Эффективность Leder Falls, онлайновая программа группового саморегулирования для людей с множественным склерозом: протокол случайного контролируемого испытания.

STRENGTHS AND LIMITATIONS OF THIS STUDY

This study protocol describes an online group-based, self-management fall prevention intervention featuring group dialogue and individual action plans for both ambulatory and non-ambulatory people with multiple sclerosis (PwMS).

The comprehensive process evaluation will yield understanding of implementation and the mechanisms of impact for the intervention.

The health economic evaluation will provide unique knowledge as no study has evaluated the cost-effectiveness of fall prevention programmes in PwMS.

The online delivery of the intervention may exclude PwMS with low computer/technical skills and low socioeconomic status.

Introduction

Multiple sclerosis (MS) is a chronic inflammatory, demyelinating and neurodegenerative disease that typically is progressive in nature. 1 Several symptoms of MS are known fall risk factors, including impaired balance, gait and cognition. 2 3 In people with MS (PwMS), approximately 56% experience a fall within 3 months. 4 Those PwMS who have experienced a fall in the past year have an 82% probability of falling again within 6 months and a 56% probability of an injurious fall. 5 Falls among PwMS are associated with fear of falling, low health-related quality of life and injuries. 3 6 Because PwMS frequently experience injurious falls, 7 the socioeconomic costs for both PwMS and society are potentially high. Surprisingly, there are no studies on costs related to falls in PwMS. However, existing research describing the cost of falls for other patient populations with neurological problems 8 9 have suggested the high healthcare costs associated with falls among PwMS.

Despite the recognition that several MS symptoms influences fall risk, 2 3 most fall prevention interventions for PwMS only address physical impairments. There is a major gap in existing evidence regarding behavioral and environmental influences on fall risk in PwMS. The importance of comprehensive approaches to fall prevention targeting modifiable risk factors through fall prevention programmes for PwMS has been highlighted. 10 Another major gap in MS falls research is the scarcity of studies that focus on falls among the 25% of the MS population who can walk only a few steps or not at all, ie, are non-ambulatory. 6 Fall prevention interventions for non-ambulatory PwMS show promising results but are rare. 11 12 Although ambulatory and non-ambulatory PwMS share the same fall risk factors, 2 13 new evidence suggests that some fall risk factors are unique to non-ambulatory PwMS. 13 Thus, fall prevention programmes for PwMS must target the unique needs and multifactorial fall risks of PwMS, with consideration that members of the target audience may be ambulatory or non-ambulatory and typically will experience fluctuations in functional status and disease over time.

To address the wide variety of fall risk factors for diverse patient populations, research has highlighted the benefits of self-management for PwMS. 10 Self-management has been defined as ‘the individual’s ability to manage the symptoms, treatment, physical and psychosocial consequences, and lifestyle changes intrinsic in living with chronic conditions’. 14 Self-management is especially important for PwMS due to the daily fluctuations in functioning and the unpredictable nature of the disease. PwMS have identified support for self-management as one of their top 10 research priorities. 15 Despite the importance of self-management, few randomised controlled trials (RCTs) have evaluated self-management fall prevention programmes for PwMS, 16 18 and none of those trials included definitions of self-management. A scoping review 19 identified that few RCTs did not favour either intervention or control groups, which displays the importance of further research.

To address the diverse influences of fall risk factors for both ambulatory and non-ambulatory PwMS, RCTs that evaluate the effectiveness of well-described self-management fall prevention interventions are needed. We have therefore used a co-design methodology and developed the online group-based fall prevention intervention Fewer Falls together with PwMS and healthcare professionals 20 21 following the Medical Research Council recommendations for complex interventions. 22 A feasibility study has been performed, 23 indicating feasible results (in manuscript). The online synchronous format was decided based on the suggestion of PwMS that online meetings would make participation in the programme possible even when energy levels are low. 21 Online programmes and applications are becoming more common, 24 25 as they can involve geographically spread participants at lower costs. 26 A thorough description of the Fewer Falls programme development process has been published. 21

Aim and research questions

This study aims to evaluate the effectiveness of the self-management fall prevention programme Fewer Falls on falls in PwMS. The hypothesis is that the fall frequency in the Fewer Falls intervention group will be lower than that in the control group.

Research questions (RQs):

RQ 1a: Is there a difference in fall frequency between the intervention group and the control group 6 months (primary endpoint) after the start of the intervention?

RQ 1b: Is there a difference in the fall frequency between the intervention group and the control group 12 months (sustainability) after the start of the intervention?

RQ 2: Are there differences in secondary outcomes between the intervention group and the control group?

RQ 3: How do process evaluation components (context, implementation and mechanisms of impact) inform the interpretation of outcomes?

RQ 4: What is the cost-effectiveness of Fewer Falls 12 months after the start of the intervention?

