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BACKGROUND: Informing the public about lifestyle-related risk factors for colorectal cancer (CRC) is central for cancer prevention. More knowledge is needed about the public’s perceptions of CRC risk and how it relates to their lifestyle decisions, in order to design and communicate risk information effectively. This study aims to explore how the general public perceives risk factors for CRC, their risk of developing CRC, and their willingness to make lifestyle changes to reduce their CRC risk. The study also explores their experiences of, and preferences for, lifestyle-related risk communication and cancer prevention in the community.

METHODS: The study employed an explorative qualitative design. Semi-structured interviews were conducted between May 2024 and January 2025 with 25 individuals from the general public in Sweden, including women and men aged 22 to 80 years. The data were analysed using reflexive thematic analysis as described by Braun and Clarke.

RESULTS: Four themes with 10 sub-themes were identified. The first theme, Information void leaves room for uninformed assumptions, describes participants’ limited understanding of CRC and its risk factors, resulting in assumptions about risks based on stereotypical and intuitive beliefs. In the second theme, Colorectal cancer risk – one of many competing aspects in the pursuit of a fulfilling life, participants described balancing values and factors beyond health risks that influenced their motivation and ability to adopt healthy lifestyle habits. The third theme, Need for comprehensible information that addresses actual knowledge gaps, describes that participants requested credible and personally engaging risk information that provides actionable advice without instilling worry or blaming individuals. The fourth theme, Community interventions should facilitate healthier behaviours but not restrict individuals’ personal choice, describes participants’ reflections on a shared responsibility for cancer prevention, emphasizing that society should support a healthy lifestyle without excessively interfering in individuals lives.

CONCLUSIONS: There was a clear need for more information about CRC and associated lifestyle risks. As individuals balance competing values in their lifestyle decisions, risk information must be nuanced and respectful of personal priorities and communicated carefully in a positive and supportive way to raise awareness and encourage healthy choices.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-026-26737-2.

Background While fatigue is highly reported in newly diagnosed people with Multiple Sclerosis (pwMS) and motor fatigability is reported in about 20% of non-disabled patients, relationship among them in early MS has been less studied. Objective To evaluate correlations between fatigue and motor fatigability in early pwMS, and their clinical, radiological, psychological underpinnings. Methods Relapsing pwMS aged 18-65 years, Expanded Disability Status Scale (EDSS) score <2.0, disease duration <5 years were recruited. PwMS underwent clinical, cognitive, radiological assessment. They performed a 6-minute-walking-test; fatigability was calculated as the ratio of distance walked in the final minute to the first minute (distance walking index, DWI6-1). Fatigue was evaluated through the Modified Fatigue Impact Scale (MFIS). Spearman rho examined the relationship among variables; linear regression analyses examined predictors of fatigue and fatigability. Results 70 pwMS (age 37.8+11years; female n=50, 71.4%, EDSS 1.5[1;2]) were enrolled. 15 (21.4%) reported significant levels of fatigue, 14 (20%) presented motor fatigability. Fatigue and motor fatigability were not significantly correlated with one another (rho=0.100;p=0.425) or with other clinical, cognitive, radiological features. Fatigue was related to Hospital Anxiety and Depression Scale (HADS) anxiety subscale (rho=0.375,p=0.002), Beck Depression Inventory (BDI-II) (rho=0.543;p<0.001), neuroticism (rho=0.313;p=0.006), and all subscales of MS-Quality-Of-Life 54. We did not find predictors of fatigability, while HADS-anxiety (b=0.76; p=0.003) and BDI-II (b=0.33; p=0.009) significantly predicted fatigue. Conclusions Our results support different neurobiological underpinnings for motor fatigue and fatigability and reinforce the need for a multidimensional assessment from the earliest stages of the disease, to tailor therapeutic and rehabilitation strategies.

Incorporating patient preferences into drug development is crucial, particularly, for rare diseases with significant unmet needs. This study used Best-Worst Scaling type 2 (BWS-2) to explore benefit-risk trade-offs for patients and caregivers in two rare neuromuscular diseases (NMDs), myotonic dystrophy type 1 (DM1), and mitochondrial myopathy (MM). Patients with DM1 and MM, along with caregivers, completed a BWS-2 survey assessing four treatment benefits (muscle strength, energy and endurance, balance, cognition) and two risks (permanent liver damage, temporary blurring of vision). Participants were stratified by disease group and age of onset (< 20, >= 20 years). A latent class analysis was used to calculate the relative importance of each treatment attribute. Sociodemographic and disease-related data were also collected. A total of 270 participants (DM1 n = 143, MM n = 127, including 37 caregivers) were included. BWS-2 results revealed a priority for improvements in muscle strength (24%), and energy and endurance (23%) across all groups, with caregivers placing a higher priority on cognition improvements (17%) compared to patients. There were no significant differences between disease groups or by age of onset. This study underscores the importance of patient preferences in drug development for rare NMDs. The consensus on treatment priorities across both diseases suggests that overlapping clinical features can inform and expedite future NMD or rare disease drug development.

