Using Granger Causal Test Associated with Trait Anxiety to Estimate STAI Scores by Constructing a Brain Activity Interdependence Network Article Swipe
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.12792/iciae2023.042
In recent years, many stress-related health problems have been reported, and an estimated 50% of suicide victims suffered from mental disorders. The State-Trait Anxiety Inventory (STAI), which measures trait and state anxieties, is one of the most widely used questionnaires for mental health, counseling, and research. However, because the STAI is a questionnaire-based test, examinees could manipulate the answers. Therefore, research has been conducted to estimate the state anxiety score, a stress evaluation index, based on brain activity. In the proposed method, Granger causality was used for cerebral blood flow to enable the numerical representation of the complex and diverse behaviors of the brain as dependencies. The brain activity interdependence network (BAIN) was constructed as a network representing the characteristics of brain activity affected by trait anxiety, and the amount of Kalbach – Leibler divergenceon obtained from the BAIN was used as a feature value. In the validation experiment, we measured resting-state cerebral blood flow using NIRS wearable optical topography in 17 male and female subjects in their 20s. Lasso regression analysis was used to estimate the characteristic anxiety score in the STAI, resulting in a correlation coefficient of 0.95 and an RMSE of 3.0 with high accuracy.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.12792/iciae2023.042
- https://www2.ia-engineers.org/conference/index.php/iciae/iciae2023/paper/download/2744/1797
- OA Status
- gold
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4367460565
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4367460565Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.12792/iciae2023.042Digital Object Identifier
- Title
-
Using Granger Causal Test Associated with Trait Anxiety to Estimate STAI Scores by Constructing a Brain Activity Interdependence NetworkWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-01-01Full publication date if available
- Authors
-
Kotaro Hasegawa, Yuri Hamada, Yosuke KuriharaList of authors in order
- Landing page
-
https://doi.org/10.12792/iciae2023.042Publisher landing page
- PDF URL
-
https://www2.ia-engineers.org/conference/index.php/iciae/iciae2023/paper/download/2744/1797Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www2.ia-engineers.org/conference/index.php/iciae/iciae2023/paper/download/2744/1797Direct OA link when available
- Concepts
-
Anxiety, Granger causality, Trait, Psychology, Clinical psychology, Regression, Regression analysis, Correlation, Resting state fMRI, Psychiatry, Statistics, Computer science, Mathematics, Neuroscience, Geometry, Psychoanalysis, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 1Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4367460565 |
|---|---|
| doi | https://doi.org/10.12792/iciae2023.042 |
| ids.doi | https://doi.org/10.12792/iciae2023.042 |
| ids.openalex | https://openalex.org/W4367460565 |
| fwci | 0.26377275 |
| type | article |
| title | Using Granger Causal Test Associated with Trait Anxiety to Estimate STAI Scores by Constructing a Brain Activity Interdependence Network |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | 247 |
| biblio.first_page | 244 |
| topics[0].id | https://openalex.org/T10241 |
| topics[0].field.id | https://openalex.org/fields/28 |
| topics[0].field.display_name | Neuroscience |
| topics[0].score | 0.9966999888420105 |
| topics[0].domain.id | https://openalex.org/domains/1 |
| topics[0].domain.display_name | Life Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2805 |
| topics[0].subfield.display_name | Cognitive Neuroscience |
| topics[0].display_name | Functional Brain Connectivity Studies |
| topics[1].id | https://openalex.org/T13283 |
| topics[1].field.id | https://openalex.org/fields/32 |
| topics[1].field.display_name | Psychology |
| topics[1].score | 0.995199978351593 |
| topics[1].domain.id | https://openalex.org/domains/2 |
| topics[1].domain.display_name | Social Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/3205 |
| topics[1].subfield.display_name | Experimental and Cognitive Psychology |
| topics[1].display_name | Mental Health Research Topics |
| topics[2].id | https://openalex.org/T10977 |
| topics[2].field.id | https://openalex.org/fields/27 |
