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. Author manuscript; available in PMC: 2023 Jul 3.
Published in final edited form as: Contemp Clin Trials. 2022 Jan 25;114:106690. doi: 10.1016/j.cct.2022.106690

Motivational Interviewing Intervention for Increasing Physical Activity and Improving Dietary Behaviors: The Lupus Intervention Fatigue Trial Protocol

Dominique Kinnett-Hopkins a,b, Linda Ehrlich-Jones b,c, Joan S Chmiel b, Anh Chung b, Daniel Erickson b, Pamela Semanik d, Bonnie Spring b, Nan E Rothrock b, Rosalind Ramsey-Goldman b
PMCID: PMC10317466  NIHMSID: NIHMS1783979  PMID: 35091136

Abstract

The Lupus Intervention Fatigue Trial (LIFT) is a prospective, randomized controlled trial to assess the effectiveness of a six-month motivational interviewing intervention program versus an educational control to reduce fatigue in persons with systematic lupus erythematosus (SLE). Participants are randomized using a stratified, 1:1 allocation design to the LIFT intervention or control arm. We plan to enroll 236 participants to achieve the target of 200 persons with six-month follow-up for the primary endpoint. Specific aims of this study are to evaluate the impact of the LIFT intervention on1) self-reported measures of fatigue and 2) impact on accelerometer-measured physical activity. The primary study outcome is six-month change in fatigue from baseline, assessed by the Fatigue Severity Scale (FSS). Additional outcomes include objective measures of physical activity, including non-sedentary behavior and moderate-to-vigorous activity (secondary outcome), and adherence to the LIFT dietary intervention, as assessed by nutrient density (diet quality) and recommended food groups/eating patterns (exploratory outcome) in persons with SLE. Intervention effectiveness will be assessed using an intention-to-treat two-arm comparison of six-month change in FSS, with one interim monitoring analysis. A two-sample independent group t-test will compare the six-month changes in FSS between the study arms. Intervention effect durability will be assessed 12-months after baseline (6 months after completion of the intervention). Enrollment began in June 2019 and is expected to end in June 2023. This study will inform future intervention strategies that promote physical activity and improved diet quality to reduce fatigue in persons with SLE.

Keywords: Physical activity, lupus, fatigue, motivational interviewing

1. Introduction

Systemic lupus erythematosus (SLE; lupus) is a chronic autoimmune disease with an estimated prevalence of approximately 204,000 persons in the US.1 SLE manifestations include chronic, debilitating fatigue,2 decreased quality of life,3 and increased risk of work disability.4,5 Fatigue is the most disabling and enduring complaint at all points along the disease continuum in this population.68 There is an urgent unmet need to identify effective pharmacologic and non-pharmacologic strategies to reduce fatigue in persons with SLE. One non-pharmacologic approach may be intervening on modifiable lifestyle behaviors such as physical activity (PA) and diet.

PA is defined as any bodily movement produced by the contraction of skeletal muscles that increases energy expenditure above resting levels (1.6 metabolic equivalents).911 Exercise is a subtype of PA that is planned, structured, and repetitive performed over an extended period (3.0 metabolic equivalents for moderate-intensity exercise/activities). Benefits of PA in persons with SLE include improving oxygen capacity, endurance, and reducing fatigue.12 Persons with SLE are not adequately meeting the recommended PA guidelines of 150 minutes of moderate-to-vigorous PA per week13,14 Preliminary cross-sectional data reported by our team and others indicate that regular aerobic exercise can improve quality of life and reduce fatigue in persons with SLE.12 Studies examining how to best promote PA in SLE are limited.12

Motivational Interviewing (MI) is a patient-centered guiding approach that improves intrinsic motivation for behavior change by exploring and resolving ambivalence.15,16 Although MI was developed to treat addiction, its utility to influence other health-related behaviors has been suggested,17,18 including to promote positive dietary19 and PA behaviors.20 MI has four key processes: engaging, focusing, evoking, and planning, and five communication skills: open-ended questions, affirmations, reflective listening, summarizing, and providing information and advice with permission. Evidence supports MI as a successful patient-centered approach for increasing PA for individuals with chronic health conditions.18 2123 Randomized controlled trials have demonstrated the efficacy of MI interventions for exercise participation for older adults with chronic conditions to improve self-reported quality of life and well-being.24,25 Research concerning MI interventions to increase PA and diet quality in persons with SLE is limited.

Existing literature suggests that diet quality may help reduce fatigue.26 Therefore, the design of the Lupus Intervention Fatigue Trial (LIFT) reflects successful interventions that included PA and diet health promotion, such as the Diabetes Prevention Program27 and Dietary Approaches to Stop Hypertension (DASH) diet.28 The DASH diet encourages a healthy diet by emphasizing eight components: high intake of fruits, vegetables, nuts and legumes, low-fat dairy products, and whole grains and low intake of sodium, sweetened beverages, and red and processed meats.29 DASH was developed to reduce hypertension and used to manage kidney disease. Since both hypertension and kidney disease are manifestations of lupus or its treatment, the DASH diet was selected for the intervention.

