An evaluation of a brief guided mindfulness workshop with older adults: A qualitative study

Redden, Jenna M.; Korol, Susan; Vassallo, Todd

doi:10.1016/j.mhp.2021.200215

Cited by 2 publications

(1 citation statement)

References 31 publications

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“…The results of this study are supported by other findings that there was an increased risk of psychological problems among young adults during the COVID-19 pandemic 10,33 . Compounding the problem was the decrease in mental health services during after the onset of the pandemic 34 . Although online mental health consultation was available at our university, these services required students to navigate where to find help, use computer skills to access telehealth, and establish reliable Internet connectivity.…”

Section: Discussionsupporting

confidence: 78%

Quality of Life, Resilience, and Related Factors of Nursing Students During the COVID-19 Pandemic

et al. 2021

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Background: COVID-19 and the associated measures to mitigate the spread of the virus have significantly disrupted nursing education.Purpose: The purpose of this study was to examine the relationship between quality of life (QoL), resilience, and associated factors among nursing students during the unprecedented COVID-19 pandemic and subsequent social distancing requirements. Methods: A cross-sectional study using an anonymous survey with nursing students (n = 152) was conducted at a public university in rural Appalachia in April 2020. Instruments included World Health Organization Quality of Life-BREF, Connor Davidson Resilience Scale, demographics and school-related questionnaires, and an open-ended question. Data were analyzed using descriptive, bivariate, and multiple linear regression analyses. Results: Resilience, having online experience, and being well prepared for online learning were associated with each QoL domain. Remarkably, 21% to 54% of nursing student QoL scores indicated poor QoL. Conclusions: Cultivating resilience among nursing students may improve QoL, help with academic success, and prepare students to sustain the demands associated with the nursing profession.

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Section: Discussionsupporting

confidence: 78%

Quality of Life, Resilience, and Related Factors of Nursing Students During the COVID-19 Pandemic

et al. 2021

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Scalable precision psychiatry with an objective measure of psychological stress: Prospective real world study (Preprint)

Wang,

Farb,

Saab

2024

Preprint

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BACKGROUND Precision psychiatry is data-driven personalisation of mental healthcare. One major aim is to identify the specific forms of therapy that will be most clinically meaningful for each patient. Before major progress towards this aim is possible however, tools that objectively assess the mental wellbeing of a patient must be validated in this context. OBJECTIVE To compare the fidelity of a therapy recommendation algorithm when trained with an objective quantification of psychological stress versus subjective ecological momentary assessments of stress and mood. METHODS From 2,786 unique individuals engaging between March 2015 and December 2022 in English language psychotherapy sessions and providing pre- and post-session self-report and facial biometric data via the AmDTx mental health platform (Mobio Interactive Pte Ltd, Singapore), analysis was conducted on 67 “super users” that completed at least 28 sessions with all pre- and post-session measures. AmDTx is a clinically validated mental health platform that provides patients with audio recordings supporting mental wellbeing (asynchronous and on-demand psychotherapy). AmDTx also contains easy to use tools that rapidly assess mental wellbeing, including an objective measure of psychological stress derived from AI analysis of facial biomarkers (Objective Stress Level; ∆OSL), and ecological momentary assessments (EMAs). Two commonly used EMAs within AmDTx are self-reported stress (∆SRS) and self-reported mood (∆SRM). These three data sources were used to independently train an algorithm designed to predict what future therapy sessions would prove most efficacious for each individual. Algorithm predictions were compared against the efficacy of the individual’s self-selected sessions. RESULTS EMAs demonstrated significant convergence with each other (r=0.53, P<.01), and divergence from the objective measure of psychological stress (r<0.03). The recommendation algorithm selected increasingly efficacious therapy sessions as a function of training data, when trained with the pre- and post-session ∆OSL (F(1, 16)=5.37, P=.034) or ∆SRM data (F(1, 16) = 3.69, P=.048). Using the first 15 therapy sessions, the algorithm trained using ∆OSL data predicted future sessions with a statistically higher efficacy relative to self-selected sessions (P<.01). Training the algorithm with self-reported data showed potential trends that did not reach significance (∆SRS: P=.092; ∆SRM: P=.12). Self-selections were over-represented amongst the algorithmically recommended sessions, an effect most pronounced for ∆OSL (F(1, 14)=30.94, P<.001). CONCLUSIONS A rapid, scalable, and objective measure of psychological stress, when combined with a robust recommendation algorithm, may improve clinical predictiveness within precision psychiatry and thereby support the capacity for healthcare professionals to meet global demand. CLINICALTRIAL clinicaltrials.gov

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An evaluation of a brief guided mindfulness workshop with older adults: A qualitative study

Cited by 2 publications

References 31 publications

Quality of Life, Resilience, and Related Factors of Nursing Students During the COVID-19 Pandemic

Quality of Life, Resilience, and Related Factors of Nursing Students During the COVID-19 Pandemic

Scalable precision psychiatry with an objective measure of psychological stress: Prospective real world study (Preprint)

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