| topics[2].field.display_name | Medicine |
| topics[2].score | 0.9886000156402588 |
| topics[2].domain.id | https://openalex.org/domains/4 |
| topics[2].domain.display_name | Health Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2741 |
| topics[2].subfield.display_name | Radiology, Nuclear Medicine and Imaging |
| topics[2].display_name | Optical Imaging and Spectroscopy Techniques |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C558461103 |
| concepts[0].level | 2 |
| concepts[0].score | 0.6662126779556274 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q154430 |
| concepts[0].display_name | Anxiety |
| concepts[1].id | https://openalex.org/C129824826 |
| concepts[1].level | 2 |
| concepts[1].score | 0.5992217659950256 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q2630107 |
| concepts[1].display_name | Granger causality |
| concepts[2].id | https://openalex.org/C106934330 |
| concepts[2].level | 2 |
| concepts[2].score | 0.573805034160614 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q1971873 |
| concepts[2].display_name | Trait |
| concepts[3].id | https://openalex.org/C15744967 |
| concepts[3].level | 0 |
| concepts[3].score | 0.5602810978889465 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q9418 |
| concepts[3].display_name | Psychology |
| concepts[4].id | https://openalex.org/C70410870 |
| concepts[4].level | 1 |
| concepts[4].score | 0.5181233286857605 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q199906 |
| concepts[4].display_name | Clinical psychology |
| concepts[5].id | https://openalex.org/C83546350 |
| concepts[5].level | 2 |
| concepts[5].score | 0.45595884323120117 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q1139051 |
| concepts[5].display_name | Regression |
| concepts[6].id | https://openalex.org/C152877465 |
| concepts[6].level | 2 |
| concepts[6].score | 0.439582884311676 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q208042 |
| concepts[6].display_name | Regression analysis |
| concepts[7].id | https://openalex.org/C117220453 |
| concepts[7].level | 2 |
| concepts[7].score | 0.4287595748901367 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q5172842 |
| concepts[7].display_name | Correlation |
| concepts[8].id | https://openalex.org/C66324658 |
| concepts[8].level | 2 |
| concepts[8].score | 0.4220479428768158 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q7316120 |
| concepts[8].display_name | Resting state fMRI |
| concepts[9].id | https://openalex.org/C118552586 |
| concepts[9].level | 1 |
| concepts[9].score | 0.26609498262405396 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q7867 |
| concepts[9].display_name | Psychiatry |
| concepts[10].id | https://openalex.org/C105795698 |
| concepts[10].level | 1 |
| concepts[10].score | 0.2533726692199707 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[10].display_name | Statistics |
| concepts[11].id | https://openalex.org/C41008148 |
| concepts[11].level | 0 |
| concepts[11].score | 0.21658900380134583 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[11].display_name | Computer science |
| concepts[12].id | https://openalex.org/C33923547 |
| concepts[12].level | 0 |
| concepts[12].score | 0.1774769425392151 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[12].display_name | Mathematics |
| concepts[13].id | https://openalex.org/C169760540 |
| concepts[13].level | 1 |
| concepts[13].score | 0.1267452836036682 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q207011 |
| concepts[13].display_name | Neuroscience |
| concepts[14].id | https://openalex.org/C2524010 |
| concepts[14].level | 1 |
| concepts[14].score | 0.0 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q8087 |
| concepts[14].display_name | Geometry |
| concepts[15].id | https://openalex.org/C11171543 |
| concepts[15].level | 1 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q41630 |
| concepts[15].display_name | Psychoanalysis |
| concepts[16].id | https://openalex.org/C199360897 |
| concepts[16].level | 1 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q9143 |
| concepts[16].display_name | Programming language |
| keywords[0].id | https://openalex.org/keywords/anxiety |
| keywords[0].score | 0.6662126779556274 |
| keywords[0].display_name | Anxiety |
| keywords[1].id | https://openalex.org/keywords/granger-causality |
| keywords[1].score | 0.5992217659950256 |
| keywords[1].display_name | Granger causality |
| keywords[2].id | https://openalex.org/keywords/trait |