We expect that LIFT will improve our understanding of the relationship between fatigue and aspects of PA (frequency, duration, and intensity) in persons with SLE. Furthermore, LIFT will help elucidate relationships between fatigue and aspects of nutrient intake. The specific aims and hypotheses of LIFT are:

  1. Implement and evaluate the impact of the LIFT intervention on self-reported measures of fatigue in persons with SLE.
    • Hypothesis: The LIFT intervention will produce a greater decline from baseline in reported fatigue at 6- and 12-month visits, than the educational program control.
  2. Evaluate the impact of the LIFT intervention on device-measured PA in persons with SLE.
    • Hypothesis: The LIFT intervention will increase PA at 6- and 12-months, to a greater extent than the educational program control.
  3. Evaluate the adherence to the LIFT dietary intervention as assessed by nutrient density and adoption of recommended eating patterns and intake of recommended food groups in persons with SLE.
    • Exploratory Hypothesis: The LIFT intervention will improve diet quality results of greater improvements in nutrient quality compared to baseline a) at the 6-month visit and b) at the 12-month visit, than the educational program control arm.

The purpose of this paper is to present the methodology and intervention design for LIFT, as it was originally designed and is currently being conducted.

2. Methods and Analysis

2.1. Trial Design

LIFT is a randomized phase II prospective controlled trial to assess the effectiveness of a six-month MI intervention program versus an educational control program to reduce fatigue in persons with SLE. The Institutional Review Board (IRB) of Northwestern University approved this study (STU00201960), and the study is registered with ClinicalTrials.gov (NCT02653287). Before study enrollment, researchers obtain written or electronic informed consent from all study participants. The intervention arm uses MI and is designed to increase PA and improve diet quality, in order to demonstrate a greater reduction in fatigue than among persons in the control arm.

The LIFT intervention was developed using a modified version of the Cox Interaction Model of Client Health Behavior (IMCHB) for persons with SLE. The IMCHB has been used to examine PA behaviors in other populations and informed the behavioral counseling intervention and evaluation models of LIFT.30 Cox’s IMCHB differentiates two domains that influence health outcomes: client determinants of behavior and client-professional interaction. Client determinants of behavior include background variables (demographics, current health status, and social influences) and dynamic variables (motivation, self-efficacy). Health outcomes are derived from these two domains. Secondary outcomes of this study were determined using the IMCHB, which includes demographic characteristics, current health, and social influences variables. LIFT includes four individual coaching sessions for participants in each trial arm. The first is delivered shortly after randomization (after baseline assessment is completed). Subsequent sessions occur 1.5, 3, and 6-months later. The session timeline was based on the Principal Investigators’ (LEJ & RRG) prior research experience and desire for a more intense environment of accountability at the beginning of the intervention and with less support as participant self-efficacy and experience with PA and diet quality were increased. See Figure 1 (Study Flow Chart).

Figure 1.

Figure 1.

Study Flow Chart

2.2. Sample Size and Power

We calculated the required sample size using the Aim 1 hypothesis and primary outcome. We plan to compare the two study arms by analyzing within-person changes in the Fatigue Severity Scale (FSS; primary outcome) for each study arm, using an Intention-to-Treat analysis approach. Specifically, we will test the null hypothesis (H0) of no difference in means between study arms using the within-person six-month change in fatigue, versus the two-sided alternative hypothesis that the true mean difference between study arms differs from zero. We set the significance level α (two-sided) at 0.05, and determined the sample size necessary to have at least 80% power to detect a difference, i.e., reject the null hypothesis, when the true (but unknown) difference (improvement) between study arms in mean within-person FSS change is 15%. We allowed for one interim monitoring analysis for the primary outcome variable half-way through the planned study accrual and six-month follow-up assessment (see Section 2.10). To inform our sample size determination, we used available data from our previous study, Activity in Lupus to Energize and Renew (ALTER), to estimate the effect size corresponding to a 15% change in FSS (effect size of 0.40).31,32 We need 97 persons/group with complete FSS 6-month change data. With 100 persons/group, we would have about 90% power if the improvement were slightly greater than 15%. Allowing for 15% attrition in each arm, we estimated that we need to randomize/enroll a total of 236 persons to have 200 persons with analyzable 6-month data for our primary FSS change outcome. For Aim 2, in our ALTER cross-sectional data, we observed a mean for moderate-to-vigorous PA of 38.4 (SD 29.6) min/day for the usual care SLE patients. We estimate that 97 persons/group would detect an effect size of 0.5 SD with 80% power when comparing the two LIFT study arms. Aim 3 is exploratory, thus we did not conduct a statistical power analysis.

2.3. Recruitment

The Chicago Lupus Database (CLD), a registry established in 1991 by RRG that has over 1,100 members, serves as our primary recruitment source. Weekly, we review clinical schedules to identify patients in the CLD who may be eligible for LIFT. Potential participants are contacted about LIFT by phone and/or in the clinic. Interested study candidates are evaluated for eligibility. Additional registries, databases, and resources used for recruitment include Northwestern’s Electronic Data Warehouse, ResearchMatch, The Lupus Society of Illinois, and the Lupus Foundation of America. Once a potential participant makes contact, study personnel send a pre-screening informed consent form for permission to review the medical records which are reviewed to assess eligibility. If eligible, study staff contact the participant to inform them they qualify and schedule a baseline assessment.

2.4. Inclusion and Exclusion Criteria

LIFT participants must: meet at least 4 of 11 ACR classification criteria for definite SLE33, or 3 out of 11 ACR criteria in addition to meeting SLICC classification criteria,34 be at least 18 years old, have a body mass index between 18–40 kg/m2, be able to ambulate at least household distances (50 feet), be able to speak and read in English, and be able to provide informed consent. After obtaining consent, a medical doctor administers the PA Readiness Questionnaire to determine any restrictions needing to be addressed for patient safety.

