Julia C. M. van Weert

Objective: Migrant patients with limited proficiency in the host country's dominant language(s) often face difficulties in making informed decisions about selecting communication strategies to overcome language barriers. This study evaluated MediLanguage’s Language Support Starter, an evidence-based digital decision aid developed through the Spiral Technology Action Research Model with migrant patients, usability experts, and healthcare providers, using an iterative process. This approach led to MediLanguage’s Language Support Starter, designed to empower patients to select appropriate communication strategies before language-discordant medical consultations, thereby facilitating shared decision-making with their healthcare providers (HCPs) during these consultations. Methods: A cluster-randomised controlled trial (RCT) was conducted in seven Dutch general practices, involving 18 participating HCPs and 75 Turkish-Dutch patients (31 in the control group and 44 in the intervention group; Mage = 61.79, SD = 12.40), all of whom had limited proficiency in Dutch. While questionnaires assessing HCPs’ demographics and perceived communication self-efficacy were administered once before the start of the trial, questionnaires were given to patients both before and after consultations. Control patients received standard care; intervention patients used MediLanguage’s Language Support Starter prior to their consultations. Results: There were no differences between HCPs in the intervention and control groups regarding their perceived communication self-efficacy. On a scale from 1 to 10, they scored an average of 7.30 (SD = 1.23), indicating a high level of confidence in their ability to communicate with Turkish-Dutch patients with limited Dutch language proficiency. MediLanguage was well received for its ease of use, comprehensiveness, and attractiveness to patients. While assessments of perceived shared decision-making, perceived decisional conflict, communication self-efficacy, and patient satisfaction were conducted, only patient satisfaction showed significant improvement. Conclusion: Although MediLanguage’s Language Support Starter did not demonstrate clear effectiveness in improving patient-reported outcomes, it may have raised HCPs’ and patients’ awareness of the importance of addressing language barriers properly in healthcare settings. Future research should investigate how MediLanguage’s Language Support Starter can be more effectively integrated into consultations to ensure that decisions on bridging language barriers are made and implemented. This would ensure equitable access to information for all patients.

Background: Mental wellness apps (MWAs) are increasingly used by young adults as demand for mental health support grows. The rapid adoption of AI in MWAs creates opportunities for more personalized care but also raises risks, including reduced user autonomy and sensitive data privacy concerns. Since MWAs are classified as “general wellness” tools, they fall outside the EU's Medical Devices Regulation, potentially leaving key public values unprotected. However, little is known about how a vulnerable subgroup of young adults, university students, assess or adopt MWAs, or how they weigh different public values in their decisions.Methods: A mixed-methods approach was employed combining semi-structured interviews and a hierarchical card sorting task. University students at a Dutch university (N=27) were interviewed on the role of 10 public values (autonomy, authenticity, agency, fairness, integrity, solidarity, privacy, security, trustworthiness, and transparency) in the decision-making process behind choosing to adopt an MWA. Additionally, they ranked these 10 values on importance in this process. Results: Reflexive thematic analysis yielded five themes: (1) motives for private MWA use, (2) tensions between digital resignation and privacy concerns, (3) how severity and urgency of mental health needs shape value trade-offs, (4) perceived personal benefits or drawbacks of specific values, and (5) sources of trust when adopting an MWA. By-person factor analysis of value rankings revealed four prioritization patterns centered on: (1) data protection, (2) effectiveness, (3) secure and reliable outcomes, or (4) fairness. No consensus in value priorities emerged.Discussion and conclusions: Although MWAs are unregulated, students are expected to make informed choices and bear the responsibility of consequences. Yet, their value priorities differ depending on personal circumstances, making some more exposed to risks than others. Many feel resigned and unable to influence how MWAs handle the values they care about, leading them to downplay those values, assuming apps will not realize them anyway. The findings show concrete mechanisms through which harm can emerge, especially considering most students turn to MWAs mainly in times of urgent need. This further emphasizes the need for regulation to ensure MWA safety, quality, and protection of public values, particularly as AI features continue to expand.Keywords: mental wellness apps, mHealth, mental health, university students, value trade-offs, public values

Background: Individuals with substance use disorders (SUD) can experience different factors influencing addiction. Personalized networks and descriptive graphs based on ecological momentary assessment (EMA) could uncover individual mechanisms, facilitating personalized psychotherapy. We tested a feedback application (fb-app) using EMA to improve client-practitioner communication in SUD interventions. Methods: One participant experiencing cannabis use problems completed EMA regarding substance use and related factors five times daily over 22 days. A clinical psychologist and a researcher generated personalized descriptive graphs and networks using the fb-app. The psychologist discussed these results with the participant using motivational interviewing (MI) techniques. Semi-structured interviews with the participant and psychologist, analyzed with thematic analysis, assessed usefulness, ease of use, and related concepts. Results: EMA-based feedback seemed a feasible and promising add-on to MI. The participant reported improved understanding of his cannabis use. The psychologist noticed improved therapeutic communication, but also that the fb-app needed simplification for independent clinical use. An fb-app error duplicated data, risking false associations in the networks, suggesting alternative explanations of reported network usefulness other than providing accurate information. Conclusions: EMA-based feedback in MI for addiction seems promising and feasible enough to justify larger studies investigating its impact on behavior change and which types of feedback work best and why.

