1
|
Fahey MC, Carpenter MJ, O'Neal R, Pebley K, Schick MR, Ware E, Toll BA, Dahne J. Expectations and Preferences for Digital Cessation Treatment: Multimethods Study Among Older Adults Who Smoke Cigarettes. J Med Internet Res 2024; 26:e52919. [PMID: 39196628 PMCID: PMC11391153 DOI: 10.2196/52919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 04/05/2024] [Accepted: 06/25/2024] [Indexed: 08/29/2024] Open
Abstract
BACKGROUND To address enduring age-related tobacco disparities, it is critical to promote cessation treatment among older adults (aged 65+ years). Digital health platforms offer opportunities for wide dissemination of evidence-based behavioral cessation support. However, existing digital cessation treatments are not tailored to unique aging-related needs and preferences, resulting in low uptake. Detailed information is needed about how to best adapt these treatments for this age group. OBJECTIVE We aimed to collect detailed, hypothesis-generating information about expectations and preferences for cessation digital treatment among older adults who smoke cigarettes. METHODS Semistructured interviews were conducted with adults aged 65+ years currently smoking or who had quit within the past month. Interviews included open-ended questions regarding prior experiences with digital health platforms and expectations and preferences for cessation treatment via various modalities (app-delivered, texting-based, or videoconferencing counseling). Interviews also elicited questions regarding digital modalities that integrated social components (app-delivered social forums and group videoconferencing counseling). Using an iterative, team-based approach, the thematic analysis identified meaningful themes. Interviews were supplemented with quantitative measures assessing sociodemographics, digital literacy, and physical health symptoms. RESULTS Participants (12/20, 60% men; 15/20, 75% White; 4/20, 20% Black or African American; 1/20, 5% Asian) were currently smoking (17/20, 85%) or had recently quit (3/20, 15%). Thematic analysis identified 3 meaningful themes across all digital modalities: convenience, accessibility, and personalization. Expected benefits of digital platforms included convenient treatment access, without reliance on transportation. Participants preferred treatments to be personalized and deliver content or strategies beyond standard education. Most (17/20, 85%) were unfamiliar with cessation apps but found them appealing given the potential for offering a novel quitting strategy. App ease of use (eg, easy navigation) was preferred. Half (10/20, 50%) would try a texting-based intervention, with many preferring texting with a counselor rather than automated messaging. Most (17/20, 85%) would use videoconferencing and expected this modality to deliver better quality counseling than via telephone. Expected videoconferencing challenges included looking presentable onscreen, technological difficulties, and privacy or security. Videoconferencing was regarded as the most personalized digital treatment, yet benefits unique to app-delivered and texting-based treatments included anonymity and access to treatment 24/7. Participants expected integrating social components into digital treatment to be useful for quit success and social connection, yet were concerned about possible interpersonal challenges. CONCLUSIONS Because a long history of quit attempts and familiarity with standard quitting advice is common among older adults who smoke cigarettes, digital platforms might offer appealing and novel strategies for cessation that are accessible and convenient. Overall, this population was open to trying digital cessation treatments and would prefer that these platforms prioritize ease of use and personalized content. These findings challenge the bias that older adults are uninterested or unwilling to engage with digital treatments for behavioral health.
