Physical Activity Behavior Change Intervention Research Articles

Physical Activity in Individuals Newly Diagnosed With Multiple Sclerosis Through the Lens of the COM-B Model.

Physical activity (PA) is a promising intervention for disease modification and symptom management in multiple sclerosis (MS); however, there is a lack of research focusing on PA behavior change interventions for persons newly diagnosed with MS. Such PA behavior change interventions should be developed based on a strong empirical foundation of understanding the behavior and its determinants (ie, what to target for changes to occur). To that end, this qualitative study examined factors explaining PA in persons newly diagnosed with MS and identified potential targets for future behavior change intervention development based on the Capability-Opportunity-Motivation-Behavior (COM-B) model. Twenty individuals diagnosed with MS within the past 2 years underwent one-on-one semistructured interviews using questions developed based on the COM-B model. Data were analyzed using reflective thematic analysis, and the identified themes were then mapped with the COM-B model. Factors explaining PA in the study sample were identified across the COM-B components. The typical factors include knowledge and skills to sufficiently engage in PA with appropriate approaches, ability to adapt and navigate through new environmental and social difficulties after diagnosis, and motivation resulting from a combination of factors, such as outcome expectation, belief of capabilities, role/identity, reinforcement, and emotions. The COM-B model was applied successfully in this study to understand PA behavior and identify potential targets for behavior change in individuals newly diagnosed with MS. Future behavior change interventions should consider addressing these factors to generate effective PA behavior change in this population.

PHYSICAL ACTIVITY AND SOCIAL COGNITIVE THEORY CORRELATES AMONG POSTOPERATIVE PERSONS WITH CROHN'S DISEASE: PRELIMINARY RESULTS FROM A CROSS-SECTIONAL ANALYSIS

Abstract INTRODUCTION There is increasing research and clinical interest in physical activity (PA) behavior among persons with Crohn's disease (CD), but little is known regarding PA and its correlates among postoperative persons with CD. This is important as most patients with CD will require surgery within 10 years of diagnosis which may drastically alter PA levels and its benefits for CD. As found in past studies with other patient populations (e.g., colorectal cancer survivors), understanding the cognitive and behavioral factors associated with PA engagement among postoperative adults with CD is useful for informing the development of PA behavior change interventions for this population. This cross-sectional study examined self-reported PA levels and its associations with social cognitive theory (SCT) variables among postoperative persons with CD. METHODS Participants included 30 persons with CD who completed an online survey between November 2022 and June 2023. Of those participants, 18 reported a history of CD-related surgery. The survey assessed demographic and clinical characteristics, disease activity (Harvey-Bradshaw Index), leisure time exercise (Godin Leisure-Time Exercise Questionnaire and International Physical Activity Questionnaire), and related SCT variables (exercise self-efficacy, social support, outcome expectations, goal setting, and planning). Analyses included independent sample t-tests and non-parametric bivariate correlations (rs) for comparing PA levels and SCT survey scores among participants with and without a history of surgery. RESULTS There were differences in PA and SCT variables based on surgical history. Postoperative participants engaged in significantly more PA (t = 2.17, p = 0.04) and reported greater outcome expectations (t = 2.45, p = 0.02) and goal setting (t = 2.22, p = 0.04) scores compared with CD participants without a history of surgery. Among postoperative participants, only exercise goal setting was significantly correlated with PA (rs = .53, p = 0.03) such that postoperative participants with greater exercise goal setting behaviors reported higher levels of PA. None of the SCT variables were significantly associated with PA in the sample of participants without a history of surgery. CONCLUSIONS This study yielded novel findings regarding PA behavior and its SCT correlates in a small sample of postoperative persons with CD. The results suggest the need for further research into exercise goal setting as a potential target of behavior change interventions for increasing PA among postoperative persons with CD.

Let's Move with Leon—A qualitative evaluation of a UK digital intervention to improve physical activity in people with a musculoskeletal condition

ObjectiveThis article presents a qualitative evaluation of a 13-week digital intervention, ‘Let's Move with Leon’, designed to improve physical activity in people with a musculoskeletal condition. Study designA qualitative evaluation embedded within a randomised controlled trial assessing the effectiveness of the intervention at improving self-reported physical activity. MethodsA total of 184 participants received the intervention and were asked each week for 13 weeks to provide comment on their use and the usefulness of the digital physical activity behaviour change intervention. In addition, after 13 weeks, 12 participants took part in a semistructured interview to understand their use and the usefulness of the intervention. A thematic analysis was conducted on the combined qualitative data set. ResultsA total of 128 of the 184 intervention participants (70.11%) provided at least one qualitative comment over the course of the evaluation (mean number of comments per participant = 5); in total, 674 comments were received. The thematic analysis identified three themes: (1) dipping in and out, (2) one size does not fit all and (3) monitoring and feedback. The qualitative data suggest that participants used the intervention sporadically, dipping in and out due to other commitments, and competing programmes, their changing physical ability, confidence and motivation. Not getting off to a good start was detrimental to use; many wanted to come back to the programme at a more appropriate time. A ‘one size fits’ approach catered for some but not all participants. Whilst not a predetermined intervention component the act of monitoring levels of activity as a data collection method seemed to encourage physical activity but may also result in negative social comparisons. ConclusionDigital physical activity behaviour change interventions are not one-size-fits-all; personalisation is key. Monitoring of activity by a named person can create commitment. Many dip in and out. Digital physical activity behaviour change interventions could complement physiotherapy exercises for people with musculoskeletal conditions. Signposting to local activities should be considered.

