Classes Of Users Research Articles

The association between self-esteem and dimensions and classes of cross-platform social media use in a sample of emerging adults – Evidence from regression and latent class analyses

There is growing interest in the role of social media use in young people's mental health, and self-esteem has been hypothesised as a potential link in this association. However, existing studies have tended to use basic indicators of use in isolation and single-platform data, and further, have not controlled for other key variables. To address these limitations, emerging adults completed online questionnaires on social media engagement and self-esteem. In line with the interpersonal-connection-behaviours framework we explored online behaviours that putatively connect and disconnect users, e.g. meeting new people and engaging in social comparisons, respectively. Data were analysed using two methodologies, facilitating examination of the relationship between self-esteem and individual engagement indicators (regression analysis) as well as patterns of use (Latent Class Analysis). Overall levels of use and upward social comparisons independently predicted variance in self-esteem scores, even after controlling for demographic and socioeconomic covariates. Further, membership to meaningful, empirically-derived classes of social media users was predicted by self-esteem. These findings indicate that the association between social media use, social comparisons and self-esteem is robust, and extends to multi-platform data. We argue that such a move away from studies of single-platform data is critical if findings are to be generalised.

Contents and risks of land reform in Ukraine (literary and legislative review)

Land reform, which has been ongoing in Ukraine since 1990, now includes several strategic tasks, including the opening of the agricultural lands market. The article aims to identify the main risks of land reform implementation in Ukraine and outline the prospects for its development and impact on the country’s economy. The current state of the problem is analyzed based on the study of literary sources, regulatory and legal base, legislative initiatives, and their discussion in Ukrainian society. An attempt to systematically outline the possible positive consequences and risks of land reform in Ukraine in its various variants was made. Key initiatives for change, their impact on the economy of the state, and the benefits of major stakeholder groups are summarized. The necessity of ensuring based on the reform of the rational land use, forming a class of efficient land users in the society, stimulating the farming development and organic production development, was emphasized.

Efficient Channel Allocation using Matching Theory for QoS Provisioning in Cognitive Radio Networks.

The focus of research efforts in cognitive radio networks (CRNs) has primarily remained confined to maximizing the utilization of the discovered resources. However, it is also important to enhance the user satisfaction in CRNs by finding a suitable match between the secondary users and the idle channels available from the primary network while taking into consideration not only the quality of service (QoS) requirements of the secondary users but the quality of the channels as well. In this work, the Gale Shapley matching theory was applied to find the best match, so that the most suitable channels from the available pool were allocated that satisfy the QoS requirements of the secondary users. Before applying matching theory, two objective functions were defined from the secondary user’s perspective as well as from the channel’s perspective. The objective function of secondary users is the weighted sum of the data rate of the secondary users and the probability of reappearance of the primary user on the channel. Whereas, the objective function of the channel is the maximum utilization of the channel. The weight factors included in the objective functions allow for diverse service classes of secondary users (SUs) or varying channel quality characteristics. The objective functions were used in developing the preference lists for the secondary users and the idle channels. The preference lists were then used by the Gale Shapely matching algorithm to determine the most suitably matched SU-channel pairs. The performance of the proposed scheme was evaluated using Monte–Carlo simulations. The results show significant improvement in the overall satisfaction of the secondary users with the proposed scheme in comparison to other contemporary techniques. Further, the impact of changing the weight factors in the objective functions on the secondary user’s satisfaction and channel utilization was also analyzed.

U-Space Concept of Operations: A Key Enabler for Opening Airspace to Emerging Low-Altitude Operations

Opening the sky to new classes of airspace user is a political and economic imperative for the European Union. Drone industries have a significant potential for economical growth according to the latest estimations. To enable this growth safely and efficiently, the CORUS project has developed a concept of operations for drones flying in Europe in very low-level airspace, which they have to share that space with manned aviation, and quite soon with urban air mobility aircraft as well. U-space services and the development of smart, automated, interoperable, and sustainable traffic management solutions are presented as the key enabler for achieving this high level of integration. In this paper, we present the U-space concept of operations (ConOps), produced around three new types of airspace volume, called X, Y, and Z, and the relevant U-space services that will need to be supplied in each of these. The paper also describes the reference high-level U-space architecture using the European air traffic management architecture methodology. Finally, the paper proposes the basis for the aircraft separation standards applicable by each volume, to be used by the conflict detection and resolution services of U-space.

