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Understanding lifestyle self-management regimens that improve the life quality of people living with multiple sclerosis: a systematic review and meta-analysis

Abstract

Background

Lifestyle self-management as an intervention for people living with multiple sclerosis (plwMS) is an emerging area of research. Previous reviews have highlighted a need to systematically identify effective self-management regimens that influence the health and well-being of plwMS using a common metric of success.

Objectives

To examine the effectiveness of lifestyle self-management strategies and interventions aimed at improving the quality of life (QOL), and/or disability of plwMS. The review also aimed to narratively explore common elements of self-management interventions that were effective at improving the outcomes of interest.

Methods

A systematic search was performed using five scientific databases. The review process followed the Cochrane Handbook for Systematic Reviews of Interventions  and was registered with PROSPERO (Ref: CRD42021235982).

Results

A total of 57 studies including 5830 individuals diagnosed with MS, met the inclusion criteria. Self-management interventions included physical activity, fatigue, dietary, stress/coping, emotional, symptom and medical management, and lifestyle and wellbeing programs. Self-reported QOL improved in 35 of 47 studies. Dietary intervention had no statistically significant overall effect on reducing MS disability, (P = 0.18). Heterogeneity limited the ability to pool the effects from a large number of eligible studies of the same design.

Conclusion

Multicomponent self-management interventions, multimodal delivery methods, and cognitive behavioural theory principles were common elements of self-management interventions that improved the QOL of plwMS. However, these results should be interpreted with caution and care should be taken in its clinical application. This review has the potential to inform future management practices for plwMS and has revealed a significant gap in the literature, warranting high-quality, large-scale experimental, and observational studies that address lifestyle management.

Introduction

Rationale

Living with multiple sclerosis (MS) is associated with unpredictable and debilitating neurological symptoms [1]. These symptoms include physical challenges (i.e. fatigue, pain, weakness, spasticity), cognitive deficits (i.e. memory loss, slow processing, poor concentration), and/or emotional symptoms (i.e. anxiety, mood swings, irritability, depression) that fluctuate throughout the disease course, regardless of the MS phenotype [1, 2]. While medical management, including the provision of disease-modifying therapies (DMT’s), is important to maintain good health when living with MS, the impact of these symptoms is not restricted to routine healthcare visits. For most people living with MS (plwMS), these symptoms are experienced daily and create a multitude of challenges that can significantly impact quality of life (QOL) [2, 3]. Therefore, it is the day-to-day management of the disease course and symptoms that can have a profound impact on the current and future health and well-being of plwMS.

Self-management is a relatively new phenomenon within healthcare but has received increased attention as an effective management strategy for chronic health conditions; it is the ideology that acknowledges neurological conditions, such as MS, as a continuous experience [4]. Self-management focuses on equipping the individual with the skills and ability to manage their symptoms, monitor medication regimens and physical disability, engage in physical activity, maintain nutritional status, and adjust to the psychological demands of their condition [5, 6]. There is considerable evidence that self-management interventions are effective in improving the health and functional status, knowledge, adherence to treatment, and the physical, psychological, and social domains of QOL among people with chronic conditions [7,8,9]. The emergence of lifestyle self-management as an intervention for plwMS is a growing area of focus, and while currently limited, the effectiveness of self-management interventions holds promise [10].

A systematic review conducted by Kidd et al. examined the impact of self-management interventions on the psychological well-being of plwMS [11]. Despite the inclusion criteria, the limited number of published studies specific to MS care at the time (n = 10) and the heterogeneity between the included studies made it difficult to compare the effectiveness of different treatment strategies on self-reported outcome measures. Similarly, a second review exploring self-management support in people with neurological conditions generally, also concluded that the limited number of studies (n = 39) and the diversity in reported self-management outcome measures challenged the ability to comment on the overall effectiveness of the strategies [12]. More recently, Yamaguchi et al. examined the potential of self-management for people living with HTLV-1 associated myelopathy by reviewing the literature within an MS context. Again, the included studies reported inconsistent outcome measures (i.e. QOL, self-efficacy, cognitive changes) and only a limited range of medical, role (i.e. social life and independence) and emotional management strategies [13].

Previous reviews [11,12,13], therefore, highlight a need to systematically identify effective elements of self-management regimens that influence the health and well-being of plwMS using a common metric of success. QOL was chosen as an accepted outcome measure in clinical studies and has been identified as an important measure in MS research as it incorporates the personal and social context of a person’s life [14]. Moreover, Mitchell et al. recommended that studies of interventions in MS populations use assessments of QOL rather than impairment or disability measures alone [15].

Aims and objectives

Therefore, the present review aimed to examine the effectiveness of lifestyle self-management strategies and interventions aimed at improving QOL, as the primary outcome, and/or disability among plwMS [14, 15]. The review also aimed to narratively explore common elements of self-management interventions that were effective at improving the outcomes of interest.

Methods

Registration and protocol

The present review was guided by the Cochrane Handbook for Systematic Reviews of Interventions [16] and reported according to the Preferred Reporting Items for Systematic Reviews and Meta Analysis (PRISMA) 2020 statement [17] and 27-item PRISMA checklist [17]. The review protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO) [18] (Ref: CRD42021235982) in February 2021, to reduce the potential for bias through a transparent review process [19].

Eligibility criteria

Studies were included in the review if they met the following criteria:

Types of studies and publications Studies published in peer-reviewed journals, including both experimental and observational studies. Non-English studies were excluded. Studies including case studies, review articles, feasibility and pilot studies, protocols, grey literature, and publications including conference abstracts, editorials, and monographs were also excluded. No date restrictions were applied to the final search.

Types of participants Adults aged \(\ge 18\) years with a clinical diagnosis of MS using the McDonald criteria (2001, 2005, 2010, or 2017) [20] regardless of their time since diagnosis. Studies that included people diagnosed with a clinically isolated syndrome phenotype, pregnant or breastfeeding females, or paediatric MS were excluded.

Types of interventions A study that described a self-management intervention followed by a participant was included. A self-management intervention was defined as a strategy that provided the individual with the opportunity to learn self-management skills by focusing on the tasks and/or healthy behaviour(s) in a person’s life, supporting them to accomplish a task, and assist in the management of their condition. The MS Research Australia Modifiable Lifestyle Factors guidance documents were used to classify self-management interventions [21]. Therefore, elements of self-management included any combination of symptom management strategies, diet and nutrition, physical activity and exercise, stress management, fatigue management, meditation/relaxation therapy, psychological management, rehabilitation strategies, supplementation use, and sun exposure [21].

Types of comparators Any comparator was considered for inclusion, and studies with no control groups were also included. The control arms of the intervention studies included participants who did not receive treatment or received usual care.

Types of outcomes Studies that described QOL as a primary outcome, or disability as a primary or secondary outcome, using a validated measure were included. This included, but was not limited to, the 36-item Short Form Survey (SF-36), multiple sclerosis impact scale (MSIS-29), multiple sclerosis quality of life-54 (MSQOL-54), quality of life-3 (QOL-3), short form-12 (SF-12), short form-8 (SF-8), Euro-quality of life, Hamburg quality of life questionnaire MS (HAQUAMS), and the World Health Organization QOL instrument (WHOQOL) [22].

Measures of disability included the expanded disability status scale (EDSS) and patient-determined disease steps (PDDS). The EDSS is a clinically administered assessment scale, and plwMS are assigned a score that corresponds to their level of ambulatory ability (ranging from 0: normal neurological exam/no disability to 10: death due to MS) in 0.5 increments [23, 24]. The PDDS is a self-reported tool to identify the level of physical disability in plwMS, which strongly correlates with the EDSS [25]. The tool is scored on a scale from 0 (normal; functionally normal with no limitations on lifestyle) to 8 (bedridden). Additional measures of disability included lesion burden (number of new lesions, size of lesions) as measured by MRI, number of relapses in a certain time period (relapse rate), and Guy’s neurological disability scale [26].

Search strategy

The research question in the PICO format was: What is the effect of lifestyle self-management strategies and/or interventions on QOL and/or disability in plwMS? A systematic search was conducted using five scientific databases: Cochrane Library, CINAHL via EBSCOhost platform, MEDLINE via Ovid platform, PubMed via ProQuest platform, and Scopus via Elsevier. Although PubMed is a subset of MEDLINE, both MEDLINE and PubMed databases were searched to ensure that the most recent studies were identified [27]. A preliminary search was performed in February 2021 to determine the feasibility of the search by identifying sentinel articles. The final search was conducted on 8 April 2021 (OW).

