Assessing the practical differences between model selection methods in inferences about choice response time tasks

The Effects of IRL-1620 in Post-ischemic Brain Injury: A Systematic Review and Meta-analysis of Experimental Studies

BACKGROUND

Sovateltide (IRL-1620), an endothelin B receptor agonist, has previously demonstrated neuroprotective and neuroregenerative effects in animal models of acute ischemic stroke. Recently, clinical trials indicated that it could also be effective in humans with stroke. Here, we systematically investigate whether IRL-1620 may be used for the treatment of ischemia-induced brain injury.

METHODS

A systematic review was performed following the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines. MEDLINE (PubMed) and Scopus databases were searched for eligible studies up to December 2022. The databases ClinicalTrials.gov and Pharmazz Inc. were screened for unpublished or ongoing trials. Only studies in English were evaluated for eligibility. Meta-analysis of the included studies was also conducted.

RESULTS

Finally, seven studies were included in the review, all in animal rat models because of scarcity of clinical trials. Six studies, all in middle cerebral artery occlusion (MCAO) models, were selected for meta-analysis. In the two studies assessing mortality, no deaths were reported in the IRL-1620 group 24 h after MCAO, whereas the vehicle group had almost a five times higher mortality risk (risk ratio 5.3, 95% confidence interval 0.7-40.1, I2 = 0%). In all five studies evaluating outcome on day 7 after MCAO, IRL-1620 was associated with statistically significantly lower neurological deficit and improved motor performance compared with the vehicle. Infract volume, differentiation potential of neuronal progenitor cells, and mitochondrial fate also improved with IRL-1620 administration.

CONCLUSIONS

According to the above, in animal MCAO models, IRL-1620 enhanced neurogenesis and neuroprotection and improved outcome. Future studies are needed to expand our understanding of its effects in human study participants with acute ischemic stroke as well as in other common causes of cerebral ischemia including cardiac arrest.

The Best Exercise Modality and Dose to Reduce Glycosylated Hemoglobin in Patients with Type 2 Diabetes: A Systematic Review with Pairwise, Network, and Dose-Response Meta-Analyses

BACKGROUND

Persistently elevated glycosylated hemoglobin (HbA1c) is associated with a higher risk of long-term vascular complications.

OBJECTIVE

We evaluated the effect of different exercise modalities and doses on HbA1c levels in patients with type 2 diabetes.

METHODS

A systematic search for randomized controlled trials involving exercise interventions in patients with type 2 diabetes was conducted across seven electronic databases, encompassing data from their inception up to October 2023. Two independent reviewers assessed the quality of the literature. Pairwise, network, and dose-response meta-analyses using the random-effects model were conducted to analyze the effect of exercise on HbA1c levels.

RESULTS

A total of 85 randomized controlled trials with 5535 participants were included. The network meta-analysis showed that high-intensity interval training (HIIT) has the highest ranked (MD =  - 0.78% [- 8.50 mmol/mol]; 95% CrI:  - 1.04, - 0.51), followed by combined aerobic and resistance exercise (CE) (MD =  - 0.54% [- 5.90 mmol/mol]; 95% CrI: - 0.69, - 0.40), yoga (MD =  - 0.45% [- 4.92 mmol/mol]; 95% CrI: - 0.77, - 0.13), and continuous aerobic exercise (CAE) (MD =  - 0.42% [- 4.58 mmol/mol]; 95% CrI: - 0.54, - 0.30). In addition, a significant improvement in HbA1c levels can be observed when the total exercise dose reaches 840 metabolic equivalent of tasks-min/week.

CONCLUSIONS

There was low-quality evidence that HIIT, CE, yoga, and CAE may be effective treatment modalities for improving HbA1c in patients with type 2 diabetes, and there was no significant difference in efficacy. Moreover, a non-linear dose-response relationship was found for total exercise and HbA1c levels. Future research should further investigate the specific effects of different exercise doses on HbA1c levels in patients with type 2 diabetes and provide a more personalized exercise prescription.

Optimal modalities and doses of mind-body exercise for depressive symptoms in adults: A systematic review of paired analyses, network analyses and dose-response meta-analyses

The relative efficacy of various mind-body exercises in the treatment of depressive symptoms remains uncertain. We examined the optimal modalities (Tai Chi, qigong, yoga) and dose of mind-body exercise to improve depressive symptoms in adults. A systematic search of six electronic databases for randomized controlled trials on the relationship between exercise and depression was carried out, encompassing data from their inception up to November 2023. Pairwise analyses, network analyses and dose-response meta-analyses using random-effects models were performed to analyse the effect of exercise on depression. Forty studies were included. Results showed that Yoga [standardised mean difference (SMD) = -0.55; 95% confidence interval (CI): (-0.76, -0.35)] was the most effective form of exercise for improving depressive symptoms, followed by Qigong (SMD = -0.52; 95%CI: -0.92, -0.11) and Tai Chi exercise (SMD = -0.42; 95%CI: -0.71, -0.13). In addition, a non-linear dose-response relationship was found between overall mind-body exercise dose and depression levels and a significant response was observed after 260 METs-min. Our study examined the effectiveness of different types of mind-body exercise in improving depression and found that yoga may be the most effective adjunctive intervention. There was a non-linear dose-response relationship between total exercise and depression levels. However, caution should be exercised in interpreting and applying these results.