Sleep, physical activity, and psychological outcomes in children and adolescents with pediatric onset multiple sclerosis.

Sleep, physical activity (PA) and sedentary behavior (SED) have bidirectional associations with mental health in children. The relationships among sleep, PA, SED, with depressive and fatigue symptoms have not been investigated in Pediatric Onset Multiple Sclerosis (POMS) but are needed to inform sleep and PA behavior change interventions. (1) To describe sleep quality including: sleep efficiency, latency, total sleep time, number of awakenings, time in bed, and wake after sleep onset using actigraphy in children and adolescents ages 11 to 18 diagnosed with POMS, and to compare these sleep metrics to those of an age- and sex-matched non-MS group (2) To examine the relationship between time spent in sedentary, light (LIPA), moderate and vigorous PA (MVPA), sleep quality, with depression, fatigue, and quality of life in children and adolescents with POMS and an age and sex matched non-MS group. A cross-sectional study recruited children and adolescents with POMS ages 11 to 18 years followed at a tertiary pediatric hospital (Toronto, Canada) and an age and sex matched non-MS group from the general population. Participants were consented prior to initiation of study procedures. Participants wore an Actiwatch monitor and GT3X accelerometer and completed standardized questionnaires validated to capture data on sleep disturbances, depression, fatigue, and quality of life. Objective sleep data were collected using an Actiwatch including sleep efficiency, total sleep time, number of awakenings, wake after sleep onset (WASO), and sleep latency. A GT3X accelerometer was used to collect PA data including time spent in SED, light (LPA), and moderate to vigorous (MVPA) PA. Correlational analyses and tests of difference were used to compare the groups. 25 POMS (21F; 16.6 years ±1.1 yrs., median Expanded Disability Status Scale (EDSS) =1.5, IQR=1) and 25 Non-MS (22 F; 16±1.3 yrs.) took part. POMS had higher BMI (T= -5.1, P<0.001) compared to Non-MS. No differences in sleep efficiency (MS mean=87%, vs. 88%) sleep time (MS Mean=7.3hrs. vs. 7.4hrs.,), WASO (MS mean=37 mins. vs. 36 mins), latency (MS mean=15 mins vs. 11 mins), SED (MS mean =763 mins. vs. 730 mins) or PA (MS, mean LPA=68 mins. vs 60 mins; MS mean MVPA=12.7 mins. vs. 12.4 mins). Within POMS, higher sleep efficiency was associated with more SED (SR= 0.4, p=0.05), while higher sleep efficiency was associated with less SED in Non-MS (SR=-0.7, p< 0.0). In children with POMS, less sleep time, shorter sleep onset latency and more WASO was associated with more SED (SR range=-0.45 to -0.58, P< 0.01). Higher sleep efficiency was associated with less fatigue. Less WASO was associated with lower depression, lower fatigue (SR=0.67, p<0.01) and better quality of life (SR= -0.6, p<0.01). Greater LPA was associated with lower sleep onset latency (-0.45, p<0.05). Children with POMS did not differ in Actiwatch monitored sleep quality metrics. However, within the POMS group sleep quality was associated with better fatigue, depression and QOL. Further, total sleep time, WASO and latency associated with time spent SED and LPA, which independently associate with mental health outcome. Longitudinal work should determine the temporal associations between WASO, sleep latency, sleep time, PA, and mental health outcomes and whether reallocation of specific sleep or PA behaviors (time to sleep, total sleep time, sedentary to MVPA) result in improved depression fatigue, or quality of life in children and adolescents with POMS.