The search strategy included alternative phrases, spelling, and truncations, using both controlled vocabulary and free-text terms. For a detailed search strategy, please refer to Additional file 1: data 1. To increase the sensitivity, manual hand searching of the reference lists of extracted systematic reviews and meta-analyses was performed to obtain additional relevant studies.

Selection process

A three-phase screening process was implemented to ensure that the included studies met eligibility criteria. All studies were exported to Covidence (Covidence Systematic Review Software, 2019, Veritas) to manage the screening process, and duplicates were removed. Two reviewers (OW and ES) independently screened titles and abstracts of the search results. Where consensus was not reached, a third and more senior researcher (YP) was consulted. For studies and reviews that met the inclusion criteria, the full text was retrieved and screened by two researchers (OW and YP). Discrepancies were resolved by discussions between the two researchers.

Data extraction

One author (OW) extracted relevant information from the included studies based on the Cochrane Consumers and Communication Review Group’s data extraction template [16]. Information extracted from each study included: study details (country, setting, date published), first author, study methodology (study design, recruitment, groups), participant characteristics (sex, age, MS phenotype, duration of disease, EDSS or PDDS score), study characteristics (intervention description, comparator/control description), description of primary and secondary outcomes (QOL or disability measurement tool used), results and a summary of the conclusions. Corresponding authors of studies with missing data were contacted via email to obtain additional information to be used in the synthesis of the results. No responses were obtained.

The effect measures of randomised control trials (RCT) included continuous outcome measures for both QOL and disability variables, which were summarised as the mean difference (\(\pm\) standard deviation) from pre to post intervention, unless otherwise stated. For observational study designs, the relative risk was reported where available from the included studies.

Data synthesis

The authors (OW, YP) identified what self-management regimen was being explored in each study and categorised it into one of five dimensions based on MS Australia’s Modifiable Lifestyle Factors Guidance document  [21]. This included: (1) physical activity, (2) diet, (3) fatigue management, (4) coping, depression, stress, and emotional management, and (5) symptom and medical management. Some interventions had multiple components (i.e. diet, exercise, and energy conservation); therefore, these interventions were categorised into a sixth dimension of (6) lifestyle and wellbeing programs. Individual studies were qualitatively synthesised under each self-management dimension to identify the findings related to participant outcomes. The outcomes are reported quantitatively in the final data summary table. The primary outcome measure was QOL (including their respective domains), and the secondary outcomes were measures of disability such as EDSS, relapse rate, and number and volume of T1 and/or T2 weighted brain lesions. Statistical significance was set at P < 0.05.

A meta-analysis was performed when there were two or more studies under the same self-management dimension that used the same disability measure or QOL domain with compatible summary measures (i.e. mean change (SD)), using Review Manager (RevMan) (Mac OS X, Version 5.4, The Cochrane Collaboration, 2020). Summary estimates were reported for studies of randomised controlled trials only, as the heterogeneity of comparing different study designs may increase the complexity of the analyses and impact the interrelation of quantitative outcomes [16, 28].

An inverse variance with random effects model was used because of the heterogeneity among participants in terms of MS disability and population characteristics [29]. The RevMan Calculator was used to calculate the standard deviation from the 95% confidence intervals and reported changes in means [30]. The I2 statistic was used to quantify the proportion of total variation attributable to between-study heterogeneity. Heterogeneity was categorised according to the Cochrane guidelines: (1) I2 = 0–40%: low heterogeneity; (2) I2 = 30–60%: moderate heterogeneity; (3) I2 = 50–90%, substantial heterogeneity; and (4) I2 = 75–100%: considerable heterogeneity [16].

Risk of bias assessment

The risk of bias (RoB) of each study was appraised according to the study design. Version 2 of the Cochrane RoB tool, as recommended in the Cochrane Handbook for Systematic Reviews of Interventions [16], was used to assess RoB in each RCT. The studies were appraised according to the RoB arising from (1) the randomisation process, (2) deviations from the intended interventions (effect of assignment to intervention), (3) missing outcome data, (4) measurements of the outcome, and (5) selection of the reported result. A proposed RoB judgment for each domain was generated using an algorithm [31] and each study was assessed as having low risk, some concerns, or high RoB.

The RoB in non-randomised studies of interventions was assessed using the ROBINS-I tool [32]. This tool focuses on seven domains of bias including: bias due to confounding, selection of participants into the study, classification of interventions, deviations from intended interventions, missing data, outcome measurements and selection of the reported results. Risk levels of low, moderate, serious, critical, or insufficient information were assigned to each of these domains.

The RoB in case–control and cohort studies was assessed according to the Newcastle Ottawa Quality Assessment Scale (NOS) [33]. This scale was adapted from the NOS for cohort studies to provide RoB assessment of cross-sectional studies [34]. A star system was used to appraise each study under the following domains: (1) the selection of study groups, (2) the comparability of the study groups, and (3) ability to identify the exposure or outcome of interest. Each study was awarded one star for each criterion under the selection and exposure/outcome categories, and a maximum of two stars for the comparability category. Therefore, cohort/case–control studies with 7–8, 5–6, 4 and 0–3 stars were identified as very good, good, satisfactory, or unsatisfactory, respectively. Cross-sectional studies with 5, 4, 3 or 0–2 stars were identified as very good, good, satisfactory, and unsatisfactory, respectively [35].

Certainty assessment

The certainty of the body of evidence of the quantitative synthesis was assessed using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) criteria [36]. The certainty of the body of evidence considered within-study risk of bias, precision and consistency of effect estimates, directness of evidence and risk of publication bias. An overall GRADE was determined as one of four levels of evidence: high, moderate, low and very low, by the two researchers (OW, YP). Randomised controlled trials begin with a high level of evidence. Factors that may increase or decrease the quality level of a body of evidence have been described elsewhere [36].

Results

Study selection

A total of 1664 references were identified from the database search, and an additional 14 references were obtained from manual searches. After removing the duplicates (n = 762), 902 references were retained. The full texts of 310 references were screened, and 43 studies met the inclusion criteria. Therefore, 57 studies were included in this systematic review [37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93]. the full selection process is presented in Fig. 1.

Fig. 1
figure 1

PRISMA flow chart of study selection

Study characteristics

The included studies were published between 1996 and 2021, with 70% of studies published after 2010 and 33% of studies published after 2016. The highest proportion (35%) of included studies were conducted in the USA (n = 20) [40, 41, 4749, 5153, 59, 60, 63, 74, 81, 8386, 88, 91, 93] followed by 28% in Europe (n = 16; Belgium, Italy, Netherlands, Slovenia, Denmark, Germany, Turkey, Finland, Norway and Switzerland) [39, 42, 43, 45, 46, 50, 55, 61, 62, 6466, 68, 71, 73, 77], 16% in Asia (n = 9; Iran and India) [55, 57, 58, 69, 70, 72, 75, 82, 92] and 9% in both Australia (n = 5) [55, 56, 7880] and UK (n = 5) [38, 67, 76, 89, 90]. In total, 70% (n = 40) of included studies were of experimental study designs of which 85% (n = 34) were RCT's [38, 4346, 50, 51, 5356, 59, 6063, 6676, 83, 84, 86, 8891]. The remaining 30% of studies were of an observational study design including case–control (n = 8) [40, 41, 52, 65, 71, 81, 92, 93], cohort (n = 7) [37, 39, 64, 7880, 87] and cross sectional analysis (n = 2) [47, 48] studies. The duration of the studies ranged from one week to five years. The full data summary is presented in Table 1.

Table 1 Results of included studies (n = 57) examining lifestyle management on QOL and disability, characterised according to self-management dimension

Participant characteristics

The 57 included studies included a total of 5830 individuals diagnosed with MS, with a median of 82 individuals per study (IQR, 110). The majority (95%) of the studies included both female and male participants, with approximately 75% of the participants being female. Five percent of the studies (n = 3) were restricted to females [59, 83, 87]. Twenty-one percent (n = 12) included only participants with the RRMS phenotype [39, 45, 49, 55, 63, 6975] and 47% (n = 27) included participants with all MS phenotypes. The median age of the participants was 45 years (IQR 9.67), with the majority of studies having mean ages of participants in the 30-or 40-year age group. Of the 14 studies (25%) that included a EDSS score to quantify disability [38, 45, 50, 51, 54, 55, 59, 64, 68, 69, 71, 7375], the median score was 2.9 (IQR 1.8), suggesting most individuals had a relatively limited disability due to MS. The median disease duration of participants was 8.6 years since MS diagnosis (IQR 4.16).