Optimal exercise modality and dose to improve depressive symptoms in adults with major depressive disorder: A systematic review and Bayesian model-based network meta-analysis of RCTs

Depression is a growing public health concern, and exercise is an adjunctive treatment modality to improve depression, but the optimal form of exercise and the optimal dose are still unclear. This systematic review examined the efficacy of four major types of exercise (aerobic, resistance, mixed, and mind-body) on depression, as well as the dose-response relationship between total and specific exercise and depressive symptoms. We included randomized controlled trials that included participants aged 18 years or older with a diagnosis of major depressive disorder or a depressive symptom score above a threshold as determined by a validated screening measure, implemented one or more exercise therapy groups, and assessed depressive symptoms at baseline and follow-up. Forty-six studies (3164 patients) were included in the meta-analysis. Aerobic (standardised mean difference (SMD) = -0.93; 95% CI: -1.25 to -0.62) and mind-body exercise (SMD) = -0.81; 95% CI: -1.19 to -0.42) improved depressive symptoms better compared to controls, followed by mixed (SMD = -0.77; 95% CI: -1.20 to -0.34) and resistance exercise (SMD = -0.76; 95% CI: -1.24 to -0.28). This dose-response meta-analysis showed a U-shaped curve between exercise dose and depressive symptoms. The minimum effective dose was estimated to be 320 metabolic equivalent (METs) -min per week and the optimal response was 860 METs-min per week. These findings lead us to advocate that clinicians carefully select the appropriate dose of exercise based on the patient's individual characteristics and needs, in conjunction with psychological care interventions.

Optimal dosage ranges of various exercise types for enhancing timed up and go performance in Parkinson's disease patients: a systematic review and Bayesian network meta-analysis

Objective

To examine the dose-response relationship between specific types of exercise for alleviating Timed up and Go (TUG) in Parkinson's disease PD.

Design

Systematic review and Bayesian network meta-analysis.

Data sources

PubMed, Medline, Embase, PsycINFO, Cochrane Library, and Web of Science were searched from inception until February 5th, 2024.

Study analysis

Data analysis was conducted using R software with the MBNMA package. Effect sizes of outcome indicators were expressed as mean deviation (MD) and 95% confidence intervals (95% CrI). The risk of bias in the network was evaluated independently by two reviewers using ROB2.

Results

A total of 73 studies involving 3,354 PD patients. The text discusses dose-response relationships in improving TUG performance among PD patients across various exercise types. Notably, Aquatic (AQE), Mix Exercise (Mul_C), Sensory Exercise (SE), and Resistance Training (RT) demonstrate effective dose ranges, with AQE optimal at 1500 METs-min/week (MD: -8.359, 95% CI: -1.398 to -2.648), Mul_C at 1000 METs-min/week (MD: -4.551, 95% CI: -8.083 to -0.946), SE at 1200 METs-min/week (MD: -5.145, 95% CI: -9.643 to -0.472), and RT at 610 METs-min/week (MD: -2.187, 95% CI: -3.161 to -1.278), respectively. However, no effective doses are found for Aerobic Exercise (AE), Balance Gait Training (BGT), Dance, and Treadmill Training (TT). Mind-body exercise (MBE) shows promise with an effective range of 130 to 750 METs-min/week and an optimal dose of 750 METs-min/week (MD: -2.822, 95% CI: -4.604 to -0.996). According to the GRADE system, the included studies' overall quality of the evidence was identified moderate level.

Conclusion

This study identifies specific exercise modalities and dosages that significantly enhance TUG performance in PD patients. AQE emerges as the most effective modality, with an optimal dosage of 1,500 METs-min/week. MBE shows significant benefits at lower dosages, catering to patients with varying exercise capacities. RT exhibits a nuanced "U-shaped" dose-response relationship, suggesting an optimal range balancing efficacy and the risk of overtraining. These findings advocate for tailored exercise programs in PD management, emphasizing personalized prescriptions to maximize outcomes.Systematic Review Registration: International Prospective Register of Systematic Reviews (PROSPERO) (CRD42024506968).

Optimal dose and type of exercise to improve depressive symptoms in older adults: a systematic review and network meta-analysis

BACKGROUND

Depression is a prevalent issue among older adults, affecting their quality of life and overall well-being. Exercise is an effective means of relieving depressive symptoms in older adults, but the optimal dose for different exercise types remains unclear. As such, the aim of this meta-analysis was to examine the dose-response relationship between overall and specific types of exercise with depression symptoms in older adults.

METHODS

This systematic review and network meta-analysis included a search of PubMed, Medline, Embase, PsycINFO, Cochrane library, and Web of Science for randomized controlled trials of exercise in older adults with depression symptoms from inception to 15 July 2023. Comprehensive data extraction covered dose, treatment regimen, demographics and study duration. Dosage metrics, encompassing METs-min/week, were scrutinized in correlation with the Minimal Clinically Importance Difference (MCID).

RESULTS

A total of 47 studies involving 2895 participants and 7 kinds of exercise were included in the review. Without considering the dose, the results of our network meta-analysis indicated that Walking was the most effective in alleviating depression in older adults, in addition to Aerobic exercise (AE), Yoga, Qigong, Resistance training (RT), and Tai Chi (TC), which were equally effective. However, the results of the dose-response analysis found that Aerobic exercise was most effective at a dose of 1000 METs-min/week. It is noteworthy that Walking is significantly effective in alleviating depressive symptoms in older adults at very low doses. In terms of clinical benefits, we found that overall exercise doses in the range of 600 ~ 970 METs-min/week were clinically effective. Considering the specific types of exercise, Aerobic exercise, Resistance training, Walking, and Yoga were found to be effective at doses ranging from 820 ~ 1000 METs-min/week, 520 ~ 1000 METs-min/week, 650 ~ 1000 METs-min/week, 680 ~ 1000 METs-min/week, respectively. At the same time, we found that when the age exceeded 81 years, even when participating in exercise, it did not achieve the effect of alleviating depressive symptoms in older adults.

CONCLUSIONS

In conclusion, including Walking, AE, Yoga, Qigong, RT, and TC, effectively alleviate depressive symptoms in older adults. Furthermore, we established statistically and clinically significant threshold doses for various exercise types. Early initiation of exercise is beneficial, but its efficacy diminishes from the age of 80, and beyond 81, exercise no longer significantly alleviates depressive symptoms.

