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Enregistrement W4405003918 · doi:10.3389/fpsyg.2024.1525122

Editorial: Psychological sleep studies: new insights to support and integrate clinical practice within the healthcare system, volume II

2024· editorial· en· W4405003918 sur OpenAlexaboutno aff
Marco Sforza, Luigi Ferini‐Strambi, Christian Franceschini

Notice bibliographique

RevueFrontiers in Psychology · 2024
Typeeditorial
Langueen
DomainePsychology
ThématiqueSleep and related disorders
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMental healthPsychologyAnxietyQuality of life (healthcare)InsomniaIntervention (counseling)CognitionDepression (economics)PsychiatryCognitive behavioral therapy for insomniaClinical psychologySleep disorderSleep (system call)Obstructive sleep apneaMedicineCognitive behavioral therapyPsychotherapist

Résumé

récupéré en direct d'OpenAlex

Sleep health is essential for overall physical and mental well-being. Insufficient sleep, whether in terms of quantity or quality, significantly impacts an individual's quality of life and day-to-day functioning [1]. Consequences of sleep disorders like insomnia include impaired daytime cognition, reduced work productivity, an increased risk of accidents and injuries, and have been linked to psychiatric disorders, cardiovascular diseases, and other chronic health conditions. [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16].Sleep problems may compromise with the treatments that are currently being administered for a wide range of illnesses. When these disorders are addressed, they have the potential to enhance the patient's quality of life and adherence to therapy, as well as the intensity of the psychological symptoms that they are experiencing. It has been shown that there is a complicated association between sleep and mental health issues, such as anxiety, depression, and traumatic stress disorders. This interaction is considered to be bidirectional [2], [16], [17]. There is a growing demand in the clinical setting for psychologists who are skilled in evidence-based psychotherapy to become members of multidisciplinary health teams. These psychologists would be tasked with providing cognitive-behavioral intervention and support for patients suffering from insomnia [18], narcolepsy [19], [20], and adherence to treatment for obstructive sleep apnea [21].This volume brings together a collection of research that delves into different aspects of sleep health and its relationship with psychological well-being, offering new approaches to addressing these challenges in various populations. The findings provide critical implications for clinical practice, aiming to improve sleep health management across diverse healthcare settings.Luo et al. [22] investigate the mental health challenges, particularly anxiety and poor sleep, experienced by healthcare workers during the COVID-19 pandemic. Their study shows that Progressive Muscle Relaxation (PMR) significantly alleviates anxiety and improves sleep quality among practitioners in high-stress environments like mobile cabin hospitals. The intervention demonstrated a reduction in both anxiety and poor sleep indices, offering an accessible and effective solution to mitigate mental health strains during pandemicrelated crises.This study highlights the potential of PMR as a non-invasive, cost-effective intervention that could be readily implemented in healthcare systems to support the mental health of frontline workers. Given the global scale of the healthcare crisis, integrating such tools into standard healthcare practice could enhance workforce wellbeing and performance.In their study, O'Regan et al. [23] explore the patient journey in managing insomnia across Europe and Canada. By mapping the phases of insomnia management, from self-initiated behavioral changes to long-term reliance on prescription medications, the authors reveal a considerable gap in the alignment of healthcare provider strategies and patient needs. Their research uncovers key points where interventions can be improved, particularly in addressing patient expectations and enhancing education around sleep hygiene and nonpharmacological treatments.Overall, the findings show that patient education is crucial to remove the stigma surrounding insomnia, helping patients recognize that chronic insomnia is a primary disorder that requires appropriate medical management, and encouraging them to seek help earlier. Additionally, healthcare provider education and training on sleep disorders are essential to increase the perception of chronic insomnia as a serious primary medical condition and to fully understand its significant impact on patients' daily lives. Furthermore, the current situation, in which many patients must settle for "manageable" insomnia, highlights a serious unmet need regarding the management and treatment of this condition. More comprehensive approaches are needed to ensure that patients receive effective care that goes beyond symptom management, addressing the root causes of their insomnia and improving their long-term