Project Overview Trends toward open science practices, along with advances in technology, have promoted increased data archiving in recent years, thus bringing new attention to the reuse of archived qualitative data. Qualitative data reuse can increase efficiency and reduce the burden on research subjects, since new studies can be conducted without collecting new data. Qualitative data reuse also supports larger-scale, longitudinal research by combining datasets to analyze more participants. At the same time, qualitative research data can increasingly be collected from online sources. Social scientists can access and analyze personal narratives and social interactions through social media such as blogs, vlogs, online forums, and posts and interactions from social networking sites like Facebook and Twitter. These big social data have been celebrated as an unprecedented source of data analytics, able to produce insights about human behavior on a massive scale. However, both types of research also present key epistemological, ethical, and legal issues. This study explores the issues of context, data quality and trustworthiness, data comparability, informed consent, privacy and confidentiality, and intellectual property and data ownership, with a focus on data curation strategies. The research suggests that connecting qualitative researchers, big social researchers, and curators can enhance responsible practices for qualitative data reuse and big social research. This study addressed the following research questions: RQ1: How is big social data curation similar to and different from qualitative data curation? RQ1a: How are epistemological, ethical, and legal issues different or similar for qualitative data reuse and big social research? RQ1b: How can data curation practices such as metadata and archiving support and resolve some of these epistemological and ethical issues? RQ2: What are the implications of these similarities and differences for big social data curation and qualitative data curation, and what can we learn from combining these two conversations? Data Description and Collection Overview The data in this study was collected using semi-structured interviews that centered around specific incidents of qualitative data archiving or reuse, big social research, or data curation. The participants for the interviews were therefore drawn from three categories: researchers who have used big social data, qualitative researchers who have published or reused qualitative data, and data curators who have worked with one or both types of data. Six key issues were identified in a literature review, and were then used to structure three interview guides for the semi-structured interviews. The six issues are context, data quality and trustworthiness, data comparability, informed consent, privacy and confidentiality, and intellectual property and data ownership. Participants were limited to those working in the United States. Ten participants from each of the three target populations—big social researchers, qualitative researchers who had published or reused data, and data curators were interviewed. The interviews were conducted between March 11 and October 6, 2021. When scheduling the interviews, participants received an email asking them to identify a critical incident prior to the interview. The “incident” in critical incident interviewing technique is a specific example that focuses a participant’s answers to the interview questions. The participants were asked their permission to have the interviews recorded, which was completed using the built-in recording technology of Zoom videoconferencing software. The author also took notes during the interviews. Otter.ai speech-to-text software was used to create initial transcriptions of the interview recordings. A hired undergraduate student hand-edited the transcripts for accuracy. The transcripts were manually de-identified. The author analyzed the interview transcripts using a qualitative content analysis approach. This involved using a combination of inductive and deductive coding approaches. After reviewing the research questions, the author used NVivo software to identify chunks of text in the interview transcripts that represented key themes of the research. Because the interviews were structured around each of the six key issues that had been identified in the literature review, the author deductively created a parent code for each of the six key issues. These parent codes were context, data quality and trustworthiness, data comparability, informed consent, privacy and confidentiality, and intellectual property and data ownership. The author then used inductive coding to create sub-codes beneath each of the parent codes for these key issues. Selection and Organization of Shared Data The data files consist of 28 of the interview transcripts themselves – transcripts from Big Science Researchers (BSR), Data Curators (DC), and Qualitative Researchers (QR)...

