Ethical Issues in Democratizing Digital Phenotypes and Machine Learning in the Next Generation of Digital Health Technologies.

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.

An analysis of the impact of suicide prevention messages and memorials on motorway bridges.

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.

Behavior of Callers to a Crisis Helpline Before and During the COVID-19 Pandemic: Quantitative Data Analysis.

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.

Why do people call crisis helplines? Identifying taxonomies of presenting reasons and discovering associations between these reasons.

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.

Anticipated Task Difficulty Provokes Pace Conservation and Slower Running Performance.

PURPOSE: Models of self-paced endurance performance suggest that accurate knowledge of the exercise end-point influences pace-related decision making. No studies have examined the effects of anticipated task difficulty during equidistant endurance activities. Accordingly, the purpose of this study was to investigate the effects of anticipated task difficulty on pacing, psychological, and physiological responses during running time trials. METHODS: Twenty-eight trained runners completed three self-paced 3000-m time trials. The first was a baseline time trial completed on a 0% treadmill gradient. Time trials 2 and 3 were counterbalanced. Before a known incline time trial, anticipated to be more difficult, subjects were accurately informed that the gradient would increase to 7% for the final 800 m. Before an equivalent, unknown incline (UI) time trial subjects were deceptively informed that the gradient would remain at 0% throughout. RESULTS: Expressed relative to baseline, running speed was 2.44% slower (d = -0.47) over the first 2200 m during known incline (KI) time trial than UI time trial. Effort perception, affective valence, heart rate, and blood lactate did not differ between time trials. Initial running speed during KI was related to pretrial motivation, pretrial vigor, perceived effort, and affective valence (all r ≥ 0.382). No such relationships existed during UI. More subjects also reported a conscious focus on pacing during KI. CONCLUSIONS: An anticipated increase in task difficulty provoked pace conservation during 3000 m running time trials. The reduced pace may have resulted from greater task uncertainty and consciously aware, effort- and affect-based decisions to conserve energy and maintain hedonic state during KI. The findings add to theoretical understandings of factors that influence pacing during endurance activity. Consequently, recommendations to minimize the potentially deleterious effects of anticipated increases in task difficulty are provided.