The Best Exercise Modality and Dose for Reducing Pain in Adults With Low Back Pain: A Systematic Review With Model-Based Bayesian Network Meta-analysis

OBJECTIVE: To quantify the dose-response relationship between overall and specific exercise modalities and pain, in patients with nonspecific chronic low back pain (LBP). DESIGN: Systematic review with Bayesian network meta-analysis. LITERATURE SEARCH: We searched the Medline, Embase, Web of Science, Cochrane Library, Scopus, and SPORTDiscus databases from inception to June 2023. STUDY SELECTION CRITERIA: We included randomized controlled trials of exercise interventions in adults with nonspecific chronic LBP and at least 1 pain outcome reported at the main trial end point. DATA SYNTHESIS: A random-effects network meta-analysis was conducted. We assessed risk of bias using the Cochrane Risk of Bias Tool 2.0, and used the GRADE approach to judge the certainty of evidence for each outcome. RESULTS: Eighty-two trials were included (n = 5033 participants). We found a nonlinear dose-response relationship between total exercise and pain in patients with nonspecific chronic LBP. The maximum significant response was observed at 920 MET minutes (standardized mean difference = -1.74; 95% credible intervals: -2.43, -1.04). The minimal clinically important difference for achieving meaningful pain improvement was 520 MET minutes per week. The dose to achieve minimal clinically important difference varied by type of exercise; Pilates was the most effective. The certainty of the evidence was very low to moderate for all outcomes. CONCLUSION: The dose-response relationship of different exercise modalities to improve pain in patients with nonspecific chronic LBP had a U-shaped trajectory and low- to moderate-certainty evidence. The clinical effect was most pronounced with Pilates exercise. J Orthop Sports Phys Ther 2024;54(5):1-13. Epub 8 March 2024. doi:10.2519/jospt.2024.12153.

Uncovering the cognitive mechanisms underlying the gaze cueing effect

The gaze cueing effect is the tendency for people to respond faster to targets appearing at locations gazed at by others, compared with locations gazed away from by others. The effect is robust, widely studied, and is an influential finding within social cognition. Formal evidence accumulation models provide the dominant theoretical account of the cognitive processes underlying speeded decision-making, but they have rarely been applied to social cognition research. In this study, using a combination of individual-level and hierarchical computational modelling techniques, we applied evidence accumulation models to gaze cueing data (three data sets total, N = 171, 139,001 trials) for the first time to assess the relative capacity that an attentional orienting mechanism and information processing mechanisms have for explaining the gaze cueing effect. We found that most participants were best described by the attentional orienting mechanism, such that response times were slower at gazed away from locations because they had to reorient to the target before they could process the cue. However, we found evidence for individual differences, whereby the models suggested that some gaze cueing effects were driven by a short allocation of information processing resources to the gazed at location, allowing for a brief period where orienting and processing could occur in parallel. There was exceptionally little evidence to suggest any sustained reallocation of information processing resources neither at the group nor individual level. We discuss how this individual variability might represent credible individual differences in the cognitive mechanisms that subserve behaviourally observed gaze cueing effects.

What exercise programme is the most appropriate to mitigate anterior cruciate ligament injury risk in football (soccer) players? A systematic review and network meta-analysis

OBJECTIVES

To examine the effectiveness of different exercise-based interventions to mitigate the risk of anterior cruciate ligament injury in football players, and to determine which is the most appropriate for them, specifically for female football players.

DESIGN

Four databases were accessed in July 2023 using the keywords football, soccer, athletic injuries, anterior cruciate ligament, knee injuries, injury prevention, exercise-based programme, and risk factor.

METHODS

Randomised controlled trials that evaluated any exercise-based injury prevention intervention compared with a control group on the prevention of anterior cruciate ligament injury in football players were included.

RESULTS

Eleven studies were included. Data were presented as logarithm hazard ratio, credible intervals and standard deviation. FIFA 11+ was the most effective in reducing anterior cruciate ligament injury risk in football players (logarithm hazard ratio = -1.23 [95% credible intervals: -2.20, -0.35]; SD = 0.47), followed by the Knäkontroll programme (logarithm hazard ratio = -0.76 [95% credible intervals: -1.60, -0.03]; standard deviation = 0.42). For females, only Knäkontroll had a significant impact on reducing the risk of anterior cruciate ligament injury (logarithm hazard ratio = -0.62 [95% credible intervals: -1.71, 0.62]; standard deviation = 0.58).

CONCLUSIONS

Our results support the use of FIFA 11+ and Knäkontroll to mitigate injury incidence at overall level. However, the effectiveness of these interventions changed when adjusting for females. Knäkontroll is postulated as the programme with the greatest preventive nature, although these results should be interpreted with caution due to the lack of the sample.

What can evidence accumulation modelling tell us about human social cognition?

Evidence accumulation models are a series of computational models that provide an account for speeded decision-making. These models have been used extensively within the cognitive psychology literature to great success, allowing inferences to be drawn about the psychological processes that underlie cognition that are sometimes not available in a traditional analysis of accuracy or reaction time (RT). Despite this, there have been only a few applications of these models within the domain of social cognition. In this article, we explore several ways in which the study of human social information processing would benefit from application of evidence accumulation modelling. We begin first with a brief overview of the evidence accumulation modelling framework and their past success within the domain of cognitive psychology. We then highlight five ways in which social cognitive research would benefit from an evidence accumulation approach. This includes (1) greater specification of assumptions, (2) unambiguous comparisons across blocked task conditions, (3) quantifying and comparing the magnitude of effects in standardised measures, (4) a novel approach for studying individual differences, and (5) improved reproducibility and accessibility. These points are illustrated using examples from the domain of social attention. Finally, we outline several methodological and practical considerations, which should help researchers use evidence accumulation models productively. Ultimately, it will be seen that evidence accumulation modelling offers a well-developed, accessible, and commonly understood framework that can reveal inferences about cognition that may otherwise be out of reach in a traditional analysis of accuracy and RT. This approach, therefore, has the potential to substantially revise our understanding of social cognition.

