The efficacy of online physical activity interventions with added mobile elements within adults aged 50 years and over: Randomized controlled trial.

Electronic health (eHealth) and mobile health (mHealth) could stimulate physical activity (PA) in a time-efficient and cost-effective way. This randomized controlled trial aims to investigate effects on moderate-to-vigorous PA (MVPA) of different combined computer- and mobile-based PA interventions targeted at adults aged 50 years and over. Participants (N = 954) were randomly allocated to a basic existing computer-based intervention (Active Plus [AP] or I Move [IM]) supplemented with one of three mobile elements being (1) activity tracker (AT), (2) ecological momentary intervention (EMI), or (3) chatbot (CB) or a control group (CG). MVPA was assessed via the SQUASH at baseline (T0), 3 months (T1), and 6 months (T2) and via accelerometers at T0 and T2. No intervention effects were found on objective (p = .502) and subjective (p = .368) MVPA for main research groups (AP/IM + AT, AP/IM + EMI, AP/IM + CB). Preliminary MVPA findings for subgroups (AP + AT, AP + EMI, AP + CB, IM + AT, IM + EMI, IM + CB) combined with drop-out data showed potential for the computer-based intervention AP with an integrated AT. Based on these preliminary findings, eHealth developers can be recommended to integrate ATs with existing computer-based PA interventions. However, further research is recommended to confirm the findings as a result of the exploratory nature of the subgroup analyses.

Recruitment strategies for reaching adults aged 50 years and older with low socioeconomic status for participation in online physical activity interventions.

Background: Generally, the health condition of those with higher socioeconomic status (SES) is better compared to those with lower SES. The application of appropriate strategies to reach low SES populations with electronic health (eHealth) interventions is thus of major importance to reduce health inequalities. eHealth-studies providing detailed information on recruitment strategies are scarce, despite the fact that this information is crucial for comparable research and implementation. Objective: To provide insight into the reach, sample characteristics and costs of three pre-planned strategies for recruiting adults aged 50 years and older with low SES for participation in an online physical activity intervention, as part of a field study. Methods: Recruitment took place via (1) invitation letters via a municipality, (2) gyms and (3) social media advertisements, aiming to include 400 participants. Additional procedures were followed to reach specifically the low SES group. Response rates, sociodemographic characteristics and costs per strategy were assessed. Results: The highest response was shown for the municipality approach (N = 281), followed by social media (N = 71) and gyms (N = 45). Ten participants were recruited via family/friends. The most low-educated participants were reached via the municipality (N = 128) followed by social media (N = 9), gyms (N = 8) and family/friends (N = 5). Recruitment costs were with €2,142.37 the highest for the municipality compared to €96.81 for social media and no costs for gyms. Conclusions: Recruitment via invitation letters through a municipality has the highest potential for reaching low SES participants of the three applied strategies, although the higher recruitment costs need to be taken into account.

Process and effect evaluation of a referral aid for smoking cessation counselling in primary care: Findings of a randomized controlled trial.

INTRODUCTION: This study explored the use and effects of a smoking cessation referral in: 1) practice nurses (PNs), and 2) smokers. The use of evidence-based smoking cessation interventions (EBSCIs) can double the likelihood of a successful smoking cessation attempt. A referral aid was developed to aid Dutch PNs in primary care in deciding which smokers are the most suitable for EBSCI. METHODS: Two different studies were conducted: 1) a randomized controlled trial with a process evaluation (n=82) and effect evaluation (n=285) among smoking patients recruited by PNs (n=73), and 2) a process evaluation among a subgroup of PNs (n=40) from January 2019 to September 2020. RESULTS: Overall, the response in both groups was low. PNs found the referral aid materials clear and understandable. Smokers had similar but (slightly) less-positive opinions. The smokers in both groups did not differ in the amount of discussion and use of EBSCIs, nor on smoking abstinence. CONCLUSIONS: Further research should assess how to better involve PNs and smokers when recruiting for an RCT and how to foster effective counselling. Additional research should also look deeper into barriers to referral of both PNs and smokers, and how to stimulate referral to EBSCIs best and help smokers to make a decision; for example by implementing a simplified strategy both within the primary care setting and outside, by involving other healthcare professionals or options outside healthcare such as the workplace and social domain. Trial registration: The study was registered at the Netherlands Trial Register (NL7020, https://www.trialregister.nl/trial/7020).

The facilitators and barriers of mHealth adoption and use among people with a low socio-economic position: A scoping review.