Collapse
Affiliation(s)
- Margaret C Fahey
- Department of Psychiatry & Behavioral Sciences, Medical University of South Carolina, Charleston, SC, United States
| | - Mathew J Carpenter
- Department of Psychiatry & Behavioral Sciences, Medical University of South Carolina, Charleston, SC, United States
- Hollings Cancer Center, Charleston, SC, United States
| | - Riley O'Neal
- School of Arts & Sciences, University of South Carolina, Columbia, SC, United States
| | - Kinsey Pebley
- Hollings Cancer Center, Charleston, SC, United States
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, United States
| | - Melissa R Schick
- School of Medicine, Yale University, New Haven, CT, United States
| | - Emily Ware
- Hollings Cancer Center, Charleston, SC, United States
- Department of Pharmacy Services, Medical University of South Carolina, Charleston, SC, United States
| | - Benjamin A Toll
- Department of Psychiatry & Behavioral Sciences, Medical University of South Carolina, Charleston, SC, United States
- Hollings Cancer Center, Charleston, SC, United States
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, United States
| | - Jennifer Dahne
- Department of Psychiatry & Behavioral Sciences, Medical University of South Carolina, Charleston, SC, United States
- Hollings Cancer Center, Charleston, SC, United States
| |
Collapse
|
2
|
Rivera-Romero O, Gabarron E, Ropero J, Denecke K. Designing personalised mHealth solutions: An overview. J Biomed Inform 2023; 146:104500. [PMID: 37722446 DOI: 10.1016/j.jbi.2023.104500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 09/14/2023] [Accepted: 09/16/2023] [Indexed: 09/20/2023]
Abstract
INTRODUCTION Mobile health, or mHealth, is based on mobile information and communication technologies and provides solutions for empowering individuals to participate in healthcare. Personalisation techniques have been used to increase user engagement and adherence to interventions delivered as mHealth solutions. This study aims to explore the current state of personalisation in mHealth, including its current trends and implementation. MATERIALS AND METHODS We conducted a review following PRISMA guidelines. Four databases (PubMed, ACM Digital Library, IEEE Xplore, and APA PsycInfo) were searched for studies on mHealth solutions that integrate personalisation. The retrieved papers were assessed for eligibility and useful information regarding integrated personalisation techniques. RESULTS Out of the 1,139 retrieved studies, 62 were included in the narrative synthesis. Research interest in the personalisation of mHealth solutions has increased since 2020. mHealth solutions were mainly applied to endocrine, nutritional, and metabolic diseases; mental, behavioural, or neurodevelopmental diseases; or the promotion of healthy lifestyle behaviours. Its main purposes are to support disease self-management and promote healthy lifestyle behaviours. Mobile applications are the most prevalent technological solution. Although several design models, such as user-centred and patient-centred designs, were used, no specific frameworks or models for personalisation were followed. These solutions rely on behaviour change theories, use gamification or motivational messages, and personalise the content rather than functionality. A broad range of data is used for personalisation purposes. There is a lack of studies assessing the efficacy of these solutions; therefore, further evidence is needed. DISCUSSION Personalisation in mHealth has not been well researched. Although several techniques have been integrated, the effects of using a combination of personalisation techniques remain unclear. Although personalisation is considered a persuasive strategy, many mHealth solutions do not employ it. CONCLUSIONS Open research questions concern guidelines for successful personalisation techniques in mHealth, design frameworks, and comprehensive studies on the effects and interactions among multiple personalisation techniques.
Collapse
Affiliation(s)
- Octavio Rivera-Romero
- Electronic Technology Department, Universidad de Sevilla, Spain; Instituto de Investigación en Informática de la Universidad de Sevilla, Spain.
| | - Elia Gabarron
- Norwegian Centre for E-health Research, University Hospital of North Norway, Tromsø, Norway; Department of Education, ICT and Learning, Østfold University College, Halden, Norway
| | - Jorge Ropero
- Electronic Technology Department, Universidad de Sevilla, Spain
| | | |
Collapse
|
3
|
Martinez Agulleiro L, Patil B, Firth J, Sawyer C, Amann BL, Fonseca F, Torrens M, Perez V, Castellanos FX, Kane JM, Guinart D. A systematic review of digital interventions for smoking cessation in patients with serious mental illness. Psychol Med 2023; 53:4856-4868. [PMID: 37161690 PMCID: PMC10476065 DOI: 10.1017/s003329172300123x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 04/06/2023] [Accepted: 04/12/2023] [Indexed: 05/11/2023]
Abstract
Tobacco smoking is highly prevalent among patients with serious mental illness (SMI), with known deleterious consequences. Smoking cessation is therefore a prioritary public health challenge in SMI. In recent years, several smoking cessation digital interventions have been developed for non-clinical populations. However, their impact in patients with SMI remains uncertain. We conducted a systematic review to describe and evaluate effectiveness, acceptability, adherence, usability and safety of digital interventions for smoking cessation in patients with SMI. PubMed/MEDLINE, EMBASE, CINAHL, Web of Science, PsychINFO and the Cochrane Tobacco Addiction Group Specialized Register were searched. Studies matching inclusion criteria were included and their information systematically extracted by independent investigators. Thirteen articles were included, which reported data on nine different digital interventions. Intervention theoretical approaches ranged from mobile contingency management to mindfulness. Outcome measures varied widely between studies. The highest abstinence rates were found for mSMART MIND (7-day point-prevalent abstinence: 16-40%). Let's Talk About Quitting Smoking reported greater acceptability ratings, although this was not evaluated with standardized measures. Regarding usability, Learn to Quit showed the highest System Usability Scale scores [mean (s.d.) 85.2 (15.5)]. Adverse events were rare and not systematically reported. Overall, the quality of the studies was fair to good. Digitally delivered health interventions for smoking cessation show promise for improving outcomes for patients with SMI, but lack of availability remains a concern. Larger trials with harmonized assessment measures are needed to generate more definitive evidence and specific recommendations.
