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.

"I Don't Believe in Age; I Believe in Staying Enthusiastic": An Exploratory Qualitative Study into Recruitment Strategies Stimulating Middle-Aged and Older Adults to Join Physical Activity Interventions.

Many middle-aged and older adults (MAOAs) do not engage in sufficient physical activity (PA), despite its well-documented benefits for healthy aging. Existing PA interventions often fail to reach or engage the target population effectively. This study investigates MAOAs' preferences for recruitment strategies to optimize the reach and uptake of PA interventions, thereby enhancing their impact on healthy aging and public health. Qualitative interviews were conducted with 39 MAOA participants (69% female, mean age = 69.46, SD = 7.07), guided by McGuire's Theory on Persuasive Communication. Factors related to the source, message content, channel, receiver characteristics and target behavior of recruitment strategies were analyzed. Our findings suggest a preference for trustworthy sources (e.g., healthcare professionals over commercial entities) and positive, non-ageist messaging. MAOAs vary in their channel preferences but emphasize the importance of personalization. Despite heterogeneity, MAOAs commonly perceive themselves as sufficiently active, indicating a need for improved knowledge on what constitutes sufficient PA, as well as easy enrollment or trying out interventions. Tailoring recruitment strategies to diverse MAOA segments based on age seems crucial for effective engagement. Future research could explore quantitative research into how communication factors relate to various target population characteristics.

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.

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.

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.

Selecting interventions for a psychosocial support program for prostate cancer patients undergoing active surveillance: A modified Delphi study.

OBJECTIVE: Curative treatment of low-risk prostate cancer (LR-PCa) does not improve cancer specific survival and active surveillance (AS) is recommended. Although AS is cost-effective and reduces treatment-related complications, it requires psychosocial support. Research on psychosocial interventions specifically focused on men undergoing AS is limited. Aim of this study is to reach consensus amongst relevant stakeholders on selecting interventions offering psychosocial support to PCa patients during AS. METHODS: In accordance with the RAND/UCLA method, a modified Delphi approach was used to establish consensus on selecting interventions. During phase one, interventions were identified through a literature review and open survey among all participants. During phase two, three consensus rounds were conducted to rate potential interventions and obtain statistical consensus. The IQ healthcare consensus tool was used to calculate statistical consensus. RESULTS: After the first consensus round, 31 participants scored individual interventions on relevance using a 9-point Likert scale resulting in the selection of six interventions. During the second consensus round 13 discussion items were reviewed during a focus group. After the third consensus round, seven additional interventions were selected by 23 participants. CONCLUSIONS: In total, 13 interventions were selected for inclusion in a support program. This included four interventions within the domain information and education, three within coping and support, one intervention within physical wellbeing and four within the domain lifestyle.

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.

What interventions affect the psychosocial burden experienced by prostate cancer patients undergoing active surveillance? A scoping review.

PURPOSE: Living with untreated prostate cancer (PCa) may cause anxiety and uncertainty in men undergoing active surveillance (AS). Developing a psychosocial support program for such patients might promote psychosocial well-being and patient engagement. This review aims to identify interventions with the potential to influence the psychosocial burden of prostate cancer patients undergoing AS. METHODS: A scoping review was conducted in accordance with the PRISMA Extension for Scoping Reviews Checklist. A systematic search was conducted in six databases and included publications dating from 2009. All available and eligible evidence was included in this review. RESULTS: After screening 2824 articles, 12 studies were included in the review: nine quantitative, one qualitative, and two mixed method papers. The relative strength of these studies was limited and the quality of most was moderate. CONCLUSIONS: The described interventions can be categorized into three major themes: information and education, coping and (psycho)social support, and lifestyle. Psychosocial support for men undergoing AS should entail involvement of family and spouse during the decision-making process, tailored information about PCa treatments, risks, benefits, protocols, lifestyle adjustments, and complementary and alternative medicine. Assessment and promotion of effective coping and self-management strategies are recommended. Healthcare providers should actively promote physical activity and nutritional improvements. Physical activity programs may also be helpful in facilitating peer support, which is especially important for men with limited social support. Future research should investigate combining interventions to increase efficacy and optimize supportive care during AS.

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 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.