Methods and analysis

Design

The study will use a parallel-group RCT design with a mixed methods process evaluation as well as a health economic evaluation. The trial is registered at ClinicalTrials.gov ( NCT05789225 ), and any updates to the protocol will be registered.

This study protocol adheres to the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) guidelines for reporting intervention trials. 27

Figure 1 displays the study enrolment, intervention and assessments. The study flow chart is presented in figure 2 .

Patient and public involvement

The intervention was co-developed in close collaboration with PwMS and healthcare professionals through an iterative process. The intervention development process has been previously described, 21 PwMS representatives from the patient organisation Neuro Sweden have collaborated as project partners in all stages of the study.

Participants

The inclusion criteria for participation are self-reported diagnosis of MS; age ≥18 years; ability to walk or independently transfer from bed to chair/wheelchair with or without aids, but without assistance of another person (corresponding to ˂7.5 on the Expanded Disability Status Scale); experienced one or more falls during the last year; ability to understand and communicate in Swedish; and access to and self-rated ability to use technical devices for online meetings and falls data submission, that is, computers or tablets with internet access and mobile phones to receive and send short message service (SMS).

The statistical power calculation for the primary outcome, fall frequency, is based on data from our feasibility pilot RCT study (in manuscript). The pilot study included 45 participants, randomised into an intervention or control group. Falls were monitored weekly via SMS for 18 weeks from the start of the intervention. Data from 27 participants who at baseline reported a fall within the previous 3 months were used. Based on the findings of 2.45 falls for the intervention group (n=11) versus 3.69 in the control group (n=16) over a period of 18 weeks, we determined that a sample size of 84 participants per group is necessary to achieve adequate statistical power (0.8, alpha=0.05). 28

Because an online publication on interventions for people with chronic conditions reported a high attrition and drop-out rate, 29 we aim to recruit up to 240 participants, allowing for up to a 35% drop-out rate. The sample size is based on a Poisson distribution, which aligns with the nature of our primary outcome falls/person/year.

Study setting

Programme content is delivered by the intervention facilitator, that is, group leader via synchronous online sessions. Between sessions, participants will be asked to complete assignments in their home environment. The assignments are designed to encourage participants to practise skills learnt during the intervention, that is, to carry out their individual action plans. The participants and intervention facilitators may be located anywhere in Sweden.

Recruitment and procedures

Participants will be recruited via flyers placed in inpatient and outpatient MS and rehabilitation clinics, from social media advertisements published by Karolinska Institutet, and by the patient organisation Neuro Sweden.

The notices will include a link to a webpage with study information and an online template where interested individuals can fill in their contact information. A research assistant with training in Good Clinical Practice 30 will screen the completed templates regularly, contact potential participants by phone or e-mail (depending on PwMS’ choice of contact), and provide potential participants with information about the study. Individuals expressing interest in the study will be screened for eligibility. The informed consent process will be initiated with PwMS who meet the eligibility criteria. Specifically, eligible PwMS will be sent written information. Informed consent ( online supplemental material ) is obtained through BASS, an integrated online treatment and assessment platform. The platform is provided by the eHealth Core Facility at Karolinska Institutet, Stockholm, Sweden. Individuals providing informed consent will be included.

Baseline assessment will be supported by the use of the BASS database. The PwMS will subsequently be randomised to the intervention group or the control group using a data-generated system (Sealed Envelope Ltd. 2021). Participants will be stratified as non-ambulatory (able to walk a maximum of 5 m with assistance or not able at all) or ambulatory in a 1:1 allocation ratio of blocks of eight. Participants will be contacted by phone to inform them about group allocation.

Recruitment began in December 2023, and the expected completion of the study is January 2027. An overview of the study schedule of enrolment, allocation, intervention and assessments are presented in figure 1 .

Control

Participants allocated to the control group will receive a brochure about fall risk factors and fall prevention for PwMS in addition to their standard MS care and rehabilitation.

Intervention

The intervention group participants will receive (a) the same brochure about fall risk factors and fall prevention strategies for PwMS provided to the control group participants, (b) the opportunity to participate in the Fewer Falls programme and (c) their standard MS care and rehabilitation. The manualised Fewer Falls programme features self-management content created to enhance the participant’s ability to manage fall risks in everyday life. The intervention is considered a complex intervention 22 as it includes multiple components, behaviours, expertise and skills both by PwMS and group leaders and permits flexibility in its components. Through Fewer Falls , participants learn to (a) identify their fall risk, (b) make own action plans and follow out the planned activities, (c) be aware of their capacity in relation to expectations and demands in daily life, (d) to follow-up on the action plan and (e) know about behavioural change and how to sustain their motivation to prevent falls.