DSM-5 Latent Classes of Alcohol Users among Treatment Seeking Older Adults

Objective: Understanding the variation of alcohol use disorder (AUD) among a clinical sample of patients aged 60 and older, by identifying latent classes of AUD and exploring risk factors and outcomes of treatment associated with the class. Method: We used the Danish subsample (n = 341) from the Elderly Study. Latent class analysis was used to identify classes based on the 11 symptoms of DSM-5 AUD. We analyzed the associations between class membership and sociodemographic variables, alcohol consumption, and drinking-related outcome of treatment. Results: Three latent classes were identified. Individuals in the low-symptomatic class (34.85%) displayed low endorsement of DSM-5 criteria “Withdrawal”, “Time Spent”, “Less activities” compared to the other classes, and had fewest drinks per drinking day. Individuals in the moderate-symptomatic class (32.69%) were most likely to be intoxicated in hazardous situations, and those in the high-symptomatic class (32.47%) displayed, with a few exceptions, the highest probabilities of all DSM-5 criteria. Female gender, living alone and prior AUD treatment was associated with increased risk of being in the high-symptomatic class. No difference between classes was found with respect to years with AUD and frequency of drinking days, and latent class membership had no effect on drinking outcome after treatment, when controlling for baseline. Conclusions: Three classes of DSM-5 AUD among older adults in treatment emerged, displaying a low-moderate-high distribution, advocating for a unidimensional construct of DSM-5 AUD. Although different with respect to baseline risk factors, no strong connection between DSM-5 latent class and alcohol consumption after AUD treatment was found.HighlightsAmong 341 older alcohol use disorder (AUD) outpatients, three latent classes of DSM-5 AUD emerged.The classes of DSM-5 AUD displayed a low-moderate-high endorsement of DSM-5 AUD characteristics.The three classes had similar alcohol-related treatment outcomes.

Exploring publish/subscribe, multilevel cloud elasticity, and data compression in telemedicine

Background and Objective: Multiple medical specialties rely on image data, typically following the Digital Imaging and Communications in Medicine (DICOM) ISO 12052 standard, to support diagnosis through telemedicine. Remote analysis by different physicians requires the same image to be transmitted simultaneously to different destinations in real-time. This scenario poses a need for a large number of resources to store and transmit DICOM images in real-time, which has been explored using some cloud-based solutions. However, these solutions lack strategies to improve the performance through the cloud elasticity feature. In this context, this article proposes a cloud-based publish/subscribe (PubSub) model, called PS2DICOM, which employs multilevel resource elasticity to improve the performance of DICOM data transmissions.Methods: A prototype is implemented to evaluate PS2DICOM. A PubSub communication model is adopted, considering the coexistence of two classes of users: (i) image data producers (publishers); and (ii) image data consumers (subscribers). PS2DICOM employs a cloud infrastructure to guarantee service availability and performance through resource elasticity in two levels of the cloud: (i) brokers and (ii) data storage. In addition, images are compressed prior to the transmission to reduce the demand for network resources using one of three different algorithms: (i) DEFLATE, (ii) LZMA, and (iii) BZIP2. PS2DICOM employs dynamic data compression levels at the client side to improve network performance according to the current available network throughput.Results: Results indicate that PS2DICOM can improve transmission quality, storage capabilities, querying, and retrieving of DICOM images. The general efficiency gain is approximately 35% in data sending and receiving operations. This gain is resultant from the two levels of elasticity, allowing resources to be scaled up or down automatically in a transparent manner.Conclusions: The contributions of PS2DICOM are twofold: (i) multilevel cloud elasticity to adapt the computing resources on demand; (ii) adaptive data compression to meet the network quality and optimize data transmission. Results suggest that the use of compression in medical image data using PS2DICOM can improve the transmission efficiency, allowing the team of specialists to communicate in real-time, even when they are geographically distant.

