Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Top 10 source disciplines for each knowledge type_
| Research Subject | Entity | Technology | Research Methodology | Data | Theory |
|---|---|---|---|---|---|
| Health Care Sciences & Services | Health Care Sciences & Services | Health Care Sciences & Services | Health Care Sciences & Services | Health Care Sciences & Services | Public, Environmental & Occupational Health |
| Medical Informatics | Medical Informatics | Medical Informatics | Medical Informatics | Medical Informatics | Health Care Sciences & Services |
| Public, Environmental & Occupational | Public, Environmental & Occupational | Public, Environmental & Occupational | Public, Environmental & Occupational | Public, Environmental & Occupational | Medical Informatics |
| Health Medicine, General & Internal | Health Medicine, General & Internal | Health Medicine, General & Internal | Health Psychiatry | Health Medicine, General & Internal | Psychology, Multidisciplinary |
| Psychiatry | Psychiatry | Computer Science, Information Systems | Medicine, General & Internal | Information Science & Library Science | Management |
| Psychology, Clinical | Nursing | Information Science & Library Science | Psychology, Clinical | Computer Science, Information Systems | Psychology, Applied |
| Substance Abuse | Psychology, Clinical | Computer Science, Interdisciplinary Application | Substance Abuse | Computer Science, Interdisciplinary Application | Psychology, Social |
| Health Policy & Services | Health Policy & Services | Psychiatry | Health Policy & Services | Health Policy & Services | Psychology |
| Nursing | Substance Abuse | Psychology, Clinical | Psychology | Multidisciplinary Sciences | Psychology, Clinical |
| Endocrinology & Metabolism | Computer Science, Information Systems | Substance Abuse | Psychology, Multidisciplinary | Psychiatry | Computer Science, Information Systems |
The knowledge classification schema for AKPs_
| Category | Description | Literature sources |
|---|---|---|
| Research Subject | subject terms related to research problems, such as diseases and research areas. | Heffernan & Teufel, 2018; Kondo et al., 2009 |
| Theory | theory related phrases, e.g., specific names of theories, and frameworks | Wang & Zhang, 2018; Pettigrew & McKechnie, 2001 |
| Research Methodology | research methodology, including research methods, scales, guidelines, evaluation indicators, etc. | Sahragard & Meihami, 2016; Heffernan & Teufel, 2018; Mesbah et al., 2017; Radoulov, 2008; |
| Technology Entity | techniques, devices, and systems people or organizations that are involved in any aspect of the research | Gupta & Manning, 2011; Tsai et al., 2013 Bahadoran et al., 2019 |
| Data | phrases related to datasets, data sources, and data material | Wang & Zhang, 2018; Sahragard & Meihami, 2016; Mesbah et al., 2017; Radoulov, 2008 |
| Others | other phrases that are not included in the above categories, e.g., geolocations, projects, etc. | Kondo et al., 2009 |
Annotation example of each knowledge category_
| AKPs | Citation sentences | Knowledge type |
|---|---|---|
| chronic illness | For effective medical care of chronic illness, such as Type 2 diabetes mellitus (T2DM), adequate and sustainable self-management initiated by patients is important | Research Subject |
| social cognitive theory | The intervention, including both the SMS text messaging and individual counseling session, was modeled after national treatment guidelines, and guided by Social Cognitive Theory and the stages of change model | Theory |
| qualitative research methodology | In recent years, qualitative research methodology has become more recognized and valued in diabetes behavioral research because it helps answer questions that quantative research might not, by exploring patient motivations, perceptions, and expectations | Research Methodology |
| SMS text messaging | Consistent with the literature, SMS text messaging was an appropriate and accepted tool to deliver health promotion content | Technology |
| heart failure patient | De Vries et al (2013) evaluated the actual use and goals of telemonitoring systems, whereas Seto et al (2012) developed a randomized trial of mobile phone-based telemonitoring systems to examine the experience of heart failure patients with these systems | Entity |
| bacteriology datum | PDA-based technologies were used to develop a PDA-based electronic system to collect, verify, and upload bacteriology data into an electronic medical record system; develop a wireless clinical care management system; and develop a data collection/entry system for public surveillance data collection | Data |
| low risk | Free et al found that while mHealth studies have been conducted many are of poor quality, few have a low risk of bias, and very few have found clinically significant benefits of the interventions | Others |
Integration characteristics of different knowledge types_
| Knowledge type | Knowledge amount | Distinct AKPs | References | Source disciplines | Knowledge integration density | Average citation interval |
|---|---|---|---|---|---|---|
| Research Subject | 104,988 | 15,324 | 51,622 | 187 | 2.03 | 5.91 |
| Entity | 25,213 | 1,665 | 18,219 | 150 | 1.38 | 5.33 |
| Technology | 17,945 | 1,885 | 13,256 | 157 | 1.35 | 4.22 |
| Research Methodology | 9,099 | 2,079 | 6,773 | 144 | 1.34 | 7.74 |
| Data | 3,297 | 296 | 2,822 | 124 | 1.17 | 5.11 |
| Theory | 1,315 | 225 | 921 | 88 | 1.43 | 10.55 |
| Others | 84,310 | 4,290 | 44,346 | 190 | 1.90 | 5.50 |
Brief information of our dataset_
| Statistical items | Value |
|---|---|
| Citing papers | 3,221 |
| Citation sentences | 119,598 |
| References | 101,751 |
| In-text citations | 199,461 |
| AKPs | 246,167 |
| Distinct AKPs | 25,764 |