JMIR Formative Research最新文献

Background: Physical activity (PA) has an important role in the prevention and treatment of type 2 diabetes (T2D). Interventions with mobile-based technology (mobile health [mHealth]) seem promising in PA promotion, but their behavioral framework is often vague, and the implementation is seldom reported.

Objective: This paper examines perceived behavior change needs and implementation of an mHealth approach in increasing nonexercise PA in patients with T2D.

Methods: A 3-arm mHealth intervention was conducted in primary care. Information on perceived behavior change needs was collected with a modified capability, opportunity, motivation-behavior (COM-B) questionnaire before the intervention from a separate sample of patients with T2D (n=25) and at the intervention baseline (n=119). Implementation evaluation focused on the fidelity and acceptability of the main arm of the intervention (n=39), which included 24-hour accelerometer use, a smartphone app with personal feedback, a PA leaflet, a YouTube video on walking, and individual counseling with 3 face-to-face sessions and 4 telephone contacts. Data on fidelity were accumulated during the intervention through counseling cards and cloud computing. Data on acceptability were collected with a questionnaire at the end of the intervention (Likert scale from 1 to 5). Data analysis was mainly descriptive.

Results: The participants' responses revealed 3 items in capability and 2 in motivation, which stood out as perceived behavior change needs. Moreover, the main intervention arm showed good fidelity (eg, face-to-face sessions: 112/117, 96% and telephone contacts completed: 145/156, 93%; mean weekly accelerometer use 54%; ranging from 80% to 17% during the intervention) and acceptability (mean score ranging from 3.8 to 4.8), although some challenges were also experienced, especially in cloud-computed feedback and accelerometer-app use.

Conclusions: The findings on behavior change needs call for additional research since no comparable studies were found. In addition, the explanatory value of the COM-B model and the psychometric properties of the COM-B questionnaire deserve further attention. The main intervention arm seemed applicable to clinical practice. However, the challenges discovered underscore the importance of pretesting technology-based approaches in patients with T2D.

Unlabelled: Although a general purpose (GPT-5), and a fine-tuned (ASReviewLab) artificial intelligence were able to rank abstracts for likely inclusion in a variety of Cochrane systematic reviews, some actually included studies were not highly ranked, necessitating human review of all abstracts.

Unlabelled: This study analyzed social media posts from patients with congenital ichthyosis and their caregivers across Europe and found that users, primarily young women, discussed hygiene care, psychological impact, therapeutic challenges, and lack of disease awareness. This allowed for the identification of unmet needs and potential actions to improve patients' quality of life.

Background: Chronic illness may cause a financial burden that affects patients, their caregivers, and families. While international research, mostly from the United States, has largely focused on cancer-related financial hardship, less is known about whether financial distress due to other chronic illnesses exists, specifically in countries that have universal health insurance coverage, such as Switzerland.

Objective: This study aims to provide insights into how financial burden is discussed by individuals living with chronic illness in Switzerland.

Methods: Based on a natural language processing (NLP) approach, alongside topic modeling, a secondary analysis of 180 qualitative interviews of individuals living with chronic illness (dementia, chronic pain, multiple sclerosis, Parkinson disease, and rare diseases) from the Swiss Database of Individual Patient Experiences was conducted.

Results: Key categories identified were money issues, disability insurance, general insurance concerns, and work and loss of income. Individuals living with dementia and Parkinson disease appear to be more concerned with money issues, whereas people living with chronic pain, multiple sclerosis, and rare diseases are more burdened by insurance-related concerns, specifically disability insurance-related challenges. Bureaucratic hurdles and employment instability appear to contribute to the financial burden of people living with chronic illness in Switzerland.

Conclusions: Financial burden is a complex issue among individuals living with chronic illness in Switzerland. Our findings indicate that effectively addressing this burden requires a comprehensive and context-sensitive strategy. Targeted interventions should consider factors such as insurance eligibility, employment flexibility, and the mitigation of out-of-pocket costs to improve financial stability and quality of life for affected individuals.

