Using Facebook for Improving the Psychological Well-Being of Individuals Experiencing Homelessness: Experimental and Longitudinal Study

A Lifeline to Fill the Silence of Homelessness: Person-Centered Analysis of Digital Coping and Links to Mental and Physical Health

Individuals experiencing homelessness are among the most vulnerable population for mental and physical health disparities. Despite navigating numerous stressors on a day-to-day basis, they are vastly underrepresented within coping research. Using a person-centered approach, this study addresses ways in which technology is leveraged to manage ongoing stressors associated with the experience of homelessness. We employed a two-step and k-means cluster analysis within a sample of unhoused individuals (n = 66). Two distinct clusters emerged, revealing unique patterning of digital coping, stress, self-efficacy, and technology use. Resulting clusters were validated across numerous health outcomes, including mental and physical health problems, as well as digital service use and experience of homelessness. High digital coping/low self-efficacy individuals (65% of sample) reported high levels of digital self-efficacy, yet lower levels of general self-efficacy. In contrast, low digital engagement/high self-efficacy individuals (35% of sample) engaged in relatively lower digital coping and technology use, with lower stress and higher general self-efficacy. High digital coping/low self-efficacy individuals, in turn, reported more mental and physical health problems; whereas low digital engagement/high self-efficacy reported somewhat decreased digital access. Relatively few differences emerged between the clusters on experiences of homelessness. Due to the transient nature of unhoused people, reaching such vulnerable populations via technology to support their digital coping and subsequently enhance well-being outcomes represents a critical next step for digital equity. This population is poised to benefit from digital equity efforts, with critical implications for reduced health disparities.

Identifying Marijuana Use Behaviors Among Youth Experiencing Homelessness Using a Machine Learning-Based Framework: Development and Evaluation Study

BACKGROUND

Youth experiencing homelessness face substance use problems disproportionately compared to other youth. A study found that 69% of youth experiencing homelessness meet the criteria for dependence on at least 1 substance, compared to 1.8% for all US adolescents. In addition, they experience major structural and social inequalities, which further undermine their ability to receive the care they need.

OBJECTIVE

The goal of this study was to develop a machine learning-based framework that uses the social media content (posts and interactions) of youth experiencing homelessness to predict their substance use behaviors (ie, the probability of using marijuana). With this framework, social workers and care providers can identify and reach out to youth experiencing homelessness who are at a higher risk of substance use.

METHODS

We recruited 133 young people experiencing homelessness at a nonprofit organization located in a city in the western United States. After obtaining their consent, we collected the participants' social media conversations for the past year before they were recruited, and we asked the participants to complete a survey on their demographic information, health conditions, sexual behaviors, and substance use behaviors. Building on the social sharing of emotions theory and social support theory, we identified important features that can potentially predict substance use. Then, we used natural language processing techniques to extract such features from social media conversations and reactions and built a series of machine learning models to predict participants' marijuana use.

RESULTS

We evaluated our models based on their predictive performance as well as their conformity with measures of fairness. Without predictive features from survey information, which may introduce sex and racial biases, our machine learning models can reach an area under the curve of 0.72 and an accuracy of 0.81 using only social media data when predicting marijuana use. We also evaluated the false-positive rate for each sex and age segment.

CONCLUSIONS

We showed that textual interactions among youth experiencing homelessness and their friends on social media can serve as a powerful resource to predict their substance use. The framework we developed allows care providers to allocate resources efficiently to youth experiencing homelessness in the greatest need while costing minimal overhead. It can be extended to analyze and predict other health-related behaviors and conditions observed in this vulnerable community.

Access to employment and the labor market among women living homeless in Madrid, Spain

BACKGROUND

People living homeless represent one of the most extreme embodiments of the phenomena of poverty and social exclusion, and women are a particularly vulnerable group among people living homeless.

METHODS

Various factors in a sample of women living homeless in Madrid, Spain (n = 136) have been analyzed for relationships to connections to the employment and labor market. Information was collected using a structured interview.

