Loneliness and social isolation detection using passive sensing techniques: Scoping review

Loneliness and social isolation are associated with multiple health problems, including depression, functional impairment, and death. Mobile sensing using smartphones and wearable devices, such as fitness trackers or smartwatches, as well as ambient sensors, can be used to acquire data remotely on individuals and their daily routines and behaviors in real time. This has opened new possibilities for the early detection of health and social problems, including loneliness and social isolation. This scoping review aimed to identify and synthesize recent scientific studies that used passive sensing techniques, such as the use of in-home ambient sensors, smartphones, and wearable device sensors, to collect data on device users' daily routines and behaviors to detect loneliness or social isolation. This review also aimed to examine various aspects of these studies, especially target populations, privacy, and validation issues. A scoping review was undertaken, following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). Studies on the topic under investigation were identified through 6 databases (IEEE Xplore, Scopus, ACM, PubMed, Web of Science, and Embase). The identified studies were screened for the type of passive sensing detection methods for loneliness and social isolation, targeted population, reliability of the detection systems, challenges, and limitations of these detection systems. After conducting the initial search, a total of 40,071 papers were identified. After screening for inclusion and exclusion criteria, 29 (0.07%) studies were included in this scoping review. Most studies (20/29, 69%) used smartphone and wearable technology to detect loneliness or social isolation, and 72% (21/29) of the studies used a validated reference standard to assess the accuracy of passively collected data for detecting loneliness or social isolation. Despite the growing use of passive sensing technologies for detecting loneliness and social isolation, some substantial gaps still remain in this domain. A population heterogeneity issue exists among several studies, indicating that different demographic characteristics, such as age and differences in participants' behaviors, can affect loneliness and social isolation. In addition, despite extensive personal data collection, relatively few studies have addressed privacy and ethical issues. This review provides uncertain evidence regarding the use of passive sensing to detect loneliness and social isolation. Future research is needed using robust study designs, measures, and examinations of privacy and ethical concerns

Attention deficit hyperactivity symptoms predict problematic mobile phone use

Attention-deficit-hyperactivity disorder (ADHD) is the most commonly diagnosed childhood disorder characterised by inattention, hyperactivity/impulsivity, or both. Some of the key traits of ADHD have previously been linked to addictive and problematic behaviours. The aim of the present study was to examine the relationship between problematic mobile phone use, smartphone addiction risk and ADHD symptoms in an adult population. A sample of 273 healthy adult volunteers completed the Adult ADHD Self-Report Scale (ASRS), the Mobile Phone Problem Usage Scale (MPPUS), and the Smartphone Addiction Scale (SAS). A significant positive correlation was found between the ASRS and both scales. More specifically, inattention symptoms and age predicted smartphone addiction risk and problematic mobile phone use. Our results suggest that there is a positive relationship between ADHD traits and problematic mobile phone use. In particular, younger adults with higher level of inattention symptoms could be at higher risk of developing smartphone addiction. The implication of our findings for theoretical frameworks of problematic mobile phone use and clinical practice are discussed

The Role of Gender in Social Network Organization

The digital traces we leave behind when engaging with the modern world offer an interesting lens through which we study behavioral patterns as expression of gender. Although gender differentiation has been observed in a number of settings, the majority of studies focus on a single data stream in isolation. Here we use a dataset of high resolution data collected using mobile phones, as well as detailed questionnaires, to study gender differences in a large cohort. We consider mobility behavior and individual personality traits among a group of more than $800$ university students. We also investigate interactions among them expressed via person-to-person contacts, interactions on online social networks, and telecommunication. Thus, we are able to study the differences between male and female behavior captured through a multitude of channels for a single cohort. We find that while the two genders are similar in a number of aspects, there are robust deviations that include multiple facets of social interactions, suggesting the existence of inherent behavioral differences. Finally, we quantify how aspects of an individual's characteristics and social behavior reveals their gender by posing it as a classification problem. We ask: How well can we distinguish between male and female study participants based on behavior alone? Which behavioral features are most predictive

Systematic review of smartphone-based passive sensing for health and wellbeing

OBJECTIVE: To review published empirical literature on the use of smartphone-based passive sensing for health and wellbeing. MATERIAL AND METHODS: A systematic review of the English language literature was performed following PRISMA guidelines. Papers indexed in computing, technology, and medical databases were included if they were empirical, focused on health and/or wellbeing, involved the collection of data via smartphones, and described the utilized technology as passive or requiring minimal user interaction. RESULTS: Thirty-five papers were included in the review. Studies were performed around the world, with samples of up to 171 (median n = 15) representing individuals with bipolar disorder, schizophrenia, depression, older adults, and the general population. The majority of studies used the Android operating system and an array of smartphone sensors, most frequently capturing accelerometry, location, audio, and usage data. Captured data were usually sent to a remote server for processing but were shared with participants in only 40% of studies. Reported benefits of passive sensing included accurately detecting changes in status, behavior change through feedback, and increased accountability in participants. Studies reported facing technical, methodological, and privacy challenges. DISCUSSION: Studies in the nascent area of smartphone-based passive sensing for health and wellbeing demonstrate promise and invite continued research and investment. Existing studies suffer from weaknesses in research design, lack of feedback and clinical integration, and inadequate attention to privacy issues. Key recommendations relate to developing passive sensing strategies matching the problem at hand, using personalized interventions, and addressing methodological and privacy challenges. CONCLUSION: As evolving passive sensing technology presents new possibilities for health and wellbeing, additional research must address methodological, clinical integration, and privacy issues. Doing so depends on interdisciplinary collaboration between informatics and clinical experts

