The Association Between Number of Chronic Conditions and Benzodiazepine Prescribing in Region Stockholm, Sweden: A Total Population-Based Cohort Study.
Authors: Kappelin C, Wachtler C, Ljunggren G, Carlsson AC
Journal: Health science reports
mental health
psychology
open access
Abstract
Regular physical activity (PA) is a major modifiable determinant of health across adult populations (, ). A large body of evidence indicates that higher PA levels are associated with reduced risks of all-cause mortality, cardiovascular disease, type 2 diabetes, several cancers, and depression, as well as better physical functioning and overall well-being (). Nevertheless, insufficient PA remains a major and growing global challenge (, ). A recent pooled analysis of population-based surveys across 197 countries and territories showed that the global prevalence of insufficient PA among adults increased from 23.4% in 2000 to 31.3% in 2022, corresponding to approximately 1.8 billion adults not meeting recommended activity levels (). Given this persistent and increasing burden, identifying effective, scalable, and sustainable strategies to support PA participation in adults remains an important public health priority. To address the growing burden of insufficient PA, considerable efforts have therefore been devoted to developing effective PA promotion strategies (, ). Among these, digital behavior change interventions (DBCIs) have been proposed as a promising and potentially scalable approach (). DBCIs use digital technologies, such as websites, mobile applications, wearable devices, or social media platforms, to support or facilitate behavior change (, ). For PA promotion, they can deliver behavior change techniques such as goal setting, self-monitoring, feedback on performance, prompts or reminders, action planning, and social support through automated or minimally supported digital systems (, ). Compared with traditional face-to-face interventions, DBCIs may offer broad reach, flexible access, relatively low delivery costs, and tailored or personalized feedback based on users’ behavior or self-reported data (, , ). These features have generated increasing interest in DBCIs as a scalable strategy for addressing insufficient PA in adults (, , ). In recent years, increasing evidence has examined the effects of DBCIs on PA across different adult populations and digital delivery formats (). However, findings across individual studies have not been entirely consistent. For example, Van Dyck et al. () reported positive or borderline intervention effects on accelerometer-measured PA and improvements in several self-reported PA outcomes among older adults. In contrast, Collombon et al. () found no significant intervention effects on either self-reported or accelerometer-measured moderate-to-vigorous physical activity among adults aged 50 years and older. These mixed findings make it difficult to determine the overall impact of DBCIs on PA and highlight the need for evidence synthesis.