The manualised intervention consists of eight online synchronous (Zoom Video Communications) sessions: seven 2-hour sessions conducted weekly, and one 2-hour booster session conducted 4 weeks after the seventh session. The participants will receive home assignments to perform between the sessions. The assignments are designed to encourage participants to practice skills learnt during the intervention, ie, to carry out their individual action plans. Each session has the following structure: check-in, follow-up on home assignments, interactive presentation with discussions in smaller groups and/or the whole group, introduction to home assignment and check-out ( table 1 ).

The intervention is delivered to groups of approximately eight participants. A health professional (ie, a physiotherapist, occupational therapist or social worker) recruited via the researchers’ network facilitates the online synchronous group sessions. Seven group leaders will be recruited to lead one or two cycles (ie, seven sessions followed by one booster session) of the programme in concurrently ran groups. The research team recognise the importance of involving several group leaders to allow for effective assessment of programme fidelity and reduce the possibility that successful programme outcomes would be attributed to the skill set of one or two group leaders. Approximately 15 cycles of the Fewer Falls programme will be run. The group leaders will not be involved in the usual care of the participants.

The group leaders will complete an extensive online training programme before delivering Fewer Falls . This training programme will consist of asynchronous online modules. Collectively, these modules (a) describe the aim, structure, content and theoretical foundation of Fewer Falls as well as the role of the group leaders; (b) provide an overview of MS, falls and fall risk factors for PwMS; (c) orient group leaders to the Fewer Falls group leader manual; and (d) provide detailed descriptions of content and process of each programme session. Each module of the training programme ends with a quiz or a reflective question. The final module of the training programme consists of a synchronous online role-play session. In addition, the group leaders will receive instructions on how to use the digital tools used during the Fewer Falls programme.

To ensure participant adherence to the programme, the group leaders will contact participants who missed one session. If participants miss two sessions in a row, the research assistant will contact the participants.

Theoretical basis, self-management approach and pedagogical model

The leading theory informing the Fewer Falls programme content and process is the Social Cognitive Theory (SCT). 31 32 Reciprocal determinism, the central concept of SCT, refers to the dynamic and reciprocal interaction of person (with learnt experiences), environment (external social context) and behaviour (responses to stimuli to achieve goals). 32 Reciprocal determinism is applied in Fewer Falls because participants, with their respective experiences, work together to learn about fall risks and management strategies and change their behaviours to reduce their risk of falling. The SCT components of observational learning and reinforcements align well with the programme’s focus on group format; participants are learning and receiving feedback from peers. According to SCT, self-regulation refers to the ability to understand and manage own behaviours. 32 In Fewer Falls , self-regulation supporting the reduction of fall risk is fostered through using two to four action plans. Through each action plan, participants identify and explain a specific fall risk, a strategy to address that fall risk, their level of confidence in implementing that strategy, the deadline for completion and resources to support their success in implementing the strategy. Each action plan includes a section for participants to evaluate the extent to which the planned strategy was implemented. Participants are given the opportunity to report on the status of their action plans and work together to refine action plans as needed. Self-efficacy, a central component in SCT, is described as a possible mechanism by which self-management is achieved. 33 An important goal of Fewer Falls is to build participants’ falls self-efficacy.

Lorig and Holman’s operationalisation of self-management 33 was carefully applied to develop Fewer Falls . Specifically, the programme includes discussions about self-management tasks: medical management of MS symptoms that can reduce fall risk; role management, for example, PwMS’ role as partner, parent and/or employee; and emotional management with emphasis on thoughts and emotions in relation to falls. The depth and focus of the discussions are dependent on participants’ interests/priorities (eg, identified fall risks) and experiences. Lorig and Holman described six self-management skills, all of which are included in Fewer Falls to foster participants’ ability to manage fall risks in daily life: problem solving, decision making, resource utilisation, patient-provider partnership, self-tailoring and the aforementioned action planning.

SCT is complemented by the Transtheoretical Model (TTM) for behaviour change 34 as a theoretical basis for Fewer Falls . TTM is primarily applied through an interactive discussion led by the group leaders on the six phases of health behaviour change (precontemplation, contemplation, preparation, action, maintenance of behaviour and relapse) that participants may experience as they learn to use action plans to prevent falls.

To guide the online learning component of Fewer Falls, the Salmon 5 Stage Model was utilised because it was specifically developed to support e-learning in groups. 35 The model consists of five stages: (1) access and motivation, (2) online socialisation (team building), (3) information exchange, (4) knowledge construction (critical thinking) and (5) development (review and responsibility for own learning). The amount of interactivity is increased in each stage of the model. The model stresses the importance of group leaders acting as moderators/facilitators of online discussions. In the early stages of the programme, group leaders support participants’ motivation and engagement with the rest of the group. The model also recommends that facilitators taper off their leadership as the course progresses, allowing space for greater peer support and peer learning. 35 The application of the model as used in Fewer Falls is presented in figure 3 .

