Journal of Medical Internet Research最新文献

Background: Mobile phone ecological momentary assessment (EMA) methods are a well-established measure of eating and drinking behaviors, but compliance can be poor. Micro-EMA (μEMA), which collects information with a single tap response to brief questions on smartwatches, offers a novel application that may improve response rates. To our knowledge, there is no data evaluating μEMA to measure eating habits in children or in low-to-middle-income countries.

Objective: In this study, we investigated the feasibility of micro-EMA to measure eating patterns in Malaysian children and adolescents.

Methods: We invited 100 children and adolescents aged 7-18 years in Segamat, Malaysia, to participate in 2021-2022. Smartwatches were distributed to 83 children and adolescents who agreed to participate. Participants were asked to wear the smartwatch for 8 days and respond to 12 prompts per day, hourly, from 9AM to 8PM, asking for information on their meals, snacks, and drinks consumed. A questionnaire captured their experiences using the smartwatch and μEMA interface. Response rate (proportion of prompts responded to) assessed participants' adherence. We explored associations between response rate with time of day, across days, age, and sex using multilevel binomial logistic regression modeling.

Results: Eighty-two participants provided usable smartwatch data. The median number (IQR) of meals, drinks, and snacks per day was 2 (2-4), 3 (1-5), and 1 (0-2), respectively, on the first day of the study. The median response rate across the study was 68% (IQR 50-83). The response rate decreased across study days from 74% (68-78) on Day 1 to 40% (30-50) on Day 7 (odds ratio [OR] per study day 0.73, 95% CI 0.64-0.83). Response rate was lowest at the start of the day and highest between the hours of 12 PM and 2 PM. Female participants responded to more prompts than male participants (OR 1.72, 95% CI 1.03-2.86). There was no evidence of differential response by age (OR 0.73, 95% CI 0.41-1.28). Most participants (65%) rated their experience using the smartwatch positively, with 33% saying they were happy to participate in future studies using the smartwatch. For children that did not wear the smartwatch for the full study duration (n=22), discomfort was the most common complaint (41%).

Conclusions: In this study of the feasibility of μEMA on smartwatches to measure eating in Malaysian children, we found the method was acceptable. However, response rates declined across study days, resulting in substantial missingness. Future studies (eg, through focus groups) should explore approaches to improving response to event prompts, trial alternative devices to increase children's comfort, and evaluate revised protocols for reporting of intake events.

Background: To meet the needs of individuals diagnosed with autism, internet-based interventions have been developed with a variety of objectives. A deeper understanding of the mechanisms of change may help tailor interventions to individual needs. The communicative behaviors of individuals with autism participating in text-based internet-based interventions remain largely unexplored, as do their potential relations to clinical outcomes. An improved understanding of participants' behaviors may help therapists better tailor support, promote engagement, and enhance treatment outcomes.

Objective: This study aimed to explore the communicative behaviors of individuals with autism participating in an internet-based intervention and to examine whether different behavioral patterns were associated with treatment outcomes or treatment adherence.

Methods: Messages from 34 participants enrolled in an 18-week internet-based cognitive behavioral therapy program were analyzed using abductive qualitative content analysis. Correlational analyses were used to examine the relationships between qualitative categories and change scores on outcome measures and rates of module completion.

Results: Fourteen behavioral categories were identified and grouped into three overarching domains: (1) "This is me," which encompasses the participants' narratives on identity, personality, autistic functioning, current and past circumstances, and worldview; (2) "Working with the treatment," which included statements related to engagement with the treatment process; and (3) "I struggle," which comprised of past and present negative experiences and challenges. Correlational analyses revealed associations between several behavioral categories and improvements in quality of life and treatment adherence.

Conclusions: The findings highlight the importance of self-narrative formulation among individuals with autism and suggest that certain communicative behaviors-particularly those involving identity reflection and recognition of treatment-related gains-were positively associated with therapeutic outcomes. The findings enhance our understanding of how individuals with autism engage in internet-based cognitive behavioral therapy and may serve as a valuable source of information for therapists when guiding expectations regarding client outcomes and identifying participants who may benefit from additional support.

Trial registration: ClinicalTrials.gov NCT03570372; https://clinicaltrials.gov/study/NCT03570372.

This study uses keyword filtering, a transformer-based algorithm, and inductive content coding to identify and characterize cannabis adverse experiences as discussed on the social media platform Reddit and reports a total of 1177 self-reported adverse experiences requiring medical attention.

Background: Improving sleep is critical for optimizing short-term and long-term health. Although in-person meditation training has been shown to impact sleep positively, there is a gap in our understanding of whether apps that teach self-guided meditation are also effective.

Objective: This study aims to test whether Headspace (Headspace, Inc) improves sleep quality, tiredness, sleep duration, and sleep efficiency.

Methods: Staff employees (N=135; mean age 38.1, SD 10.9; 75.0% female; 59.3% non-Hispanic White; 27.1% Hispanic) from a university in California's San Joaquin Valley participated in the study. Participants were randomized to complete 10 minutes of daily meditation via the Headspace app for 8 weeks or waitlist control. Sleep assessments were taken for 4 consecutive days at baseline, and then for 4-day bursts at 2, 5, and 8 weeks after randomization. Sleep quality and subjective sleep duration were assessed each morning with a sleep diary, tiredness was assessed throughout the day using ecological momentary assessment, and objective sleep duration and efficiency were measured using a Fitbit Charge 2.

Results: Both subjective and objective sleep outcomes improved. For subjective sleep outcomes, multilevel modeling revealed that those in the Headspace condition, compared to the control group, reported better sleep quality at sessions 2 (β=0.48, SE=0.12; P<.001), 5 (β=0.91, SE=0.13; P<.001), and 8 (β=0.69, SE=0.15; P<.001) compared to baseline, and a decrease in tiredness at session 5 (β=-0.58, SE=0.19; P=.001) compared to baseline, but not at sessions 2 or 8. For objective sleep outcomes, those in the Headspace condition compared to the control group had longer sleep durations at session 5 (β=23.96, SE=12.19; P=.04) compared to baseline, but not at sessions 2 or 8. There were no significant effects for sleep efficiency.

Conclusions: This study continues adding to the ever-developing field of mobile health apps by demonstrating that Headspace can positively impact sleep quality, tiredness, and duration.