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Chih-Huang Yu , Virgil Mathiowetz; Evidence-Based Literature Review on Fatigue Management and Adults With Multiple Sclerosis. Am J Occup Ther July 2015, Vol. 69(Supplement_1), 6911515067p1. doi: https://doi.org/10.5014/ajot.2015.69S1-PO2100

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Date Presented 4/16/2015

This review found strong evidence that group fatigue management education is effective for persons with multiple sclerosis while finding no evidence supporting the individual format. These results have the potential to change practice and demonstrate the need for research on the individual format.

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Fatigue interventions in long term, physical health conditions: A scoping review of systematic reviews

Roles Formal analysis, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing

Affiliations Health Psychology Section, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom, Health Psychology Department, Staffordshire University, Stoke-on-Trent, United Kingdom

Roles Formal analysis, Investigation, Methodology, Validation, Writing – review & editing

Affiliation Health and Social Care Research Centre, University of Derby, Derby, United Kingdom

Roles Conceptualization, Formal analysis, Methodology, Supervision, Validation, Writing – review & editing

Affiliation Faculty of Health and Social Sciences, Bournemouth University, Bournemouth, United Kingdom

Roles Conceptualization, Writing – review & editing

Affiliation Centre for Health, Activity and Rehabilitation Research, Queen Margaret University, Edinburgh, United Kingdom

Roles Conceptualization, Methodology, Writing – review & editing

Affiliation Division of Health & Social Care Research, Faculty of Life Sciences & Medicine, King’s College London, London, United Kingdom

Roles Conceptualization, Investigation, Writing – review & editing

Roles Conceptualization, Formal analysis, Funding acquisition, Methodology, Supervision, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Health Psychology Section, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom

• Katrin Hulme, 
• Reza Safari, 
• Sarah Thomas, 
• Tom Mercer, 
• Claire White, 
• Marietta Van der Linden, 
• Rona Moss-Morris

• Published: October 12, 2018
• https://doi.org/10.1371/journal.pone.0203367
• Reader Comments

Fatigue is prominent across many long term physical health conditions. This scoping review aimed to map the fatigue intervention literature, to ascertain if certain interventions may be effective across conditions, and if novel interventions tested in specific long term conditions may be promising for other conditions.

Scoping review methodological frameworks were used. Electronic bibliographic databases were searched (inception to November 2016) for systematic reviews of fatigue interventions in long term conditions. Inclusion criteria were: long term physical health condition; review focus on fatigue management; objective and systematic review process; primary review outcome is fatigue. Articles focussing on surgical interventions or treatments thought to trigger fatigue were excluded. A narrative synthesis was performed.

Of 115 full texts screened, 52 reviews were included. Interventions were categorised as pharmacological and non-pharmacological (exercise, psychological/behavioural and complementary medicine). Pharmacological interventions did not consistently demonstrate benefit, except for anti-TNFs and methylphenidate which may be effective at reducing fatigue. Non-pharmacological interventions such as graded exercise and fatigue-specific psychological interventions may be effective, but heterogeneous intervention components limit conclusions. ‘Complementary medicine’ interventions (e.g. Chinese herbal medicines) showed promise, but the possibility of publication bias must be considered.

Conclusions

Further research is necessary to inform clinical practice. The reported effectiveness of some interventions across inflammatory health conditions, such as anti-TNFs, aerobic exercise, and psychologically based approaches such as CBT, highlights a potential transdiagnostic avenue for fatigue management. More novel strategies that may be worth exploring include expressive writing and mindfulness, although the mechanisms for these in relation to fatigue are unclear. More work is needed to identify transdiagnostic mechanisms of fatigue and to design interventions based on these.

Citation: Hulme K, Safari R, Thomas S, Mercer T, White C, Van der Linden M, et al. (2018) Fatigue interventions in long term, physical health conditions: A scoping review of systematic reviews. PLoS ONE 13(10): e0203367. https://doi.org/10.1371/journal.pone.0203367

Editor: Urs M. Nater, Universitat Wien, AUSTRIA

Received: April 3, 2018; Accepted: August 20, 2018; Published: October 12, 2018

Copyright: © 2018 Hulme et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: This work was supported by the MS Society Grant 26. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have read the journal's policy and the authors of this manuscript have the following competing interests: One of the authors of this review (CW) is an author of one of the included papers. One of the authors (RMM) was the author of two identified protocols, both of which are still on-going. This does not alter the authors’ adherence to PLOS ONE policies on sharing data and materials.

Abbreviations: LTCs, Long term conditions; HIV, Human immunodeficiency virus; RA, Rheumatoid arthritis; MS, Multiple sclerosis; JBI, Joanna Briggs Institute; RCTs, Randomised controlled trials; CFS, Chronic fatigue syndrome; DHEA, Dehydroepiandrosterone; TBI, Traumatic brain injury; IBD, Inflammatory bowel disease; ESKD, End stage kidney disease; SLE, Systemic lupus erythematosus; TNF, Tumour necrosis factor; PD, Parkinson’s disease; GET, Graded exercise therapy; CBT, Cognitive behavioural therapy

Introduction

Fatigue can be described as a lack of energy, feeling of exhaustion or overwhelming sense of tiredness (either physical or mental), that is not relieved by rest and is a common and debilitating symptom in many long-term, physical health conditions (LTCs) [ 1 – 4 ]. LTCs are, defined as a physical health conditions that require on-going management over a period of years [ 5 ], for example liver disease, HIV, rheumatoid arthritis (RA) and multiple sclerosis (MS)[ 6 , 7 ]. Recently there has been a move towards conceptualising fatigue as having commonalities across conditions and identifying person-specific (rather than solely illness-specific) factors across domains (i.e. behavioural, cognitive, physiological, social and emotional) [ 8 , 9 ] in a more transdiagnostic approach to management.

A recent scoping review of systematic reviews investigated interventions for fatigue in adults with advanced progressive illness. Authors concluded there is a lack of robust evidence available in support of intervention effectiveness [ 10 ]. However, only Cochrane reviews were searched, and only six conditions included under ‘advanced progressive illness’ (cancer, motor neuron disease, chronic obstructive pulmonary disease, cystic fibrosis, HIV/AIDS and MS). The search for relevant articles is likely to have been limited and insights missed from other conditions where fatigue is prominent, e.g. chronic fatigue syndrome and rheumatoid arthritis [ 11 , 12 ]. Additional systematic reviews have also been conducted since, so an updated and more inclusive scoping review may provide more in-depth insights of clinical relevance.

Scoping reviews are a relatively new approach to collating health research evidence. They aim to map the existing literature in a field of interest and can be of particular use for topics that have not been extensively reviewed or are complex in nature [ 13 ]. They are becoming increasingly popular due to their ability to map key concepts, sources of evidence and types of evidence underpinning a research area [ 13 ]. They are valuable for comparing reviews of fatigue interventions across health conditions, where different study designs and interventions may be of interest [ 14 ].

The aims of this scoping review are:

• Map the range of reviews conducted on interventions used to treat, reduce or manage fatigue in LTCs, defined as a long-term, physical health condition
• Identify commonalities between interventions used across conditions and whether these are effective, which may highlight transdiagnostic aspects of fatigue management.
• Identify novel interventions trialled in any single condition, which may be promising in the treatment of fatigue in other health conditions.

A protocol was developed prior to conducting this review, based upon detailed methodology outlined in the Joanna Briggs Institute (JBI) Reviewers’ Manual [ 15 ] and the framework proposed by Arksey & Malley [ 14 ] and updated by Levac et al. [ 16 ]. This framework consists of six stages: (1) identifying the research question, (2) identifying relevant studies, (3) selecting studies, (4) charting the data, (5) collating, summarising and reporting the results, and (6) consultation. The scoping review process is an iterative one, particularly during the study selection phase [ 16 ]. During full text screening, the inclusion and exclusion criteria were refined for clarity and specificity to the review’s objectives after discussion amongst the research team. In line with the published guidelines for scoping reviews [ 15 ] and the aims of mapping rather than rating the existing literature, we did not conduct quality assessment.

Stage 1: Identifying the research question

The specific questions guiding this scoping review were: i) What fatigue interventions are used to treat, reduce or manage fatigue in LTCs, defined as a long-term, physical health condition?? ii) What interventions are commonly used across conditions, and which are consistently reported as effective? iii) Which novel interventions from individual LTCs may be promising?

Stage 2: Identifying relevant studies

Search strategy..

Comprehensive and systematic electronic searches were designed, refined and conducted in consultation with an information specialist, combining MeSH terms and keywords relating to ‘fatigue intervention’ and ‘review’ (full search strategies can be found in Appendix A). Search strategies were designed to maximise comprehensiveness and sensitivity in the initial search [ 15 ], and then increase specificity in the later screening. Therefore, names of individual conditions, as well as the term ‘long term condition’, were not specified in the initial search criteria. This minimised the risk of missing potentially relevant research, either reviews in less well-known LTCs or those in individual conditions not specifying ‘long term condition’ as a key word for searches.

