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Gepubliceerd in: Quality of Life Research 3/2016

01-03-2016 | Special Section: PROs in Non-Standard Settings (by invitation only)

Symptom clusters in women with breast cancer: an analysis of data from social media and a research study

Auteurs: Sarah A. Marshall, Christopher C. Yang, Qing Ping, Mengnan Zhao, Nancy E. Avis, Edward H. Ip

Gepubliceerd in: Quality of Life Research | Uitgave 3/2016

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Abstract

Purpose

User-generated content on social media sites, such as health-related online forums, offers researchers a tantalizing amount of information, but concerns regarding scientific application of such data remain. This paper compares and contrasts symptom cluster patterns derived from messages on a breast cancer forum with those from a symptom checklist completed by breast cancer survivors participating in a research study.

Methods

Over 50,000 messages generated by 12,991 users of the breast cancer forum on MedHelp.org were transformed into a standard form and examined for the co-occurrence of 25 symptoms. The k-medoid clustering method was used to determine appropriate placement of symptoms within clusters. Findings were compared with a similar analysis of a symptom checklist administered to 653 breast cancer survivors participating in a research study.

Results

The following clusters were identified using forum data: menopausal/psychological, pain/fatigue, gastrointestinal, and miscellaneous. Study data generated the clusters: menopausal, pain, fatigue/sleep/gastrointestinal, psychological, and increased weight/appetite. Although the clusters are somewhat different, many symptoms that clustered together in the social media analysis remained together in the analysis of the study participants. Density of connections between symptoms, as reflected by rates of co-occurrence and similarity, was higher in the study data.