Purpose Multifactorial falls risk assessment tools (FRATs) help identify and target individual falls risk factors in older adults, but barriers can limit their effectiveness. This study evaluated a User-Centered Design (UCD) developed digital multifactorial FRAT, the Fall Analysis 2.0 in Dutch primary care. Methods A randomized effectiveness-implementation study included 19 health care professionals (HCPs) from 15 primary care practices, randomly assigned to either the intervention or usual care group (control). The intervention involved using the Fall Analysis 2.0 and corresponding training. Participants were community-dwelling (65 +) at high risk of falling (36 intervention vs 27 control; mean age 81 years; 63.5% female). Primary outcomes included HCPs falls risk management behavior and older adults’ adherence-related motivation to falls prevention advice, analyzed using Fisher’s Exact tests and Mann Whitney U tests. Secondary outcomes of the Fall Analysis 2.0 user experience was explored through HCP interviews. Results Fully completed multifactorial falls risk assessments (86.1%; n = 31) were significantly higher in the intervention than control group (3.7%, n = 1), p < .001. Use of validated tools was lower in the control group (11.1%; n = 3), p < .001. HCPs rated the Fall Analysis 2.0 highly for user experience. Successful implementation is dependent on improved reimbursement and interoperability with electronic health records. No significant differences in older adults’ adherence-related motivation were found due to a ceiling effect. Conclusion UCD developed digital multifactorial FRATs like the Fall Analysis 2.0 show promise for improving falls prevention care quality. Future research should disentangle the effects of UCD from digitalization.

Technology has gained an important role in health communication in recent decades. One example is the use of health technology for tailoring, i.e., using adapted, rather than generic, messages based on the receiver’s unique characteristics and preferences. ASCoR researchers have investigated content tailoring, mode tailoring, and message frame tailoring, in the context of multiple topics (e.g., cancer treatment and smoking cessation), applying different methodologies. The results of these studies highlight the potential of tailoring health messages. In particular, tailoring of intervention content and delivery mode seem to be promising approaches to enhance effective health communication. Implications for practice and theory are discussed, as well as future directions, with technological developments high on our health communication research agenda.

Background and aims. Interventions for cannabis use problems could improve through personalization with ecological momentary assessment (EMA) and derived personalized feedback including idiographic networks. To study preliminary efficacy and feasibility, this pilot preclinical randomized controlled trial compared a short version of treatment as usual (TAU) to the same with the add-on of EMA and personalized feedback.Design. We conducted a pilot parallel two-arm randomized controlled trial.Setting. Data were collected at the University of Amsterdam, the Netherlands (March to November 2023).Participants. We included participants aged 18-30, with good English proficiency, owning smartphones, using cannabis flower at least weekly, and wanting help to stop or diminish use. Current treatment for or diagnosis of a substance use or psychotic disorder were exclusion criteria. We recruited through flyers, social media, peer-to-peer recruitment, and the University of Amsterdam lab. We used block randomization stratified by gender; participants were blind to condition.Intervention. Both groups received TAU, additionally, the experimental group received EMA and personalized feedback (TAU+).Measurements. Main outcomes were self-reported cannabis use and cannabis use disorder (CUD) DSM-5 symptoms. Secondary outcomes were mental health variables. Predictors were time, condition, and their interaction. Semi-structured interviews were conducted with TAU+ participants and practitioners giving the intervention and analyzed with thematic analysis.Findings. 90 participants were screened, 76 were randomized, 13 per group were included (target sample size), other randomized participants either declined participation/had to be excluded or were in the waiting list. Two experimental and one control participants dropped out (23 participants included in the analyses). Average cannabis grams smoked per day, days smoking cannabis, and CUD symptoms decreased in both groups (p < .001). However, only TAU+ participants maintained the change for the three main outcome measures at three-months follow-up (p = .038, .035, .056 respectively). Both interventions diminished depression, stress, and negative emotions. No adverse events occurred. Participants reported high perceived usefulness, ease of use and motivation regarding the personalized feedback, but some difficulties and negative emotions in answering EMA. Practitioners’ interview results suggested the need to simplify the tool for practitioners and give more training on communicating feedback. Conclusions. Adding personalized EMA and feedback to TAU seems feasible and may reduce relapse rates in problematic cannabis use compared to TAU alone. A larger trial is needed to support these results.