This data set contains the replication data and supplements for the article "Knowing, Doing, and Feeling: A three-year, mixed-methods study of undergraduates’ information literacy development." The survey data is from two samples: - cross-sectional sample (different students at the same point in time) - longitudinal sample (the same students and different points in time)Surveys were distributed via Qualtrics during the students' first and sixth semesters. Quantitative and qualitative data were collected and used to describe students' IL development over 3 years. Statistics from the quantitative data were analyzed in SPSS. The qualitative data was coded and analyzed thematically in NVivo. The qualitative, textual data is from semi-structured interviews with sixth-semester students in psychology at UiT, both focus groups and individual interviews. All data were collected as part of the contact author's PhD research on information literacy (IL) at UiT. The following files are included in this data set: 1. A README file which explains the quantitative data files. (2 file formats: .txt, .pdf)2. The consent form for participants (in Norwegian). (2 file formats: .txt, .pdf)3. Six data files with survey results from UiT psychology undergraduate students for the cross-sectional (n=209) and longitudinal (n=56) samples, in 3 formats (.dat, .csv, .sav). The data was collected in Qualtrics from fall 2019 to fall 2022. 4. Interview guide for 3 focus group interviews. File format: .txt5. Interview guides for 7 individual interviews - first round (n=4) and second round (n=3). File format: .txt 6. The 21-item IL test (Tromsø Information Literacy Test = TILT), in English and Norwegian. TILT is used for assessing students' knowledge of three aspects of IL: evaluating sources, using sources, and seeking information. The test is multiple choice, with four alternative answers for each item. This test is a "KNOW-measure," intended to measure what students know about information literacy. (2 file formats: .txt, .pdf)7. Survey questions related to interest - specifically students' interest in being or becoming information literate - in 3 parts (all in English and Norwegian): a) information and questions about the 4 phases of interest; b) interest questionnaire with 26 items in 7 subscales (Tromsø Interest Questionnaire - TRIQ); c) Survey questions about IL and interest, need, and intent. (2 file formats: .txt, .pdf)8. Information about the assignment-based measures used to measure what students do in practice when evaluating and using sources. Students were evaluated with these measures in their first and sixth semesters. (2 file formats: .txt, .pdf)9. The Norwegain Centre for Research Data's (NSD) 2019 assessment of the notification form for personal data for the PhD research project. In Norwegian. (Format: .pdf)

This dataset was created and deposited onto the University of Sheffield Online Research Data repository (ORDA) on 23-Jun-2023 by Dr. Matthew S. Hanchard, Research Associate at the University of Sheffield iHuman Institute.

The dataset forms part of three outputs from a project titled ‘Fostering cultures of open qualitative research’ which ran from January 2023 to June 2023:

· Fostering cultures of open qualitative research: Dataset 1 – Survey Responses · Fostering cultures of open qualitative research: Dataset 2 – Interview Transcripts · Fostering cultures of open qualitative research: Dataset 3 – Coding Book

The project was funded with £13,913.85 Research England monies held internally by the University of Sheffield - as part of their ‘Enhancing Research Cultures’ scheme 2022-2023.

The dataset aligns with ethical approval granted by the University of Sheffield School of Sociological Studies Research Ethics Committee (ref: 051118) on 23-Jan-2021.This includes due concern for participant anonymity and data management.

ORDA has full permission to store this dataset and to make it open access for public re-use on the basis that no commercial gain will be made form reuse. It has been deposited under a CC-BY-NC license.

This dataset comprises one spreadsheet with N=91 anonymised survey responses .xslx format. It includes all responses to the project survey which used Google Forms between 06-Feb-2023 and 30-May-2023. The spreadsheet can be opened with Microsoft Excel, Google Sheet, or open-source equivalents.

The survey responses include a random sample of researchers worldwide undertaking qualitative, mixed-methods, or multi-modal research.

The recruitment of respondents was initially purposive, aiming to gather responses from qualitative researchers at research-intensive (targetted Russell Group) Universities. This involved speculative emails and a call for participant on the University of Sheffield ‘Qualitative Open Research Network’ mailing list. As result, the responses include a snowball sample of scholars from elsewhere.

The spreadsheet has two tabs/sheets: one labelled ‘SurveyResponses’ contains the anonymised and tidied set of survey responses; the other, labelled ‘VariableMapping’, sets out each field/column in the ‘SurveyResponses’ tab/sheet against the original survey questions and responses it relates to.

The survey responses tab/sheet includes a field/column labelled ‘RespondentID’ (using randomly generated 16-digit alphanumeric keys) which can be used to connect survey responses to interview participants in the accompanying ‘Fostering cultures of open qualitative research: Dataset 2 – Interview transcripts’ files.

A set of survey questions gathering eligibility criteria detail and consent are not listed with in this dataset, as below. All responses provide in the dataset gained a ‘Yes’ response to all the below questions (with the exception of one question, marked with an asterisk (*) below):

· I am aged 18 or over · I have read the information and consent statement and above. · I understand how to ask questions and/or raise a query or concern about the survey. · I agree to take part in the research and for my responses to be part of an open access dataset. These will be anonymised unless I specifically ask to be named. · I understand that my participation does not create a legally binding agreement or employment relationship with the University of Sheffield · I understand that I can withdraw from the research at any time. · I assign the copyright I hold in materials generated as part of this project to The University of Sheffield. · * I am happy to be contacted after the survey to take part in an interview.

