JMIR mHealth and uHealth最新文献

{"title":"User Archetypes of a Well-Being-Promoting Mobile App Among Adults: Cross-Sectional Study and Cluster Analysis of Usage Patterns.","authors":"Hanna Rekola, Tommi Tolmunen, Elina Mattila, Juho Strömmer, Timo A Lakka, Helena Länsimies, Tomi Mäki-Opas","doi":"10.2196/68982","DOIUrl":"10.2196/68982","url":null,"abstract":"<p><strong>Background: </strong>A healthy lifestyle is associated with mental well-being, and digital lifestyle interventions can be effective in promoting a healthy lifestyle. However, they do not appear to work for all, and we have limited knowledge of how users' background characteristics affect their tendency to adopt well-being-promoting digital apps and actively use them.</p><p><strong>Objective: </strong>This study aimed to explore the association of the study participants' characteristics and current well-being with their likelihood of using a well-being-promoting mobile app.</p><p><strong>Methods: </strong>The BitHabit web app (Wellpro Impact Solutions Ltd) was available for a 2-month trial in spring 2023 after completing a short cross-sectional digital questionnaire with questions about well-being, life satisfaction, and lifestyle. Individuals aged 15 years or younger were excluded from the analysis. We used logistic regression to assess how individual characteristics were associated with the initiation of BitHabit app use. To assess user archetypes among those who initiated app use, and k-means clustering analysis and multinomial logistic regression to assess user archetypes among those who initiated app use.</p><p><strong>Results: </strong>A total of 1646 eligible individuals responded to the questionnaire, and 863 initiated app use. Lower odds of initiating app use were detected among males (odds ratio [OR] 0.66, 95% CI 0.51-0.85; P<.001), the unemployed (OR 0.68, 95% CI 0.48-0.97; P=.03), those with higher general life satisfaction (OR 0.94, 95% CI 0.89-1.00; P=.04), and those reporting fewer life challenges (OR 1.13, 95% CI 1.02-1.24; P=.02). We identified (1) thriving non-active users, (2) struggling non-active users, and (3) active users as archetypes based on app use activity, life satisfaction, and reported life challenges. Older participants had lower odds of being thriving nonactive (OR 0.96, 95% CI 0.94-0.99; P=.01) or struggling nonactive users (OR 0.93, 95% CI 0.90-0.96; P<.001) than active users. Retired participants had higher odds of being struggling nonactive than active users (OR 4.06, 95% CI 1.44-11.42; P=.01) and unemployed lower odds of being thriving nonactive than active users (OR 0.2, 95% CI 0.08-0.51; P<.001). Those who were physically more active had higher odds of being thriving nonactive than active users (OR 2.71, 95% CI 1.00-7.32; P=.05). Participants with higher alcohol consumption had higher odds of being struggling nonactive users than active users (OR 3.22, 95% CI 1.16-8.99; P=.03).</p><p><strong>Conclusions: </strong>While lower general life satisfaction and less favorable health behavior appeared to increase the likelihood of trying the app, those who eventually actively used the app were more satisfied with their lives at baseline. In addition, among nonactive users, there were recognizable user profiles of thriving and struggling nonactive users, which were associated with various individual charac","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"13 ","pages":"e68982"},"PeriodicalIF":6.2,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12360720/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144873254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adolescent Engagement With a Multicomponent mHealth Tool: Identifying Usage Patterns, Determinants, and Health Behavior Change in an Intervention Trial.","authors":"Carmen Peuters, Ann DeSmet, Laura Maenhout, Greet Cardon, Dries Debeer, Geert Crombez","doi":"10.2196/59041","DOIUrl":"10.2196/59041","url":null,"abstract":"<p><strong>Background: </strong>Research about the engagement of adolescents with mobile health (mHealth) interventions is scarce, while it is generally assumed that the engagement affects the intervention efficacy.</p><p><strong>Objective: </strong>Using an mHealth intervention that targets the general population of adolescents to promote healthy behaviors (physical activity, low sedentary time, adequate sleep, and taking breakfast) and mental health, we aimed to investigate (1) how adolescents engage with the intervention, (2) which engagement styles can be identified and how these differ according to personal characteristics, and (3) which style of engagement predicts behavior change. The intervention used, #LIFEGOALS, includes self-regulation techniques, a support chatbot, narrative videos, and gamification, brought together in an app coupled to an activity tracker.</p><p><strong>Methods: </strong>Logged usage data and self-reports of experience with #LIFEGOALS were collected from 159 adolescents (mean age 13.54, SD 0.95 years) over a 12-week intervention period and used to describe behavioral and experiential engagement with the intervention components over time. Baseline data on sociodemographic variables, mental health, and behavioral determinants were explored as determinants of engagement and were used to characterize engagement styles that were identified through exploratory cluster analysis on the frequency of usage of the components. Linear mixed-effects regression was used to analyze the effect of engagement style on health behavior change.