Illuminating novel predictors of psychosis: Investigations of environmental and bioelectromagnetic predictors of psychosis symptoms in healthy adults
Notice bibliographique
Résumé
Schizophrenia is a debilitating disorder, which often results in irreversible tissue loss in the \nbrain, making it a difficult disorder to treat. The defining feature of schizophrenia is psychosis, \nwhich also occurs in schizoaffective disorder, substance use disorders, bipolar disorder, delusional \ndisorder, and dementia. We are slowly getting a better understanding of schizophrenia as novel \nbiomarkers are discovered and we learn what influences its prevalence rates. For example, many \nstudies have shown that schizophrenia is positively correlated with latitude. This knowledge \ncompliments our understanding of the importance of inflammation and vitamin D deficiency as \nrisks for schizophrenia. The purpose of the current thesis was three-fold: first, to determine \nseasonal variability of background photons as a novel environmental variable to use as a psychosis \npredictor. Second, to determine if the relationship with latitude was present with psychosis \nsymptoms in healthy adults. And third, to investigate a novel biomarker, biophotons, as a predictor \nof psychosis/schizotypy symptoms in healthy adults. There were three different studies completed \nto investigate these questions. The first measured background photon over the course of a year to \nunderstand seasonal variations and correlations with other geophysical variables. In the second \nstudy, online psychological questionnaires were administered to a global sample. The results \nsuggested the symptoms of psychosis were negatively correlated with latitude, opposite of the \nprevious findings with schizophrenia. Negative correlations were present in spirituality and \nhypomanic scores, but not depression or anxiety. Additionally, regression analysis revealed that in \nfemales but not males, components of the Earth’s electromagnetic field were better at predicting \npsychosis symptoms. In the third study, biophoton emissions from the hands (BPEs), quantitative \nelectroencephalographic (QEEG), electrocardiographic (ECG), and psychological questionnaires \nwere measured from participants in Sudbury, ON, Canada. The psychological questionnaires used were the Millon Clinical Multiaxial Inventory (MCMI-IV) and the Temperament Character \nInventory (TCI-R). The results suggested that biophotons showed some specificity, with overall \nBPEs from the hands predictive of affective scales in females, and the absolute difference between \nhands predictive of Schizotypal, Paranoid, and Schizophrenic Spectrum scores in females. \nSurprisingly, there were very few significant correlations in males. We also found that BPE and \nQEEG variables combined were able to predict scores on a Depression/Somatic Symptom factor. \nThese results demonstrate that biophotons could be a potential biomarker for mental health \ndisturbances. Taken together, these results demonstrate the importance of investigating the \nenvironmental electromagnetic and bioelectromagnetic variables to predict and understand \npsychosis.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».