Willingness of women at increased genetic and non-genetic risk of breast cancer to participate in intervention trials to prevent cancer.

e24190 Background: The factors that influence willingness to participate (WTP) in breast cancer (BC) prevention trials are not well understood. WTP in BC prevention trials was examined in patients at increased risk of BC considering intervention and participant characteristics. Methods: Women self-identifying as being at increased risk for BC were recruited to a cross-sectional study of WTP in BC prevention trials. 78% (87 of 112) of participants completed ≥50% of a 29 item Likert Scale questionnaire about WTP in BC prevention trials that varied in intervention type and intensity, duration, time commitment, study procedures, and side effects of medications. Responses were dichotomized into “more willing” (“a lot” and “moderately”) versus “less willing” (“some,” “a little,” and “not at all”). A chi-square test was used to determine if responses differed between participants based on intervention and participant characteristics. Results: General WTP in BC ‘prevention’ studies was high at 79% “more willing”, including 67% and 72%, respectively, for unspecified physical activity and diet behavior change interventions. WTP differed significantly for diet-based behavior change interventions by type and duration; WTP was significantly lower for 12- versus 3-month interventions for both eliminating foods (28% versus 53% “more willing”, p = 0.0007) and for engaging in intermittent fasting (30% versus 45% “more willing”, p = 0.042). For physical activity, WTP decreased with duration of the intervention with 28% fewer WTP for one hour of low intensity exercise/day when compared to 30 minutes (p &lt; 0.0001). For medications, less than half of participants (46%) expressed being “more willing” to participate, and WTP decreased significantly when possible side effects were presented (81% “less willing”) with 95% “less willing” for medications with a rare risk of serious side effects. WTP was influenced by BC risk gene mutation status, with higher proportions among gene carriers compared to non-gene carriers (59% versus 21% “more willing,” p = 0.0013), including WTP in medication chemoprevention studies (38% versus 8% “more willing,” p = 0.002). Conclusions: WTP in BC prevention trials of behavior change is high among patients at elevated risk of BC but for all women was found to be significantly negatively influenced by greater time commitment and duration of intervention beyond a few months. WTP in studies of medication is lower compared to behavior change, and very low for medications with any side effects. Overall, WTP is greater in women with known genetic risk. This study suggests that WTP may be influenced by how patients perceive their level of risk. These results also suggest that despite interest in behavior change prevention, patients may not fully recognize the relationship between sustained behavior change and potential for prevention benefit.

Theory-based physical activity and/or nutrition behavior change interventions for cancer survivors: a systematic review.

Theory-based interventions aimed at promoting health behavior change in cancer survivors seem to be effective but remain scarce. More information on intervention features is also needed. This review aimed to synthesize the evidence from randomized controlled trials evaluating the efficacy of theory-based interventions (and its features) on physical activity (PA) and/or diet behaviors in cancer survivors. A systematic search in three databases (PubMed, PsycInfo, and Web of Science) identified studies that (i) targeted adult cancer survivors and (ii) included theory-based randomized controlled trials designed to influence PA, diet, or weight management. A qualitative synthesis of interventions' effectiveness, extensiveness of theory use, and applied intervention techniques was conducted. Twenty-six studies were included. Socio-Cognitive Theory was the most used theory, showing promising results in PA-only trials and mixed findings in multiple-behavior interventions. Mixed findings were observed for interventions based on the Theory of Planned Behavior and Transtheoretical Model. Limited findings were found in diet-only interventions. A large variability in the extensiveness of theory use, and in intervention techniques was found. Further research is required to understand how and why these interventions offer promise for improving behavior. Theory-based interventions seem to improve PA and diet behaviors in cancer survivors. Further studies, including thorough intervention descriptions, are needed to confirm these findings and identify the optimal features and content of lifestyle theory-based interventions for cancer survivors. This systematic review can contribute to the development of more effective interventions to promote long-term adherence to healthy lifestyle behaviors.

Breast cancer survivors’ exercise preferences change during an exercise intervention are associated with post-intervention physical activity

Exercise program preferences are important for designing physical activity (PA) interventions; yet may change following an intervention. Further, the relationship between preferences and PA behavior change is unclear. This study evaluated exercise program preferences among breast cancer survivors (BCS) before and after a behavioral intervention and associations between program preferences and PA change. BCS were randomized to the BEAT Cancer intervention (n = 110) or written materials (n = 112). Questionnaires assessed exercise program preferences. Minutes per week of moderate-to-vigorous PA (MVPA) were accelerometer-measured and self-reported at baseline (M0), post-intervention (M3), and 3-month follow-up (M6). At M0, the majority of intervention group participants preferred exercising with others (62%) yet shifted to preferring exercising alone (59%) at M3 (p < 0.001). Furthermore, preferring exercising with others at M0 was associated with greater increases in self-reported MVPA between M0 and M6 (124.2 ± 152 vs. 53.1 ± 113.8, p = 0.014). BCS preferring facility-based exercise decreased after the BEAT Cancer intervention (14% vs. 7%, p = 0.039) and preferring exercising at home/had no preference at M0 had greater improvements in accelerometer-measured MVPA from M0 to M3 (74.3 ± 118.8 vs. -2.3 ± 78.4, p = 0.033) and M0 to M6 (44.9 ± 112.8 vs. 9.3 ± 30.4, p = 0.021). Exercise program preferences regarding mode of counseling, training supervision, and type of exercise changed from M0 to M3 but were not associated with changes in MVPA. Findings suggest BCS exercise program preferences may change after an intervention and be associated with changes in MVPA. Understanding the role of PA preferences will better inform the design and success of PA behavior change interventions. ClinicTrials.gov, ClinicalTrials.gov number: NCT00929617.