Data collection and outcome measures

RQ 1a, RQ 1b and RQ 2: effectiveness study

Data will be collected using the digital platform BASS database. The data collection will be blinded as the participants receive a link to the BASS database, which provides them with access to the questionnaires that are completed online. Baseline data includes the sociodemographic information (ie, age, sex, civil status, work status and educational level); disease-related characteristics (ie, MS severity, time since diagnosis, symptoms, medications and other treatments, other diagnosis and aids); formal/informal care; cognitive function (collected through the short version of the Montreal Cognitive Assessment Scale 36 ); anxiety and depression (collected through the Hospital Anxiety and Depression scale 37 ); fatigue (assessed by the Fatigue Severity Scale 38 ); health literacy (assessed via the Swedish version of the Health Literacy Survey European Questionnaire/16 item version 39 ); self-reported falls and fall related injuries in the previous 6 months; and expectations on the programme.

The primary outcome of Fewer Falls is fall frequency. 40 The primary endpoint is 6 months after the start of the intervention. However, falls will be monitored in both intervention and control groups from the start of the Fewer Falls programme until 12 months after the start of intervention, as recommended in fall prevention literature. 41 An online SMS will be sent to the intervention and control participants once a week asking, ‘Have you fallen within the last week?’ The total number of falls, number of fallers and injurious fall incidence 40 will be recorded. Participants answering ‘yes’ to the weekly SMS will receive a questionnaire through BASS that includes a series of questions about fall-related injuries. A fall is defined as ‘an unexpected event in which the participants come to rest on the ground, floor or lower level’. 41 Secondary outcomes, collected at baseline and 3, 6 and 12 months after the start of intervention, are sense of control of falls prevention assessed by the Falls Control Scale 42 (administered to all participants), a direct measure of fear of falling 43 and falls self-efficacy assessed by the Short Falls Efficacy Scale-International 44 (administered to ambulatory participants), the Spinal Cord Injury Falls Concern Scale 45 (administered to non-ambulatory participants) and a revised version of the Short Falls Efficacy Scale-International 46 (administered to all participants). The following are also administered to all participants to collect data: activity curtailment assessed by a single question, 43 perceived impact of MS assessed by the Multiple Sclerosis Impact Scale 47 and self-rated health assessed by the EuroQol-5D-5L. 48

Participants who discontinue the intervention will be contacted and asked if they are willing to continue responding to the SMS and questionnaires.

RQ 3: process evaluation

Consistent with the Medical Research Council guidelines, 22 49 the process evaluation will focus on contextual factors (eg, online delivery of the programme), implementation (the implementation process, fidelity, dose, adaptations and reach) and mechanisms of impact (participant responses to and interactions with the intervention).

Data will be collected from all group leaders before and after the training programme, after each session and after the end of the Fewer Falls programme. Data collection will include structured questions on group leader background (eg, sex, age and profession), perceived preparedness in facilitating the group and fidelity to programme manual, and semi-structured interviews. The semi-structured interviews conducted after the training programme and after the last session of the intervention will cover group leaders’ perspective on experiences of participation, contextual factors, implementation and mechanisms of impact. The interviews will be conducted face-to-face or through Zoom.

Process evaluation data will also be yielded from intervention group participants. Specifically, data will be collected from a purposively selected sample of intervention group participants (n=20–30) to represent variation in, for example, age, sex and ambulation level. Semi-structured individual interviews will be conducted by a research team member via telephone or Zoom within approximately 3, 6 and 12 months after the start of the intervention. The interviews will explore the experiences of the study participants, contextual factors and mechanisms of impact. Data from the programme platform will be collected on intervention group participants’ online activities, for example, the action plans. Participants who discontinue the intervention will be contacted and asked if they are willing to participate in a short interview to understand their reasons for not completing the programme.

RQ 4: health economic evaluation

Participants answering ‘yes’ to the weekly SMS inquiring about falls experienced in the last week will receive a questionnaire through the BASS database with questions on fall-related injuries, that is, healthcare utilisation, municipal care utilisation, sickness absence, medications, support from significant others and need for technical aids, including walking aids.

Estimations of resources needed to deliver the Fewer Falls programme will be made. Group leaders’ involvement, which includes participating in the group leader training and subsequently preparing for and delivering the Fewer Falls programme, will be the main programme expense. To estimate the monetary value of resource use, both for participants in the RCT and for resources needed to conduct the intervention, cost data will be retrieved from the cost per patient database held at the Swedish Association of local authorities and regions, regional price lists, as well as from Statistics Sweden. Data on quality-adjusted life years (QALYs) will be measured using the EQ-5D-5L at all timepoints.