A literature review and meta-analysis of the optimal factors study of repetitive transcranial magnetic stimulation in post-infarction aphasia

BACKGROUND

The existing literature indicates that repetitive transcranial magnetic stimulation (rTMS) can potentially enhance the prognosis of poststroke aphasia (PSA). Nevertheless, these investigations did not identify the most effective parameters or settings for achieving optimal treatment outcomes. This study involved a meta-analysis aimed to identify the optimal variables for rTMS in treating post-infarction aphasia to guide the use of rTMS in rehabilitating PSA.

METHODS

PubMed, Embase, and Cochrane Library databases were searched from inception to May 2023, and articles were reviewed manually using subject words and free words and supplemented with references from the included literature to obtain additional relevant literature. The search terms included "poststroke aphasia" and "repetitive transcranial magnetic stimulation (rTMS)" repetitive transcranial magnetic stimulation. Additionally, a review of the reference lists of previously published systematic reviews identified through the Cochrane Database of Systematic Reviews (search terms: poststroke aphasia, rTMS; restrictions: none) and PubMed (search terms: poststroke aphasia, rTMSs; restrictions: systematic review or meta-analysis) was performed. Information from studies involving different doses of rTMS in PSA was independently screened and extracted by 2 researchers.

RESULTS

This meta-analysis included 387 participants with PSA across 18 randomized controlled trials. The results showed that the total pulse had a trend toward a significant correlation with the treatment effect (P = 0.088), while all other variables did not correlate significantly. When rTMS was not grouped by stimulus parameter and location, our nonlinear results showed that when the total pulses were 40,000 (standardized mean difference (SMD):1.86, 95% credible interval (CrI) 0.50 to 3.33), the pulse/session was 1000 (SMD:1.05, 95% CrI 0.55-1.57), and an RMT of 80% (SMD:1.08, 95% CrI 0.60-1.57) had the best treatment effect. When rTMS was grouped by stimulus parameters and location, our nonlinear results showed that when the total low-frequency (LF)-rTMS-right inferior frontal gyrus (RIFG) pulse was 40,000 (SMD:1.76, 95% CrI:0.36-3.29), the pulse/session was 1000 (SMD:1.06, 95% CrI:0.54-1.59). Optimal results were obtained with an RMT of 80% (SMD:1.14, 95% CrI 0.54 - 1.76).

CONCLUSIONS

The optimal treatment effects of rTMS for PSA may be obtained with a total pulse of 40,000, a pulse/session of 1000, and an RMT of 80%. Further rigorous randomized controlled studies are required to substantiate the validity of these results.

Optimal dose and type of physical activity to improve functional capacity and minimise adverse events in acutely hospitalised older adults: a systematic review with dose-response network meta-analysis of randomised controlled trials

OBJECTIVE

To identify the optimal dose and type of physical activity to improve functional capacity and reduce adverse events in acutely hospitalised older adults.

DESIGN

Systematic review and Bayesian model-based network meta-analysis.

DATA SOURCES

Four databases were searched from inception to 20 June 2022.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Randomised controlled trials that assessed the effectiveness of a physical activity-based intervention on at least one functional outcome in people aged ≥50 years hospitalised due to an acute medical condition were included. Pooled effect estimates (ie, standardised mean differences for functional capacity and the ratio of means for adverse events) were calculated using random treatment effects network meta-analysis models.

RESULTS

Nineteen studies (3842 participants) met the inclusion criteria. Approximately 100 Metabolic Equivalents of Task per day (METs-min/day) (~40 min/day of light effort or ~25 min/day of moderate effort activities) was the minimal dose to improve the functional capacity of acute hospitalised older adults (standardised mean difference (SMD)=0.28, 95% credible interval (CrI) 0.01 to 0.55). The optimal dose was estimated at 159 METs-min/day (~70 min/day of light effort or ~40 min/day of moderate effort activities; SMD=0.41, 95% CrI 0.08 to 0.72). Ambulation was deemed the most efficient intervention, and the optimal dose was reached at 143 METs-min/day (~50 min/day of slow-paced walking; SMD=0.76, 95% CrI 0.35 to 1.16), showing a high evidential power (87.68%). The minimal effective ambulation dose was estimated at 74 METs-min/day (~25 min/day of slow-paced walking; SMD=0.25, 95% CrI 0.01 to 0.41). Physical activity interventions resulted in a decrease in the rate of adverse events compared with usual care at discharge (ratio of means=0.96, 95% CrI 0.95 to 0.97; median time 7 days).

CONCLUSIONS

This meta-analysis yielded low to moderate evidence supporting the use of in-hospital supervised physical activity programmes in acutely hospitalised older adults. As little as ~25 min/day of slow-paced walking is sufficient to improve functional capacity and minimise adverse events in this population.

TRIAL REGISTRATION NUMBER

PROSPERO CRD42021271999.

Optimal type and dose of hypoxic training for improving maximal aerobic capacity in athletes: a systematic review and Bayesian model-based network meta-analysis

