Phthalates are a class of known endocrine disrupting chemicals that are found in common everyday products. Several studies associate phthalate exposure with detrimental effects on ovarian functions, including growth and development of the follicle and production of steroid hormones. We hypothesized that dysregulation of the ovary by phthalates may be mediated by phthalate toxicity towards granulosa cells, a major cell type in ovarian follicles responsible for key steps of hormone production and nourishing the developing oocyte. To test the hypothesis that phthalates target granulosa cells, we harvested granulosa cells from adult CD-1 mouse ovaries and cultured them for 96 hours in vehicle control, a phthalate mixture, or a phthalate metabolite mixture (0.1-100 µg/mL). After culture, we measured metabolism of the phthalate mixture into monoester metabolites by the granulosa cells, finding that granulosa cells do not significantly contribute to ovarian metabolism of phthalates. Immunohistochemistry of phthalate metabolizing enzymes in whole ovaries confirmed that these enzymes are not strongly expressed in granulosa cells of antral follicles and that ovarian metabolism of phthalates likely occurs primarily in the stroma. RNA sequencing of treated granulosa cells identified 407 differentially expressed genes, with overrepresentation of genes from lipid metabolic processes, cholesterol metabolism, and peroxisome proliferator-activated receptor (PPAR) signaling pathways. Expression of significantly differentially expressed genes related to these pathways were confirmed using qPCR. Our results agree with previous findings that phthalates and phthalate metabolites have different effects on the ovary and interfere with PPAR signaling in granulosa cells.
INTRODUCTION: Despite the evidence supporting the value of digital supports for enhancing youth mental health services, there is a lack of guidance on how best to engage with young people in coproduction processes during the design and evaluation of these technologies. User input is crucial in digital mental health, especially for disadvantaged, vulnerable and marginalised young people as they are often excluded from coproduction. A scoping review of international literature written in English will explore the coproduction processes with marginalised young people in digital mental health supports, from mental health promotion to targeted interventions. The review is guided by the research question: what are the most appropriate coproduction processes for engaging young people, especially marginalised young people, in the different stages of designing and evaluating digital mental health supports? The review aims to map and summarise the evidence, inform the overall research project and address the knowledge gaps. METHODS AND ANALYSIS: The scoping review uses Arksey and O'Malley's framework and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols Extension for Scoping Reviews. From 22-24 October 2023, PubMed, Scopus, EBSCO, ASSIA, Web of Science, Ovid MEDLINE, Cochrane database, Embase, Google Scholar, ProQuest, OAIster and BASE will be systematically searched. Papers from 2021 onwards with a range of study designs and evidence that illustrate engagement with marginalised young people (aged 16-25) in the design, implementation and evaluation of digital technologies for young people's mental health will be considered for inclusion. At least two reviewers will screen full texts and chart data. The results of this review will be summarised quantitatively through numerical counts of included literature and qualitatively through a narrative synthesis. ETHICS AND DISSEMINATION: Ethical approval is not required. Results will be disseminated through publications in peer-reviewed journals. TRIAL REGISTRATION NUMBER: This scoping review protocol has been registered with the Open Science Framework (https://osf.io/9xhgv).
Mental Health Services , Humans , Adolescent , Mental Health Services/organization & administration , Mental Health , Young Adult , Research Design , Review Literature as Topic
BACKGROUND: In recent years, advances in technology have led to an influx of mental health apps, in particular the development of mental health and well-being chatbots, which have already shown promise in terms of their efficacy, availability, and accessibility. The ChatPal chatbot was developed to promote positive mental well-being among citizens living in rural areas. ChatPal is a multilingual chatbot, available in English, Scottish Gaelic, Swedish, and Finnish, containing psychoeducational content and exercises such as mindfulness and breathing, mood logging, gratitude, and thought diaries. OBJECTIVE: The primary objective of this study is to evaluate a multilingual mental health and well-being chatbot (ChatPal) to establish if it has an effect on mental well-being. Secondary objectives include investigating the characteristics of individuals that showed improvements in well-being along with those with worsening well-being and applying thematic analysis to user feedback. METHODS: A pre-post intervention study was conducted where participants were recruited to use the intervention (ChatPal) for a 12-week period. Recruitment took place across 5 regions: Northern Ireland, Scotland, the Republic of Ireland, Sweden, and Finland. Outcome measures included the Short Warwick-Edinburgh Mental Well-Being Scale, the World Health Organization-Five Well-Being Index, and the Satisfaction with Life Scale, which were evaluated at baseline, midpoint, and end point. Written feedback was collected from participants and subjected to qualitative analysis to identify themes. RESULTS: A total of 348 people were recruited to the study (n=254, 73% female; n=94, 27% male) aged between 18 and 73 (mean 30) years. The well-being scores of participants improved from baseline to midpoint and from baseline to end point; however, improvement in scores was not statistically significant on the Short Warwick-Edinburgh Mental Well-Being Scale (P=.42), the World Health Organization-Five Well-Being Index (P=.52), or the Satisfaction With Life Scale (P=.81). Individuals that had improved well-being scores (n=16) interacted more with the chatbot and were significantly younger compared to those whose well-being declined over the study (P=.03). Three themes were identified from user feedback, including "positive experiences," "mixed or neutral experiences," and "negative experiences." Positive experiences included enjoying exercises provided by the chatbot, while most of the mixed, neutral, or negative experiences mentioned liking the chatbot overall, but there were some barriers, such as technical or performance errors, that needed to be overcome. CONCLUSIONS: Marginal improvements in mental well-being were seen in those who used ChatPal, albeit nonsignificant. We propose that the chatbot could be used along with other service offerings to complement different digital or face-to-face services, although further research should be carried out to confirm the effectiveness of this approach. Nonetheless, this paper highlights the need for blended service offerings in mental health care.