| keywords[2].score | 0.573805034160614 |
| keywords[2].display_name | Trait |
| keywords[3].id | https://openalex.org/keywords/psychology |
| keywords[3].score | 0.5602810978889465 |
| keywords[3].display_name | Psychology |
| keywords[4].id | https://openalex.org/keywords/clinical-psychology |
| keywords[4].score | 0.5181233286857605 |
| keywords[4].display_name | Clinical psychology |
| keywords[5].id | https://openalex.org/keywords/regression |
| keywords[5].score | 0.45595884323120117 |
| keywords[5].display_name | Regression |
| keywords[6].id | https://openalex.org/keywords/regression-analysis |
| keywords[6].score | 0.439582884311676 |
| keywords[6].display_name | Regression analysis |
| keywords[7].id | https://openalex.org/keywords/correlation |
| keywords[7].score | 0.4287595748901367 |
| keywords[7].display_name | Correlation |
| keywords[8].id | https://openalex.org/keywords/resting-state-fmri |
| keywords[8].score | 0.4220479428768158 |
| keywords[8].display_name | Resting state fMRI |
| keywords[9].id | https://openalex.org/keywords/psychiatry |
| keywords[9].score | 0.26609498262405396 |
| keywords[9].display_name | Psychiatry |
| keywords[10].id | https://openalex.org/keywords/statistics |
| keywords[10].score | 0.2533726692199707 |
| keywords[10].display_name | Statistics |
| keywords[11].id | https://openalex.org/keywords/computer-science |
| keywords[11].score | 0.21658900380134583 |
| keywords[11].display_name | Computer science |
| keywords[12].id | https://openalex.org/keywords/mathematics |
| keywords[12].score | 0.1774769425392151 |
| keywords[12].display_name | Mathematics |
| keywords[13].id | https://openalex.org/keywords/neuroscience |
| keywords[13].score | 0.1267452836036682 |
| keywords[13].display_name | Neuroscience |
| language | en |
| locations[0].id | doi:10.12792/iciae2023.042 |
| locations[0].is_oa | True |
| locations[0].source | |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://www2.ia-engineers.org/conference/index.php/iciae/iciae2023/paper/download/2744/1797 |
| locations[0].version | publishedVersion |
| locations[0].raw_type | proceedings-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | The Proceedings of The 11th IIAE International Conference on Industrial Application Engineering 2023 |
| locations[0].landing_page_url | https://doi.org/10.12792/iciae2023.042 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5075855465 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | Kotaro Hasegawa |
| authorships[0].countries | JP |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I131231118 |
| authorships[0].affiliations[0].raw_affiliation_string | Aoyama Gakuin University |
| authorships[0].institutions[0].id | https://openalex.org/I131231118 |
| authorships[0].institutions[0].ror | https://ror.org/002rw7y37 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I131231118 |
| authorships[0].institutions[0].country_code | JP |
| authorships[0].institutions[0].display_name | Aoyama Gakuin University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Kotaro Hasegawa |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Aoyama Gakuin University |
| authorships[1].author.id | https://openalex.org/A5021956037 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-1200-4530 |
| authorships[1].author.display_name | Yuri Hamada |
| authorships[1].countries | JP |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I131231118 |
| authorships[1].affiliations[0].raw_affiliation_string | Aoyama Gakuin University |
| authorships[1].institutions[0].id | https://openalex.org/I131231118 |
| authorships[1].institutions[0].ror | https://ror.org/002rw7y37 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I131231118 |
| authorships[1].institutions[0].country_code | JP |
| authorships[1].institutions[0].display_name | Aoyama Gakuin University |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Yuri Hamada |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Aoyama Gakuin University |
| authorships[2].author.id | https://openalex.org/A5090187549 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-4592-0807 |
| authorships[2].author.display_name | Yosuke Kurihara |
| authorships[2].countries | JP |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I131231118 |
| authorships[2].affiliations[0].raw_affiliation_string | Aoyama Gakuin University |
| authorships[2].institutions[0].id | https://openalex.org/I131231118 |