Exclusion criteria include: pregnancy, an acute medical illness requiring hospitalization, functionally limiting comorbidities such as spinal stenosis, symptomatic avascular necrosis of the hip or knee, peripheral vascular disease, or residual effects of a stroke, a contraindication to PA or dietary intervention due to comorbid conditions, having had a total joint replacement surgery within the past year or plans for total joint replacement in the next 12 months, or plans to relocate away from the Chicago area in the next 12 months.

2.5. Randomization

Randomization procedures are based on a stratified randomization scheme with one stratification variable (disease activity). Separate randomization schedules are developed for each disease activity stratum, but otherwise the same design (1:1 allocation, using random block sizes) is used. Before initiation of the study, randomization schedules were uploaded into the study database to enable blinded allocation of eligible consenting participants after baseline assessments are completed. The physician outcome assessors and research staff who assist with assessments are blinded to the study group assignment. Research staff administering the intervention are blinded to the data collection for the assessments. Participants are asked not to reveal their study arm assignment to the physician outcome assessors and research staff.

2.6. Intervention Group

Participants in the intervention group receive six PowerPoint presentations with supplementary video presentations of each PowerPoint and four individualized coaching sessions focused on motivation and goal setting related to PA and nutrition. Two PowerPoint and video presentations that augment the coaching session are sent by email after each session. The PowerPoints and videos cover the following topics: 1) dietary management, 2) introduction to PA and PA safety, 3) motivation, 4) fruits and vegetables, 5) lifestyle PA, and 6) controlling your environment. The sessions occur shortly after randomization, 1.5, 3, and 6-months. All coaching sessions are led by a Healthy Lifestyle Coach (HLC) trained in MI.

The four individualized sessions incorporate MI skills,35 encouraging the participant to weigh the pros/cons of committing to behavior change, reflect upon short and long-term goals, and take a leading role in problem-solving. The participant sets personal goals that s/he finds relevant, meaningful, and achievable using a semi-structured interview that explores facilitators and barriers to PA and healthy nutrition that might impact fatigue. Short-term goals are established to support an overarching long-term goal. Together, the participant and HLC negotiate the strategies and develop an action plan to help achieve her/his self-identified goals to reduce fatigue. Individual intervention contacts occur by telephone, lasting approximately 10–20 minutes, and include an assessment of achievement of short-term goals, assessment of long-term goals, and revision of short- and/or long-term goals as needed. Initially, the intervention arm included six in-person group sessions. Due to early scheduling complications (i.e., identifying a mutually convenient time for research participants), the group sessions were canceled. Intervention fidelity is assessed by an unblinded staff member trained in MI who listens to a random selection of 25% of the recorded phone calls on an ongoing basis to document use of MI. Based on the outcome of these checks, additional training of the interventionists may take place.

Participants in the intervention group are asked to daily self-monitor their PA using a Fitbit Inspire HR (or a device that they currently own/feel comfortable with) and their dietary behavior using a paper diary for the six-month duration of the intervention. The Fitbit self-monitoring tool has been used successfully in studies assessing behavior change.36,37

2.7. Education Control Program

Education on disease management is considered standard of care. Using standard of care condition allows for an ethical control comparator arm.38 Participants in the educational control group receive six PowerPoint presentations with supplementary video presentations of each PowerPoint and four individualized sessions focused on educational topics found on websites of organizations that advocate for people with SLE (e.g., the Lupus Society of Illinois, the Lupus Foundation of America). The PowerPoint and video presentations cover the following topics: 1) what is lupus, 2) how lupus is diagnosed, 3) how lupus is treated, 4) how to work with your healthcare providers, 5) how to live with lupus, and 6) how to develop a support system; these occur shortly after randomization, 1.5, 3, and 6-months. The individual sessions mimic the attention that the treatment intervention participants receive and follow a structured topic guide discussing program materials, answering questions about the study, or general SLE education-related questions. PA and diet related content are not explicitly discussed in the educational control program. Research staff leading these sessions are trained to refrain from discussing these topics and utilizing MI techniques. Initially, the educational control arm included six in-person group sessions to mimic the attention that the intervention participants receive. These sessions were canceled once the in-person sessions in the intervention arm were canceled.

2.8. Study Timeline and Assessments

Initial participation in the study lasts approximately 2–4 months, including pre-screening (for non-CLD participants only), the screening/baseline visit, and, if eligible, randomization assignment to intervention or control. Once the study arm assignment occurs, active participation lasts approximately 12–14 months. The total time for participation is approximately 16–18 months, subject to scheduling.

Participants complete an assessment at baseline and then at 3, 6, and 12-months following the initial intervention/control visit. All clinical assessments are performed in the Northwestern Clinical Research Unit. See Table 1 for the assessment measures list and timeline.

Table 1.