Collapse
Affiliation(s)
- Luis Martinez Agulleiro
- Department of Child and Adolescent Psychiatry, New York University Grossman School of Medicine, New York, NY, USA
| | - Bhagyashree Patil
- Department of Psychiatry, Maimonides Medical Center, Brooklyn, NY, USA
| | - Joseph Firth
- Division of Psychology and Mental Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK, M13 9 PL
| | - Chelsea Sawyer
- Division of Psychology and Mental Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK, M13 9 PL
| | - Benedikt L. Amann
- Institute of Neuropsychiatry and Addictions (INAD), Parc de Salut Mar, Barcelona, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto Carlos III, Madrid, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Francina Fonseca
- Institute of Neuropsychiatry and Addictions (INAD), Parc de Salut Mar, Barcelona, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Marta Torrens
- Institute of Neuropsychiatry and Addictions (INAD), Parc de Salut Mar, Barcelona, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Universitat Autònoma de Barcelona, Bellaterra, Spain
- Universitat de Vic i Central de Catalunya, Vic, Spain
| | - Victor Perez
- Institute of Neuropsychiatry and Addictions (INAD), Parc de Salut Mar, Barcelona, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto Carlos III, Madrid, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Francisco Xavier Castellanos
- Department of Child and Adolescent Psychiatry, New York University Grossman School of Medicine, New York, NY, USA
- Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - John M. Kane
- Department of Psychiatry Research, The Zucker Hillside Hospital, Glen Oaks, NY, USA
- Institute of Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Manhasset, NY, USA
| | - Daniel Guinart
- Institute of Neuropsychiatry and Addictions (INAD), Parc de Salut Mar, Barcelona, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto Carlos III, Madrid, Spain
- Department of Psychiatry Research, The Zucker Hillside Hospital, Glen Oaks, NY, USA
- Institute of Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Manhasset, NY, USA
| |
Collapse
|
4
|
Bold KW, Garrison KA, DeLucia A, Horvath M, Nguyen M, Camacho E, Torous J. Smartphone Apps for Smoking Cessation: Systematic Framework for App Review and Analysis. J Med Internet Res 2023; 25:e45183. [PMID: 37440305 PMCID: PMC10375280 DOI: 10.2196/45183] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 06/06/2023] [Accepted: 06/12/2023] [Indexed: 07/14/2023] Open
Abstract
BACKGROUND Cigarette smoking is a leading cause of preventable death, and identifying novel treatment approaches to promote smoking cessation is critical for improving public health. With the rise of digital health and mobile apps, these tools offer potential opportunities to address smoking cessation, yet the functionality of these apps and whether they offer scientifically based support for smoking cessation are unknown. OBJECTIVE The goal of this research was to use the American Psychiatric Association app evaluation model to evaluate the top-returned apps from Android and Apple app store platforms related to smoking cessation and investigate the common app features available for end users. METHODS We conducted a search of both Android and iOS app stores in July 2021 for apps related to the keywords "smoking," "tobacco," "smoke," and "cigarette" to evaluate apps for smoking cessation. Apps were screened for relevance, and trained raters identified and analyzed features, including accessibility (ie, cost), privacy, clinical foundation, and features of the apps, using a systematic framework of 105 objective questions from the American Psychiatric Association app evaluation model. All app rating data were deposited in mindapps, a publicly accessible database that is continuously updated every 6 months given the dynamic nature of apps available in the marketplace. We characterized apps available in July 2021 and November 2022. RESULTS We initially identified 389 apps, excluded 161 due to irrelevance and nonfunctioning, and rated 228, including 152 available for Android platforms and 120 available for iOS platforms. Some of the top-returned apps (71/228, 31%) in 2021 were no longer functioning in 2022. Our analysis of rated apps revealed limitations in accessibility