</p><p><strong>Results: </strong>Average time in the app was 26 minutes (SD 26) over the 12-week period, with usage decreasing substantially after the first week. The use of self-regulation techniques and gamification was strongly interrelated (0.65 <r <0.70), whereas use of Fitbit showed weaker correlations with other component usage (0.15 <r <0.31). Exploratory analyses suggest that engagement was influenced by immigration background and by adolescents' attitudes, self-efficacy, and intentions toward healthy living. Younger participants tended to use the Fitbit more frequently. Cluster analysis identified 4 engagement styles: narrative usage (n=19), app usage (n=36), Fitbit usage (n=32), and no usage (n=72), which were associated with differences in age, peer support, and mental health. Engagement style did not affect change in health behavior outcomes from preintervention to postintervention.</p><p><strong>Conclusions: </strong>Different engagement styles were identified based on the frequency and type of components used. Findings support the relevance of tailoring mHealth to individual, interpersonal, and contextual characteristics. The overall low engagement with the intervention may have limited the detection of differences in health effects between engagement styles.</p>","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"13 ","pages":"e59041"},"PeriodicalIF":6.2,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12360726/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144873252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Outcomes of an App-Based Intervention to Target Naming Among Individuals With Poststroke Aphasia: Virtual Randomized Controlled Trial.","authors":"Esther S Kim, Laura Laird, Carlee Wilson, Steven Stewart, Philip Mildner, Sebastian Möller, Raimund Schatz, Robert P Spang, Jan-Niklas Voigt-Antons, Elizabeth Rochon","doi":"10.2196/67711","DOIUrl":"10.2196/67711","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;People with aphasia present with language and communication deficits, most notably in lexical retrieval (naming). Although positive outcomes in naming have been observed following speech-language treatment, many individuals with aphasia continue to face impairments after the acute phase of rehabilitation. Mobile app-based therapies are increasingly being used by speech-language pathologists in the rehabilitation of people with aphasia as an adjunct to or in lieu of traditional in-person therapy approaches. These apps can increase the intensity of treatment and have been shown to result in meaningful outcomes across several domains.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;VoiceAdapt is a mobile therapy app addressing naming impairments, designed within a user-centered design framework. The VoiceAdapt app uses two evidence-based lexical retrieval treatments to engage people with aphasia to improve their naming abilities through interaction with the app. The purpose of this study was to conduct a randomized controlled trial to examine the preliminary clinical efficacy of training with VoiceAdapt on the language and communication outcomes of people with aphasia.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A two-arm, waitlist-controlled, crossover group randomized controlled trial was conducted at two sites within Canada. During the intervention phase, participants completed 5 weeks of independent training with the app, which involved naming practice using Semantic Features Analysis and Phonological Components Analysis. The primary outcome measure was naming performance (Boston Naming Test); secondary outcomes included measures of overall language and naming (Western Aphasia Battery-Revised), communication (Communication Effectiveness Index), and quality of life (Stroke and Aphasia Quality of Life Scale-39).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 37 people with aphasia in the chronic stages (average 4.6 y postonset of aphasia) participated in this study. Participants used the app for an average of 20 hours over the 5-week intervention phase. Training with VoiceAdapt resulted in an increase of 1.6 points on the Boston Naming Test (Cohen d=0.3). Evidence for improved naming was also observed on trained items, as well as subtests of naming or word-finding on the WAB-R. Training with the app also resulted in a significant increase in participants' perceptions of their communication quality of life (increase of 0.1 points; Cohen d=0.3), but no other measures (WAB-R Aphasia Quotient, Communicative Effectiveness Index) were significant.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Individuals with aphasia who used the VoiceAdapt app for 5 weeks to target naming skills demonstrated measurable gains in naming and communication-based quality of life. Notably, these changes were observed in a remotely delivered program, in participants who were in the chronic stages of aphasia. These findings inform the profession on the use of app-based home therapy pr","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"13 ","pages":"e67711"},"PeriodicalIF":6.2,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12440831/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145075121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automatic Image Recognition Meal Reporting Among Young Adults: Randomized Controlled Trial.","authors":"Prasan Kumar Sahoo, Sherry Yueh-Hsia Chiu, Yu-Sheng Lin, Chien-Hung Chen, Denisa Irianti, Hsin-Yun Chen, Mekhla Sarkar, Ying-Chieh Liu","doi":"10.2196/60070","DOIUrl":"10.2196/60070","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Advances in artificial intelligence technology have raised new possibilities for the effective evaluation of daily dietary intake, but more empirical study is needed for the use of such technologies under realistic meal scenarios. This study developed an automated food recognition technology, which was then integrated into its previous design to improve usability for meal reporting. The newly developed app allowed for the automatic detection and recognition of multiple dishes within a single real-time food image as input. App performance was tested using young adults in authentic dining conditions.