Adverse events

All adverse events associated with the trial will be discussed and recorded.

Analysis

Data management and statistical methods

RQ 1a, RQ 1b and RQ 2: effectiveness study

Intention-to-treat and per-protocol analyses will be performed. Per-protocol analyses will include participants who fulfil content adherence, defined as completion of at least two action plans.

Descriptive statistics will be used to present data, for example, means, medians, frequencies, SD, quartiles and counts. Drop-out analyses of baseline characteristics will be explored with parametric and non-parametric analyses depending on the data level.

The primary analysis for falls (falls/person/year) will be conducted using generalised linear mixed models (GLMM) with a Poisson link function to account for count data distribution and potential overdispersion. The model will include fixed effects for the intervention group and random effects for participant variations over time. Interactions between variables will be included if deemed necessary. Linear mixed model analyses will be used for normally distributed secondary outcomes. For categorical outcomes, GLMM with logistic or ordinal regression will be used, depending on the nature of the outcome (binary or ordinal). The primary endpoint is 6 months after the start of the intervention. In addition, analyses of sustainability of potential effects will be performed after 12 months. Any missing data will be handled using appropriate methods, such as multiple imputation, to ensure robustness in analyses. Analyses will be performed and reported in accordance with the Consolidated Standards of Reporting Trials (CONSORT) guidelines for RCT. 50 A data management plan is established and stored at the Research Data Office at Karolinska Institutet.

RQ 3: process evaluation

RQ 3: Qualitative content analysis will be used for interview data, and descriptive statistics will be used for quantitative data. Data from the group leaders and participants will be analysed separately.

RQ 4: health economic evaluation

The PwMS participating in the Fewer Falls programme will be compared with the control group using intention-to-treat analysis. Appropriate statistical models will be used to estimate changes in resource use over time, considering the distribution of the data collected. Incremental costs will be estimated and compared between the intervention group and the control group. QALYs will be used as the primary health outcome in the economic evaluation, estimated from EQ-5D-5L data. Analyses will be performed and reported in accordance with the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) guidelines for health economic evaluations. 51

Ethics and dissemination

This study has ethical permission from the Swedish Ethical Review Authority (registration no 2022-06667-01 and 2023-07723-02), and the procedures will be performed in accordance with the Declaration of Helsinki. Information will be given orally and in writing, and all participants will give their signed informed consent before the study will start. The results will be published in peer-reviewed journals, at research conferences and meetings, through the patient organisation Neuro Sweden and in social media. Deidentified data will be available on reasonable request after publication of the results.

Discussion

The evaluation of the Fewer Falls programme is an important advancement in fall prevention research because findings will yield insights regarding the effectiveness of an intervention designed to address the specific needs of a unique patient population (ie, ambulatory and non-ambulatory PwMS). This protocol directly addresses the imperative stated by Tuvemo Johnson et al 19 by defining and operationalising ‘self-management’ to support efforts to explain how the intervention activities relate to established frameworks of self-management and mechanisms of impact. Fewer Falls is based on theories and incorporates a self-management approach, which will help PwMS to identify and manage their individual multifactorial fall risks.

Previous RCTs of self-management fall prevention programmes 16 18 designed for PwMS have not shown intervention superiority compared with control. However, none of these were developed using a co-design process with PwMS and/or healthcare professionals. Thereto, none of the programmes were grounded in self-management theories regarding programme activities. Fewer Falls is based on, and all components of the programme are linked to, theories of self-management. This will potentially support PwMS to identify, understand and self-manage their multifactorial fall risks, for example, by using their individual action plans.

The fact that the intervention is delivered online adds to the uniqueness of the programme. To our knowledge, Fewer Falls is the only fall prevention intervention in Sweden that uses an online platform to deliver synchronous and asynchronous programme content. Available evidence suggests that online delivery will support recruitment and programme implementation, including reach, by reducing barriers to programme access. 52 Importantly, online delivery eliminates the need to travel to the site where the programme is being delivered, thus increasing programme availability across Sweden. Access to specialised MS care and rehabilitation in Sweden is largely available only in larger cities. Thus, online delivery has great potential to contribute to more equal access to fall prevention programmes and, thus, support healthcare equality in our country. In addition to eliminating travel-related expenses and logistics, the online intervention will require less time for/effort associated with travelling and therefore may reduce fatigue associated with programme participation.

However, the study has some limitations. The programme is directed to PwMS in Sweden with technical and cognitive ability to participate in a complex intervention. The online delivery will exclude PwMS without technical devices for online meetings and those without technical and cognitive ability to use such devices. Further, unstable network connectivity for PwMS and group leaders may cause short or long outages, which can affect the programme delivery and outcome. In addition, PwMS with impaired communication abilities and skills might not benefit from group discussions. Finally, data including outcomes are mainly self-reported, which should be kept in mind when interpreting the forthcoming results.