Purpose Multifactorial falls risk assessment tools (FRATs) identify and target individual falls risk factors in older adults. However, barriers can hinder their effectiveness. User-Centered Design (UCD) could improve multifactorial FRATs for both primary (HCPs) and secondary (patients) users. This study investigated a UCD developed multifactorial FRAT, the Fall Analysis 2.0. Methods A randomized effectiveness-implementation study included 19 HCPs from 15 primary care practices, randomly assigned to either the intervention or control group (usual care). The intervention involved using the Fall Analysis 2.0 and corresponding training. Participants were community-dwelling (65 + years) at high risk of falling (36 intervention, 27 control). Primary outcomes included differences in HCPs falls risk management behavior and older adults’ adherence-related motivation to falls prevention advice, analyzed using Fisher’s Exact tests and Mann Whitney U tests. Secondary outcomes of the Fall Analysis 2.0 user experience and implementation was explored through HCP interviews. Results Fully completed multifactorial falls risk assessments (86.1%) by HCPs was higher in the intervention compared to the control group (3.7%), p < .001. Use of validated tools was lower in the control group (11.1%), p < .001. HCPs rated the Fall Analysis 2.0 highly for user experience. Successful implementation is dependent on HCP reimbursement and interoperability with electronic health records. No significant differences in older adults’ adherence-related motivation were found between groups due to a ceiling effect. Conclusion UCD developed multifactorial FRATs like the Fall Analysis 2.0 show promise for enhancing falls prevention care quality by improving delivery for HCPs and older adults.

Objectives: This study evaluated the impact of the OnVaCT intervention, a narrative‐based Online Value Clarification Tool (OnVaCT), combined with communication training for oncologists, on shared decision‐making (SDM) in discussions on potential early phase clinical trial participation and palliative care. These high‐stakes decisions often challenge patients and oncologists in addressing patient values, a crucial component of SDM. We hypothesized that the intervention would improve oncologist‐patient communication, specifically SDM application, and (consequently) reduce patient decisional conflict.Methods: In this prospective, multicentre pre‐post clinical study, patients completed two surveys, and their recorded consultations on early phase clinical trials and palliative care were assessed by independent coders. Pre‐intervention patients received usual care, while post‐intervention patients used the OnVaCT. Oncologists underwent communication training between study phases. Endpoints included decisional conflict (primary), the extent to which oncologists, patients and relatives participate in SDM, consultation length, and patient decisions (secondary).Results: Decisional conflict (p = 0.394) did not differ between pre‐test (n = 116, M = 30.0, SD = 16.9) and post‐test (n = 99, M = 29.4, SD = 15.2). Oncologists significantly increased their SDM application post‐intervention (p < 0.001; n = 129, M = 38.5, SD = 12.6) compared to pre‐intervention (n = 163, M = 28.8, SD = 9.2), particularly when the OnVaCT was discussed. Other outcomes, including consultation length, remained stable.Conclusions: The OnVaCT intervention enhanced SDM and supported value‐based discussions, without prolonging consultations. Further research should explore whether additional implementation efforts could reduce decisional conflict and the intervention's potential impact on other patient‐centred outcomes. Some decisions, however, may inherently involve unresolved conflict.

Background: Patients with cancer increasingly use the internet to seek health information. However, thus far, research treats web-based health information seeking (WHIS) behavior in a rather dichotomous manner (ie, approaching or avoiding) and fails to capture the dynamic nature and evolving motivations that patients experience when engaging in WHIS throughout their disease trajectory. Insights can be used to support effective patient-provider communication about WHIS and can lead to better designed web-based health platforms. Objective: This study explored patterns of motivations and emotions behind the web-based information seeking of patients with cancer at various stages of their disease trajectory, as well as the cognitive and emotional responses evoked by WHIS via a scenario-based, think-aloud approach. Methods: In total, 15 analog patients were recruited, representing patients with cancer, survivors, and informal caregivers. Imagining themselves in 3 scenarios—prediagnosis phase (5/15, 33%), treatment phase (5/15, 33%), and survivor phase (5/15, 33%)—patients were asked to search for web-based health information while being prompted to verbalize their thoughts. In total, 2 researchers independently coded the sessions, categorizing the codes into broader themes to comprehend analog patients’ experiences during WHIS. Results: Overarching motives for WHIS included reducing uncertainty, seeking reassurance, and gaining empowerment. At the beginning of the disease trajectory, patients mainly showed cognitive needs, whereas this shifted more toward affective needs in the subsequent disease stages. Analog patients’ WHIS approaches varied from exploratory to focused or a combination of both. They adapted their search strategy when faced with challenging cognitive or emotional content. WHIS triggered diverse emotions, fluctuating throughout the search. Complex, confrontational, and unexpected information mainly induced negative emotions. Conclusions: This study provides valuable insights into the motivations of patients with cancer underlying WHIS and the emotions experienced at various stages of the disease trajectory. Understanding patients’ search patterns is pivotal in optimizing web-based health platforms to cater to specific needs. In addition, these findings can guide clinicians in accommodating patients’ specific needs and directing patients toward reliable sources of web-based health information.