Background: Adverse childhood experiences are strongly associated with mental disorders in young people. Parenting interventions are available through community health settings and can intervene with adverse childhood experiences that are within a parent's capacity to modify. Technology can minimize common barriers associated with engaging in face-to-face parenting interventions. However, families experiencing adversity face unique barriers to engaging with technology-assisted parenting interventions. Formative research using co-design methodology to provide a deep contextual understanding of these barriers can help overcome unique barriers and ensure these families can capitalize on the benefits of technology-assisted parenting interventions.
Objective: This study aims to innovate the parenting support delivered by a community health and social service with technology by adapting an existing, evidence-based, technology-assisted parenting intervention.
Methods: Staff (n=3) participated in dialogues (n=2) and co-design workshops (n=8) exploring needs and preferences for a technology-assisted parenting intervention and iteratively developing a prototype intervention (Parenting Resilient Kids [PaRK]-Lite). Parents (n=3) received PaRK-Lite and participated in qualitative interviews to provide feedback on their experience and PaRK-Lite's design.
Results: PaRK-Lite's hybrid design leverages simple and familiar modes of technology (podcasts) to deliver intervention content and embeds reflective practice into service provision (microcoaching) to enhance parents' empowerment and reduce service dependency. A training session, manuals, session plans, and templates were also developed to support the delivery of microcoaching. Feedback data from parents overall indicated that PaRK-Lite met their needs, suggesting that service providers can play a key role in the early phases of service innovation for parents.
Conclusions: The co-designed technology-assisted parenting intervention aims to offer both parents and clinicians a novel and engaging resource for intervening with maladaptive parenting, contributing to efforts to respond to childhood adversity and improve child mental health. Future research in the field of human-computer interaction and health service design can consider our findings in creating engaging interventions that have a positive impact on the well-being of children and families.
Background: The field of epidemiological criminology (or justice health research) has emerged in the past decade, studying the intersection between the public health and justice systems. To ensure research efforts are focused and equitable, it is important to reflect on the outputs in this area and address knowledge gaps.
Objective: This study aimed to examine the characteristics of populations researched in a large sample of published outputs and identify research gaps and biases.
Methods: A rule-based, text mining method was applied to 34,481 PubMed abstracts published from 1963 to 2023 to identify 4 population characteristics (sex, age, offender type, and nationality).
Results: We evaluated our method in a random sample of 100 PubMed abstracts. Microprecision was 94.3%, with microrecall at 85.9% and micro-F1-score at 89.9% across the 4 characteristics. Half (n=17,039, 49.4%) of the 34,481 abstracts did not have any characteristic mentions and only 1.3% (n=443) reported sex, age, offender type, and nationality. From the 5170 (14.9%) abstracts that reported age, 3581 (69.3%) mentioned young people (younger than 18 years) and 3037 (58.7%) mentioned adults. Since 1990, studies reporting female-only populations increased, and in 2023, these accounted for almost half (105/216, 48.6%) of the research outputs, as opposed to 33.3% (72/216) for male-only populations. Nordic countries (Sweden, Norway, Finland, and Denmark) had the highest number of abstracts proportional to their incarcerated populations. Offenders with mental illness were the most common group of interest (840/4814, 17.4%), with an increase from 1990 onward.
Conclusions: Research reporting on female populations increased, surpassing that involving male individuals, despite female individuals representing 5% of the incarcerated population; this suggests that male prisoners are underresearched. Although calls have been made for the justice health area to focus more on young people, our results showed that among the abstracts reporting age, most mentioned a population aged <18 years, reflecting a rise of youth involvement in the youth justice system. Those convicted of sex offenses and crimes relating to children were not as researched as the existing literature suggests, with a focus instead on populations with mental illness, whose rates rose steadily in the last 30 years. After adjusting for the size of the incarcerated population, Nordic countries have conducted proportionately the most research. Our findings highlight that despite the presence of several research reporting guidelines, justice health abstracts still do not adequately describe the investigated populations. Our study offers new insights in the field of justice health with implications for promoting diversity in the selection of research participants.
Background: Despite the benefits of smoking cessation, maintaining abstinence during a quit attempt is difficult, and most attempts result in relapse. Innovative, evidence-based methods of preventing relapse are needed. We present a smartwatch-based relapse prevention system that uses passive detection of smoking to trigger just-in-time smoking cessation support.
Objective: This study aims to evaluate the feasibility of hosting just-in-time smoking cessation support on a smartwatch and the acceptability of the "StopWatch" intervention on this platform.
Methods: The person-based approach for intervention development was used to design the StopWatch smoking relapse prevention intervention. Intervention delivery was triggered by an algorithm identifying hand movements characteristic of smoking from the smartwatch's motion sensors, and the system-generated intervention messages (co-designed by smokers) were delivered on the smartwatch screen. A total of 18 smokers tested the intervention over a 2-week period, and at the end of this period, they provided qualitative feedback on the acceptability of both the intervention and the smartwatch platform.
Results: Participants reported that the smartwatch intervention increased their awareness of smoking and motivated them to quit. System-generated intervention messages were generally felt to be relevant and timely. There were some challenges with battery life that had implications for intervention adherence, and the bulkiness of the device and the notification style reduced some participants' acceptability of the smartwatch platform.
Conclusions: Our findings indicate our smoking relapse prevention intervention and the use of a smartwatch as a platform to host a just-in-time behavior change intervention are both feasible and acceptable to most (12/18, 66%) participants as a relapse prevention intervention, but we identify some concerns around the physical limitations of the smartwatch device. In particular, the bulkiness of the device and the battery capacity present risks to adherence to the intervention and the potential for missed detections. We recommend that a longer-term efficacy trial be carried out as the next step.