THE EFFECTS OF MOBILE DEVICE USE ON SOCIAL INTERACTIONS AMONG COLLEGE STUDENTS

This paper evaluates the impact that increased cellphone use causes on face-to- face interactions. An introduction to the literature will show the dramatic increase of cell phone ownership across the United States (Anderson, 2015). This dramatic increase can have numerous effects on all persons who own a cellular device. A brief look at the research conducted by different researchers (Hakuno, Omori, Yamamoto, & Minigawa, 2017; Gottman, Gonso, & Rasmussen, 1975; Hay, n.d.; Shneidman & Woodward, 2016), reveals that cell phones can have a negative impact on the users, if used in excessive amounts. The current study uses true experimental design to measure the impact that cell phones have on our face-to-face interactions. 37 students from a Central Florida university participated in the experiment. Each participant came in to the study and interacted with a confederate, either with or without their phone. In the end, the research showed no statistically significant evidence that cell phones caused a decrease in the number of interactions, as well as, the length of time each interaction occurred

Digital Literacy for Older Adult English Language Learners

When essential services transition to digital platforms, individuals with limited digital proficiency, immigrant English Language Learners (ELLs), and older adults aged 65 and above face challenges accessing these resources, leading to potential exclusion. The COVID-19 pandemic accelerated the shift to online interactions and services due to lockdown measures, reducing face-to-face interactions. This sudden transition left individuals without digital skills unable to access healthcare, essential services, and maintain connections with their support networks. Addressing this issue presents an opportunity to promote inclusivity, empowerment, and community engagement through targeted digital literacy training. Digital literacy encompasses the ability to navigate technology such as smartphones, applications, and the internet. However, existing digital literacy courses for adults often assume familiarity with computers, website navigation, and intermediate English proficiency. This gap highlights the need for tailored digital skills training for beginner ELLs. The Digital ESL field project, informed by Kolb\u27s Experiential Theory and aligned with the U.S. Department of Education recommendations on digital literacy education, aims to bridge this gap. By supporting community-based programs, this project equips newcomers, immigrants, and refugees with essential digital skills, empowering them to thrive in a digital society

The Influence of Personal Values on Internet Use and Wellbeing [La influencia de los valores personales en el uso de Internet y el bienestar]

AbstractPersonal values influence the behavior, feelings, and lives of individuals, but also, Internet use which penetration is expected it continues expanding all over the world. Values determine attitudes and behaviors of individuals and they also affect relationships people maintain with others and themselves. Furthermore, those relations are as well influenced by the adoption and usage of the internet, that is changing the way individuals interact and relate. So, both, values and internet use, impact on individuals Wellbeing (WB) perception. The present study analyses the influence of personal values on internet use and WB perception on a  sample of 33.123 respondents of the European Social Survey (2016), 51% of female respondents and 47.9% male aged 15 and over, from different European countries. By this way, first, an Exploratory Factorial Analysis has been applied on data related to personal values, and four different profiles have been defined. Second, there have been individually analyzed and correlated the level of internet use and life satisfaction individuals report to analyze their influence on each profile.  Finally, the interaction of both variables has been considered. When p-value is significative (p < 0.05) individual profile moderate relationship between internet use and life satisfaction. Results demonstrate personal values influence internet use and life satisfaction.ResumenLos valores personales influyen en el comportamiento, los sentimientos y la vida de las personas, pero también, el uso de Internet cuya penetración se espera sigue expandiéndose por todo el mundo. Los valores determinan las actitudes y los comportamientos de las personas, y también afectan las relaciones que las personas mantienen con los demás y con ellas mismas. Además, esas relaciones se ven influenciadas por la adopción y el uso de Internet, lo que está cambiando la forma en que las personas interactúan y se relacionan. Así, tanto los valores como el uso de Internet, impactan en la percepción del Bienestar (WB) de las personas. El presente estudio analiza la influencia de los valores personales en el uso de Internet y la percepción del Bienestar en una muestra de 33123 encuestados de la Encuesta Social Europea (2016), 51 % de mujeres encuestadas y 47.9 % hombres de 15 y más años, de diferentes países europeos. De esta forma, en primer lugar, se ha aplicado un Análisis Factorial Exploratorio sobre datos relacionados con los valores personales, y se han definido cuatro perfiles diferentes. En segundo lugar, se ha analizado y correlacionado individualmente el nivel de uso de Internet y la satisfacción con la vida que reportan las personas para analizar su influencia en cada perfil. Finalmente, se ha considerado la interacción de ambas variables. Cuando el valor p es significativo (p < .05), el perfil individual modera la relación entre el uso de Internet y la satisfacción con la vida. Los resultados demuestran que los valores personales influyen en el uso de Internet y la satisfacción con la vid

Multimodal Sensor Data Integration for Indoor Positioning in Ambient-Assisted Living Environments

A reliable Indoor Positioning System (IPS) is a crucial part of the Ambient-Assisted Living (AAL) concept. The use of Wi-Fi fingerprinting techniques to determine the location of the user, based on the Received Signal Strength Indication (RSSI) mapping, avoids the need to deploy a dedicated positioning infrastructure but comes with its own issues. Heterogeneity of devices and RSSI variability in space and time due to environment changing conditions pose a challenge to positioning systems based on this technique. The primary purpose of this research is to examine the viability of leveraging other sensors in aiding the positioning system to provide more accurate predictions. In particular, the experiments presented in this work show that Inertial Motion Units (IMU), which are present by default in smart devices such as smartphones or smartwatches, can increase the performance of Indoor Positioning Systems in AAL environments. Furthermore, this paper assesses a set of techniques to predict the future performance of the positioning system based on the training data, as well as complementary strategies such as data scaling and the use of consecutive Wi-Fi scanning to further improve the reliability of the IPS predictions. This research shows that a robust positioning estimation can be derived from such strategies