The following databases were searched from their inception to November week 1, 2016: Cochrane Database of Systematic Reviews, PsycINFO; EMBASE; OvidMEDLINE(R); OvidMEDLINE(R) in process and other non-indexed citations; CINAHL; Web of Science; LILACS; PEDro. OpenGrey and Google Scholar were used to search for grey literature, and experts in the field were contacted. Reference lists and citations of included reviews were hand-searched. Only articles in the English language were considered for inclusion.

Stage 3: Selecting studies

Eligibility criteria..

Inclusion and exclusion criteria can be found in Table 1 . It is recommended that eligibility criteria are defined through an iterative process [ 15 ]. Therefore, we refined the inclusion and exclusion criteria during the screening process, in collaboration with an information specialist, to ensure our research aims were accurately met:

• Some reviews were found to group healthy and LTC populations together during analysis and not clearly describe the different populations, so we refined our initial inclusion criterion of ‘long term physical health conditions’ to ‘ solely long term physical health conditions, clearly described’ .
• Initially our focus was interventions with fatigue as the primary outcome. It became clear that most reviews included studies which had measured fatigue as a primary or secondary outcome. To maintain breadth across the field of research, we shifted the focus to defining the primary outcome of the systematic review.
• In addition to point 2, we specified that fatigue management was the focus of review as some reviews include measures of fatigue but focus on reviewing ways of assessing fatigue or documenting fatigue as a side effect of a treatment.
• The exclusion criterion ‘population undergoing surgical intervention’ was added during the second screening phase, as surgery was deemed to be a permanent, condition specific procedure (where fatigue was not the primary outcome), not of relevance to our aims of identifying transdiagnostic interventions.
• Similarly, fatigue caused by treatments or medications for specific conditions has a physiological basis that was beyond the scope of this review, thus an exclusion criterion was defined during the second phase of screening. These iterations were defined after discussion amongst the research team.

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https://doi.org/10.1371/journal.pone.0203367.t001

Types of studies.

We initially searched for reviews of fatigue interventions, including (but not limited to) systematic reviews, meta-analyses, narrative synthesis, literature reviews and scoping reviews, to ensure comprehensive identification of potentially relevant articles. Inclusion criteria were employed to select reviews which had systematically searched for papers, to identify the highest order of evidence. We defined ‘systematically conducted’ as employing a systematic and objective search strategy, using inclusion criteria and searching two or more databases.

Population.

The population of interest was ‘long term health condition’, defined as a long-term, physical health problem.

Interventions could include (but were not limited to) pharmacological, psychological, educational, behavioural and exercise methods. Initially, the focus was interventions with a primary aim of treating fatigue but it became clear that relevant reviews often included studies which had measured fatigue as both a primary or secondary outcome. Rather than specifying the outcomes of individual studies, we specified that a primary outcome and focus of the review had to be fatigue.

Interventions for fatigue due to treatment, as opposed to the health condition, were beyond the scope of this review. As cancer treatment is known to be associated with fatigue after treatment and reviews did not typically distinguish between disease-related and treatment-related fatigue, cancer-related fatigue was not included in analyses.

No limitations were set regarding the context of reviews.

Titles and abstracts of identified articles were screened by KH. Full texts of potentially relevant articles were then screened by KH against the eligibility criteria, 10% of which were quality checked/screened by ST. Any articles where inclusion was unclear were cross-checked and discussed between KH and ST.

In the absence of full texts of abstracts or review protocols, authors were emailed to ask for the full review article. In the case of abstracts, if the author did not reply but enough information was included for a decision to be made using the eligibility criteria, abstracts were evaluated for inclusion.

Stage 4: Charting the data

Data extraction..

Data were extracted using two tables; one for review characteristics and the other for fatigue related findings of each review (see supplementary tables for further details). Data extraction was conducted by KH and RS, with half of full texts assigned to each extractor. Double extraction occurred for the first ten articles. Extraction was discussed and any necessary amendments to extraction table headings were made to maximise clarity and accuracy.

Stage 5: Collating, summarising and reporting the data

Data synthesis..

A descriptive numerical summary and tabulation of findings was conducted. Findings were presented in a narrative synthesis, grouped by type of intervention, to identify fatigue interventions common (and beneficial) across LTCs, as well as interventions only implemented in certain physical health conditions.

Stage 6: Consultation

Experts in the field of fatigue and individual health conditions were consulted during protocol preparation, to help establish inclusion criteria and identify grey literature. Findings were also discussed.

Search and selection of included reviews

The database search returned 5,232 records, of which 97 were deemed potentially relevant after removing duplicates and title/abstract screening. Searching additional sources (e.g. references from experts and reference/citation lists) identified 18 further articles of potential relevance. In all, 115 articles were assessed for eligibility.

Of the four authors emailed about conference abstracts, none responded. For protocols, three authors (for four of eight protocols) replied, indicating that reviews were ongoing [ 17 – 20 ].

After full text screening, 51 articles were retained for inclusion in the scoping review, encompassing 52 reviews ( Fig 1 ). Branas et al. [ 21 ] included both a scoping and a systematic review in one article so both were included.

https://doi.org/10.1371/journal.pone.0203367.g001

Included reviews

An overview of the included reviews can be seen in Table 2 . References for all included reviews can be found in supplementary information ( S1 Text ). Review characteristics are also outlined in more detail in supplementary information ( S1 Table ), as are review findings ( S2 – S5 Tables).

https://doi.org/10.1371/journal.pone.0203367.t002

The majority of included reviews have been published or conducted in the past five years (n = 33). Twenty two reviews only included randomised controlled trials (RCTs), whereas other reviews included other study designs, such as pretest-posttest, open-label, pilot and crossover trials.

Reviews included a wide range of research articles, ranging from zero (Adams et al. [ 22 ] who did not identify any Chinese medicine chronic fatigue syndrome (CFS) intervention papers fulfilling their inclusion criteria) to 45 [ 23 , 24 ]. Reporting of total participant numbers was variable; some reviews omitted this information whilst others provided a range and/or overall total. Of the 38 reviews that stated the total, this ranged from 36 to 14,628 participants. The next largest samples were 4,765, 4,696 and 2,882, with most reviews reporting on fewer than 1,500 participants. The larger participant samples tended to be from reviews including a variety of study designs, investigating several health conditions or reviewing pharmacological interventions.

In line with the aims of this review, findings have been grouped by intervention type; pharmacological and non-pharmacological interventions. Non-pharmacological interventions have been further divided into three broad categories; ‘exercise’, ‘psychological/behavioural’ and ‘complementary medicine’ ( Table 3 ). The descriptors provided for the various interventions grouped under these broad categories are listed in Table 3 , which also presents review categories in relation to specified LTCs.

https://doi.org/10.1371/journal.pone.0203367.t003

For each intervention type, we first describe the type of interventions used and for which conditions as per aim 1. In line with aim 2 we then describe effectiveness findings, highlighting if these have been shown to be effective across more than one condition (i.e. whether they have potential for transdiagnostic fatigue management). The final section explores novel interventions trialled in any single condition, which may be promising in the treatment of fatigue in other health conditions.

Multiple reviews in the same health condition often included the same intervention studies, so findings are primarily presented in relation to health conditions as a whole, as opposed to each review individually.

Pharmacological interventions

Pharmacological interventions were considered in 24 reviews, of which 10 focussed specifically on pharmacological agents (see S2 Table ).

The most common pharmacological agents in multiple conditions were:

• Psychostimulants; methylphenidate and modafinil (sarcoidosis, Parkinson’s disease (PD), traumatic brain injury (TBI), HIV and MS).
• Anti-TNF biologic agents, such as adalimumab and infliximab (RA, inflammatory bowel disease (IBD), sarcoidosis and Sjogren’s syndrome).
• Dehydroepiandrosterone (DHEA) (systemic lupus erythematosus (SLE), HIV and Sjogren’s syndrome).
• Fluoxetine (HIV, post-stroke and CFS).
• Amantadine (peripheral neuropathy and MS).

In terms of aim 2, the magnitude of effect sizes reported by meta-analyses ranged from 0.07 to 1.23. Anti-TNF biologic agents (for example, adalimumab and infliximab) were consistently reported to be effective in reducing fatigue in RA [ 25 , 26 ], IBD [ 27 ], and sarcoidosis [ 28 ]. An effect size of 0.43 was reported for biologics in RA, with similar effects for anti-TNFs and non-anti-TNFs [ 26 ]. The psychostimulant methylphenidate also showed potential benefit across multiple health conditions, including sarcoidosis, PD, TBI and HIV. Results for the psychostimulant modafinil were inconsistent. It was reported as potentially effective in HIV [ 29 ] but findings in MS and TBI were mixed [ 7 , 30 – 33 ]. It was reported to be ineffective for PD fatigue [ 32 , 34 ] with a possible trend towards a larger effect in people with depression, than those not depressed [ 35 ].