Objective: This study aimed to compare and rank the effect of hypoxic practices on maximum oxygen consumption (VO2max) in athletes and determine the hypoxic dose-response correlation using network meta-analysis. Methods: The Web of Science, PubMed, EMBASE, and EBSCO databases were systematically search for randomized controlled trials on the effect of hypoxc interventions on the VO2max of athletes published from inception until 21 February 2023. Studies that used live-high train-high (LHTH), live-high train-low (LHTL), live-high, train-high/low (HHL), intermittent hypoxic training (IHT), and intermittent hypoxic exposure (IHE) interventions were primarily included. LHTL was further defined according to the type of hypoxic environment (natural and simulated) and the altitude of the training site (low altitude and sea level). A meta-analysis was conducted to determine the standardized mean difference between the effects of various hypoxic interventions on VO2max and dose-response correlation. Furthermore, the hypoxic dosage of the different interventions were coordinated using the "kilometer hour" model. Results: From 2,072 originally identified titles, 59 studies were finally included in this study. After data pooling, LHTL, LHTH, and IHT outperformed normoxic training in improving the VO2max of athletes. According to the P-scores, LHTL combined with low altitude training was the most effective intervention for improving VO2max (natural: 0.92 and simulated: 0.86) and was better than LHTL combined with sea level training (0.56). A reasonable hypoxic dose range for LHTH (470-1,130 kmh) and HL (500-1,415 kmh) was reported with an inverted U-shaped curve relationship. Conclusion: Different types of hypoxic training compared with normoxic training serve as significant approaches for improving aerobic capacity in athletes. Regardless of the type of hypoxic training and the residential condition, LHTL with low altitude training was the most effective intervention. The characteristics of the dose-effect correlation of LHTH and LHTL may be associated with the negative effects of chronic hypoxia.

Assessing the Practical Differences in LDL-C Estimates Calculated by Friedewald, Martin/Hopkins, or NIH Equation 2: An Observation Cross-Sectional Study

Objective

Low-density lipoprotein-cholesterol (LDL-C) remains a clinically important cholesterol target in primary prevention of atherosclerotic cardiovascular disease. The present study aimed to assess the practical differences among three equations utilized for the estimation of LDL-C: the Friedewald, the Martin/Hopkins, and the NIH equation 2.

Methods

Blood lipid measurements from 4,556 noninstitutionalized participants, aged 12 to 80, were obtained from the 2017-2020 National Health and Nutrition Examination Survey study. We 1) assessed the differences between three calculated LDL-C estimates, 2) examined the correlations between LDL-C estimates using correlation coefficients and regression, and 3) investigated the degree of agreement in classifying individuals into the LDL-C category using weighted Kappa and percentage of agreement.

Results

The differences in LDL-C estimates between equations varied by sex and triglyceride levels (p<0.001). Overall, the mean of absolute differences between Friedewald and Martin/Hopkins was 3.17 mg/dL (median=2.0, 95% confidence interval [CI] [3.07-3.27]). The mean of absolute differences between Friedewald and NIH Equation 2 was 2.08 mg/dL (median=2.0, 95% CI [2.03-2.14]). Friedewald correlated highly with Martin/Hopkins (r=0.991, rho=0.989) and NIH Equation 2 (r=0.998, rho=0.997). Cohen's weighted Kappa=0.92 between Friedewald and Martin/Hopkins, and 0.95 between Friedewald and NIH equation 2. The percentage of agreement in classifying individuals into the same LDL-C category was 93.0% between Friedewald and Martin/Hopkins, and 95.4% between Friedewald and NIH equation 2.

Conclusion

Understanding the practical differences in LDL-C calculations can be helpful in facilitating decision-making during a paradigm shift.

Public Preference Heterogeneity and Predicted Uptake Rate of Upper Gastrointestinal Cancer Screening Programs in Rural China: Discrete Choice Experiments and Latent Class Analysis

BACKGROUND

Rapid increases in the morbidity and mortality of patients with upper gastrointestinal cancer (UGC) in high-incidence countries in Asia have raised public health concerns. Screening can effectively reduce the incidence and mortality of patients with UGC, but the low population uptake rate seriously affects the screening effect.

OBJECTIVE

We aimed to determine the characteristics that influence residents' preference heterogeneity for a UGC-screening program and the extent to which these characteristics predict residents' uptake rates.

METHODS

A discrete choice experiment was conducted in 1000 residents aged 40-69 years who were randomly selected from 3 counties (Feicheng, Linqu, and Dongchangfu) in Shandong Province, China. Each respondent was repeatedly asked to choose from 9 discrete choice questions of 2 hypothetical screening programs comprising 5 attributes: screening interval, screening technique, regular follow-up for precancerous lesions, mortality reduction, and out-of-pocket costs. The latent class logit model was used to estimate residents' preference heterogeneity for each attribute level, their willingness to pay, and the expected uptake rates.

RESULTS

Of the 1000 residents invited, 926 (92.6%) were included in the final analyses. The mean age was 57.32 (SD 7.22) years. The best model contained 4 classes of respondents (Akaike information criterion=7140.989, Bayesian information criterion=7485.373) defined by different preferences for the 5 attributes. In the 4-class model, out of 926 residents, 88 (9.5%) were assigned to class 1, named as the negative latent type; 216 (3.3%) were assigned to class 2, named as the positive integrated type; 434 (46.9%) were assigned to class 3, named as the positive comfortable type; and 188 (20.3%) were assigned to class 4, named as the neutral quality type. For these 4 latent classes, "out-of-pocket cost" is the most preferred attribute in negative latent type and positive integrated type residents (45.04% vs 66.04% importance weights), whereas "screening technique" is the most preferred factor in positive comfortable type residents (62.56% importance weight) and "screening interval" is the most valued attribute in neutral quality type residents (47.05% importance weight). Besides, residents in different classes had common preference for painless endoscopy, and their willingness to pay were CNY ¥385.369 (US $59.747), CNY ¥93.44 (US $14.486), CNY ¥1946.48 (US $301.810), and CNY ¥3566.60 (US $552.961), respectively. Residents' participation rate could increase by more than 89% (except for the 60.98% in class 2) if the optimal UGC screening option with free, follow-up for precancerous lesions, 45% mortality reduction, screening every year, and painless endoscopy was implemented.

CONCLUSIONS

Public preference heterogeneity for UGC screening does exist. Most residents have a positive attitude toward UGC screening, but their preferences vary in selected attributes and levels, except for painless endoscopy. Policy makers should consider these heterogeneities to formulate UGC-screening programs that incorporate the public's needs and preferences to improve participation rates.