Background: Chronic insomnia affects more than 30% of US adults, is more prevalent in women and older adults, and is strongly associated with poor mental and physical health outcomes. Poor sleep quality and intraindividual variability of sleep are recognized to be key characteristics of chronic insomnia, but longitudinal assessment of sleep is largely subjective, with no objective characterization of sleep patterns and intraindividual variability over extended periods. Objective, ecologically valid longitudinal sleep measurements are needed to help identify and manage insomnia in both clinical and population settings. Consumer sleep technologies offer a possible solution, but their clinical utility remains relatively unexplored.

Objective: We aimed to evaluate the utility of a contactless, radio frequency-based device by demonstrating its ability to objectively characterize sleep in individuals with insomnia over an extended observation period in a naturalistic home environment.

Methods: Eighty-three participants meeting criteria for chronic insomnia and 29 healthy good-sleeper controls underwent 8 consecutive weeks of home-based sleep monitoring using an objective, contactless, radio frequency-based sleep monitoring device. Sleep efficiency, sleep latency, intermittent wakefulness, time in bed, and total sleep time were objectively quantified as daily means and SDs.

Results: Compared to healthy controls, individuals with chronic insomnia exhibited reduced sleep efficiency, increased sleep latency, and increased intermittent wakefulness. They also demonstrated significantly higher night-to-night variability (SDs) in sleep efficiency, sleep latency, and intermittent wakefulness than good-sleeper controls (all P<.001).

Conclusions: In the longest known objective characterization of sleep among individuals with chronic insomnia, we show that a radio frequency-based, contactless sleep monitoring device deployed in the participants' typical sleep environments accurately distinguished healthy good sleepers from those with insomnia. Importantly, we show that persistent night-to-night variability in objective sleep measures is a hallmark of chronic insomnia.

Background: Smartwatches have gained popularity for their potential to provide accurate measurements of various physiological parameters. However, the validity of energy expenditure (EE) across different smartwatch models remains a topic of ongoing investigation. Discrepancies between results obtained from different models and gold standard methods are particularly critical across varying exercise intensities and types, as validation studies have demonstrated overestimation when wearable activity monitors are compared with indirect calorimetry.

Objective: This study investigated the accuracy of 2 versions of the Samsung smartwatch (Galaxy Watch [GW] 6 and 7) in measuring EE during intermittent moderate-intensity running exercises, using indirect calorimetry as the gold standard method.

Methods: This study included 148 healthy adults, comprising 80 men and 68 women. Participants performed intermittent treadmill running, consisting of walking at 5 km·h⁻¹ for 1 minute and running between 8 and 16 km·h⁻¹ for 2 minutes, based on participant preference, for a total duration of 27 minutes. The GW6 and GW7 models were used and EE was measured by indirect calorimetry using a wearable portable metabolic gas analysis system (K5; Cosmed), which is considered a gold standard method.

Results: No statistically significant differences were found between the GW models and the K5. The K5 showed a mean EE of 213.60 (SD 43.04) kilocalories, compared with 219.53 (SD 35.70) kilocalories for the GW6 and 202.67 (SD 47.42) kilocalories for the GW7 (all P>.05). Good Spearman correlations (0.63-0.70) and moderate intraclass correlation coefficients (0.65-0.74) were found. Mean absolute percentage error values ranged from 10.10% to 12.55%. Bland-Altman analysis revealed limits of agreement for all comparisons (K5 vs GW6 and GW7, -61.93 to 65.80 kcal).

Conclusions: The GW6 and GW7 devices showed moderate validity for estimating EE during intermittent running exercises, demonstrating the suitability of the GW as a low-cost and practical wearable option for daily physical activities.

Unlabelled: Prospective integration of large language model tools into a classical hematology challenging-cases conference was feasible, increased clinician familiarity and interest, and was perceived as diagnostically and educationally valuable.