Exercise , Mental Health , Humans , Male , Female , Adolescent , Young Adult , Adult , Middle Aged , Aged , Software , Exercise Therapy , Psychological Well-Being
BACKGROUND: Conversational user interfaces, or chatbots, are becoming more popular in the realm of digital health and well-being. While many studies focus on measuring the cause or effect of a digital intervention on people's health and well-being (outcomes), there is a need to understand how users really engage and use a digital intervention in the real world. OBJECTIVE: In this study, we examine the user logs of a mental well-being chatbot called ChatPal, which is based on the concept of positive psychology. The aim of this research is to analyze the log data from the chatbot to provide insight into usage patterns, the different types of users using clustering, and associations between the usage of the app's features. METHODS: Log data from ChatPal was analyzed to explore usage. A number of user characteristics including user tenure, unique days, mood logs recorded, conversations accessed, and total number of interactions were used with k-means clustering to identify user archetypes. Association rule mining was used to explore links between conversations. RESULTS: ChatPal log data revealed 579 individuals older than 18 years used the app with most users being female (n=387, 67%). User interactions peaked around breakfast, lunchtime, and early evening. Clustering revealed 3 groups including "abandoning users" (n=473), "sporadic users" (n=93), and "frequent transient users" (n=13). Each cluster had distinct usage characteristics, and the features were significantly different (P<.001) across each group. While all conversations within the chatbot were accessed at least once by users, the "treat yourself like a friend" conversation was the most popular, which was accessed by 29% (n=168) of users. However, only 11.7% (n=68) of users repeated this exercise more than once. Analysis of transitions between conversations revealed strong links between "treat yourself like a friend," "soothing touch," and "thoughts diary" among others. Association rule mining confirmed these 3 conversations as having the strongest linkages and suggested other associations between the co-use of chatbot features. CONCLUSIONS: This study has provided insight into the types of people using the ChatPal chatbot, patterns of use, and associations between the usage of the app's features, which can be used to further develop the app by considering the features most accessed by users.
Mental Health , Mobile Applications , Humans , Female , Male , Psychological Well-Being , Affect , Cluster Analysis
This paper makes a case for digital mental health and provides insights into how digital technologies can enhance (but not replace) existing mental health services. We describe digital mental health by presenting a suite of digital technologies (from digital interventions to the application of artificial intelligence). We discuss the benefits of digital mental health, for example, a digital intervention can be an accessible stepping-stone to receiving support. The paper does, however, present less-discussed benefits with new concepts such as 'poly-digital', where many different apps/features (e.g. a sleep app, mood logging app and a mindfulness app, etc.) can each address different factors of wellbeing, perhaps resulting in an aggregation of marginal gains. Another benefit is that digital mental health offers the ability to collect high-resolution real-world client data and provide client monitoring outside of therapy sessions. These data can be collected using digital phenotyping and ecological momentary assessment techniques (i.e. repeated mood or scale measures via an app). This allows digital mental health tools and real-world data to inform therapists and enrich face-to-face sessions. This can be referred to as blended care/adjunctive therapy where service users can engage in 'channel switching' between digital and non-digital (face-to-face) interventions providing a more integrated service. This digital integration can be referred to as a kind of 'digital glue' that helps join up the in-person sessions with the real world. The paper presents the challenges, for example, the majority of mental health apps are maybe of inadequate quality and there is a lack of user retention. There are also ethical challenges, for example, with the perceived 'over-promotion' of screen-time and the perceived reduction in care when replacing humans with 'computers', and the trap of 'technological solutionism' whereby technology can be naively presumed to solve all problems. Finally, we argue for the need to take an evidence-based, systems thinking and co-production approach in the form of stakeholder-centred design when developing digital mental health services based on technologies. The main contribution of this paper is the integration of ideas from many different disciplines as well as the framework for blended care using 'channel switching' to showcase how digital data and technology can enrich physical services. Another contribution is the emergence of 'poly-digital' and a discussion on the challenges of digital mental health, specifically 'digital ethics'.
The goal of the current exploratory study was to examine the feasibility and acceptability of an evidence-based group counseling intervention for individuals with opioid use disorders (OUD) reporting mental health issues and using medications for OUD. The intervention combines motivational interviewing and cognitive-behavioral therapy. Qualitative research methodology, specifically focus group interviewing, with seven individuals was used to examine the feasibility and acceptability of the intervention. Qualitative analysis of the focus group yielded four themes: Intervention Format, Group Counseling Factors, Comorbid Mental Health Issues, and Counselor Factors. The intervention proposed was found to be acceptable and feasible for addressing OUD and co-occurring mental health conditions, specifically depression, anxiety, and stress. [Journal of Psychosocial Nursing and Mental Health Services, 60(6), 7-10.].
Mental Health Services , Motivational Interviewing , Opioid-Related Disorders , Comorbidity , Feasibility Studies , Humans , Opioid-Related Disorders/drug therapy
This study explored homeless people's (N = 164) spiritual well-being (SWB) in relation to race, mental illness, physical disease, resilience, and trait mindfulness. The results of hierarchical regression analysis revealed that variables of race (p = 0.003), mental illness (p = 0.04), resilience (p < 0.001) and trait mindfulness (p < 0.001) contributed to participants' SWB. These findings were critical to research related to homelessness and service provisions in finding that homeless people with certain backgrounds (e.g., mental illness) might have lower SWB than their counterparts. This research also revealed protective factors (e.g., resilience) that could help promote SWB.
Ill-Housed Persons , Mental Disorders , Humans , Regression Analysis
Digital phenotyping is the term given to the capturing and use of user log data from health and wellbeing technologies used in apps and cloud-based services. This paper explores ethical issues in making use of digital phenotype data in the arena of digital health interventions. Products and services based on digital wellbeing technologies typically include mobile device apps as well as browser-based apps to a lesser extent, and can include telephony-based services, text-based chatbots, and voice-activated chatbots. Many of these digital products and services are simultaneously available across many channels in order to maximize availability for users. Digital wellbeing technologies offer useful methods for real-time data capture of the interactions of users with the products and services. It is possible to design what data are recorded, how and where it may be stored, and, crucially, how it can be analyzed to reveal individual or collective usage patterns. The paper also examines digital phenotyping workflows, before enumerating the ethical concerns pertaining to different types of digital phenotype data, highlighting ethical considerations for collection, storage, and use of the data. A case study of a digital health app is used to illustrate the ethical issues. The case study explores the issues from a perspective of data prospecting and subsequent machine learning. The ethical use of machine learning and artificial intelligence on digital phenotype data and the broader issues in democratizing machine learning and artificial intelligence for digital phenotype data are then explored in detail.
Recently, there has been activity at public locations where people have died by suicide, including the erection of suicide prevention messages and memorials (decorations). This research looks at the impact of these decorations and associated media coverage of the decorations on suicidal behaviour at bridges. Incidents (n = 160) of suicidal behaviour on 26 bridges across motorways in England were analysed. Overall, there was no significant difference in the proportion of incidents pre-decoration versus post-decoration (p-value = .55). The incident rates were not significantly different pre- and post-decoration (p = .46). Only one bridge had statistically significantly more incidents post-decoration and media reporting (p = .03). However, following correction for multiple testing there was no significant difference in pre- and post-incident rates at any of the bridges. In total, 58% of bridges had a greater frequency of incidents when decorations were absent; however, this proportion was not statistically significant (p = .41). Further research is required to establish how suicide prevention messages are perceived. There does not appear to be any benefit, but it often generates media coverage which has been shown to increase risk.