Description of outcomes

QOL was most commonly measured at follow-up or post intervention using the MS Quality of Life-54 form (MSQOL-54) in 15 of the 57 studies (26%) [37, 38, 5557, 6266, 69, 7880, 82]. The Short Form-36 was used in a further 12 studies (21%) [42, 53, 59, 74, 76, 81, 83, 84, 86, 8890]. The most commonly used tool to measure neurologic disability was the EDSS in 14 out of 57 studies (25%) [38, 45, 50, 51, 53, 59, 64, 68, 69, 71, 72, 7476]. This was followed by the relapse rate (n = 7) [46, 7073, 74, 93], MRI brain scans, including lesion count and volume (n = 6) [45, 46, 55, 68, 70, 73] and the PDDS (n = 4) [41, 49, 52, 84].

Qualitative synthesis of individual studies

The most commonly reported intervention dimensions were physical activity and exercise (n = 21, 37%) [37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57]; coping, depression, stress, and emotional management (n = 10, 18%) [58,59,60,61,62,63,64,65,66,67]; diet (n = 8, 14%) [68,69,70,71,72,73,74,75], lifestyle and wellbeing (n = 8, 14%) [76,77,78,79,80,81,82,83]; fatigue management (n = 7, 12%) [84,85,86,87,88,89,90] and symptom and medical management (n = 3, 5%) [91,92,93]. Key findings are explored below for each dimension.

Physical activity interventions

Of the 21 studies that assessed physical activity, seven reported a significant improvement in QOL domains and only one saw a significant improvement in disability measures among plwMS [37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57]. One study was delivered via multimodal means [43] and the remaining 20 were delivered face-to-face [37,38,39,40,41,42,43,44,45,46,47,48,49,50,42, 4457]. The most common QOL domains that saw significant improvement among the seven studies were physical (n = 4), mental (n = 4), emotional (n = 2), energy (n = 1), and fatigue (n = 1) domains.

Disability was most commonly measured using EDSS (n = 6) and lesion characteristics (n = 3). The most common intervention activity was general exercise (n = 5), followed by aerobic exercise (n = 5) and yoga (n = 3). Other types include walking, expedition, live-in training programs, resistance training, and inpatient rehabilitation programs.

Among those studies reporting a significant improvement in outcome measures, group-based interventions were a common occurrence, and exercise sessions ranged from to 60–90 minutes in duration.

General exercise interventions ranged from six weeks to 14 months, with typical programs involving team sports, walking, and group activities. Of these, none of the general exercise programs saw a significant change in MS disability, with only one study reporting a significant improvement in QOL for up to 14-months after a combined exercise program.

Of the five studies assessing aerobic exercise [38, 46, 51, 55, 56], four reported significant improvements in QOL subscales [38, 51, 55, 56] including mental, physical, pain, energy, social, sexual function, fatigue, and overall QOL. Two studies reported a significant decrease in the disability measures [46, 55]. One of these studies was restricted to participants with only the RRMS phenotype and included only those prescribed fingolimod as a DMT. Among those studies exploring yoga as an intervention, two reported significant improvements in emotional, energy, and vitality QOL domains at the six month time point.

Coping, depression, stress and emotional management interventions

Of the ten studies that explored coping, depression, stress, and emotional self-management strategies [58,59,60,61,62,63,64,65,66,67], seven studies were RCT's, all of which reported a significant improvement in QOL post intervention, relative to the controls [5963, 66, 67]. Controls were not exposed to the interventions and continued with routine standardised MS care. Six were delivered face to face [59, 6163, 66, 67] and one was delivered via telephone [60]. One of these studies was conducted among adults with a RRMS phenotype only, all others did not restrict the MS phenotype in their inclusion criteria. Physical (n = 6) and mental health (n = 5)-related QOL were the most common domains reported. A key finding was that significant improvements in QOL domains among the seven interventional studies were reported almost immediately and lasted for up to six months. Few studies have included data on the long-term effects of these interventions (i.e. 12 months and beyond).

Common theories, models, and practical strategies were used in the seven studies that reported a significant improvement in QOL domains. The most popular theory was cognitive behavioural theory (n = 3), followed by supportive/positive expressive psychotherapy (n = 3), and mindfulness practice (n = 2). Two studies explored the effect of the Social Cognitive Can Do Program (SCDP) among people with a RRMS phenotype [64, 65]. Each study collectively reported a significant immediate improvement in mental and physical health-related QOL at six months; however, only physical QOL maintained statistical significance at 12-months post intervention.

Dietary interventions

The impact of dietary patterns and nutritional supplementation on QOL and disability measures in plwMS was assessed in eight studies. [68,69,70,71,72,73,74,75] Of the three studies that assessed the impact of fish oil supplementation [7375], only one reported an immediate improvement in the physical composite score of QOL post intervention relative to a control group [74]. The intervention group received a combination of six fish oil capsules per day (198 mg EPA, 132 mg DHA), 400 units of vitamin E, 1 multivitamin, and 500 mg calcium while following a very low fat diet (i.e. < 15% total energy from fat). The control group was fed a low-cholesterol diet (i.e. < 30% total energy from fat), 400 units of vitamin E, 1 multivitamin, 500 mg calcium, and an olive oil supplement as a placebo. No clinical benefit of fish oil supplementation was found in relation to disability measured using the EDSS or the number of new T1 enhanced and hypo-intensive brain lesions [73, 75].

One study evaluated the effect of probiotic intake and reported a significant improvement in EDSS and general health QOL, favouring the intervention [72].

Only one study assessing the impact of vitamin D supplementation found a significant improvement in mental and health-related subscales [69]. The intervention consisted of patients on interferon-beta as their main DMT, supplementing 50,000 IU vitamin D3 every five days for three months. Controls consumed a placebo. Vitamin D supplementation at 20,000 IU was found to have no significant impact on disability measures via the EDSS or relapse rate [68, 71] however, one study of the same supplemental dose did observe a significant decrease in the number of T1 weighted lesions [68]. Control participants were given a placebo and continued with usual care.

Lifestyle and wellbeing

Of the eight studies that assessed lifestyle and/or well-being programs, all were delivered face-to-face, and all reported a significant improvement in QOL, favouring lifestyle self-management courses or exposures [76,77,78,79,80,81,82,83]. The most common QOL domains that saw a significant improvement across the eight studies included mental health (n = 7) [76, 7883] and physical health (n = 6) [76, 7882] related QOL. All studies included an intervention or exposure to at least two or more self-management dimensions, and the most common combinations included a dietary (n = 6), exercise (n = 6), and a psychological (emotional, fatigue, stress, coping, support) component (n = 6). In two studies, a group-based self-management workshop, delivered by trained healthcare professionals, reported both a short-term (immediate) and long-term (three years) improvement in QOL [80, 82]. A key finding, however, was the sustained improvement in a majority of QOL subscales, including physical health, mental health, pain, and social and overall QOL, for up to five years post intervention [78, 79]. Only one study [83] used a combination of delivery methods including a face-to-face lifestyle program, followed by three months of accountability telephone calls. Improvements in QOL domains, including pain and mental health, were sustained for the duration of the 8-month intervention period.

Fatigue management

Of the seven studies that assessed the impact of fatigue management programs on QOL [84,85,86,87,88,89,90], four reported a significant improvement in QOL, favouring the fatigue management course. Five were delivered face-to-face [8587,86,, 89, 90] and two were delivered remotely [84, 88] via teleconference sessions. Of the interventions delivered remotely, both were conducted over a 6-month period however only one reported a significant improvement in physical, vitality and social QOL, favouring the intervention [9193]. The remaining study comprised of a simpler intervention including only three teleconference sessions and four individually tailored counselling phone calls [88].

Of the interventions delivered face-to-face, three reported a significant improvement in domains of QOL [8486]. These three studies ranged from six weeks to three years, however they displayed similar participant characteristics, including mean age of participants around 48 years and disease duration of ~ 9.5 years. The most common QOL domains that saw a significant improvement after fatigue and energy conservation courses included vitality, social, mental health, and physical health-related QOL [8486, 90]. One study that reported no significant improvement after a fatigue intervention accompanied by usual care suggested a longer term follow-up of two years or more may be required to observe a consistent and significant change in QOL [89].

Symptom and medical management

The impact of symptom and medical management on QOL was assessed in three studies [92, 94]. Participants followed either a symptom self-care program [91, 92] or program combining medication management and education [93]. Of these three, one study reported a significant improvement in general health-related QOL after a 12 month intervention period, relative to a control group [91]. This study was delivered via an electronic messaging system between plwMS and their clinicians, to enhance symptom control and management. Controls continued their usual MS care. Of the remaining two observational studies, only one revealed a significant improvement in physical, psychological, social, and environmental QOL after a self-care management course [92]. The remaining study found no significant improvement in QOL after a DMT self-management program; however, they reported a 33.6% significant decrease in relapse rate [93].

