The Integration of Olanzapine and Cognitive Behavioural Therapy for the Treatment of Schizophrenia: A Literature Review
Bibliographic record
Abstract
Introduction: Schizophrenia is a serious psychiatric disorder that significantly impacts a person’s quality of life. This condition is characterized by three groups of symptoms: positive, negative and cognitive. There have been developments of new therapeutic methods for treating schizophrenia, both pharmacological and psychotherapeutic. Antipsychotic drugs such as the second generation antipsychotic olanzapine are often the first course of treatment, for the purpose of controlling symptoms. However, research has determined that using antipsychotics alone may limit its long-term effectiveness and produce adverse effects. Psychosocial interventions like cognitive behavioural therapy (CBT) aim to reduce psychotic symptoms and prevent relapse when used in conjunction with medication. This review aims to discuss the effectiveness of the integration of olanzapine and CBT, and how these treatments improve symptom reduction, reduce relapse and reduce the occurrence of adverse effects. Methods: A literature search between the years of 2010 to 2020 was conducted using PubMed and PsycInfo. Keywords included variations of “schizophrenia”, “treatment”, “olanzapine”, and “cognitive behavioural therapy”. Results: Olanzapine by itself was found to improve symptom reduction, yet showed adverse effects such as weight gain and extrapyramidal symptoms. CBT used as a lone treatment of schizophrenia showed less adverse effects than antipsychotics, yet was significantly less effective than both antipsychotics alone and the combinatorial treatment of CBT and olanzapine. The integration of olanzapine and CBT demonstrated an overall improvement in a schizophrenic patient’s health. Discussion: The integration of olanzapine and CBT show promise for symptom reduction, relapse prevention, reduced occurrence of adverse side effects, and the overall improvement of one’s health. Conclusion: Individuals diagnosed with schizophrenia experience emotional, physical and social hardships, thus it is imperative that physicians are aware of current treatments that can be tailored to best treat their patients.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".