In line with the Medical Research Council recommendation for the development and evaluation of complex interventions, 22 throughout the project, we have collaborated with PwMS and healthcare professionals in the development of the intervention. 20 21 The described project involves outcome and process evaluations, as well as a health economic evaluation. Programme effectiveness will be evaluated using a full-scale powered RCT, which is unique to self-management fall prevention research involving both ambulatory and non-ambulatory PwMS. In addition, falls will be monitored up to 12 months, as recommended. 41

The comprehensive process evaluation will enhance understanding of implementation strengths and challenges and the mechanisms of impact for the intervention. The latter is limited in fall prevention research and an important contribution to self-management fall prevention research. As no study has evaluated the cost-effectiveness of fall prevention programmes in PwMS, the health economic evaluation will contribute with unique insights. Our extensive level of collaboration with stakeholders throughout previous and present phases of the project is original and highly salient to the ultimate benefit for end users.

supplementary material

Acknowledgements

The authors would like to acknowledge the patient organisation Neuro Sweden, research colleagues and co-workers in the Neuroepidemiology and health services research group at Karolinska Institutet, and Laura Rice and colleagues, University of Illinois, for their valuable insights regarding outcome measures and effective use of action plans.

Funding: This work was supported by the Swedish Research Council [2023-02648]; the Swedish Research Council for Health, Working Life, and Welfare (FORTE) [2023-00276]; the Strategic Research Area Healthcare at Karolinska Institutet (SFO-V); the Research School in Health Science at Karolinska Institutet; the Regional Agreement on Medical Training and Clinical Research (ALF) between Region Stockholm and Karolinska Institutet [FoUI-987859]; the Center for Innovative Medicine (CIMED) [FoUI-988653]; and Neuro Sweden.

Prepublication history and additional supplemental material for this paper are available online. To view these files, please visit the journal online ( https://doi.org/10.1136/bmjopen-2024-089217 ).

Provenance and peer review: Not commissioned; externally peer reviewed.

Patient consent for publication: Consent obtained directly from patient(s)

Patient and public involvement: Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.

References

1 Walton C King R Rechtman L et al Rising prevalence of multiple sclerosis worldwide: Insights from the Atlas of MS, third edition Mult Scler 2020 26 1816 21 10.1177/1352458520970841 33174475 PMC7720355

2 Gunn HJ Newell P Haas B et al Identification of risk factors for falls in multiple sclerosis: a systematic review and meta-analysis Phys Ther 2013 93 504 13 10.2522/ptj.20120231 23237970

3 Coote S Comber L Quinn G et al Falls in People with Multiple Sclerosis: Risk Identification, Intervention, and Future Directions Int J MS Care 2020 22 247 55 10.7224/1537-2073.2020-014 33424479 PMC7780704

4 Nilsagård Y Gunn H Freeman J et al Falls in people with MS--an individual data meta-analysis from studies from Australia, Sweden, United Kingdom and the United States Mult Scler 2015 21 92 100 10.1177/1352458514538884 24948687 PMC4361466

5 Cameron MH Thielman E Mazumder R et al Predicting falls in people with multiple sclerosis: fall history is as accurate as more complex measures Mult Scler Int 2013 2013 496325 10.1155/2013/496325 24191198 PMC3804404

6 Rice L Kalron A Berkowitz SH et al Fall prevalence in people with multiple sclerosis who use wheelchairs and scooters Medicine (Baltimore) 2017 96 e7860 10.1097/MD.0000000000007860 28858096 PMC5585490

7 Cameron MH Asano M Bourdette D et al People With Multiple Sclerosis Use Many Fall Prevention Strategies but Still Fall Frequently Arch Phys Med Rehabil 2013 94 1562 6 10.1016/j.apmr.2013.01.021 23391522

8 Minet LR Peterson E von Koch L et al Healthcare Utilization After Stroke: A 1-Year Prospective Study J Am Med Dir Assoc 2020 21 1684 8 10.1016/j.jamda.2020.04.036 32669239

9 Weir S Samnaliev M Kuo T-C et al Short- and long-term cost and utilization of health care resources in Parkinson’s disease in the UK Mov Disord 2018 33 974 81 10.1002/mds.27302 29603405

10 Gunn H Endacott R Haas B et al Development of a balance, safe mobility and falls management programme for people with multiple sclerosis Disabil Rehabil 2018 40 2857 66 10.1080/09638288.2017.1362041 28783979

11 McArthur AR Peterson EW Sosnoff J et al Online Delivery of the Individualized Reduction of Falls Intervention for Persons With Multiple Sclerosis Who Use a Wheelchair or Scooter Full-time: A Pilot Study Int J MS Care 2023 25 82 90 10.7224/1537-2073.2022-044 36923574 PMC10010107