Identifying deprived "slum" neighbourhoods in the Greater Accra Metropolitan Area of Ghana using census and remote sensing data

Background

Identifying urban deprived areas, including slums, can facilitate more targeted planning and development policies in cities to reduce socio-economic and health inequities, but methods to identify them are often ad-hoc, resource intensive, and cannot keep pace with rapidly urbanizing communities.

Objectives

We apply a spatial modelling approach to identify census enumeration areas (EAs) in the Greater Accra Metropolitan Area (GAMA) of Ghana with a high probability of being a deprived area using publicly available census and remote sensing data.

Methods

We obtained United Nations (UN) supported field mapping data that identified deprived "slum" areas in Accra's urban core, data on housing and population conditions from the most recent census, and remotely sensed data on environmental conditions in the GAMA. We first fitted a Bayesian logistic regression model on the data in Accra's urban core (n=2,414 EAs) that estimated the relationship between housing, population, and environmental predictors and being a deprived area according to the UN's deprived area assessment. Using these relationships, we predicted the probability of being a deprived area for each of the 4,615 urban EAs in GAMA.

Results

899 (19%) of the 4,615 urban EAs in GAMA, with an estimated 745,714 residents (22% of its urban population), had a high predicted probability (≥80%) of being a deprived area. These deprived EAs were dispersed across GAMA and relatively heterogeneous in their housing and environmental conditions, but shared some common features including a higher population density, lower elevation and vegetation abundance, and less access to indoor piped water and sanitation.

Conclusion

Our approach using ubiquitously available administrative and satellite data can be used to identify deprived neighbourhoods where interventions are warranted to improve living conditions, and track progress in achieving the Sustainable Development Goals aiming to reduce the population living in unsafe or vulnerable human settlements.

Can monetary incentives overturn fairness-based decisions?

Fairness norms and resulting behaviours are an important prerequisite for cooperation in human societies. At the same time, financial incentives are commonly used to motivate social behaviours, yet it remains unclear how financial incentives affect fairness-based behaviours. Combining a decision paradigm from behavioural economics with hierarchical drift-diffusion modelling, we investigated the effect of different financial incentives on two types of fairness-based decisions in four experimental groups. In two groups, participants divided points between themselves and a disadvantaged person, inciting fairness-based compensation behaviour, in two other groups they divided points between themselves and a fairness violator, inciting fairness-based punishment behaviour. In addition, each group received financial incentives that were either aligned or in conflict with the respective fairness-based behaviour. This design allowed us to directly investigate how different incentives shape the cognitive mechanism of fairness-based decisions and whether these effects are comparable across different fairness domains (fairness-based punishment versus fairness-based compensation). Results showed that offering conflicting incentives diminished fairness-congruent decision behaviour and rendered the fairness-congruent decision process less efficient. These findings demonstrate that financial incentives can undermine fairness-based behaviour, and thus are relevant for the development of incentive schemes aimed at fostering cooperative behaviour.

Expert agreement in prior elicitation and its effects on Bayesian inference

Bayesian inference requires the specification of prior distributions that quantify the pre-data uncertainty about parameter values. One way to specify prior distributions is through prior elicitation, an interview method guiding field experts through the process of expressing their knowledge in the form of a probability distribution. However, prior distributions elicited from experts can be subject to idiosyncrasies of experts and elicitation procedures, raising the spectre of subjectivity and prejudice. Here, we investigate the effect of interpersonal variation in elicited prior distributions on the Bayes factor hypothesis test. We elicited prior distributions from six academic experts with a background in different fields of psychology and applied the elicited prior distributions as well as commonly used default priors in a re-analysis of 1710 studies in psychology. The degree to which the Bayes factors vary as a function of the different prior distributions is quantified by three measures of concordance of evidence: We assess whether the prior distributions change the Bayes factor direction, whether they cause a switch in the category of evidence strength, and how much influence they have on the value of the Bayes factor. Our results show that although the Bayes factor is sensitive to changes in the prior distribution, these changes do not necessarily affect the qualitative conclusions of a hypothesis test. We hope that these results help researchers gauge the influence of interpersonal variation in elicited prior distributions in future psychological studies. Additionally, our sensitivity analyses can be used as a template for Bayesian robustness analyses that involve prior elicitation from multiple experts.

Navigating the Statistical Minefield of Model Selection and Clustering in Neuroscience

Model selection is often implicit: when performing an ANOVA, one assumes that the normal distribution is a good model of the data; fitting a tuning curve implies that an additive and a multiplicative scaler describes the behavior of the neuron; even calculating an average implicitly assumes that the data were sampled from a distribution that has a finite first statistical moment: the mean. Model selection may be explicit, when the aim is to test whether one model provides a better description of the data than a competing one. As a special case, clustering algorithms identify groups with similar properties within the data. They are widely used from spike sorting to cell type identification to gene expression analysis. We discuss model selection and clustering techniques from a statistician's point of view, revealing the assumptions behind, and the logic that governs the various approaches. We also showcase important neuroscience applications and provide suggestions how neuroscientists could put model selection algorithms to best use as well as what mistakes should be avoided.

Behavioural and neural indices of perceptual decision-making in autistic children during visual motion tasks

Many studies report atypical responses to sensory information in autistic individuals, yet it is not clear which stages of processing are affected, with little consideration given to decision-making processes. We combined diffusion modelling with high-density EEG to identify which processing stages differ between 50 autistic and 50 typically developing children aged 6-14 years during two visual motion tasks. Our pre-registered hypotheses were that autistic children would show task-dependent differences in sensory evidence accumulation, alongside a more cautious decision-making style and longer non-decision time across tasks. We tested these hypotheses using hierarchical Bayesian diffusion models with a rigorous blind modelling approach, finding no conclusive evidence for our hypotheses. Using a data-driven method, we identified a response-locked centro-parietal component previously linked to the decision-making process. The build-up in this component did not consistently relate to evidence accumulation in autistic children. This suggests that the relationship between the EEG measure and diffusion-modelling is not straightforward in autistic children. Compared to a related study of children with dyslexia, motion processing differences appear less pronounced in autistic children. Exploratory analyses also suggest weak evidence that ADHD symptoms moderate perceptual decision-making in autistic children.