Physical activity intervention benefits persist months post-intervention: randomized trial in breast cancer survivors.

Determine durable effects of the 3-month Better Exercise Adherence after Treatment for Cancer (BEAT Cancer) physical activity (PA) behavior change intervention 12months post-baseline (i.e., 9months after intervention completion). This 2-arm multicenter trial randomized 222 post-primary treatment breast cancer survivors to BEAT Cancer (individualized exercise and group education) vs. usual care (written materials). Assessments occurred at baseline, 3, 6, and 12months, with the 12months assessment reported here. Measures included PA (accelerometer, self-report), cardiorespiratory fitness, muscle strength, body mass index, Functional Assessment of Cancer Therapy (FACT), SF-36, fatigue, depression, anxiety, satisfaction with life, Pittsburgh Sleep Quality Index (PSQI), lower extremity joint dysfunction, and perceived memory. Adjusted linear mixed-model analyses demonstrated statistically significant month 12 between-group differences favoring BEAT Cancer for weekly minutes of moderate-to-vigorous self-report PA (mean between-group difference (M) = 44; 95% confidence interval (CI) = 12 to 76; p = .001), fitness (M = 1.5ml/kg/min; CI = 0.4 to 2.6; p = .01), FACT-General (M = 3.5; CI = 0.7 to 6.3; p = .014), FACT-Breast (M = 3.6; CI = 0.1 to 7.1; p = .044), social well-being (M = 1.3; CI = 0.1 to 2.5; p = .037), functional well-being (M = 1.2; CI = 0.2 to 2.3; p = .023), SF-36 vitality (M = 6.1; CI = 1.4 to 10.8; p = .011), fatigue (M = - 0.7; CI = - 1.1 to - 0.2; p = .004), satisfaction with life (M = 1.9; CI = 0.3 to 3.5; p = .019), sleep duration (M = - 0.2; CI = - 0.4 to - 0.03, p = .028), and memory (M = 1.1; CI = 0.2 to 2.1; p = .024). A 3-month PA intervention resulted in statistically significant and clinically important benefits compared to usual care at 12months. Three months of individualized and group PA counseling causes benefits detectable 9months later. ClinicalTrials.gov NCT00929617 ( https://clinicaltrials.gov/ct2/show/NCT00929617 ; registered June 29, 2009).

Acceptability and Feasibility of the Telehealth Bariatric Behavioral Intervention to Increase Physical Activity: Protocol for a Single-Case Experimental Study.

BackgroundRegular physical activity (PA) is recommended to optimize weight and health outcomes in patients who have undergone metabolic and bariatric surgery (MBS). However, >70% of patients have low PA levels before MBS that persist after MBS. Although behavioral interventions delivered face-to-face have shown promise for increasing PA among patients who have undergone MBS, many may experience barriers, preventing enrollment into and adherence to such interventions. Delivering PA behavior change interventions via telehealth to patients who have undergone MBS may be an effective strategy to increase accessibility and reach, as well as adherence.ObjectiveThis paper reports the protocol for a study that aims to assess the feasibility and acceptability of the protocol or methods and the Telehealth Bariatric Behavioral Intervention (TELE-BariACTIV). The intervention is designed to increase moderate-to-vigorous intensity PA (MVPA) in patients awaiting bariatric surgery and is guided by a multitheory approach and a patient perspective. Another objective is to estimate the effect of the TELE-BariACTIV intervention on presurgical MVPA to determine the appropriate sample size for a multicenter trial.MethodsThis study is a multicenter trial using a repeated (ABAB’A) single-case experimental design. The A phases are observational phases without intervention (A1=pre-MBS phase; A2=length personalized according to the MBS date; A3=7 months post-MBS phase). The B phases are interventional phases with PA counseling (B1=6 weekly pre-MBS sessions; B2=3 monthly sessions starting 3 months after MBS). The target sample size is set to 12. Participants are inactive adults awaiting sleeve gastrectomy who have access to a computer with internet and an interface with a camera. The participants are randomly allocated to a 1- or 2-week baseline period (A1). Protocol and intervention feasibility and acceptability (primary outcomes) will be assessed by recording missing data, refusal, recruitment, retention, attendance, and attrition rates, as well as via web-based acceptability questionnaires and semistructured interviews. Data collected via accelerometry (7-14 days) on 8 occasions and via questionnaires on 10 occasions will be analyzed to estimate the effect of the intervention on MVPA. Generalization measures assessing the quality of life, anxiety and depressive symptoms, and theory-based constructs (ie, motivational regulations for PA, self-efficacy to overcome barriers to PA, basic psychological needs satisfaction and frustration, PA enjoyment, and social support for PA; secondary outcomes for a future large-scale trial) will be completed via web-based questionnaires on 6-10 occasions. The institutional review board provided ethics approval for the study in June 2021.ResultsRecruitment began in September 2021, and all the participants were enrolled (n=12). Data collection is expected to end in fall 2023, depending on the MBS date of the recruited participants.ConclusionsThe TELE-BariACTIV intervention has the potential for implementation across multiple settings owing to its collaborative construction that can be offered remotely.International Registered Report Identifier (IRRID)DERR1-10.2196/39633

Moderators Of A Multi-Component Physical Activity Behavior Change Intervention Effects On Fatigue, Depression, And Anxiety

BACKGROUND: Fatigue, depression, and anxiety significantly reduce quality of life in breast cancer survivors (BCS). Identifying factors that predict symptom response to physical activity (PA) behavior change interventions may allow for more targeted interventions. PURPOSE: To determine demographic and medical factors that moderate the effects of a multi-component PA behavior change intervention (i.e., BEAT Cancer) on fatigue, depressive symptomatology, and anxiety in BCS. METHODS: In this multi-center randomized controlled trial, post-primary treatment BCS (N=222; Stage 0-III) were assigned to BEAT Cancer PA intervention or usual care (i.e., PA-related written materials) Fatigue Symptom Inventory (11-point, Likert scale (0=best; 10=worst) and Hospital Anxiety and Depression Scale were assessed at baseline, 3 months (immediately post-intervention) and 6 months. Moderators (baseline value of each outcome, age, income, marital status, cancer stage, months since diagnosis, cancer treatment, body mass index [BMI], and comorbidities) were assessed at baseline (BMI measured on-site; remaining factors self-reported). This study is a post-hoc exploratory analysis using linear regression to test hypothesized moderators. RESULTS: Participants with baseline fatigue interference ≥3 experienced greater improvements in fatigue interference (p = .020; -1.35 vs. -.42 for interference <3). Those with a history of radiation experienced greater reductions in depressive symptomatology (p = .013; -1.53 vs. 0.08 if no history of radiation). Finally, participants with <2 comorbidities or BMI <30 experienced greater reductions in anxiety (p = .010; -1.97 vs. -.26 for ≥ 2 comorbidities and p = .033; -1.66 vs. -.33 for BMI ≥ 30, respectively). No statistically significant moderators of the intervention effects on fatigue intensity were found. CONCLUSIONS: Findings indicate that BCS with higher baseline fatigue interference, history of radiation, <2 comorbidities, and BMI <30 may have a more favorable symptom response with a PA behavior change intervention. Future research is needed to identify etiologic mechanisms for lack of response (e.g., radiation therapy) and unmet needs of less responsive subgroups (e.g., multiple comorbidities, obesity).

Assessing Open Science practices in physical activity behaviour change intervention evaluations.

ObjectivesConcerns on the lack of reproducibility and transparency in science have led to a range of research practice reforms, broadly referred to as ‘Open Science’. The extent that physical activity interventions are embedding Open Science practices is currently unknown. In this study, we randomly sampled 100 reports of recent physical activity randomised controlled trial behaviour change interventions to estimate the prevalence of Open Science practices.MethodsOne hundred reports of randomised controlled trial physical activity behaviour change interventions published between 2018 and 2021 were identified, as used within the Human Behaviour-Change Project. Open Science practices were coded in identified reports, including: study pre-registration, protocol sharing, data, materials and analysis scripts sharing, replication of a previous study, open access publication, funding sources and conflict of interest statements. Coding was performed by two independent researchers, with inter-rater reliability calculated using Krippendorff’s alpha.Results78 of the 100 reports provided details of study pre-registration and 41% provided evidence of a published protocol. 4% provided accessible open data, 8% provided open materials and 1% provided open analysis scripts. 73% of reports were published as open access and no studies were described as replication attempts. 93% of reports declared their sources of funding and 88% provided conflicts of interest statements. A Krippendorff’s alpha of 0.73 was obtained across all coding.ConclusionOpen data, materials, analysis and replication attempts are currently rare in physical activity behaviour change intervention reports, whereas funding source and conflict of interest declarations are common. Future physical activity research should increase the reproducibility of their methods and results by incorporating more Open Science practices.

Study protocol for the investigation of the clinical effectiveness of a physical activity behaviour change intervention for individuals living with and beyond cancer

Most individuals living with and beyond cancer are not sufficiently active to achieve the health benefits associated with regular physical activity (PA). The purpose of this study was to describe the study protocol for a two-arm non-randomised comparison trial conducted within a community-based setting, which aimed to investigate the clinical effectiveness of a cancer-specific PA behaviour change (BC) intervention, namely MedEx IMPACT (IMprove Physical Activity after Cancer Treatment), compared to a general exercise rehabilitation programme, among survivors of cancer. Individuals who had completed active-cancer treatment who were referred to a community-based exercise rehabilitation programme were invited to participate in the trial. Participants in the control group (CG) attended twice-weekly supervised exercise classes for 12 weeks. Classes were delivered as part of a chronic illness exercise rehabilitation programme. Participants in the MedEx IMPACT intervention group (IG) also attended the twice-weekly supervised exercise classes for 12 weeks and received cancer-specific materials, namely an independent PA programme, 4 PA information sessions and a 1:1 exercise consultation. The primary outcome was PA levels measured by 6-day accelerometry and self-report PA. Secondary outcomes included cardiorespiratory fitness (CRF), quality of life (QoL) and sedentary behaviour. Outcomes were measured at baseline and months 3, 6 and 12. Few effective PA BC interventions for individuals living with and beyond cancer have been identified. The results of this study will have implications for the planning and provision of community-based exercise oncology rehabilitation programmes for individuals living with and beyond cancer.

Studying the implementation of exercise oncology interventions: a path forward.

Extensive scientific evidence supports exercise benefits after a cancer diagnosis and the field now needs to focus on elucidating effective strategies for implementing exercise evidence-based interventions (EBIs) for cancer survivors. This paper brings together three implementation efforts to describe pragmatic observations and strategies when implementing exercise oncology EBIs in non-research settings. From these projects, we report on common implementation barriers and facilitators. We then mapped these observations and strategies on to the phases and processes described in the Exploration, Preparation, Implementation, and Sustainment (EPIS) Framework. The first implementation project used key stakeholders' perspectives to develop a toolkit to implement BEAT Cancer (Better Exercise Adherence after Treatment for Cancer), a self-managed intervention led by fitness professionals. The second project adapted a physical activity behavior change intervention (Active Living after Cancer) for use in the broader community. The third project adapted an in-person exercise intervention in a community setting (Physical Activity and Lymphedema) into an out-patient rehabilitation setting, including home-based intervention elements (Strength After Breast Cancer). We retrospectively collated and operationalized the implementation strategies based on the Experts Recommending Implementation Change (ERIC) study. The most common implementation barriers were related to funding, organizational capacity and training, relationship building, patient referral, and engagement with patients. These implementation strategies provide initial starting points for the implementation of exercise oncology EBIs in clinical and community settings while also serving as examples for future implementation research to advance the translation of exercise oncology evidence.

Let’s build an app for that

The promotion of physical activity behavior change among adults with cancer is a research priority. Within this field, increasing attention is being devoted to the use of health technology, which includes mobile phones and applications, or apps, to support and deliver physical activity behavior change interventions. While building a mobile app is a popular proposal among exercise oncology researchers, little practical information exists on how this process should be done or what considerations researchers should take in collaboration with participants and industry. The present article provides an overview of recent experiences with app development in exercise oncology and outlines several recommendations for future research. Methods and Results: After forming an interdisciplinary team of researchers, industry partners, and exercise oncology program participants, an iterative, user-centered app improvement process was followed to collect feedback and make meaningful changes to an existing mobile health app for its use in exercise oncology. Participant feedback was summarized and addressed collaboratively via open discussion and detailed action plans. Changes made include enhanced introductory materials for the app and improvements to usability and personalization. Some requests remain to be addressed in future updates. Two challenges identified during the app improvement process were balancing the unique needs and priorities of all parties, as well as addressing the variable feedback from a variable population of adults with cancer. Conclusions and significance: A multidisciplinary participant-oriented app improvement process led to meaningful updates to the mobile application of interest, preparing researchers to carry out an evaluation of its effectiveness within exercise oncology. Furthermore, based on lessons learned, the research team present key recommendations to consider in future mobile app research before, during, and after the development process.

Smartphone-Based Interventions to Reduce Sedentary Behavior and Promote Physical Activity Using Integrated Dynamic Models: Systematic Review.