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;A 2-group comparative study was conducted to assess app performance using metrics including accuracy, efficiency, and user perception. The experimental group, named the automatic image-based reporting (AIR) group, was compared against a control group using the previous version, named the voice input reporting (VIR) group. Each application is primarily designed to facilitate a distinct method of food intake reporting. AIR users capture and upload images of their selected dishes, supplemented with voice commands where appropriate. VIR users supplement the uploaded image with verbal inputs for food names and attributes.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;The 2 mobile apps were subjected to a head-to-head parallel randomized evaluation. A cohort of 42 young adults aged 20-25 years (9 male and 33 female participants) was recruited from a university in Taiwan and randomly assigned to 2 groups, that is, AIR (n=22) and VIR (n=20). Both groups were assessed using the same menu of 17 dishes. Each meal was designed to represent a typical lunch or dinner setting, with 1 staple, 1 main course, and 3 side dishes. All participants used the app on the same type of smartphone, with the interfaces of both using uniform user interactions, icons, and layouts. Analysis of the gathered data focused on assessing reporting accuracy, time efficiency, and user perception.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;For the AIR group, 86% (189/220) of dishes were correctly identified, whereas 68% (136/200) of dishes were accurately reported. The AIR group exhibited a significantly higher degree of identification accuracy compared to the VIR group (P&lt;.001). The AIR group also required significantly less time to complete food reporting (P&lt;.001). System usability scale scores showed both apps were perceived as having high usability and learnability (P=.20).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The AIR group outperformed the VIR group concerning accuracy and time efficiency for overall dish reporting within the meal testing scenario. While further technological enhancement may be required, artificial intelligence vision technology integration into existing mobile apps holds promise. Our results provide evidence-based contributions to the integration of automatic image recognition technology into existing apps in terms of user interac","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"13 ","pages":"e60070"},"PeriodicalIF":6.2,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12352700/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144855212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the Utility of Digital Voice Assistants for Primary Care Patients, Including Those With Physical and Visual Disabilities: Cross-Sectional Study.","authors":"Maya Rajan, Allison Furgal, Reema Kadri, Omar Arman, Kate Panzer, Donna Wicker, Michael M McKee, Melissa Plegue, Alexandria Degner, Lorraine R Buis","doi":"10.2196/66185","DOIUrl":"10.2196/66185","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Today, most smartphones provide a digital voice assistant (DVA) for their user, and it is estimated that about 91% of adults report owning and operating a smartphone. A DVA is an automated system preinstalled on technological devices, such as smartphones, computers, tablets, and speakers, which serves to aid users in performing tasks like answering questions, managing smart devices at home, playing music, managing schedules, sending messages, and more. Research with DVA is emerging, and its applicability to health and health care needs to be elucidated.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;The objective of this study was to describe the use of DVAs among primary care patients, as well as purposely sampled clinics including patients with visual and physical disabilities.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A convenience sample of adult participants was recruited to complete a needs assessment survey to ascertain the interest and possible utility of DVAs to promote and enhance health from among three populations at an academic medical center: (1) general primary care patients recruited from a primary care clinic, (2) patients with visual disabilities recruited from a low vision clinic, and (3) patients with physical disabilities recruited from a physical medicine and rehabilitation clinic. The survey used in this study was a 46-item investigator-developed instrument administered to participants assessing knowledge, use, and perceptions of DVAs, participant interest to participate in related future studies, and demographics.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The results of the survey showed that the majority of participants have used a DVA before (69.7%, 152/218) and were or might be willing to use them in the future (84.0%, 178/212). Participants reported moderate to high concern about the privacy (47.8%, 97/203), security (54.5%, 110/202), and confidentiality (51.7%, 105/203) of DVAs. A greater proportion of those with visual disabilities reported having never used DVA than those without visual disabilities (39.0% vs 24.6%, P=.03). There was no significant difference in reliance on DVAs for participants with and those without physical disabilities (45.0% vs 34.9%, P=.31), indicating that they do not require it for everyday needs.