Communications Media , Suicide Prevention , Humans , Suicidal Ideation
BACKGROUND: The World Health Organization declared the outbreak of COVID-19 to be an international pandemic in March 2020. While numbers of new confirmed cases of the disease and death tolls are rising at an alarming rate on a daily basis, there is concern that the pandemic and the measures taken to counteract it could cause an increase in distress among the public. Hence, there could be an increase in need for emotional support within the population, which is complicated further by the reduction of existing face-to-face mental health services as a result of measures taken to limit the spread of the virus. OBJECTIVE: The objective of this study was to determine whether the COVID-19 pandemic has had any influence on the calls made to Samaritans Ireland, a national crisis helpline within the Republic of Ireland. METHODS: This study presents an analysis of calls made to Samaritans Ireland in a four-week period before the first confirmed case of COVID-19 (calls=41,648, callers=3752) and calls made to the service within a four-week period after a restrictive lockdown was imposed by the government of the Republic of Ireland (calls=46,043, callers=3147). Statistical analysis was conducted to explore any differences between the duration of calls in the two periods at a global level and at an hourly level. We performed k-means clustering to determine the types of callers who used the helpline based on their helpline call usage behavior and to assess the impact of the pandemic on the caller type usage patterns. RESULTS: The analysis revealed that calls were of a longer duration in the postlockdown period in comparison with the pre-COVID-19 period. There were changes in the behavior of individuals in the cluster types defined by caller behavior, where some caller types tended to make longer calls to the service in the postlockdown period. There were also changes in caller behavior patterns with regard to the time of day of the call; variations were observed in the duration of calls at particular times of day, where average call durations increased in the early hours of the morning. CONCLUSIONS: The results of this study highlight the impact of COVID-19 on a national crisis helpline service. Statistical differences were observed in caller behavior between the prelockdown and active lockdown periods. The findings suggest that service users relied on crisis helpline services more during the lockdown period due to an increased sense of isolation, worsening of underlying mental illness due to the pandemic, and reduction or overall removal of access to other support resources. Practical implications and limitations are discussed.
BACKGROUND: User-interaction event logs provide rich and large data sets that can provide valuable insights into how people engage with technology. Approaches such as ecological momentary assessment (EMA) can be used to gather accurate real-time data in an individual's natural environment by asking questions at any given instant. OBJECTIVE: The purpose of this study was to evaluate user engagement and responses to EMA questions using InspireD, an app used for reminiscence by persons with dementia and their caregivers. Research findings can be used to inform EMA use within digital health interventions. METHODS: A feasibility trial was conducted in which participants (n=56) used the InspireD app over a 12-week period. Participants were a mean age of 73 (SD 13) and were either persons with dementia (n=28) or their caregivers (n=28). Questions, which they could either answer or choose to dismiss, were presented to participants at various instants after reminiscence with personal or generic photos, videos, and music. Presentation and dismissal rates for questions were compared by hour of the day and by trial week to investigate user engagement. RESULTS: Overall engagement was high, with 69.1% of questions answered when presented. Questions that were presented in the evening had the lowest dismissal rate; the dismissal rate for questions presented at 9 PM was significantly lower than the dismissal rate for questions presented at 11 AM (9 PM: 10%; 11 AM: 50%; χ21=21.4, P<.001). Questions asked following reminiscence with personal media, especially those asked after personal photos, were less likely to be answered compared to those asked after other media. In contrast, questions asked after the user had listened to generic media, in particular those asked after generic music, were much more likely to be answered. CONCLUSIONS: The main limitation of our study was the lack of generalizability of results to a larger population given the quasi-experimental design and older demographic where half of participants were persons with dementia; however, this study shows that older people are willing to participate and engage in EMA. Based on this study, we propose a series of recommendations for app design to increase user engagement with EMA. These include presenting questions no more than once per day, after 8 PM in the evening, and only if the user is not trying to complete a task within the app.
Caregivers , Dementia , Ecological Momentary Assessment , Aged , Aged, 80 and over , Dementia/therapy , Female , Humans , Male , Research Design
The objective of this study is to identify the most common reasons for contacting a crisis helpline through analysing a large call log data set. Two taxonomies were identified within the call log data from a Northern Ireland telephone crisis helpline (Lifeline), categorising the cited reason for each call. One taxonomy categorised the reasons at a fine granular level; the other taxonomy used the relatively coarser International Classification of Diseases-10. Exploratory data analytic techniques were applied to discover insights into why individuals contact crisis helplines. Risk ratings of calls were also compared to assess the associations between presenting issue and of risk of suicide as assessed. Reasons for contacting the service were assessed across geolocations. Association rule mining was used to identify associations between the presenting reasons for client's calls. Results demonstrate that both taxonomies show that calls with reasons relating to suicide are the most common reasons for contacting Lifeline and were a prominent feature of the discovered association rules. There were significant differences between reasons in both taxonomies concerning risk ratings. Reasons for calling helplines that are associated with higher risk ratings include those calling with a personality disorder, mental disorders, delusional disorders and drugs (legal). In conclusion, employing two differing taxonomy approaches to analyse call log data reveals the prevalence of main presenting reasons for contacting a crisis helpline. The association rule mining using each taxonomy provided insights into the associations between presenting reasons. Practical and research applications are discussed.
Mental Disorders , Suicide , Hotlines , Humans , Prevalence , Telephone
