Cognitive neurosciences: A new paradigm in management and outcome of schizophrenia
Bibliographic record
Abstract
Byline: Amresh. Shrivastava, Megan. Johnston Cognitive neuroscience of schizophrenia has truly emerged as a connection between neurobiological changes and psychological processes. The current state of research is reflective of the evidence that brain changes correlate with psychological dysfunctions and may have a causal relationship. Thus, a significant number of behavioral traits, functional limitations and psychological vulnerabilities can now be explained on the basis of underlying neurobiological deficits. Cognitive neurosciences have thus emerged as one of the 'missing-links' in understanding the phenomenology of schizophrenia. Schizophrenia is an illness with functional disability as a major issue.[sup] [1] Outcome in schizophrenia has always been a complex matter, as the concept of outcome changes not only with scientific developments but also with rising consumer expectations. In the past, measures of outcome have focused only on clinical symptoms, but today it is recognized that social outcomes are an equally important consideration. In order to best capture the quality of life of individuals affected by schizophrenia, it has become necessary to consider social, occupational, and cognitive variables while defining outcome. Re-appearance of cognitive functions in the scene of schizophrenia outcome is viewed as a turning point in the research progress. It has provided various arguments as well as mechanisms to look beyond the symptom clusters. Cognitive functions have become a visible link between dysfunction, disability, symptomatology and neurobiological changes. The issue amongst clinicians is whether it will become a measurable marker for clinical outcomes, whether therapeutic interventions can change cognition functions, and whether cognitive enhancers will become the central therapeutic focus in future. Some of these issues have the potential to change the focus from treatment to prevention in psychiatrists' practice. The implications are much broader for clinical practice and the most significant question is whether cognitive enhancers effective in schizophrenia will also be useful in treating the 'risk-syndromes'. This paper deals with some of the basic findings of cognitive research, in relation to outcome in schizophrenia and atypical antipsychotics. Outcome status for individuals with schizophrenia over a 100-year span, from 1895 to 1985, in a meta-analysis of published literature, shows good outcome limited to about 30% of individuals before the mid nineties and less than 37% of individuals in the late nineties. It seems clear that patients were, and are, continuing to suffer from dysfunction and disability.[sup] [2] Outcome in schizophrenia is multidimensional, and has typically been heterogeneous and variable across cultures and regions. Cognitive function has recently emerged as an independent domain of psychopathology in schizophrenia. Its re-emergence and new significance is obvious from the proposal that cognition needs to be a diagnostic criterion for schizophrenia in the forthcoming Diagnostic and Statistical Manual of Mental Disorders (DSM V). The cognitive functions are also significantly correlated with the level of functioning. It is expected that effective treatment in schizophrenia will significantly enhance cognitive function and thereby result in good level of functioning. Atypical antipsychotics are the mainstream treatment for schizophrenia, which reduce symptoms significantly, in three psychopathological domains: positive symptoms, negative symptoms and general psychopathology. There is an expectation that these molecules would also significantly enhance cognitive function. Considering the emerging findings in the literature, it is important to consider measures to enhance cognitive functions or at least prevent progressive cognitive impairment in schizophrenia. We have seen an increasing emphasis on the importance of cognition in understanding psychosis over the past 20 years. …
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.012 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.015 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".