The project was undertaken by two staff: Co-investigator: Dr. Itzel San Roman Pineda ORCiD ID: 0000-0002-3785-8057 i.sanromanpineda@sheffield.ac.uk

Postdoctoral Research Assistant Principal Investigator (corresponding dataset author): Dr. Matthew Hanchard ORCiD ID: 0000-0003-2460-8638 m.s.hanchard@sheffield.ac.uk Research Associate iHuman Institute, Social Research Institutes, Faculty of Social Science

This dataset was created and deposited onto the University of Sheffield Online Research Data repository (ORDA) on 23-Jun-2023 by Dr. Matthew S. Hanchard, Research Associate at the University of Sheffield iHuman Institute. The dataset forms part of three outputs from a project titled ‘Fostering cultures of open qualitative research’ which ran from January 2023 to June 2023:

· Fostering cultures of open qualitative research: Dataset 1 – Survey Responses · Fostering cultures of open qualitative research: Dataset 2 – Interview Transcripts · Fostering cultures of open qualitative research: Dataset 3 – Coding Book

The project was funded with £13,913.85 of Research England monies held internally by the University of Sheffield - as part of their ‘Enhancing Research Cultures’ scheme 2022-2023.

The dataset aligns with ethical approval granted by the University of Sheffield School of Sociological Studies Research Ethics Committee (ref: 051118) on 23-Jan-2021. This includes due concern for participant anonymity and data management.

ORDA has full permission to store this dataset and to make it open access for public re-use on the basis that no commercial gain will be made form reuse. It has been deposited under a CC-BY-NC license. Overall, this dataset comprises:

· 15 x Interview transcripts - in .docx file format which can be opened with Microsoft Word, Google Doc, or an open-source equivalent.

All participants have read and approved their transcripts and have had an opportunity to retract details should they wish to do so.

Participants chose whether to be pseudonymised or named directly. The pseudonym can be used to identify individual participant responses in the qualitative coding held within the ‘Fostering cultures of open qualitative research: Dataset 3 – Coding Book’ files.

For recruitment, 14 x participants we selected based on their responses to the project survey., whilst one participant was recruited based on specific expertise.

· 1 x Participant sheet – in .csv format which may by opened with Microsoft Excel, Google Sheet, or an open-source equivalent.

The provides socio-demographic detail on each participant alongside their main field of research and career stage. It includes a RespondentID field/column which can be used to connect interview participants with their responses to the survey questions in the accompanying ‘Fostering cultures of open qualitative research: Dataset 1 – Survey Responses’ files.

The project was undertaken by two staff:

Co-investigator: Dr. Itzel San Roman Pineda ORCiD ID: 0000-0002-3785-8057 i.sanromanpineda@sheffield.ac.uk Postdoctoral Research Assistant Labelled as ‘Researcher 1’ throughout the dataset

Principal Investigator (corresponding dataset author): Dr. Matthew Hanchard ORCiD ID: 0000-0003-2460-8638 m.s.hanchard@sheffield.ac.uk Research Associate iHuman Institute, Social Research Institutes, Faculty of Social Science Labelled as ‘Researcher 2’ throughout the dataset

BackgroundAs more people living with HIV are identified and prescribed antiretroviral treatment in Zambia, detecting new HIV infections to complete the last mile of epidemic control is challenging. To address this, innovative targeted testing strategies are essential. Therefore, Right to Care Zambia developed and implemented a novel digital health surveillance application, Lynx, in three Zambian provinces—Northern, Luapula, and Muchinga in 2018. Lynx offers real-time HIV testing data with geo-spatial analysis for targeted testing, and has proven effective in enhancing HIV testing yield. This cross-sectional mixed methods study assessed the acceptability of Lynx among HIV testing healthcare workers in Zambia.MethodsA quantitative Likert scale (1–5) survey was administered to 176 healthcare workers to gauge Lynx’s acceptability. Additionally, six qualitative key person interviews and five focus group discussions were conducted to gain an in-depth understanding of acceptability, and identify relevant barriers and facilitators. Quantitative data were analysed by averaging survey responses and running descriptive statistics. Qualitative data were transcribed and analysed in thematic coding. Data triangulation was utilised between the data sources to verify findings.ResultsOverall, the average survey score of perceived ease of use was 3.926 (agree), perceived usefulness was 4.179 (strongly agree) and perceived compatibility was 3.574 (agree). Survey questions related to network requirements, resource availability, and IT support had the most “strongly disagree” responses. The qualitative data collection revealed that Lynx was perceived as useful, and easy to use. Training for staff and regular updates were identified as facilitators, while conflicting work priorities and inconsistent IT support were identified barriers.ConclusionLynx was identified as acceptable by health workers due to its perceived usefulness, staff trainings, and regular updates. For a mobile health intervention to be embraced in rural Zambian settings, key facilitators include robust IT support, comprehensive training, user feedback-based updates, and consideration of facility staff priorities.