Background: Caregiver burden can impact the mental health of family caregivers, but self-compassion may help reduce this impact. Brief self-compassion interventions have been shown to be useful but have not been tested in family caregivers of older adults.
Objective: This study aimed to test the effects of a brief self-compassion intervention and its components (self-kindness, common humanity, and mindfulness) on mental well-being and mood when reflecting on difficult family caregiving experiences.
Methods: British caregivers were recruited through a web-based panel. Three experimental studies manipulated the self-compassion intervention. In study 1 (n=206) and study 2 (n=224), participants wrote about a difficult caregiving experience while focusing on 1 self-compassion component (self-kindness, common humanity, or mindfulness). In study 3 (n=222) participants focused on all components. Self-compassion, serenity, guilt, and sadness were measured.
Results: In studies 1 and 2, condition effects showed mindfulness unexpectedly lowered mood. Inconsistent and modest benefits to affect were achieved by engagement in self-kindness and common humanity in study 1 (guilt [lowered]: P=.02 and sadness [lowered]: P=.04; serenity [nonsignificantly raised]: P=.20) and also in study 2 (sadness [nonsignificantly lowered]: P=.23 and guilt [nonsignificantly lowered]: P=.26; serenity [raised]: P=.33); significant benefits for self-compassion and mood were found in study 3 (serenity [raised]: P=.01, kindness [raised]: P=.003, and common humanity [raised]: P≤.001; guilt [lowered]: P<.001 and sadness [lowered]: P≤.001). More intensive efforts should be made to promote self-compassion in caregivers of older adults, with caution advised when relying primarily on mindfulness approaches.
Conclusions: Self-compassionate writing may be beneficial for family caregivers, but more intensive interventions are needed. Further research is needed to determine the optimal dosage and content for achieving the greatest effects.
Background: Acceptance and commitment therapy (ACT) is promising in the treatment of early psychosis. Augmenting face-to-face ACT with mobile health ecological momentary interventions may increase its treatment effects and empower clients to take treatment into their own hands.
Objective: This study aimed to investigate and predict treatment engagement with and acceptability of acceptance and commitment therapy in daily life (ACT-DL), a novel ecological momentary intervention for people with an ultrahigh risk state and a first episode of psychosis.
Methods: In the multicenter randomized controlled trial, 148 individuals with ultrahigh risk or first-episode psychosis aged 15-65 years were randomized to treatment as usual only (control) or to ACT-DL combined with treatment as usual (experimental), consisting of 8 face-to-face sessions augmented with an ACT-based smartphone app, delivering ACT skills and techniques in daily life. For individuals in the intervention arm, we collected data on treatment engagement with and acceptability of ACT-DL during and after the intervention. Predictors of treatment engagement and acceptability included baseline demographic, clinical, and functional outcomes.
Results: Participants who received ACT-DL in addition to treatment as usual (n=71) completed a mean of 6 (SD 3) sessions, with 59% (n=42) of participants completing all sessions. App engagement data (n=58) shows that, on a weekly basis, participants used the app 13 times and were compliant with 6 of 24 (25%) notifications. Distribution plots of debriefing scores (n=46) show that 85%-96% of participants reported usefulness on all acceptability items to at least some extent (scores ≥2; 1=no usefulness) and that 91% (n=42) of participants reported perceived burden by number and length of notifications (scores ≥2; 1=no burden). Multiple linear regression models were fitted to predict treatment engagement and acceptability. Ethnic minority backgrounds predicted lower notification response compliance (B=-4.37; P=.01), yet higher app usefulness (B=1.25; P=.049). Negative (B=-0.26; P=.01) and affective (B=0.14; P=.04) symptom severity predicted lower and higher ACT training usefulness, respectively. Being female (B=-1.03; P=.005) predicted lower usefulness of the ACT metaphor images on the app.
Conclusions: Our results corroborate good treatment engagement with and acceptability of ACT-DL in early psychosis. We provide recommendations for future intervention optimization.
Trial registration: OMON NL46439.068.13; https://onderzoekmetmensen.nl/en/trial/24803.
Background: Low engagement with mental health apps continues to limit their impact. New approaches to help match patients to the right app may increase engagement by ensuring the app they are using is best suited to their mental health needs.
Objective: This study aims to pilot how digital phenotyping, using data from smartphone sensors to infer symptom, behavioral, and functional outcomes, could be used to match people to mental health apps and potentially increase engagement.
Methods: After 1 week of collecting digital phenotyping data with the mindLAMP app (Beth Israel Deaconess Medical Center), participants were randomly assigned to the digital phenotyping arm, receiving feedback and recommendations based on those data to select 1 of 4 predetermined mental health apps (related to mood, anxiety, sleep, and fitness), or the control arm, selecting the same apps but without any feedback or recommendations. All participants used their selected app for 4 weeks with numerous metrics of engagement recorded, including objective screentime measures, self-reported engagement measures, and Digital Working Alliance Inventory scores.
Results: A total of 82 participants enrolled in the study; 17 (21%) dropped out of the digital phenotyping arm and 18 (22%) dropped out from the control arm. Across both groups, few participants chose or were recommended the insomnia or fitness app. The majority (39/47, 83%) used a depression or anxiety app. Engagement as measured by objective screen time and Digital Working Alliance Inventory scores were higher in the digital phenotyping arm. There was no correlation between self-reported and objective metrics of app use. Qualitative results highlighted the importance of habit formation in sustained app use.
Conclusions: The results suggest that digital phenotyping app recommendation is feasible and may increase engagement. This approach is generalizable to other apps beyond the 4 apps selected for use in this pilot, and practical for real-world use given that the study was conducted without any compensation or external incentives that may have biased results. Advances in digital phenotyping will likely make this method of app recommendation more personalized and thus of even greater interest.
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