In terms of aim 3, several pharmacological agents were considered in only one or two reviews, but were shown to significantly reduce fatigue in the respective condition of interest: non-anti-TNFs (RA) [ 25 , 26 ]; thiamine (IBD) [ 27 ]; N-acetylcysteine and belimumab (SLE) [ 36 ]; rasagiline, pergolide mesilate and pramipexole (dopamines) (PD) [ 35 , 37 ] and prokarin (MS) [ 30 ].

Pharmacological study limitations

Reviews highlighted common limitations of pharmacological studies: small sample sizes, high risk of bias, variety of outcome measures, fatigue included as a secondary outcome, participants not fatigued at baseline, not stating whether change meets minimal clinically important difference, short study duration and inadequate statistical analyses.

Non-pharmacological interventions

Non-pharmacological interventions were considered in 42 reviews, which we grouped into exercise, psychological/behavioural and ‘complementary medicine’ interventions ( S3 – S5 Tables).

Exercise interventions

Twenty-nine reviews addressed the effect of exercise on fatigue. These reviews spanned 12 conditions, as shown in Table 3 . Two reviews [ 38 , 39 ] included mixed clinical populations, overlapping with single condition reviews.

Type and mode of exercise interventions varied considerably, both within and between reviews. Across health conditions, most exercise interventions included an aerobic component. Mode of exercise typically included cycling, walking, and swimming; however, climbing, yoga, dancing and aerobics were also featured. Exercise intensity was mentioned in five reviews and was only reported in relation to aerobic exercise. Of the five reviews, two were unable to or did not draw conclusions about exercise intensity [ 7 , 40 ] (both MS), one merely reported that exercise intensity in studies ranged from low to high [ 41 ] (CFS), one reported effective exercise interventions were of moderate intensity [ 42 ], (fibromyalgia) and one reported that GET appears to be more effective when started at low levels of intensity [ 43 ](CFS).

Resistance training interventions were reported in reviews in sarcoidosis, HIV, CFS, RA and MS, but were the independent focus in only one review in MS [ 44 ](Abstract). Most reviews did not compare types of exercise, instead including all under the umbrella term ‘exercise’. Only two reviews (both MS) compared exercise modalities, concluding that a combination of endurance (aerobic) and resistance training may be of most benefit to reduce MS fatigue [ 23 , 45 ], mirroring conclusions drawn by Godhrawala et al. [ 44 ]. There was considerable variation within and across reviews in terms of intervention dose frequency and duration. Exercise interventions were reported as typically occurring three times per week, lasting approximately 40 minutes and continuing for around 12 weeks. However, this ranged from exercising one to seven times per week, for 5–60 minutes and continuing for up to six months.

In terms of the effectiveness of these exercise interventions, addressing aims 2 and 3, effect sizes of meta-analyses conducted ranged from 0.36 to 0.68. The considerable variation across reviews in different conditions made it difficult to identify specific details of exercise interventions that were effective across conditions. Within individual conditions, findings suggest graded exercise therapy (GET) could be effective in ameliorating fatigue in CFS [ 43 , 46 , 47 ]. Physical activity such as yoga, Tai Chi and pool based exercise are reported to be beneficial for RA fatigue [ 12 ]. Aerobic exercise was the predominant exercise studied in SLE patients and was reported to reduce fatigue [ 36 , 48 , 49 ]. Findings presented in the following conditions also suggest that exercise may be beneficial in ameliorating fatigue: cardiac rehabilitation in coronary heart disease; exercise advice in IBD; aerobic and resistance training in sarcoidosis; physical activity such as yoga, walking and pool based exercise in fibromyalgia. Reviews also indicate that exercise has an overall moderate effect on fatigue in MS. Findings reported in PD, TBI, post-stroke and ESKD reviews suggest exercise may not be an effective fatigue intervention. However, one should note that the number and quality of studies included in the reviews of PD were limited.

Inconsistencies were reported within reviews as all individual studies did not necessarily find exercise interventions to be beneficial. Six reviews highlighted sub-group differences or moderators as outlined in Table 4 . The sub-groups assessed varied, but factors for consideration highlighted by multiple reviews were type of control condition, exercise modality, and whether the study sample was fatigued at baseline.

https://doi.org/10.1371/journal.pone.0203367.t004

Psychological/Behavioural interventions

Twenty-six reviews addressed the effect of psychological or behavioural interventions on fatigue. These reviews spanned twelve conditions, see Table 3 . Four reviews included mixed clinical populations; two reviews combined conditions while investigating general fatigue interventions [ 38 , 39 ], while one focused specifically on mindfulness [ 52 ] and one on guided imagery [ 53 ].

Cognitive behavioural therapy (CBT) was the most cited intervention, referenced in reviews of fatigue management in all conditions except IBD, either as a standalone treatment or as a basis for treatment, (e.g. CBT based interventions targeting fluid adherence, sleep or physical functioning (ESKD) and cognitive-behavioural stress management (HIV)). Other cross-condition intervention techniques included energy conservation (MS and RA), expressive writing (RA and SLE), (psycho-)education (SLE, TBI, post-stroke, HIV, MS), mindfulness (Post-stroke, TBI, MS– 1 review) and guided imagery (asthma, bronchitis and emphysema, cancer, congestive heart failure, MS, HIV– 1 review). Self-management based interventions were also common, centring around a variety of topics such as fatigue, stress, lifestyle and nutrition (SLE, post-stroke, ESKD, RA, MS, IBD). Finally, other treatment modalities reported included ‘relaxation’, ‘solution-focused therapy’, ‘multi-disciplinary rehabilitation’, ‘counselling’ and ‘community support’. The use of varying terminology and grouping of interventions for overall analysis in reviews must be noted, making accurate comparison of individual intervention mechanisms difficult.

Referring to aim 2, taken together as a broad category, CBT/behavioural interventions were generally reported to be effective in reducing fatigue. Effect sizes reported in meta-analyses ranged from 0.24 to 0.48. CBT, psychoeducation, relaxation, counselling, stress management and expressive writing were reported as effective in SLE [ 48 , 49 ], although evidence was reported as weak and inconsistent by Yuen & Cunningham [ 36 ]. Psychosocial interventions, including CBT, expressive writing, mindfulness and group education, were reported to reduce RA fatigue, but this was a grouped analysis so the differential effects of individual modalities was unclear [ 12 ]. Again, grouped analyses suggested that psychosocial interventions may be beneficial for ESKD fatigue [ 54 ]. Relaxation was shown to significantly reduce fatigue in HIV, however, cognitive-behavioural stress management/psychoeducation was not [ 29 ]. In MS, energy conservation and CBT were reported to be effective but long term effects were inconsistent [ 55 , 56 ].

Two reviews focussed on a specific type of intervention, as opposed to a health condition. Mindfulness was reported to have a significant treatment effect on fatigue compared to no treatment or control treatments in post-stroke, TBI and MS [ 52 ]. Guided imagery findings were more inconsistent, but it was noted that studies demonstrating a significant improvement were those that had the greatest total duration of exposure, used targeted imagery (based upon condition and outcome) and had over 30 participants [ 53 ].

In terms of identifying novel interventions, solution focussed therapy, although only noted in one review (IBD), was reported as a promising intervention.

Psychological/behavioural interventions varied, for example, in duration of sessions, who provided/facilitated the intervention, the length of the intervention, whether it was delivered one-to-one or in a group, mode of delivery (e.g. face-to-face, telephone), and intervention content. Six reviews addressed sub-group differences ( Table 5 ) suggesting that interventions targeting a population fatigued at baseline (compared to non-fatigued) (MS and CFS) and one-to-one interventions (ESKD and mixed in mindfulness) may be more effective. Reviews in PD, TBI and post-stroke reported that there is little evidence for the effectiveness of CBT/behavioural programmes.

https://doi.org/10.1371/journal.pone.0203367.t005

‘Complementary medicine’ interventions

Fifteen reviews addressed interventions categorised as ‘complementary medicine’ (RA, SLE, IBD, MS, TBI, CFS, Post-stroke, ESKD and PD), although one of these did not include any papers [ 22 ](CFS). Further sub-groups were identified;interventions of Eastern origin (e.g. acupuncture, acupuncture based treatment, Chinese herbs, Japanese massage), physiological interventions (e.g. cooling, pulsed electro-magnetic devices, phototherapy), diet and nutritional supplements (e.g. fish oil, acetyl-carnitine). Interventions included under this category in single reviews were reflexology and health tracker information (RA), Qigong (CFS) and Tai Chi and Yoga (mixed) (which other reviews considered under physical activity), continuous positive airway pressure therapy (post-stroke) and occupational therapy (ESKD).