12 Rice LA Yarnot R Sung J et al Pilot Study of a Fall Prevention and Management Intervention Program for People With Multiple Sclerosis Who Use a Wheelchair or Scooter Full-Time Arch Rehabil Res Clin Transl 2022 4 100225 10.1016/j.arrct.2022.100225 36545518 PMC9761259

13 Rice LA Sung J Peters J et al Perceptions of fall circumstances, injuries and recovery techniques among power wheelchair users: a qualitative study Clin Rehabil 2018 32 985 93 10.1177/0269215518768385 29627995

14 Barlow J Wright C Sheasby J et al Self-management approaches for people with chronic conditions: a review Patient Educ Couns 2002 48 177 87 10.1016/s0738-3991(02)00032-0 12401421

15 National Institute for Health and Care Research James lind alliance top 10s priorities for research 2023 Available https://www.jla.nihr.ac.uk/top-10-priorities

16 Chanes DC Piza FM de T San Martin G et al Fall prevention education for people with multiple sclerosis: a randomized clinical trial Int J Qual Health Care 2021 33 mzab035 10.1093/intqhc/mzab035 33638988

17 Cameron MH Hildebrand A Hugos CL et al Free From Falls education and exercise program for reducing falls in people with multiple sclerosis: A randomized controlled trial Mult Scler 2022 28 980 8 10.1177/13524585211046898 34595963

18 Cattaneo D Gervasoni E Pupillo E et al n.d. Educational and Exercise Intervention to Prevent Falls and Improve Participation in Subjects With Neurological Conditions: The NEUROFALL Randomized Controlled Trial Front Neurol 10 865 10.3389/fneur.2019.00865 PMC6754067 31572282

19 Tuvemo Johnson S Flink M Peterson E et al Self-management of falls in people with multiple sclerosis: A scoping review Clin Rehabil 2023 37 162 76 10.1177/02692155221128723 36177511 PMC9772893

20 Meijer U Flink M Tuvemo Johnson S et al Preventing falls in multiple sclerosis: a qualitative study on user requirements for a self-management programme Disabil Rehabil 2024 1 8 10.1080/09638288.2024.2348725 38711397

21 Tuvemo Johnson S Ytterberg C Peterson E et al Development of Fewer Falls in MS-An Online, Theory-Based, Fall Prevention Self-Management Programme for People With Multiple Sclerosis Health Expect 2024 27 e14154 10.1111/hex.14154 39032151 PMC11259746

22 Skivington K Matthews L Simpson SA et al A new framework for developing and evaluating complex interventions: update of Medical Research Council guidance BMJ 2021 374 2061 10.1136/bmj.n2061 PMC8482308 34593508

23 Kierkegaard M Peterson E Tuvemo Johnson S et al Online self-management fall prevention intervention for people with multiple sclerosis: a feasibility study protocol of a parallel group randomised trial BMJ Open 2022 12 e061325 10.1136/bmjopen-2022-061325 PMC9272100 35803627

24 Kannan M Hildebrand A Hugos CL et al Evaluation of a web-based fall prevention program among people with multiple sclerosis Mult Scler Relat Disord 2019 31 151 6 10.1016/j.msard.2019.04.015 31004969 PMC6948349

25 Mazuz K Biswas S Lindner U Developing Self-Management Application of Fall Prevention Among Older Adults: A Content and Usability Evaluation Front Digit Health 2020 2 11 10.3389/fdgth.2020.00011 34713024 PMC8522022

26 Murgado-Armenteros EM Torres-Ruiz FJ Vega-Zamora M Differences between Online and Face to Face Focus Groups, Viewed through Two Approaches J theor appl electron commer res 2012 7 15 6 10.4067/S0718-18762012000200008

27 Butcher NJ Monsour A Mew EJ et al Guidelines for Reporting Outcomes in Trial Protocols: The SPIRIT-Outcomes 2022 Extension JAMA 2022 328 2345 56 10.1001/jama.2022.21243 36512367

28 Gu K Ng HKT Tang ML et al Testing the ratio of two poisson rates Biom J 2008 50 283 98 10.1002/bimj.200710403 18311854

29 Meyerowitz-Katz G Ravi S Arnolda L et al Rates of Attrition and Dropout in App-Based Interventions for Chronic Disease: Systematic Review and Meta-Analysis J Med Internet Res 2020 22 e20283 10.2196/20283 32990635 PMC7556375

30 Good clinical practice 2024 Available https://kliniskastudier.se/english/training/good-clinical-practice-gcp

31 Bandura A Health Promotion by Social Cognitive Means Health Educ Behav 2004 31 143 64 10.1177/1090198104263660 15090118