Conclusions

The copious amount of data generated by social media outlets can augment findings from traditional data sources. When different sources of information are combined, areas of overlap and discrepancy can be detected, perhaps giving researchers a more accurate picture of reality. However, data derived from social media must be used carefully and with understanding of its limitations.
Literatuur
1.
go back to reference Grajales, F. J., III, Sheps, S., Ho, K., Novak-Lauscher, H., & Eysenbach, G. (2014). Social media: A review and tutorial of applications in medicine and health care. Journal of Medical Internet Research, 11(16), e13. CrossRef Grajales, F. J., III, Sheps, S., Ho, K., Novak-Lauscher, H., & Eysenbach, G. (2014). Social media: A review and tutorial of applications in medicine and health care. Journal of Medical Internet Research, 11(16), e13. CrossRef
2.
go back to reference Young, S. D. (2014). Behavioral insights on big data: Using social media for predicting biomedical outcomes. Trends in Microbiology, 22(11), 601–602. PubMedCentralCrossRefPubMed Young, S. D. (2014). Behavioral insights on big data: Using social media for predicting biomedical outcomes. Trends in Microbiology, 22(11), 601–602. PubMedCentralCrossRefPubMed
5.
go back to reference Chaung, K. Y., & Yang, C. C. (2012). Interaction patterns of nurturant support exchanged in online health social networking. Journal of Medical Internet Research, 14(3), e54. CrossRef Chaung, K. Y., & Yang, C. C. (2012). Interaction patterns of nurturant support exchanged in online health social networking. Journal of Medical Internet Research, 14(3), e54. CrossRef
6.
go back to reference Capurro, D., Cole, K., Echavarria, M. I., Joe, J., Neogi, T., & Turner, A. M. (2014). The use of social networking sites for public health practice and research: A systematic review. Journal of Medical Internet Research, 16(3), e79. PubMedCentralCrossRefPubMed Capurro, D., Cole, K., Echavarria, M. I., Joe, J., Neogi, T., & Turner, A. M. (2014). The use of social networking sites for public health practice and research: A systematic review. Journal of Medical Internet Research, 16(3), e79. PubMedCentralCrossRefPubMed
7.
go back to reference Corley, C. D., Cook, D. J., Mikler, A. R., & Singh, K. P. (2010). Using web and social media for influenza surveillance. Advances in Experimental Medicine and Biology, 680, 559–564. CrossRefPubMed Corley, C. D., Cook, D. J., Mikler, A. R., & Singh, K. P. (2010). Using web and social media for influenza surveillance. Advances in Experimental Medicine and Biology, 680, 559–564. CrossRefPubMed
8.
go back to reference Kuehn, B. M. (2014). Agencies use social media to track foodborne illness. Journal of the American Medical Association, 312(2), 117–118. CrossRefPubMed Kuehn, B. M. (2014). Agencies use social media to track foodborne illness. Journal of the American Medical Association, 312(2), 117–118. CrossRefPubMed
9.
go back to reference Liu, M., Hu, Y., & Tang, B. (2014). Role of text mining in early identification of potential drug safety issues. Methods in Molecular Biology, 1159, 227–251. CrossRefPubMed Liu, M., Hu, Y., & Tang, B. (2014). Role of text mining in early identification of potential drug safety issues. Methods in Molecular Biology, 1159, 227–251. CrossRefPubMed
10.
go back to reference Vaughan Sarrazin, M. S., Cram, P., Mazur, A., Ward, M., & Reisinger, H. S. (2014). Patient perspectives of dabigatran: Analysis of online discussion forums. Patient, 7(1), 47–54. CrossRefPubMed Vaughan Sarrazin, M. S., Cram, P., Mazur, A., Ward, M., & Reisinger, H. S. (2014). Patient perspectives of dabigatran: Analysis of online discussion forums. Patient, 7(1), 47–54. CrossRefPubMed
11.
go back to reference Abou Taam, M., Rossard, C., Cantaloube, L., Bouscaren, N., Roche, G., Pochard, L., et al. (2014). Analysis of patients’ narratives posted on social media websites on benfluorex’s (mediator) withdrawal in France. Journal of Clinical Pharmacy and Therapeutics, 39(1), 53–55. CrossRefPubMed Abou Taam, M., Rossard, C., Cantaloube, L., Bouscaren, N., Roche, G., Pochard, L., et al. (2014). Analysis of patients’ narratives posted on social media websites on benfluorex’s (mediator) withdrawal in France. Journal of Clinical Pharmacy and Therapeutics, 39(1), 53–55. CrossRefPubMed
12.