Assessment Measures and Timeline

Concept Variable Measure Data Collection Method Baseline 3 m 6 m 12 m
Background Variables
Demographics Age, gender, race, marital status, education level CLD Online questionnaire via REDCap X
Current Health Disease activity, severity SLEDAI/SLICC-DI Laboratory tests Face to face interview, MD history, an examination, and lab tests X X X X
Disease duration, medications, comorbid conditions including fibromyalgia, anemia, hypothyroidism CLD Face to face interview, MD history, and examination (fibromyalgia) X X X X
Comorbid condition: pregnancy Pregnancy Test Urine X
Comorbid condition: physical activity restriction PAR-Q Online questionnaire via REDCap X
Dynamic Variables
Motivation Motivation MPAM-R Self-report: Online questionnaire via REDCap X X X X
Decisional Control Self-Efficacy Generalized Self-Efficacy Scale Self-report: online questionnaire via REDCap X X X X
Health Behaviors
Physical Activity Physical Activity Accelerometer: Vector magnitude, minutes of non-sedentary behavior, minutes of MVPA/day ActiGraph Triaxial accelerometer worn during waking hours × 7 days X X X X
Physical Activity IPAQ Telephone interview after seven days of wearing an accelerometer X X X X
Diet Behavior 24-hour dietary recall NDSR Dietary recall per interview for two days (1 weekday and one weekend day) X X X
Health Outcomes
Vital signs, anthropometric measurements Vital signs, height, weight, waist-hip ratio MESA protocol In-person clinical assessment X X X X
Patient-Reported Outcomes Patient Perception of MI Client Perception of Motivational Interviewing Encounter Self-report: Online questionnaire via REDCap X
Fatigue FSS Self-report: Online questionnaire via REDCap X X X X
Fatigue PROMIS CAT Self-report: Online questionnaire via REDCap X X X X
Pain Interference PROMIS CAT Self-report: Online questionnaire via REDCap X X X X
Depression PROMIS CAT Self-report: Online questionnaire via REDCap X X X X
Anxiety PROMIS CAT Self-report: Online questionnaire via REDCap X X X X
Sleep Disturbance PROMIS CAT Self-report: Online questionnaire via REDCap X X X X
Sleep-Related Impairment PROMIS CAT Self-report: Online questionnaire via REDCap X X X X
Physical Function PROMIS CAT Self-report: Online questionnaire via REDCap X X X X

Notes. M=month; CLD=Chicago Lupus Database; REDCap=Research Electronic Data Capture; SLEDAI/SLICC-DI=Systemic Lupus Erythematosus Disease Activity Index/ Systemic Lupus International Collaborating Clinics-Damage Index; MD=Medical Doctor; PAR-Q=Physical Activity Readiness-Questionnaire; MPAM-R=Motives for Physical Activity Measure-Revised; MVPA=Moderate-to-vigorous physical activity; IPAQ=International Physical Activity Questionnaire; NDSR=Nutrition Data System for Research; MESA=Multi-Ethnic Study of Atherosclerosis; MI=Motivational Interviewing; FSS=Fatigue Severity Scale; PROMIS CAT=Patient-Reported Outcomes Measurement Information System Computer Adaptive Test

Motivation is assessed by the Motives for PA Measure-Revised, a 30-item questionnaire assessing the strength of fitness, appearance, competence/challenge, social and enjoyment motives for participating in PA.39 Decisional Control is assessed by the brief Generalized Self-Efficacy Scale, a 10-item questionnaire that assesses a general sense of perceived self-efficacy in order to predict coping with daily hassles and adaptation after experiencing stressful life events.40 Self-reported PA is measured by the International PA Questionnaire, a 27-item questionnaire that reflects on the previous 7 days’ activities according to domain: 1) occupation 2) transportation 3) housework, house maintenance, and caring for family 4) recreation, sport, and leisure-time PA and 5) time spent sitting.41,42 PA is assessed objectively by an Actigraph GT3X triaxial accelerometer worn for seven consecutive days. Accelerometer vector magnitude, minutes of non-sedentary behavior, and minutes of moderate-to-vigorous PA are captured. Diet behavior is assessed utilizing the Nutrition Data Systems for Research (NDSR) via 24-hr dietary recall for one weekday and one weekend day per assessment.43 Client Perception of Motivational Interviewing Encounter (CPMIE), a 20-item questionnaire rating the frequency of the coaches’ behavior of MI skills from the patient’s perspective on a 5-point Likert scale is collected at the end of the intervention period.44

The primary fatigue outcome is assessed by the FSS, a validated 9-item scale that measures the severity of fatigue and its effect on a person’s activities and lifestyle.45 Additional self-reported outcomes are assessed by PROMIS computer adaptive tests (CATs). CATs utilize item response theory to dynamically select the most appropriate questions from an item bank in response to a participant’s prior answers.46 Each CAT administers 4–12 items providing a high level of measurement precision. The fatigue CAT measures the experience and impact of fatigue. The Pain Interference CAT measures the extent to which pain hinders engagement with social, cognitive emotional, physical and recreational activities. The Depression CAT measures negative mood, views of self, and decreased engagement. The anxiety CAT measures fear, worry, and hyperarousal. The Sleep Disturbance and Sleep-related Impairment CATs measure the sleep quality, depth, and restoration and the alertness, sleepiness, tiredness, and functional impairments associated with sleep problems during waking hours, respectively, and the Physical Function CAT measures the participant’s perceived capability of physical activities.

At the end of the six-month intervention, all participants undergo a semi-structured interview administered by a trained qualitative researcher to assess the acceptability and experiences of the LIFT intervention by study participants. The interview findings will guide future trials and inform modifications to the LIFT intervention that may increase its effectiveness.

2.9. Human Subjects and Study Monitoring

An IRB approved the LIFT study, and informed consent is obtained from all study participants before enrollment. Trial safety monitoring currently is provided by Navitas Clinical Research (NCR), which is contracted by the National Institute of Arthritis and Musculoskeletal and Skin Diseases. All study materials, protocols, and modifications are assessed and approved by NCR before submission to the IRB for final approval. NCR assesses safety, trial progress, and data integrity and conducts site visits as needed to guide development, recruitment and retention, intervention implementation, and outcomes of the clinical trial.