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;DVA use remains low among the surveyed participants with physical and visual disabilities. For those with visual disabilities, DVA use was seen to be advantageous in everyday life for tasks such as answering questions and seeking information, but not for those with physical disabilities. However, further research should be conducted that focuses on the use of DVAs by accessing data that represent an individual's DVA use without being biased by knowledge of a research study. In addition, research is needed on DVA use that includes diverse samples of participants with physical and visual disabilities, which address the barriers to using DVAs for these adult populati","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"13 ","pages":"e66185"},"PeriodicalIF":6.2,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12352795/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144855213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors Influencing Engagement in a Digital Substance Use Prevention Program: Qualitative Study Using the Capability, Opportunity, Motivation Model and Theoretical Domains Framework.","authors":"Nikolai Kiselev, Rebecca Schaffner, Zsofia Csepregi, Andreas Wenger, Raquel Paz Castro, Severin Haug","doi":"10.2196/64861","DOIUrl":"10.2196/64861","url":null,"abstract":"<p><strong>Background: </strong>Digital interventions are promising for the prevention of substance use in young people. However, engagement with these interventions is often insufficient, and their full potential remains unrealized. Given the established link between engagement in digital interventions and their effectiveness, understanding user factors that influence involvement in eHealth and mobile health (mHealth) interventions is essential.</p><p><strong>Objective: </strong>This study aimed to identify factors influencing user engagement in a mobile phone-based life skills training program for substance use prevention among adolescents and to collect suggestions for program optimization.</p><p><strong>Methods: </strong>A qualitative study was conducted with 171 participants of the mHealth prevention SmartCoach (Pathmate Technologies) program. The program provided individualized text messages to foster life skills for 4 months and proved to be effective in preventing the onset of cigarette and cannabis use. Semistructured phone interviews were conducted with program participants to explore factors associated with program engagement and to gather suggestions for program optimization. Interviews were recorded, transcribed, and analyzed using thematic analysis with both inductive and deductive coding. The capability, opportunity, and motivation model of behavior change (COM-B) model and Theoretical Domains Framework (TDF) were used to assess behavioral influences.</p><p><strong>Results: </strong>Key factors positively influencing program engagement included the timing of text messages, social influences and support, engaging and helpful content, and rewards (points and prizes). Conversely, barriers to engagement were identified as forgetfulness, short response time limits, limited time resources, lack of interest, concerns related to personal disclosure, and difficulty identifying with the challenge task type (posting). Suggestions for optimization included implementing reminders, providing better guidance for using tips, allowing personalization of message timing and content, extending time limits for tasks, and reducing the concerns related to personal disclosure.</p><p><strong>Conclusions: </strong>The study confirms the critical role of timing, content relevance, and social support in enhancing engagement with digital interventions. Specific recommendations for optimizing the SmartCoach program were derived, highlighting the importance of reminders, personalization, and addressing concerns related to personal disclosure.</p>","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"13 ","pages":"e64861"},"PeriodicalIF":6.2,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12352799/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144855214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Authors' Reply: Clarifying Blood Indices in Patients With Ovarian Cancer.","authors":"Jiahua Zhang","doi":"10.2196/74931","DOIUrl":"10.2196/74931","url":null,"abstract":"","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"13 ","pages":"e74931"},"PeriodicalIF":6.2,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12349731/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144846539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clarifying Blood Indices in Patients With Ovarian Cancer.","authors":"Chengwei Lian, Yu Fan, Jinke Li","doi":"10.2196/70895","DOIUrl":"10.2196/70895","url":null,"abstract":"","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"13 ","pages":"e70895"},"PeriodicalIF":6.2,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12349733/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144846540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of ActiGraph CentrePoint Insight Watch Placement on Dominant and Nondominant Wrists in Young Adults in Free-Living Conditions: Observational Validation Study.","authors":"Daehyoung Lee, Haley Voermans-Dean, Jung Eun Lee, Jong Cheol Shin, Gregory Dominick","doi":"10.2196/63033","DOIUrl":"10.2196/63033","url":null,"abstract":"<p><strong>Background: </strong>With the continuous evolution of technology, wearable accelerometers have become one of the most popular means of measuring daily physical activity (PA) levels. Despite the conventional use of the nondominant wrist as a device placement in numerous PA studies, the impact of wrist-worn accelerometer placement on PA data outcomes remains uncertain.