This study explores a new way to model the adoption of AI, specifically online recommender systems. It aims to find factors that can explain the variation in usage in terms of differences between individuals and differences over technologies. We analyzed survey data from users of online platforms in the U.S. using a two-level structural equation model (SEM) (N = 1007). In this model, the dependent variable was the usage rate, which was defined as the share of time a person used a particular recommender system (e.g., "People You May Know") when they use the platform (e.g., Facebook). The individual responses (within-systems level) were clustered in the 26 recommender systems (between-systems level). We hypothesized that three technology-specific factors, adapted from the Diffusion of Innovations (DOI) theory and the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), could explain the variations in usage at both levels: perceived performance expectancy (PE), perceived effort expectancy (EE), and perceived hedonic motivation (HM). Our estimated model showed that usage was associated with PE and HM at the within-system level and only with PE at the between-system level. A considerable part of the variation in usage across the 26 systems could be explained by PE only (R² = 0.30). The most important contribution to practitioners is that this study provides evidence for the idea that there are inherent, measurable differences across recommender technologies that affect their usage rates, and specifically it finds usefulness to be a key factor. This is potentially valuable for app developers and marketeers who look to promote the adoption of novel recommender systems. The main contribution to the literature is that it presents a proof-of-concept of a two-level model for AI adoption, conceptualizing it as an effect of both variations over users and variations over applications. This finding is potentially valuable for policymakers, as better predictive models might enable improved assessments of AI's social implications. In future studies, the two-level approach presented here could be applied to other forms of AI, such as voice assistants, chatbots, or Internet of Things (IoT).

Objective

This study aimed to explore radiologists’ views on using an artificial intelligence (AI) tool named ScreenTrustCAD with Philips equipment) as a diagnostic decision support tool in mammography screening during a clinical trial at Capio Sankt Göran Hospital, Sweden.

Methods

We conducted semi-structured interviews with seven breast imaging radiologists, evaluated using inductive thematic content analysis.

Results

We identified three main thematic categories: AI in society, reflecting views on AI’s contribution to the healthcare system; AI-human interactions, addressing the radiologists’ self-perceptions when using the AI and its potential challenges to their profession; and AI as a tool among others. The radiologists were generally positive towards AI, and they felt comfortable handling its sometimes-ambiguous outputs and erroneous evaluations. While they did not feel that it would undermine their profession, they preferred using it as a complementary reader rather than an independent one.

Conclusion

The results suggested that breast radiology could become a launch pad for AI in healthcare. We recommend that this exploratory work on subjective perceptions be complemented by quantitative assessments to generalize the findings.

BACKGROUND: Informing individuals about their risk of cancer can sometimes have negative consequences, such as inflicting unnecessary worry and fostering stigma. This study aims to explore how patients diagnosed with breast or colorectal cancer perceive and experience risk communication, particularly concerning the increased focus on lifestyle behaviors as the cause of cancer.

METHODS: Semi-structured interviews were conducted during autumn 2023, with 23 Swedish individuals, aged 34 to 79 years, diagnosed with breast or colorectal cancer. The collected data were analyzed using inductive thematic analysis described by Braun & Clark. The study adopted an experiential orientation grounded in critical realism.

RESULTS: Five themes with ten sub-themes were identified: Thoughts and feelings about the causes of cancer, Moralizing messages and negative encounters, The need to take action, Balancing uncertain risks and a fulfilling life, and Societal benefits of risk communication. The participants expressed that knowledge of the the cause of cancer is closely related to the possibility of taking preventive action against relapses. Ability to take action was also perceived important for their well-being. Therefore, risk information entails both feelings of self-blame and hope for the future. Participants asked for both information and lifestyle support from healthcare professionals. Lifestyle interventions and patient support groups were solicited and perceived as an important aspect of cancer survivals' well-being, and may help to reduce the cancer-related stigma.

