Effects of personalized music intervention on nurse burnout: A feasibility randomized controlled trial

Matthew, Josephine; Mike, Lerinda; Huang, Hui‐Chuan; Wang, Chia‐Hui; Shih, Chun-Ying; Chen, Yi‐Chen; Chiu, Hsiao‐Yean

doi:10.1111/nhs.12984

Cited by 6 publications

(7 citation statements)

References 43 publications

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“…Mindful Self Compassion training has been found to be helpful (Kotera and Gordon, 2021). Opportinities to connect with others in ways that bring joy and energy may help (Matthew et al,2022). However burnout is a consequence of working conditions.…”

Section: Discussionmentioning

confidence: 99%

Understanding emotional and health indicators underlying the burnout risk of healthcare workers

Güveyi,

Elvin,

Kennedy

et al. 2024

Preprint

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BackgroundBurnout of healthcare workers is of increasing concern as workload pressures mount. Burnout is usually conceptualised as resulting from external pressures rather than internal resilience and although is not a diagnosable condition, it is related to help seeking for its psychological sequelae.ObjectiveTo understand how staff support services can intervene with staff heading for burnout, it is important to understand what other intrapsychic factors that are related to it.MethodsA diary tool was used by staff in a region of England to self monitor their wellbeing over time. The tool explores many areas of mental health and wellbeing and enabled regression analysis to predict which of the various factors predicted scores on the burnout item.FindingsBurnout can be best explained with independent variables includingdepression, receptiveness, mental wellbeing, andconnectedness(p<0.05) using a multiple linear regression model. It was also shown that 71% of the variance present in the response variable, i.e. burnout, explained by independent variables. There is no evidence found for multicollinearity in our regression models confirmed by both the Spearman Rank Correlation and the Variance Inflation Factor methods.ConclusionWe showed how burnout can be explained using a handful number of factors including emotional and mental health indicators.Clinical implicationsThe findings suggest a simple set of items can predict burnout and could be used for screening. The data suggests attention to four factors around social safeness, grounding and care in the self, hope and meaning and having sufficient energy could form the basis of attention in weelbeing programs.

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Section: Discussionmentioning

confidence: 99%

Understanding emotional and health indicators underlying the burnout risk of healthcare workers

Güveyi,

Elvin,

Kennedy

et al. 2024

Preprint

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“…Previous studies provided general burnout programs even though dimensions of nurse burnout have long been studied. Providing tailored intervention is effective in reducing the emotional exhaustion of nurses [66]. A tailored program is an effective intervention that provides motivation to continue the program, reduces stress by increasing participant engagement, and increases participant satisfaction [67].…”

Section: Discussionmentioning

confidence: 99%

Development of an Artificial Intelligence–Based Tailored Mobile Intervention for Nurse Burnout: Single-Arm Trial

Cho,

Cha,

Baek

2024

J Med Internet Res

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Background: Nurse burnout leads to an increase in turnover, which is a serious problem in the health care system. Although there is ample evidence of nurse burnout, interventions developed in previous studies were uniform and did not consider burnout dimensions and individual characteristics. Objective:The objectives of this study were to develop and optimize the first tailored mobile intervention for nurse burnout, which recommends programs based on artificial intelligence (AI) algorithms, and to test its usability, effectiveness, and satisfaction. Methods:In this study, an AI-based mobile intervention, Nurse Healing Space©, was developed to provide tailored programs for nurse burnout. The 4-week program included mindfulness meditation, laughter therapy, storytelling, reflective writing, and acceptance commitment therapy. The AI algorithm recommended one of these programs to participants by calculating similarity through a pre-test consisting of participants' demographics, research variables, and burnout dimension scores. After completing a 2-week program, program satisfaction and burnout were measured. Users were recommended another 2-week program based on the burnout dimension scores. AI recognized the recommended program as effective if the user's burnout score reduced after the 2-week program and updated the algorithm accordingly. After a pilot test (n=10), AI optimization was performed (n=300). A paired t-test and ANOVA and Spearman's correlation were conducted to test the effect of the intervention and algorithm optimization.Results: Nurse Healing Space© was implemented as a mobile application equipped with a system that recommended one program out of four based on similarity between users through AI. The AI algorithm worked well in matching the program recommended to participants who were most similar using valid data. Users scored the program more than 4 out of 5 points for convenience and visual quality, but were dissatisfied with the absence of notifications and inability to customize the program. The overall usability score of the application was 3.4 out of 5 points. Nurses' burnout scores decreased significantly after the completion of the first 2-week program and reduced further after the second 2-week program. After completing the Nurse Healing Space© program, job stress and stress responses decreased significantly. During the second 2-week program, the level of burnout reduction increased in the order of participation. User satisfaction increased for both the first and second programs, and the post-hoc test showed significant differences between the first 100 and the third 100 participants for the first and second programs.Conclusions: This program effectively reduced burnout, job stress, and stress responses. Nurse managers were able to prevent nurses from resigning and maintain the quality of medical services using this AI-based program to provide tailored interventions for nurse burnout. Thus, this application could improve qualitative health care, increase employee satisfaction, reduce costs, ...