2.10. Data Analysis Plan

Analysis of Study Progress and Outcomes

As mentioned previously in Section 2.2, an interim monitoring plan is incorporated into the analysis plan to allow for one interim review that compares the two study arms using the primary study fatigue outcome after 50% of planned participants have enrolled and completed the 6-month FSS assessment. The purpose of the interim analysis is to recommend whether the study should be allowed to continue as designed, estimate whether the sample size needs adjustment based on revised power calculation assumptions, or recommend whether the study should be stopped early or be modified for efficacy or futility. We will use O’Brien-Fleming stopping boundaries for the interim review of the FSS to maintain the overall 5% Type 1 (alpha) level.

Baseline values for the FSS and PA outcomes, covariables (e.g., patient characteristics and demographics, comorbidities, and self-reported PROMIS scores) will be incorporated into the intention-to-treat comparative analysis of the 6- and 12-month outcome data (both FSS and the objective measures of PA) after the basic unadjusted comparisons of the two groups at 6-months have been completed. Persons with missing data will be included in all analyses to the extent that the data permit; multiple imputations will be used to impute missing covariable data where feasible for the primary study analyses. Sensitivity analyses will be done to evaluate potential biases due to missing data and dropouts; characteristics of randomized participants who do not complete the study will be compared to those who complete the follow-up visits to help assess the generalizability of LIFT findings. Planned subgroup analyses will be limited, but we will conduct stratified analyses to assess sex and race/ethnicity by treatment group interactions.

Analysis of the Primary Efficacy Endpoint(s)

The primary endpoint for Aim 1 is the within-person change in FSS between baseline and 6-month evaluation. Using an intention-to-treat approach for analysis, our randomized two-group study will compare the mean of the 6-month within-person changes in FSS for persons in the intervention group vs. the corresponding mean of the changes in FSS for persons in the control group, using a two-sample independent group t-test (with possibly unequal variances) with a two-sided alpha (α) of 0.05.

Baseline, 6- and 12-month FSS data will be analyzed. Mean changes in FSS from baseline will be calculated for each follow-up time point (i.e., baseline minus 6-month and baseline minus 12-month FSS) with associated variability estimates (SD, SEM) calculated for the changes. Mean changes in FSS will be compared between the two study groups for each follow-up time point (6- and 12-month), using two-sample t-tests with possibly unequal variances. We will use generalized estimating equation (GEE) methods (to account for repeated observations on each person) to analyze changes in FSS outcomes at both 6- and 12-month follow-up times jointly when comparing the study groups. If important imbalances in baseline variables occur, we will adjust for these baseline variables to further assess the intervention’s effect on fatigue outcomes.

Analysis of the Secondary Endpoint(s):

While the outcome is different for Aim 2, the strategy for calculating within-person changes between baseline and 6-months and then comparing the mean changes between the two treatment groups is similar to that for Aim 1. Analyses will be similar to those for Aim 1. The average daily non-sedentary minutes, both light and moderate-to-vigorous PA min/day, may be skewed in their distributions, so we first will examine the distributions of these variables. We likely will analyze these PA measures after logarithmically transforming the data and adjusting for wear time.

Exploratory Analyses:

To examine the extent to which the effect of the LIFT intervention in increasing PA may mediate the LIFT effect on reducing fatigue, we will conduct two separate exploratory multivariable GEE regression analyses with FSS measures as response variables, and a LIFT treatment group indicator, follow-up time variable, and their interaction term as covariates. One regression model will include PA levels over time as covariates, and the other will not. Estimated associations between the LIFT treatment group indicator and the FSS outcome measures in the models will be compared. If the demonstrated associations in the models with PA levels as covariates are statistically significantly weaker than those in the models without, we will conclude that the PA levels partially explain and indirectly mediate the effect of the LIFT intervention in reducing fatigue. Future studies and analyses may be needed to fully explore potential underlying causal paths for such interactions and potential indirect and direct mediating effects.

The protocol asks each participant to complete two separate dietary evaluations at baseline and the 6- and 12-month assessments. Results from these two evaluations will be averaged for subsequent analyses. Our primary summary measure of nutrient quality and dietary behavior is the Healthy Eating Index (HEI), calculated using participant data from the NDSR via 24-hour dietary recall. We will assess food groups using the NDSR. The overall approach to analyses of changes from baseline for comparison of the LIFT treatment groups will be similar to that described for other hypotheses. Other pre-specified analyses will analyze changes at 6- and 12-month follow-up visits in SLEDAI score (exploratory), changes in medications (exploratory), and PROMIS scores (see Table 1). Analyses will compare the two study groups as randomized, and stratified by disease activity. We also will conduct sex-specific subgroup analyses to compare the two study groups.

3. 0. Results

Enrollment began in June 2019 and is expected to end in June 2023. All assessments will conclude in June 2024. Study results are expected in the fall of 2024.

4.0. Discussion

Fatigue, a frequent and pervasive problem with multiple adverse consequences for persons with SLE, has limited treatment options to date.68 PA and dietary intake are modifiable behaviors considered potentially relevant to reducing fatigue in persons with SLE.12,26 The LIFT study is a lifestyle behavior program with an MI approach aimed at understanding the relationship between fatigue, PA, and diet quality to inform development of more effective and efficient interventions that include PA and dietary behaviors.

Mancuso and colleagues47 documented the quantity and perceptions of PA in 50 persons with SLE, which indicated only 28% self-reported meeting the recommended health guidelines of at least 150 min/week of moderate-to-vigorous PA.13 Although 92% believed that PA was beneficial for SLE and that they could be more physically active, over 78% believed that SLE impeded their ability to be physically active. Persons with SLE expressed fears about getting injured during PA, but thought PA would be good if it were managed appropriately.47 Persons with SLE have concerns about becoming physically active, and LIFT’s method of utilizing MI to increase PA and improve diet will allow for individualized approaches to address these concerns. LIFT results will further our understanding of the relationship between fatigue and essential aspects of PA (frequency, duration, and intensity) and SLE, and inform development of better intervention programs, including PA promotion.