In terms of aim 2, Eastern origin interventions have been investigated in RA (n = 1), SLE (n = 2), CFS (n = 1), Post-stroke (n = 1), ESKD (n = 1) and PD (n = 1). These included herbal medicine (two reviews; RA and CFS), acupuncture, acupuncture related treatments (e.g. minimal needling, electroacupuncture, acupressure, acupoint application) and Japanese massage (one review; PD), all of which were reported as effective in reducing fatigue. Acupuncture/acupuncture based treatment was the most common intervention, applied and reported to be effective across four conditions (all except RA).

Diet manipulation was included in reviews in RA and SLE. In both conditions, diet was reported to be effective in reducing fatigue, specifically a Mediterranean diet [ 12 ](RA), a low glycaemic index diet or a low calorie diet [ 36 , 48 ](SLE). Nutritional supplements were reported to not reduce fatigue; omega-3 fish oil (IBD and RA), Vitamin D (SLE). Acetyl-L-carnitine was reported to be more effective for reducing fatigue than amantadine in MS but was not compared to an alternative control group [ 38 ], overlapping with Tejani et al. [ 60 ] in pharmacological).

Physiological interventions included: electroencephalographic biofeedback, cranial electrotherapy stimulation and bright blue light treatment in TBI [ 33 ]; cooling and pulsed electromagnetic therapy in MS [ 7 , 30 ]; and UV phototherapy in SLE [ 36 ]. Again, all reviews reported fatigue reduction. These interventions were more novel, identified as effective in individual conditions, addressing aim 3.

Non-pharmacological study limitations

Reviews highlighted several issues: few studies specifying fatigue as a primary outcome; heterogeneous intervention protocols and study designs (e.g. sample sizes, intervention length, dose, frequency and session duration); single study findings; heterogeneity in control conditions (e.g. waiting list control, active control, treatment as usual); and not considering findings in relation to clinically important differences. For ‘complementary medicine’ interventions in particular, reviews highlighted that most interventions were only investigated by one study, and these studies were often of low quality. This limits the conclusions that can be drawn and highlights the need for caution when interpreting the findings. Potential publication bias was also noted in this group as most interventions, especially the Chinese medicine ones, reported positive findings.

Fatigue outcome measures in pharmacological and non-pharmacological reviews

Most reviews (n = 44) reported details of fatigue outcome measures, encompassing a large number of diverse measures. These ranged from illness specific measures (e.g. PD fatigue scale, MS Quality of Life Questionnaire, Kidney Disease Questionnaire), single item Likert-type scales, subscales of questionnaires (e.g. POMS (vigor/fatigue), SF-36 (vitality)) and visual analogue scales, to specific fatigue questionnaires such as Chalder Fatigue Scale, Modified Fatigue Impact Scale, Fatigue Severity Scale, Brief Fatigue Inventory and Chronic Illness Therapy Fatigue Domain.

We conducted a comprehensive scoping review mapping fatigue interventions in chronic health conditions, ranging from those where fatigue is a clearly defined key symptom, such as CFS and MS, to less common conditions, such as Sjogren’s syndrome and peripheral neuropathy. In the last five years, there has been an increase in the number of published reviews. However, we note that interventional studies included in reviews often do not specifically target fatigue and include study samples that may not be fatigued at baseline.

Of the pharmacological agents, only anti-TNFs and methylphenidate were identified as beneficial across multiple conditions, in line with aim 2. Anti-TNFs were reported to be effective treatments for fatigue in RA, IBD, Sjogren’s syndrome and sarcoidosis, all conditions classified as autoimmune/inflammatory. Anti-TNF medication acts to suppress the response to the tumour necrosis factor (TNF), for example blocking TNFa (a cytokine which stimulates and regulates inflammation and release of other cytokines as part of the inflammation cascade) to reduce the inflammatory response [ 61 ]. Although this medication is targeting inflammatory disease activity as opposed to the fatigue symptom, the cross-condition benefits indicate fatigue mechanisms may be similar, possibly linked to the body’s inflammatory response [ 62 ].

In contrast, fluoxetine (an anti-depressant) was reported as ineffective for reducing fatigue in HIV [ 29 ], post-stroke [ 63 ], mixed palliative care population [ 24 ] and CFS [ 46 ], suggesting fatigue in these LTCs is not a symptom of depressed mood [ 11 ].

Non-pharmacological interventions were particularly heterogeneous, varying in modality, duration and type of intervention provider/facilitator. Even after categorising them into three sub-groups (exercise, psychological/behavioural and ‘complementary medicine’), comparison was hampered by intervention heterogeneity. Broadly speaking, aerobic exercise (as well as general and mixed exercise models that included a substantial aerobic component) and CBT based interventions were the most common and seemed effective in reducing fatigue.

However, none of these were reported to significantly reduce fatigue in three neurological conditions: PD, TBI and post-stroke, indicating mechanisms underlying fatigue in these conditions may be different. Neurological pathology can cause cognitive difficulties, which may account for the ineffectiveness of these interventions in these LTCs [ 64 – 66 ], whereas other non-pharmacological interventions, such as cranial electrotherapy stimulation(which do not rely on patients’ cognitive abilities), were shown to be effective. Programmes such as CBT and graded exercise involve cognitions, planning and goal setting [ 67 ]. These may be harder to engage in if attentional or memory deficits are present. This is not to say that cognitive impairment makes exercise and CBT interventions ineffective, as physical activity has been reported to be beneficial for cognition in a meta-analysis in dementia for example [ 68 ]. Instead the delivery of these interventions may need structuring in such a way that is accessible for patients.

Review limitations may also account for inconsistencies: i) reviews included studies which had measured fatigue both as a primary (i.e. targeted) outcome or as a secondary outcome; and ii) reviews included a range of measures of fatigue, ranging from fatigue-specific measures to single item statements. As fatigue was often a secondary outcome, interventions may not have been powered to detect changes in fatigue. However, these limitations were not confined to reviews in PD, TBI and post-stroke so do not necessarily account for the inter-condition differences.

Strengths and limitations

The in-depth search conducted yielded posters, conference abstracts, protocols, unpublished and published articles, and is likely to have captured the relevant research in this area.

However, non-English language papers were not included. Also, of the 64 excluded reviews, 22 investigated CFS. Although fatigue is the condition-defining symptom, most CFS reviews were excluded because they did not specify fatigue as a primary outcome, instead including either a range of undefined outcomes or not explicitly stating outcome of interest (see S6 Table ).Cancer-related fatigue was also not included, due to the known association of fatigue with the treatment of the condition. Insights and conclusions from reviews in these conditions will have been missed. One person undertook screening and extraction. A 10% quality check during screening and extraction aimed to minimise the potential of papers or findings being missed, but does not negate the risk completely.

It is not in the scoping review remit to analyse the quality of reviews or individual studies [ 15 ], so the review is restrained by reporting; findings for a particular intervention may be based on a single or small number of studies of varying quality, as is the case with interventions from Eastern origin, for example. This highlights the need to bear in mind the aims of the review; to map the current literature and identify patterns, rather than draw definite conclusions about the efficacy of a certain intervention. Nonetheless, the quality of reviews themselves was also variable: inconsistencies in reporting findings from the same studies across reviews arose [ 34 , 35 , 37 ]; findings were often categorised unclearly and inconsistently; some full texts were not received in response to requests; and some reviews included studies with a non-RCT design, which may result in high risk of bias. Heterogeneity across reviews means it is difficult to assess what the underlying fatigue reduction mechanism may be, and subsequently deduce what components would be needed for an ‘ideal’ fatigue intervention. As per scoping review protocol [ 15 ], we did not formally quality assess the reviews to rank/ weight the findings we report so conclusions need to be drawn cautiously.Our findings narratively describe and map the fatigue intervention literature. Thus, only areas of limited research can be identified, which future research could address. Specific recommendations for care pathways cannot be made.

Implications for future research and practice

Reviewing literature across LTCs highlighted commonalities as well as novel approaches, both of which may be potentially useful for developing interventions. As highlighted by reviews’ recommendations ( S1 Table ), the methodological quality of the research in this area requires improvement. High quality, guideline adherent RCTs are needed which: recruit participants who are fatigued at baseline; trial interventions that specifically target fatigue as a primary outcome; have a well specified theory/hypothesis regarding the mechanisms through which intervention reduces fatigue; include long term follow up; and report clinical significance.Future reviews should ensure accurate and complete reporting, outline all intervention details and analyse moderators where possible.

In response to aim 2, interventions which may appear most promising for future transdiagnostic research include 1) anti-TNFs and methylphenidate, 2) exercise that is substantially aerobic in nature (either when delivered alone or as part of a general or mixed exercise approach) and graded, 3) psychologically based approaches including CBT, psychoeducation (possibly more so when delivered individually, for increased number of hours and, importantly, when specifically targeting fatigue), 4) diet alteration, 5) acupuncture.

Regarding aim 3, more novel, non-pharmacological strategies which may be worth considering in other LTCs include solution-focussed therapy, expressive writing and guided imagery (if fatigue focussed), and mindfulness.

