Efficacy of Hypnosis on Dental Anxiety and Phobia: A Systematic Review and Meta-Analysis

Hypnosis is a commonly used therapy option in dentistry and medicine for fear and pain reduction. Nevertheless, it is viewed very critically, as there is still insufficient evidence for a treatment effect. Specific phobia of dental treatment and dental anxiety are prevalent conditions that can cause an oral health impairment. This paper critically reviews 19 clinical trials aimed at reducing dental anxiety and fear avoidance in adults, published in peer-reviewed journals between 1979 and 2021. The search identified 257 papers; 223 were selected after removing duplicates. A total of 188 articles were excluded after title and abstract evaluation; 35 full text articles were assessed for eligibility. Another 10 papers were discharged after full text evaluation, as these were case reports and questionnaires. Six papers were discharged due to the lack of a comparable scale to measure dental anxiety. The following treatment techniques were reviewed: various forms of cognitive-behavioral therapy (CBT), relaxation training, benzodiazepine premedication, self-hypnosis by audio therapy, hypnotherapy, hypnosis, and nitrous oxide sedation. CBT delivered in a variety of formats, including one-session treatment, showed the most evidence for the efficacy of reducing anxiety. A wide heterogeneity of methods allowed only the inclusion of five studies to the performed meta-analysis, showing contrasting results for the application of hypnosis. The main reason for this issue is the great variety in methods used, making a distinct assessment of hypnotic interventions difficult. However, the results of the systematic review are promising in that hypnosis can also be regarded as powerful and successful method for anxiety reduction, while there are also studies with a small or even slightly negative effect. Therefore, further research is needed. Within the limitations of the current study, a more consistent use of methods to examine anxiety for hypnosis research is recommended

A double-blind randomized clinical trial on the suggestive effect of anxiety management questionnaires in dental emergencies.

OBJECTIVE Dental anxiety is widespread among both children and adults. To diagnose dental anxiety, standardized anxiety questionnaires are recommended. Based on the suggestive nature of the questionnaires, the study aimed to find out whether asking respondents about personal coping strategies before dental treatment influences their anxiety. METHODS This prospective, double-blind, randomized controlled clinical trial included a total of 158 patients of a university dental clinic on emergency service. The intervention group (n = 82) received the Coping with Anxiety Questionnaire (CAQ) and the control group (n = 76) the Hierarchical Anxiety Questionnaire (HAF). State anxiety scores were assessed by using the State-Trait Anxiety Inventory (STAI) before and after the completion of each questionnaire. RESULTS Anxiety decreased in the intervention group (CAQ) (p < 0.001) and increased in the control group (HAF) (p < 0.001). CONCLUSION Within the limitations of the current study, a diagnostic tool of a standardized questionnaire for the assessment to assess personal coping strategies decreased state anxiety in comparison to a questionnaire assessing anxiety. CLINICAL TRIAL REGISTRATION https://www.drks.de, German Trials Register (DRKS00032450)

Table_1_A double-blind randomized clinical trial on the suggestive effect of anxiety management questionnaires in dental emergencies.DOC

ObjectiveDental anxiety is widespread among both children and adults. To diagnose dental anxiety, standardized anxiety questionnaires are recommended. Based on the suggestive nature of the questionnaires, the study aimed to find out whether asking respondents about personal coping strategies before dental treatment influences their anxiety.MethodsThis prospective, double-blind, randomized controlled clinical trial included a total of 158 patients of a university dental clinic on emergency service. The intervention group (n = 82) received the Coping with Anxiety Questionnaire (CAQ) and the control group (n = 76) the Hierarchical Anxiety Questionnaire (HAF). State anxiety scores were assessed by using the State–Trait Anxiety Inventory (STAI) before and after the completion of each questionnaire.ResultsAnxiety decreased in the intervention group (CAQ) (p ConclusionWithin the limitations of the current study, a diagnostic tool of a standardized questionnaire for the assessment to assess personal coping strategies decreased state anxiety in comparison to a questionnaire assessing anxiety.Clinical trial registrationhttps://www.drks.de, German Trials Register (DRKS00032450).</p

The PLATO Mission

International audiencePLATO (PLAnetary Transits and Oscillations of stars) is ESA's M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to &lt;2 R_(Earth)) around bright stars (&lt;11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5 %, 10 %, 10 % for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO's target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile at the beginning of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases

The PLATO Mission

International audiencePLATO (PLAnetary Transits and Oscillations of stars) is ESA's M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to &lt;2 R_(Earth)) around bright stars (&lt;11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5 %, 10 %, 10 % for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO's target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile at the beginning of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases

A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns

In cancer, the primary tumour's organ of origin and histopathology are the strongest determinants of its clinical behaviour, but in 3% of cases a patient presents with a metastatic tumour and no obvious primary. Here,as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we train a deep learning classifier to predict cancer type based on patterns of somatic passenger mutations detected in whole genome sequencing (WGS) of 2606 tumours representing 24 common cancer types produced by the PCAWG Consortium. Our classifier achieves an accuracy of 91% on held-out tumor samples and 88% and 83% respectively on independent primary and metastatic samples, roughly double the accuracy of trained pathologists when presented with a metastatic tumour without knowledge of the primary. Surprisingly, adding information on driver mutations reduced accuracy. Our results have clinical applicability, underscore how patterns of somatic passenger mutations encode the state of the cell of origin, and can inform future strategies to detect the source of circulating tumour DNA