Background: Despite the fact that 95% of the global population has a mobile phone, the adoption of mHealth lags among people with a low socio-economic position (SEP). As they face health risks and many barriers in the traditional offline healthcare system, mHealth has an important role. Therefore, it is important to understand the factors that promote and impede mHealth adoption among people with a lower SEP. Objective: The current study aims to provide an overview of what is known about the facilitators and barriers to the adoption and use of autonomous mHealth applications among people with low SEP. Methods: A PRISMA scoping review in which the scientific databases PubMed, Web of Science, PsychInfo and SocINDEX were searched in the period of March 2017 to March 2022. Results: Of the 1827 indexed papers, 13 papers were included in the review. In these papers, 30 factors have been identified as promoting or hindering the adoption of autonomous mHealth applications among low SEP people. Conclusions: Thirty factors were found to facilitate or impede mHealth adoption among people with a low SEP, categorised into intrapersonal, interpersonal, community, ecological and app specific levels. Factors are assumed to be interrelated. The relationship between traditional (offline) care and digital care appeared to be of particular interest as the current study revealed that face-to-face contact is a prerequisite of mHealth adoption among people with low SEP. Therefore, a well-structured cosmopolitan system of stakeholders has been recommended. Trial registration: This study was registered in OSF (https://doi.org/10.17605/OSF.IO/ATU9D).

Long-term efficacy of a computer-tailored physical activity intervention for prostate and colorectal cancer patients and survivors: A randomized controlled trial.

BACKGROUND: Physical activity (PA) can improve the physical and psychological health of prostate and colorectal cancer survivors, but PA behavior change maintenance is necessary for long-term health benefits. OncoActive is a print- and web-based intervention in which prostate and colorectal cancer patients and survivors receive automatically generated, personalized feedback aimed at integrating PA into daily life to increase and maintain PA. We evaluated the long-term outcomes of OncoActive by examining the 12-month follow-up differences between OncoActive and a control group, and we explored whether PA was maintained during a 6-month non-intervention follow-up period. METHODS: Prostate or colorectal cancer patients were randomly assigned to an OncoActive (n = 249) or a usual care waitlist control group (n = 229). OncoActive participants received PA advice and a pedometer. PA outcomes (i.e., ActiGraph and self-report moderate-to-vigorous intensity PA (MVPA) min/week and days with ≥30 min PA) and health-related outcomes (i.e., fatigue, depression, physical functioning) were assessed at baseline, 6 months, and 12 months. Differences between groups and changes over time were assessed with multilevel linear regressions for the primary outcome (ActiGraph MVPA min/week) and all additional outcomes. RESULTS: At 12 months, OncoActive participants did not perform better than control group participants at ActiGraph MVPA min/week, self-report MVPA min/week, or ActiGraph days with PA. Only self-report days with PA were significantly higher in OncoActive compared to the control group. For health-related outcomes only long-term fatigue was significantly lower in OncoActive. When exploratively examining PA within OncoActive, the previously found PA effects at the end of the intervention (6 months follow-up) were maintained at 12 months. Furthermore, all PA outcomes improved significantly from baseline to 12 months. The control group showed small but non-significant improvements from 6 months to 12 months (and from baseline to 12 months), resulting in a decline of differences between groups. CONCLUSION: The majority of previously reported significant between-group differences at 6 months follow-up were no longer present at long-term follow-up, possibly because of natural improvement in the control group. At long-term follow-up, fatigue was significantly lower in OncoActive compared to control group participants. Computer-tailored PA advice may give participants an early start toward recovery and potentially contributes to improving long-term health.

The Adoption of a COVID-19 Contact-Tracing App: Cluster Analysis.

BACKGROUND: During the COVID-19 pandemic, there was limited adoption of contact-tracing apps (CTAs). Adoption was particularly low among vulnerable people (eg, people with a low socioeconomic position or of older age), while this part of the population tends to have lesser access to information and communication technology and is more vulnerable to the COVID-19 virus. OBJECTIVE: This study aims to understand the cause of this lagged adoption of CTAs in order to facilitate adoption and find indications to make public health apps more accessible and reduce health disparities. METHODS: Because several psychosocial variables were found to be predictive of CTA adoption, data from the Dutch CTA CoronaMelder (CM) were analyzed using cluster analysis. We examined whether subgroups could be formed based on 6 psychosocial perceptions (ie, trust in the government, beliefs about personal data, social norms, perceived personal and societal benefits, risk perceptions, and self-efficacy) of (non)users concerning CM in order to examine how these clusters differ from each other and what factors are predictive of the intention to use a CTA and the adoption of a CTA. The intention to use and the adoption of CM were examined based on longitudinal data consisting of 2 time frames in October/November 2020 (N=1900) and December 2020 (N=1594). The clusters were described by demographics, intention, and adoption accordingly. Moreover, we examined whether the clusters and the variables that were found to influence the adoption of CTAs, such as health literacy, were predictive of the intention to use and the adoption of the CM app. RESULTS: The final 5-cluster solution based on the data of wave 1 contained significantly different clusters. In wave 1, respondents in the clusters with positive perceptions (ie, beneficial psychosocial variables for adoption of a CTA) about the CM app were older (P<.001), had a higher education level (P<.001), and had higher intention (P<.001) and adoption (P<.001) rates than those in the clusters with negative perceptions. In wave 2, the intention to use and adoption were predicted by the clusters. The intention to use CM in wave 2 was also predicted using the adoption measured in wave 1 (P<.001, ß=-2.904). Adoption in wave 2 was predicted by age (P=.022, exp(B)=1.171), the intention to use in wave 1 (P<.001, exp(B)=1.770), and adoption in wave 1 (P<.001, exp(B)=0.043). CONCLUSIONS: The 5 clusters, as well as age and previous behavior, were predictive of the intention to use and the adoption of the CM app. Through the distinguishable clusters, insight was gained into the profiles of CM (non)intenders and (non)adopters. TRIAL REGISTRATION: OSF Registries osf.io/cq742; https://osf.io/cq742.

Adding Mobile Elements to Online Physical Activity Interventions for Adults Aged Over 50 Years: Prototype Development Study.

BACKGROUND: Only a minority of adults aged over 50 years meet physical activity (PA) guidelines of the World Health Organization (WHO). eHealth interventions are proven effective tools to help this population increase its PA levels in the short term, among which the Active Plus and I Move interventions have been developed by our own research group. To achieve long-term effects, increase intervention use, and decrease dropout rates, 3 emergent but different mobile elements (an activity tracker, an ecological momentary intervention [EMI] program, and a chatbot) were added separately to Active Plus and I Move. In this study, the prototype development and pilot-testing of these interventions is described. OBJECTIVE: This study aims to enhance 2 existing PA-stimulating computer-based interventions with 3 mobile elements (an activity tracker, an EMI program, or a chatbot) and test the prototypes on usability and appreciation within a target population of adults aged over 50 years. METHODS: A systematic design protocol consisting of development, evaluation, and adaptation procedures was followed with involvement of the target population. Literature searches separated per mobile element and interviews with the target population (N=11) led to 6 prototypes: Active Plus or I Move including (1) an activity tracker, (2) EMI, or (3) a chatbot. These prototypes were tested on usability and appreciation during pilot tests (N=47) and subsequently fine-tuned based on the results. RESULTS: The literature searches and interviews provided important recommendations on the preferences of the target population, which enabled us to develop prototypes. The subsequent pilot tests showed that the mobile elements scored moderate to good on usability, with average System Usability Scale (SUS) scores of 52.2-82.2, and moderate to good on enjoyment and satisfaction, with average scores ranging from 5.1 to 8.1 on a scale of 1-10. The activity tracker received the best scores, followed by EMI, followed by the chatbot. Based on the findings, the activity tracker interventions were fine-tuned and technical difficulties regarding EMI and the chatbot were solved, which is expected to further improve usability and appreciation. CONCLUSIONS: During this study, 6 prototypes of online PA interventions with added mobile elements were developed and tested for usability and appreciation. Although all prototypes scored moderate to high on usability, enjoyment, and satisfaction, it can be concluded that the integration of an activity tracker with a computer-based PA intervention is the most promising option among the 3 mobile elements tested during this study. The prototype development steps of the systematic design protocol followed can be considered useful and successful for the purposes of this study. The interventions can now be evaluated on a larger scale through a randomized controlled trial. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/31677.

Digital health interventions to improve eating behaviour of people with a lower socioeconomic position: a scoping review of behaviour change techniques.