BackgroundTraditional psychological theories are inadequate to fully leverage the potential of smartphones and improve the effectiveness of physical activity (PA) and sedentary behavior (SB) change interventions. Future interventions need to consider dynamic models taken from other disciplines, such as engineering (eg, control systems). The extent to which such dynamic models have been incorporated in the development of interventions for PA and SB remains unclear.ObjectiveThis review aims to quantify the number of studies that have used dynamic models to develop smartphone-based interventions to promote PA and reduce SB, describe their features, and evaluate their effectiveness where possible.MethodsDatabases including PubMed, PsycINFO, IEEE Xplore, Cochrane, and Scopus were searched from inception to May 15, 2019, using terms related to mobile health, dynamic models, SB, and PA. The included studies involved the following: PA or SB interventions involving human adults; either developed or evaluated integrated psychological theory with dynamic theories; used smartphones for the intervention delivery; the interventions were adaptive or just-in-time adaptive; included randomized controlled trials (RCTs), pilot RCTs, quasi-experimental, and pre-post study designs; and were published from 2000 onward. Outcomes included general characteristics, dynamic models, theory or construct integration, and measured SB and PA behaviors. Data were synthesized narratively. There was limited scope for meta-analysis because of the variability in the study results.ResultsA total of 1087 publications were screened, with 11 publications describing 8 studies included in the review. All studies targeted PA; 4 also included SB. Social cognitive theory was the major psychological theory upon which the studies were based. Behavioral intervention technology, control systems, computational agent model, exploit-explore strategy, behavioral analytic algorithm, and dynamic decision network were the dynamic models used in the included studies. The effectiveness of quasi-experimental studies involved reduced SB (1 study; P=.08), increased light PA (1 study; P=.002), walking steps (2 studies; P=.06 and P<.001), walking time (1 study; P=.02), moderate-to-vigorous PA (2 studies; P=.08 and P=.81), and nonwalking exercise time (1 study; P=.31). RCT studies showed increased walking steps (1 study; P=.003) and walking time (1 study; P=.06). To measure activity, 5 studies used built-in smartphone sensors (ie, accelerometers), 3 of which used the phone’s GPS, and 3 studies used wearable activity trackers.ConclusionsTo our knowledge, this is the first systematic review to report on smartphone-based studies to reduce SB and promote PA with a focus on integrated dynamic models. These findings highlight the scarcity of dynamic model–based smartphone studies to reduce SB or promote PA. The limited number of studies that incorporate these models shows promising findings. Future research is required to assess the effectiveness of dynamic models in promoting PA and reducing SB.Trial RegistrationInternational Prospective Register of Systematic Reviews (PROSPERO) CRD42020139350; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=139350.

Dose and engagement during an extended contact physical activity and dietary behavior change intervention delivered via tailored text messaging: exploring relationships with behavioral outcomes

BackgroundExtended contact interventions delivered via text messaging are a low-cost option for promoting the long-term continuation of behavior change. This secondary analysis of a text message–delivered extended contact intervention (‘Get Healthy, Stay Healthy’ (GHSH)) explores the extent to which changes in physical activity, dietary behaviors and body weight were associated with the frequency of text messages (dose) and contact between the health coach and participant (engagement).MethodsFollowing a telephone coaching program, participants were randomised to receive extended contact via tailored text messages (GHSH, n = 114) or no additional contact (n = 114) over a 6-month period. Message dose, timing, and content were based on participant preferences, ascertained during two tailoring telephone calls. All incoming and outgoing messages were recorded. At baseline and 6 months, participants self-reported body weight and dietary behaviors (fruit and vegetable servings/day). Moderate-vigorous physical activity (MVPA) was assessed via accelerometry.ResultsMedian dose (25th, 75th percentile) was 53 (33, 72) text messages in total across six months. Mean fortnightly dose in weeks 1–2 was 5.5 (95 % CI: 4.3, 6.6) text messages, and remained stable (with the exception of planned decreases in weeks involving additional intervention contacts). Offset against the average fortnightly dose of goal checks (1.6, 95 % CI: 1.3, 2.0 and 1.5, 95 % CI: 1.2, 1.8, for physical activity and diet respectively), mean replies to goal checks were highest in weeks 1–2 (1.4, 95 % CI: 1.4, 1.5 and 1.3, 95 % CI: 1.2, 1.4, respectively) and tended to become lower in most weeks thereafter. Greater weight loss was positively associated with text message dose (P = 0.022), with a difference of 1.9 kg between participants receiving the most and fewest texts. There was no association between engagement and changes in outcome measures.ConclusionsA fixed dose of texts does not seem suitable to meet participants’ individual preferences. Higher self-selected text doses predicted better weight outcomes. However, greater participant engagement through text replies does not predict more favourable outcomes, despite being a suggested facilitator of successful behavior change maintenance.Trial registrationAustralian New Zealand Clinical Trials Registry number: ACTRN12613000949785. Date registered: 27 August 2013. Retrospectively registered. http://www.anzctr.org.au/.

Tailored physical activity behavior change interventions: challenges and opportunities

A physically active lifestyle provides innumerable benefits; yet, few individuals are physically active enough to reap those benefits. Tailored physical activity interventions may address low rates of physical activity by offering individualized strategies that consider a person's characteristics, needs, preferences, and/or context, rather than the traditional one-size-fits-all approach. However, the tailoring methodology is in its nascency, and an understanding of how best to develop such interventions is needed. In this commentary, we identify future directions to enhance the impact of tailored interventions designed to increase physical activity participation. A multi-country collaborative was established to review the literature and discuss an agenda for future research. Two overarching research opportunities are suggested for improving the development of tailored, behavioral physical activity interventions: (a) optimize the engagement of diverse knowledge users in intervention co-design and (b) examine ethical considerations that may impact the use of technology to support tailored physical activity delivery. Specifically, there is a need for better reporting and evaluation of knowledge user involvement alongside targeting diversity in the inclusion of knowledge users. Furthermore, while technology boasts many opportunities to increase the scale and precision of interventions, examinations of how it impacts recipients' experiences of and participation in tailored interventions are needed to ensure the benefits of technology use outweigh the risks. A better understanding of these research areas will help ensure that the diverse needs of individuals are met, technology is appropriately used to support tailoring, and ultimately it improves the effectiveness of tailored physical activity interventions.

