An investigation of the information provided to the parents of young people with mental health needs on an internet forum

Commenting and connecting: A thematic analysis of responses to YouTube vlogs about borderline personality disorder

Borderline Personality Disorder (BPD) is an often misunderstood and stigmatized mental health difficulty. Increasingly, social media has been used as a forum to share dialogue on such difficulties. This research analysed YouTube comments in response to personal vlogs about living with BPD. The key term 'Living with Borderline Personality Disorder Vlog' was inputted into a YouTube Ireland search, results were displayed by relevance and the top four vlogs that met the criteria were chosen for analysis. A total of 1197 comments (approximately 55,574 words) were analysed using inductive thematic analysis (Braun and Clarke, 2006). Five distinct themes were identified: 1) Sharing advice, support and encouragement, 2) Vlogs destigmatizing, informing and educating, 3) Solidarity, relatability and personal connection, 4) Intense, unstable intrapersonal and interpersonal functioning, 5) Prompting disclosures about mental health struggles. The vlogs gave people insight and understanding, increasing empathy towards those suffering with BPD or with their mental health. The overall picture drawn from the data was one of solidarity, support, de-stigmatization, normalization, sharing, comfort and encouragement. Further research into people's attitudes towards BPD, their opinions and knowledge of the disorder, may help make important changes, inform policies and practice, and ultimately improve the lives of those living with the disorder.

Caregivers of children feel confident about using the internet for health information

BACKGROUND

Caregivers of children may rely on internet sources, health care providers, peers or family for health information.

OBJECTIVE

To examine the impact of sociodemographic factors on the use of the internet for health information by caregivers of children, and the impact on self-efficacy, effort and frustration.

METHODS

Using data from the 2019 Health Information National Trends Survey, the effects of information source on self-efficacy, effort and frustration was examined using the complex samples module of SPSS.

RESULTS

The internet was the most common source of health information for caregivers of children (n = 247), with high confidence, low frustration and effort reported. Younger, higher educated and higher income caregivers were significantly more likely to use the internet for health information. Information from Health Care Providers (HCPs) was associated with greater confidence, and information from peers associated with lesser effort and frustration. No significant effects on self-efficacy, effort or frustration for online health information was noted compared to other sources.

CONCLUSIONS

Efforts to reduce barriers to online health information may be required for some groups of caregivers, and health care providers may have a role to play in this.

Human-Computer Interaction in Digital Mental Health

Human-computer interaction (HCI) has contributed to the design and development of some efficient, user-friendly, cost-effective, and adaptable digital mental health solutions. But HCI has not been well-combined into technological developments resulting in quality and safety concerns. Digital platforms and artificial intelligence (AI) have a good potential to improve prediction, identification, coordination, and treatment by mental health care and suicide prevention services. AI is driving web-based and smartphone apps; mostly it is used for self-help and guided cognitive behavioral therapy (CBT) for anxiety and depression. Interactive AI may help real-time screening and treatment in outdated, strained or lacking mental healthcare systems. The barriers for using AI in mental healthcare include accessibility, efficacy, reliability, usability, safety, security, ethics, suitable education and training, and socio-cultural adaptability. Apps, real-time machine learning algorithms, immersive technologies, and digital phenotyping are notable prospects. Generally, there is a need for faster and better human factors in combination with machine interaction and automation, higher levels of effectiveness evaluation and the application of blended, hybrid or stepped care in an adjunct approach. HCI modeling may assist in the design and development of usable applications, and to effectively recognize, acknowledge, and address the inequities of mental health care and suicide prevention and assist in the digital therapeutic alliance.