Effective University Facility Management Plan Proposal Reflecting the Needs of the Main Users.

As the low birthrates in Korea intensify, the average school-age population is showing great reduction and the resources used for admission to the university are gradually decreasing as well, due to the continuing economic downturn. Therefore, in order for the university to remain competitive and keep up with the fast paced changes, it is very significant that they induce qualitative growth of university education and facilities through extensive and thorough analysis on the university facility management (UFM) for students who are the main users of university facilities. However, research done on university facilities in Korea has been focused mainly on space management, while the effective UFM reflecting in-depth opinions on the user class has been quite inadequate. Therefore, in order to improve student satisfaction and improve the efficiency of UFM, it is crucial to understand the importance and status of the UFM items. This way, an initial plan for improvement of UFM considering the priorities that actively reflect the opinions of the students is prepared in this research. For the UFM items, the eight classifications of UFM, which can be evaluated by users, and the details of the classifications are used for this research. For the UFM strategies, the first 176 performance indicators (PIs) are collected, consolidated, and deleted. Finally, eight UFM strategies are derived. In order to find out which UFM items need more focus on, importance–performance analysis (IPA) is conducted. The priority of management is determined by where each factor is located on the grid. Additionally, multiple linear regression analysis is conducted to examine the effect of the importance value on the UFM items on the importance value on the UFM strategies. Finally, the average values of importance for the strategies of UFM of two groups are compared and analyzed. As a result of the stages listed above, this research attempts to provide basic data on preparing the UFM plan. Therefore, it is possible to apply the method that reflects the needs of actual users in preparing future UFM plans throughout the research methods proposed in this research.

THE STRUCTURAL ROLE OF USER CLASS IN CHAT INTERACTIONS ON TWITCH

Twitch.tv has become an important platform for video streaming, especially of games, with more than 100 million monthly users. The structure of content on the platform, which merges live video feeds with chat rooms for user feedback, problematizes existing theoretical frameworks for understanding the roles and hierarchies of different types of users. Combined with efforts to monetize user engagement for the benefit of both platform owners and user-generators of content, there is a need for greater understanding of the new interaction paradigm introduced by the platform. The present study introduces a framework for systematic, quantitative analysis of user interactions in the chat rooms associated with Twitch channels, as well as a preliminary data set. Social network analysis techniques are used to analyse the centrality and homophily of different classes of users, and the theoretical significance of these observations is briefly discussed.

A Determination Scheme for Quasi-Identifiers Using Uniqueness and Influence for De-Identification of Clinical Data

Background: The accumulation and usefulness of clinical data have increased with IT development. While using clinical data that needs to be identifiable to obtain meaningful information, it is essential to ensure that data is de-identified. Methods: To formulate such a method, first, primary quasi-identifiers were selected by classifying information in 20 clinical personal information database tables into Direct-Identifier (DID), Quasi-Identifier (QI), Sensitive Attribute (SA), and Non-Sensitive Attribute (NSA) according to its type. Secondary QIs were then selected by assessing the risk for outliers by measuring uniqueness values of the selected data and scoring re-identification by calculating equivalence class of the influence on other data on QI removal. Third, the risk of re-identification of data users was numeralized and classified. Lastly, the final QI according to user class was determined by comparing the calculated re-identification scores to the threshold values of user classes. Results: Eventually, final QIs ranging 17 to 28 were selected by making an assumption. Conclusions: Therefore, clinical data users can securely and efficiently use clinical data containing personal information by objectively selecting QIs using the method proposed in the present study.

