Human social sensing is an untapped resource for computational social science.

The ability to 'sense' the social environment and thereby to understand the thoughts and actions of others allows humans to fit into their social worlds, communicate and cooperate, and learn from others' experiences. Here we argue that, through the lens of computational social science, this ability can be used to advance research into human sociality. When strategically selected to represent a specific population of interest, human social sensors can help to describe and predict societal trends. In addition, their reports of how they experience their social worlds can help to build models of social dynamics that are constrained by the empirical reality of human social systems.

Sampling complex social and behavioral phenomena.

We comment on the limits of relying on prior literature when constructing the design space for an integrative experiment; the adaptive nature of social and behavioral phenomena and the implications for the use of theory and modeling when constructing the design space; and on the challenges of measuring random errors and lab-related biases in measurement without replication.

Interobserver reproducibility of cribriform cancer in prostate needle biopsies and validation of International Society of Urological Pathology criteria.

AIMS: There is strong evidence that cribriform morphology indicates a worse prognosis of prostatic adenocarcinoma. Our aim was to investigate its interobserver reproducibility in prostate needle biopsies. METHODS AND RESULTS: A panel of nine prostate pathology experts from five continents independently reviewed 304 digitised biopsies for cribriform cancer according to recent International Society of Urological Pathology criteria. The biopsies were collected from a series of 702 biopsies that were reviewed by one of the panellists for enrichment of high-grade cancer and potentially cribriform structures. A 2/3 consensus diagnosis of cribriform and noncribriform cancer was reached in 90% (272/304) of the biopsies with a mean kappa value of 0.56 (95% confidence interval 0.52-0.61). The prevalence of consensus cribriform cancers was estimated to 4%, 12%, 21%, and 20% of Gleason scores 7 (3 + 4), 7 (4 + 3), 8, and 9-10, respectively. More than two cribriform structures per level or a largest cribriform mass with ≥9 lumina or a diameter of ≥0.5 mm predicted a consensus diagnosis of cribriform cancer in 88% (70/80), 84% (87/103), and 90% (56/62), respectively, and noncribriform cancer in 3% (2/80), 5% (5/103), and 2% (1/62), respectively (all P < 0.01). CONCLUSION: Cribriform prostate cancer was seen in a minority of needle biopsies with high-grade cancer. Stringent diagnostic criteria enabled the identification of cribriform patterns and the generation of a large set of consensus cases for standardisation.

Cross-cultural adaption and inter-rater reliability of the Swedish version of the updated clinical frailty scale 2.0.

BACKGROUND: Worldwide, there is a large and growing group of older adults. Frailty is known as an important discriminatory factor for poor outcomes. The Clinical Frailty Scale (CFS) has become a frequently used frailty instrument in different clinical settings and health care sectors, and it has shown good predictive validity. The aims of this study were to describe and validate the translation and cultural adaptation of the CFS into Swedish (CFS-SWE), and to test the inter-rater reliability (IRR) for registered nurses using the CFS-SWE. METHODS: An observational study design was employed. The ISPOR principles were used for the translation, linguistic validation and cultural adaptation of the scale. To test the IRR, 12 participants were asked to rate 10 clinical case vignettes using the CFS-SWE. The IRR was assessed using intraclass correlation and Krippendorff's alpha agreement coefficient test. RESULTS: The Clinical Frailty Scale was translated and culturally adapted into Swedish and is presented in its final form. The IRR for all raters, measured by an intraclass correlation test, resulted in an absolute agreement value among the raters of 0.969 (95% CI: 0.929-0.991) and a consistency value of 0.979 (95% CI: 0.953-0.994), which indicates excellent reliability. Krippendorff's alpha agreement coefficient for all raters was 0.969 (95% CI: 0.917-0.988), indicating near-perfect agreement. The sensitivity of the reliability was examined by separately testing the IRR of the group of specialised registered nurses and non-specialised registered nurses respectively, with consistent and similar results. CONCLUSION: The Clinical Frailty Scale was translated, linguistically validated and culturally adapted into Swedish following a well-established standard technique. The IRR was excellent, judged by two established, separately used, reliability tests. The reliability test results did not differ between non-specialised and specialised registered nurses. However, the use of case vignettes might reduce the generalisability of the reliability findings to real-life settings. The CFS has the potential to be a common reference tool, especially when older adults are treated and rehabilitated in different care sectors.