Qualitative Data Analysis Software Market size was valued at USD 1.2 Billion in 2024 and is projected to reach USD 1.9 Billion by 2032, growing at a CAGR of 6% from 2026 to 2032.

Global Qualitative Data Analysis Software Market Overview

In the report, the market outlook section mainly encompasses the fundamental dynamics of the market which include drivers, restraints, opportunities, and challenges faced by the industry. Drivers and restraints are intrinsic factors whereas opportunities and challenges are extrinsic factors of the market.

The proliferation of open-source frameworks for big data analytics and the ability of powerful HPC systems to process data at higher resolutions drive the Qualitative Data Analysis Software Market. High investment costs involved in the deployment of HPC systems, Government rules, and regulations act as a restrain to the market.

After several years of over concentration on communicable diseases, Ghana has finally made notable strides in the prevention of NCDs by introducing key policies and programmes. Evident shows that there is limited NCD-related data on mortality and risk factors to inform NCD policy, planning, and implementation in Ghana. We explored the evidence base for noncommunicable disease policies in Ghana. A qualitative approach was adopted using key informant interviews and documents as data sources. An adaptation of the framework method for analysing qualitative data by Gale and colleagues’ (2013) was used to analyse data. Our findings show that effort has been made in terms of institutions and systems to provide evidence for the policy process with the creation of the Centre for Health Information Management and the District Health Information Management System. Although there is overreliance on routine facility data, policies have also been framed using surveys, burden of disease estimates, monitoring reports, and systematic reviews. There is little emphasis on content analysis, key informant interviews, case studies, and implementation science techniques in the policy process of Ghana. Inadequate and poor data quality are key challenges that confront policymakers. Ghana has improved its information infrastructure but access to quality noncommunicable disease data remains a daunting challenge. A broader framework for the integration of different sources of data such as verbal autopsies and natural experiments is needed while strengthening existing systems. This, however, requires greater investments in personnel and logistics at national and district levels.

IntroductionMany studies have now demonstrated the efficacy of text messaging in positively changing behaviours. We aimed to identify features and factors that explain the effectiveness of a successful text messaging program in terms of user engagement, perceived usefulness, behavior change and program delivery preferences.MethodsMixed methods qualitative design combining four data sources; (i) analytic data extracted directly from the software system, (ii) participant survey, (iii) focus groups to identify barriers and enablers to implementation and mechanisms of effect and (iv) recruitment screening logs and text message responses to examine engagement. This evaluation was conducted within the TEXT ME trial—a parallel design, single-blind randomized controlled trial (RCT) of 710 patients with coronary heart disease (CHD). Qualitative data were interpreted using inductive thematic analysis.Results307/352 (87% response rate) of recruited patients with CHD completed the program evaluation survey at six months and 25 participated in a focus group. Factors increasing engagement included (i) ability to save and share messages, (ii) having the support of providers and family, (iii) a feeling of support through participation in the program, (iv) the program being initiated close to the time of a cardiovascular event, (v) personalization of the messages, (vi) opportunity for initial face-to-face contact with a provider and (vii) that program and content was perceived to be from a credible source. Clear themes relating to program delivery were that diet and physical activity messages were most valued, four messages per week was ideal and most participants felt program duration should be provided for at least for six months or longer.ConclusionsThis study provides context and insight into the factors influencing consumer engagement with a text message program aimed at improving health-related behavior. The study suggests program components that may enhance potential success but will require integration at the development stage to optimize up-scaling.Trial RegistrationAustralia and New Zealand Clinical Trials Registry, ACTRN12611000161921.