Foreigners as gentrifiers and tourists in a Mexican historic district

Transnational gentrification has become a key element of urban and sociocultural transformations in several Latin American countries. New urban policies and transnational real estate markets adapt the city in order to respond to the expectations of transnational middle classes. This paper explores the case of San Miguel de Allende in Mexico. Methodologically, it adopts a qualitative approach and analyses two of the most important manifestations of transnational gentrification: lifestyle migration and luxury tourism. Historical files on protected buildings in San Miguel de Allende’s historic centre were used to observe functional alterations. This is supplemented with other statistical data (including the spatial pattern of Airbnb rentals) and direct observations of public spaces. I propose that transnational gentrification leads to a heritage-led transnationalisation of real estate, evidenced by luxury housing, boutique hotels, art galleries and other high culture spaces that cater to higher-income lifestyle migrants and tourists. As a result, the new class of owners and users changes the place’s identity, which has implications for lower-income groups’ right to the city. The process in San Miguel de Allende is analogous to processes in cities such as London, New York or Paris, where notions of heritage urbanism have also helped transnationalise local real estate markets. However, it also evinces other processes that are more difficult to appreciate in the Global North (growing rent gaps, real estate companies’ aggressive pursuit of gentrification and deep historical inequalities that are exacerbated by heritage-led gentrification).

Investigating differences in sex, race/ethnicity, and impulsivity across substance user profiles: a person-centered approach

Although substance use is considered normative in college, continued examination of factors associated with problematic use is merited. This study identified latent substance user classes and examined their relations with sex, race/ethnicity, impulsivity-like facets, and substance use outcomes among 702 undergraduate students. Non-Alcohol Abstaining Users (NAA), Minimal Users (MU), and Polysubstance Users (PSU) emerged from latent class analysis. Variable-centered analyses indicated that substance user classes did not differ by sex. Students in the Asian and Other groups were at greater odds of being in the MU class than either NAA or PSU class, compared to White students. Differential patterns of impulsigenic trait levels emerged across latent classes. The present study highlights the utility of integrating person- and variable-centered approaches in studying heterogeneous substance use behaviors among college students. College PSU are particularly at risk for problematic outcomes, thus warranting preventive intervention that may target impulsigenic traits or polysubstance use.

Stability analysis and prevention strategies of tobacco smoking model

This research work is related to a tobacco smoking model having a significance class of users of tobacco in the form of snuffing. For this purpose, the formulation of the model containing snuffing class is presented; then the equilibrium points as regards being smoking free and smoking positive are discussed. The Hurwitz theorem is used for finding the local stability of the model and Lyaponov function theory is used for the search of global stability. We use different controls for control of smoking and the Pontryagin maximum principle for characterization of the optimal level. For the solution of the proposed model, a nonstandard finite difference (NSFD) scheme and the Runge–Kutta fourth order method are used. Finally, some numerical results are presented for control and without control systems with the help of MATLAB.

Spatiotemporal Characterization of Users’ Experience in Massive Cognitive Radio Networks

The need to capture the actual network traffic condition and fundamental queueing dynamics in a massive cognitive radio network (CRN) is important for proper analysis of the intrinsic effects of spatial distribution while capturing the essential temporal distribution properties of the network. In massive CRN, many users, including primary and secondary users, transmit on scarce spectrum resources. While primary users (PUs) are delay-sensitive users that require prioritized access over secondary users (SUs), carrying out analysis that captures this property becomes imperative if users’ service experience is to be satisfactory. This paper presents priority conscious spatiotemporal analysis capable of characterizing users’ experience in massive CRN. Users in the primary priority queue were considered to have pre-emptive priory over users in the virtual and secondary priority queues. A Geo/G/1 discrete-time Markov chain queueing system was adopted to characterize both primary and secondary priority queues, while the virtual priority queue was analyzed as part of the secondary priority queue. Using the tools of stochastic geometry and queueing theory, the user’s coverage probability was determined while the delay experienced by each class of users in the network was obtained using existing results. Through the obtained delay for each class of users in the network, the corresponding quality of service was also obtained. The results obtained show that the proposed framework is capable of accurately characterizing users’ service experience in massive CRN.

Understanding the Emergence of Collaborative Problem-Solving Practices in Enterprise Social Media: The Roles of Social Factors

Firms are increasingly introducing enterprise social media (ESM) technologies to nurture the virtual community of practice, offering a prospect for collaborative problem-solving (CPS) within organizations. Based on a unique dataset including 10101 actual problem-solving scenarios across 519 ESM groups, our objective is to identify the relationships between many social factors and the occurrence of CPS by drawing on different social theories. Via multilevel logistic regression, we found that the quality and decentralized degree of social interactions in an ESM group can increase the likelihood of CPS; one user’s social similarity with other members of the group and the user’s user classes are positively related to the likelihood of CPS. Finally, social ties’ strength between the user and other members in the ESM group has a U-shaped association with the likelihood of CPS. These findings can provide companies with meaningful implications for using ESM sites to support CPS.

Qn: Quality and Quantity Based Unified Approach for Secure and Trustworthy Mobile Crowdsensing

A major challenge in mobile crowdsensing applications is the generation of false (or spam) contributions resulting from selfish and malicious behaviors of users, or wrong perception of an event. Such false contributions induce loss of revenue owing to undue incentivization, and also affect the operational reliability of the applications. To counter these problems, we propose an event-trust and user-reputation model, called QnQ, to segregate different user classes such as honest, selfish, or malicious. The resultant user reputation scores, are based on both `quality' (accuracy of contribution) and `quantity' (degree of participation) of their contributions. Specifically, QnQ exploits a rating feedback mechanism for evaluating an event-specific expected truthfulness, which is then transformed into a robust quality of information (QoI) metric to weaken various effects of selfish and malicious user behaviors. Eventually, the QoIs of various events in which a user has participated are aggregated to compute his reputation score, which in turn is used to judiciously disburse user incentives with a goal to reduce the incentive losses of the CS application provider. Subsequently, inspired by cumulative prospect theory (CPT), we propose a risk tolerance and reputation aware trustworthy decision making scheme to determine whether an event should be published or not, thus improving the operational reliability of the application. To evaluate QnQ experimentally, we consider a vehicular crowdsensing application as a proof-of-concept. We compare QoI performance achieved by our model with Jøsang's belief model, reputation scoring with Dempster-Shafer based reputation model, and operational (decision) accuracy with expected utility theory. Experimental results demonstrate that QnQ is able to better capture subtle differences in user behaviors based on both quality and quantity, reduces incentive losses, and significantly improves operational accuracy in presence of rogue contributions.

Neural network based model for global Total Electron Content forecasting

We introduce a novel empirical model to forecast, 24 h in advance, the Total Electron Content (TEC) at global scale. The technique leverages on the Global Ionospheric Map (GIM), provided by the International GNSS Service (IGS), and applies a nonlinear autoregressive neural network with external input (NARX) to selected GIM grid points for the 24 h single-point TEC forecasting, taking into account the actual and forecasted geomagnetic conditions. To extend the forecasting at a global scale, the technique makes use of the NeQuick2 Model fed by an effective sunspot number R12 (R12eff), estimated by minimizing the root mean square error (RMSE) between NARX output and NeQuick2 applied at the same GIM grid points. The novel approach is able to reproduce the features of the ionosphere especially during disturbed periods. The performance of the forecasting approach is extensively tested under different geospatial conditions, against both TEC maps products by UPC (Universitat Politècnica de Catalunya) and independent TEC data from Jason-3 spacecraft. The testing results are very satisfactory in terms of RMSE, as it has been found to range between 3 and 5 TECu. RMSE depend on the latitude sectors, time of the day, geomagnetic conditions, and provide a statistical estimation of the accuracy of the 24-h forecasting technique even over the oceans. The validation of the forecasting during five geomagnetic storms reveals that the model performance is not deteriorated during disturbed periods. This 24-h empirical approach is currently implemented on the Ionosphere Prediction Service (IPS), a prototype platform to support different classes of GNSS users.

METHOD FOR ASSESSING OF RELIABILITY CHARACTERISTICS IN DESIGNING OF FAILURERESISTANT REAL-TIME OPERATING SYSTEMS

For many years, real-time OS-based applications have been used in embedded special-purpose systems. Recently they have been used everywhere, from on-board control systems for aircraft, to household appliances. The development of multiprocessor computing systems usually aims to increase either the level of reliability or the level of system performance to values that are inaccessible or difficult to implement in traditional computer systems. In the first case, the question of the availability of special means of ensuring the fault tolerance of computer systems arises, the main feature (and advantage) of which is the absence of any single resource, failure of which leads to a fatal failure of the entire system. The use of a real-time operating system is always associated with equipment, with an object and with events occurring at an object. A real-time system, as a hardware-software complex, includes sensors that record events at an object, input / output modules that convert sensor readings into a digital form suitable for processing these readings on a computer, and finally, a computer with a program that responds to events occurring at the facility. The RTOS is focused on processing external events. It is this that leads to fundamental differences (compared with general-purpose OS) in the structure of the system as well as in the functions of the kernel and in the construction of the input-output system. The RTOS can be similar in its user interface to general-purpose operating systems, but it is completely different in its structure. In addition, the use of RTOS is always specific. If users (not developers) usually perceive a general-purpose OS as a ready-made set of applications, then the RTOS serves only as a tool for creating a specific hardware-software complex in real time. Therefore, the widest class of users of RTOS is the developers of real-time complexes, people designing control and data collection systems. When designing and developing a specific real-time system, the programmer always knows exactly what events can occur at the facility, and he knows the critical terms for servicing each of these events. We call a real-time system (SRV) a hardware-software complex that responds in predictable times to an unpredictable stream of external events. The system must have time to respond to the event that occurred at the facility, during the time critical for this event. The critical time for each event is determined by the object and by the event itself, and, of course, it can be different, but the response time of the system must be predicted (calculated) when creating the system. Lack of response at the predicted time is considered an error for real-time systems. The system must have time to respond to simultaneously occurring events. Even if two or more external events occur simultaneously, the system must have time to respond to each of them during time intervals critical for these events. In this study, as part of a network fault-tolerant technology, the RTOS becomes a special type of control software that is used to organize the operation of embedded applications, which are characterized by limited memory resources, low productivity and the requirements of a guaranteed response time (T<4 μs), high level availability and availability of auto-monitoring facilities.

Survey to Explore Behavior, Intelligent Transportation Systems Needs, and Level of Service Expectations for Student Parking at a University Campus

University campuses generate large volumes of traffic, with students forming the largest user class with distinctive trip characteristics. This study examined the parking choices of students at a large urban campus. A student survey was conducted with 1,022 respondents to collect data on students’ parking behavior, intelligent transportation systems (ITS) needs, and level of service (LOS) expectations. The survey results included home-to-campus mode choices, arrival time buffers, parking locations, “last-mile” mode choices, and factors that influence the type of permit to purchase. Online permit sales, flexible parking zones, and real-time parking lot availability information were the three most preferred ITS enabled services. Using the survey feedback, new LOS criteria for parking search time are proposed, which range from up to 2 min for LOS A, to longer than 15 min for LOS F. This research makes several contributions. The survey results not only contribute to a better understanding of student transportation choices and parking patterns on campus, but the list of preferred ITS enabled services also gives the university valuable user feedback on where to improve the campus parking experience. More importantly, the LOS criteria for parking search time provides a new tool for traffic engineers to measure the quality of service of a parking facility. Although the survey was conducted on a particular campus, information gathered for the ITS enabled services for parking and LOS criteria for parking search time are likely to be transferable to other university campuses.

Sistem Pendukung Keputusan Pemilihan Kamera DSLR Dengan Metode Promethee

Kamera Digital Single Lens Reflex (DSLR) adalah sebuah kamera dengan sistem digital yang memakai satu buah lensa yang terpasang di body kamera. Semua merk kamera DSLR membagi konsumen mereka di kelas-kelas pengguna kamera untuk mepermudah pengguna menbedakan fiturnya, seperti : kelas pemula (entry level), kelas profesional (semi-professional & professional) dan kelas menengah (semi advanced & advanced). Pemilihan kamera DSLR untuk komsumen memiliki cukup banyak parameter yang dapat dijadikan tolak ukur bagi seseorang untuk menentukan kamera DSLR mana yang sesuai dengan kebutuhan dan keinginannya. Parameter digunakan dalam penentuan kamera DSLR dapat berupa penilaian subjektif atau penilaian objektif. Terkadang seseorang kesulitan dalam menentukan parameter yang diambil dalam menentukan keputusan, sehingga pilihan yang diambil pada akhirnya kurang begitu sesuai dengan apa yang diharapkan. Metode promethee merupakan salah satu penentuan urutan (prioritas) dalam analisis multikriteria. Kesederhanaan, kejelasan, dan kestabilan, merupakan fokus masalah pokok dalam metode promethee. Seperti kebanyakan metode lainnya, proses perangkingan dilakukan dengan melakukan seleksi kepada beberapa alternatif dengan kriteria yang telah ditentukan. Terdapat Sembilan kriteria yang akan diuji, yaitu : image resolution, video resolution, ISO, focus point, screen pixel, shutter speed, battery life, class camera dan harga. Aplikasi Sistem Pendukung Keputusan Pemilihan Kamera DSLR ini dibuat dengan Bahasa pemrograman berbasis web PHP dan mysql sebagai perangkat lunak sistem manajemen database. Sistem ini diharapkan dapat memberikan rekomendasi kamera DSLR sesuai dengan kriteria yang ditentukan oleh calon konsumen secara efisien dan efektif, sehingga meminimalisir kemungkinan kerugian yang didapatkan oleh konsumen.

Toward understanding the impact of mHealth features for people with HIV: a latent class analysis of PositiveLinks usage.

PositiveLinks (PL) is a multi-feature smartphone-based platform to improve engagement-in-care and viral suppression (VS) among clinic patients living with HIV. Features include medication reminders, mood/stress check-ins, a community board, and secure provider messaging. Our goal was to examine how PL users interact with the app and determine whether usage patterns correlate with clinical outcomes. Patients (N = 83) at a university-based Ryan White clinic enrolled in PL from June 2016 to March 2017 and were followed for up to 12 months. A subset (N = 49) completed interviews after 3 weeks of enrollment to explore their experiences with and opinions of PL. We differentiated PL members based on 6-month usage of app features using latent class analysis. We explored characteristics associated with class membership, compared reported needs and preferences by class, and examined association between class and VS. The sample of 83 PL members fell into four classes. "Maximizers" used all app features frequently (27%); "Check-in Users" tended to interact only with daily queries (22%); "Moderate All-Feature Users" used all features occasionally (33%); and "As-Needed Communicators" interacted with the app minimally (19%). VS improved or remained high among all classes after 6 months. VS remained high at 12 months among Maximizers (baseline and 12-month VS: 100%, 94%), Check-in Users (82%, 100%), and Moderate All-Feature Users (73%, 94%) but not among As-Needed Communicators (69%, 60%). This mixed-methods study identified four classes based on PL usage patterns that were distinct in characteristics and clinical outcomes. Identifying and characterizing mHealth user classes offers opportunities to tailor interventions appropriately based on patient needs and preferences as well as to provide targeted alternative support to achieve clinical goals.