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Enregistrement W4404551905 · doi:10.3389/fpsyt.2024.1513000

Editorial: Tales from across the psychosis spectrum: understanding differences and similarities in mechanisms and experiences

2024· editorial· en· W4404551905 sur OpenAlexaff
Emma Palmer‐Cooper, Lyn Ellett, David Benrimoh

Notice bibliographique

RevueFrontiers in Psychiatry · 2024
Typeeditorial
Langueen
DomaineArts and Humanities
ThématiqueMental Health and Psychiatry
Établissements canadiensMcGill UniversityDouglas College
Organismes subventionnairesnon disponible
Mots-clésPsychologyFeelingPsychosisMental healthEthnic groupMental illnessClinical psychologySocial distanceHelp-seekingPsychiatryMedicineSocial psychologyCoronavirus disease 2019 (COVID-19)Disease

Résumé

récupéré en direct d'OpenAlex

In their study evaluating the prevalence of psychosis within a national sample in the United States. Sankoh et al. (2024) highlight the complex socio-cultural relationship between psychosis prevalence and ethnic or racial background. Individuals selfidentifying as Black and Hispanic were nearly twice as likely to experience psychosis as individuals from White ethnic backgrounds, but had lower rates of comorbid mental illness. Surprisingly, individuals from Black and Hispanic backgrounds had lower overall rates of mental illness. The authors suggest this paradoxical finding may be related to underreporting of other mental illness experiences in ethnically minoritised groups due to stigma, which may lead to delays or avoidance of seeking help. This could explain the greater likelihood of individuals from Black and Hispanic backgrounds experiencing serious mental health problems like psychosis before seeking help, compared to individuals from White backgrounds, who may seek help earlier or more often. This study is an important reminder that measuring phenomenology across the psychosis spectrum intersects with the social determinants of health in important ways.Focussing on the combined impact of perceptions and experiences of psychosis, O'Brien-Venus et al. ( 2023) investigated how people who hear distressing voices feel dehumanised. Dehumanisation was experienced on a continuum, with personal, social and environmental factors influencing the degree to which individuals felt the loss or reclamation of feeling human. Factors influencing the degree to which individuals felt human included sense of self-worth, agency, belonging, trust in the self, and subjective experience of hearing voices as distressing or harmless. Additionally, feelings of dehumanisation (rather than subjective experience of hearing voices) were more strongly identified as occurring at the 'end of the continua' by participants. Participants reported a 'push and pull' of these influences moving them up or down the spectrum in response to internal experiences such as the content of voices they heard, and interpersonal responses to these (for example, social rejection and stigma versus acceptance). Hansson et al. (2023) highlighted the critical role of connection and family involvement in psychosis treatment. Interviews highlighted that people with psychosis found systematic family involvement in treatment led to increased knowledge about psychosis through psychoeducation for both individuals with psychosis and family members. This was accompanied by improved understanding of one another's perspectives and experiences, which led to better interpersonal interactions. This in turn led to better perceived support for the person with psychosis and for the family members supporting them. Having a dedicated space, with structure and boundaries within which to explore information, along with thoughts and feelings of individuals with psychosis and their families were noted as a positive. However, patient hesitancy toward family involvement and a lack of tailored approaches were noted as areas for improvement, along with earlier referral to this intervention. Echoing Hansson et al.'s findings, in previous work, we have argued that specialty care teams in psychosis may operate in part by helping patients better understand and make us of information in the world around them-including improving communication with family (Benrimoh et al., 2021).Finally, Amir et al. (2023) investigated the complex interaction between biopsychosocial factors and psychosis, comparing clinical high-risk (CHR-P) individuals to those with genetic risk (22q11.2 deletion syndrome). Results demonstrated that CHR-P individuals experienced increased positive psychosis symptoms, dysphoric mood, social functioning, social anhedonia, and a higher IQ than individuals at increased genetic risk. Findings also highlighted that genetic versus clinical risk had a di`erential impact on substance misuse. CHR-P participants were more likely to use tobacco, alcohol, and cannabis compared to controls. Conversely, individuals at increased genetic risk were less likely to use these substances than controls, which was linked to neurobehavioral factors associated with to 22q11.2 deletion (including lower global social functioning and increased incidence of autism spectrum disorders). This study emphasises that the profiles of those at risk for psychosis can di`er greatly, suggesting that the spectrum is not a singular left-right trajectory, but rather a manifold of trajectories and potential subgroups which have yet to be elucidated.Overall, the articles in this special issue highlight complexities that need to be addressed in the field of psychosis research, and especially early and prodromal psychosis. They highlight the importance of understanding how biopsychosocial influences interact in the onset, help-seeking, diagnosis, and treatment of psychosis.These factors need to be carefully considered when designing research protocols and sampling strategies as they may deeply impact the representativeness of the samples collected and, unaddressed, may lead to biased or inaccurate conclusions. More research is needed to understand how social and biological influences interact, how this interaction changes along the continuum, and where on the continuum intervention is likely to be most impactful. Ultimately, larger, more densely temporally sampled studies of psychosis development, sampling from across the continuum and employing a combination of traditional (e.g. questionnaire, imaging, interview) as well as novel computational measures aimed at parsing underlying di`erences in information processing (Powers et al.) between potential subgroups on the continuum, may be necessary to fully capture the complexity of the psychosis continuum (see Benrimoh et al. (2024)for discussion).

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,024
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,016
Score d'incertitude au seuil0,053

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0050,024
Méta-épidémiologie (sens strict)0,0050,001
Méta-épidémiologie (sens large)0,0040,003
Bibliométrie0,0030,002
Études des sciences et des technologies0,0030,003
Communication savante0,0060,006
Science ouverte0,0050,002
Intégrité de la recherche0,0160,020
Charge utile insuffisante (le modèle a refusé de juger)0,0160,010

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.

Tête enseignante Opus0,020
Tête enseignante GPT0,273
Écart entre enseignants0,253 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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