go back to reference Alshaikh, F., Ramzan, F., Rawaf, S., & Majeed, A. (2014). Social network sites as a mode to collect health data: A systematic review. Journal of Medical Internet Research, 16(7), e171. PubMedCentralCrossRefPubMed Alshaikh, F., Ramzan, F., Rawaf, S., & Majeed, A. (2014). Social network sites as a mode to collect health data: A systematic review. Journal of Medical Internet Research, 16(7), e171. PubMedCentralCrossRefPubMed
13.
go back to reference Karmen, C., Hsiung, R. C., & Wetter, T. (2015). Screening internet forum participants for depression symptoms by assembling and enhancing multiple NLP methods. Computer Methods and Programs in Biomedicine, 120(1), 27–36. CrossRefPubMed Karmen, C., Hsiung, R. C., & Wetter, T. (2015). Screening internet forum participants for depression symptoms by assembling and enhancing multiple NLP methods. Computer Methods and Programs in Biomedicine, 120(1), 27–36. CrossRefPubMed
14.
go back to reference Lloyd, A. (2014). Social media, help or hindrance: What role does social media play in young people’s mental health? Psychiatria Danubia, 26(1), 340–346. Lloyd, A. (2014). Social media, help or hindrance: What role does social media play in young people’s mental health? Psychiatria Danubia, 26(1), 340–346.
15.
go back to reference Leng, H. K. (2013). Methodological issues in using data from social networking sites. Cyberpsychology, Behavior, and Social Networking, 16(9), 686–689. CrossRef Leng, H. K. (2013). Methodological issues in using data from social networking sites. Cyberpsychology, Behavior, and Social Networking, 16(9), 686–689. CrossRef
16.
go back to reference Bainbridge, W. S. (2007). The scientific research potential of virtual worlds. Science, 317(5837), 472–476. CrossRefPubMed Bainbridge, W. S. (2007). The scientific research potential of virtual worlds. Science, 317(5837), 472–476. CrossRefPubMed
18.
go back to reference Park, K., Harris, M., Khavari, N., & Khosla, C. (2014). Rationale for using social media to collect patient-reported outcomes in patients with celiac disease. Journal of Gastrointestinal and Digestive System, 4(1), 166. PubMedCentralPubMed Park, K., Harris, M., Khavari, N., & Khosla, C. (2014). Rationale for using social media to collect patient-reported outcomes in patients with celiac disease. Journal of Gastrointestinal and Digestive System, 4(1), 166. PubMedCentralPubMed
19.
go back to reference Harpaz, R., Callahan, A., Tamang, S., Low, Y., Odgers, D., Finlayson, S., et al. (2014). Text mining for adverse drug events: The promise, challenges, and state of the art. Drug Safety, 37(10), 777–790. PubMedCentralCrossRefPubMed Harpaz, R., Callahan, A., Tamang, S., Low, Y., Odgers, D., Finlayson, S., et al. (2014). Text mining for adverse drug events: The promise, challenges, and state of the art. Drug Safety, 37(10), 777–790. PubMedCentralCrossRefPubMed
20.
go back to reference Peek, N., Holmes, J. H., & Sun, J. (2014). Technical challenges for big data in biomedicine and health: Data sources, infrastructure, and analytics. Yearbook of Medical Informatics, 9(1), 42–47. PubMedCentralCrossRefPubMed Peek, N., Holmes, J. H., & Sun, J. (2014). Technical challenges for big data in biomedicine and health: Data sources, infrastructure, and analytics. Yearbook of Medical Informatics, 9(1), 42–47. PubMedCentralCrossRefPubMed
22.
go back to reference Cavallo, D. N., Chou, W. Y., McQueen, A., Ramirez, A., & Riley, W. T. (2014). Cancer prevention and control interventions using social media: User-generated approaches. Cancer Epidemiology, Biomarkers and Prevention, 23(9), 1953–1956. PubMedCentralCrossRefPubMed Cavallo, D. N., Chou, W. Y., McQueen, A., Ramirez, A., & Riley, W. T. (2014). Cancer prevention and control interventions using social media: User-generated approaches. Cancer Epidemiology, Biomarkers and Prevention, 23(9), 1953–1956. PubMedCentralCrossRefPubMed
23.
go back to reference Taurob, S., Tucker, C. S., Salathe, M., & Ram, N. (2014). An ensemble heterogeneous classification methodology for discovering health-related knowledge in social media messages. Journal of Biomedical Informatics, 49, 255–268. CrossRef Taurob, S., Tucker, C. S., Salathe, M., & Ram, N. (2014). An ensemble heterogeneous classification methodology for discovering health-related knowledge in social media messages. Journal of Biomedical Informatics, 49, 255–268. CrossRef
24.