Optimal dose and type of exercise to improve cognitive function in older adults: A systematic review and bayesian model-based network meta-analysis of RCTs

OBJECTIVE

To examine the dose-response relationship between overall and specific types of exercise with cognitive function in older adults.

DESIGN

Systematic Review and Bayesian Model-Based Network Meta-Analysis.

DATA SOURCES

Systematic search of MEDLINE, Web of Science, Scopus, PsycINFO and SPORTDiscus.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Randomized controlled trials of exercise interventions in participants aged 50 years or over, and that reported on at least one global cognition outcome.

RESULTS

The search returned 1998 records, of which 44 studies (4793 participants; 102 different effect sizes) were included in this review with meta-analysis. There was a non-linear, dose-response association between overall exercise and cognition. We found no minimal threshold for the beneficial effect of exercise on cognition. The estimated minimal exercise dose associated with clinically relevant changes in cognition was 724 METs-min per week, and doses beyond 1200 METs-min per week provided less clear benefits. We also found that the dose-response association was exercise type dependent, and our results show that clinically important effects may occur at lower doses for many types of exercise. Our findings also highlighted the superior effects of resistance exercises over other modalities.

CONCLUSIONS

If provided with the most potent modalities, older adults can get clinical meaningful benefits with lower doses than the WHO guidelines. Findings support the WHO recommendations to emphasise resistance training as a critical component of interventions for older adults.

Microbial Translocation and Perinatal Asphyxia/Hypoxia: A Systematic Review

The microbiome is vital for the proper function of the gastrointestinal tract (GIT) and the maintenance of overall wellbeing. Gut ischemia may lead to disruption of the intestinal mucosal barrier, resulting in bacterial translocation. In this systematic review, according to PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) guidelines, we constructed a search query using the PICOT (Patient, Intervention, Comparison, Outcome, Time) framework. Eligible studies reported in PubMed, up to April 2021 were selected, from which, 57 publications’ data were included. According to these, escape of intraluminal potentially harmful factors into the systemic circulation and their transmission to distant organs and tissues, in utero, at birth, or immediately after, can be caused by reduced blood oxygenation. Various factors are involved in this situation. The GIT is a target organ, with high sensitivity to ischemia–hypoxia, and even short periods of ischemia may cause significant local tissue damage. Fetal hypoxia and perinatal asphyxia reduce bowel motility, especially in preterm neonates. Despite the fact that microbiome arouse the interest of scientists in recent decades, the pathophysiologic patterns which mediate in perinatal hypoxia/asphyxia conditions and gut function have not yet been well understood.

Visual Motion and Decision-Making in Dyslexia: Reduced Accumulation of Sensory Evidence and Related Neural Dynamics

Children with and without dyslexia differ in their behavioral responses to visual information, particularly when required to pool dynamic signals over space and time. Importantly, multiple processes contribute to behavioral responses. Here we investigated which processing stages are affected in children with dyslexia when performing visual motion processing tasks, by combining two methods that are sensitive to the dynamic processes leading to responses. We used a diffusion model which decomposes response time and accuracy into distinct cognitive constructs, and high-density EEG. Fifty children with dyslexia (24 male) and 50 typically developing children (28 male) 6-14 years of age judged the direction of motion as quickly and accurately as possible in two global motion tasks (motion coherence and direction integration), which varied in their requirements for noise exclusion. Following our preregistered analyses, we fitted hierarchical Bayesian diffusion models to the data, blinded to group membership. Unblinding revealed reduced evidence accumulation in children with dyslexia compared with typical children for both tasks. Additionally, we identified a response-locked EEG component which was maximal over centro-parietal electrodes which indicated a neural correlate of reduced drift rate in dyslexia in the motion coherence task, thereby linking brain and behavior. We suggest that children with dyslexia tend to be slower to extract sensory evidence from global motion displays, regardless of whether noise exclusion is required, thus furthering our understanding of atypical perceptual decision-making processes in dyslexia.SIGNIFICANCE STATEMENT Reduced sensitivity to visual information has been reported in dyslexia, with a lively debate about whether these differences causally contribute to reading difficulties. In this large preregistered study with a blind modeling approach, we combine state-of-the art methods in both computational modeling and EEG analysis to pinpoint the stages of processing that are atypical in children with dyslexia in two visual motion tasks that vary in their requirement for noise exclusion. We find reduced evidence accumulation in children with dyslexia across both tasks, and identify a neural marker, allowing us to link brain and behavior. We show that children with dyslexia exhibit general difficulties with extracting sensory evidence from global motion displays, not just in tasks that require noise exclusion.

Preregistration in diverse contexts: a preregistration template for the application of cognitive models

In recent years, open science practices have become increasingly popular in psychology and related sciences. These practices aim to increase rigour and transparency in science as a potential response to the challenges posed by the replication crisis. Many of these reforms-including the increasingly used preregistration-have been designed for purely experimental work that tests straightforward hypotheses with standard inferential statistical analyses, such as assessing whether an experimental manipulation has an effect on a variable of interest. But psychology is a diverse field of research. The somewhat narrow focus of the prevalent discussions surrounding and templates for preregistration has led to debates on how appropriate these reforms are for areas of research with more diverse hypotheses and more intricate methods of analysis, such as cognitive modelling research within mathematical psychology. Our article attempts to bridge the gap between open science and mathematical psychology, focusing on the type of cognitive modelling that Crüwell et al. (Crüwell S, Stefan AM, Evans NJ. 2019 Robust standards in cognitive science. Comput. Brain Behav. 2, 255-265) labelled model application, where researchers apply a cognitive model as a measurement tool to test hypotheses about parameters of the cognitive model. Specifically, we (i) discuss several potential researcher degrees of freedom within model application, (ii) provide the first preregistration template for model application and (iii) provide an example of a preregistered model application using our preregistration template. More broadly, we hope that our discussions and concrete proposals constructively advance the mostly abstract current debate surrounding preregistration in cognitive modelling, and provide a guide for how preregistration templates may be developed in other diverse or intricate research contexts.