Meta-analysis of studies

Only one self-management dimension met the inclusion criteria for a meta-analysis to calculate pooled estimates of the effect of self-management interventions on homogenous disability outcome measures. An additional two meta-analyses were eligible based purely on a homogenous self-management dimension, QOL domain and summary measure. However, the heterogeneity that was created by comparing different study designs would impact the interrelation of results and a decision to exclude these meta-analyses was made by the authors.

  • i. Diet

Five studies, including 286 participants, examined the effect of dietary interventions on disability, using the EDSS [68, 70,71,72, 75]. Aivo et al. [68] Kouchaki et al. [72] and Zandi- Esfahan et al. [75] reported a reduction in EDSS scores following dietary intervention, while Bitarafan et al. [70] and Kampan et al. [71] did not observe a change in EDSS between the intervention and control arms. None of the results were statistically significant.

As demonstrated in Fig. 2, dietary intervention had no statistically significant overall effect on reducing disability as measured by EDSS scores (MD = − 0.13, 95% CI = − 0.31–0.06, Heterogeneity: Tau2 = 0.02, Chi2 = 8.55, df = 4 (P = 0.07); I2 = 53%, test for overall effect Z = 1.35 (P = 0.18). An I2 value of 53% indicated substantial heterogeneity between studies therefore caution is warranted in interpreting these summary estimates. The certainty of the body of evidence by GRADE for dietary interventions was very low, based on downgrading for inconsistency, indirectness, and imprecision. Results of individual GRADE domains are outlined in Additional file 1: data 3.

Fig. 2
figure 2

Effect of dietary intervention on mean EDSS difference. Standard deviation (SD), inverse variance (IV), confidence interval (CI)

Risk of bias in individual studies

The RoB for each included study is presented in Additional file 1: data 2. The RoB ranged from low to high across 35 RCT’s. Overall, nine studies had a RoB [44, 52, 62, 65, 68, 71, 73, 79, 88], 11 had some [46, 50, 51, 60, 67, 69, 75, 76, 83, 84, 90] and 15 had a high RoB [38, 43, 45, 5356, 59, 61, 63, 66, 74, 86, 89, 91]. The majority (97%) had a low RoB with selection of the reported results [4346, 48, 50, 51, 5356, 59, 6163, 6676, 83, 86, 88, 89, 91].Thirty-seven percent of studies had some or a high RoB due to the effect of assignment to intervention [38, 43, 46, 50, 53, 55, 59, 61, 63, 66, 89, 90, 91] and 34% of studies had some or a high RoB due to missing outcome data [43, 45, 55, 59, 60, 66, 67, 74, 89, 91].

The RoB in nonrandomised studies of interventions ranged from low to serious. Overall, one study had a low RoB [77], five had a moderate [42, 57, 58, 77, 85] and one had a serious RoB due to intervention classification [49]. All (100%) of studies had a low RoB due to confounding and selective reporting of results. However, 57% (n = 4) [49, 57, 58, 82] studies had a moderate RoB due to measurement of the outcome, and 42% (n = 3) [58, 82, 85] studies had a moderate RoB in the selection of participants.

Based on the NOS, four of the 13-cohort/case control studies were of good quality [41, 78, 87, 93], three were of satisfactory quality [39, 64, 65], and the remaining six were unsatisfactory [37, 52, 79, 80, 83, 92]. Most studies with unsatisfactory scores did not follow appropriate recruitment methods, assessment of outcomes, and/or adequate follow-up of cohorts. The two cross-sectional studies were of satisfactory quality [47, 48]. None of the studies were appraised as having very good quality, mainly because the selected participants were not representative of the exposed cohort and a poor description of outcome assessments. This was possibly due to the nature of the study design and the inability to blind the participants.

Discussion

To the best of our knowledge, this is the first review to systematically explore the effectiveness of lifestyle self-management strategies and/or intervention(s) that influence the health and well-being of plwMS, using a common metric of success. For each of the six self-management dimensions (physical activity and exercise; coping, depression, stress, and emotional management; diet, lifestyle, and well-being; fatigue management; and symptom management), varying impacts on participants’ self-reported QOL and objective measures of disability were reported. Qualitative syntheses of results initially appear promising and are reflected in previous work that has explored lifestyle self-management in MS cohorts [11,12,13]. However, the meta-analysis did not identify any statistically significant effects, which may be a result of the heterogeneity between the included studies and/or due to the small number of studies being meta-analysed [94]. Further to this, the review found that the evidence base for high-quality randomised controlled trials (n = 9) designed to improve QOL and reduce objective measures of disability was limited. Therefore, the overall ability to answer the research question: What are the elements of lifestyle self-management strategies and/or interventions that improve the QOL of plwMS patients, was challenged.

The first key finding was that the eight studies that incorporated multicomponent self-management interventions (i.e. lifestyle and well-being programs) [76,77,78,79,80,81,82,83] all reported a significant improvement in self-reported QOL. A reasonable explanation for this finding can be provided through their respective self-management programs that assist participants in gaining skills to control physical symptoms, identify coping strategies to deal with emotional challenges, conserve energy to deal with fatigue, and provide education regarding appropriate dietary choices. As lifestyle is multidimensional, these results were somewhat expected, as the interventions were able to address multiple aspects of care to improve overall QOL. This is consistent with the findings of other studies that have explored multicomponent interventions to improve QOL in chronic disease [95]. Furthermore, these studies used a range of teaching modalities, which have been found to reinforce knowledge comprehension and ensure individual learning styles are addressed [96]. This may have further contributed to the positive improvements in QOL, as self-reported by the participants. Future research should explore the best combinations of self-management dimensions with the greatest effect on improving QOL.

A second key finding was the positive effect of coping, depression, stress, mental health, and/or emotional management strategies in improving the QOL of plwMS [58,59,60,61,62,63,64,67]. This result has been described in the literature for other chronic diseases [97,98,99]. It is well established that people with chronic illness find it difficult to cope with the physical and/or emotional challenges of their condition [100]. Furthermore, these challenges have been previously reported to significantly affect QOL due to the impact on one’s ability to work, participate in leisure activities, and engage in social functions. Therefore, it was anticipated that a program equipped with plwMS with the confidence to self-manage the emotions of their diagnosis and develop coping strategies to deal with stress would reduce the burden of their condition and improve QOL. This finding is consistent with a previous systematic review exploring the effectiveness of self-management to improve depression, anxiety and QOL among plwMS [11]. As reported by Kidd et al. effective interventions included principles of the cognitive behavioural theory, in 30% of the studies. One meta-analysis reported that incorporating cognitive behavioural theory in interventions for plwMS is effective in improving QOL domains [11, 101]. The present review has validated this finding.

Fatigue is one of the most common symptoms and burdens approximately 75% of plwMS [102]. It is well established that fatigue is independently associated with impaired QOL in MS, suggesting that recognising and treating fatigue can potentially improve overall life quality [102, 103]. Therefore, interventions encapsulating self-management of fatigue would significantly improve QOL. However, this assumption was only reflected in four out of the seven studies exploring fatigue self-management with interventions ranging from six weeks to three years. One possible reason for these inconsistencies is that behavioural change takes time and, therefore, longer term follow up of two years or more may be required to observe a consistent and significance change in QOL. This was observed in a similar review of fatigue self-management in patients with chronic health conditions such as chronic fatigue syndrome, rheumatoid arthritis, and cancer, suggesting longer follow up times are needed [104].

The pooled estimate of the effect of dietary interventions among the five studies indicated no significant reduction in disability measures reported through the EDSS. According to Higgins et al. [105] the I2 value indicated substantial heterogeneity; therefore, the results should be interpreted with caution. This may be attributed to the substantial variation in the study design, intervention, and methodology among the six included studies. Due to the scarcity of evidence confirming particular food(s) or dietary patterns that are effective in reducing the symptom burden of MS, it was anticipated that no significant effect would be found in this review. These results are consistent with a 2020 Cochrane review, which indicated that there is an insufficient level of evidence to determine whether dietary supplementation and certain dietary patterns have an impact on MS-related outcomes [106]. However, a promising effect of diet on improving QOL domains was observed in these studies. Despite this, high-quality, food-focused clinical trials exploring dietary interventions as a self-management strategy are still warranted.