go back to reference Gustafson, D. L., & Woodworth, C. F. (2014). Methodological and ethical issues in research using social media: A metamethod of Human Papillomavirus vaccine studies. BMC Medical Research Methodology, 14, 127. PubMedCentralCrossRefPubMed Gustafson, D. L., & Woodworth, C. F. (2014). Methodological and ethical issues in research using social media: A metamethod of Human Papillomavirus vaccine studies. BMC Medical Research Methodology, 14, 127. PubMedCentralCrossRefPubMed
25.
go back to reference Chang, V. T., Hwang, S. S., Feuerman, M., & Kasimis, B. S. (2000). Symptom and quality of life survey of medical oncology patients at a veterans affairs medical center: A role for symptom assessment. Cancer, 88(5), 1175–1183. CrossRefPubMed Chang, V. T., Hwang, S. S., Feuerman, M., & Kasimis, B. S. (2000). Symptom and quality of life survey of medical oncology patients at a veterans affairs medical center: A role for symptom assessment. Cancer, 88(5), 1175–1183. CrossRefPubMed
26.
go back to reference Deshields, T. L., Potter, P., Olsen, S., & Liu, J. (2014). The persistence of symptom burden: Symptom experience and quality of life of cancer patients across one year. Supportive Care in Cancer, 22(4), 1089–1096. CrossRefPubMed Deshields, T. L., Potter, P., Olsen, S., & Liu, J. (2014). The persistence of symptom burden: Symptom experience and quality of life of cancer patients across one year. Supportive Care in Cancer, 22(4), 1089–1096. CrossRefPubMed
27.
go back to reference Naughton, M. J., & Weaver, K. E. (2014). Physical and mental health among cancer survivors: Considerations for long-term care and quality of life. North Carolina Medical Journal, 75(4), 283–286. PubMedCentralCrossRefPubMed Naughton, M. J., & Weaver, K. E. (2014). Physical and mental health among cancer survivors: Considerations for long-term care and quality of life. North Carolina Medical Journal, 75(4), 283–286. PubMedCentralCrossRefPubMed
28.
go back to reference Deshields, T. L., Potter, P., Olsen, S., Liu, J., & Dye, L. (2011). Documenting the symptom experience of cancer patients. The Journal of Supportive Oncology, 9(6), 216–223. CrossRefPubMed Deshields, T. L., Potter, P., Olsen, S., Liu, J., & Dye, L. (2011). Documenting the symptom experience of cancer patients. The Journal of Supportive Oncology, 9(6), 216–223. CrossRefPubMed
29.
go back to reference Portenoy, R. K., Thaler, H. T., Kornblith, A. B., Lepore, J. M., Friedlander-Klar, H., Coyle, N., et al. (1994). Symptom prevalence, characteristics and distress in a cancer population. Quality of Life Research, 3(3), 183–189. CrossRefPubMed Portenoy, R. K., Thaler, H. T., Kornblith, A. B., Lepore, J. M., Friedlander-Klar, H., Coyle, N., et al. (1994). Symptom prevalence, characteristics and distress in a cancer population. Quality of Life Research, 3(3), 183–189. CrossRefPubMed
30.
go back to reference Dodd, M. J., Miaskowski, C., & Paul, S. M. (2001). Symptom clusters and their effect on the functional status of patients with cancer. Oncology Nursing Forum, 28(3), 465–470. PubMed Dodd, M. J., Miaskowski, C., & Paul, S. M. (2001). Symptom clusters and their effect on the functional status of patients with cancer. Oncology Nursing Forum, 28(3), 465–470. PubMed
31.
go back to reference Kim, H. J., McGuire, D. B., Tulman, L., & Barsevick, A. M. (2005). Symptom clusters: Concept analysis and clinical implications for cancer nursing. Cancer Nursing, 28(4), 270–282. CrossRefPubMed Kim, H. J., McGuire, D. B., Tulman, L., & Barsevick, A. M. (2005). Symptom clusters: Concept analysis and clinical implications for cancer nursing. Cancer Nursing, 28(4), 270–282. CrossRefPubMed
32.
33.
go back to reference Kirkova, J., Aktas, A., Walsh, D., & Davis, M. P. (2011). Cancer symptoms clusters: Clinical and research methodology. Journal of Palliative Medicine, 14(10), 1149–1166. CrossRefPubMed Kirkova, J., Aktas, A., Walsh, D., & Davis, M. P. (2011). Cancer symptoms clusters: Clinical and research methodology. Journal of Palliative Medicine, 14(10), 1149–1166. CrossRefPubMed
34.
go back to reference Xiao, C. (2010). The state of science in the study of cancer symptom clusters. European Journal of Oncology Nursing, 14(5), 417–434. CrossRefPubMed Xiao, C. (2010). The state of science in the study of cancer symptom clusters. European Journal of Oncology Nursing, 14(5), 417–434. CrossRefPubMed
35.
go back to reference Denieffe, S., Cowman, S., & Gooney, M. (2014). Symptoms, clusters, and quality of life prior to surgery for breast cancer. Journal of Clinical Nursing, 23(17–18), 2491–2502. CrossRefPubMed Denieffe, S., Cowman, S., & Gooney, M. (2014). Symptoms, clusters, and quality of life prior to surgery for breast cancer. Journal of Clinical Nursing, 23(17–18), 2491–2502. CrossRefPubMed
36.
go back to reference Walsh, D., & Rybicki, L. (2006). Symptom clustering in advanced cancer. Supportive Care in Cancer, 14(8), 831–836. CrossRefPubMed Walsh, D., & Rybicki, L. (2006). Symptom clustering in advanced cancer. Supportive Care in Cancer, 14(8), 831–836. CrossRefPubMed
37.
go back to reference Fan, G., Hadi, S., & Chow, E. (2007). Symptom clusters in patients with advanced-stage cancer referred for palliative radiation therapy in an outpatient setting. Supportive Cancer Therapy, 4(3), 157–162. CrossRefPubMed Fan, G., Hadi, S., & Chow, E. (2007). Symptom clusters in patients with advanced-stage cancer referred for palliative radiation therapy in an outpatient setting. Supportive Cancer Therapy, 4(3), 157–162. CrossRefPubMed
38.
go back to reference Tsai, J. S., Wu, C. H., Chiu, T. Y., & Chen, C. Y. (2010). Significance of symptom clustering in palliative care of advanced cancer patients. Journal of Pain and Symptom Management, 39(4), 655–662. CrossRefPubMed Tsai, J. S., Wu, C. H., Chiu, T. Y., & Chen, C. Y. (2010). Significance of symptom clustering in palliative care of advanced cancer patients. Journal of Pain and Symptom Management, 39(4), 655–662. CrossRefPubMed
39.
go back to reference Gleason, J. F., Case, D., Rapp, S. R., Ip, E., Naughton, M., Butler, J. M., et al. (2007). Symptom clusters in patients with newly-diagnosed brain tumors. Journal of Supportive Oncology, 5(9), 427–433. PubMed Gleason, J. F., Case, D., Rapp, S. R., Ip, E., Naughton, M., Butler, J. M., et al. (2007). Symptom clusters in patients with newly-diagnosed brain tumors. Journal of Supportive Oncology, 5(9), 427–433. PubMed
40.
go back to reference Broeckel, J. A., Jacobsen, P. B., Horton, J., Balducci, L., & Lyman, G. H. (1998). Characteristics and correlates of fatigue after adjuvant chemotherapy for breast cancer. Journal of Clinical Oncology, 16(5), 1689–1696. PubMed Broeckel, J. A., Jacobsen, P. B., Horton, J., Balducci, L., & Lyman, G. H. (1998). Characteristics and correlates of fatigue after adjuvant chemotherapy for breast cancer. Journal of Clinical Oncology, 16(5), 1689–1696. PubMed
41.
go back to reference Berger, A. M., & Farr, L. (1999). The influence of daytime inactivity and nighttime restlessness on cancer-related fatigue. Oncology Nursing Forum, 26(10), 1663–1671. PubMed Berger, A. M., & Farr, L. (1999). The influence of daytime inactivity and nighttime restlessness on cancer-related fatigue. Oncology Nursing Forum, 26(10), 1663–1671. PubMed
42.
go back to reference Byar, K. L., Berger, A. M., Bakken, S. L., & Cetak, M. A. (2006). Impact of adjuvant breast cancer chemotherapy on fatigue, other symptoms, and quality of life. Oncology Nursing Forum, 33(1), E18–E26. CrossRefPubMed Byar, K. L., Berger, A. M., Bakken, S. L., & Cetak, M. A. (2006). Impact of adjuvant breast cancer chemotherapy on fatigue, other symptoms, and quality of life. Oncology Nursing Forum, 33(1), E18–E26. CrossRefPubMed
43.
go back to reference Gaston-Johansson, F., Fall-Dickson, J. M., Bakos, A. B., & Kennedy, M. J. (1999). Fatigue, pain, and depression in pre-autotransplant breast cancer patients. Cancer Practice, 7(5), 240–247. CrossRefPubMed Gaston-Johansson, F., Fall-Dickson, J. M., Bakos, A. B., & Kennedy, M. J. (1999). Fatigue, pain, and depression in pre-autotransplant breast cancer patients. Cancer Practice, 7(5), 240–247. CrossRefPubMed
44.
go back to reference Ho, S. Y., Rohan, K. J., Parent, J., Tager, F. A., & McKinley, P. S. (2015). A longitudinal study of depression, fatigue, and sleep disturbances as a symptom cluster in women with breast cancer. Journal of Pain and Symptom Management, 49(4), 707–715. CrossRefPubMed Ho, S. Y., Rohan, K. J., Parent, J., Tager, F. A., & McKinley, P. S. (2015). A longitudinal study of depression, fatigue, and sleep disturbances as a symptom cluster in women with breast cancer. Journal of Pain and Symptom Management, 49(4), 707–715. CrossRefPubMed
45.
go back to reference Bender, C. M., Ergyn, F. S., Rosenzweig, M. Q., Cohen, S. M., & Sereika, S. M. (2005). Symptom clusters in breast cancer across 3 phases of the disease. Cancer Nursing, 28(3), 219–225. CrossRefPubMed Bender, C. M., Ergyn, F. S., Rosenzweig, M. Q., Cohen, S. M., & Sereika, S. M. (2005). Symptom clusters in breast cancer across 3 phases of the disease. Cancer Nursing, 28(3), 219–225. CrossRefPubMed
46.
go back to reference Glaus, A., Boehme, C., Thurlimann, B., Ruhstaller, T., Hsu Schmitz, S. F., Morant, R., et al. (2006). Fatigue and menopausal symptoms in women with breast cancer undergoing hormonal cancer treatment. Annals of Oncology, 17(5), 801–806. CrossRefPubMed Glaus, A., Boehme, C., Thurlimann, B., Ruhstaller, T., Hsu Schmitz, S. F., Morant, R., et al. (2006). Fatigue and menopausal symptoms in women with breast cancer undergoing hormonal cancer treatment. Annals of Oncology, 17(5), 801–806. CrossRefPubMed
47.
go back to reference Kim, H. J., Barsevick, A. M., Tulman, L., & McDermott, P. A. (2008). Treatment-related symptom clusters in breast cancer: A secondary analysis. Journal of Pain and Symptom Management, 36(5), 468–479. CrossRefPubMed Kim, H. J., Barsevick, A. M., Tulman, L., & McDermott, P. A. (2008). Treatment-related symptom clusters in breast cancer: A secondary analysis. Journal of Pain and Symptom Management, 36(5), 468–479. CrossRefPubMed
48.
go back to reference Fu, O. S., Crew, K. D., Jacobson, J. S., Greenlee, H., Yu, G., Campbell, J., et al. (2009). Ethnicity and persistent symptom burden in breast cancer survivors. Journal of Cancer Survivorship, 3(4), 241–250. CrossRefPubMed Fu, O. S., Crew, K. D., Jacobson, J. S., Greenlee, H., Yu, G., Campbell, J., et al. (2009). Ethnicity and persistent symptom burden in breast cancer survivors. Journal of Cancer Survivorship, 3(4), 241–250. CrossRefPubMed
49.
go back to reference Avis, N., Levine, B., Naughton, M., Case, L. D., Naftalis, E., & Van Zee, K. J. (2013). Age related longitudinal changes in depressive symptoms following breast cancer diagnosis and treatment. Breast Cancer Research and Treatment, 139(10), 199–206. CrossRefPubMed Avis, N., Levine, B., Naughton, M., Case, L. D., Naftalis, E., & Van Zee, K. J. (2013). Age related longitudinal changes in depressive symptoms following breast cancer diagnosis and treatment. Breast Cancer Research and Treatment, 139(10), 199–206. CrossRefPubMed
50.
go back to reference Barnabei, V. M., Cochrane, B. B., Aragaki, A. K., et al. (2005). Menopausal symptoms and treatment-related effects of estrogen and progestin in the women’s health initiative. Obstetrics and Gynecology, 105, 1063–1073. CrossRefPubMed Barnabei, V. M., Cochrane, B. B., Aragaki, A. K., et al. (2005). Menopausal symptoms and treatment-related effects of estrogen and progestin in the women’s health initiative. Obstetrics and Gynecology, 105, 1063–1073. CrossRefPubMed
51.
go back to reference Zeng, Q. T., & Tse, T. (2006). Exploring and developing consumer health vocabularies. Journal of the American Medical Informatics Association, 13(1), 24–29. PubMedCentralCrossRefPubMed Zeng, Q. T., & Tse, T. (2006). Exploring and developing consumer health vocabularies. Journal of the American Medical Informatics Association, 13(1), 24–29. PubMedCentralCrossRefPubMed
52.
go back to reference Jiang, L., Yang, C. C. (2013). Using co-occurrence analysis to expand consumer health vocabularies from social media data. In Proceedings of IEEE international conference on healthcare informatics, pp 74–81. Jiang, L., Yang, C. C. (2013). Using co-occurrence analysis to expand consumer health vocabularies from social media data. In Proceedings of IEEE international conference on healthcare informatics, pp 74–81.
53.
go back to reference Kaufman, L., & Rousseeuw, P. J. (1987). Clustering by means of medoids. In Y. Dodge (Ed.), Statistical data analysis based on the L1-norm and related methods (pp. 405–416). Birkhauser: North-Holland. Kaufman, L., & Rousseeuw, P. J. (1987). Clustering by means of medoids. In Y. Dodge (Ed.), Statistical data analysis based on the L1-norm and related methods (pp. 405–416). Birkhauser: North-Holland.
Metagegevens
Titel
Symptom clusters in women with breast cancer: an analysis of data from social media and a research study
Auteurs
Sarah A. Marshall
Christopher C. Yang
Qing Ping
Mengnan Zhao
Nancy E. Avis
Edward H. Ip
Publicatiedatum
01-03-2016
Uitgeverij
Springer International Publishing
Gepubliceerd in
Quality of Life Research / Uitgave 3/2016
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-015-1156-7

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