| authorships[2].institutions[0].ror | https://ror.org/002rw7y37 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I131231118 |
| authorships[2].institutions[0].country_code | JP |
| authorships[2].institutions[0].display_name | Aoyama Gakuin University |
| authorships[2].author_position | last |
| authorships[2].raw_author_name | Yosuke Kurihara |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Aoyama Gakuin University |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www2.ia-engineers.org/conference/index.php/iciae/iciae2023/paper/download/2744/1797 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Using Granger Causal Test Associated with Trait Anxiety to Estimate STAI Scores by Constructing a Brain Activity Interdependence Network |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10241 |
| primary_topic.field.id | https://openalex.org/fields/28 |
| primary_topic.field.display_name | Neuroscience |
| primary_topic.score | 0.9966999888420105 |
| primary_topic.domain.id | https://openalex.org/domains/1 |
| primary_topic.domain.display_name | Life Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2805 |
| primary_topic.subfield.display_name | Cognitive Neuroscience |
| primary_topic.display_name | Functional Brain Connectivity Studies |
| related_works | https://openalex.org/W2068027638, https://openalex.org/W3155296579, https://openalex.org/W2360771067, https://openalex.org/W2197749859, https://openalex.org/W2784892907, https://openalex.org/W1970646221, https://openalex.org/W1851436302, https://openalex.org/W2355836845, https://openalex.org/W2187885877, https://openalex.org/W3004997939 |
| cited_by_count | 1 |
| counts_by_year[0].year | 2024 |
| counts_by_year[0].cited_by_count | 1 |
| locations_count | 1 |
| best_oa_location.id | doi:10.12792/iciae2023.042 |
| best_oa_location.is_oa | True |
| best_oa_location.source | |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://www2.ia-engineers.org/conference/index.php/iciae/iciae2023/paper/download/2744/1797 |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | proceedings-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | The Proceedings of The 11th IIAE International Conference on Industrial Application Engineering 2023 |
| best_oa_location.landing_page_url | https://doi.org/10.12792/iciae2023.042 |
| primary_location.id | doi:10.12792/iciae2023.042 |
| primary_location.is_oa | True |
| primary_location.source | |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www2.ia-engineers.org/conference/index.php/iciae/iciae2023/paper/download/2744/1797 |
| primary_location.version | publishedVersion |
| primary_location.raw_type | proceedings-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | The Proceedings of The 11th IIAE International Conference on Industrial Application Engineering 2023 |
| primary_location.landing_page_url | https://doi.org/10.12792/iciae2023.042 |
| publication_date | 2023-01-01 |
| publication_year | 2023 |
| referenced_works_count | 0 |
| abstract_inverted_index.a | 51, 70, 115, 142, 185 |
| abstract_inverted_index.17 | 161 |
| abstract_inverted_index.In | 0, 78, 145 |
| abstract_inverted_index.an | 11, 191 |
| abstract_inverted_index.as | 104, 114, 141 |
| abstract_inverted_index.by | 124 |
| abstract_inverted_index.in | 160, 166, 180, 184 |
| abstract_inverted_index.is | 32, 50 |
| abstract_inverted_index.of | 14, 34, 95, 101, 120, 130, 188, 193 |
| abstract_inverted_index.on | 75 |
| abstract_inverted_index.to | 64, 90, 174 |
| abstract_inverted_index.we | 149 |
| abstract_inverted_index.3.0 | 194 |
| abstract_inverted_index.50% | 13 |
| abstract_inverted_index.The | 21, 106 |
| abstract_inverted_index.and | 10, 29, 44, 98, 127, 163, 190 |
| abstract_inverted_index.for | 40, 86 |
| abstract_inverted_index.has | 61 |
| abstract_inverted_index.one | 33 |
| abstract_inverted_index.the | 35, 48, 57, 66, 79, 92, 96, 102, 118, 128, 137, 146, 176, 181 |
| abstract_inverted_index.was | 84, 112, 139, 172 |
| abstract_inverted_index.– | 132 |
| abstract_inverted_index.0.95 | 189 |
| abstract_inverted_index.20s. | 168 |
| abstract_inverted_index.BAIN | 138 |
| abstract_inverted_index.NIRS | 156 |
| abstract_inverted_index.RMSE | 192 |
| abstract_inverted_index.STAI | 49 |
| abstract_inverted_index.been | 8, 62 |
| abstract_inverted_index.flow | 89, 154 |
| abstract_inverted_index.from | 18, 136 |
| abstract_inverted_index.have | 7 |
| abstract_inverted_index.high | 196 |
| abstract_inverted_index.male | 162 |
| abstract_inverted_index.many | 3 |
| abstract_inverted_index.most | 36 |