</p><p><strong>Objective: </strong>This study aimed to examine the degree of agreement between accelerometry data collected from CentrePoint Insight Watches (CPIWs; ActiGraph) worn on the dominant and nondominant wrists of young adults in free-living conditions.</p><p><strong>Methods: </strong>Twenty-nine participants (mean age 20.2, SD 1.6 years; 23 females) simultaneously wore an ActiGraph CPIW on both dominant and nondominant wrists for 7 consecutive days during waking hours. A sampling frequency of 32 Hz and Montoye 2020 cut-points were used to categorize activity intensity based on counts per minute. Data validity criteria included (1) ≥600 minutes per day of monitor wear time for both wrists, (2) a daily wear time difference of <1% of the average wear time between the dominant and nondominant wrists, and (3) a minimum of 3 valid days of monitor wear for both wrists. Bland-Altman plots and intraclass correlation coefficient (ICC) analyses were performed to compare the accelerometry data between the two device placements.</p><p><strong>Results: </strong>Average daily monitor wear time was 789.6 (SD 86.1) minutes per day for the dominant wrist and 793.0 (SD 91.8) minutes per day for the nondominant wrist. All accelerometer variables, including sedentary time (ST), light PA, moderate-to-vigorous PA (MVPA), steps, triaxial counts, and vector magnitude (VM), showed good-to-excellent levels of reliability between the two measurements (ICC >0.88 for all; P<.001). Bland-Altman analysis calculated mean bias and SD between the two device placements as follows: ST (-18.8, SD 27.6 min/d), light PA (2.7, SD 15.9 min/d), MVPA (12.7, SD 26.7 min/d), steps (218.1, SD 476.6 counts/d), x-axis (99.4, SD 188.8 counts/min), y-axis (73.9, SD 147.0 counts/min), z-axis (107.6, SD 183.5 counts/min), and VM (161.2, SD 273.4 counts/min). Bland-Altman plots revealed that the upper and lower limits of agreement across most variables were considerably wide.</p><p><strong>Conclusions: </strong>Our findings partially align with previous research, demonstrating higher MVPA and step counts on the dominant wrist, while the nondominant wrist produced a higher level of ST. Despite the acceptable level of reliability between the two placements based on ICC analyses, the dominant wrist tended to produce greater outcomes as the intensity of PA increased, highlighting the need for careful consideration when determining the wear location of CPIWs and interpreting data outcomes.</p>","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"13 ","pages":"e63033"},"PeriodicalIF":6.2,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12338961/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144821480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of Information Length and Implementation Intentions on Adherence to Weight Management Strategies: Experimental Study.","authors":"Khaleda Ahmadyar, Joanna Szypula, Angeliki Bogosian, Katy Tapper","doi":"10.2196/65260","DOIUrl":"10.2196/65260","url":null,"abstract":"<p><strong>Background: </strong>Adherence to weight management strategies may be undermined where lengthy strategy explanations limit engagement and understanding, weakening intervention efficacy. By contrast, implementation intentions have been shown to promote adherence across various health behaviors.</p><p><strong>Objective: </strong>This study aimed to investigate the impact of explanation length and implementation intentions on adherence to brief weight management strategies.</p><p><strong>Methods: </strong>Participants (N=200) with a BMI above 25 and an interest in losing weight were recruited from a commercial digital weight management service provider. Participants received information about 1 of 4 weight management strategies on a smartphone app in either a brief or detailed format and were asked to plan their use of the strategy with implementation intentions or were given tips on strategy use. Participants received daily prompts over a 2-week period to report whether they used their assigned strategy. Proposed moderators (need for cognition and planning skills) were measured at baseline.</p><p><strong>Results: </strong>Strategy adherence was greater with brief information (mean 74%, SD 23%) compared with detailed information (mean 69%, SD 23%); however, this small effect size (Cohen d=0.24) was not statistically significant (P=.13). There was no moderation by need for cognition (P=.25). Adherence did not differ significantly between implementation intentions (mean 71%, SD 27%) and tips (mean 72%, SD 21%; P=.73); however, there was moderation by planning skills (P=.04). As predicted, adherence was greater with implementation intentions compared with tips among those with poorer planning skills.</p><p><strong>Conclusions: </strong>Shorter explanation length and implementation intentions (in poorer planners) may enhance adherence to brief weight management strategies, and further investigation is required to confirm these effects.</p>","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"13 ","pages":"e65260"},"PeriodicalIF":6.2,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12334108/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144804127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}