and features. While most apps (179/228, 78%) were free to download, over half had costs associated with in-app purchases or full use. Less than 65% (149/228) had a privacy policy addressing the data collected in the app. In terms of intervention features, more than 56% (128/228) of apps allowed the user to set and check in on goals, and more than 46% (106/228) of them provided psychoeducation, although few apps provided evidence-based support for smoking cessation, such as peer support or skill training, including mindfulness and deep breathing, and even fewer provided evidence-based interventions, such as acceptance and commitment therapy or cognitive behavioral therapy. Only 12 apps in 2021 and 11 in 2022 had published studies supporting the feasibility or efficacy for smoking cessation. CONCLUSIONS Numerous smoking cessation apps were identified, but analysis revealed limitations, including high rates of irrelevant and nonfunctioning apps, high rates of turnover, and few apps providing evidence-based support for smoking cessation. Thus, it may be challenging for consumers to identify relevant, evidence-based apps to support smoking cessation in the app store, and a comprehensive evaluation system of mental health apps is critically important.
Collapse
Affiliation(s)
- Krysten W Bold
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States
| | - Kathleen A Garrison
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States
| | - Angela DeLucia
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States
| | - Mark Horvath
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States
| | - Milton Nguyen
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States
| | - Erica Camacho
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - John Torous
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, United States
| |
Collapse
|
5
|
Xie JH, Qiu YF, Zhu L, Hu Y, Chang X, Wang W, Zhang LM, Chen OY, Zhong X, Yu X, Zou Y, Zhong R. Evaluation of the smoking cessation effects of QuitAction, a smartphone WeChat platform. Tob Induc Dis 2023; 21:49. [PMID: 37057059 PMCID: PMC10088363 DOI: 10.18332/tid/161257] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 02/06/2023] [Accepted: 02/14/2023] [Indexed: 04/15/2023] Open
Abstract
INTRODUCTION Many smokers in China desire to quit, though the success rate among adults is low. This study evaluated the effects of QuitAction, a WeChat smoking cessation platform, summarized the intervention experience of the smoking cessation platform, identified aspects of the platform that necessitated improvement, and provided references for further optimization of the smoking cessation platform. METHODS This single-arm study was conducted in Hunan, China, from September 2020 to October 2021. Regular smokers, who were aged ≥15 years and willing to quit smoking using QuitAction, were recruited. An in-application questionnaire evaluated participants' baseline smoking status and intention to quit smoking. The QuitAction program included questionnaires regarding the participants' ongoing smoking cessation status at 24 hours, one week, one month and three months after quitting. The smoking cessation procedure was discontinued if the participant had no intention of continuing. The smoking cessation rate, influencing success factors, frequency of use satisfaction, and helpfulness of QuitAction were recorded. RESULTS A total of 303 participants registered and logged into the QuitAction program, including 59 with incomplete information and 64 with no intention of quitting. The study finally included 180 participants. The smoking cessation rate was 33.9% at 24 hours, 27.2% at one week, 26.1% at one month, and 25.0% at three months. QuitAction was reported as helpful by 94.9% of participants and 95.7% were satisfied with the program. Participants with a quitting difficulty score of 80-100 were less likely to quit smoking than participants with a difficulty score of 0-60 (OR=0.28; 95% CI: 0.10-0.78; p=0.015). Participants using the platform ≥5 times were more likely to quit smoking than those who used the platform <5 times (OR=3.59; 95% CI: 1.51-8.52; p=0.004). CONCLUSIONS The QuitAction platform provides smoking cessation services that can improve smokers' success rate and improve user experience satisfaction.