Although the standard mean differences and their confidence intervals reported in the meta-analyses suggest treatments were generally more efficacious than control (see S2 – S5 Tables), effect sizes were only small or moderate in size. Therefore, a multifactorial approach incorporating multiple strategies (for example, a combined exercise-psychological/behavioural-acupuncture-diet programme) may be more effective for reducing fatigue [ 69 ] and[ 70 ](RA). Interventions need to consider different possible underlying fatigue mechanisms across different LTCs (e.g. neurological versus inflammatory) so a flexible transdiagnostic approach may be needed, taking the pathology and characteristics of the patient populations into account [ 9 ]. Importantly, several reviews highlighted that interventions may need to focus specifically on fatigue in order to elicit the most benefit.

The aim of a scoping review is to map literature, rather than quality assess or rate evidence, so direct recommendations for practice cannot be made [ 15 ].Further research into the effectiveness, safety and cost of interventions would be needed, as would clear identification of mechanisms of action. However, the aims and research questions of this scoping review were addressed. Firstly, the evidence reported by systematic reviews on the topic of fatigue interventions in LTCs was collated and summarised. Secondly, this highlighted the potential transdiagnostic effectiveness of anti-TNFs, methylphenidate, graded aerobic exercise, psychological based approaches, diet and acupuncture. Importantly, the pathology of conditions may determine effectiveness (for example, whether the condition has an autoimmune/inflammatory basis). Lastly, individual condition interventions were identified, of which solution focussed therapy, expressive writing, fatigue focussed guided imagery and mindfulness may be valuable to explore across other conditions. More work is needed to identify transdiagnostic mechanisms of fatigue and to design interventions based on these.

Appendix A. Database search strategies

1806- Nov week 1

• (fatig* adj4 (interven* or improv* or prevent* or program* or therap* or treat* or reduc* or manag*))
• Exp “Literature Review”/ or review.mp
• ((systematic or quantitative or scoping or narrative or literature) adj4 (review or overview or synthesis).mp
• Exp Meta Analysis/
• (meta-analysis or meta analysis or metaanalysis).mp
• 2 or 3 or 4 or 5

1974-11/11/2016

• meta analysis/

Ovid MEDLINE(R) 6

1946 –Nov week 1 2016

• “Review Literature as Topic”/ or review.mp

Ovid MEDLINE(R) In process and other non-indexed citations 6

Until Nov 9 th 2016

• Review.mp or exp “Review”/

(-> 18/11/2016)

N = 223 (reviews and protocols)

N = 117 (‘other’ reviews)

1900–2016 present (14/11/2016)

TX (fatig* N4 (interven* or improv* or prevent* or program* or therap* or treat* or reduc* or manag*)) AND TX ((systematic or quantitative or scoping or narrative or literature) N4 (review or overview or synthesis) or meta analysis)

Web of science

TOPIC: (fatig* near/4 (interven* or improv* or prevent* or program* or therap* or treat* or reduc* or manag*)) AND TOPIC: (meta analysis OR ((systematic or quantitative or scoping or narrative or literature) NEAR/4 (review or overview or synthesis)))

N = 3 in English (none of those relevant). 1 is potentially relevant but article in Spanish:

Efectividad del ejercicio físico en la fatiga de pacientes con cáncer durante el tratamiento activo: revisión sistemática y metaanálisis / Effectiveness of physical exercise on fatigue in cancer patients during active treatment: a systematic review and meta-analysis / Eficácia do exercício físico na fadiga dos pacientes com câncer durante o tratamento ativo: revisão sistemática e meta-análise

Meneses-Echávez, Jose Francisco; González-Jiménez, Emilio; Correa-Bautista, Jorge Enrique; Valle, Jacqueline Schmidt-Río; Ramírez-Vélez, Robinson.

Cad Saude Publica; 31(4): 667–681, 04/2015. tab, graf

Article in Spanish | LILACS | ID: lil-744849

(fatigue) AND (intervention OR improve OR prevent OR program OR therap OR treat OR reduc OR manag) AND (review)

fatig* interven* (Method selected from drop down list = systematic review)

OpenGrey 12/12/16

“Fatigue [intervention/treatment/management/prevention/therapy/program/improve] Review”

N = 9. None relevant.

Consultation suggested to check:

• Ankylosing spondylitis– 1 –for full text review
• SLE– 1- (already captured in database search)
• Polymyositis– 0
• Vasculitis– 0

Review Fatigue [Intervention/Treatment] ([condition])

New/previously not found: n = 3 for full text screening.

Supporting information

S1 text. references of studies included in scoping review..

https://doi.org/10.1371/journal.pone.0203367.s001

S2 Text. List of protocols identified.

https://doi.org/10.1371/journal.pone.0203367.s002

S1 Table. Review characteristics.

https://doi.org/10.1371/journal.pone.0203367.s003

S2 Table. Reviews including pharmacological interventions for fatigue treatment.

https://doi.org/10.1371/journal.pone.0203367.s004

S3 Table. Reviews including exercise interventions for fatigue treatment.

https://doi.org/10.1371/journal.pone.0203367.s005

S4 Table. Reviews including psychological/behavioural interventions for fatigue treatment.

https://doi.org/10.1371/journal.pone.0203367.s006

S5 Table. Reviews including complementary medicine non-pharmacological interventions for fatigue treatment.

https://doi.org/10.1371/journal.pone.0203367.s007

S6 Table. Excluded reviews.

https://doi.org/10.1371/journal.pone.0203367.s008

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Fatigue management: a literature review.

• MLA style: "Fatigue management: a literature review.." The Free Library . 2003 Employee Assistance Professionals 01 May. 2024 https://www.thefreelibrary.com/Fatigue+management%3a+a+literature+review.-a0108442800
• Chicago style: The Free Library . S.v. Fatigue management: a literature review.." Retrieved May 01 2024 from https://www.thefreelibrary.com/Fatigue+management%3a+a+literature+review.-a0108442800
• APA style: Fatigue management: a literature review.. (n.d.) >The Free Library. (2014). Retrieved May 01 2024 from https://www.thefreelibrary.com/Fatigue+management%3a+a+literature+review.-a0108442800

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• Open access
• Published: 23 April 2024

Alarm fatigue and perceived stress among critical care nurses in the intensive care units: Palestinian perspectives

• Basma Salameh   ORCID: orcid.org/0000-0003-1372-7199 1 ,
• Jihad Abdallah 2 ,
• Sameer A Alkubati 3 , 5 &
• Mohammed ALBashtawy 4  

BMC Nursing volume  23 , Article number:  261 ( 2024 ) Cite this article

151 Accesses

Metrics details

The frequency of alarms generated by monitors and other electro-medical devices is undeniably valuable but can simultaneously escalate the workload for healthcare professionals, potentially subjecting intensive care unit nurses to alarm fatigue. The aim of this study is to investigate alarm fatigue and stress levels among critical care nursing personnel. Additionally, the study aims to assess predictors for both alarm fatigue and perceived stress.

Methodology

: A descriptive cross-sectional study recruited 187 Intensive Care Unit (ICU) nurses from hospitals located in the northern and central regions of the West Bank, Palestine. Data were gathered through online surveys due to logistic concerns using the Alarm Fatigue Scale and the Perceived Stress Scale. The research was conducted between November 2023 and January 2024.

The mean overall alarm fatigue score was 23.36 (SD = 5.57) out of 44. The study showed that 62.6% of the participating ICU nurses experience average to high degree of alarm fatigue, while 69.5% experience average to high levels of perceived stress. A significant positive Pearson correlation was found between stress and alarm fatigue (0.40, P  < 0.01). Important predictors of alarm fatigue include perceived stress, nurse-to-patient ratio, gender, and years of experience, while important predictors of perceived stress include alarm fatigue, type of working shift and hospital unit.

Alarm fatigue can compromise the timely intervention required to prevent adverse outcomes by causing delayed responses or missed critical alarm, which can have major ramifications for patient safety. Addressing stress is crucial for mitigating alarm fatigue and fostering a supportive work environment to ensure optimal patient care. Consequently, exploring strategies to alleviate the negative impacts of alarm fatigue on critical care nurses’ stress merits further investigation in future research studies.

Peer Review reports

Today’s healthcare organizations have access to a wide range of technologies and resources to assist everyday clinical practice, particularly in intensive care units, where patients are continuously monitored with specialized alarm systems to alert health care providers [ 1 , 2 , 3 ].