Nutritional status contributes to a person’s health and immunological integrity with SLE and potentially influences fatigue.26 More than energy density (calories), the nutrient density or quality of the diet measured by the levels of vitamins, minerals, and nutrients provided can significantly impact an individual’s overall well-being.48 Persons with SLE are typically at greater risk of developing coronary heart disease, diabetes, metabolic syndrome, and other diet-related diseases that require careful consideration in balancing appropriate macro- and micro-nutrient intake.4951 To fully document and quantify these relationships, LIFT includes multiple 24-hour recalls via the NDSR,5,43,52 and the HEI is calculated as a composite score to evaluate the exploratory outcomes. LIFT results will improve our understanding of the relationship between fatigue and critical aspects of nutrient intake from diet/supplements and the impact of changing and subsequently maintaining the desired diet behavior, thereby informing development of intervention programs, including diet.

To our knowledge, LIFT is the first randomized controlled trial to investigate an MI approach for reducing fatigue and improving PA and diet quality in persons with SLE. This paper describes the methods and intervention design of LIFT. The results will provide insight into the efficacy and the six-month durability for maintaining increases in PA and improvements in diet quality.

Funding:

Research reported in this publication was supported by the National Institute Of Arthritis And Musculoskeletal And Skin Diseases of the National Institutes of Health under Award Numbers R01AR071091-02S1, P30AR072579, AR059989, and 1U34AR064513. This study was also supported by the Northwestern University, Feinberg School of Medicine Dean’s office. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Abbreviations:

PA

physical activity

LIFT

Lupus Intervention Fatigue Trial

SLE

Systemic Lupus Erythematosus

CLD

Chicago Lupus Database

REDCap

Research Electronic Data Capture

SLEDAI/SLICC-DI

Systemic Lupus Erythematosus Disease Activity Index/ Systemic Lupus International Collaborating Clinics-Damage Inde

