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Thematic analysis is a highly popular technique among qualitative researchers for analyzing qualitative data, which usually comprises thick descriptive data. However, the application and use of thematic analysis has also involved complications due to confusion regarding the final outcome’s presentation as a conceptual model. This paper develops a systematic thematic analysis process for creating a conceptual model from qualitative research findings. It explores the adaptability of the proposed process across various research methodologies, including constructivist methodologies, positivist methodologies, grounded theory, and interpretive phenomenology, and justifies their application. The paper distinguishes between inductive and deductive coding approaches and emphasizes the merits of each. It suggests that the derived systematic thematic analysis model is valuable across multiple disciplines, particularly in grounded theory, ethnographic approaches, and narrative approaches, while also being adaptable to more descriptive, positivist-based methodologies. By providing a methodological roadmap, this study enhances the rigor and replicability of thematic analysis and offers a comprehensive strategy for theoretical conceptualization in qualitative research. The contribution of this paper is a systematic six-step thematic analysis process that leads to the development of a conceptual model; each step is described in detail and examples are given.

Digital transformation is currently one of the most influential developments. It is fundamentally changing consumers' expectations and behaviors, challenging traditional firms, and disrupting numerous markets. Recent discussions in the health care sector tend to assess the influence of technological implications but neglect other factors needed for a holistic view on the digital transformation. This calls for a reevaluation of the current state of digital transformation in health care. Consequently, there is a need for a holistic view on the complex interdependencies of digital transformation in the health care sector. This study aimed to examine the effects of digital transformation on the health care sector. This is accomplished by providing a conceptual model of the health care sector under digital transformation. First, the most essential stakeholders in the health care sector were identified by a scoping review and grounded theory approach. Second, the effects on these stakeholders were assessed. PubMed, Web of Science, and Dimensions were searched for relevant studies. On the basis of an integrative review and grounded theory methodology, the relevant academic literature was systematized and quantitatively and qualitatively analyzed to evaluate the impact on the value creation of, and the relationships among, the stakeholders. Third, the findings were synthesized into a conceptual model of the health care sector under digital transformation. A total of 2505 records were identified from the database search; of these, 140 (5.59%) were included and analyzed. The results revealed that providers of medical treatments, patients, governing institutions, and payers are the most essential stakeholders in the health care sector. As for the individual stakeholders, patients are experiencing a technology-enabled growth of influence in the sector. Providers are becoming increasingly dependent on intermediaries for essential parts of the value creation and patient interaction. Payers are expected to try to increase their influence on intermediaries to exploit the enormous amounts of data while seeing their business models be challenged by emerging technologies. Governing institutions regulating the health care sector are increasingly facing challenges from new entrants in the sector. Intermediaries increasingly interconnect all these stakeholders, which in turn drives new ways of value creation. These collaborative efforts have led to the establishment of a virtually integrated health care ecosystem. The conceptual model provides a novel and evidence-based perspective on the interrelations among actors in the health care sector, indicating that individual stakeholders need to recognize their role in the system. The model can be the basis of further evaluations of strategic actions of actors and their effects on other actors or the health care ecosystem itself.

Domestic violence (DV) victim service programs have been increasingly expected by legislators and funders to demonstrate that they are making a significant difference in the lives of those using their services. Alongside this expectation, they are being asked to describe the Theory of Change guiding how they believe their practices lead to positive results for survivors and their children. Having a widely accepted conceptual model is not just potentially useful to funders and policy makers as they help shape policy and practice -- it can also help programs continually reflect upon and improve their work. This paper describes the iterative and collaborative process undertaken to generate a conceptual model describing how DV victim services are expected to improve survivors’ lives. The Social and Emotional Well-Being Framework guiding the model is an ideal structure to use to describe the goals and practices of DV programs because this framework: (1) accurately represents DV programs’ goal of helping survivors and their children thrive; and (2) recognizes the importance of community, social, and societal context in influencing individuals’ social and emotional well-being. The model was designed to guide practice and to generate new questions for research and evaluation that address individual, community, and systems factors that promote or hinder survivor safety and well-being.

Despite recent applications of a developmental psychopathology perspective to the perinatal period, these conceptualizations have largely ignored the role that childbirth plays in the perinatal transition. Thus, we present a conceptual model of childbirth as a bridge between prenatal and postnatal health. We argue that biopsychosocial factors during pregnancy influence postnatal health trajectories both directly and indirectly through childbirth experiences, and we focus our review on those indirect effects. In order to frame our model within a developmental psychopathology lens, we first describe “typical” biopsychosocial aspects of pregnancy and childbirth. Then, we explore ways in which these processes may deviate from the norm to result in adverse or traumatic childbirth experiences. We briefly describe early postnatal health trajectories that may follow from these birth experiences, including those which are adaptive despite traumatic childbirth, and we conclude with implications for research and clinical practice. We intend for our model to illuminate the importance of including childbirth in multilevel perinatal research. This advancement is critical for reducing perinatal health disparities and promoting health and well-being among birthing parents and their children.

This applied paper is intended to serve as a “how to” guide for public health researchers, practitioners, and policy makers who are interested in building conceptual models to convey their ideas to diverse audiences. Conceptual models can provide a visual representation of specific research questions. They also can show key components of programs, practices, and policies designed to promote health. Conceptual models may provide improved guidance for prevention and intervention efforts if they are based on frameworks that integrate social ecological and biological influences on health and incorporate health equity and social justice principles. To enhance understanding and utilization of this guide, we provide examples of conceptual models developed by the Prevention of Lower Urinary Tract Symptoms (PLUS) Research Consortium. PLUS is a transdisciplinary U.S. scientific network established by the National Institutes of Health in 2015 to promote bladder health and prevent lower urinary tract symptoms, an emerging public health and prevention priority. The PLUS Research Consortium is developing conceptual models to guide its prevention research agenda. Research findings may in turn influence future public health practices and policies. This guide can assist others in framing diverse public health and prevention science issues in innovative, potentially transformative ways.