Specific approaches are needed to reach and support people with a lower socioeconomic position (SEP) to achieve healthier eating behaviours. There is a growing body of evidence suggesting that digital health tools exhibit potential to address these needs because of its specific features that enable application of various behaviour change techniques (BCTs). The aim of this scoping review is to identify the BCTs that are used in diet-related digital interventions targeted at people with a low SEP, and which of these BCTs coincide with improved eating behaviour. The systematic search was performed in 3 databases, using terms related to e/m-health, diet quality and socioeconomic position. A total of 17 full text papers were included. The average number of BCTs per intervention was 6.9 (ranged 3-15). BCTs from the cluster 'Goals and planning' were applied most often (25x), followed by the clusters 'Shaping knowledge' (18x) and 'Natural consequences' (18x). Other frequently applied BCT clusters were 'Feedback and monitoring' (15x) and 'Comparison of behaviour' (13x). Whereas some BCTs were frequently applied, such as goal setting, others were rarely used, such as social support. Most studies (n = 13) observed a positive effect of the intervention on eating behaviour (e.g. having breakfast) in the low SEP group, but this was not clearly associated with the number or type of applied BCTs. In conclusion, more intervention studies focused on people with a low SEP are needed to draw firm conclusions as to which BCTs are effective in improving their diet quality. Also, further research should investigate combinations of BCTs, the intervention design and context, and the use of multicomponent approaches. We encourage intervention developers and researchers to describe interventions more thoroughly, following the systematics of a behaviour change taxonomy, and to select BCTs knowingly.

Addendum: The Dutch COVID-19 Notification App: Lessons Learned From a Mixed Methods Evaluation Among End Users and Contact-Tracing Employees.

[This corrects the article DOI: 10.2196/38904.].

Determinants of physical activity behaviour change in (online) interventions, and gender-specific differences: a Bayesian network model.

BACKGROUND: Physical activity (PA) is known to be beneficial for health, but adherence to international PA guidelines is low across different subpopulations. Interventions have been designed to stimulate PA of different target groups by influencing relevant psycho-social determinants, essentially based on a combination of the Integrated Model for Change, the Theory of Planned Behaviour, its successor the Reasoned Action Approach and the self-determination theory. The current study investigates the pathways through which interventions influence PA. Further, gender differences in pathways of change are studied. METHODS: An integrated dataset of five different randomised controlled trial intervention studies is analysed by estimating a Bayesian network. The data include measurements, at baseline and at 3, 6 (short-term), and 12 (long-term) months after the baseline, of important socio-cognitive determinants of PA, demographic factors, and PA outcomes. A fragment is extracted from the Bayesian network consisting of paths between the intervention variable, determinants, and short- and long-term PA outcomes. For each relationship between variables, a stability indicator and its mutual information are computed. Such a model is estimated for the full dataset, and in addition such a model is estimated based only on male and female participants' data to investigate gender differences. RESULTS: The general model (for the full dataset) shows complex paths, indicating that the intervention affects short-term PA via the direct determinants of intention and habit and that self-efficacy, attitude, intrinsic motivation, social influence concepts, planning and commitment have an indirect influence. The model also shows how effects are maintained in the long-term and that previous PA behaviour, intention and attitude pros are direct determinants of long-term PA. The gender-specific models show similarities as well as important differences between the structures of paths for the male- and female subpopulations. For both subpopulations, intention and habit play an important role for short-term effects and maintenance of effects in the long-term. Differences are found in the role of self-efficacy in paths of behaviour change and in the fact that attitude is relevant for males, whereas planning plays a crucial role for females. The average of these differences in subpopulation mechanisms appears to be presented in the general model. CONCLUSIONS: While previous research provided limited insight into how interventions influence PA through relevant determinants, the Bayesian network analyses show the relevance of determinants mentioned by the theoretical framework. The model clarifies the role that different determinants play, especially in interaction with each other. The Bayesian network provides new knowledge about the complex working mechanism of interventions to change PA by giving an insightful overview of influencing paths. Furthermore, by presenting subpopulation-specific networks, the difference between the influence structure of males and females is illustrated. These new insights can be used to improve interventions in order to enhance their effects. To accomplish this, we have developed a new methodology based on a Bayesian network analysis which may be applicable in various other studies.

Factors Associated With Intention and Use of e-Mental Health by Mental Health Counselors in General Practices: Web-Based Survey.