MD

Medical Doctor

PAR-Q

Physical Activity Readiness-Questionnaire

MPAM-R

Motives for Physical Activity Measure-Revised

MVPA

Moderate-to-vigorous physical activity

IPAQ

International Physical Activity Questionnaire

GLTEQ

Godin Leisure Time Exercise Questionnaire

NDSR

Nutrition Data System for Research

MESA

Multi-Ethnic Study of Atherosclerosis

MI

Motivational Interviewing

FSS

Fatigue Severity Scale

PROMIS CATs

Patient-Reported Outcomes Measurement Information System Computer Adaptive Tests

ALTER

Activity in Lupus to Energize and Renew

IMCHB

Interaction Model of Client Health Behavior

References

  • 1.Izmirly PM, Parton H, Wang L, et al. Prevalence of Systemic Lupus Erythematosus in the United States: Estimates From a Meta-Analysis of the Centers for Disease Control and Prevention National Lupus Registries. Arthritis Rheumatol. Jan 20 2021;doi: 10.1002/art.41632 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Ramsey-Goldman R, Rothrock N. Fatigue in systemic lupus erythematosus and rheumatoid arthritis. PM R. May 2010;2(5):384–92. doi: 10.1016/j.pmrj.2010.03.026 [DOI] [PubMed] [Google Scholar]
  • 3.Wang C, Mayo NE, Fortin PR. The relationship between health related quality of life and disease activity and damage in systemic lupus erythematosus. J Rheumatol. Mar 2001;28(3):525–32. [PubMed] [Google Scholar]
  • 4.Da Costa D, Dritsa M, Bernatsky S, et al. Dimensions of fatigue in systemic lupus erythematosus: relationship to disease status and behavioral and psychosocial factors. J Rheumatol. Jul 2006;33(7):1282–8. [PubMed] [Google Scholar]
  • 5.Feskanich D, Sielaff BH, Chong K, Buzzard IM. Computerized collection and analysis of dietary intake information. Comput Methods Programs Biomed. Sep 1989;30(1):47–57. doi: 10.1016/0169-2607(89)90122-3 [DOI] [PubMed] [Google Scholar]
  • 6.Krupp LB, LaRocca NG, Muir J, Steinberg AD. A study of fatigue in systemic lupus erythematosus. J Rheumatol. Nov 1990;17(11):1450–2. [PubMed] [Google Scholar]
  • 7.Tench CM, McCurdie I, White PD, D’Cruz DP. The prevalence and associations of fatigue in systemic lupus erythematosus. Rheumatology (Oxford). Nov 2000;39(11):1249–54. doi: 10.1093/rheumatology/39.11.1249 [DOI] [PubMed] [Google Scholar]
  • 8.Ahn GE, Ramsey-Goldman R. Fatigue in systemic lupus erythematosus. Int J Clin Rheumtol. Apr 1 2012;7(2):217–227. doi: 10.2217/IJR.12.4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Bouchard CSR, Stephens T. Physical activity, fitness, and health - International proceedings and consensus statement. Human Kinetics Publishers. 1994:77–88. [Google Scholar]
  • 10.Caspersen CJ PK, Christenson GM. Physical activity, exercise, and physical fitness: definitions and distinctions for health-related research. Public Health Reports. 1985;100(2):126–131. [PMC free article] [PubMed] [Google Scholar]
  • 11.Sandroff BM, Motl RW, Suh Y. Accelerometer output and its association with energy expenditure in persons with multiple sclerosis. J Rehabil Res Dev. 2012;49(3):467–475. doi: 10.1682/Jrrd.2011.03.0063 [DOI] [PubMed] [Google Scholar]
  • 12.O’Dwyer T, Durcan L, Wilson F. Exercise and physical activity in systemic lupus erythematosus: A systematic review with meta-analyses. Semin Arthritis Rheum. Oct 2017;47(2):204–215. doi: 10.1016/j.semarthrit.2017.04.003 [DOI] [PubMed] [Google Scholar]
  • 13.WHO. Global recommendations on physical activity for health. WHO Press, World Health Organization. 2010; [PubMed] [Google Scholar]
  • 14.Margiotta DPE, Basta F, Dolcini G, et al. Physical activity and sedentary behavior in patients with Systemic Lupus Erythematosus. PLoS One. 2018;13(3):e0193728. doi: 10.1371/journal.pone.0193728 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Lundahl B K C, Brownell C, Tollefson D, Burke B. A meta-analysis of motivational interviewing: Twenty-five years of empirical studies. Res Social Work Prac. 2010;20(2):137–160 [Google Scholar]
  • 16.Miller WR S R. Motivational Interviewing: Helping People Change. Third ed. The Guilford Press; 2012. [Google Scholar]
  • 17.Lundahl B, Moleni T, Burke BL, et al. Motivational interviewing in medical care settings: a systematic review and meta-analysis of randomized controlled trials. Patient Educ Couns. Nov 2013;93(2):157–68. doi: 10.1016/j.pec.2013.07.012 [DOI] [PubMed] [Google Scholar]
  • 18.Spencer JC, Wheeler SB. A systematic review of Motivational Interviewing interventions in cancer patients and survivors. Patient Educ Couns. Jul 2016;99(7):1099–1105. doi: 10.1016/j.pec.2016.02.003 [DOI] [PubMed] [Google Scholar]
  • 19.Thorpe M Motivational interviewing and dietary behavior change. J Am Diet Assoc. Feb 2003;103(2):150–1. doi: 10.1016/s0002-8223(03)00005-1 [DOI] [PubMed] [Google Scholar]
  • 20.Bischof G, Bischof A, Rumpf HJ. Motivational Interviewing: An Evidence-Based Approach for Use in Medical Practice. Dtsch Arztebl Int. Feb 19 2021;118(7):109–115. doi: 10.3238/arztebl.m2021.0014 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Naar-King S, Parsons JT, Johnson AM. Motivational interviewing targeting risk reduction for people with HIV: a systematic review. Curr HIV/AIDS Rep. Dec 2012;9(4):335–43. doi: 10.1007/s11904-012-0132-x [DOI] [PubMed] [Google Scholar]
  • 22.Smedslund G, Berg RC, Hammerstrom KT, et al. Motivational interviewing for substance abuse. Cochrane Database Syst Rev. May 11 2011;(5):CD008063. doi: 10.1002/14651858.CD008063.pub2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Lindson-Hawley N, Thompson TP, Begh R. Motivational interviewing for smoking cessation. Cochrane Database Syst Rev. Mar 2 2015;(3):CD006936. doi: 10.1002/14651858.CD006936.pub3 [DOI] [PubMed] [Google Scholar]
  • 24.Soderlund PD. Effectiveness of motivational interviewing for improving physical activity self-management for adults with type 2 diabetes: A review. Chronic Illn. Mar 2018;14(1):54–68. doi: 10.1177/1742395317699449 [DOI] [PubMed] [Google Scholar]
  • 25.O’Halloran PD, Blackstock F, Shields N, et al. Motivational interviewing to increase physical activity in people with chronic health conditions: a systematic review and meta-analysis. Clin Rehabil. Dec 2014;28(12):1159–71. doi: 10.1177/0269215514536210 [DOI] [PubMed] [Google Scholar]
  • 26.de Medeiros MCS, Medeiros JCA, de Medeiros HJ, Leitao J, Knackfuss MI. Dietary intervention and health in patients with systemic lupus erythematosus: A systematic review of the evidence. Crit Rev Food Sci Nutr. 2019;59(16):2666–2673. doi: 10.1080/10408398.2018.1463966 [DOI] [PubMed] [Google Scholar]