Neurocomputational models of altruistic decision-making and social motives: Advances, pitfalls, and future directions

This article discusses insights from computational models and social neuroscience into motivations, precursors, and mechanisms of altruistic decision-making and other-regard. We introduce theoretical and methodological tools for researchers who wish to adopt a multilevel, computational approach to study behaviors that promote others' welfare. Using examples from recent studies, we outline multiple mental and neural processes relevant to altruism. To this end, we integrate evidence from neuroimaging, psychology, economics, and formalized mathematical models. We introduce basic mechanisms-pertinent to a broad range of value-based decisions-and social emotions and cognitions commonly recruited when our decisions involve other people. Regarding the latter, we discuss how decomposing distinct facets of social processes can advance altruistic models and the development of novel, targeted interventions. We propose that an accelerated synthesis of computational approaches and social neuroscience represents a critical step towards a more comprehensive understanding of altruistic decision-making. We discuss the utility of this approach to study lifespan differences in social preference in late adulthood, a crucial future direction in aging global populations. Finally, we review potential pitfalls and recommendations for researchers interested in applying a computational approach to their research. This article is categorized under: Economics > Interactive Decision-Making Psychology > Emotion and Motivation Neuroscience > Cognition Economics > Individual Decision-Making.

Think fast! The implications of emphasizing urgency in decision-making

Evidence accumulation models (EAMs) have become the dominant explanation of how the decision-making process operates, proposing that decisions are the result of a process of evidence accumulation. The primary use of EAMs has been as "measurement tools" of the underlying decision-making process, where researchers apply EAMs to empirical data to estimate participants' task ability (i.e., the "drift rate"), response caution (i.e., the "decision threshold"), and the time taken for other processes (i.e., the "non-decision time"), making EAMs a powerful tool for discriminating between competing psychological theories. Recent studies have brought into question the mapping between the latent parameters of EAMs and the theoretical constructs that they are thought to represent, showing that emphasizing urgent responding - which intuitively should selectively influence decision threshold - may also influence drift rate and/or non-decision time. However, these findings have been mixed, leading to differences in opinion between experts in the field. The current study aims to provide a more conclusive answer to the implications of emphasizing urgent responding, providing a re-analysis of 6 data sets from previous studies using two different EAMs - the diffusion model and the linear ballistic accumulator (LBA) - with state-of-the-art methods for model selection based inference. The findings display clear evidence for a difference in conclusions between the two models, with the diffusion model suggesting that decision threshold and non-decision time decrease when urgency is emphasized, and the LBA suggesting that decision threshold and drift rate decrease when urgency is emphasized. Furthermore, although these models disagree regarding whether non-decision time or drift rate decrease under urgency emphasis, both show clear evidence that emphasizing urgency does not selectively influence decision threshold. These findings suggest that researchers should revise their assumptions about certain experimental manipulations, the specification of certain EAMs, or perhaps both.

Perceptual Decision-Making in Children: Age-Related Differences and EEG Correlates

Children make faster and more accurate decisions about perceptual information as they get older, but it is unclear how different aspects of the decision-making process change with age. Here, we used hierarchical Bayesian diffusion models to decompose performance in a perceptual task into separate processing components, testing age-related differences in model parameters and links to neural data. We collected behavioural and EEG data from 96 6- to 12-year-old children and 20 adults completing a motion discrimination task. We used a component decomposition technique to identify two response-locked EEG components with ramping activity preceding the response in children and adults: one with activity that was maximal over centro-parietal electrodes and one that was maximal over occipital electrodes. Younger children had lower drift rates (reduced sensitivity), wider boundary separation (increased response caution) and longer non-decision times than older children and adults. Yet, model comparisons suggested that the best model of children's data included age effects only on drift rate and boundary separation (not non-decision time). Next, we extracted the slope of ramping activity in our EEG components and covaried these with drift rate. The slopes of both EEG components related positively to drift rate, but the best model with EEG covariates included only the centro-parietal component. By decomposing performance into distinct components and relating them to neural markers, diffusion models have the potential to identify the reasons why children with developmental conditions perform differently to typically developing children and to uncover processing differences inapparent in the response time and accuracy data alone.

ChaRTr: An R toolbox for modeling choices and response times in decision-making tasks

BACKGROUND

Decision-making is the process of choosing and performing actions in response to sensory cues to achieve behavioral goals. Many mathematical models have been developed to describe the choice behavior and response time (RT) distributions of observers performing decision-making tasks. However, relatively few researchers use these models because it demands expertise in various numerical, statistical, and software techniques.

NEW METHOD

We present a toolbox - Choices and Response Times in R, or ChaRTr - that provides the user the ability to implement and test a wide variety of decision-making models ranging from classic through to modern versions of the diffusion decision model, to models with urgency signals, or collapsing boundaries.

RESULTS

In three different case studies, we demonstrate how ChaRTr can be used to effortlessly discriminate between multiple models of decision-making behavior. We also provide guidance on how to extend the toolbox to incorporate future developments in decision-making models.

COMPARISON WITH EXISTING METHOD(S)

Existing software packages surmounted some of the numerical issues but have often focused on the classical decision-making model, the diffusion decision model. Recent models that posit roles for urgency, time-varying decision thresholds, noise in various aspects of the decision-formation process or low pass filtering of sensory evidence have proven to be challenging to incorporate in a coherent software framework that permits quantitative evaluation among these competing classes of decision-making models.

CONCLUSION

ChaRTr can be used to make insightful statements about the cognitive processes underlying observed decision-making behavior and ultimately for deeper insights into decision mechanisms.