BACKGROUND: Mental health care counselors have a high intention to use e-mental health (EMH), whereas actual use is limited. Facilitating future use requires insight into underlying factors as well as eligibility criteria that mental health care counselors use in their decision to apply EMH. OBJECTIVE: The aim of this study was to unfold the intention and underlying reasons for mental health counselors to use EMH and to unveil the criteria they use to estimate patient eligibility for EMH. The theoretical framework was based on the reasoned action approach model, the Unified Theory of Acceptance and Use of Technology, and the Measurement Instrument for Determinants of Innovation model. METHODS: To empirically validate our theoretical model, a web-based survey was conducted among mental health care counselors (n=132). To unveil the eligibility criteria, participants were asked to rank their reasons for considering EMH suitable or unsuitable for a patient. RESULTS: The mean intention to use EMH was positive (mean 4.04, SD 0.64). The mean use of EMH before the COVID-19 pandemic was 38% (mean 0.38, SD 0.22), and it was 49% (mean 0.49, SD 0.25) during the pandemic. In total, 57% of the patient population was considered eligible for EMH. Usefulness and benefits (ß=.440; P<.001), Task perception (ß=.306; P=.001), and Accessibility (ß=.140; P=.02) explained the intention to use EMH (F3,131=54.151; P<.001; R2=0.559). In turn, intention explained patient eligibility (F1,130=34.716; P<.001; R2=0.211), whereas intention and patient eligibility explained EMH use (F2,129=41.047; P<.001; R2=0.389). Patient eligibility partially mediated the relationship between intention to use EMH and EMH use, with a larger direct effect (c'=0.116; P<.001) than indirect effect (c=0.065, 95% CI 0.035-0.099; P<.001). Mental health counselors assessed patients' eligibility for EMH mainly through the availability of computers and the internet and patient motivation. CONCLUSIONS: To stimulate the use of EMH, intention and patient eligibility need to be influenced. Intention, in turn, can be enhanced by addressing the perceived usefulness and benefits of EMH, perceived accessibility, and task perception. Access to a computer and patients' motivation to use EMH are important in facilitating patient eligibility. To cause an impact with EMH in general practice, mental health counselors need to be convinced of the benefits of EMH and transfer this enthusiasm to the patient. It is recommended to involve mental health counselors in the development of EMH to increase the (perceived) added value and use.

How to persuade more primary care professionals to adopt a valued smoking cessation referral aid: a cross-sectional study of facilitators and barriers.

BACKGROUND: To study the factors associated with the intention of primary care professionals (PCPs) to use or not use a referral aid (RA) for selecting an evidence-based smoking cessation intervention (EBSCI). METHODS: Participants (n = 85) were recruited from June to September 2020 to complete an online questionnaire based on the I-Change Model to assess the factors associated with the adoption of RA. The differences between PCPs with (n = 37) and without (n = 48) the intention to adopt in terms of demographics, motivational factors, and post-motivational factors were subsequently assessed. Correlation and logistic regression analyses were conducted to investigate the factors associated with the intention to adopt. RESULTS: Both groups indicated that they highly appreciated the RA. However, PCPs without the intention to adopt expressed a more negative attitude towards the RA, experienced less social support, showed low self-efficacy, and encountered barriers such as lack of time and skills. The factors most strongly associated with the intention to adopt were advantages, disadvantages, self-efficacy, less barriers, working in a solo practice and age. CONCLUSIONS: The adoption of RA can be facilitated in two ways. The first one is by increasing the added value of the tool through a second round of co-creation focusing on the adoptability of the RA in practice. The second approach is by communicating the added value of referring to EBSCIS and thereby using the RA by implementing it in smoking cessation training for PCPs, which could also help to improve the attitude, social support, self-efficacy, and perceived skills in terms of RA usage among PCPs. IMPACT: This study is the first work in the Netherlands to investigate the willingness of PCPs to actively refer patients to other EBSCIs in addition to providing face-to-face counseling themselves. TRIAL REGISTRATION: The study was registered at the Netherlands Trial Register (NL7020, https://www.trialregister.nl/trial/7020 ).

The Dutch COVID-19 Notification App: Lessons Learned From a Mixed Methods Evaluation Among End Users and Contact-Tracing Employees.