Long-Term Effects on Loneliness of a Computer-Tailored Intervention for Older Adults With Chronic Diseases: A Randomized Controlled Trial.

Objectives: This study explores the effects of the Active Plus intervention aiming to decrease loneliness among older adults (>65 years) with chronic diseases. Methods: A randomized controlled trial (RCT) was performed (N = 585; age: M = 74.5 years, SD = 6.4), assessing loneliness at baseline, 6 months and 12 months. Outcome measures in the multilevel linear regression analyses were total, social and emotional loneliness. Results: At 12 months, significant decreases in total (B = -.37, p = .01) and social loneliness (B = -.24, p = .02) were found. Age was a significant moderator for total and social loneliness; however, the intervention was effective only for participants aged 80 years and older. Discussion: The Active Plus intervention showed a significant decrease in total and social loneliness and was especially beneficial for the vulnerable age group of 80 years and older. A more comprehensive tool for measuring social activity and mobility impairments, and using a longer time frame to detect loneliness changes, may form interesting future research.

Equity-specific effects of interventions to promote physical activity among middle-aged and older adults: results from applying a novel equity-specific re-analysis strategy.

BACKGROUND: Reducing inequalities in physical activity (PA) and PA-associated health outcomes is a priority for public health. Interventions to promote PA may reduce inequalities, but may also unintentionally increase them. Thus, there is a need to analyze equity-specific intervention effects. However, the potential for analyzing equity-specific effects of PA interventions has not yet been sufficiently exploited. The aim of this study was to set out a novel equity-specific re-analysis strategy tried out in an international interdisciplinary collaboration. METHODS: The re-analysis strategy comprised harmonizing choice and definition of outcomes, exposures, socio-demographic indicators, and statistical analysis strategies across studies, as well as synthesizing results. It was applied in a collaboration of a convenience sample of eight European PA intervention studies in adults aged ≥45 years. Weekly minutes of moderate-to-vigorous PA was harmonized as outcome. Any versus no intervention was harmonized as exposure. Gender, education, income, area deprivation, and marital status were harmonized as socio-demographic indicators. Interactions between the intervention and socio-demographic indicators on moderate-to-vigorous PA were analyzed using multivariable linear regression and random-effects meta-analysis. RESULTS: The collaborative experience shows that the novel re-analysis strategy can be applied to investigate equity-specific effects of existing PA interventions. Across our convenience sample of studies, no consistent pattern of equity-specific intervention effects was found. Pooled estimates suggested that intervention effects did not differ by gender, education, income, area deprivation, and marital status. CONCLUSIONS: To exploit the potential for equity-specific effect analysis, we encourage future studies to apply the strategy to representative samples of existing study data. Ensuring sufficient representation of 'hard to reach' groups such as the most disadvantaged in study samples is of particular importance. This will help to extend the limited evidence required for the design and prioritization of future interventions that are most likely to reduce health inequalities.

A randomized controlled trial into the cognitive effects of a computer-tailored physical activity intervention in older adults with chronic disease(s).

BACKGROUND: Cognitive functioning (CF) is important for wellbeing and an independent life. However, older adults with chronic diseases are at a higher risk of poorer CF levels. Although, research suggests that physical activity (PA) could play an essential role in maintaining good CF, older adults with chronic diseases have low levels of PA. PA interventions to prevent cognitive decline for this specific group exist. Yet, until now these interventions focused on a single specific chronic disease. Active Plus is a proven effective computer-tailored PA stimulating intervention focused on increasing PA in daily life for the older adult population suffering from a broad range of chronic diseases. This study tests the cognitive effects of Active Plus in older adults with chronic diseases. METHODS: In this RCT older adults with at least one chronic disease (≥65 years) were allocated to the intervention group (N = 260, mean age = 74.2) or waiting list control group (N = 325, mean age = 74.5). In total, intervention group participants received three times computer-tailored PA stimulating advice within four months (i.e., at baseline, after two months, and after three to four months). The online and print delivered advice were tailored to the specific needs and wishes of the participant and focused on incorporating PA in daily life. Baseline and follow-up measurements of the CF verbal memory (Verbal Learning Test), shifting (Trailmaking Test), inhibition (Stop-signal Task) and processing speed (Letter Digit Substitution Test) were assessed after six and 12 months. Intervention effects were analyzed with multilevel linear mixed-effects models adjusted for the clustered design and confounding variables. RESULTS: The dropout rate was 19.1% after 6 months and 25.1% after 12 months. Although both conditions improved on all verbal memory outcomes after 6 months, and all CF outcomes except inhibition after 12 months, no intervention effects were found, not even in subgroups (p > .05). CONCLUSIONS: To our knowledge this is the first study to test the cognitive effects of a computer-tailored PA stimulating intervention in older adults suffering from a broad range of chronic diseases. The effects of the Active Plus intervention were not strong enough to improve CF or prevent cognitive decline. A blended approach, in which this computer-tailored intervention is combined with a face-to-face PA intervention and / or cognitive training, might be a good suggestion to increase the effects of Active Plus on PA and CF in older adults with chronic diseases. TRIAL REGISTRATION: Netherlands Trial Register NL6005; Date of Registration 03-21-2017; https://www.trialregister.nl/trial/6005.

