Nvivo software

Manufactured by QRS International

Sourced in Australia

NVivo is a software package designed for qualitative and mixed-methods research. It provides tools for organizing, analyzing, and visualizing data from various sources, such as interviews, focus groups, social media, and documents.

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Lab products found in correlation

Stata, by StataCorp (2 mentions) Spss statistics 24, by IBM (1 mentions) Spss 24 statistical software, by IBM (1 mentions)

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NVivo software (Version 11, (2 citations) NVivo qualitative data analysis software (2 citations)

22 protocols using nvivo software

Thematic Analysis of Interview Transcripts

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All interview transcripts were cross-checked with video recordings to ensure accuracy. Identification codes were assigned [WHO, CoD or NC -non-completer-, with consecutive numbers (e.g., CoD4)]. Thematic analysis was employed to identify emergent themes until saturation was reached (Braun and Clarke, 2006 (link)). Two researchers independently reviewed one transcript to identify codes using NVIVO software (version 2, QRS International Pty Ltd). Then, they discussed the findings and presented the proposed principles derived from the data to the research team until consensus was reached on the final regulations.

Almarcha M., González I., Balagué N, & Javierre C. (2022). Prescribing or co-designing exercise in healthy adults? Effects on mental health and interoceptive awareness. Frontiers in Behavioral Neuroscience, 16, 944193.

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Analyzing Qualitative and Quantitative Data

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Quantitative data from questionnaires were analysed descriptively using SPSS software (IBM SPSS Statistics 24). Qualitative data from the interview transcripts were managed and retrieved using NVivo software (Version 12; QRS International Pty Ltd) and analysed using deductive content analysis, following a 5-stage unconstrained matrix approach (see Additional file 1: Table S3 for further details) [41 (link)]. Trustworthiness of the qualitative analysis was supported by investigator triangulation (two researchers developed the categorisation matrix) and the recording of detailed observations during interviews. Emerging findings were discussed with the research team during the analytical process to support an on-going process of reflexivity. A detailed account of the study methods supports the confirmability of the findings.

Harris E., Conway D., Jimenez-Aranda A., Butts J., Hedley-Takhar P., Thomson R, & Astin F. (2022). Development and user-testing of a digital patient decision aid to facilitate shared decision-making for people with stable angina. BMC Medical Informatics and Decision Making, 22, 143.

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Qualitative Analysis of Behavioral Healthcare Utilization

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Data analysis was conducted from January to August 2020. We used the constant comparative method, guided by modified grounded theory, to analyze the qualitative data.²¹ Consistent with study objectives and Andersen’s Behavioral Model, we deductively identified a priori domains of interest and inductively explored emergent themes within and across participants.¹⁶ This process included several stages of analysis. First, directed by an experienced qualitative researcher (KR), 2 trained coders from the MMRL independently read through a subset of the transcripts to identify themes within each a priori domain. Second, we used this list to develop an initial coding dictionary and apply it to a subset of the interview transcripts. Third, we iteratively refined the code-book using inter-rater reliability to document and improve coding consistency. Last, once high inter-rater reliability was achieved (kappa >.7), we applied the full coding dictionary to the transcripts using NVivo software (Version 12, QRS International) and produced thematic reports summarizing our findings. We conducted descriptive and bivariate analysis to analyze structured questionnaire data using Stata (Version 15.1, StataCorp) and used concurrent mixed methods to compare and triangulate quantitative data with qualitative patterns.¹⁶

Wainwright J.V., Mehta S.J., Clifton A., Bocage C., Ogden S.N., Cohen S, & Rendle K.A. (2021). Persistent Barriers to Colorectal Cancer Screening Completion Amid Centralized Outreach: A Mixed Methods Study. American journal of health promotion : AJHP, 36(4), 697-705.