BACKGROUND: The Dutch CoronaMelder (CM) app is the official Dutch contact-tracing app (CTA). It has been used to contain the spread of the SARS-CoV-2 in the Netherlands. It allows its users and those of connected apps to anonymously exchange warnings about potentially high-risk contacts with individuals infected with the SARS-CoV-2. OBJECTIVE: The goal of this mixed methods study is to understand the use of CTA in the pandemic and its integration into the Municipal Health Services (MHS) efforts of containment through contact tracing. Moreover, the study aims to investigate both the motivations and user experience-related factors concerning adherence to quarantine and isolation measures. METHODS: A topic analysis of 56 emails and a web-based survey of 1937 adults from the Netherlands, combined with a series of 48 in-depth interviews with end users of the app and 14 employees of the Dutch MHS involved in contact tracing, were conducted. Mirroring sessions were held (n=2) with representatives from the development (n=2) and communication teams (n=2) responsible for the creation and implementation of the CM app. RESULTS: Topic analysis and interviews identified procedural and technical issues in the use of the CTA. Procedural issues included the lack of training of MHS employees in the use of CTAs. Technical issues identified for the end users included the inability to send notifications without phone contact with the MHS, unwarranted notifications, and nightly notifications. Together, these issues undermined confidence in and satisfaction with the app's use. The interviews offered a deeper understanding of the various factors at play and their effects on users; for example, the mixed experiences of the app's users, the end user's own fears, and uncertainties concerning the SARS-CoV-2; problematic infrastructure at the time of the app's implementation on the side of the health services; the effects of the society-wide efforts in containment of the SARS-CoV-2 on the CM app's perception, resulting in further doubts concerning the app's effectiveness among MHS workers and citizens; and problems with adherence to behavioral measures propagated by the app because of the lack of confidence in the app and uncertainty concerning the execution of the behavioral measures. All findings were evaluated with the app's creators and have since contributed to improvements. CONCLUSIONS: Although most participants perceived the app positively, procedural and technical issues identified in this study limited satisfaction and confidence in the CM app and affected its adoption and long-term use. Moreover, these same issues negatively affected the CM app's effectiveness in improving compliance with behavioral measures aimed at reducing the spread of the SARS-CoV-2. This study offers lessons learned for future eHealth interventions in pandemics. Lessons that can aid in more effective design, implementation, and communication for more effective and readily adoptable eHealth applications.

Adding Mobile Elements to Online Physical Activity Interventions Targeted at Adults Aged 50 Years and Older: Protocol for a Systematic Design.

BACKGROUND: Physical activity (PA) can increase mental and physical health in adults aged 50 years and older. However, it has been shown that PA guidelines are often not met within this population. Therefore, our research group developed 2 computer-tailored intervention programs in the last decade to stimulate PA: Active Plus and I Move. Although these programs were proven effective, positive effects diminished over time and attrition rates were relatively high. To respond to this, we will integrate 3 interactive mobile elements into the existing programs: activity tracker, ecological momentary intervention program, and virtual coach app. OBJECTIVE: The goal of the research is to define systematic and evidence-based steps for extending our online computer-based PA intervention programs with 3 interactive mobile elements. METHODS: Components often included in other (eHealth) design models were identified as key components and served as a base for the definition of systematic steps: exploration of context, involvement of the target population, prototype and intervention testing, and implementation. Based on these key components, 10 systematic steps were defined. The initial step is a literature search, with the results serving as a base for development of the low-fidelity prototypes in step 2. The pilot phase comprises the 3rd to 6th steps and includes semistructured interviews, pilot tests, and adaptations of the prototypes with intensive involvement of the target population of adults aged 50 years and older, where particular attention will be paid to lower educated persons. The 7th step is an effect evaluation in the form of a randomized controlled trial. During the 8th step, the most effective intervention programs will be selected and reinforced. These reinforced intervention programs will be used during the design of an implementation plan in the 9th step and the subsequent field study in the 10th step. RESULTS: The project will be executed from December 2019 to December 2023. During this period, the systematic approach presented will be practically executed according to the methodological procedures described. CONCLUSIONS: Based on the 4 identified key components, we were able to design an evidence-based systematic design approach for separately adding 3 mobile elements to our existing online PA intervention programs. The 10 steps are presented as a useful approach to guide future eHealth design studies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/31677.

The effects of a web-based computer-tailored diet and physical activity intervention based on self-determination theory and motivational interviewing: A randomized controlled trial.

Background: According to self-determination theory (SDT), autonomous forms of motivation are more likely to result in sustained behavioral changes than controlled forms. Principles of motivational interviewing (MI) can be applied to facilitate more autonomous forms of motivation. This study investigated whether a combined diet and physical activity (PA) web-based computer-tailored intervention based on SDT and MI, called MyLifestyleCoach, was effective in promoting dietary and PA behaviors. Methods: A two-arm randomized controlled trial with 1142 Dutch adults was conducted. The intervention and control group completed questionnaires at baseline, 6, and 12 months from baseline. Only participants in the intervention condition had access to MyLifestyleCoach. The waiting list control condition had access to the intervention after completing the 12-month follow-up questionnaire. A modified food frequency questionnaire was used to measure dietary behaviors (fruit, vegetables, fish, and unhealthy snacks). The Dutch Short Questionnaire to ASsess Health was used to measure the weekly minutes of moderate-to-vigorous PA (MVPA). Usage data, which is operationalized as completed sessions in this study, was objectively assessed by log data. We conducted two-step linear mixed effect models. In the first step, a model consisting of condition, time, potentially confounding variables and a random intercept for participants was tested. In the second step, an interaction term was added to investigate the intervention's (time × condition) and usage (time × opening session and time × completed sessions) effects over time for the dietary and PA outcomes. Results: The findings showed no differences between the groups for all four dietary behaviors and the weekly minutes of MVPA at any of the time points. In-depth analyses showed that participants who followed the opening session of the intervention, in which they received personalized feedback on their behaviors, had a stronger increase in fruit consumption at 6 months and 12 months than participants who did not follow the interventions' opening session. Lastly, participants who followed more sessions in the diet module had a stronger increase in fruit and vegetable consumption at 6 months, and a stronger decrease in the consumption frequency of unhealthy snacks at 12 months post-baseline. Conclusion: Overall, the intervention was not effective in changing dietary and PA behavior. However, moderation analyses suggest that the intervention is effective in changing dietary behavior for those participants who used the intervention more intensively. Further research should focus on improving intervention use.