Anthropologists have a rich tradition of using a networked approach in data analysis. The purpose of this article is to continue that tradition by demonstrating how social network analysis can be used by anthropologists to improve their analysis and reporting of ethnographic data, and thereby expanding the methodological tool kit traditionally used by anthropologists. We use a case study based on a 1967 social movement aimed at increasing black power in a small Midwestern community in the United States to demonstrate the utility of network analysis in ethnographic studies and reporting, particularly ones that use oral or life story narratives as primary data sources. In addition to examining the data through Multinet, we also expand the Network View functionality in ATLAS.ti in our analysis. We suggest that the networked approach taken in this case study can be used by anthropologists across all four subfields as a method to show relations embedded in the ethnographic data anthropologists are known for collecting.

De dataset bestaat uit drie onderdelen:I: bijlagen bij de hoofdstukken uit deel I van het boek.II: bijlagen bij de hoofdstukken uit deel II van het boek, bestaande uit ATLAS.ti bestanden, verslagen van sparringbijeenkomsten of analyseproducten in Excel van de respectievelijke auteurs.III: een beschrijving van de 17 databronnen die gebruikt zijn door de auteurs aan deel II van het boek. Het gaat daarbij om blogs, audio-visueel materiaal en krantenartikelen met als onderwerp de economische crisis van 2008. De beschrijving van deze dataset is vrij toegankelijk. Indien de individuele bronnen auteursrechtelijk beschermd zijn, zijn deze niet toegankelijk. Waar mogelijk wordt een link opgenomen naar een online versie van de bron.This dataset consists of three parts:I: Appendices for differente chapters in part I of the book.II: Appendices for several chapters in part II of the book, consisting of ATLAS.ti files, notes from sparring meetings or analysis products in Excel.III: a description for the 17 qualitative datasources which have been used by the authors in part II of the book. These sources consist of blogs, audio-visual materials and newspaper articles on the 2008 economic crisis. The description of the dataset is openly available. When the individual sources have not been published under cc0 license, they are not available through EASY. Whenever possible a link has been added to the online location of the source.

BackgroundReceiving a breast cancer diagnosis and treatment is both a physical and emotional journey. Previous studies using single-source data have revealed common and culture-specific emotional experiences of patients living with breast cancer. However, few studies have combined such data from multiple sources. Thus, using a variety of data sources, the current study sought to explore the emotional experiences of women in China newly diagnosed, post-operative, or undergoing chemotherapy. We posited that even though women living with breast cancer in China have multiple channels through which they can express these emotional experiences, little variance would be found in their emotional expressivity and the themes they want to express due to cultural inhibitions.MethodsText data from female patients newly diagnosed, post-operative, or undergoing chemotherapy were collected between June 2021 and January 2022 via a Python web crawler, semi-structured interviews, and an expressive writing intervention. Data were transcribed and subjected to thematic analysis. Reporting followed the consolidated criteria for reporting qualitative studies (COREQ) guidelines.ResultsAnalyses were based on 5,675 Weibo posts and comments published by 448 posters and 1,842 commenters, transcription texts from 17 semi-structured interviews, and 150 expressive writing texts. From this total collection of 461,348 Chinese characters, three major themes emerged: (i) conflicting emotions after diagnosis; (ii) long-term suffering and treatment concerns; and (iii) benefit finding and cognitive reappraisal.ConclusionsDespite gathering information from various sources, we found that distress from body-image disturbances, gender role loss and conflict, and changes in sexuality and fertility, were consistent among this sample of female Chinese patients with breast cancer. However, when women engaged actively in benefit finding and cognitive reappraisal with strong social support, patients were able to find ways to adapt and reported post-traumatic growth. Strong social support was an important facilitator in this growth. These study findings emphasize that healthcare professionals ought to increase cultural sensitivity, provide multiple channels to encourage patients to express their emotions, and incorporate screening for patients' emotional distress at all diagnostic and treatment phases as part of routine nursing care.

The spreadsheets in the present dataset (CSV format) include:

the sources considered during the literature review stage of the Knowledge Exchange activity on publishing reproducible research outputs (KE-PRRO); and

the thematic coding that has been applied to these sources. It should be noted that not all sources considered are available in the thematic coding file, due to copyright considerations (e.g. in cases where significant portions of a subscription-only article have been coded).