  • 27.Delahanty LM. Research charting a course for evidence-based clinical dietetic practice in diabetes. J Hum Nutr Diet. Aug 2010;23(4):360–70. doi: 10.1111/j.1365-277X.2010.01065.x [DOI] [PubMed] [Google Scholar]
  • 28.Fung TT, Chiuve SE, McCullough ML, Rexrode KM, Logroscino G, Hu FB. Adherence to a DASH-style diet and risk of coronary heart disease and stroke in women. Arch Intern Med. Apr 14 2008;168(7):713–20. doi: 10.1001/archinte.168.7.713 [DOI] [PubMed] [Google Scholar]
  • 29.Appel LJ, Moore TJ, Obarzanek E, et al. A clinical trial of the effects of dietary patterns on blood pressure. New Engl J Med. Apr 17 1997;336(16):1117–1124. doi:Doi 10.1056/Nejm199704173361601 [DOI] [PubMed] [Google Scholar]
  • 30.Cox CL. Online exclusive: a model of health behavior to guide studies of childhood cancer survivors. Oncol Nurs Forum. Sep-Oct 2003;30(5):E92–9. doi: 10.1188/03.ONF.E92-E99 [DOI] [PubMed] [Google Scholar]
  • 31.Ahn GE, Chmiel JS, Dunlop DD, et al. Self-reported and objectively measured physical activity in adults with systemic lupus erythematosus. Arthritis Care Res (Hoboken). May 2015;67(5):701–7. doi: 10.1002/acr.22480 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Mahieu MA, Ahn GE, Chmiel JS, et al. Fatigue, patient reported outcomes, and objective measurement of physical activity in systemic lupus erythematosus. Lupus. Oct 2016;25(11):1190–9. doi: 10.1177/0961203316631632 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Hochberg MC. Updating the American College of Rheumatology revised criteria for the classification of systemic lupus erythematosus. Arthritis Rheum. Sep 1997;40(9):1725. doi: 10.1002/art.1780400928 [DOI] [PubMed] [Google Scholar]
  • 34.Petri M, Orbai AM, Alarcon GS, et al. Derivation and validation of the Systemic Lupus International Collaborating Clinics classification criteria for systemic lupus erythematosus. Arthritis Rheum. Aug 2012;64(8):2677–86. doi: 10.1002/art.34473 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Ehrlich-Jones L, Mallinson T, Fischer H, et al. Increasing physical activity in patients with arthritis: a tailored health promotion program. Chronic Illn. Dec 2010;6(4):272–81. doi: 10.1177/1742395309351243 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Kaewkannate K, Kim S. A comparison of wearable fitness devices. BMC Public Health. 2016;16:433–46. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Mercer K, al. e. Behavior change techniques present in wearable activity trackers: a critical analysis. JIMR Mhealth U Health. 2016;2:e40. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Freedland KE, Mohr DC, Davidson KW, Schwartz JE. Usual and unusual care: existing practice control groups in randomized controlled trials of behavrioal interventions. Pscychosom Med. 2011;73(4):323–35. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Richard M, Christina MF, Deborah LS, Rubio N, & Kennon MS Intrinsic motivation and exercise adherence. Int J Sport Psychology. 1997;28(4):335–354. [Google Scholar]
  • 40.Schwarzer R, Jerusalem M. Generalized Self-Efficacy scale. In Weinman J, Wright S, & Johnston M, Measures in health psychology: A user’s portfolio. Causal and control beliefs. Measures in health psychology: A user’s portfolio Causal and control beliefs. 1995;Windsor, UK: NFER-NELSON. [Google Scholar]
  • 41.Craig CL, Marshall AL, Sjostrom M, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sport Exer. Aug 2003;35(8):1381–1395. doi: 10.1249/01.Mss.0000078924.61453.Fb [DOI] [PubMed] [Google Scholar]
  • 42.Hagstromer M, Oja P, Sjostrom M. The International Physical Activity Questionnaire (IPAQ): a study of concurrent and construct validity. Public Health Nutr. Sep 2006;9(6):755–762. doi: 10.1079/Phn2005898 [DOI] [PubMed] [Google Scholar]
  • 43.Nutrition Data System for Research. http://www.ncc.umn.edu/ndsr-database-page/
  • 44.Ehrlich-Jones L Motivational Interviewing from the Patient’s Perspective to Increase Physical Activity in Arthritis. Ann Rheum Dis. Jun 2013;71:26–27. doi:DOI 10.1136/annrheumdis-2012-eular.1580 [DOI] [Google Scholar]
  • 45.Krupp LB, Larocca NG, Muirnash J, Steinberg AD. The Fatigue Severity Scale - Application to Patients with Multiple-Sclerosis and Systemic Lupus-Erythematosus. Arch Neurol-Chicago. Oct 1989;46(10):1121–1123. doi:DOI 10.1001/archneur.1989.00520460115022 [DOI] [PubMed] [Google Scholar]
  • 46.Cella D, Gershon R, Lai JS, Choi S. The future of outcomes measurement: item banking, tailored short-forms, and computerized adaptive assessment. Qual Life Res. 2007;16 Suppl 1:133–41. doi: 10.1007/s11136-007-9204-6 [DOI] [PubMed] [Google Scholar]
  • 47.Mancuso CA, Perna M, Sargent AB, Salmon JE. Perceptions and measurements of physical activity in patients with systemic lupus erythematosus. Lupus. Mar 2011;20(3):231–42. doi: 10.1177/0961203310383737 [DOI] [PubMed] [Google Scholar]
  • 48.Guenther PM, Reedy J, Krebs-Smith SM. Development of the Healthy Eating Index-2005. Journal of the American Dietetic Association. Nov 2008;108(11):1896–1901. doi: 10.1016/j.jada.2008.08.016 [DOI] [PubMed] [Google Scholar]
  • 49.Nuttall SL, Heaton S, Piper MK, Martin U, Gordon C. Cardiovascular risk in systemic lupus erythematosus - evidence of increased oxidative stress and dyslipidaemia. Rheumatology. Jun 2003;42(6):758–762. doi: 10.1093/rheumatology/keg212 [DOI] [PubMed] [Google Scholar]
  • 50.Parker B, Urowitz MB, Gladman DD, et al. Impact of early disease factors on metabolic syndrome in systemic lupus erythematosus: data from an international inception cohort. Annals of the Rheumatic Diseases. Aug 2015;74(8):1530–1536. doi: 10.1136/annrheumdis-2013-203933 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Tam LS, Li EK, Leung VY, et al. Effects of vitamins C and E on oxidative stress markers and endothelial function in patients with systemic lupus erythematosus: a double blind, placebo controlled pilot study. J Rheumatol. Feb 2005;32(2):275–82. [PubMed] [Google Scholar]
  • 52.Schakel SF, Sievert YA, Buzzard IM. Sources of Data for Developing and Maintaining a Nutrient Database. Journal of the American Dietetic Association. Oct 1988;88(10):1268–1271. [PubMed] [Google Scholar]

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