health outcomes.Wale et al. [24] shed light on the high prevalence of insomnia among university students in Ethiopia. Their study identifies key predictors, including gender, age, mild anxiety symptoms, and excessive use of mobile devices before bedtime, which significantly contribute to poor sleep quality among students. The findings underscore the impact of lifestyle factors and mental health challenges on sleep patterns in young adults, a group particularly vulnerable to sleep disturbances due to academic stress and lifestyle transitions.The study calls for targeted interventions focusing on mental health support and promoting better sleep hygiene among university students. Educational institutions should integrate sleep health education into their wellness programs, emphasizing the importance of mental health and limiting late-night screen exposure.Zambelli et al. evaluate the feasibility of delivering CBT-I through telehealth to chronic pain patients suffering from insomnia [25]. The study shows that adapted CBT-I delivered via telehealth not only improved sleep quality but also alleviated symptoms of anxiety, and depression. The research highlights the growing role of telehealth in making effective sleep interventions more accessible, particularly for populations with mobility issues or those living in remote areas.Telehealth-based interventions offer a scalable and practical solution to reach populations with limited access to in-person therapy. As healthcare systems continue to embrace digital health solutions, telehealth-based CBT-I can play a pivotal role in addressing sleep disorders, particularly in the post-pandemic era where telehealth has become more prominent.While the studies presented in this volume offer important insights, several areas remain unexplored, signaling opportunities for future research. First, the long-term effectiveness of non-pharmacological interventions like PMR and CBT-I across diverse populations, including adolescents and the elderly, needs further investigation. Additionally, the impact of behavioral and lifestyle factors, such as mobile device use before bedtime, which has been shown to significantly influence sleep quality, particularly among younger populations, requires deeper examination.As telehealth becomes an increasingly central component of healthcare delivery, there is also a need to assess its broader efficacy across varying cultural contexts, socioeconomic groups, and medical conditions.Understanding how digital interventions like telehealth-delivered CBT-I can be optimized to meet the needs of different populations will be crucial for the equitable expansion of these services.The collection of research in this volume underscores the profound interconnectedness of sleep health and psychological well-being. From frontline healthcare workers grappling with anxiety during pandemics to chronic pain patients benefiting from telehealth-delivered CBT-I, these studies highlight the necessity of integrating sleep health into broader mental healthcare strategies. Sleep disorders, particularly insomnia, are often underdiagnosed and undertreated, despite their substantial repercussions on both individual and societal health.Psychologists play a crucial role in addressing sleep-related disorders, not only through therapeutic interventions such as CBT-I but also by promoting sleep hygiene and mental wellness as foundational elements of health. Academic training programs in psychology should emphasize the importance of sleep as a pillar of mental well-being, equipping future practitioners with the skills to recognize, address, and treat sleep disturbances as part of a comprehensive mental health approach.To advance a holistic approach, healthcare systems must prioritize early detection and treatment of sleep disorders, leveraging cross-disciplinary methods that integrate mental health, technology, and lifestyle interventions. This volume provides a robust foundation for understanding the significance of sleep in clinical practice, yet ongoing research and innovation will be essential to refine and expand these approaches, fostering a truly integrative model of mental healthcare that includes sleep as a central component.

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)0,008
score de la tête « metaresearch » (Gemma)0,040
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 enseignants0,023
Score d'incertitude au seuil0,075

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0080,040
Méta-épidémiologie (sens strict)0,0060,002
Méta-épidémiologie (sens large)0,0060,004
Bibliométrie0,0050,002
Études des sciences et des technologies0,0040,005
Communication savante0,0110,007
Science ouverte0,0060,002
Intégrité de la recherche0,0230,026
Charge utile insuffisante (le modèle a refusé de juger)0,0220,015

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 Opus0,034
Tête enseignante GPT0,426
Écart entre enseignants0,392 · 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

Citations2
Publié2024
Routes d'admission1
Résumé présentoui

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