The thematic coding has been applied by using NVivo, a professional qualitative analysis software, and then exported in spreadsheet form for public sharing. The findings of this analysis have been used to produce a slide deck, which is also available on Zenodo at: http://doi.org/10.5281/zenodo.4675457

Abstract

Abstract

Background: Adolescent girls in Kenya are disproportionately affected by early and unintended pregnancies, unsafe abortion and HIV infection. The In Their Hands (ITH) programme in Kenya aims to increase adolescents' use of high-quality sexual and reproductive health (SRH) services through targeted interventions. ITH Programme aims to promote use of contraception and testing for sexually transmitted infections (STIs) including HIV or pregnancy, for sexually active adolescent girls, 2) provide information, products and services on the adolescent girl's terms; and 3) promote communities support for girls and boys to access SRH services.

Objectives: The objectives of the evaluation are to assess: a) to what extent and how the new Adolescent Reproductive Health (ARH) partnership model and integrated system of delivery is working to meet its intended objectives and the needs of adolescents; b) adolescent user experiences across key quality dimensions and outcomes; c) how ITH programme has influenced adolescent voice, decision-making autonomy, power dynamics and provider accountability; d) how community support for adolescent reproductive and sexual health initiatives has changed as a result of this programme.

Methodology ITH programme is being implemented in two phases, a formative planning and experimentation in the first year from April 2017 to March 2018, and a national roll out and implementation from April 2018 to March 2020. This second phase is informed by an Annual Programme Review and thorough benchmarking and assessment which informed critical changes to performance and capacity so that ITH is fit for scale. It is expected that ITH will cover approximately 250,000 adolescent girls aged 15-19 in Kenya by April 2020. The programme is implemented by a consortium of Marie Stopes Kenya (MSK), Well Told Story, and Triggerise. ITH's key implementation strategies seek to increase adolescent motivation for service use, create a user-defined ecosystem and platform to provide girls with a network of accessible subsidized and discreet SRH services; and launch and sustain a national discourse campaign around adolescent sexuality and rights. The 3-year study will employ a mixed-methods approach with multiple data sources including secondary data, and qualitative and quantitative primary data with various stakeholders to explore their perceptions and attitudes towards adolescents SRH services. Quantitative data analysis will be done using STATA to provide descriptive statistics and statistical associations / correlations on key variables. All qualitative data will be analyzed using NVIVO software.

Study Duration: 36 months - between 2018 and 2020.

Geographic coverage

Homabay county

Analysis unit

Households

Universe

Adolescent girls aged 15-19 years, parents and the community health volunteers

Sampling procedure

Quantitative Sampling

We estimated a sample size of 1,918 to detect a five percentage-point difference in the use of long term methods between baseline and endline time points at 80% power.As baseline, 23% of the adolescent girls reported that they were using long term methods in Homa Bay county. We sampled three sub counties—Ndhiwa, Homa Bay town and Kasipul for the endline survey. However, as fieldwork was interrupted due to the COVID-19 pandemic, we added one sub county—Karachuonyo sub county—when data collection resumed in September 2020. Sub counties and wards were purposively selected from sub counties that had been prioritized for the ITH program based on availability of ITH affiliated health facilities. The purposive selection of sub counties based on presence of ITH intervention affiliated health facilities meant that urban and peri-urban areas were oversampled due to the concentration of the health facilities in urban/peri-urban areas. In each ward, eight villages that formed the immediate catchment area for each ITH program affiliated health facilities were then selected for the study. We conducted a household listing of all households in each sampled village to identify households with an adolescent girl who met the study's inclusion criteria. Households were then randomly sampled from the list of households with eligible adolescents of age 15-19 years. To be eligible, an adolescent girl had to be aged 15-19 years, resident in the study area for at least six months preceding the study. Accordingly, students who stayed in boarding schools away from their parents were excluded from the study.

Qualitative Sampling

The qualitative component involved in-depth interviews (IDIs) with adolescent girls ages 15-19 years and focus group discussions (FGDs) with parents/adults and CHVs. We conducted IDIs with adolescent girls who had enrolled in the program but dropped out for various reasons, as well as girls who were enrolled and still using t-safe services. In addition, we conducted FGDs with CHVs and parents/adult caretakers of adolescents aged 15-19 years from the program areas. Participants were purposively selected from the villages included in the evaluation study. For the endline study, we conducted 17 IDIs with adolescents who had been enrolled in the ITH program and were receiving services or had dropped from the program. We also conducted two FGDs with CHVs and four FGDs with parents/adultcaretakers of adolescents aged 15-19 years.