The reported effect of physical activity on outcome measures was largely inconsistent across 21 studies. In total, 50% (n = 9/18) of studies reported a significant improvement in QOL, and only 38% (n = 3/8) of studies reported a significant improvement in disability measures, such as decreased EDSS score, lesion count, and annualised relapse rate. Previous studies have found that plwMS who participate in regular physical activity report higher QOL [107]. Therefore, if MS participants in these studies were already actively partaking in planned physical activity and exercise, it was anticipated that a ceiling effect was observed [108]. That is, participants were involved in regular physical activity as a self-management strategy prior to the intervention; therefore, there was little opportunity for improvements in QOL to be observed post intervention [108]. Again, future reviews should aim to quantitatively synthesise homogenous results via a meta-analysis to comment on overall effectiveness.

Despite these findings, it is important to note the limitations of this review. Multiple scientific databases were searched using specific terms and truncations. However, the review may have excluded potential relevant studies due to the subjectivity of what constitutes self-management.” Additionally, excluding non-English studies, case studies, review articles, feasibility and pilot studies, protocols and grey literature, conference abstracts, editorials, and monographs may mean that the analysis in the review is limited.

Despite rigorous inclusion criteria, the heterogeneity of the included studies was still evident, therefore, a qualitative synthesis of the included studies was conducted. Several studies recruited only female participants or only individuals with a relapsing–remitting MS phenotype. Multiple QOL questionnaires that differed in their reported domains of QOL were included, making cross-study comparisons difficult. Moreover, a number of studies did not report sufficient outcome and summary measures detailed to their intervention; therefore, quantitative analysis through a meta-analysis was not possible for a majority of the included studies and their respective self-management dimensions. This prevents a definitive answer to the PICO question, without further research.

Conclusion

Multicomponent self-management interventions that incorporate coping, stress, depression, emotional management, multimodal delivery methods, and cognitive behavioural theory principals were common elements of self-management interventions that improved the QOL of plwMS. Dietary intervention had no statistically significant overall effect on reducing MS disability, (P = 0.18). The overall effect of physical activity on these measures was inconsistent.

This review revealed a significant gap in the literature, warranting high-quality, large-scale experimental, and observational studies that address the research question. Therefore, these results should be interpreted with caution, and care should be taken in clinical applications. Heterogeneity continues to limit the ability to pool the effects from a large number of studies. A future review addressing this as evidence-based growth is warranted. The question of the best combination of lifestyle self-management dimensions to improve QOL remains. Therefore, future studies should not only address one dimension, but also explore different combinations of plwMS.

Availability of data and materials

The datasets analysed during the current review are available from the corresponding author on reasonable request.

Abbreviations

MS:

Multiple sclerosis

DMT:

Disease-modifying therapy

plwMS:

People living with MS

QOL:

Quality of life

EDSS:

Expanded disability status scale

PDDS:

Patient-determined disease steps

RoB:

Risk of bias

RCT:

Randomised control trial

NOS:

Newcastle–Ottawa scale

NHMRC:

National health and medical research council

References

  1. National Multiple Sclerosis Society [Internet]. MS Symptoms. 2021. [Cited 7 July 2021]. Available at: https://www.nationalmssociety.org/Symptoms-Diagnosis/MS-Symptoms

  2. Robertson D, Moreo N. Disease-modifying therapies in multiple sclerosis: overview and treatment considerations. Fed Pract [Internet]. 2016;33(6):28–34.

    PubMed  Google Scholar 

  3. Boeije HR, Duijnstee MS, Grypdonck MH, Pool A. Encountering the downward phase: biographical work in people with multiple sclerosis living at home. Soc Sci Med [Internet]. 2002;55(6):881–93.

    Article  PubMed  Google Scholar 

  4. Grady PA, Gough LL. Self-management: a comprehensive approach to management of chronic conditions. Am J Public Health [Internet]. 2014;104(8):25–31.

    Article  Google Scholar 

  5. Fraser R, Ehde D, Amtmann D, et al. Self-management for people with multiple sclerosis: report from the first international consensus conference. Int J MS Care [Internet]. 2010;15(2):99–106.

    Article  Google Scholar 

  6. Wagner EH, Austin BT, Davis C, Hindmarsh M, Schaefer J, Bonomi A. Improving chronic illness care: translating evidence into action. Health Aff [Internet]. 2001;20(6):64–78.

    Article  CAS  Google Scholar 

  7. Harris MF, Willians AM, Dennis SM, Zwar NA, Powell DG. Chronic disease self management: implementation with and within Australian general practice. MJA [Internet]. 2008;189:10.

    Google Scholar 

  8. Dennis SM, Zwar NA, Griffiths R, Roland M, Hasan I, Powell Davies G, et al. Chronic disease self management in primary care: from evidence to policy. MJA [Internet]. 2008;188:8.

    Google Scholar 

  9. Australian Health Ministers’ Advisory Council [Internet]. National strategic framework for chronic conditions. Canberra, ACT: Australian Government Canberra; 2017 [cited 2021 Feb 2]. Available from: https://www.health.gov.au/sites/default/files/documents/2019/09/national- strategic-framework-for-chronic-conditions.pdf

  10. Clark NM, et al. Self- management of chronic disease by older adults: a review and questions for research. Sage J. 1991;3(1):3–27.

    Google Scholar 

  11. Kidd T, et al. A systematic review of the effectiveness of self-management interventions in people with multiple sclerosis at improving depression, anxiety and quality of life. PLoS ONE [Internet]. 2017;12(10):e0185931.

    Article  PubMed  Google Scholar 

  12. Rae-Grant AD, Turner AP, Sloan A, Miller D, Hunziker J, Haselkorn JK. Self-management in neurological disorders: systematic review of the literature and potential interventions in multiple sclerosis care. J Rehabil Res Dev [Internet]. 2011;48:1087–100.

    Article  PubMed  Google Scholar 

  13. Yamaguchi S, Yatsushiro R. Significance and potential of self-management research for HTLV-1 associated myelopathy: review of self-management for people with multiple sclerosis. J Rural Med [Internet]. 2019;14(1):7–25.

    Article  PubMed  Google Scholar 

  14. Higginson IJ, Carr AJ. Measuring quality of life: using quality of life measures in the clinical setting. BMJ [Internet]. 2001;322(7297):1297–300.

    Article  CAS  PubMed  Google Scholar 

  15. Mitchell AJ, Benito-León J, González JM, Rivera-Navarro J. Quality of life and its assessment in multiple sclerosis: integrating physical and psychological components of wellbeing. Lancet Neurol [Internet]. 2005;4(9):556–66.

    Article  PubMed  Google Scholar 

  16. Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA. Cochrane Handbook for Systematic Reviews of Interventions [Internet]. 2020 [cited 2021 Feb 9]; version 6.1 Available from: www.training.cochrane.org/handbook.

  17. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffman TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ [Internet]. 2021;372(71).

  18. National Institute for Health Research. PROSPERO [Internet]. York, UK: University of York; 2016 [cited 2021 Feb 12]. Available from: https://www.crd.york.ac.uk/prospero/

  19. Stewart L, Moher D, Shekelle P. Why prospective registration of systematic reviews makes sense. Syst Rev [Internet]. 2012;1(7):1–4.

    PubMed  Google Scholar 

  20. MS Research Australia [Internet]. How is MS diagnosed? MS Research Australia, 2020 [cited 2021 Jan 28]. Available from: https://msra.org.au/news/how-is-ms-diagnosed/.

  21. MS Research Australia [Internet]. Adapting your lifestyle: A guide for people with MS/A guide for healthcare professionals. MS Research Australia; 2020 Aug [Cited 2021 Feb 28]. Available from: https://msra.org.au/modifiable-lifestyle-guide-2020/for-people-with-ms/guide/?physical_id=37161 (21)

  22. Baumstarck K, Boyer L, Boucekine M, Michel P, Pelletier J, Auquier P. Measuring the quality of life in patients with multiple sclerosis in clinical practice: a necessary challenge Mult Scler Int [Internet]. 2013;524894

  23. MS Trust [Internet]. Expanded Disability Status Scale (EDSS) MS Trust; 2020 Jan [cited 2021 Feb 4]. Available from: https://mstrust.org.uk/a-z/expanded-disability-status-scale-edss

  24. Meyer-Moock S, Feng YS, Maeurer M, Dippel FW, Kohlmann T. Systematic literature review and validity evaluation of the expanded disability status scale (EDSS) and the multiple sclerosis functional composite (MSFC) in patients with multiple sclerosis. BMC Neurol [Internet]. 2014;14:58.

    Article  PubMed  Google Scholar 

  25. Learmonth YC, Motl RW, Sandroff BM, et al. Validation of patient determined disease steps (PDDS) scale scores in persons with multiple sclerosis. BMC Neurol [Internet]. 2013;13:37.