However, continuous monitors frequently produce excessive alarm warnings that may not always indicate significant changes in the patient’s clinical status. [ 4 – 5 ]

Every day, nurses in intensive care units (ICUs) deal with 350 alarms per bed, 85–99% of which are not actionable. [ 6 – 7 ] As a result, nurses often find themselves grappling with alarm fatigue, which affects their ability to react to alarms effectively and reduce their receptivity to these notifications [ 8 , 9 , 10 , 11 , 12 ]. Alarm fatigue poses a significant risk for critical care nurses, who serve as the frontline healthcare providers interacting directly with patients and monitoring them around the clock [ 13 ]. Critical care nurses are often subjected to excessively frequent and burdensome alarms, potentially impeding their ability to concentrate on tasks and responsibilities, leading to lapses in `attention and increased likelihood of errors [ 14 ]. Alarm fatigue, a concerning phenomenon, is triggered by the constant stream of alarms in the ICU [ 6 , 14 ]. Alarm fatigue occurs when healthcare professionals become desensitized to the frequent occurrence of alarms, particularly those with non-actionable character [ 6 ]. This tendency may cause crucial alarms to be missed or responded to slowly, endangering the safety and wellbeing of patients, which could lead to patient mortality [ 10 ].

Increased levels of alarm fatigue may be associated with suboptimal nursing practices, such as altering alarm parameters outside of acceptable ranges, turning down alert volume, or even turning off alarm systems entirely. Such acts may put patient safety in danger [ 15 , 16 ]. Recognizing the severity of this issue, The Joint Commission, reaffirmed alarm fatigue management as a global priority for patient safety in recognition of the seriousness of this problem (Joint Commission, 2022). [ 9 – 10 ] This reiteration emphasizes how crucial it is to address alarm fatigue in healthcare settings in order to protect the wellbeing and safety of patients.

Critical care units are widely recognized as highly stressful work environments, attributed to several factors including demanding and complex job descriptions, escalating admissions, unpredictability schedule changes, unrealistic expectations from patients and their families, and the frequent encounters with moral and end-of-life dilemmas. Nurses within these units contend with extended work hours, time constrains, limited breaks, staffing shortage, and substandard working conditions [ 7 , 8 ]. Research consistently associated work-related stress with diminished performance, reduced quality of life, and a host of health issues encompassing physical, psychological, and interpersonal problems [ 9 , 10 ]. Given the overwhelming responsibilities and demands associated with providing care in today’s healthcare systems, especially in critical care units, nurses are frequently exposed to high levels of stress [ 17 ]. Additionally, studies have consistently shown that nurses working in critical care units experience significantly higher levels of stress compared to their counterparts in other nursing specialties [ 18 , 19 ]. Consequently, prolonged exposure to such heightened stress levels poses a grave risk to patient safety and the overall care quality of care provided [ 20 ].

When multiple alarms in the critical care unit sound simultaneously, nurses often feel overburdened. A monitor that emits unnecessary sounds or false alert has been identified as a stress-inducing factors for healthcare providers [ 21 ]. According to previous studies, a significant and positive correlation has been observed between the socio-demographic characteristics of nurses, such as work experience, education level, age, gender, nurse-patient ratio and the occurrence of alarm fatigue [ 22 , 23 , 24 ]. Furthermore, there is abundant evidence indicating that psychological factors such as stress and anxiety among nurses, play a substantial role in contributing to alarm fatigue [ 25 ].

To our knowledge, no previous studies have addresses alarm fatigue in Palestine. Therefore, the aim of the current study is to examine alarm fatigue among nurses working in critical care units. Additionally, the study aims to assess the relationship between alarm fatigue and perceived stress. This knowledge can be used to create strategies aimed at mitigating the adverse consequences of alarm fatigue among critical care nurses. The adverse effects of alarm fatigue on the professional achievements of nurses and patients’ outcomes can be reduced by education, planning, and providing counseling to nurses regarding the factors that have the greatest impact on the development of alarm fatigue.

Study design

Descriptive cross-sectional study was conducted. The target population ( N  = 251) included critical care nurses working in hospitals located in the northern and central regions of the West Bank, Palestine. Due to the constrains imposed by the October 7th war in Palestine, which rendered physical access to all hospitals challenging, data were gathered through online surveys. The research was carried out between November 2023 and January of 2024.

The researcher initiated contact with the nursing directors of each hospital. Subsequently, they obtained consent to distribute the survey to all nurses working in intensive care units (ICUs) via email and social media groups, with the assistance of the head of ICU nurses. An explanatory letter detailing the study goals and purpose was attached to the online survey to ensure data quality and accuracy during data collection process. Additionally, the researchers included a cell phone number in the explanatory letter to address any potential questions or concerns from the participants.

Sample size

The required sample size was determined using an Excel calculation sheet developed by Abdallah (2024) [ 26 ], (available at: https://www.researchgate.net/publication/378550258_Sample_size_calculation_sheet ) based on the formula by Daniel (1999) [ 27 ], which adjusts for finite population size as follows:

n* = \( \frac{nN}{n+(N-1)}\) , where \( n=\frac{{\left({Z}_{\frac{\alpha }{2}}+{Z}_{\beta }\right)}^{2}\left[P\left(1-P\right)\right]}{{d}^{2}}\) for two-sided tests. N is the population size (= 251), P is the assumed population proportion (= 0.50), d is the margin of error (= 0.05), α is the significance level (= 0.05), and β is the probability of Type II error (= 0.20, i.e., statistical power = 80%). \( {Z}_{\frac{\alpha }{2}} \) and 𝑍 𝛽 (1.64 and 1.28, respectively) are the standard normal values such that 𝑃 ( 𝑍 ≥ \( {Z}_{\frac{\alpha }{2}}\) ) = 𝛼 /2 and 𝑃 ( 𝑍 ≥ 𝑍 𝛽 ) = 𝛽 . The calculated sample size was 191. The actual sample included 187 ICU nurses who completed the questionnaire out of the 251 nurses targeted in the study (a response rate of 74.5%).

Inclusion / exclusion criteria

All nurses working in the ICU units for at least one year in Palestinian hospitals in the central and northern regions of the West Bank were included in the study. Student nurses and nurses on leave such as maternity leave was excluded from the study.

Tool of the study

Structured questionnaire consisting of demographic characteristics of the nurses including age, gender, marital status, experience, qualifications, type of hospital, hospital unit, nurse to patient ratio, type of work shift, and extra outside work.

Alarm Fatigue Questionnaire. It comprises 13 items. The tool was originally developed by Torabizadeh et al. (2017) [ 28 ] with approval obtained to use this scale for conducting the study. Answers to each item are given using the 5-Point Likert scale: “always”, “usually”, “sometimes”, “rarely”, and “never”. These are scored from 0 (never) to 4 (always) except items 1 and 9 which are scored reversely. The total score range of the questionnaire is between 8 (minimum) and 44 (maximum), with higher scores indicating a greater impact of alarm fatigue on nurse’s performance.

Perceived Stress Scale: is a classic stress assessment instrument. The tool, while originally developed in 1983, remains a popular choice to help understand how different situations affect feelings and perceived stress. The scale is publicly available and consists of 10 items which ask about feelings and thoughts during the last month [ 29 ].

The overall alarm fatigue scale (AFS) and perceived stress scale (PSS) scores were obtained as the sum of points of individual items and then converted into three categories using the sten (standard ten) scale (Canfield, 1951) [ 30 ]. As applied by Nagórska et al. (2021) [ 31 ], a final sten score of 1–4 is defined as low, 5–6 is defined as average, and 7–10 is defined as high.

After creating the questionnaire, it was presented to 5 nursing PhDs and experts in scientific research and the field of critical care nursing to assess its face and content validity and obtain comments and feedback. Cronbach’s Alpha was determined for the Alarm fatigue scale (13 items, Chronbach’s α = 0.60) and for the Perceived stress scale (10 items, Chronbach’s α = 0.73).

The questionnaire was translated into Arabic and reverse -translated to ensure accuracy. The validity of the tool was assessed by consulting five experts in the field: two university professors and three ICU nurses. They were asked to review and approve its validity, provide feedback on clarity, and assess whether the items reflected the main objectives of the study. Any necessary modifications were made based on their feedback.

Pilot study

Twenty ICU nurses completed the questionnaire as a pre-test before the full data collection process. This allowed the nurses to identify any ambiguities in the questionnaire’s wording, estimate the response rate, determine the actual time required for completion, and assess the questionnaire’s suitability and validity. Completing the surveys takes approximately 15 to 20 min.

Ethical approval

was obtained from Ministry of Health, Helsinki Committee in Palestine and from the Arab American University (Approval number: PHRC/HC/23). Participation in the study was entirely voluntary for nurses, and declining to participate would not result in any negative consequences or penalties. Furthermore, the study meticulously safeguarded the confidentiality of the participants by not disclosing any names or personal information, which were kept securely for research purposes only. Informed consent was obtained from all participants, and all procedures were conducted in compliance with the guidelines outlined in the Declaration of Helsinki.