Sampling deviation

N/A

Mode of data collection

Face-to-face [f2f] for quantitative data collection and Focus Group Discussions and In Depth Interviews for qualitative data collection

Research instrument

An interviewer-administered questionnaire was used to collect data from adolescent girls. The questionnaire included questions on socio-demographic and household characteristics; SRH knowledge and sources of information; sexual activity and relationships; contraceptive knowledge, access, choice and use; and exposure to family planning messages and contraceptive decision making. To assess adolescents’ exposure to the t-safe program we included a series of questions drawn from similar project evaluation surveys as well as t-safe project program monitoring indicators. The questions assessed whether adolescents had ever heard the t-safe program, whether they have ever been contacted by mobilizers, whether they participated in any community event organized by the t-safe mobilizers, whether they received information about SRH through t-safe affiliated organizations Facebook or website, and whether they received SMS or WhatsApp messages focused on SRH from tsafe. For those who responded positively, the survey asked further questions on the sources; from which site on internet or Facebook’ or ‘which person or organization sent you these messages’ and ‘how many times have you received information’. Adolescents were also asked whether they had ever registered to a t-safe or Triggerise platform using a mobile phone after discussing with a mobilizer, after discussing with their peers or family members or by themselves after hearing from some other places. The questionnaire was developed in English and then translated into Kiswahili. Data were collected on android tablets programmed using the Open Data Kit (ODK)-based SurveyCTO platform.

For the qualitative component ;Semi-structured interview guides were developed by experienced researchers in consultation with the program partners for the qualitative interviews (with adolescent girls) and FGDs (with parents/adult caretakers of adolescents and CHVs). The guides included probes to explore adolescents' exposure to the ITH program; their experiences with program's SRH services; their perceptions on quality of services; as well as challenges and barriers to access of SRH services. The guides also included probes on the community’s "support" for adolescents' sexual and reproductive health services and; their perspectives on the effects of the program. The guides were developed in English and then translated into Kiswahili for data collection. The guides were pre-tested during the pilot study.

Cleaning operations

Quantitative data was collected on android tablets programmed using the Open Data Kit (ODK)-based SurveyCTO platform while qualitative data was collected using a recorder.Once quantitative data were confirmed to be complete, the data was approved for synchronization. Data were electronically transmitted to a secure password protected SurveyCTO server at the APHRC office. Backup versions of the data remained in the encrypted and password-protected tablets until the end of field activities when all the data were considered to have been synchronized. Subsequently, tablet was securely and permanently cleaned. Data on the server were retrieved by the data manager and then downloaded for use. For qualitative data, audio recordings from qualitative interviews were transcribed and saved in MS Word format. The transcripts were stored electronically in password protected computers and were only accessible to the evaluation team working on the project.

Response rate

N/A

Sampling error estimates

N/A

This study focuses on the evidence summary of the dignity experience of the elderly in nursing homes, aiming to explain the understanding of dignity of the elderly in nursing homes, the influencing factors of dignity of the elderly, and the maintenance strategies of dignity. The data of this study are from the included qualitative research literature, and the data sources are true and reliable. Every included article can be found in Pubmed, web of science and other data. The following documents contain the included literature and extracted data.

Qualitative data from community observations are stored and managed using NVivo software that provides functionality for classifying, sorting and arranging qualitative research data. The sampling unit used is a harvest event, typically a hunting or fishing event in a particular season. As of 5 September, 2008 we have received and encoded data for 56 harvest events as follows: Harvest type: Mammal (10), Fish (45), Shellfish (1) Community: Gambell (10), Kanchalan (22), Nikolskoye (6), Sandpoint (18) Preliminary NVivo Data structure: Nodes (collections of related material by topic): ANIMAL HABITATS ANIMAL SPECIES CLIMATE CHANGE AND ENVIRONMENTAL CONDITIONS FAMILY SIZE HARVEST USE HOW PROCESS CATCH HUNT FISH LOCATON INFO SOURCE LEGAL VERSUS NATURAL HUNT FISH SEASON MIGRATION PATTERN QUALITY OF CATCH QUANTITY OF CATCH RESPONDENT CANNOT RECALL OR IS NOT KEEPING TRACK OF PREVIOUS FISH HUNT DETAILS SOCIAL TIES AND FOOD SHARING THE FISHING EXPERIENCE UNCLEAR Queries (primary topics that have had queries created): AIR TEMPERATURE BY LOCATION CHANGES IN WIND STRENGTH FACTORS AFFECTING ABILITY TO REACH HUNT FISH BY LOCATION ICE BREAK-UP ICE FREEZE-UP ILL HEALTH CONDITIONS INFORMATION SOURCE LOCATION BY AIR TEMPERATURE PROXIMITY TO ISLAND OF HUNT FISH LOCATION QUANTITY AND QUALITY OF ICE STRENGTH OF RESPONDENTS OBSERVATION WIND STRENGTH BY LOCATION Classifications (attributes by which cases can be classified): ANIMAL LOCATION SEX

