Developing and Testing an Integrated mHealth Learning Program for Gynecological Cancer

The purpose of this project is to develop and test an integrated mHealth learning program (L-mHealth program) for gynecological cancer that integrates effective educational strategies and mobile health application to meet the learning needs of Taiwanese Women with Gynecological Cancer (WGC) through the process of co-creation, with the active input of WGC and experts' directly impacting content and design. This project was to develop the L-mHealth system and prototype of a smartphone app for WGC through the process of co-creation, with the active input of WGC and experts' directly impacting content and design.

Study Overview

• Status: Completed
• Conditions: Mobile Health
• Intervention / Treatment: Other: L-mHealth program

Detailed Description

The second year research purpose is to establish the L-mHealth program's framework, which according to the needs assessment and health education strategies of the first year. The L-mHealth system will be then developed according to the course framework use TTM theory and self-efficacy theory as the basis. A single-blinded, randomized controlled parallel-group clinical trial with repeated- measures research will be conducted in the third year. A total of 120 ovarian cancer women will be recruited from a medical center in northern Taiwan and then assigned to one of two groups (the experiment and control groups) by stratified randomization. Women were randomized either to the intervention group (n=60) receiving the L-mHealth program plus care as usual or the control group (n=60) receiving care as usual alone. Data will be collected at baseline (T0), 1 months (T1) and 3 months (T2) after the intervention. Co-creation is a user-involved process that can create a useful and customized product for the WGC target population. As such, this process is a beneficial process to tilize when addressing the specific needs of WGC. Through the study of the L-mHealth program, it is expected to improve women's use of ICT and demonstrate its potential as an effective and easily accessible intervention to promote women's symptom interference and quality of life for WGC.

• Study Type: Interventional
• Enrollment (Actual): 67
• Phase: Not Applicable

Contacts and Locations

Study Locations

• Taiwan
  • Guishan Dist.
    • Taoyuan District, Guishan Dist., Taiwan, 333
      • Cheng Gung Memorial Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

1. Women definitively or suspected to be diagnosed with ovarian cancer, with the cancer staged at Stage 3 or below.
2. Women receiving surgery, chemotherapy, or immunotherapy at the recruiting hospital.

3.20 to 70 years old. 4.Possesses and is able to use an internet-enabled mobile device (such as a smartphone or tablet).

5.Able to clearly communicate and read/write in Mandarin or Taiwanese. 6.Agrees to participate in the study and signs the informed consent form.

Exclusion Criteria:

1. History of other malignant tumors.
2. Intellectual disability or mental disorders.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Other
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Single

