This study aimed to identify factors that influence the intention to use smart monitor-based mobile health (SBM) technology among middle-aged inpatients, based on the technology acceptance model II (TAM II).

A total of 222 participants were surveyed. Data were analyzed using SPSS Statistics 23.0 and IBM SPSS Amos 23. Seven exogenous variables–social influence (SI), personal self-efficacy, (PSE), environmental self-efficacy (ESE), health literacy, health concerns, resistance to innovative technology (RIT), accessibility (AC)– and three endogenous variables–perceived ease of use (PEOU), perceived usability (PU), and intention to use (ITU)–were investigated.

The hypothesized path model demonstrated a good fit for the data. SI (β = .13, p = .042), PU (β = .46, p < .001), and PEOU (β = .16, p = .008) had significant direct effects on the ITU, which explained 39.5% of the variance. Additionally, SI (β = .27, p < .001), ESE (β = .16, p = .010), RIT (β = - .12, p = .026), AC (β = .28, p < .001), and PEOU (β = .20, p = .001) indirectly affected ITU through PU, which explained 50.7% of the variance. Furthermore, PSE (β = .38, p < .001) indirectly influenced ITU via PEOU, which explained 38.4% of the variance.

This study demonstrates that the TAM II can be used to effectively predict ITU in SBMs among middle-aged inpatients. To expand the intention to use SBMs, it is necessary to develop SBMs that include content and programs that promote PU, SI, and PEOU.

This review aimed to evaluate the effectiveness of telemonitoring (TM) in the management of children and adolescents with asthma.

We searched Ovid-MEDLINE, Ovid-EMBASE, CENTRAL (Cochrane Central Register of Controlled Trials), CINAHL (Cumulative Index to Nursing and Allied Health Literature), and 5 domestic databases to identify randomized controlled trials (RCTs) published through December 2017. Two reviewers independently selected relevant studies, assessed methodological quality and extracted data. We performed a meta-analysis of TM versus usual care and summarized the intervention characteristics of included studies.

Of the 3,095 articles identified, 8 RCTs (9 articles) were included in this review. The type of TM intervention of included studies was varying across studies (transmitted data, transmission frequency, data review, etc.). The pooled asthma control score was not significantly different between TM and usual care (standardized mean difference 0.04, 95% confidence interval (CI) -0.20~0.28). Another pooled analysis demonstrated no statistically significant difference in asthma exacerbation between TM and usual care (odds ratio 0.95, 95% CI 0.43~2.09). Overall, the pooled results from these studies revealed that TM did not lead to clinically significant improvements in health outcomes, but some studies in our analysis suggested that TM increased patient medication adherence and intervention adherence.

The current evidence base does not demonstrate any differences between TM intervention and usual care, but TM intervention might be considered a promising strategy for the delivery of self-management support for children and adolescents with asthma. Further well-designed studies are needed to assess the effects on clinical outcomes.