Clustering of motivational constructs based on self-determination theory for diet and physical activity and their associations with behaviour: a cross-sectional study.

The present study explored whether motivational constructs for diet and physical activity (PA) cluster and how these motivational constructs relate to dietary and PA behaviour. Data of 1142 participants were used from a randomised controlled trial examining the effects of a web-based diet and PA promotion intervention based on self-determination theory and motivational interviewing. Motivation was assessed using the Treatment Self-Regulation Questionnaire and Behavioural Regulation in Exercise Questionnaire. The dietary outcomes were measured using an adapted Food Frequency Questionnaire. PA was assessed using the Short QUestionnaire to ASsess Health. Spearman rank-order correlations showed large correlation coefficients (rs ≥ 0⋅63) between similar motivational constructs between the two lifestyle domains, except for intrinsic motivation where a medium correlation coefficient was found (rs = 0⋅41). Furthermore, the exploratory factor analysis illustrated that more self-determined forms of motivation seem to be more domain-specific. In contrast, non-self-determined forms of motivation seem to be domain-independent. Last, regression analyses demonstrated that intrinsic motivation towards PA was the only motivational construct significantly positively associated with all PA sub-behaviours (standardised regression coefficients ranging from 0⋅17 to 0⋅28, all P < 0⋅0125). Intrinsic motivation to eat healthily was significantly positively associated with fruits, vegetables and fish intake (standardised regression coefficients ranging from 0⋅11 to 0⋅16, all P < 0⋅0125), but not with unhealthy snacks. Insight of this exploratory study is useful for understanding the interrelationships of motivational induced behaviours, the development of interventions targeting multiple behaviours, and the construction of questionnaires.

Do professional perspectives on evidence-based smoking cessation methods align? A Delphi study among researchers and healthcare professionals.

The use of evidence-based smoking cessation interventions (SCIs) can significantly increase the number of successful smoking cessation attempts. To obtain an overview of the knowledge and viewpoints on the effectiveness and use of SCIs, a three-round online Delphi study was conducted among researchers and primary care professionals (PCPs). The four objectives of this study are to gain an overview of (i) the criteria important for recommending SCIs, (ii) the perceptions of both groups on the effectiveness of SCIs, (iii) the factors to consider when counseling different (high-risk) groups of smokers and (iv) the perceptions of both groups on the use of e-cigarettes as an SCI. We found a high level of agreement within groups on which smoker characteristics should be considered when recommending an SCI to smokers. We also found that PCPs display a lower degree of consensus on the effectiveness of SCIs. Both groups see a value in the use of special protocols for different (high-risk) groups of patients, but the two groups did not reach consensus on the use of e-cigarettes as a means to quit. Making an inventory of PCPs' needs regarding SCIs and their usage may provide insight into how to facilitate a better uptake in the primary care setting.

Use and Appreciation of a Web-Based, Computer-Tailored Diet and Physical Activity Intervention Based on the Self-determination Theory: Evaluation Study of Process and Predictors.