Collapse
Affiliation(s)
- Jianghua H. Xie
- Hunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha City, China
- School of Nursing, Hunan University of Chinese Medicine, China
- Department of Otorhinolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University, China
| | - Yanfang F. Qiu
- Hunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha City, China
| | - Lei Zhu
- Hunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha City, China
- School of Nursing, Hunan University of Chinese Medicine, China
| | - Yina Hu
- School of Nursing and Health Management, Wuhan Donghu University, Wuhan, China
| | - Xiaochang Chang
- Hunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha City, China
| | - Wei Wang
- Hunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha City, China
| | - Lemeng M. Zhang
- Hunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha City, China
| | - Ouying Y. Chen
- School of Nursing, Hunan University of Chinese Medicine, China
| | - Xianmin Zhong
- Hunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha City, China
| | - Xinhua Yu
- Hunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha City, China
| | - Yanhui Zou
- Hunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha City, China
| | - Rui Zhong
- Hunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha City, China
| |
Collapse
|
6
|
The current evidence for substance use disorder apps. Curr Opin Psychiatry 2022; 35:237-245. [PMID: 35674724 DOI: 10.1097/yco.0000000000000800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
PURPOSE OF REVIEW New mHealth (smartphone) apps for substance use disorders (SUD) are emerging at an accelerated rate, with consumer choice typically guided by app-store user ratings rather than their effectiveness. The expansive reach, low-cost and accessibility of mHealth apps have driven their popularity and appeal as alternatives to traditional treatment; as such, rigorously establishing their effectiveness is of paramount importance. RECENT FINDINGS Several systematic reviews conclude that the evidence-base for mHealth SUD apps is weak, inconclusive and hampered by substantial heterogeneity in study designs. However, there have been a number of interesting and novel developments in this area in recent years, which have not been synthesised to date. SUMMARY Most mHealth apps deliver either multiple-component behaviour change techniques, discrete psychological interventions or cognitive training interventions, or are designed to act as adjuncts to facilitate the delivery of clinical or continuing care. There are promising signals of their feasibility, acceptability and preliminary effectiveness in numerous open-label pilot studies of mHealth apps targeting alcohol and smoking. However, only a handful of sufficiently-powered, well-designed randomised controlled trials have been conducted to date with mixed findings. Furthermore, there has been limited recent attention on mHealth apps aiming to improve outcomes for individuals using other drugs.
Collapse
|
7
|
Hijab MHF, Al-Thani D, Banire B. A Multimodal Messaging App (MAAN) for Adults With Autism Spectrum Disorder: Mixed Methods Evaluation Study. JMIR Form Res 2021; 5:e33123. [PMID: 34878998 PMCID: PMC8693202 DOI: 10.2196/33123] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 11/08/2021] [Accepted: 11/17/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Individuals with autism spectrum disorder (ASD) often exhibit difficulties in social and communication skills. For more than 30 years, specialists, parents, and caregivers have used techniques, such as applied behavioral analysis, augmentative and alternative communication, and the picture exchange communication system to support the social and communication skills of people with ASD. Even though there are many techniques devised to enhance communication, these techniques are not considered in existing social media apps for people with ASD. OBJECTIVE This study aimed to investigate the effect of adding accessibility features, such as text-to-speech (TTS), speech-to-text (STT), and communication symbols (CS), to a messaging app (MAAN). We hypothesized that these accessibility features can enhance the social and communication skills of adults with ASD. We also hypothesized that usage of this app can reduce social loneliness in adults with ASD. METHODS Semistructured interviews were conducted with 5 experts working in fields related to ASD to help design the app. Seven adults with ASD participated in the study for a period of 10 to 16 weeks. Data logs of participants' interactions with the app were collected. Additionally, 6 participants' parents and 1 caregiver were asked to complete a short version of the Social and Emotional Loneliness Scale for Adults (SELSA-S) questionnaire to compare pre-post study results. The Mobile Application Rating Scale: user version questionnaire was also used to evaluate the app's usability. Following the study, interviews were conducted with participants to discuss their experiences with the app. RESULTS The SELSA-S questionnaire results showed no change in the family subscale; however, the social loneliness subscale showed a difference between prestudy and poststudy. The Wilcoxon signed-rank test indicated that poststudy SELSA-S results were statistically significantly higher than prestudy results (z=-2.047; P=.04). Point-biserial correlation indicated that the SELSA-S rate of change was strongly related to usage of the TTS feature (r=0.708; P=.04) and CS feature (r=-0.917; P=.002), and moderately related to usage of the STT feature (r=0.428; P=.17). Lastly, we adopted grounded theory to analyze the interview data, and the following 5 categories emerged: app support, feature relevance, user interface design, overall feedback, and recommendations. CONCLUSIONS This study discusses the potential for improving the communication skills of adults with ASD through special features in mobile messaging apps. The developed app aims to support the inclusion and independent life of adults with ASD. The study results showed the importance of using TTS, STT, and CS features to enhance social and communication skills, as well as reduce social loneliness in adults with ASD.