    Article  PubMed  Google Scholar 

  26. Van Munster CEP, Uitdehaag BM. Outcome measures in clinical trials for multiple sclerosis. CNS Drugs [Internet]. 2017;31:217–36.

    Article  PubMed  Google Scholar 

  27. Rosen L, Suhami R. The art and science of study identification: a comparative analysis of two systematic reviews. BMC Med Res Methodol [Internet]. 2016;16:24.

    Article  PubMed  Google Scholar 

  28. Shea BJ, Reeves BC, Wells G, Thuku M, Hamel C, Moran J, et al. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ Res Methods Rep [Internet]. 2017;358.

  29. Higgins JPT, Thompson SG, Spiegelhalter DJ. A re-evaluation of random-effects meta-analysis. J R Stat Soc [Internet] Ser A Stat Soc. 2009;172:137–59.

    Article  PubMed  Google Scholar 

  30. Drahota A, Beller E. RevMan Calculator [Internet]. Cochrane training. [Cited 2021 June 30]. Available from; https://training.cochrane.org/resource/revman-calculator

  31. Higgins JPT, Savovic J, Page MJ, Sterne JAC. Revised Cochrane risk- of- bias tool for randomised trials (RoB 2) SHORT VERSION (CRIBSHEET) [Internet]. 2019

  32. Sterne JAC, Hernan MA, McAleenan A, Reeves BC, Higgins JPT. Chapter 25: Assessing risk of bias in non- randomised study [Internet]. Cochrane Handbook for Systematic Reviews of Interventions version 6.2. 2021.

  33. Wells GA, O’Connell D, Peterson J, Welch V, Losos M, Tugwell P. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. Ottawa Hosp Res Inst [Internet]. 2021 [Cited 2021 9 August].

  34. Modesti PA, Reboldi G, Cappuccio FP, Agyemang C, Remuzzi G, et al. Panethnic differences in blood pressure in europe: a systematic review and meta-analysis. PloS One [Internet]. 2016;11(1):e0147601.

    Article  PubMed  Google Scholar 

  35. Takahashi N, Hashizume M. A systematic review of the influence of occupational organophosphate pesticides exposure on neurological impairment. BMJ Open [Internet]. 2014;4:004798.

    Google Scholar 

  36. Schünemann HJ, Higgins JPT, Vist GE, Glasziou P, Akl EA, Skoetz N, et al. Chapter 14: Completing ‘Summary of findings’ tables and grading the certainty of the evidence. In: Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (editors). Cochrane Handbook for Systematic Reviews of Interventions version 6.3 (updated February 2022). Cochrane, 2022. Available from www.training.cochrane.org/handbook.

  37. Beatus J, O’Neill JK, Townsend T, Robrecht K. The effect of a one-week retreat on self-esteem, quality of life, and functional ability for persons with multiple sclerosis. Neurol Rep [Internet]. 2002;26(3):154–9.

    Article  Google Scholar 

  38. Carter A, Daley A, Humphreys L, Snowdon N, Woodroofe N, Petty J, et al. Pragmatic intervention for increasing self-directed exercise behaviour and improving important health outcomes in people with multiple sclerosis: a randomised controlled trial. Mult Scler [Internet]. 2014;20(8):1112–22.

    Article  CAS  PubMed  Google Scholar 

  39. D’Hooghe MB, Feys P, Deltour S, Van de Putte I, De Meue J, Kos D, et al. Impact of a 5-day expedition to machu picchu on persons with multiple sclerosis. Mult Scler Int [Internet]. 2014;2014: 761210.

    PubMed  Google Scholar 

  40. Fasczewski KS, Gill DL, Rothberger SM. Physical activity motivation and benefits in people with multiple sclerosis. Disabil Rehabil [Internet]. 2018;40(13):1517–23.

    Article  PubMed  Google Scholar 

  41. Fasczewski KS, Garner LM, Clark LA, Michels HS, Migliarese SJ. Medical Therapeutic Yoga for multiple sclerosis: examining self-efficacy for physical activity, motivation for physical activity, and quality of life outcomes. Disabil Rehabil [Internet]. 2020:1–8.

  42. Feys P, Tytgat K, Gijbels D, De Groote L, Baert I, Van Asch P. Effects of an 1-day education program on physical functioning, activity and quality of life in community living persons with multiple sclerosis. NeuroRehabilitation [Internet]. 2013;33(3):439–48.

    Article  PubMed  Google Scholar 

  43. Flachenecker P, Bures AK, Gawlik A, Weiland AC, Kuld S, Gusowski K, et al. Efficacy of an internet-based program to promote physical activity and exercise after inpatient rehabilitation in persons with multiple sclerosis: a randomized, single-blind, controlled study. Int J Environ Res Public Health [Internet]. 2020;17(12):4544.

    Article  PubMed  Google Scholar 

  44. Khan F, Pallant JF, Brand C, Kilpatrick TJ, Khan F, Pallant JF, et al. Effectiveness of rehabilitation intervention in persons with multiple sclerosis: a randomised controlled trial. J Neurol Neurosurg Psychiatry [Internet]. 2008;79(11):1230–5.

    Article  CAS  PubMed  Google Scholar 

  45. Kjølhede T, Siemonsen S, Wenzel D, Stellmann JP, Ringgaard S, Pedersen BG, et al. Can resistance training impact MRI outcomes in relapsing-remitting multiple sclerosis? Mult Scler [Internet]. 2018;24(10):1356–65.

    Article  PubMed  Google Scholar 

  46. Langeskov-Christensen M, Grøndahl Hvid L, Nygaard MKE, Ringgaard S, Jensen HB, Nielsen HH, et al. Efficacy of high-intensity aerobic exercise on brain mri measures in multiple sclerosis. Neurology [Internet]. 2021;96(2):e203–13.

    Article  CAS  PubMed  Google Scholar 

  47. Motl RW, McAuley E, Snook EM. Physical activity and quality of life in multiple sclerosis: possible roles of social support, self-efficacy, and functional limitations. Rehabil Psychol [Internet]. 2007;52(2):143–51.

    Article  Google Scholar 

  48. Motl RW, McAuley E. Pathways between physical activity and quality of life in adults with multiple sclerosis. Health Psychol [Internet]. 2009;28(6):682–9.

    Article  PubMed  Google Scholar 

  49. Motl RW, McAuley E, Wynn D, Vollmer T. Lifestyle physical activity and walking impairment over time in relapsing-remitting multiple sclerosis: results from a panel study. Am J Phys Med Rehabil [Internet]. 2011;90(5):372–9.

    Article  PubMed  Google Scholar 

  50. Mutluay FK, Demir R, Ozyilmaz S, Caglar AT, Altintas A, Gurses HN. Breathing-enhanced upper extremity exercises for patients with multiple sclerosis. Clin Rehabil [Internet]. 2007;21(7):595–602.

    Article  CAS  PubMed  Google Scholar 

  51. Petjan JH, Gappmaier E, White AT, Spencer MK, Mino L, Hicks RW. Impact of aerobic training on fitness and quality of life in multiple sclerosis. Ann Neurol [Internet]. 1996;39:432–41.

    Article  Google Scholar 

  52. Pilutti LA, Dlugonski D, Sandroff BM, Klaren R, Motl RW. Randomized controlled trial of a behavioral intervention targeting symptoms and physical activity in multiple sclerosis. Mult Scler [Internet]. 2014;20(5):594–601.

    Article  CAS  PubMed  Google Scholar 

  53. Oken BS, Kishiyama S, Zajdel D, Bourdette MD, Carlsen AB, Haas DC. Randomised controlled trial of yoga and exercise in multiple sclerosis. Neurology [Internet]. 2004;62:2058–64.

    Article  CAS  PubMed  Google Scholar 

  54. Sangelaji B, Nabavi SM, Estebsari F, Banshi MR, Rashidian H, Jamshidi E, et al. Effect of combination exercise therapy on walking distance, postural balance, fatigue and quality of life in multiple sclerosis patients: a clinical trial study. Iran Red Crescent Med J [Internet]. 2014;16(6): e17173.

    PubMed  Google Scholar 

  55. Savšek L, Stergar T, Strojnik V, Ihan A, Koren A, Špiclin Ž, et al. Impact of aerobic exercise on clinical and magnetic resonance imaging biomarkers in persons with multiple sclerosis: an exploratory randomized controlled trial. J Rehabil Med [Internet]. 2021;53(4):jrm00178.

    Article  PubMed  Google Scholar 

  56. Sutherland G, Andersen MB, Stoove MA. Can aerobic exercise training affect health- realted quality of life for people with multiple sclerosis? J Sport Exerc Psych [Internet]. 2001;23:122–35.