This paper proposes a conceptual model of sustainable supply chain management (SSCM) in small and medium enterprises (SME) using blockchain technology (BT). With growing focus on sustainable business process, research on SSCM is gaining prominence. BT, being a disruptive technology, has potential to impact the SSCM. Using the extant literature, the antecedents of SSCM using BT have been identified. Multiple-criteria decision-making has been deployed to develop the conceptual model. Various managerial and theoretical implications along with scope for future research have been discussed.

Objective: To provide an evidence-based review of plausible causal pathways that could best explain well-established associations between limited health literacy and health outcomes.Methods: Through analysis of current findings in medical and public health literature on health literacy we derived a conceptual causal model.Results: Health literacy should be viewed as both a patient and a system phenomenon. Three distinct points along a continuum of health care are suggested to be influenced by health literacy: (1) access and utilization of health care, (2) patient-provider relationship, and (3) self-care.Conclusions: The conceptual model organizes what has been learned to date and underscores promising areas of future inquiry and intervention.

Fueled by innovations in technology and health interventions to promote, restore, and maintain health and safeguard well-being, the field of eHealth has yielded significant scholarly output over the past 25 years. This study aims to offer a big picture of research developments and multidisciplinary contributions to eHealth that shaped this field up to 2024. To that end, we analyze evidence from 3 corpora: 10,022 OpenAlex documents with eHealth in the title, the 5000 most relevant eHealth articles according to the Web of Science (WoS) algorithm, and all available (n=1885) WoS eHealth reviews. Using VOSviewer, we built co-occurrence networks for WoS keywords and OpenAlex concepts. We examined clusters, categorized terminology, and added custom overlays about eHealth technologies, stakeholders, and objectives. A cocitation map of sources referenced in WoS reviews helped identify scientific fields supporting eHealth. After synthesizing eHealth terminology, we proceeded to build a conceptual model of eHealth scholarship grounded in bibliometric evidence. Several research directions emerged from bibliometric networks: eHealth studies on self-management and interventions, especially in mental health; telemedicine, telehealth, and technology acceptance; privacy, security, and design concerns; health information consumers' literacy; health promotion and prevention; mHealth and digital health; and HIV prevention. Conducted at the individual, health system, community, and society levels, eHealth studies focused on health and wellness across the human lifespan. Keywords such as internet (mean publication year 2017), telemedicine (2018), telehealth (2018), mHealth (2019), mobile health (2020), and digital health (2021) were strongly linked to literature indexed with eHealth (2019). Different types of eHealth apps were supported by research on infrastructures: networks, data exchange, computing technologies, information systems, and platforms. Researchers' concerns for eHealth data security and privacy, including advanced access control and encryption methods, featured prominently in the maps, along with terminology related to health analytics. Review authors cited a wide range of medical sources and journals specific to eHealth technologies, as well as journals in psychology, psychiatry, public health, policy, education, health communication, and other fields. The Journal of Medical Internet Research stood out as the most cited source. The concept map showed a prominent role of political science and law, economics, nursing, business, and knowledge management. Our empirically derived conceptual model of eHealth scholarship incorporated commonly researched stakeholder groups, eHealth application types, supporting infrastructure, health analytics concepts, and outcomes. Drawing upon contributions from many disciplines, the field of eHealth has evolved from early studies of internet-enabled communications, telemedicine, and telehealth to research on mobile health and emerging digital health technologies serving diverse stakeholders. Digital health has become a popular alternative term to eHealth. We offered practical implications and recommendations on future research directions, as well as guidance on study design and publication.

The forest-landscape image is the bridge for communication between human beings and the forest. The aim of this paper is to construct the landscape-image conceptual model from the personal perception of the forest, with what people are looking at and how they are viewing themselves as a part of the forest. This research constructed a forest-landscape image by young adults by utilizing the landscape-image-sketching technique and selecting 140 young adults who had lived in Changsha, Central China for ten years, using convenience sampling, during April and May 2018. The results demonstrated that the forest was considered as the people’s life world, as rural scenery around the respondents’ homes, instead of the perception of the objective forest, an important habitat for animals and a limited resource supplier for human living. In fact, the natural values of the forest, such as the ecological and aesthetic values, received more attention than the social ones of the forest, including the life, production, and cultural values. Finally, it is important to raise the public’s awareness of the objective entity of the forest and to guide the variety of experiences for the respondents in the forest.

Introduction Substance use disorder (SUD) is a persistent and long‐standing public health issue in the United States. While SUD is medically considered a chronic illness, it is also one that is viewed as self‐inflicted, thereby resulting in judgmental attitudes and stigmatization from care providers, specifically from nurses. Design In 2020, the authors completed an analytical cross‐sectional study that included open‐ended questions to examine nurses' knowledge and attitudes toward caring for patients with SUD across practice settings. Methods A conceptual model was constructed by examining original study data and published literature on SUD, re‐analyzing themes, determining constructs and variables, then coming to a consensus on critical aspects of the model. Conclusion The resulting conceptual model highlights antecedents of nursing behaviors that directly affect patient care outcomes, providing a roadmap to improving patient outcomes. Clinical relevance Understanding antecedents that affect nurses' attitudes and perceptions of patients with SUD highlights changes that can influence patient outcomes.