Is normal science good science?

“Normal science” is a concept introduced by Thomas Kuhn in The Structure of Scientific Revolutions (1962). In Kuhn’s view, normal science means “puzzle solving”, solving problems within the paradigm—framework most successful in solving current major scientific problems—rather than producing major novelties. This paper examines Kuhnian and Popperian accounts of normal science and their criticisms to assess if normal science is good. The advantage of normal science according to Kuhn was “psychological”: subjective satisfaction from successful “puzzle solving”. Popper argues for an “intellectual” science, one that consistently refutes conjectures (hypotheses) and offers new ideas rather than focus on personal advantages. His account is criticized as too impersonal and idealistic. Feyerabend’s perspective seems more balanced; he argues for a community that would introduce new ideas, defend old ones, and enable scientists to develop in line with their subjective preferences. The paper concludes that normal science has no one clear-cut set of criteria encompassing its meaning and enabling clear assessment.“Normal science” is a concept introduced by Thomas Kuhn in The Structure of Scientific Revolutions (1962). In Kuhn’s view, normal science means “puzzle solving”, solving problems within the paradigm—framework most successful in solving current major scientific problems—rather than producing major novelties. This paper examines Kuhnian and Popperian accounts of normal science and their criticisms to assess if normal science is good. The advantage of normal science according to Kuhn was “psychological”: subjective satisfaction from successful “puzzle solving”. Popper argues for an “intellectual” science, one that consistently refutes conjectures (hypotheses) and offers new ideas rather than focus on personal advantages. His account is criticized as too impersonal and idealistic. Feyerabend’s perspective seems more balanced; he argues for a community that would introduce new ideas, defend old ones, and enable scientists to develop in line with their subjective preferences. The paper concludes that normal science has no one clear-cut set of criteria encompassing its meaning and enabling clear assessment

Is normal science good science?

“Normal science” is a concept introduced by Thomas Kuhn in The Structure of Scientific Revolutions (1962). In Kuhn’s view, normal science means “puzzle solving”, solving problems within the paradigm—framework most successful in solving current major scientific problems—rather than producing major novelties. This paper examines Kuhnian and Popperian accounts of normal science and their criticisms to assess if normal science is good. The advantage of normal science according to Kuhn was “psychological”: subjective satisfaction from successful “puzzle solving”. Popper argues for an “intellectual” science, one that consistently refutes conjectures (hypotheses) and offers new ideas rather than focus on personal advantages. His account is criticized as too impersonal and idealistic. Feyerabend’s perspective seems more balanced; he argues for a community that would introduce new ideas, defend old ones, and enable scientists to develop in line with their subjective preferences. The paper concludes that normal science has no one clear-cut set of criteria encompassing its meaning and enabling clear assessment

Cognitive performance at first episode of psychosis and the relationship with future treatment resistance: Evidence from an international prospective cohort study

Background Antipsychotic treatment resistance affects up to a third of individuals with schizophrenia, with recent research finding systematic biological differences between antipsychotic resistant and responsive patients. Our aim was to determine whether cognitive impairment at first episode significantly differs between future antipsychotic responders and resistant cases. Methods Analysis of data from seven international cohorts of first-episode psychosis (FEP) with cognitive data at baseline (N = 683) and follow-up data on antipsychotic treatment response: 605 treatment responsive and 78 treatment resistant cases. Cognitive measures were grouped into seven cognitive domains based on the pre-existing literature. We ran multiple imputation for missing data and used logistic regression to test for associations between cognitive performance at FEP and treatment resistant status at follow-up. Results On average patients who were future classified as treatment resistant reported poorer performance across most cognitive domains at baseline. Univariate logistic regressions showed that antipsychotic treatment resistance cases had significantly poorer IQ/general cognitive functioning at FEP (OR = 0.70, p = .003). These findings remained significant after adjusting for additional variables in multivariable analyses (OR = 0.76, p = .049). Conclusions Although replication in larger studies is required, it appears that deficits in IQ/general cognitive functioning at first episode are associated with future treatment resistance. Cognitive variables may be able to provide further insight into neurodevelopmental factors associated with treatment resistance or act as early predictors of treatment resistance, which could allow prompt identification of refractory illness and timely interventions

Ten simple rules for implementing open and reproducible research practices after attending a training course

Open, reproducible, and replicable research practices are a fundamental part of science. Training is often organized on a grassroots level, offered by early career researchers, for early career researchers. Buffet style courses that cover many topics can inspire participants to try new things; however, they can also be overwhelming. Participants who want to implement new practices may not know where to start once they return to their research team. We describe ten simple rules to guide participants of relevant training courses in implementing robust research practices in their own projects, once they return to their research group. This includes (1) prioritizing and planning which practices to implement, which involves obtaining support and convincing others involved in the research project of the added value of implementing new practices; (2) managing problems that arise during implementation; and (3) making reproducible research and open science practices an integral part of a future research career. We also outline strategies that course organizers can use to prepare participants for implementation and support them during this process

Schizophrenia polygenic risk predicts general cognitive deficit but not cognitive decline in healthy older adults

There has been a long argument over whether schizophrenia is a neurodegenerative disorder associated with progressive cognitive impairment. Given high heritability of schizophrenia, ascertaning if genetic susceptibility to schizophrenia is also associated with cognitive decline in healthy people would support the view that schizophrenia leads to an accelerated cognitive decline. Using the population representative sample of 6817 adults aged >50 years from the English Longitudinal Study of Ageing, we investigated associations between the biennial rate of decline in cognitive ability and the schizophrenia polygenic score (SZ-PGS) during the 10-year follow-up period. SZ-PGS was calculated based on summary statistics from the Schizophrenia Working Group of the Psychiatric Genomics Consortium. Cognition was measured sequentially across four time points using verbal memory and semantic fluency tests. The average baseline verbal memory was 10.4 (SD = 3.4) and semantic fluency was 20.7 (SD = 6.3). One standard deviation (1-SD) increase in SZ-PGS was associated with lower baseline semantic fluency (β = −0.25, 95%CI = −0.40 to −0.10, p = 0.002); this association was significant in men (β = −0.36, 95%CI = −0.59 to −0.12, p = 0.003) and in those who were aged 60–69 years old (β = −0.32, 95%CI = −0.58 to −0.05, p = 0.019). Similarly, 1-SD increase in SZ-PGS was associated with lower verbal memory score at baseline in men only (β = −0.12, 95%CI = −0.23 to −0.01, p = 0.040). However, SZ-PGS was not associated with a greater rate of decline in these cognitive domains during the 10-year follow-up. Our findings highlight that while genetic susceptibility to schizophrenia conveys developmental cognitive deficit, it is not associated with an ongoing cognitive decline, at least in later life. These results do not support the neo-Kraepelinian notion of schizophrenia as a genetically determined progressively deteriorating brain disease

Ten simple rules for implementing open and reproducible research practices after attending a training course

Training in robust research practices is becoming increasingly common. However, many course participants may encounter challenges in implementation of what they learned after returning to their research groups. In this piece, we summarize insights and "lessons learned" from a group of former course participants. We offer practical tips on implementation and cultural change that may be useful for researchers at any career stage. In addition, we provide a list of considerations for course instructors to help them support course attendees after training is over