    Article  Google Scholar 

  57. Vasudevan S, Devulapally S, Chirravuri K, Elangovan V, Kesavan N. Personalized yoga therapy for multiple sclerosis: effect on symptom management and quality of life. Int J Yoga Therap [Internet]. 2020.

  58. Abolghasemi A, Farhand S, Taherifard M, Kiamarsi A, Saharkhix- AA. The effect of supportive expressive therapy on hope and quality of life in patients with MS. Psych Psycho [Internet]. 2016;4:20–7.

    Google Scholar 

  59. Besharat M, Nabavi SM, Geranmayepour S, Morsali D, Haghani S. Mindfulness- based stress reduction program: the effect of a novel psycho- interventional method on quality of life, mental health and self- efficacy in female patients with multiple sclerosis. A randomised controlled trial. J Biol [Internet]. 2017;6(11):211–5.

    Google Scholar 

  60. Ehde DM, Elzea JL, Verrall AM, Gibbons LE, Smith AE, Amtmann D. Efficacy of a telephone-delivered self-management intervention for persons with multiple sclerosis: a randomized controlled trial with a one-year follow-up. Arch Phys Med Rehabil [Internet]. 2015;96(11):1945–58.

    Article  PubMed  Google Scholar 

  61. Grossman P, Kappos L, Gensicke H, D’Souza M, Mohr DC, Penner LK. MS quality of life, depression and fatigue improve after mindfulness training. Neurology [Internet]. 2010;75(13):1141–9.

    Article  CAS  PubMed  Google Scholar 

  62. Graziano F, Calandri E, Borghi M, Bonino S. The effects of a group-based cognitive behavioral therapy on people with multiple sclerosis: a randomized controlled trial. Clin Rehabil [Internet]. 2014;28(3):264–74.

    Article  PubMed  Google Scholar 

  63. Hart S, Fonareva I, Merluzzi N, Mohr D. Treatment for depression and its relationship to improvement in quality of life and psychological well-being in multiple sclerosis patients. Qual Life Res [Internet]. 2005;14:695–703.

    Article  PubMed  Google Scholar 

  64. Jongen PJ, Ruimschotel R, Heerings M, Hussaarts A, Duyverman L, van der Zande A, et al. Improved self-efficacy in persons with relapsing remitting multiple sclerosis after an intensive social cognitive wellness program with participation of support partners: a 6-months observational study. Health Qual Life Outcomes [Internet]. 2014;12(1):40.

    Article  PubMed  Google Scholar 

  65. Jongen PJ, Heerings M, Ruimschotel R, Hussaarts A, Duyverman L, van der Zande A, et al. Intensive social cognitive treatment (can do treatment) with participation of support partners in persons with relapsing remitting multiple sclerosis: observation of improved self-efficacy, quality of life, anxiety and depression 1 year later. BMC Res Notes [Internet]. 2016;9:375.

    Article  PubMed  Google Scholar 

  66. Jongen PJ, van Mastrigt GA, Heerings M, Visser LH, Ruimschotel RP, Hussaarts A, et al. Effect of an intensive 3-day social cognitive treatment (can do treatment) on control self-efficacy in patients with relapsing remitting multiple sclerosis and low disability: a single-centre randomized controlled trial. PLoS One [Internet]. 2019;14(10):e0223482.

    Article  CAS  PubMed  Google Scholar 

  67. Lincoln NB, Yuill F, Holmes J, Drummond AE, Constantinescu CS, Armstrong S, et al. Evaluation of an adjustment group for people with multiple sclerosis and low mood: a randomized controlled trial. Mult Scler [Internet]. 2011;17(10):1250–7.

    Article  PubMed  Google Scholar 

  68. Aivo J, Lindsrom BM, Soilu-Hanninen M. A randomised, double- blind, placebo- controlled trial with vitamin D3 in MS: subgroup analysis of patients with baseline disease activity despite interferon treatment. MS Int [Internet]. 2012;2012:802796.

    CAS  Google Scholar 

  69. Ashtari F, Toghianifar N, Zarkesh-Esfahani SH, Mansourian M. High dose Vitamin D intake and quality of life in relapsing-remitting multiple sclerosis: a randomized, double-blind, placebo-controlled clinical trial. Neurol Res [Internet]. 2016;38(10):888–92.

    Article  CAS  PubMed  Google Scholar 

  70. Bitarafan S, Saboor-Yaraghi A, Sahraian MA, Nafissi S, Togha M, Beladi Moghadam N, et al. Impact of vitamin A Supplementation on disease progression in patients with multiple sclerosis. Arch Iran Med [Internet]. 2015;18(7):435–40.

    PubMed  Google Scholar 

  71. Kampman MT, Steffensen LH, Mellgren SI, Jørgensen L. Effect of vitamin D3 supplementation on relapses, disease progression, and measures of function in persons with multiple sclerosis: exploratory outcomes from a double-blind randomised controlled trial. Mult Scler [Internet]. 2012;18(8):1144–51.

    Article  PubMed  Google Scholar 

  72. Kouchaki E, Tamtaji Salami M, Bahmani F, Daneshvar Kakhaki R, Akbari E, Tajabadi-Ebrahimi M, et al. Clinical and metabolic response to probiotic supplementation in patients with multiple sclerosis: a randomized, double-blind, placebo-controlled trial. Clin Nutr [Internet]. 2017;36(5):1245–9.

    Article  CAS  PubMed  Google Scholar 

  73. Torkildsen O, Wergeland S, Bakke S, Beiske AG, Bjerve KS, Hovdal H, et al. ω-3 fatty acid treatment in multiple sclerosis (OFAMS Study): a randomized, double-blind, placebo-controlled trial. Arch Neurol [Internet]. 2012;69(8):1044–51.

    PubMed  Google Scholar 

  74. Weinstock-Guttman B, Baier M, Park Y, Feichter J, Lee-Kwen P, Gallagher E, et al. Low fat dietary intervention with omega-3 fatty acid supplementation in multiple sclerosis patients. Prostaglandins Leukot Essent Fatty Acids [Internet]. 2005;73(5):397–404.

    Article  CAS  PubMed  Google Scholar 

  75. Zandi-Esfahan S, Fazeli M, Shaygannejad V, Hasheminia J, Badihian S, Aghayerashti M, et al. Evaluating the effect of adding fish oil to Fingolimod on TNF-α, IL1β, IL6, and IFN-γ in patients with relapsing-remitting multiple sclerosis: a double-blind randomized placebo-controlled trial. Clin Neurol Neurosurg [Internet]. 2017;163:173–8.

    Article  PubMed  Google Scholar 

  76. Ennis M, Thain J, Boggild M, Baker GA, Young CA. A randomized controlled trial of a health promotion education programme for people with multiple sclerosis. Clin Rehabil [Internet]. 2006;20(9):783–92.

    Article  CAS  PubMed  Google Scholar 

  77. Feicke J, Spörhase U, Köhler J, Busch C, Wirtz M. A multicenter, prospective, quasi-experimental evaluation study of a patient education program to foster multiple sclerosis self-management competencies. Patient Educ Couns [Internet]. 2014;97(3):361–9.

    Article  PubMed  Google Scholar 

  78. Hadgkiss EJ, Jelinek GA, Weiland TJ, Rumbold G, Mackinlay CA, Gutbrod S, et al. Health-related quality of life outcomes at 1 and 5 years after a residential retreat promoting lifestyle modification for people with multiple sclerosis. Neurol Sci [Internet]. 2013;34(2):187–95.

    Article  PubMed  Google Scholar 

  79. Li MP, Jelinek GA, Weiland TJ, Mackinlay CA, Dye S, Gawler I. Effect of a residential retreat promoting lifestyle modifications on health-related quality of life in people with multiple sclerosis. Qual Prim Care [Internet]. 2010;18(6):379–89.

    PubMed  Google Scholar 

  80. Marck CH, De Livera AM, Brown CR, Neate SL, Taylor KL, Weiland TJ, et al. Health outcomes and adherence to a healthy lifestyle after a multimodal intervention in people with multiple sclerosis: three year follow-up. PLoS One [Internet]. 2018;13(5): e0197759.

    Article  PubMed  Google Scholar 

  81. Ng A, Kennedy P, Hutchinson B, Ingram A, Vondrell S, Goodman T, et al. Self-efficacy and health status improve after a wellness program in persons with multiple sclerosis. Disabil Rehabil [Internet]. 2013;35(12):1039–44.

    Article  PubMed  Google Scholar 

  82. Sahebalzamani M, Zamiri M, Rashvand F. The effects of self-care training on quality of life in patients with multiple sclerosis. Iran J Nurs Midwifery Res [Internet]. 2012;17(1):7–11.

