD.com and DD.com + MI groups were combined. DD.com participants reported fewer hypoglycemia-related driving mishaps than HR participants receiving RC (P = 0.01), but more than LR participants receiving RC, reducing the difference between the HR and LR participants receiving RC by 63%. HR drivers differed from LR drivers at baseline across a variety of hypoglycemia and driving parameters. CONCLUSIONS: The RADD identified higher-risk drivers, and identification seemed relatively stable across time, samples, and procedures. This 11-item questionnaire could inform patients at higher risk, and their clinicians, that they should take preventive steps to reduce driving mishaps, which was accomplished in aim B using DD.com.

Evidence-Based Psychosocial Treatments for Pediatric Elimination Disorders.

Pediatric elimination disorders are common in childhood, yet psychosocial correlates are generally unclear. Given the physiological concomitants of both enuresis and encopresis, and the fact that many children with elimination disorders are initially brought to their primary care physician for treatment, medical evaluation and management are crucial and may serve as the first-line treatment approach. Scientific investigation on psychological and behavioral interventions has progressed over the past couple of decades, resulting in the identification of effective treatments for enuresis and encopresis. However, the body of literature has inherent challenges, particularly given the multicomponent nature of many of the treatment packages. This review identified 25 intervention studies-18 for nocturnal enuresis and 7 for encopresis-over the past 15 years and classified them according to the guidelines set forth by the Task Force on the Promotion and Dissemination of Psychological Procedures. For nocturnal enuresis, the urine alarm and dry-bed training were identified as well-established treatments, Full Spectrum Home Therapy was probably efficacious, lifting was possibly efficacious, and hypnotherapy and retention control training were classified as treatments of questionable efficacy. For encopresis, only two probably efficacious treatments were identified: biofeedback and enhanced toilet training (ETT). Best practice recommendations and suggestions for future research are provided to address existing limitations, including heterogeneity and the multicomponent nature of many of the interventions for pediatric elimination disorders.

Psychology, technology, and diabetes management.

Use of technology in diabetes management is rapidly advancing and has the potential to help individuals with diabetes achieve optimal glycemic control. Over the past 40 years, several devices have been developed and refined, including the blood glucose meter, insulin pump, and continuous glucose monitor. When used in tandem, the insulin pump and continuous glucose monitor have prompted the Artificial Pancreas initiative, aimed at developing control system for fully automating glucose monitoring and insulin delivery. In addition to devices, modern technology, such as the Internet and mobile phone applications, have been used to promote patient education, support, and intervention to address the behavioral and emotional challenges of diabetes management. These state-of-the-art technologies not only have the potential to improve clinical outcomes, but there are possible psychological benefits, such as improved quality of life, as well. However, practical and psychosocial limitations related to advanced technology exist and, in the context of several technology-related theoretical frameworks, can influence patient adoption and continued use. It is essential for future diabetes technology research to address these barriers given that the clinical benefits appear to largely depend on patient engagement and consistence of technology use. (PsycINFO Database Record

Is Psychological Stress a Factor for Incorporation Into Future Closed-Loop Systems?

BACKGROUND: The relationship between daily psychological stress and BG fluctuations in type 1 diabetes (T1DM) is unclear. More research is needed to determine if stress-related BG changes should be considered in glucose control algorithms. This study in the usual free-living environment examined relationships among routine daily stressors and BG profile measures generated from CGM readings. METHODS: A total of 33 participants with T1DM on insulin pumps wore a CGM device for 1 week and recorded daily ratings of psychological stress, carbohydrates, and insulin boluses. RESULTS: Within-subjects ANCOVAs found a significant relationship between daily stress and indices of BG variability/instability (r = .172 to .185, P = .011 to .018, r(2) = 2.97% to 3.43%), increased % time in hypoglycemia (r = .153, P = .036, r(2) = 2.33%) and decreased carbohydrate consumption (r = -.157, P = .031, r(2) = 2.47%). Models accounted for more variance for individuals reporting the highest daily stress. There was no relationship between stress and mean daily glucose or low/high glucose risk indices. CONCLUSIONS: These preliminary findings suggest that naturally occurring daily stressors can be associated with increased glucose instability and hypoglycemia, as well as decreased food consumption. In addition, findings support the hypothesis that some individuals are more metabolically reactive to stress. More rigorous studies using CGM technology are needed to understand whether the impact of daily stress on BG is clinically meaningful and if it is a behavioral factor that should be considered in glucose control systems for some individuals.

Does correcting astigmatism with toric lenses improve driving performance?

PURPOSE: Driving is a vision-based activity of daily living that impacts safety. Because visual disruption can compromise driving safety, contact lens wearers with astigmatism may pose a driving safety risk if they experience residual blur from spherical lenses that do not correct their astigmatism or if they experience blur from toric lenses that rotate excessively. Given that toric lens stabilization systems are continually improving, this preliminary study tested the hypothesis that astigmats wearing toric contact lenses, compared with spherical lenses, would exhibit better overall driving performance and driving-specific visual abilities. METHODS: A within-subject, single-blind, crossover, randomized design was used to evaluate driving performance in 11 young adults with astigmatism (-0.75 to -1.75 diopters cylinder). Each participant drove a highly immersive, virtual reality driving simulator (210 degrees field of view) with (1) no correction, (2) spherical contact lens correction (ACUVUE MOIST), and (3) toric contact lens correction (ACUVUE MOIST for Astigmatism). Tactical driving skills such as steering, speed management, and braking, as well as operational driving abilities such as visual acuity, contrast sensitivity, and foot and arm reaction time, were quantified. RESULTS: There was a main effect for type of correction on driving performance (p = 0.05). Correction with toric lenses resulted in significantly safer tactical driving performance than no correction (p < 0.05), whereas correction with spherical lenses did not differ in driving safety from no correction (p = 0.118). Operational tests differentiated corrected from uncorrected performance for both spherical (p = 0.008) and toric (p = 0.011) lenses, but they were not sensitive enough to differentiate toric from spherical lens conditions. CONCLUSIONS: Given previous research showing that deficits in these tactical skills are predictive of future real-world collisions, these preliminary data suggest that correcting low to moderate astigmatism with toric lenses may be important to driving safety. Their merits relative to spherical lens correction require further investigation.