An exploration of perceptions and preferences for healthy eating in Dutch consumers: a qualitative pilot study.

BACKGROUND: Unhealthy dietary patterns are highly prevalent in Western countries, and they have been associated with depression, hypertension, heart disease, cancer, type 2 diabetes, and obesity. Many dietary interventions have been developed to promote healthier dietary behavior, yet most do not achieve the intended dietary change. This study aims to provide a better understanding of what Dutch consumers perceive as a healthy diet, how this relates to the current Dutch nutrition guidelines, and their preferences for how to eat more healthily. This is an essential consideration for the development of tailored interventions aimed to help people adopt changes in their dietary behavior. METHODS: Seventy-eight participants filled in an online questionnaire containing both open-ended and closed-ended questions. The qualitative data was analyzed using content analysis resulting in a classification scheme. Two students then identified to which category each part of a participant's answer belonged. RESULTS: For both the perception of a healthy diet and how to eat healthily, four major categories and a residual category were identified: dietary patterns, food processing, food products, content/nutrients, and non-food. These major categories consisted of several categories. The results showed that how people perceived a healthy diet was mostly represented at the level of food product (vegetables and fruit) and the content/nutrient level (carbohydrates), whereas how they would like to eat healthily was mostly represented at the level of food processing (preparation), food product (vegetables), and dietary patterns (amount). CONCLUSIONS: Our findings are mostly in line with how the Dutch dietary guidelines are communicated ("product level"). However, consumers primarily mention single aspects instead of naming the guidelines as a whole. Health policymakers can use this insight in future communications regarding the guidelines to the general public. A challenge for future (eHealth) diet interventions is how to implement and tailor dietary information that optimally connects with the perceptions of the target population.

Psychiatric and behavioral problems and well-being in gerontopsychiatric nursing home residents.

OBJECTIVES: Gerontopsychiatric nursing home residents are residents with a chronic mental condition (not dementia), in combination with one or more physical disorders. Psychiatric and behavioral problems are common within this population. The objective of this study is to examine these behaviors and their relationship to the level of both observed and self-rated well-being in the gerontopsychiatric population. METHOD: Both gerontopsychiatric residents, and their primary formal caregiver in several nursing homes in The Netherlands were asked to participate in a structured interview concerning psychiatric and behavioral problems and resident well-being. Psychiatric and behavioral problems were measured with the Neuropsychiatric Inventory Questionnaire (NPI-Q) and the Cohen Mansfield Agitation Index (CMAI). Well-being was measured through the self-rated Laurens Well-being Inventory for Gerontopsychiatry (LWIG), and the observer rated Laurens Well-being Observations for Gerontopsychiatry (LWOG). RESULTS: A total of 126 residents participated in the study with ages varying from 42 to 90. Different types of chronic mental disorders such as schizophrenia spectrum disorder, bipolar disorders and personality disorders were prevalent in the population. Most psychiatric and behavioral problems are associated with lower observed and self-rated well-being. For irritability and affective problem behaviors the relationship with well-being was the most evident. CONCLUSION: In daily care practice the relationship between well-being and psychiatric and behavioral problems should be taken into account in care planning and treatment. To further explore the direction and details of this relationship, more research is needed.