    PubMed  Google Scholar 

  83. Stuifbergen AK, Becker H, Blozis S, Timmerman G, Kullberg V. A randomized clinical trial of a wellness intervention for women with multiple sclerosis. Arch Phys Med Rehabil [Internet]. 2003;84(4):467–76.

    Article  PubMed  Google Scholar 

  84. Finlayson M, Preissner K, Cho C, Plow M. Randomized trial of a teleconference-delivered fatigue management program for people with multiple sclerosis. Mult Scler [Internet]. 2011;17(9):1130–40.

    Article  PubMed  Google Scholar 

  85. Mathiowetz V, Matuska KM, Murphy ME. Efficacy of an energy conservation course for persons with multiple sclerosis. Arch Phys Med Rehabil [Internet]. 2001;82(4):449–56.

    Article  CAS  PubMed  Google Scholar 

  86. Mathiowetz VG, Finlayson ML, Matuska KM, Chen HY, Luo P. Randomized controlled trial of an energy conservation course for persons with multiple sclerosis. Mult Scler [Internet]. 2005;11(5):592–601.

    Article  PubMed  Google Scholar 

  87. Mulligan H, Wilkinson A, Barclay A, Whiting H, Heynike C, Snowdon J. Evaluation of a fatigue self-management program for people with multiple sclerosis. Int J MS Care [Internet]. 2016;18(3):116–21.

    Article  PubMed  Google Scholar 

  88. Plow M, Finlayson M, Liu J, Motl RW, Bethoux F, Sattar A. Randomized controlled trial of a telephone-delivered physical activity and fatigue self-management interventions in adults with multiple sclerosis. Arch Phys Med Rehabil [Internet]. 2019;100(11):2006–14.

    Article  PubMed  Google Scholar 

  89. Thomas PW, Thomas S, Kersten P, Jones R, Slingsby V, Nock A, et al. One year follow-up of a pragmatic multi-centre randomised controlled trial of a group-based fatigue management programme (FACETS) for people with multiple sclerosis. BMC Neurol [Internet]. 2014;14(1):109.

    Article  PubMed  Google Scholar 

  90. Thomas S, Thomas PW, Kersten P, et al. A pragmatic parallel arm multi-centre randomised controlled trial to assess the effectiveness and costeffectiveness of a group-based fatigue management programme (FACETS) for people with multiple sclerosis. J Neurol Neurosurg Psychiatry [Internet]. 2013;84:1092–9.

    Article  PubMed  Google Scholar 

  91. Miller DM, Moore SM, Fox RJ, Atreja A, Fu AZ, Lee JC, et al. Web-based self-management for patients with multiple sclerosis: a practical, randomized trial. Telemed J E Health [Internet]. 2011;17(1):5–13.

    Article  PubMed  Google Scholar 

  92. Seifi K, Moghaddam HE. The effectiveness of self-care program on the life quality of patients with multiple sclerosis in 2015. J Natl Med Assoc [Internet]. 2018;110(1):65–72.

    PubMed  Google Scholar 

  93. Stockl KM, Shin JS, Gong S, Harada ASM, Solow BK, Lew HC. Improving patient self-management of multiple sclerosis through a disease therapy management program. Am J Manag Care [Internet]. 2010;16(2):139–44.

    PubMed  Google Scholar 

  94. Von Hippel PT. The heterogeneity statistic I2 can be biased in small meta-analyses. BMC Med Res Methodol [Internet]. 2015;15:35.

    Article  Google Scholar 

  95. Senchak JJ, Fang CYX, Bauman JR. Interventions to improve quality of life (QOL) and/or mood in patients with head and neck cancer (HNC): a review of the evidence. Cancers Head Neck [Internet]. 2019;4:2.

    Article  PubMed  Google Scholar 

  96. Lynch K, Star JR. Teachers' views about multiple strategies in middle and high school mathematics: perceived advantages, disadvantages, and reported instructional practices. Math Think Learn [Internet]. 2013.

  97. Baumstarck K, Chinot O, Tabouret E, et al. Coping strategies and quality of life: a longitudinal study of high-grade glioma patient-caregiver dyads. Health Qual Life Outcomes [Internet]. 2018;16:157.

    Article  PubMed  Google Scholar 

  98. Brunault P, Champagne AL, Huguet G, Suzanne I, Senon JL, Body G, et al. Major depressive disorder, personality disorders, and coping strategies are independent risk factors for lower quality of life in non-metastatic breast cancer patients. Psychooncol [Internet]. 2016;25:513–20.

    Article  Google Scholar 

  99. D’Onofrio G, Simeoni M, Rizza P, Caroleo M, Capria M, Mazzitello G, et al. Quality of life, clinical outcome, personality and coping in chronic hemodialysis patients. Ren Fail [Internet]. 2017;39:45–53.

    Article  PubMed  Google Scholar 

  100. Liddy C, Blazkho V, Mill K. Challenges of self-management when living with multiple chronic conditions: systematic review of the qualitative literature. Can Fam Phys [Internet]. 2014;60(12):1123–33.

    Google Scholar 

  101. Hind D, Cotter J, Thake A, Bradburn M, Cooper C, Isaac C, et al. Cognitive behavioural therapy for the treatment of depression in people with multiple sclerosis: a systematic review and meta-analysis. BMC Psychiatry [Internet]. 2014;14(1):5.

    Article  PubMed  Google Scholar 

  102. Braley TJ, Chervin RD. Fatigue in multiple sclerosis: mechanisms, evaluation, and treatment. Sleep [Internet]. 2010;33(8):1061–7.

    Article  PubMed  Google Scholar 

  103. Janardhan V, Bakshi R. Quality of life in patients with multiple sclerosis: the impact of fatigue and depression. J Neurol Sci [Internet]. 2002;205(1):51–8.

    Article  PubMed  Google Scholar 

  104. Kim S, Xu Y, Dore K, Gewurtz R, Lariviere N, Letts L. Fatigue self-management led by occupational therapists and/or physiotherapists for chronic conditions: a systematic review and meta-analysis. Chronic Illness [Internet]. 2021.

  105. Higgins JPT, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta analysis. BMJ [Internet]. 2003;327:557.

    Article  PubMed  Google Scholar 

  106. Parks NE, Jackson-Tarlton CS, Vacchi L, Merdad R, Johnston BC. Dietary interventions for multiple sclerosis-related outcomes. Cochrane Datab Syst Rev [Internet]. 2020;5

  107. Motl RW, McAuley E, Snook EM, Gliottoni RC. Physical activity and quality of life in multiple sclerosis: intermediary roles of disability, fatigue, mood, pain, self-efficacy and social support. Psychol Health Med [Internet]. 2009;14(1):111–24.

    Article  PubMed  Google Scholar 

  108. Salkind, NJ. Ceiling effect SAGE [Internet]. 2010 [Cited 2021 Sep 5].

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Acknowledgements

The authors would like to acknowledge Emiliana Saffioti for her contribution to the review and screening process.

Funding

This research received no specific grants from any funding agency, commercial, or not-for-profit sectors.

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The authors’ responsibilities were as follows: OW was involved in the development of the research question, review process, writing, and final content of the manuscript; YP was involved in the review process, writing, and final content of the manuscript. Both authors read and approved the final manuscript.

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Correspondence to Yasmine C. Probst.

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Competing interests

YP has received research grants from Multiple Sclerosis Research Australia, a fellowship from Multiple Sclerosis Australia, is a reviewer for a range of multiple sclerosis scientific journals, and has received honoraria from Multiple Sclerosis Research Australia. YP is also a person living with multiple sclerosis. OW declares no conflict of interest.

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Supplementary Information

Additional file 1

: Data 1. Database search strategy and search results. Data 2. A. Cochrane risk of bias assessment for included randomised controlled trials (n = 35). B. Newcastle Ottawa risk of bias scale (NOS) for case control and cohort studies (n = 13). C. Newcastle Ottawa risk of bias scale (NOS) adapted for cross- sectional studies (n = 2) D. Risk of bias in non- randomised studies of interventions (ROBINS-I) (n = 7). Data 3. GRADE for assessing the certainty of the body of evidence.

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Wills, O.C., Probst, Y.C. Understanding lifestyle self-management regimens that improve the life quality of people living with multiple sclerosis: a systematic review and meta-analysis. Health Qual Life Outcomes 20, 153 (2022). https://doi.org/10.1186/s12955-022-02046-1

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Keywords

  • Multiple sclerosis
  • Self-management
  • Quality of life
  • Self-care
  • Lifestyle