RESULTS

Results show the considerable difficulties women living homeless have in accessing the employment and labor market, despite largely having worked throughout their lives, mainly in unstable jobs, in the informal sector or in related marginal activities. In general, women living homeless tended to attribute their difficulties in accessing the labor market to personal characteristics, dispositional factors, or situational factors beyond their control. A large number of interviewees wanted to work, although few of them did so. Interviewees who reported that they were seeking employment were primarily younger women, in better health, who had been unemployed for a short time, had spent less time homeless, and were of foreign origin.

Use of Technology to Promote Health and Wellbeing of People Who Are Homeless: A Systematic Review

BACKGROUND

People who are homeless experience poorer health outcomes and challenges accessing healthcare contribute to the experienced health inequality. There has been an expansion in using technology to promote health and wellbeing and technology has the potential to enable people who are socially excluded, including those who are homeless, to be able to access health services. However, little research has been undertaken to explore how technology is used to promote health and wellbeing for those who are homeless. This review aims to address the questions: 'what mobile health (mHealth) related technology is used by homeless populations' and 'what is the health impact of mobile technology for homeless populations'?

METHODS

An integrative review methodology was employed. A systematic search of electronic databases was carried out between 4 January 2021 and 30 April 2021, searching for papers published between 2015 and 2021, which yielded 2113 hits, relevant papers were selected using specified inclusion and exclusion criteria reported using the Preferred Reporting Items for Systematic reviews and Meta-Analysis. The quality assessment of each paper included in the review was undertaken using the Mixed Methods Appraisal Tool.

RESULTS

Seventeen papers were selected for review and thematic analysis identified four themes: technology ownership, barriers to use, connectivity and health benefits.

CONCLUSION

It is evident that technology has the potential to support the health and wellbeing of individuals who are homeless; however, there are challenges regarding connectivity to the internet, as well as issues of trust in who has access to personal data and how they are used. Further research is needed to explore the use of health technology with people who are homeless to address these challenges.

Social Impact of Psychological Research on Well-Being Shared in Social Media

The purpose of this article is to demonstrate how the Social Impact in Social Media (SISM, hereinafter) methodology applied in psychological research provides evidence for the visibility of the social impact of the research. This article helps researchers become aware of whether and how their improvements are capturing the interest of citizens and how citizens are applying such evidence and obtaining better outcomes, in this case, in relation to well-being. In addition, citizens can access the latest evidence on social media and act as channels of communication between science and social or personal networks and, in doing so, they can improve the living conditions of others. This methodology is also useful for agencies that support researchers in psychology with financial assistance, which can use it to evaluate the social impact of the funds that they invest in research. In this article, the 10 studies on well-being were selected for analysis using the following criteria: their research results led to demonstrable improvement in well-being, and these improvements are presented on social media. We applied the social impact coverage ratio to identify the percentage of the social impact shared in social media in relation to the total amount of social media data collected. Finally, examples of quantitative and qualitative evidence of the social impact of the research on well-being are presented.

Is Facebook use healthy for individuals experiencing homelessness? A scoping review on social networking and living in the streets

Background: Although they are faced with a situation of extreme social exclusion, individuals experiencing homelessness (IEH) have gradually begun to incorporate the use of social networking sites (SNS) into their everyday lives. Aims: To review the publications that have examined the use of SNS among IEH and to analyze the impact that this online activity has on the health of these individuals. Methods: This study employed a scoping review method, analyzing scientific literature published up to the end of 2016. Results: An analysis was performed on nineteen peer-reviewed articles and three grey literature publications. IEH, especially those who are younger, use SNS in a similar proportion to the overall population. When these individuals used the networks due to their own initiative, it was found to have a positive health effect in that it mitigated the consequences of living on the street. Interventions aimed at improving the participants' health achieved positive results, both in terms of preventing problems associated with drug abuse and high-risk sexual behavior and of promoting mental health. Conclusions: The use of SNS presents some health benefits for IEH. Virtual communication and information alternatives provide opportunities to improve the mental and general health of people in social exclusion situations.