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“…A total of 637 articles were initially identified , of which 477 were removed after duplicates. After reading the title , abstract, keywords, and full text , 16 articles were finally included [16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31] ,…”

Section: General Characteristics Of Included Literaturementioning

confidence: 99%

“…including 1 guideline , 1 consensus, 1 evidence summary , 1 randomized controlled trial , and 12 systematic reviews (see Table 1). Association [16] guideline CINAHL Nurses' Guide to Self-Care American Academy of Nursing [17] consensus WOS Consensus recommendations for promoting nurses ' well-being Pamaiahgari [18] evidence summary JBI Intervention measures for stress and burnout of perioperative nurses Matthew [19] rct Pubmed Effect of personalized music intervention on nurses' job burnout Cohen [20] system assesment BMJ Workplace interventions to reduce nurse burnout Xu [21] system assesment JBI Effectiveness of interventions to reduce burnout among emergency department nurses Wang [22] system assesment Pubmed Effect of mindfulness therapy on nurses' job burnout Finnerty [23] system assesment Pubmed The impact of music management on nurses' job burnout Jun [24] system assesment Pubmed The relationship between nurse burnout and patients and work organization Velando [25] system assesment Pubmed The role of social support in preventing nurses' job burnout Khatatbeh [26] system assesment Pubmed Intervention implementation on nurses' job burnout and quality of life 2022 Aryankhesal [27] system assesment Pubmed Evaluation of intervention measures to reduce nurses' job burnout 2019 Zhang [28] system assesment Pubmed Evaluation of intervention measures to reduce nurses' job burnout 2020…”

Section: General Characteristics Of Included Literaturementioning

confidence: 99%

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Summary of best evidence for interventions for nurse burnout

Wang,

Li,

Liu

et al. 2024

Preprint

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ObjectiveTo search, evaluate and summarize the best evidence on nurse burnout intervention at home and abroad, and provide evidence-based basis for clinical nursing staff.MethodsThe literature on nurse burnout intervention was searched in Chinese and English guideline websites and databases, including guidelines, evidence summaries, systematic reviews, clinical decision-making, expert consensus, and randomized controlled studies. The search period was from database establishment to December 31, 2023.Results16 articles were included, including 1 guideline, 1 consensus, 1 evidence summary, 1 randomized controlled study, and 12 systematic reviews. After comprehensive analysis and induction, we extracted five aspects, including effective communication, self-care, resource support, education and training, and social environment, with a total of 15 best evidence.ConclusionThe best evidence for evidence-based intervention for nurse burnout is scientific and practical, and can provide a certain reference for clinical practice in reducing nurse burnout.

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Effects of personalized music intervention on nurse burnout: A feasibility randomized controlled trial

Cited by 6 publications

References 43 publications

Understanding emotional and health indicators underlying the burnout risk of healthcare workers

Understanding emotional and health indicators underlying the burnout risk of healthcare workers

Development of an Artificial Intelligence–Based Tailored Mobile Intervention for Nurse Burnout: Single-Arm Trial

Summary of best evidence for interventions for nurse burnout

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