One Size Does Not Fit All: Financial Incentives Needed to Change Physical Exercise Levels for Different Groups.

This study estimated the distribution of willingness to accept (WTA) for a physical activity behavior change intervention entailing the completion of 10,000 steps/day to shed light on which levels of incentives trigger a change in behavior for different proportions of the population and for more at-risk subgroups. An online contingent valuation (CV) survey was administered to 1130 respondents in the Basque Autonomous Community, Spain. The survey queried respondents about their physical activity levels and intention to engage in physical activity before presenting the WTA questions. Nonparametric WTA values were estimated for the whole sample and for subsamples of active, inactive, and overweight and obese people. One-quarter of respondents would engage with the hypothetical program even without payment, but if a monetary incentive was offered them, they would take it. The median WTA for committing to complete 10,000 steps/day is €0.23 for the full sample, €0.21 for active, €0.25 for inactive, and €0.23 for overweight and obese people. The WTA at 75th percentile is €4 for the full sample, €1.70 for active, €10.80 for inactive, and €5 for overweight and obese respondents. WTA is positively affected by a person's lack of disposable time to increase their physical activity and, for inactive people, by their poor intention to become physically active.

Physical Activity and Sedentary Behavior Patterns Across Weekdays and Weekend Days in Youth With Multiple Sclerosis and Controls.

This study quantified and compared weekday and weekend patterns of device-measured physical activity (PA) and sedentary behavior between youth with pediatric multiple sclerosis (MS) and controls for the purpose of informing future PA behavior change interventions. Participant data were obtained from 3 ongoing observational studies, and the sample included 40 participants with pediatric MS and 41 controls. Light PA (LPA), moderate to vigorous PA (MVPA), and sedentary behavior data were collected using activity monitors (ActiGraph LLC) over 1 week. The main analysis involved a 2-way mixed factor analysis of variance with group as a between-subjects factor (pediatric MS vs control) and day as a within-subjects factor (weekday vs weekend day). There was no group by day interaction from the analysis of variance for percentage of activity monitor wear time spent in LPA, MVPA, or sedentary behavior. There was no effect of group for LPA, MVPA, or sedentary behavior. There was an effect of day of week on percentage of day spent in LPA, MVPA, and sedentary behavior. These results suggest that youth with pediatric MS and controls were less physically active and more sedentary on weekends than on weekdays, but there were no differences between groups in PA and sedentary behavior overall or by day of the week. Physical activity interventions may be more successful by initially targeting weekend day activity.

Feasibility and efficacy of a physical activity intervention for managing restless legs syndrome in multiple sclerosis: Results of a pilot randomized controlled trial

BackgroundThis pilot randomized controlled trial examined the feasibility and efficacy of a physical activity behavior change intervention for improving restless legs syndrome (RLS) severity and secondary sleep outcomes among a sample of adults with multiple sclerosis (MS). MethodsParticipants with MS(N=15) were randomly assigned into intervention(n=8) or waitlist control(n=7) conditions. The physical activity intervention was delivered over a 16-week period and outcomes were assessed at baseline and immediately following the 16-week period in both conditions. ResultsThere was a significant, positive effect of the intervention on overall RLS severity (p=.01;ηρ2=.43), severity during the night(p=.03,ηρ2=.35), severity during the day while resting(p=.01,ηρ2=.44), and severity during the day while active(p<.01,ηρ2=.61), and non-significant improvements in RLS severity while falling asleep (p=.33,ηρ2=.09). There were significant positive effects on sleep satisfaction(p<.01,ηρ2=.49) and non-significant improvements in self-reported global sleep quality(p=.35,ηρ2=.08). There was a significant intervention effect on self-reported time in bed(p=.03,ηρ2=.37) and total sleep time(p=.03,ηρ2=.36), and non-significant improvements in self-reported sleep latency (p=.08,ηρ2=.25), sleep efficiency(p=.27,ηρ2=.11), and daytime sleepiness (p=.52,ηρ2=.04;p=.35,ηρ2=.08;p=.51,ηρ2=.04). There was no significant effect of the intervention on device-measured sleep quality. ConclusionsWe provide preliminary evidence for the feasibility and efficacy of a physical activity intervention for reducing RLS severity and potentially improving self-reported sleep outcomes in adults with MS. ClinicalTrials.gov Identification NumberNCT04061681