Collapse
Affiliation(s)
- Mohamad Hassan Fadi Hijab
- Division of Information and Computer Technology, College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar
| | - Dena Al-Thani
- Division of Information and Computer Technology, College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar
| | - Bilikis Banire
- Division of Information and Computer Technology, College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar
| |
Collapse
|
8
|
Martin-Payo R, Carrasco-Santos S, Cuesta M, Stoyan S, Gonzalez-Mendez X, Fernandez-Alvarez MDM. Spanish adaptation and validation of the User Version of the Mobile Application Rating Scale (uMARS). J Am Med Inform Assoc 2021; 28:2681-2686. [PMID: 34613400 PMCID: PMC8633643 DOI: 10.1093/jamia/ocab216] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 09/16/2021] [Accepted: 09/30/2021] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE While the professional version of the Mobile App Rating Scale (MARS) has already been translated, and validated into the Spanish language, its user-centered counterpart has not yet been adapted. Furthermore, no other similar tools exist in the Spanish language. The aim of this paper is to adapt and validate User Version of the MARS (uMARS) into the Spanish language. MATERIALS AND METHODS Cross-cultural adaptation, translation, and metric evaluation. The internal consistency and test-retest reliability of the Spanish version of the uMARS were evaluated using the RadarCovid app. Two hundred and sixteen participants rated the app using the translated scale. The app was then rated again 2 weeks later by 21 of these participants to measure test-retest reliability. RESULTS No major differences were observed between the uMARS original and the Spanish version. Discrimination indices (item-scale correlation) obtained appropriate results for both raters. The Spanish uMARS presented with excellent internal consistency, α = .89 and .67 for objective and subjective quality, respectively, and temporal stability (r > 0.82 for all items and subscales). DISCUSSION The Spanish uMARS is a useful tool for health professionals to recommend high-quality mobile apps to their patients based on the user's perspective and for researchers and app developers to use end-user feedback and evaluation, to help them identify highly appraised and valued components, as well as areas for further development, to continue ensuring the increasing quality and prominence of the area of mHealth. CONCLUSION uMARS Spanish version is an instrument with adequate metric properties to assess the quality of health apps from the user perspective.
Collapse
Affiliation(s)
- Ruben Martin-Payo
- Facultad de Medicina y Ciencias de la Salud, Universidad de Oviedo, Oviedo, Spain.,PRECAM Research Group, Instituto de Investigación Sanitaria del Principado de Asturias, Spain
| | - Sergio Carrasco-Santos
- Facultad de Medicina y Ciencias de la Salud, Universidad de Oviedo, Oviedo, Spain.,PRECAM Research Group, Instituto de Investigación Sanitaria del Principado de Asturias, Spain.,Área Sanitaria 3, Servicio de Salud del Principado de Asturias, Spain
| | | | - Stoyan Stoyan
- School of Psychology and Counselling, Queensland University of Technology, Brisbane, Australia.,Division of Advocacy and Research, Yourtown, Brisbane, Australia
| | - Xana Gonzalez-Mendez
- Facultad de Medicina y Ciencias de la Salud, Universidad de Oviedo, Oviedo, Spain.,PRECAM Research Group, Instituto de Investigación Sanitaria del Principado de Asturias, Spain.,Área Sanitaria 3, Servicio de Salud del Principado de Asturias, Spain
| | - María Del Mar Fernandez-Alvarez
- Facultad de Medicina y Ciencias de la Salud, Universidad de Oviedo, Oviedo, Spain.,PRECAM Research Group, Instituto de Investigación Sanitaria del Principado de Asturias, Spain
| |
Collapse
|