BACKGROUND: eHealth is a promising tool for promoting lifestyle behaviors such as a healthy diet and physical activity (PA). However, making people use interventions is a crucial and challenging problem in eHealth. More insight into use patterns and predicting factors is needed to improve future interventions. OBJECTIVE: This study aims to examine the use, predictors of use, and appreciation of a web-based, computer-tailored, dietary and PA promotion intervention, MyLifestyleCoach, which is based on the self-determination theory. First, we depict the participants' flow in the intervention and identify moments when they are likely to discontinue use. Second, we investigate whether demographic, motivational, and program-related characteristics predict the use of several intervention elements. Finally, we report the appreciation scores for the intervention and the participant and program characteristics associated with these scores. METHODS: This study was based on data from web-based self-report questionnaires. Here, objectively assessed intervention use data were analyzed from participants randomized to the intervention condition. Multiple stepwise (logistic) regression analyses were conducted to examine the predictors of intervention use and evaluation scores. RESULTS: Our findings indicate a low full completion rate for the intervention among those who chose and completed the diet module (49/146, 33.6%), the PA module (2/12, 17%), and both modules (58/273, 21.2%). Several points in the intervention where participants were likely to stop using the intervention were identified. Autonomous and intrinsic motivation toward diet were related to the completion of the initial sessions of the intervention (ie, the opening session in which participants could choose which module to follow and the first session of the diet module). In contrast, controlled motivation was linked to the completion of both modules (initial and follow-up sessions). Appreciation scores were somewhat positive. Appreciation was predicted by several motivational constructs, such as amotivation and basic psychological needs (eg, competence) and program-related features (eg, number of completed sessions). CONCLUSIONS: This study adds meaningful information on the use and appreciation of a web-based, computer-tailored dietary and PA intervention, MyLifestyleCoach. The results indicate that different types of motivations, such as extrinsic and intrinsic motivation, are at play at the points when people are likely to stop using the intervention. The intervention was appreciated fairly well, and several motivational constructs and fulfillment of basic psychological needs were associated with appreciation. Practical implications of these findings have been provided in this study.

The Usability of an Online Tool to Promote the Use of Evidence-Based Smoking Cessation Interventions.

To increase usage of evidence-based smoking cessation interventions (EBSCIs) among smokers, an online decision aid (DA) was developed. The aims of this study were (1) to conduct a usability evaluation; (2) to conduct a program evaluation and evaluate decisional conflict after using the DA and (3) to determine the possible change in the intention to use EBSCIs before and directly after reviewing the DA. A cross-sectional study was carried out in September 2020 by recruiting smokers via the Internet (n = 497). Chi-squared tests and t-tests were conducted to test the differences between smokers who differed in the perceived usability of the DA on the program evaluation and in decisional conflict. The possible changes in intention to use EBSCIs during a cessation attempt before and after reviewing the DA were tested using t-tests, McNemar's test and χ2 analysis. The participants evaluated the usability of the DA as moderate (MU; n = 393, 79.1%) or good (GU; n = 104, 20.9%). GU smokers rated higher on all the elements of the program evaluation and experienced less decisional conflict, but also displayed a higher intention to quit. After reviewing the DA, the participants on average had a significantly higher intention to use more EBSCIs, in particular in the form of eHealth. Recommendations to make the DA more usable could include tailoring, using video-based information and including value clarification methods. Furthermore, a hybrid variant in which smokers can use the DA independently and with the guidance of a primary care professional could aid both groups in choosing a fitting EBSCI option.

The longitudinal associations between change in physical activity and cognitive functioning in older adults with chronic illness (es).

BACKGROUND: Regular physical activity (PA) is potentially beneficial for age-related cognitive decline. Although moderate-to-vigorous physical activity (MVPA) is mostly advised, older adults with chronic illnesses might benefit more from light physical activity (LPA), as they suffer from mobility problems, pain, and fatigue, limiting high-intensity PA. Therefore, the longitudinal association between change in LPA and MVPA and the change in cognitive functioning (CF) is investigated in older adults with chronic illnesses. METHODS: In total 432 older adults (mean age 73.7 [±6.1] years; 46.8% female) with at least one chronic illness participated in this longitudinal observational study. Longitudinal associations between accelerometer-assessed change in PA (LPA and MVPA) and change in CF, measured with an objective validated neuropsychological test battery, were tested with multivariate linear regressions. RESULTS: An increase in LPA between baseline and 6 months follow-up was significantly associated with improved short-term verbal memory and inhibition over the first 6 months. In addition, the change score in LPA over the first 6 months was predictive for the change score in short-term verbal memory over 12 months. Furthermore, an increase in MVPA between baseline and 6 months follow-up was significantly associated with a decrease in longer-term verbal memory scores over the same six-month period. CONCLUSIONS: For older adults with chronic illnesses who may experience difficulties in being sufficiently active, an increase in LPA is probably more achievable than an increase in MVPA. In addition, an increase in LPA enhances CF more than an increase in MVPA does. TRIAL REGISTRATION: Netherlands Trial Register NL6005 ; Date of Registration 21-03-2017.