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Qualitative Analysis of Oncology Facilitators

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Using qualitative content analysis, five study team members with medical anthropology, public health, and oncological expertise reviewed transcripts and developed a preliminary open coding scheme based on key topics of focus in the interview guide. Two coders subsequently used NVivo software (QRS International) and Atlas.ti 8 (Scientific Software Development GmbH) to conduct “focused coding,” which included a detailed analysis of themes identified during open coding. For example, the initial coding scheme listed facilitators as a theme. During the intensive coding process, all facilitators mentioned by participants were coded separately in order to determine the number of times a specific facilitator was mentioned and by how many participants. Analysts then combined statements with similar meaning (i.e., “less toxicity” and “fewer side effects”). A third study team member was brought in to resolve any discrepancies during this process. Once all coders felt that thematic saturation had been reached, the saliency of each theme was determined based on the number of participants who mentioned that theme. Finally, exemplary quotes characterizing themes were highlighted, and investigator insights relevant to specific facilitators and barriers were noted.

Andrews C., Childers T.C., Wiseman K.D., Lawhon V., Ingram S., Smith M.L., Wolff A.C., Wagner L, & Rocque G.B. (2022). Facilitators and barriers to reducing chemotherapy for early-stage breast cancer: a qualitative analysis of interviews with patients and patient advocates. BMC Cancer, 22, 141.

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Qualitative Analysis of Interview Transcripts

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Data analysis was guided by the Framework Method,37 (link) with transcripts analyzed both deductively and inductively. Once a majority of interviews were completed, two authors (SWL, AP) began reading the transcripts for familiarity and content, and writing memos. A set of a priori codes, developed from the interview guide, was piloted with a subset of transcripts. These transcripts were double coded using NVivo software (release 1.4.1, QRS International), and differences in coding were reconciled for each transcript until full agreement was achieved. Memos were used to identify emergent themes and finalize the codebook. Once the codebook was finalized, two authors (SWL, AP) ensured each transcript was fully coded with a second round of coding. These authors met regularly to review coding and achieve coding consensus.38 Detailed matrices were then created in Microsoft Excel, with rows representing individual participants and columns representing single codes. Content relevant to each code was summarized between and within participants.39 The Consolidated Criteria for Reporting Qualitative Research (COREQ) was followed for reporting findings40 (link) (see

Supplementary Material 2

Light S.W., Pack A., Vela A., Bailey S.C., Zuleta A., O’Conor R, & Wolf M.S. (2022). Perceptions and Motivating Factors Regarding COVID-19 Vaccination in Latinx Older Adults in Chicago: A Local, Qualitative Perspective. Patient preference and adherence, 16, 2321-2333.

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Analyzing Research Protocols through Qualitative Insights

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All data were aggregated and anonymized, so no personally identifiable information was included in the analysis and presentation of results. Quantitative data management and descriptive statistics were conducted using Microsoft Excel (Version 16.73, 2023), while statistical analyses were performed using R statistical software (Version 4.2.2, 2022). FGDs were recorded and transcribed verbatim, using two auto-transcription services, Zoom (Version 5.13.11, 2023) and Mediasite (Version 8.16.0, 2023), with manual verification by the OSU-CVM team. Transcript correction, coding, and thematic analysis were performed using NVivo software (Version 20.6.2, QRS International) by multiple team members together (range: 2–4) to reduce confirmation bias. Coding was done inductively (31 ), utilizing the constant comparison method (32 (link)), while also listening to the meeting recordings to make any additional corrections to each transcript. Once the initial coding and thematic analysis process was complete, results were shared with the whole team (OSU-CVM and UoG-CVMAS) to discuss and validate the findings.

Bessler A.L., Hoet A.E., Nigatu S., Swisher S., Fentie T., Admassu B., Molla A., Brown M, & Berrian A.M. (2024). Advancing One Health through veterinary education: a mixed methods needs assessment for implementing a WOAH-harmonized national veterinary medicine curriculum in Ethiopia. Frontiers in Veterinary Science, 11, 1357855.

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Health Sector Resilience During Domestic EVD Response

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A literature review¹⁶ was conducted to identify prospective interviewees and interview themes. Phone interviews were conducted from February-November 2016 to distill factors that influenced health sector resilience during the domestic EVD response. Participants (N = 73) were identified through the literature review, snowball sampling, and the researchers’ knowledge of the response. A semi-structured interview guide facilitated discussions with individuals from Atlanta (n = 17), Dallas (n = 22), New York (n = 13), Omaha (n = 18), and the CDC (n = 3). Themes included the following: risk perception; health care; and local, state, and federal response. Each interview was audio-recorded, transcribed, and coded using NVivo software (QRS International, Melbourne, Australia). Two focus groups—New York (December 2016) and Dallas (January 2017)—further explored themes identified during interviews. An expert advisory group considered the preliminary findings and commented on recommendation relevancy, accuracy, and feasibility.
This research was designated exempt by the University of Pittsburgh Institutional Review Board and deemed not human subjects research by the CDC Human Research Protection Office.

Meyer D., Sell T.K., Schoch-Spana M., Shearer M.P., Chandler H., Thomas E., Rose D.A., Carbone E.G, & Toner E. (2017). Lessons from the domestic Ebola response: Improving health care system resilience to high consequence infectious diseases. American journal of infection control, 46(5), 533-537.

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Qualitative Exploration of PHC Workforce

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Interviews will be transcribed verbatim in-country and transcripts in Hindi, Telugu, Spanish and Ateso, Jopadhola and Runyoro will be translated to English for analysis. The qualitative data for each country will be coded using NVivo software (QRS International, Vic) and analysed using an inductive approach. Two coders from each country will review and analyse the data. Weekly calls will be set up to discuss the emerging themes with the research team. This approach will enable us to explore and identify the important issues in PHC workforce organisation, composition and comprehensiveness, and will also help us to identify shared challenges and differences across countries.

Joshi R., Besigye I., Heredia-Pi I., Sharma M., Peiris D., Mash R.J., Reyes-Morales H., Goodyear-Smith F., John R., Ortega-Altamirano D.V., Orozco-Núñez E., Ávila-Burgos L., Jeyakumar R., Serván-Mori E., Upadhyaya S., Arora V, & Praveen D. (2022). How do diverse low-income and middle-income countries implement primary healthcare team integration to support the delivery of comprehensive primary health care? A mixed-methods study protocol from India, Mexico and Uganda. BMJ Open, 12(5), e055218.

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Qualitative Data Analysis Framework

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Analysis of qualitative data will be carried out by two independent researchers on the original transcripts and document-review extracts. Analysis will utilize the framework method (61 (link)) assisted by N-Vivo software (QRS-international). This method suits our study because of its flexibility (61 (link)) and offers a possibility of comparing results within and between levels at which data are collected (51 (link)). Qualitative analysis will proceed by reading interview transcripts and writing memos, coding the data, developing themes, and constructing a comprehensive narrative (52 ). Credibility will be established by triangulating data collection methods and sources and having at least two researchers independently code and analyze the transcripts (analyst triangulation) (52 , 62 ).

Kalolo A., Radermacher R., Stoermer M., Meshack M, & De Allegri M. (2015). Factors affecting adoption, implementation fidelity, and sustainability of the Redesigned Community Health Fund in Tanzania: a mixed methods protocol for process evaluation in the Dodoma region. Global Health Action, 8, 10.3402/gha.v8.29648.

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Qualitative Analysis of Treatment De-escalation

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Using qualitative content analysis,¹² three independent coders with medical anthropology, public health, and medical expertise (CA, KW, and CC) developed an open coding scheme.¹³ The final coding schema was reviewed and finalized by the multidisciplinary team, which included three primary coders (CA, KW, and CC), an oncologist (GR), and a psychologist (LW). Two primary coders with medical anthropology and psychology expertise (CA and KW) subsequently used NVivo software (QRS International) and Atlas.ti (Version 8) to conduct “focused coding,” which included a detailed analysis of themes identified during open coding. Discrepancies were resolved by a third coder (CC). The process was repeated until thematic saturation was reached.¹⁴ Overarching themes pertaining to treatment de‐escalation were identified, exemplary quotes characterizing themes were highlighted, and investigator insights relevant to the decision‐making process were noted in memo format. Descriptive statistics were calculated for patient demographic data and the frequency of specific themes.

Rocque G.B., Williams C.P., Andrews C., Childers T.C., Wiseman K.D., Gallagher K., Tung N., Balch A., Lawhon V.M., Ingram S.A., Brown T., Kaufmann T., Smith M.L., DeMichele A., Wolff A.C, & Wagner L. (2021). Patient perspectives on chemotherapy de‐escalation in breast cancer. Cancer Medicine, 10(10), 3288-3298.

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