| abstract_inverted_index.used | 38, 85, 140, 173 |
| abstract_inverted_index.with | 195 |
| abstract_inverted_index.Lasso | 169 |
| abstract_inverted_index.STAI, | 182 |
| abstract_inverted_index.based | 74 |
| abstract_inverted_index.blood | 88, 153 |
| abstract_inverted_index.brain | 76, 103, 107, 121 |
| abstract_inverted_index.could | 55 |
| abstract_inverted_index.score | 179 |
| abstract_inverted_index.state | 30, 67 |
| abstract_inverted_index.test, | 53 |
| abstract_inverted_index.their | 167 |
| abstract_inverted_index.trait | 28, 125 |
| abstract_inverted_index.using | 155 |
| abstract_inverted_index.which | 26 |
| abstract_inverted_index.(BAIN) | 111 |
| abstract_inverted_index.amount | 129 |
| abstract_inverted_index.enable | 91 |
| abstract_inverted_index.female | 164 |
| abstract_inverted_index.health | 5 |
| abstract_inverted_index.index, | 73 |
| abstract_inverted_index.mental | 19, 41 |
| abstract_inverted_index.recent | 1 |
| abstract_inverted_index.score, | 69 |
| abstract_inverted_index.stress | 71 |
| abstract_inverted_index.value. | 144 |
| abstract_inverted_index.widely | 37 |
| abstract_inverted_index.years, | 2 |
| abstract_inverted_index.(STAI), | 25 |
| abstract_inverted_index.Anxiety | 23 |
| abstract_inverted_index.Granger | 82 |
| abstract_inverted_index.Kalbach | 131 |
| abstract_inverted_index.Leibler | 133 |
| abstract_inverted_index.anxiety | 68, 178 |
| abstract_inverted_index.because | 47 |
| abstract_inverted_index.complex | 97 |
| abstract_inverted_index.diverse | 99 |
| abstract_inverted_index.feature | 143 |
| abstract_inverted_index.health, | 42 |
| abstract_inverted_index.method, | 81 |
| abstract_inverted_index.network | 110, 116 |
| abstract_inverted_index.optical | 158 |
| abstract_inverted_index.suicide | 15 |
| abstract_inverted_index.victims | 16 |
| abstract_inverted_index.However, | 46 |
| abstract_inverted_index.activity | 108, 122 |
| abstract_inverted_index.affected | 123 |
| abstract_inverted_index.analysis | 171 |
| abstract_inverted_index.answers. | 58 |
| abstract_inverted_index.anxiety, | 126 |
| abstract_inverted_index.cerebral | 87, 152 |
| abstract_inverted_index.estimate | 65, 175 |
| abstract_inverted_index.measured | 150 |
| abstract_inverted_index.measures | 27 |
| abstract_inverted_index.obtained | 135 |
| abstract_inverted_index.problems | 6 |
| abstract_inverted_index.proposed | 80 |
| abstract_inverted_index.research | 60 |
| abstract_inverted_index.subjects | 165 |
| abstract_inverted_index.suffered | 17 |
| abstract_inverted_index.wearable | 157 |
| abstract_inverted_index.Inventory | 24 |
| abstract_inverted_index.accuracy. | 197 |
| abstract_inverted_index.activity. | 77 |
| abstract_inverted_index.behaviors | 100 |
| abstract_inverted_index.causality | 83 |
| abstract_inverted_index.conducted | 63 |
| abstract_inverted_index.estimated | 12 |
| abstract_inverted_index.examinees | 54 |
| abstract_inverted_index.numerical | 93 |
| abstract_inverted_index.reported, | 9 |
| abstract_inverted_index.research. | 45 |
| abstract_inverted_index.resulting | 183 |
| abstract_inverted_index.Therefore, | 59 |
| abstract_inverted_index.anxieties, | 31 |
| abstract_inverted_index.disorders. | 20 |
| abstract_inverted_index.evaluation | 72 |
| abstract_inverted_index.manipulate | 56 |
| abstract_inverted_index.regression | 170 |
| abstract_inverted_index.topography | 159 |
| abstract_inverted_index.validation | 147 |
| abstract_inverted_index.State-Trait | 22 |
| abstract_inverted_index.coefficient | 187 |
| abstract_inverted_index.constructed | 113 |
| abstract_inverted_index.correlation | 186 |
| abstract_inverted_index.counseling, | 43 |
| abstract_inverted_index.experiment, | 148 |
| abstract_inverted_index.divergenceon | 134 |
| abstract_inverted_index.representing | 117 |
| abstract_inverted_index.dependencies. | 105 |
| abstract_inverted_index.resting-state | 151 |
| abstract_inverted_index.characteristic | 177 |
| abstract_inverted_index.questionnaires | 39 |
| abstract_inverted_index.representation | 94 |
| abstract_inverted_index.stress-related | 4 |
| abstract_inverted_index.characteristics | 119 |
| abstract_inverted_index.interdependence | 109 |
| abstract_inverted_index.questionnaire-based | 52 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 90 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.5299999713897705 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.47278149 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |