webPOISONCONTROL: can poison control be automated?

A Mobile Health Information Behavior Model: Theoretical Development and Mixed-Method Testing in the Context of Mobile Apps on Child Poisoning Prevention

While several studies have explored the use of mobile health applications, few have observed determinants of mobile health information behavior. To develop a model explaining parents' mobile information behavior on child poisoning prevention, we first explored relevant theories to suggest a theoretical model. In that, we combine existing models on risk and health information seeking, such as the Planned Risk Information Seeking Model, with models on the acceptance of mobile technologies, such as the Unified Theory of Acceptance and Use of Technologies. Thereafter, we employed a sequential mixed-method design with an initial qualitative study (four online focus groups with n = 25 parents in total) and a standardized online survey of n = 1,013 parents to evaluate our research model. Results confirm that both, determinants of information seeking and determinants of technology acceptance, contribute to the explanation of mobile information behavior. App use intention was mainly related to the performance expectancy of app use, the subjective information norm, and social influence on app use. To increase the usage of prevention apps and contribute to the reduction of child injuries, communication on poisoning apps should address subdimensions of the performance expectancy, such as their utility and peoples' trust in app providers. Moreover, physicians are important multipliers for these messages.

Mobile Apps Aimed at Preventing and Handling Unintentional Injuries in Children Aged <7 Years: Systematic Review

BACKGROUND

Despite various global health crises, the prevention and handling of unintentional childhood injuries remains an important public health objective. Although several systematic reviews have examined the effectiveness of different child injury prevention measures, these reviews did not address the evaluation of mobile communication intervention tools. Whether and how mobile apps were evaluated provides information on the extent to which communication theories, models, and evidence-based knowledge were considered. Previous studies have shown that the effectiveness of mobile apps increases when theories and evidence are considered during their development.

OBJECTIVE

This systematic review aimed to identify research on mobile apps dealing with the prevention and handling of unintentional injuries in children and examine the theoretical and methodological approaches thereof. In addition, this review analyzed the different needs of various target groups of the mobile apps described in the articles.

METHODS

In total, 8 electronic databases, ranging from interdisciplinary to medical and technical as well as social sciences databases, were searched for original research articles or brief reports in peer-reviewed journals or conference proceedings. Moreover, this review encompassed a systematic scan of articles published in the BMJ journal Injury Prevention. These steps were followed by a snowball search based on the literature references in the articles identified through the initial screening. The articles had to be written in English or German, published between 2008 and 2021, and evaluate mobile apps dealing with the prevention and handling of unintentional child injuries. The identified 5 studies were analyzed by 5 independent researchers using an inductive approach. Furthermore, the quality of the studies was assessed using the Mixed Methods Appraisal Tool.

RESULTS

A total of 5 articles were included and assessed with regard to overall quality of theoretical and methodological foundations, assessed variables, the focal app's architecture, and the needs of the study participants. The overall study quality was moderate, although part of this classification was due to a lack of details reported in the studies. Each study examined 1 mobile app aimed at parents and other caregivers. Each study assessed at least 1 usability- or user experience-related variable, whereas the needs of the included study participants were detailed in only 20% (1/5) of the cases. However, none of the studies referred to theories such as the Technology Acceptance Model during the development of the apps.

CONCLUSIONS

The future development and evaluation of apps dealing with the prevention and handling of child injuries should combine insights into existing models on user experience and usability with established theories on mobile information behavior. This theory-based approach will increase the validity of such evaluation studies.

Poison control centres and alternative forms of communication: comparison of response rates between text message and telephone follow-up

INTRODUCTION

In recent years, the number of patients managed by poison control centres (PCCs) has increased without a proportional increase in the number of physicians. To improve efficiency without neglecting patient follow-up, some PCCs have begun using text messages. We evaluated the difference in response rates between text messaging and traditional telephone follow-up.

MATERIALS AND METHODS

This retrospective, monocentric, non-randomised cohort study was conducted using data from calls made by the New Aquitaine PCC between February 27, 2019, and March 31, 2019. Patients were contacted up to three times by a phone call or short message service (SMS).

RESULTS

For the analysis, 823 patients were included. At the end of follow-up, the response rates were similar in the phone call and SMS group (94 vs. 94%; p = 0.76) with median [interquartile range] response times of 0 min [0; 27 min] and 29 min [6; 120 min], respectively. The response rates did not differ in subgroups stratified according to sex, self-poisoning vs. relative response, age class, and solicitation during working hours vs. outside of working hours (all p > 0.5). Moreover, health practitioners required 2.4-fold more time to call than to send text messages (p < 0.001), and all practitioners were satisfied or very satisfied with text messaging implementation.

CONCLUSION

Patients had good adherence to text messages. Text messages are easy to use, rapid, and allow the physician to easily prioritise follow-up without occupying the emergency line. Additionally, the costs of installation and maintenance are low for text message systems; these low costs facilitate the implementation of such services in various medical situations.

The Role and Promise of Artificial Intelligence in Medical Toxicology

Artificial intelligence (AI) refers to machines or software that process information and interact with the world as understanding beings. Examples of AI in medicine include the automated reading of chest X-rays and the detection of heart dysrhythmias from wearables. A key promise of AI is its potential to apply logical reasoning at the scale of data too vast for the human mind to comprehend. This scaling up of logical reasoning may allow clinicians to bring the entire breadth of current medical knowledge to bear on each patient in real time. It may also unearth otherwise unreachable knowledge in the attempt to integrate knowledge and research across disciplines. In this review, we discuss two complementary aspects of artificial intelligence: deep learning and knowledge representation. Deep learning recognizes and predicts patterns. Knowledge representation structures and interprets those patterns or predictions. We frame this review around how deep learning and knowledge representation might expand the reach of Poison Control Centers and enhance syndromic surveillance from social media.

Trends in types of calls managed by U.S. poison centers 2000-2015

AIM

The number of cases reported to poison centers has decreased since 2008 but there is evidence that the complexity of calls is increasing.

OBJECTIVES

The objectives are to evaluate national poison center data for trends in reason and how these changes effect management site, medical outcomes, and poison center workload.

METHODS

Data regarding reason, age, management site, and medical outcome were extracted from annual reports of the National Poison Data System from 2000 to 2015. The proportion of cases by year were determined for unintentional and intentional exposures. Analysis of data from a single poison center from 2005 to 2015 compared the number of interactions between poison center staff and callers for unintentional versus intentional reasons.

RESULTS

Trend analyses found that from 2000 to 2015 the percent of unintentional cases decreased (from 85.9 to 78.4%, p < .0001) and the percent of intentional cases increased (from 11.3 to 17.6%, p < .0001). Age distribution changed with a decrease in children <13 years of age and increase in adolescents and adults. In these latter two age groups, the proportion due to intentional exposure increased while unintentional declined. The distribution of management sites changed over the 16-year period, with a decrease in non-HCF cases and significant increase in percent of cases treated in a HCF. The frequencies of moderate effect, major effect, and death were significantly higher for intentional exposures than for unintentional exposures. Analysis of data entry notes from a single center showed that the mean number of notes per unintentional case (1.61 ± 0.08) was significantly different from the mean number of notes per intentional case (9.23 ± 0.68) (p < .0001).

DISCUSSION

Poison centers are managing more intentional exposures and fewer unintentional exposures. Intentional exposures require more poison center staff expertise and time.

CONCLUSION

Looking only at poison center total call volume may not be an adequate method to gauge productivity.