CONCLUSION: Individuals that have or have had breast or colorectal cancer, including those leading healthy lifestyles, found moralistic risk information offensive, leading to feelings of shame when thinking about other peoples thoughts. Balancing information involves providing transparent, evidence-based information while considering individual and social contexts, avoiding stigmatization and blame, and supplementing information with support.

BACKGROUND: Understanding women's perspectives can help to create an effective and acceptable artificial intelligence (AI) implementation for triaging mammograms, ensuring a high proportion of screening-detected cancer. This study aimed to explore Swedish women's perceptions and attitudes towards the use of AI in mammography.

METHOD: Semistructured interviews were conducted with 16 women recruited in the spring of 2023 at Capio S:t Görans Hospital, Sweden, during an ongoing clinical trial of AI in screening (ScreenTrustCAD, NCT04778670) with Philips equipment. The interview transcripts were analysed using inductive thematic content analysis.

RESULTS: In general, women viewed AI as an excellent complementary tool to help radiologists in their decision-making, rather than a complete replacement of their expertise. To trust the AI, the women requested a thorough evaluation, transparency about AI usage in healthcare, and the involvement of a radiologist in the assessment. They would rather be more worried because of being called in more often for scans than risk having overlooked a sign of cancer. They expressed substantial trust in the healthcare system if the implementation of AI was to become a standard practice.

CONCLUSION: The findings suggest that the interviewed women, in general, hold a positive attitude towards the implementation of AI in mammography; nonetheless, they expect and demand more from an AI than a radiologist. Effective communication regarding the role and limitations of AI is crucial to ensure that patients understand the purpose and potential outcomes of AI-assisted healthcare.

Background and Objectives

Case 2 best-worst scaling (BWS-2) is an increasingly popular method to elicit patient preferences. Because BWS-2 potentially has a lower cognitive burden compared with discrete choice experiments, the aim of this study was to compare treatment preference weights and relative importance scores.

Methods

Patients with neuromuscular diseases completed an online survey at two different moments in time, completing one method per occasion. Patients were randomly assigned to either first a discrete choice experiment or BWS-2. Attributes included: muscle strength, energy endurance, balance, cognition, chance of blurry vision, and chance of liver damage. Multinomial logit was used to calculate overall relative importance scores and latent class logit was used to estimate heterogeneous preference weights and to calculate the relative importance scores of the attributes for each latent class.

Results

A total of 140 patients were included for analyses. Overall relative importance scores showed differences in attribute importance rankings between a discrete choice experiment and BWS-2. Latent class analyses indicated three latent classes for both methods, with a specific class in both the discrete choice experiment and BWS-2 in which (avoiding) liver damage was the most important attribute. Ex-post analyses showed that classes differed in sex, age, level of education, and disease status. The discrete choice experiment was easier to understand compared with BWS-2.

Conclusions

This study showed that using a discrete choice experiment and BWS-2 leads to different outcomes, both in preference weights as well as in relative importance scores, which might have been caused by the different framing of risks in BWS-2. However, a latent class analysis revealed similar latent classes between methods. Careful consideration about method selection is required, while keeping the specific decision context in mind and pilot testing the methods.

Objectives: Over the last few decades, there have been significant improvements in the treatment of rheumatoid arthritis (RA), with the development of new treatments and guidelines for teamwork and patient self-care and access to digital tools. This study aimed to explore the experiences of individuals with RA interacting with healthcare. It also looked at how a self-care application, an educational programme called the ‘healthcare encounter’, improved patient–doctor communication.

Design: Semistructured interviews were conducted, and qualitative content analysis was performed.Setting The potential participants, individuals with established, or under investigation for, RA diagnosis at rheumatology clinics in Sweden, were asked to participate in the study via a digital self-care application called the Elsa Science Self-care app.

Participants: Ten interviews were performed with participants from nine clinics following a meeting with the rheumatologist or other healthcare personnel between September 2022 and October 2022. Phrases, sentences or paragraphs referring to experiences from healthcare meetings and opinions about the digital programme were identified and coded. Codes that reflected similar concepts were grouped; subcategories were formulated, and categories were connected to their experiences and opinions.

Results: Among our participants, three main categories emerged: the availability of healthcare, individual efforts to have a healthier life and personal interaction with healthcare. Participants described that the ‘healthcare encounter’ educational programme can be a source of information, which confirms, supports and creates a sense of control.

Conclusion: The participants valued being seen and taking part in a dialogue when they had prepared themselves (observed symptoms over time and prepared questions). The implementation of digital self-care applications might need to be incorporated into the healthcare setting, so that both the patients and the healthcare personnel have a shared understanding. Collaboration is essential in this context.