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: The intervention group; The intervention group will receive the L-mHealth program along with routine care, which includes the "L-mHealth APP" This app is complemented by an "Online Community Support System" and the "LINE Instant Messaging Software."	Other: L-mHealth program; The intervention group receiving the L-mHealth program plus care as usual. Data will be collected at baseline (T0), 1 months (T1) and 3 months (T2) after the intervention.
No Intervention: The control group; The control group receiving care as usual alone.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Symptom Distress	The research project assessed changes in symptom distress by Symptom Distress Scale-Chinese Modified Form (SDS-CMF) . Symptom Distress Scale-Chinese Modified Form (SDS-CMF), revised by Lai (1998), for the symptom assessment of ovarian cancer patients. The scale is adapted from the Symptom Distress Scale (SDS) developed by McCorkle and Young (1978) for lung cancer patients. The scoring method uses a 5-point Likert scale to assess the level of symptom distress as self-reported by cancer patients. A score of 1 indicates no distress at all, 2 indicates mild distress, 3 indicates moderate distress, 4 indicates severe distress, and 5 indicates very severe distress. The total score ranges from 25 to 125, with higher scores indicating more severe symptom distress. The Cronbach's alpha value for cervical cancer patients in our country was 0.87, and the content validity was 0.92 (Chen et al., 2007).	Data were collected at baseline.
Symptom Distress	The research project assessed changes in symptom distress by Symptom Distress Scale-Chinese Modified Form (SDS-CMF) . Symptom Distress Scale-Chinese Modified Form (SDS-CMF), revised by Lai (1998), for the symptom assessment of ovarian cancer patients. The scale is adapted from the Symptom Distress Scale (SDS) developed by McCorkle and Young (1978) for lung cancer patients. The scoring method uses a 5-point Likert scale to assess the level of symptom distress as self-reported by cancer patients. A score of 1 indicates no distress at all, 2 indicates mild distress, 3 indicates moderate distress, 4 indicates severe distress, and 5 indicates very severe distress. The total score ranges from 25 to 125, with higher scores indicating more severe symptom distress.The Cronbach's alpha value for cervical cancer patients in our country was 0.87, and the content validity was 0.92 (Chen et al., 2007).	Data were collected at 1 months after the Interventions.
Symptom Distress	The research project assessed changes in symptom distress by Symptom Distress Scale-Chinese Modified Form (SDS-CMF). Symptom Distress Scale-Chinese Modified Form (SDS-CMF), revised by Lai (1998), for the symptom assessment of ovarian cancer patients. The scale is adapted from the Symptom Distress Scale (SDS) developed by McCorkle and Young (1978) for lung cancer patients. The scoring method uses a 5-point Likert scale to assess the level of symptom distress as self-reported by cancer patients. A score of 1 indicates no distress at all, 2 indicates mild distress, 3 indicates moderate distress, 4 indicates severe distress, and 5 indicates very severe distress. The total score ranges from 25 to 125, with higher scores indicating more severe symptom distress. The Cronbach's alpha value for cervical cancer patients in our country was 0.87, and the content validity was 0.92 (Chen et al., 2007).	Data were collected at 3 months after the Interventions.
Communication and Attitudinal Self-Efficacy for cancer	The research project assessed changes in communication and attitudinal self-efficacy for cancer by Communication and Attitudinal Self-Efficacy scale for cancer (CASE). The "Communication and Attitudinal Self-Efficacy Scale for Cancer (CASE)," originally designed by Wolf et al. (2005) and translated by Yang (2005). The scale comprises three major dimensions: the ability to understand and participate in care, the ability to maintain a positive attitude, and the ability to seek and obtain information, totaling 12 items. The scoring uses a Likert scale, ranging from strongly disagree (1 point) to strongly agree (5 points). The reliability of the scale, as measured by internal consistency, shows a Cronbach's α value ranging from 0.80 to 0.95 across the different dimensions.	Data were collected at baseline.
Communication and Attitudinal Self-Efficacy for cancer	The research project assessed changes in communication and attitudinal self-efficacy for cancer by Communication and Attitudinal Self-Efficacy scale for cancer (CASE) . The "Communication and Attitudinal Self-Efficacy Scale for Cancer (CASE)," originally designed by Wolf et al. (2005) and translated by Yang (2005). The scale comprises three major dimensions: the ability to understand and participate in care, the ability to maintain a positive attitude, and the ability to seek and obtain information, totaling 12 items. The scoring uses a Likert scale, ranging from strongly disagree (1 point) to strongly agree (5 points). The reliability of the scale, as measured by internal consistency, shows a Cronbach's α value ranging from 0.80 to 0.95 across the different dimensions.	Data were collected at 1 months after the Interventions.
Communication and Attitudinal Self-Efficacy for cancer	The research project assessed changes in communication and attitudinal self-efficacy for cancer by Communication and Attitudinal Self-Efficacy scale for cancer (CASE). The "Communication and Attitudinal Self-Efficacy Scale for Cancer (CASE)," originally designed by Wolf et al. (2005) and translated by Yang (2005). The scale comprises three major dimensions: the ability to understand and participate in care, the ability to maintain a positive attitude, and the ability to seek and obtain information, totaling 12 items. The scoring uses a Likert scale, ranging from strongly disagree (1 point) to strongly agree (5 points). The reliability of the scale, as measured by internal consistency, shows a Cronbach's α value ranging from 0.80 to 0.95 across the different dimensions.	Data were collected at 3 months after the Interventions.
Needs of Health Information for the patients with Gynecological Cancer	The research project assessed changes in needs of health information for the patients with gynecological cancer by Informational Needs Questionnaires- Gynecological Cancer. The study utilizes the Chinese version of Informational Needs Questionnaires- Gynecological Cancer, adapted by Lei, Har, & Abdullah (2011) from the "Toronto Informational Needs Questionnaire-Breast Cancer (TINQ-BC)," and used with the authors' permission (Huang & Hsieh, 2015). The Chinese version for gynecologic cancer patients was modified from 52 to 50 items, with a scoring system ranging from 1 ('Not needed at all') to 5 ('Greatly needed'). Higher scores indicate a greater need for the information in that item. The Cronbach's alpha coefficients for the subscales range from 0.835 to 0.958 (Chen & Hsieh, 2017). The Content Validity Index (CVI) values for expert validity range from 0.75 to 0.94 (Hsieh et al., 2018; Huang & Hsieh, 2015)."	Data were collected at baseline.
Needs of Health Information for the patients with Gynecological Cancer	The research project assessed changes in needs of health information for the patients with gynecological cancer by Informational Needs Questionnaires- Gynecological Cancer . The study utilizes the Chinese version of Informational Needs Questionnaires- Gynecological Cancer, adapted by Lei, Har, & Abdullah (2011) from the "Toronto Informational Needs Questionnaire-Breast Cancer (TINQ-BC)," and used with the authors' permission (Huang & Hsieh, 2015). The Chinese version for gynecologic cancer patients was modified from 52 to 50 items, with a scoring system ranging from 1 ('Not needed at all') to 5 ('Greatly needed'). Higher scores indicate a greater need for the information in that item.The Cronbach's alpha coefficients for the subscales range from 0.835 to 0.958 (Chen & Hsieh, 2017). The Content Validity Index (CVI) values for expert validity range from 0.75 to 0.94 (Hsieh et al., 2018; Huang & Hsieh, 2015)."	Data were collected at 1 months after the Interventions.
Needs of Health Information for the patients with Gynecological Cancer	The research project assessed changes in needs of health information for the patients with gynecological cancer by Informational Needs Questionnaires- Gynecological Cancer. The study utilizes the Chinese version of Informational Needs Questionnaires- Gynecological Cancer, adapted by Lei, Har, & Abdullah (2011) from the "Toronto Informational Needs Questionnaire-Breast Cancer (TINQ-BC)," and used with the authors' permission (Huang & Hsieh, 2015). The Chinese version for gynecologic cancer patients was modified from 52 to 50 items, with a scoring system ranging from 1 ('Not needed at all') to 5 ('Greatly needed'). Higher scores indicate a greater need for the information in that item. The Cronbach's alpha coefficients for the subscales range from 0.835 to 0.958 (Chen & Hsieh, 2017). The Content Validity Index (CVI) values for expert validity range from 0.75 to 0.94 (Hsieh et al., 2018; Huang & Hsieh, 2015)."	Data were collected at 3 months after the Interventions.
Chatbot Usability	The research project assessed changes in chatbot usability by Chatbot Usability Questionnaire (CUQ). The Chatbot Usability Questionnaire (CUQ) was developed by Holmes et al. (2019) based on principles of user experience with chatbots. It is similar in design to the System Usability Scale (SUS) by Brooke (1996) but was specifically developed for assessing chatbot usability. The questionnaire consists of 16 items, with 8 related to positive aspects of chatbot usability and 8 related to negative aspects. It uses a 5-point Likert scale for users to rate the chatbot's usability, where 1 indicates strong disagreement, 2 disagreement, 3 neutrality, 4 agreement, and 5 strong agreement. The scores are standardized on a scale of 100 points.The Chatbot Usability Questionnaire (CUQ) demonstrates good internal consistency (r > 0.7) (Holmes et al., 2023).	Data were collected at baseline.
Chatbot Usability	The research project assessed changes in chatbot usability by Chatbot Usability Questionnaire (CUQ) . The Chatbot Usability Questionnaire (CUQ) was developed by Holmes et al. (2019) based on principles of user experience with chatbots. It is similar in design to the System Usability Scale (SUS) by Brooke (1996) but was specifically developed for assessing chatbot usability. The questionnaire consists of 16 items, with 8 related to positive aspects of chatbot usability and 8 related to negative aspects. It uses a 5-point Likert scale for users to rate the chatbot's usability, where 1 indicates strong disagreement, 2 disagreement, 3 neutrality, 4 agreement, and 5 strong agreement. The scores are standardized on a scale of 100 points. The Chatbot Usability Questionnaire (CUQ) demonstrates good internal consistency (r > 0.7) (Holmes et al., 2023).	Data were collected at 1 months after the Interventions.
Chatbot Usability	The research project assessed changes in chatbot usability by Chatbot Usability Questionnaire (CUQ) from baseline to 3 months after the Interventions. The Chatbot Usability Questionnaire (CUQ) was developed by Holmes et al. (2019) based on principles of user experience with chatbots. It is similar in design to the System Usability Scale (SUS) by Brooke (1996) but was specifically developed for assessing chatbot usability. The questionnaire consists of 16 items, with 8 related to positive aspects of chatbot usability and 8 related to negative aspects. It uses a 5-point Likert scale for users to rate the chatbot's usability, where 1 indicates strong disagreement, 2 disagreement, 3 neutrality, 4 agreement, and 5 strong agreement. The scores are standardized on a scale of 100 points.The Chatbot Usability Questionnaire (CUQ) demonstrates good internal consistency (r > 0.7) (Holmes et al., 2023).	Data were collected at 3 months after the Interventions.
System Usability	The research project assessed changes in system usability by System Usability Scale (SUS) . The System Usability Scale (SUS), originally proposed by Brooke in 1986 (Brooke, 1996). The SUS consists of 10 items, scored using a 5-point Likert scale, with options ranging from strongly agree to strongly disagree. Strongly agree is scored as 5 points, and strongly disagree as 1 point. For positively worded items, the score is calculated by subtracting 1 from the item score, while for negatively worded items, the score is obtained by subtracting the item score from 5. The total SUS score is then calculated by summing the item scores and multiplying by 2.5, yielding a final score that can be categorized into six grades: A (90-100), B (80-89), C (70-79), D (60-69), and F (0-59) according to Bangor, Kortum, and Miller (2009).	Data were collected at baseline.
System Usability	The research project assessed changes in system usability by System Usability Scale (SUS) . The System Usability Scale (SUS), originally proposed by Brooke in 1986 (Brooke, 1996). The SUS consists of 10 items, scored using a 5-point Likert scale, with options ranging from strongly agree to strongly disagree. Strongly agree is scored as 5 points, and strongly disagree as 1 point. For positively worded items, the score is calculated by subtracting 1 from the item score, while for negatively worded items, the score is obtained by subtracting the item score from 5. The total SUS score is then calculated by summing the item scores and multiplying by 2.5, yielding a final score that can be categorized into six grades: A (90-100), B (80-89), C (70-79), D (60-69), and F (0-59) according to Bangor, Kortum, and Miller (2009).	Data were collected at 1 months after the Interventions.
System Usability	The research project assessed changes in system usability by System Usability Scale (SUS) . The System Usability Scale (SUS), originally proposed by Brooke in 1986 (Brooke, 1996). The SUS consists of 10 items, scored using a 5-point Likert scale, with options ranging from strongly agree to strongly disagree. Strongly agree is scored as 5 points, and strongly disagree as 1 point. For positively worded items, the score is calculated by subtracting 1 from the item score, while for negatively worded items, the score is obtained by subtracting the item score from 5. The total SUS score is then calculated by summing the item scores and multiplying by 2.5, yielding a final score that can be categorized into six grades: A (90-100), B (80-89), C (70-79), D (60-69), and F (0-59) according to Bangor, Kortum, and Miller (2009).	Data were collected at 3 months after the Interventions.
mHealth App Usability	The research project assessed changes in mHealth App usability by mHealth App Usability Questionnaire (MAUQ) . This study chose to use the 21-item mHealth App Usability Questionnaire (MAUQ) (Zhou et al., 2009). Strongly agree is scored as 7 points, and strongly disagree as 1 point. The MAUQ has demonstrated good reliability and validity during its development process. In terms of internal consistency, the three subscales-Ease of Use and Satisfaction (MAUQ_E), System Information Arrangement (MAUQ_S), and Usefulness (MAUQ_U)-have Cronbach's α values of 0.895, 0.829, and 0.900, respectively.	Data were collected at baseline.
mHealth App Usability	The research project assessed changes in mHealth App usability by mHealth App Usability Questionnaire (MAUQ). This study chose to use the 21-item mHealth App Usability Questionnaire (MAUQ) (Zhou et al., 2009). Strongly agree is scored as 7 points, and strongly disagree as 1 point. The MAUQ has demonstrated good reliability and validity during its development process. In terms of internal consistency, the three subscales-Ease of Use and Satisfaction (MAUQ_E), System Information Arrangement (MAUQ_S), and Usefulness (MAUQ_U)-have Cronbach's α values of 0.895, 0.829, and 0.900, respectively.	Data were collected at 1 months after the Interventions.
mHealth App Usability	The research project assessed changes in mHealth App usability by mHealth App Usability Questionnaire (MAUQ) from baseline to 3 months after the Interventions. This study chose to use the 21-item mHealth App Usability Questionnaire (MAUQ) (Zhou et al., 2009). Strongly agree is scored as 7 points, and strongly disagree as 1 point. The MAUQ has demonstrated good reliability and validity during its development process. In terms of internal consistency, the three subscales-Ease of Use and Satisfaction (MAUQ_E), System Information Arrangement (MAUQ_S), and Usefulness (MAUQ_U)-have Cronbach's α values of 0.895, 0.829, and 0.900, respectively.	Data were collected at 3 months after the Interventions.
Bot Usability	The research project assessed changes in Chatbot usability by Chatbot Usability Scale(BUS). This study utilizes the Chatbot Usability Scale (BUS-11) developed by Borsci et al. (2023) to assess chatbot usability. The scale uses a 5-point Likert scale, with scores ranging from 1 (strongly disagree) to 5 (strongly agree). The total score ranges from 11 to 55, with higher scores indicating greater user satisfaction with the chatbot's usability (Borsci et al., 2023).The Cronbach's alpha value is 0.90, indicating a high level of internal consistency among the items in the scale (Borsci et al., 2023).	Data were collected at baseline.
Bot Usability	The research project assessed changes in Chatbot usability by Chatbot Usability Scale(BUS). This study utilizes the Chatbot Usability Scale (BUS-11) developed by Borsci et al. (2023) to assess chatbot usability. The scale uses a 5-point Likert scale, with scores ranging from 1 (strongly disagree) to 5 (strongly agree). The total score ranges from 11 to 55, with higher scores indicating greater user satisfaction with the chatbot's usability (Borsci et al., 2023).The Cronbach's alpha value is 0.90, indicating a high level of internal consistency among the items in the scale (Borsci et al., 2023).	Data were collected at 1 months after the Interventions.
Bot Usability	The research project assessed changes in Chatbot usability by Chatbot Usability Scale(BUS) from baseline to 3 months after the Interventions. This study utilizes the Chatbot Usability Scale (BUS-11) developed by Borsci et al. (2023) to assess chatbot usability. The scale uses a 5-point Likert scale, with scores ranging from 1 (strongly disagree) to 5 (strongly agree). The total score ranges from 11 to 55, with higher scores indicating greater user satisfaction with the chatbot's usability (Borsci et al., 2023).The Cronbach's alpha value is 0.90, indicating a high level of internal consistency among the items in the scale (Borsci et al., 2023).	Data were collected at 3 months after the Interventions.

Collaborators and Investigators

• Sponsor: Chang Gung Memorial Hospital
• Investigators: Principal Investigator: Jian Tao LEE, Professor, Chang Gung University

Publications and helpful links

General Publications

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• American Cancer Society. Cancer facts & figures.Retrieved from https://www.cancer.org/ 2018.
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• Athilingam P, Labrador MA, Remo EF, Mack L, San Juan AB, Elliott AF. Features and usability assessment of a patient-centered mobile application (HeartMapp) for self-management of heart failure. Appl Nurs Res. 2016 Nov;32:156-163. doi: 10.1016/j.apnr.2016.07.001. Epub 2016 Jul 11.
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• Broderick, J., Devine, T., Langhans, E., Lemerise, A. J., Lier, S., & Harris, L. Designing health literate mobile apps: Institute of Medicine of the National Academies Washington, DC.2014.
• Brooke, J. SUS-A quick and dirty usability scale. Usability evaluation in industry, 189(194), 4-7.1996.
• Chaudry, B. M., Connelly, K. H., Siek, K. A., & Welch, J. L. Mobile interface design for low-literacy populations. Paper presented at the Proceedings of the 2nd ACM SIGHIT international health informatics symposium.2012.
• Faller H, Koch U, Brahler E, Harter M, Keller M, Schulz H, Wegscheider K, Weis J, Boehncke A, Hund B, Reuter K, Richard M, Sehner S, Szalai C, Wittchen HU, Mehnert A. Satisfaction with information and unmet information needs in men and women with cancer. J Cancer Surviv. 2016 Feb;10(1):62-70. doi: 10.1007/s11764-015-0451-1. Epub 2015 May 9.
• Fischer OJ, Marguerie M, Brotto LA. Sexual Function, Quality of Life, and Experiences of Women with Ovarian Cancer: A Mixed-Methods Study. Sex Med. 2019 Dec;7(4):530-539. doi: 10.1016/j.esxm.2019.07.005. Epub 2019 Sep 7.
• Hevner, A. R. A three cycle view of design science research. Scandinavian journal of information systems. 2007;19(2), 4.
• Holmes, S., Bond, R., Moorhead, A., Zheng, J., Coates, V., & McTear, M.Towards Validating a Chatbot Usability Scale Design, User Experience, and Usability: 12th International Conference, DUXU 2023, Held as Part of the 25th HCI International Conference, HCII 2023, Copenhagen, Denmark, July 23-28, 2023, Proceedings, Part IV, Copenhagen, Denmark. 2023. https://doi.org/10.1007/978-3-031-35708-4_24
• Holmes, S., Moorhead, A., Bond, R., Zheng, H., Coates, V., & McTear, M. Usability testing of a healthcare chatbot: Can we use conventional methods to assess conversational user interfaces?. In Proceedings of the 31st European Conference on Cognitive Ergonomics 2019. (pp. 207-214).
• Hsieh LY, Chou FJ, Guo SE. Information needs of patients with lung cancer from diagnosis until first treatment follow-up. PLoS One. 2018 Jun 21;13(6):e0199515. doi: 10.1371/journal.pone.0199515. eCollection 2018.
• Sekse RJT, Dunberger G, Olesen ML, Osterbye M, Seibaek L. Lived experiences and quality of life after gynaecological cancer-An integrative review. J Clin Nurs. 2019 May;28(9-10):1393-1421. doi: 10.1111/jocn.14721. Epub 2019 Jan 11.
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• McCorkle R, Quint-Benoliel J. Symptom distress, current concerns and mood disturbance after diagnosis of life-threatening disease. Soc Sci Med. 1983;17(7):431-8. doi: 10.1016/0277-9536(83)90348-9.
• Meeringa, R. S. What does value-in-use assessment add to usability assessment of an artificial pancreas for type 1 diabetes patients in the Netherlands with different treatment conditions? An experimental study in medical innovation management. University of Twente. 2016.
• Reb AM, Cope DG. Quality of Life and Supportive Care Needs of Gynecologic Cancer Survivors. West J Nurs Res. 2019 Oct;41(10):1385-1406. doi: 10.1177/0193945919846901. Epub 2019 May 12.
• Ryu, Y. S., & Smith-Jackson, T. L. (2006). Reliability and validity of the mobile phone usability questionnaire (MPUQ). Journal of usability studies. 2006; 2(1), 39-53.
• Schnall R, Rojas M, Bakken S, Brown W, Carballo-Dieguez A, Carry M, Gelaude D, Mosley JP, Travers J. A user-centered model for designing consumer mobile health (mHealth) applications (apps). J Biomed Inform. 2016 Apr;60:243-51. doi: 10.1016/j.jbi.2016.02.002. Epub 2016 Feb 20.
• Schulman-Green D, Bradley EH, Nicholson NR Jr, George E, Indeck A, McCorkle R. One step at a time: self-management and transitions among women with ovarian cancer. Oncol Nurs Forum. 2012 Jul;39(4):354-60. doi: 10.1188/12.ONF.354-360.
• Sekse RJ, Blaaka G, Buestad I, Tengesdal E, Paulsen A, Vika M. Education and counselling group intervention for women treated for gynaecological cancer: does it help? Scand J Caring Sci. 2014 Mar;28(1):112-21. doi: 10.1111/scs.12024. Epub 2013 Jan 15.
• Simon JA, Kokot-Kierepa M, Goldstein J, Nappi RE. Vaginal health in the United States: results from the Vaginal Health: Insights, Views & Attitudes survey. Menopause. 2013 Oct;20(10):1043-8. doi: 10.1097/GME.0b013e318287342d.
• Tayor, S. J., & Bogdan, R. Introduction to qualitative research methods: London: Wilsy.1984.
• Vistad I, Fossa SD, Kristensen GB, Dahl AA. Chronic fatigue and its correlates in long-term survivors of cervical cancer treated with radiotherapy. BJOG. 2007 Sep;114(9):1150-8. doi: 10.1111/j.1471-0528.2007.01445.x. Epub 2007 Jul 26.

Study record dates

Study Major Dates

• Study Start (Actual): October 16, 2020
• Primary Completion (Actual): December 31, 2024
• Study Completion (Actual): December 31, 2024

Study Registration Dates

• First Submitted: August 8, 2024
• First Submitted That Met QC Criteria: August 13, 2024
• First Posted (Actual): August 14, 2024

Study Record Updates

• Last Update Posted (Actual): March 23, 2026
• Last Update Submitted That Met QC Criteria: March 19, 2026
• Last Verified: March 1, 2026

More Information

Terms related to this study

• Keywords: mobile health; mHealth application; gynecological cancer; mobile health learning
• Other Study ID Numbers: 109-2629-H-182-001

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No