OpenPhi: an interface to access Philips iSyntax whole slide images for computational pathology.

SUMMARY: Digital pathology enables applying computational methods, such as deep learning, in pathology for improved diagnostics and prognostics, but lack of interoperability between whole slide image formats of different scanner vendors is a challenge for algorithm developers. We present OpenPhi-Open PatHology Interface, an Application Programming Interface for seamless access to the iSyntax format used by the Philips Ultra Fast Scanner, the first digital pathology scanner approved by the United States Food and Drug Administration. OpenPhi is extensible and easily interfaced with existing vendor-neutral applications. AVAILABILITY AND IMPLEMENTATION: OpenPhi is implemented in Python and is available as open-source under the MIT license at: https://gitlab.com/BioimageInformaticsGroup/openphi. The Philips Software Development Kit is required and available at: https://www.openpathology.philips.com. OpenPhi version 1.1.1 is additionally provided as Supplementary Data. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Microbial community development during syngas methanation in a trickle bed reactor with various nutrient sources.

Microbial community development within an anaerobic trickle bed reactor (TBR) during methanation of syngas (56% H2, 30% CO, 14% CO2) was investigated using three different nutrient media: defined nutrient medium (241 days), diluted digestate from a thermophilic co-digestion plant operating with food waste (200 days) and reject water from dewatered digested sewage sludge at a wastewater treatment plant (220 days). Different TBR operating periods showed slightly different performance that was not clearly linked to the nutrient medium, as all proved suitable for the methanation process. During operation, maximum syngas load was 5.33 L per L packed bed volume (pbv) & day and methane (CH4) production was 1.26 L CH4/Lpbv/d. Microbial community analysis with Illumina Miseq targeting 16S rDNA revealed high relative abundance (20-40%) of several potential syngas and acetate consumers within the genera Sporomusa, Spirochaetaceae, Rikenellaceae and Acetobacterium during the process. These were the dominant taxa except in a period with high flow rate of digestate from the food waste plant. The dominant methanogen in all periods was a member of the genus Methanobacterium, while Methanosarcina was also observed in the carrier community. As in reactor effluent, the dominant bacterial genus in the carrier was Sporomusa. These results show that syngas methanation in TBR can proceed well with different nutrient sources, including undefined medium of different origins. Moreover, the dominant syngas community remained the same over time even when non-sterilised digestates were used as nutrient medium. KEY POINTS: • Independent of nutrient source, syngas methanation above 1 L/Lpbv/D was achieved. • Methanobacterium and Sporomusa were dominant genera throughout the process. • Acetate conversion proceeded via both methanogenesis and syntrophic acetate oxidation.

Predictors of short- and long-term mortality in critically ill, older adults admitted to the emergency department: an observational study.

BACKGROUND: In the future, we can expect an increase in older patients in emergency departments (ED) and acute wards. The main purpose of this study was to identify predictors of short- and long-term mortality in the ED and at hospital discharge. METHODS: This is a retrospective, observational, single-center, cohort study, involving critically ill older adults, recruited consecutively in an ED. The primary outcome was mortality. All patients were followed for 6.5-7.5 years. The Cox proportional hazards model was used. RESULTS: Regarding all critically ill patients aged ≥ 70 years and identified in the ED (n = 402), there was a significant association between mortality at 30 days after ED admission and unconsciousness on admission (HR 3.14, 95% CI 2.09-4.74), hypoxia on admission (HR 2.51, 95% CI 1.69-3.74) and age (HR 1.06 per year, 95% CI 1.03-1.09), (all p < 0.001). Of 402 critically ill patients aged ≥ 70 years and identified in the ED, 303 were discharged alive from hospital. There was a significant association between long-term mortality and the Charlson Comorbidity Index (CCI) > 2 (HR 1.90, 95% CI 1.46-2.48), length of stay (LOS) > 7 days (HR 1.72, 95% CI 1.32-2.23), discharge diagnosis of pneumonia (HR 1.65, 95% CI 1.24-2.21) and age (HR 1.08 per year, 95% CI 1.05-1.10), (all p < 0.001). The only symptom or vital sign associated with long-term mortality was hypoxia on admission (HR 1.70, 05% CI 1.30-2.22). CONCLUSIONS: Among critically ill older adults admitted to an ED and discharged alive the following factors were predictive of long-term mortality: CCI > 2, LOS > 7 days, hypoxia on admission, discharge diagnosis of pneumonia and age. The following factors were predictive of mortality at 30 days after ED admission: unconsciousness on admission, hypoxia and age. These data might be clinically relevant when it comes to individualized care planning, which should take account of risk prediction and estimated prognosis.

Predictors of adverse pathology on radical prostatectomy specimen in men initially enrolled in active surveillance for low-risk prostate cancer.

PURPOSE: To evaluate clinical variables, including magnetic resonance imaging (MRI) predictive of adverse pathology (AP) at radical prostatectomy (RP) in men initially enrolled in active surveillance (AS). METHODS: A population-based cohort study of men diagnosed with low-risk prostate cancer (PCa), in Stockholm County, Sweden, during 2008-2017 enrolled in AS their intended primary treatment followed by RP. AP was defined as ISUP grade group ≥ 3 and/or pT-stage ≥ T3. Association between clinical variables at diagnosis and time to AP was evaluated using Cox regression and multivariate logistic regression to evaluate the association between AP and clinical variables at last biopsy before RP. RESULTS: In a cohort of 6021 patients with low-risk PCa, 3116 were selected for AS and 216 underwent RP. Follow-up was 10 years, with a median time on AS of 23 months. 37.7% of patients had AP at RP. Clinical T-stage [Hazard ratio (HR): 1.81, 95% confidence interval (CI) 1.04-3.18] and PSA (HR: 1.31, 95% CI 1.17-1.46) at diagnosis and age [Odds Ratio (OR): 1.09, 95% CI 1.02-1.18), PSA (OR: 1.22, 95% CI 1.07-1.41), and PI-RADS (OR 1.66, 95% CI 1.11-2.55)] at last re-biopsy were significantly associated with AP. CONCLUSION: PI-RADS score is significantly associated with AP at RP and support current guidelines recommending MRI before enrollment in AS. Furthermore, age, cT-stage, and PSA are significantly associated with AP.

Artificial intelligence for diagnosis and grading of prostate cancer in biopsies: a population-based, diagnostic study.

BACKGROUND: An increasing volume of prostate biopsies and a worldwide shortage of urological pathologists puts a strain on pathology departments. Additionally, the high intra-observer and inter-observer variability in grading can result in overtreatment and undertreatment of prostate cancer. To alleviate these problems, we aimed to develop an artificial intelligence (AI) system with clinically acceptable accuracy for prostate cancer detection, localisation, and Gleason grading. METHODS: We digitised 6682 slides from needle core biopsies from 976 randomly selected participants aged 50-69 in the Swedish prospective and population-based STHLM3 diagnostic study done between May 28, 2012, and Dec 30, 2014 (ISRCTN84445406), and another 271 from 93 men from outside the study. The resulting images were used to train deep neural networks for assessment of prostate biopsies. The networks were evaluated by predicting the presence, extent, and Gleason grade of malignant tissue for an independent test dataset comprising 1631 biopsies from 246 men from STHLM3 and an external validation dataset of 330 biopsies from 73 men. We also evaluated grading performance on 87 biopsies individually graded by 23 experienced urological pathologists from the International Society of Urological Pathology. We assessed discriminatory performance by receiver operating characteristics and tumour extent predictions by correlating predicted cancer length against measurements by the reporting pathologist. We quantified the concordance between grades assigned by the AI system and the expert urological pathologists using Cohen's kappa. FINDINGS: The AI achieved an area under the receiver operating characteristics curve of 0·997 (95% CI 0·994-0·999) for distinguishing between benign (n=910) and malignant (n=721) biopsy cores on the independent test dataset and 0·986 (0·972-0·996) on the external validation dataset (benign n=108, malignant n=222). The correlation between cancer length predicted by the AI and assigned by the reporting pathologist was 0·96 (95% CI 0·95-0·97) for the independent test dataset and 0·87 (0·84-0·90) for the external validation dataset. For assigning Gleason grades, the AI achieved a mean pairwise kappa of 0·62, which was within the range of the corresponding values for the expert pathologists (0·60-0·73). INTERPRETATION: An AI system can be trained to detect and grade cancer in prostate needle biopsy samples at a ranking comparable to that of international experts in prostate pathology. Clinical application could reduce pathology workload by reducing the assessment of benign biopsies and by automating the task of measuring cancer length in positive biopsy cores. An AI system with expert-level grading performance might contribute a second opinion, aid in standardising grading, and provide pathology expertise in parts of the world where it does not exist. FUNDING: Swedish Research Council, Swedish Cancer Society, Swedish eScience Research Center, EIT Health.

Is there any association between prostate-specific antigen screening frequency and uptake of active surveillance in men with low or very low risk prostate cancer?

BACKGROUND: Patient-related factors such as concern about cancer are believed to influence both men's decisions to undergo prostate specific antigen (PSA) testing and to have definitive treatment if diagnosed with low risk prostate cancer (PCa). The potential link between screening frequency and choice of active surveillance (AS) for low risk disease has not been studied previously. Our aim was to investigate whether there is any association between PCa screening frequency or previous negative prostate biopsy and uptake of AS among men with low risk PCa. METHODS: This register-based study included all men ≤75 years from Stockholm who were diagnosed with low risk PCa from 2008 to 2014 (n = 4336). Pre-diagnostic PSA testing and biopsy histories were obtained from the Stockholm PSA and Biopsy Register, a population-based register for the Stockholm country. The association between previous screening/biopsy history and AS uptake (based on primary treatment recorded in the National Prostate Cancer Register) was examined using multivariable logistic regression. RESULTS: Forty seven percent of men with low risk PCa underwent AS. Uptake was associated with older age, very low risk disease, more recent diagnosis and absence of family history. None of the screening/biopsy measures (testing frequency, mean interval, PSA velocity, highest pre-diagnostic PSA or prior negative biopsy) were associated with uptake of AS among men with low risk PCa. Generalisability to settings with different policies and practices may be limited. CONCLUSION: We found no evidence that screening frequency and negative biopsy influence uptake of AS among Swedish men with low risk PCa. Further research is required to determine factors that still present barriers for men taking up AS.

Maternal depressive symptoms, maternal asthma, and asthma in school-aged children.

BACKGROUND: Little is known about the joint effects of maternal asthma and maternal depression on childhood asthma. OBJECTIVE: To examine whether maternal depression and maternal asthma lead to greater risk of childhood asthma than maternal asthma alone. METHODS: Cross-sectional studies of children (6-14 years old) in San Juan, Puerto Rico (n = 655) and Sweden (n = 6,887) were conducted. In Puerto Rico, maternal depressive symptoms were defined using the Center for Epidemiologic Studies Depression Scale (CES-D) questionnaire. In Sweden, maternal physician-diagnosed depression was derived from national registries, and maternal depressive symptoms were defined using an abbreviated CES-D questionnaire. Childhood asthma was defined as physician-diagnosed asthma plus current wheeze (in Puerto Rico) or plus medication use (in Sweden). Logistic regression was used for multivariable analysis. RESULTS: Compared with Puerto Rican children whose mothers had neither asthma nor depressive symptoms, those whose mothers had asthma but no depressive symptoms had 3.2 times increased odds of asthma (95% confidence interval [CI] = 2.1-4.8) and those whose mothers had asthma and depressive symptoms had 6.5 times increased odds of asthma (95% CI = 3.3-13.0). Similar results were obtained for maternal depression and maternal asthma in the Swedish cohort (odds ratio for maternal asthma without maternal depression = 2.8, 95% CI = 2.1-3.7; odds ratio for maternal asthma and maternal depression = 4.0, 95% CI = 1.7-9.6). Although the estimated effect of maternal asthma on childhood asthma was increased when maternal depressive symptoms (Puerto Rico) or maternal depression (Sweden) was present, there were no statistically significant additive interactions. CONCLUSION: Maternal depression can further increase the risk of asthma in children whose mothers have a history of asthma.

Sentinel node location in trunk and extremity melanomas: uncommon or multiple lymph drainage does not affect survival.

BACKGROUND: Patients with cutaneous melanoma (CM) on the trunk have a worse prognosis than those with extremity CM. One reason could be multiple or uncommon (outside axilla or groin) sentinel node locations (SNLs). METHODS: We identified 859 patients who underwent sentinel node biopsy for trunk (n = 465) or extremity (n = 394) CM in three Swedish healthcare regions from 2000 to 2008. We collected patient, tumor, and sentinel node characteristics through clinical registers and medical records. We investigated the distribution of SNLs in a logistic regression model, and risk of overall and melanoma-specific death through 2011 in a multivariable Cox regression model. RESULTS: Trunk CM was associated with multiple SNLs (31 vs. 7 %; odds ratio [OR] 7.1; 95 % confidence interval [CI] 4.6-11.5; p < 0.001) but not uncommon SNLs (8 vs. 7 %; OR 1.1; 95 % CI 0.6-1.9; p = 0.75) compared with extremity CM. The increased risk of melanoma-specific death was confirmed for trunk CM (hazard ratio [HR] 1.9; 95 % CI 1.3-2.9; p = 0.003), especially on the upper back (HR 2.3; 95 % CI 1.4-3.6; p < 0.001) compared with extremity CM. Uncommon SNLs (HR 0.5; 95 % CI 0.2-1.4; p = 0.21) or multiple SNLs (HR 1.1; 95 % CI 0.4-2.9; p = 0.81) were not associated with melanoma-specific death compared with those with common/single SNL. CONCLUSIONS: Trunk melanomas were associated with multiple lymph drainage, but the worse prognosis of trunk melanomas could not be explained by the increased frequency of multiple or uncommon SNLs.

Aspirin intake and breast cancer survival - a nation-wide study using prospectively recorded data in Sweden.

BACKGROUND: Aspirin (ASA) use has been associated with improved breast cancer survival in several prospective studies. METHODS: We conducted a nested case-control study of ASA use after a breast cancer diagnosis among women using Swedish National Registries. We assessed prospectively recorded ASA exposure during several different time windows following cancer diagnosis using conditional logistic regression with breast cancer death as the main outcome. Within each six-month period of follow-up, we categorized dispensed ASA doses into three groups: 0, less than 1, and 1 or more daily doses. RESULTS: We included 27,426 women diagnosed with breast cancer between 2005 and 2009; 1,661 died of breast cancer when followed until Dec 31, 2010. There was no association between ASA use and breast cancer death when exposure was assessed either shortly after diagnosis, or 3-12 months before the end of follow-up. Only during the period 0-6 months before the end of follow-up was ASA use at least daily compared with non-use associated with a decreased risk of breast cancer death: HR (95% CI) =0.69 (0.56-0.86). However, in the same time-frame, those using ASA less than daily had an increased risk of breast cancer death: HR (95% CI) =1.43 (1.09-1.87). CONCLUSIONS: Contrary to other studies, we did not find that ASA use was associated with a lower risk of death from breast cancer, except when assessed short term with no delay to death/end of follow-up, which may reflect discontinuation of ASA during terminal illness.

Household air pollution and pneumococcal density related to nasopharyngeal inflammation in mothers and children in Ethiopia: A cross-sectional study.

BACKGROUND: Three billion people in low- and middle-income countries are exposed to household air pollution as they use biomass fuel for cooking. We investigated the associations between solid fuel use and nasopharyngeal (NP) inflammation, as well as the associations between high pneumococcal density and NP inflammation, in mothers and children in rural and urban Ethiopia. MATERIALS AND METHODS: Sixty pairs of mothers (median age, 30 years; range, 19-45 years) with a child (median age, 9 months; range, 1-24 months) were included from rural Butajira (n = 30) and urban Addis Ababa (n = 30) in Ethiopia. The cohort was randomly selected from a previous study of 545 mother/child pairs included 2016. Questionnaire-based data were collected which included fuel type used (solid: wood, charcoal, dung or crop waste; cleaner: electricity, liquefied petroleum gas). Nasopharyngeal (NP) samples were collected from all mothers and children and analyzed for the levels of 18 cytokines using a Luminex immunoassay. Pneumococcal DNA densities were measured by a real-time multiplex PCR and a high pneumococcal density was defined as a cyclic threshold (Ct) value ≤ 30. RESULTS: Mothers from rural areas had higher median CXCL8 levels in NP secretions than those from urban areas (8000 versus 1900 pg/mL; p < 0.01), while rural children had slightly higher IL-10 levels than those from the urban area (26 vs 13 pg/mL; p = 0.04). No associations between fuel type and cytokine levels were found. However, a high pneumococcal density was associated with higher levels of cytokines in both mothers (CCL4, CXCL8, IL-1ß, IL-6 and VEGF-A) and children (CCL4, CXCL8, IL-1ß, IL-6 and IL-18). CONCLUSIONS: No significant associations were found between solid fuel use and NP inflammation in Ethiopian mothers and children, but the inflammatory activity was higher in individuals living in the rural compared to the urban area. In addition, high cytokine levels were associated with high pneumococcal density in both mothers and children, indicating a significant impact of NP pathogens on inflammatory mediator levels in upper airways.

Effectiveness and Cost-effectiveness of Artificial Intelligence-assisted Pathology for Prostate Cancer Diagnosis in Sweden: A Microsimulation Study.

BACKGROUND AND OBJECTIVE: Image-based artificial intelligence (AI) methods have shown high accuracy in prostate cancer (PCa) detection. Their impact on patient outcomes and cost effectiveness in comparison to human pathologists remains unknown. Our aim was to evaluate the effectiveness and cost-effectiveness of AI-assisted pathology for PCa diagnosis in Sweden. METHODS: We modeled quadrennial prostate-specific antigen (PSA) screening for men between the ages of 50 and 74 yr over a lifetime horizon using a health care perspective. Men with PSA ≥3 ng/ml were referred for standard biopsy (SBx), for which cores were either examined via AI followed by a pathologist for AI-labeled positive cores, or a pathologist alone. The AI performance characteristics were estimated using an internal STHLM3 validation data set. Outcome measures included the number of tests, PCa incidence and mortality, overdiagnosis, quality-adjusted life years (QALYs), and the potential reduction in pathologist-evaluated biopsy cores if AI were used. Cost-effectiveness was assessed using the incremental cost-effectiveness ratio. KEY FINDINGS AND LIMITATIONS: In comparison to a pathologist alone, the AI-assisted workflow increased the number of PSA tests, SBx procedures, and PCa deaths by ≤0.03%, and slightly reduced PCa incidence and overdiagnosis. AI would reduce the proportion of biopsy cores evaluated by a pathologist by 80%. At a cost of €10 per case, the AI-assisted workflow would cost less and result in <0.001% lower QALYs in comparison to a pathologist alone. The results were sensitive to the AI cost. CONCLUSIONS AND CLINICAL IMPLICATIONS: According to our model, AI-assisted pathology would significantly decrease the workload of pathologists, would not affect patient quality of life, and would yield cost savings in Sweden when compared to a human pathologist alone. PATIENT SUMMARY: We compared outcomes for prostate cancer patients and relevant costs for two methods of assessing prostate biopsies in Sweden: (1) artificial intelligence (AI) technology and review of positive biopsies by a human pathologist; and (2) a human pathologist alone for all biopsies. We found that addition of AI would reduce the pathology workload and save money, and would not affect patient outcomes when compared to a human pathologist alone. The results suggest that adding AI to prostate pathology in Sweden would save costs.

SAUNA QB - Array: The realization of a new concept in radioxenon detection.

We introduce a new concept in radioxenon detection - the radioxenon Array, defined as a system where air sampling and activity measurement is performed at multiple locations, using measurement units that are less sensitive, but on the other hand less costly, and easier to install and operate, compared to current state-of-the-art radioxenon systems. The inter-unit distance in the Array is typically hundreds of kilometres. Using synthetic nuclear explosions together with a parametrized measurement system model, we argue that, when such measurement units are combined into an Array, the aggregated verification performance (detection, location, and characterization) can be high. The concept has been realized by developing a measurement unit named SAUNA QB, and the world's first radioxenon Array is now operating in Sweden. The operational principles and performance of the SAUNA QB and the Array is described, and examples of first measured data are presented, indicating a measurement performance according to expectations.

Beyond collective intelligence: Collective adaptation.

We develop a conceptual framework for studying collective adaptation in complex socio-cognitive systems, driven by dynamic interactions of social integration strategies, social environments and problem structures. Going beyond searching for 'intelligent' collectives, we integrate research from different disciplines and outline modelling approaches that can be used to begin answering questions such as why collectives sometimes fail to reach seemingly obvious solutions, how they change their strategies and network structures in response to different problems and how we can anticipate and perhaps change future harmful societal trajectories. We discuss the importance of considering path dependence, lack of optimization and collective myopia to understand the sometimes counterintuitive outcomes of collective adaptation. We call for a transdisciplinary, quantitative and societally useful social science that can help us to understand our rapidly changing and ever more complex societies, avoid collective disasters and reach the full potential of our ability to organize in adaptive collectives.

Social sampling explains apparent biases in judgments of social environments.

How people assess their social environments plays a central role in how they evaluate their life circumstances. Using a large probabilistic national sample, we investigated how accurately people estimate characteristics of the general population. For most characteristics, people seemed to underestimate the quality of others' lives and showed apparent self-enhancement, but for some characteristics, they seemed to overestimate the quality of others' lives and showed apparent self-depreciation. In addition, people who were worse off appeared to enhance their social position more than those who were better off. We demonstrated that these effects can be explained by a simple social-sampling model. According to the model, people infer how others are doing by sampling from their own immediate social environments. Interplay of these sampling processes and the specific structure of social environments leads to the apparent biases. The model predicts the empirical results better than alternative accounts and highlights the importance of considering environmental structure when studying human cognition.

Type of learning task impacts performance and strategy selection in decision making.

In order to be adaptive, cognition requires knowledge about the statistical structure of the environment. We show that decision performance and the selection between cue-based and exemplar-based inference mechanisms can depend critically on how this knowledge is acquired. Two types of learning tasks are distinguished: learning by comparison, by which the decision maker learns which of two objects has a higher criterion value, and direct criterion learning, by which the decision maker learns an object's criterion value directly. In three experiments, participants were trained either with learning by comparison or with direct criterion learning and subsequently tested with paired-comparison, classification, and estimation tasks. Experiments 1 and 2 showed that although providing less information, learning by comparison led to better generalization (at test), both when generalizing to new objects and when the task format at test differed from the task format during training. Moreover, learning by comparison enabled participants to provide rather accurate continuous estimates. Computational modeling suggests that the advantage of learning by comparison is due to differences in strategy selection: whereas direct criterion learning fosters the reliance on exemplar processing, learning by comparison fosters cue-based mechanisms. The pattern in decision performance reversed when the task environment was changed from a linear (Experiments 1 and 2) to a nonlinear structure (Experiment 3), where direct criterion learning led to better decisions. Our results demonstrate the critical impact of learning conditions for the subsequent selection of decision strategies and highlight the key role of comparison processes in cognition.