Data analysis

The statistical analyses of data were conducted using the Statistical Package for Social Sciences (SPSS), version 21.0. Chronbach’s α was obtained as a measure of reliability. The distributions of the overall AFS and PSS scores were assessed graphically using Boxplots and Normal Probability Plots. Boxplots of the data showed symmetric distributions with no extreme values, and the Normal Probability Plots did not reveal any serious deviations from normality. Therefore, we adopted a parametric statistical approach for the analysis of data. Descriptive statistics (frequencies, percentages, means, and standard deviations) were used to summarize the data. Correlation analysis was performed to obtain Pearson correlation coefficients between the overall AFS and PSS scores, while Fisher’s Exact test was performed to test the association between AFS and PSS score categories. Independent samples t-test and one-way ANOVA were carried out to test differences in means of overall AFS and PSS scores among levels of categorical variables (e.g., socio-demographic, and other characteristics of participating nurses). The Linear Automatic Modeling regression function of SPSS was utilized to determine which factors are important predictors of alarm fatigue and perceived stress using the forward stepwise method based on the adjusted-R 2 criterion for entry and removal of predictor variables. The factors assessed for prediction are summarized in Table  1 . Assessment of the distribution of the studentized residuals from the final prediction models showed that the distributions are fairly close to the normal distribution (Fig.  1 ).

Histograms of studentized residuals from the final prediction models using Linear Automatic Modelling. The smooth line represents the normal distribution. The closer the frequencies of the residuals to the line, the closer the distribution of the residuals is to the normal distribution

Alarm fatigue scale (AFS)

Table  2 presents the means of individual item and overall AFS scores. The mean overall AFS score was 23.36 (SD = 5.57) out of 44. Among all participating nurses, 70 (37.4%) experience low alarm fatigue, 62 (33.2%) experience average alarm fatigue, and 55 (29.4%) experience high alarm fatigue.

The responses to individual items by the ICU nurses participating in the study indicated a greater impact of alarm fatigue on their performance when they were asked about item 5 “I pay more attention to the alarms in certain shifts” (3.58 out of 4), and item 4 “I believe much of the noise in the ward is from the alarms of the monitoring equipment ” (3.06 out of 4). On the other hand, the lowest impact of alarm fatigue on ICU nurses’ performance were for item 11 “When alarms go off repeatedly, I become in different to them” (0.80 out of 4), and item 2 “I turn off the alarms at the beginning of every shift” (0.82 out of 4).

Among all characteristics of participating nurses, only gender have a significant effect ( P  < 0.05) on the overall AFS score, with female nurses having a higher average score (24.60) than male nurses (22.65). All the other characteristics showed non-significant effects ( P  > 0.05), as shown in Table  3 .

Perceived stress scale (PSS)

The means of PSS scores for individual items and the overall scores for nurses working in the ICU units are presented in Table  3 . The mean of the overall PSS scores was 16.99 out of 40. Among all participating nurses, 57 (30.5%) were categorized as having low perceived stress level, 73 (39.0%) were categorized as having an average perceived stress level, and 57(30.5%) were categorized as having a high perceived stress level.

The response of the ICU nurses to individual PSS items regarding their feelings and thoughts in the last month showed that the highest average scores were for item 3 “how often have you felt nervous and “stressed?” (2.09 out of 4), item 6 “how often have you found that you could not cope with all the things that you had to do?” (1.95out of 4), and item 1 “how often have you been upset because of something that happened unexpectedly” (1.88 out of 4). While the lowest averages for ICU nurse’s responses were for item 8 “how often have you felt that you were on top of things” (1.28 out of 4), for item 4 “how often have you felt confident about your ability to handle your personal problems?” (1.45 out of 4), and item 7 “how often have you been able to control irritations in your life?” (1.48 out of 4).

The analysis of variance showed a statistically significant effect of the type of work shift on ICU nurses’ perceived stress ( P  < 0.05), where nurses working double shifts had the lowest average score (15.23), and nurses working regular morning shifts had the highest average score (17.92). Conversely, there were no statistically significant effects ( P  > 0.05) of age, marital status, experience, qualification, hospital unit, nurse-to- patient ratio, and extra work on ICU nurses’ alarm fatigue and perceived stress (see Table  4 ).

Relationship of alarm fatigue scores and perceived stress scores

A significant positive Pearson correlation coefficient of 0.40 was found between AFS and PSS overall scores ( P  < 0.01). Fisher’s Exact test showed a highly significant association ( P  < 0.001) between the AFS and PSS score categories. A high frequency of nurses in the low AFS score category were in the low PSS score category (50.9%) and vice versa (41.4%); a high frequency of nurses in the average AFS score category were in the average PSS score category (49.3%) and vice versa (58.1%); and a high frequency of nurses in the high AFS category were in the high PSS category (61.4) and vice versa (63.6%) (refer to Table  5 ). Furthermore, the results from One-way ANOVA showed significant differences ( P  < 0.001) among AFS categories in mean PSS scores where nurses in the high AFS category had a significantly higher mean PSS score (19.45) than nurses in the low and average AFS categories (15.53 and 16.45, respectively). Similarly, significant differences ( P  < 0.001) were found among PSS categories in mean AFS scores where nurses in the high PSS category had significantly higher mean AFS score (26.79) than nurses in the low and average AFS categories (21.37 and 22.23, respectively).

Prediction model for the overall AFS (alarm fatigue scale) scores

The variables retained for predicting the AFS overall score using the Linear Automatic Modeling procedure included (in order of importance): PSS score category ( P  < 0.001, importance = 0.689), nurse-to-patient ratio ( P  = 0.034, importance = 0.176), gender ( P  = 0.024, importance = 0.085), and experience ( P  = 0.216, importance = 0.051) with adjusted R 2  = 0. 217 (Fig.  2 ; Table  6 ). Nurses in the low and average PSS score categories had -ve coefficients (− 5.533 and − 4.706, respectively) compared to those in the high PSS score category; nurses caring for fewer than 5 patients had–ve coefficients compared to those caring for 5 or more patients; female nurses had + ve coefficient (1.732) compared to male nurses; and nurses with less than 5 year experiences and those with 5–10 year experience have + ve coefficients compared to those with more than 10-year experience (see Table  6 ).

Important predictors of overall AFS (Alarm Fatigue Scale) scores of nurses working in the critical care units in Palestine

Prediction model for the overall PSS (perceived stress scale) scores

For predicting the PSS overall score, the prediction model included AFS score category ( P  < 0.001, importance = 0.674), type of working shift ( P  = 0.099, importance = 0.195), and hospital unit ( P  = 0.375, importance = 0.131), with adjusted R 2  = 0.138 (Fig.  3 ; Table  7 ). Nurses in the low and average AFS score categories have -ve coefficients (− 3.582 and − 2.463, respectively) compared to those in the high AFS score category; nurses working double shifts and irregular shifts had–ve coefficients compared to those working regular morning shifts (-2.144 and − 0.288, respectively) while nurses working regular evening shifts had a slight positive coefficient (0.029); nurses working in the emergency care units, general critical care units, medical critical care units, and other types of hospital units had positive coefficients (0.619, 0.655, 1.566, and 2.114, respectively) compared to nurses working in the surgical cardiac units, (Table  7 ).

Important predictors of overall PSS (Perceived Stress Scale) scores of nurses working in the critical care units in Palestine

To the best of our knowledge, no previous study has been conducted to examine the impact of alarm fatigue on nurses’ performance, its associated factors, and its relationship with perceived stress in Palestine. Our study revealed that the mean total score of the Alarm Fatigue Scale was 23.36, indicating that critical care nurses in Palestine experience moderate levels of alarm fatigue. Critical care nurses are particularly susceptible to alarm fatigue due to the extensive time they devote for patient care and monitoring, necessitating continuous vigilance and prompt response to alarms generated by numerous medical devices [ 14 ]. Consequently, health care professionals may develop a desensitization to the frequent alarm occurrences. This desensitization could lead to crucial alarms being missed or responded to slowly, resulting in decrease concentration and physical exhaustion, thereby jeopardizing patient safety and wellbeing, potentially leading to adverse outcomes, including patient mortality. These findings are in line with studies conducted in Iran, Italy, and China [ 32 , 33 , 34 ]. Conversely, a study conducted in Ghana found that the majority of nurses experienced severe alarm fatigue [ 35 ].

Additionally, our findings revealed that the item with the highest average score was “I pay more attention to the alarms in certain shifts”. This tendency may be attributed to the nature of work in intensive care units, where alarm fatigue is prevalent, and behaviors during specific shifts may be influenced by factors such as nurse-patient ratio, patient acuity, and varying workload. For example, during morning shifts, the workload on nurses may increase, leading to heightened attention to alarms [ 36 ]. Conversely, in Korea the highest scoring item was “I hear a certain amount of noise in the ward” [ 38 ]. The items with the lowest scores were “I turn off the alarms at the beginning of every shift” and “I regularly readjust the limits of alarms based on the clinical symptoms of patients”. These findings sugest that ICU nurses, despite experiencing alarm fatigue, promptly respond to any alterations in patients’ conditions. These findings are consistent with previous studies [ 37 , 38 ]. However, they contrast with a study conducted in Ireland, where the majority of nurses either disregarded the alarm or exhibited delayed responses when experiencing alarm fatigue [ 39 ].