32 Bandura A Social foundations of thought and action: a social cognitive theory Englewood Cliffs, New Jersey Prentice-Hall 1986

33 Lorig KR Holman H Self-management education: history, definition, outcomes, and mechanisms Ann Behav Med 2003 26 1 7 10.1207/S15324796ABM2601_01 12867348

34 Prochaska JO Velicer WF The transtheoretical model of health behavior change Am J Health Promot 1997 12 38 48 10.4278/0890-1171-12.1.38 10170434

35 E-Moderating SG The key to online teaching and learning 3rd edn London Routledge 2011 288

36 Nasreddine ZS Phillips NA Bédirian V et al The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment J Am Geriatr Soc 2005 53 695 9 10.1111/j.1532-5415.2005.53221.x 15817019

37 Zigmond AS Snaith RP The hospital anxiety and depression scale Acta Psychiatr Scand 1983 67 361 70 10.1111/j.1600-0447.1983.tb09716.x 6880820

38 Krupp LB LaRocca NG Muir-Nash J et al The Fatigue Severity Scale: Application to Patients With Multiple Sclerosis and Systemic Lupus Erythematosus Arch Neurol (Chicago) 1989 46 1121 3 2803071 10.1001/archneur.1989.00520460115022

39 Bergman L Nilsson U Dahlberg K et al Validity and reliability of the swedish versions of the HLS-EU-Q16 and HLS-EU-Q6 questionnaires BMC Public Health 2023 23 724 10.1186/s12889-023-15519-9 37081538 PMC10117247

40 O’Malley N Coote S Staunton FM et al A core outcome set for evaluating the effectiveness of mixed-diagnosis falls prevention interventions for people with Multiple Sclerosis, Parkinson’s Disease and stroke PLoS One 2023 18 e0294193 10.1371/journal.pone.0294193 37956176 PMC10642845

41 Lamb SE Jørstad‐Stein EC Hauer K et al Development of a Common Outcome Data Set for Fall Injury Prevention Trials: The Prevention of Falls Network Europe Consensus J American Geriatrics Society 2005 53 1618 22 10.1111/j.1532-5415.2005.53455.x 16137297

42 Tennstedt S Howland J Lachman M et al A Randomized, Controlled Trial of a Group Intervention to Reduce Fear of Falling and Associated Activity Restriction in Older Adults J Gerontol Ser B: Psychol Sci Soc Sci 1998 53B 384 92 10.1093/geronb/53B.6.P384 9826971

43 Clemson L Kendig H Mackenzie L et al Predictors of injurious falls and fear of falling differ: an 11-year longitudinal study of incident events in older people J Aging Health 2015 27 239 56 10.1177/0898264314546716 25117181

44 Kempen GIJM Yardley L van Haastregt JCM et al The Short FES-I: a shortened version of the falls efficacy scale-international to assess fear of falling Age Ageing 2008 37 45 50 10.1093/ageing/afm157 18032400

45 Butler Forslund E Roaldsen KS Hultling C et al Concerns about falling in wheelchair users with spinal cord injury--validation of the Swedish version of the spinal cord injury falls concern scale Spinal Cord 2016 54 115 9 10.1038/sc.2015.125 26261075

46 Yardley L Beyer N Hauer K et al Development and initial validation of the Falls Efficacy Scale-International (FES-I) Age Ageing 2005 34 614 9 10.1093/ageing/afi196 16267188

47 Hobart J Lamping D Fitzpatrick R et al The Multiple Sclerosis Impact Scale (MSIS-29): A new patient-based outcome measure Brain (Bacau) 2001 124 962 73 10.1093/brain/124.5.962 11335698

48 Herdman M Gudex C Lloyd A et al Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L) Qual Life Res 2011 20 1727 36 10.1007/s11136-011-9903-x 21479777 PMC3220807

49 Moore GF Audrey S Barker M et al Process evaluation of complex interventions: Medical Research Council guidance BMJ 2015 350 h1258 10.1136/bmj.h1258 25791983 PMC4366184

50 Schulz KF Altman DG Moher D et al CONSORT 2010 statement: updated guidelines for reporting parallel group randomized trials Obstet Gynecol 2010 115 1063 70 10.1097/AOG.0b013e3181d9d421 20410783

51 Husereau D Drummond M Augustovski F et al Consolidated Health Economic Evaluation Reporting Standards 2022 (CHEERS 2022) statement: updated reporting guidance for health economic evaluations BMJ 2022 376 e067975 10.1136/bmj-2021-067975 35017145 PMC8749494

52 Van Denend T Peterson EW McArthur AR et al A process evaluation of an on-line fall prevention and management program for individuals who use wheelchairs or scooters living with multiple sclerosis Front Public Health 2022 10 1042668 10.3389/fpubh.2022.1042668 36579061 PMC9791181