scholarly journals A Rapid Realist Review of Effective Mental Health Interventions for Individuals with Chronic Physical Health Conditions during the COVID-19 Pandemic Using a Systems-Level Mental Health Promotion Framework

2021 ◽  
Vol 18 (23) ◽  
pp. 12292
Author(s):  
Lorna Stabler ◽  
Maura MacPhee ◽  
Benjamin Collins ◽  
Simon Carroll ◽  
Karen Davison ◽  
...  
Keyword(s):  
Mental Health ◽  
Health Promotion ◽  
Physical Health ◽  
Contextual Factors ◽  
Realist Review ◽  
Mental Health Promotion ◽  
Health Interventions ◽  
Health Conditions ◽  
Mental Health Interventions ◽  
Rapid Realist Review

The 2020 global outbreak of COVID-19 exposed and heightened threats to mental health across societies. Research has indicated that individuals with chronic physical health conditions are at high risk for suffering from severe COVID-19 illness and from the adverse consequences of public health responses to COVID-19, such as social isolation. This paper reports on the findings of a rapid realist review conducted alongside a scoping review to explore contextual factors and underlying mechanisms or drivers associated with effective mental health interventions within and across macro–meso–micro systems levels for individuals with chronic physical health conditions. This rapid realist review extracted 14 qualified studies across 11 countries and identified four key mechanisms from COVID-19 literature—trust, social connectedness, accountability, and resilience. These mechanisms are discussed in relation to contextual factors and outcomes reported in the COVID literature. Realist reviews include iterative searches to refine their program theories and context–mechanism–outcome explanations. A purposive search of pre-COVID realist reviews on the study topic was undertaken, looking for evidence of the robustness of these mechanisms. There were differences in some of the pre-COVID mechanisms due to contextual factors. Importantly, an additional mechanism—power-sharing—was highlighted in the pre-COVID literature, but absent in the COVID literature. Pre-existing realist reviews were used to identify potential substantive theories and models associated with key mechanisms. Based on the overall findings, implications are provided for mental health promotion policy, practice, and research.

The predictive relationship between sensory reactivity and depressive symptoms in young autistic children with few to no words

2021 ◽  
Author(s):  
Timothy Rossow ◽  
Keren MacLennan
Keyword(s):  
Mental Health ◽  
Depressive Symptoms ◽  
Health Interventions ◽  
Language Delay ◽  
Health Conditions ◽  
Autistic Children ◽  
Sensory Reactivity ◽  
Mental Health Interventions ◽  
Positive Correlations ◽  
Predictive Relationship

Depression, much like other mental health conditions, is common in autism, with autistic individuals much more likely to be diagnosed than their non-autistic peers. Sensory reactivity differences are also commonly experienced by autistic individuals and have been associated with depressive symptoms. However, there is little understanding of the predictive relationship between sensory reactivity and depressive symptoms, or the nature of this relationship in autistic children who speak few to no words. This study set out to explore the longitudinal relationship between sensory reactivity and depressive symptoms in 33 young autistic children who speak few to no words over two timepoints. We found positive correlations between depressive symptoms and hyper-reactivity and sensory seeking at both timepoints. We further found a bidirectional predictive relationship between depressive symptoms and sensory seeking. These results implicate sensory seeking in the development of depressive symptoms in young autistic children who use few to no words. Our findings have important implications for preventative mental health interventions, especially for those with a developmental language delay.Key words: autism; sensory reactivity; depression; children; language delay

scholarly journals Biofeedback-Based Connected Mental Health Interventions for Anxiety: Systematic Literature Review

10.2196/26038 ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. e26038
Author(s):  
Mahra Alneyadi ◽  
Nidal Drissi ◽  
Mariam Almeqbaali ◽  
Sofia Ouhbi
Keyword(s):  
Mental Health ◽  
Literature Review ◽  
Physical Health ◽  
Systematic Literature Review ◽  
Health Interventions ◽  
Psychological State ◽  
Physiological Data ◽  
Health Issues ◽  
Mental Health Interventions ◽  
Final Selection

Background Connected mental health, which refers to the use of technology for mental health care and technology-based therapeutic solutions, has become an established field of research. Biofeedback is one of the approaches used in connected mental health solutions, which is mainly based on the analysis of physiological indicators for the assessment and management of the psychological state. Biofeedback is recommended by many therapists and has been used for conditions including depression, insomnia, and anxiety. Anxiety is associated with several physiological symptoms, including muscle tension and breathing issues, which makes the inclusion of biofeedback useful for anxiety detection and management. Objective The aim of this study was to identify interventions using biofeedback as a part of their process for anxiety management and investigate their perceived effectiveness. Methods A systematic literature review of publications presenting empirically evaluated biofeedback-based interventions for anxiety was conducted. The systematic literature review was based on publications retrieved from IEEE Digital Library, PubMed, ScienceDirect, and Scopus. A preliminary selection of papers was identified, examined, and filtered to include only relevant publications. Studies in the final selection were classified and analyzed to extract the modalities of use of biofeedback in the identified interventions, the types of physiological data that were collected and analyzed and the sensors used to collect them. Processes and outcomes of the empirical evaluations were also extracted. Results After final selection, 13 publications presenting different interventions were investigated. The interventions addressed either primarily anxiety disorders or anxiety associated with health issues such as migraine, Parkinson disease, and rheumatology. Solutions combined biofeedback with other techniques including virtual reality, music therapy, games, and relaxation practices and used different sensors including cardiovascular belts, wrist sensors, or stretch sensors to collect physiological data such as heart rate, respiration indicators, and movement information. The interventions targeted different cohorts including children, students, and patients. Overall, outcomes from the empirical evaluations yielded positive results and emphasized the effectiveness of connected mental health solutions using biofeedback for anxiety; however, certain unfavorable outcomes, such as interventions not having an effect on anxiety and patients’ preferring traditional therapy, were reported in studies addressing patients with specific physical health issues. Conclusions The use of biofeedback in connected mental health interventions for the treatment and management of anxiety allows better screening and understanding of both psychological and physiological patient information, as well as of the association between the two. The inclusion of biofeedback could improve the outcome of interventions and boost their effectiveness; however, when used with patients suffering from certain physical health issues, suitability investigations are needed.

scholarly journals Biofeedback-Based Connected Mental Health Interventions for Anxiety: Systematic Literature Review (Preprint)

2020 ◽  
Author(s):  
Mahra Alneyadi ◽  
Nidal Drissi ◽  
Mariam Almeqbaali ◽  
Sofia Ouhbi
Keyword(s):  
Mental Health ◽  
Literature Review ◽  
Physical Health ◽  
Systematic Literature Review ◽  
Health Interventions ◽  
Psychological State ◽  
Physiological Data ◽  
Health Issues ◽  
Mental Health Interventions ◽  
Final Selection

BACKGROUND Connected mental health, which refers to the use of technology for mental health care and technology-based therapeutic solutions, has become an established field of research. Biofeedback is one of the approaches used in connected mental health solutions, which is mainly based on the analysis of physiological indicators for the assessment and management of the psychological state. Biofeedback is recommended by many therapists and has been used for conditions including depression, insomnia, and anxiety. Anxiety is associated with several physiological symptoms, including muscle tension and breathing issues, which makes the inclusion of biofeedback useful for anxiety detection and management. OBJECTIVE The aim of this study was to identify interventions using biofeedback as a part of their process for anxiety management and investigate their perceived effectiveness. METHODS A systematic literature review of publications presenting empirically evaluated biofeedback-based interventions for anxiety was conducted. The systematic literature review was based on publications retrieved from IEEE Digital Library, PubMed, ScienceDirect, and Scopus. A preliminary selection of papers was identified, examined, and filtered to include only relevant publications. Studies in the final selection were classified and analyzed to extract the modalities of use of biofeedback in the identified interventions, the types of physiological data that were collected and analyzed and the sensors used to collect them. Processes and outcomes of the empirical evaluations were also extracted. RESULTS After final selection, 13 publications presenting different interventions were investigated. The interventions addressed either primarily anxiety disorders or anxiety associated with health issues such as migraine, Parkinson disease, and rheumatology. Solutions combined biofeedback with other techniques including virtual reality, music therapy, games, and relaxation practices and used different sensors including cardiovascular belts, wrist sensors, or stretch sensors to collect physiological data such as heart rate, respiration indicators, and movement information. The interventions targeted different cohorts including children, students, and patients. Overall, outcomes from the empirical evaluations yielded positive results and emphasized the effectiveness of connected mental health solutions using biofeedback for anxiety; however, certain unfavorable outcomes, such as interventions not having an effect on anxiety and patients’ preferring traditional therapy, were reported in studies addressing patients with specific physical health issues. CONCLUSIONS The use of biofeedback in connected mental health interventions for the treatment and management of anxiety allows better screening and understanding of both psychological and physiological patient information, as well as of the association between the two. The inclusion of biofeedback could improve the outcome of interventions and boost their effectiveness; however, when used with patients suffering from certain physical health issues, suitability investigations are needed.

Sign in / Sign up

Export Citation Format

Share Document