Another important finding of this study was that the majority of respondents reported an average to high level of perceived stress. In addition to work and social factors, this can also be attributed to the prolonged conflict between Israel and Palestine, which increases the risk of anxiety and stress among Palestinians [ 40 ]. Furthermore, healthcare professionals in Palestine are more likely to experience stress and burnout when working in an extremely restricted healthcare system under Israeli military occupation [ 41 , 42 ]. This finding aligns with a previous study conducted in India, which found that the majority of NICU nurse experienced a moderate level of stress [ 43 ]. In contrast to our findings, a previous study conducted in Qatar reported that nurses experienced a high level of perceived stress [ 44 ]. Given the demanding nature of the healthcare professionals, nurses are particularly susceptible to issues related to occupational stress [ 45 ].

The PSS Score category emerged as the most important predictor of the AFS overall score and vice versa (the AFS Score category emerged as the most important predictor of the PSS overall score). Nurses in the low and average PSS score categories are expected to have lower AFS scores than the high PSS category by an average of 5.53 and 4.71 points, respectively. Nurses in the low and average PSS score categories are expected to have lower AFS scores than the high PSS category by an average of 3.582 and 2.463 points, respectively This suggests that ICU noises may be stressful to healthcare professionals [ 46 ], but also suggests that stressed nurses may have aggravated alarm fatigue. Research has shown that loud noise in intensive care units (ICUs) can negatively impact health care professionals, leading to increased stress and decreased performance [ 47 ]. Alarms contribute to this noise and can be disruptive to nurses, hindering their ability to effectively carry out their tasks [ 48 ]. Therefore, it is essential to reduce noise-induced stress among critical care nurses to improve the working environment and patient care [ 49 ]. Furthermore, healthcare institutions should consider evaluating their alarm policies and procedures, potentially integrating artificial intelligence technologies for more efficient alarm management.

In intensive care units, the utilization of numerous medical devices contributes to the escalating noise level and increasingly loud alarms, which are reported psychological issues by nurses [ 38 ]. Health professionals exposed to this sensory overload for extended periods of time experience both cognitive and physical stress [ 50 , 51 ].

Additionally, nurse- to-patient ratio and gender were identified as predictors of alarm fatigue, with female nurses being more susceptible experiencing it. This could be attributed to the heavier workload carried by female ICU nurses, not only due to stressful working environment but also compounded by personal responsibilities such as housework, childcare, and balancing work -life commitments [ 36 , 52 ]. Our results align with a previous study, which also indicated a higher likelihood of alarm fatigue among female nurses [ 32 ]. However, this contrasts with the findings of Bourji H, et al. (2020), which found that male nurses experience alarm fatigue more frequently than female nurses [ 25 ].

The study’s results also revealed that nurses working regular morning shifts experienced high levels of perceived stress. This could be attributed to the heavy workload of morning shift nurses, which includes tasks such as patient admission and discharge, patient care responsibilities, and managing visitors. Occasionally, these demands may lead them to skip their breaks [ 53 , 54 , 55 , 56 ].

A Self-administered survey was considered a limitation in this study. Future research should consider employing observational checklist and qualitative research designs to address alarm fatigue more accurately among critical care nurses. Furthermore, certain factors were not addressed, such as the consequences of alarm fatigue on quality of patient care, resilience, and burnout. These aspects warrant further investigation in future studies.

Implications for clinical practice

To mitigate alarm fatigue among critical care nurses, managers should implement comprehensive alarm management protocols, including regular adjustment of alarm settings and the integration of artificial intelligence technologies for efficient alarm management. Continuous training and education programs on alarm management best practices are also essential. Addressing nurses’ stress levels is imperative to ensure patient safety and improve the quality of care. Identifying sources of stress and implementing effective stress reduction intervention, such as mindfulness-based techniques, is crucial. Further studies are warranted to explore these interventions. Additionally, it is essential to assess the complex relationship between alarm fatigue, stress and patient outcomes. This will facilitate the development of evidence-based practices and policies that support critical care nurses and enhance patient care outcomes.

Alarm fatigue can compromise the timely intervention necessary to prevent adverse outcomes by causing delayed responses or missed critical alarm, thereby posing a major risk for patient safety. The study indicated that the highest score was related to nurses’ attention to alarm varying according to shift, a factor not addressed in the current study. Therefore, future research should examine the impact of different shifts on alarm fatigue and patient outcomes. Additionally, it is imperative that healthcare providers address stress, as it has been found to be an important predictor of alarm fatigue. This will aid in mitigating alarm fatigue and fostering a supportive work environment conducive to providing optimal patient care. Furthermore, future research studies are needed to assess the effectiveness of educational training in managing alarm fatigue and reducing stress levels among critical care nurses.

Data availability

The data utilized to support the results of the research are accessible to the corresponding author upon request.

Abbreviations

Intensive Care Unit

Alarm Fatigue Scale

Perceived Stress Scale

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Acknowledgements

We would like to express our thanks to all critical nurses who participated in the study.

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Basma Salameh

Department of Animal Production, An-Najah National University,Nablus, Jenin, Palestine

Jihad Abdallah

Department of Nursing, Faculty of Medicine and Health Sciences, Hodeida University, Hodeida, Yemen

Sameer A Alkubati

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B.S, J.A, S.A, M.A designed the study B.S, J.A, collected the data B.S, J.A, S.A & M.A analyzed the data All authors prepared the manuscript All authors approved the final version for submission.

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Salameh, B., Abdallah, J., Alkubati, S.A. et al. Alarm fatigue and perceived stress among critical care nurses in the intensive care units: Palestinian perspectives. BMC Nurs 23 , 261 (2024). https://doi.org/10.1186/s12912-024-01897-x

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Improving fatigue risk management in healthcare: A systematic scoping review of sleep-related/fatigue-management interventions for nurses and midwives

Affiliations.

• 1 Faculty of Sport, Health and Applied Science, St Mary's University, London TW1 4SX, UK. Electronic address: [email protected].
• 2 Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7YH, UK.
• PMID: 32283414
• DOI: 10.1016/j.ijnurstu.2019.103513

Background: Nurses and midwives make up almost 50% of the global healthcare shift working workforce. Shift work interferes with sleep and causes fatigue with adverse effects for nurses' and midwives' health, as well as on patient safety and care. Where other safety-critical sectors have developed Fatigue Risk Management Systems, healthcare is behind the curve; with published literature only focussing on the evaluation of discreet sleep-related/fatigue-management interventions. Little is known, however, about which interventions have been evaluated for nurses and midwives. Our review is a critical first step to building the evidence-base for healthcare organisations seeking to address this important operational issue.

Objectives: We address two questions: (1) what sleep-related/fatigue-management interventions have been assessed in nurses and midwives and what is their evidence-base? and (2) what measures are used by researchers to assess intervention effectiveness?

Design and data sources: The following databases were searched in November, 2018 with no limit on publication dates: MEDLINE, PsychINFO and CINAHL.

Review methods: We included: (1) studies conducted in adult samples of nurses and/or midwives that had evaluated a sleep-related/fatigue-management intervention; and (2) studies that reported intervention effects on fatigue, sleep, or performance at work, and on measures of attention or cognitive performance (as they relate to the impact of shift working on patient safety/care).

Results: The search identified 798 potentially relevant articles, out of which 32 met our inclusion criteria. There were 8619 participants across the included studies and all were nurses (88.6% female). We did not find any studies conducted in midwives nor any studies conducted in the UK, with most studies conducted in the US, Italy and Taiwan. There was heterogeneity both in terms of the interventions evaluated and the measures used to assess effectiveness. Napping could be beneficial but there was wide variation regarding nap duration and timing, and we need to understand more about barriers to implementation. Longer shifts, shift patterns including nights, and inadequate recovery time between shifts (quick returns) were associated with poorer sleep, increased sleepiness and increased levels of fatigue. Light exposure and/or light attenuation interventions showed promise but the literature was dominated by small, potentially unrepresentative samples.

Conclusions: The literature related to sleep-related/fatigue-management interventions for nurses and midwives is fragmented and lacks cohesion. Further empirical work is warranted with a view to developing comprehensive Fatigue Risk Management Systems to protect against fatigue in nurses, midwives, and other shift working healthcare staff.

Keywords: Circadian dysregulation; Fatigue; Night shift work; Nurse-midwives; Nurses; Patient care; Patient safety; Rotating shift work; Shift work schedule; Sleep.

Copyright © 2019. Published by Elsevier Ltd.

Publication types

• Systematic Review
• Delivery of Health Care / methods*
• Delivery of Health Care / trends
• Fatigue / prevention & control*
• Fatigue / psychology
• Fatigue / therapy
• Middle Aged
• Nurses / psychology*
• Risk Management / methods*
• Risk Management / trends
• Sleep Wake Disorders / prevention & control*
• Sleep Wake Disorders / psychology
• Sleep Wake Disorders / therapy