The CLARISSA Cash Plus intervention represented an innovative social protection scheme for tackling social ills, including the worst forms of child labour (WFCL). A universal and unconditional ‘cash plus’ programme, it combined community mobilisation, case work, and cash transfers (CTs). It was implemented in a high-density, low-income neighbourhood in Dhaka to build individual, family, and group capacities to meet needs. This, in turn, was expected to lead to a corresponding decrease in deprivation and community-identified social issues that negatively affect wellbeing, including WFCL. Four principles underpinned the intervention: Unconditionality, Universality, Needs-centred and people-led, and Emergent and open-ended.The intervention took place in Dhaka – North Gojmohol – over a 27-month period, between October 2021 and December 2023, to test and study the impact of providing unconditional and people‑led support to everyone in a community. Cash transfers were provided between January and June 2023 in monthly instalments, plus one investment transfer in September 2023. A total of 1,573 households received cash, through the Upay mobile financial service. Cash was complemented by a ‘plus’ component, implemented between October 2021 and December 2023. Referred to as relational needs-based community organising (NBCO), a team of 20 community mobilisers (CMs) delivered case work at the individual and family level and community mobilisation at the group level. The intervention was part of the wider CLARISSA programme, led by the Institute of Development Studies (IDS) and funded by UK’s Foreign, Commonwealth & Development Office (FCDO). The intervention was implemented by Terre des hommes (Tdh) in Bangladesh and evaluated in collaboration with the BRAC Institute of Governance and Development (BIGD) and researchers from the University of Bath and the Open University, UK.The evaluation of the CLARISSA Social Protection pilot was rooted in contribution analysis that combined multiple methods over more than three years in line with emerging best practice guidelines for mixed methods research on children, work, and wellbeing. Quantitative research included bi-monthly monitoring surveys administered by the project’s community mobilisers (CMs), including basic questions about wellbeing, perceived economic resilience, school attendance, etc. This was complimented by baseline, midline, and endline surveys, which collected information about key outcome indicators within the sphere of influence of the intervention, such as children’s engagement with different forms of work and working conditions, with schooling and other activities, household living conditions and sources of income, and respondents’ perceptions of change. Qualitative tools were used to probe topics and results of interest, as well as impact pathways. These included reflective diaries written by the community mobilisers; three rounds of focus group discussions (FGDs) with community members; three rounds of key informant interviews (KIIs) with members of case study households; and long-term ethnographic observation.Quantitative DataThe quantitative evaluation of the CLARISSA Cash Plus intervention involved several data collection methods to gather information about household living standards, children’s education and work, and social dynamics. The data collection included a pre-intervention census, four periodic surveys, and 13 rounds of bi-monthly monitoring surveys, all conducted between late 2020 and late 2023. Details of each instrument are as follows:Census: Conducted in October/November 2020 in the target neighbourhood of North Gojmohol (n=1,832) and the comparison neighbourhood of Balurmath (n=2,365)Periodic surveys: Baseline (February 2021, n=752 in North Gojmohol), Midline 1 (before cash) (October 2022, n=771 in North Gojmohol), Midline 2 (after 6 rounds of cash) (July 2023, n=769 in North Gojmohol), and Endline (December 2023, n=750 in North Gojmohol and n=773 in Balumath)Bi-monthly monitoring data (13 rounds): Conducted between December 2021 and December 2023 in North Gojmohol (average of 1,400 households per round)The present repository summarizes this information, organized as follows:1.1 Bimonthly survey (household): Panel dataset comprising 13 rounds of bi-monthly monitoring data at the household level (average of 1,400 households per round, total of 18,379 observations)1.2 Bimonthly survey (child): Panel dataset comprising 13 rounds of bi-monthly monitoring data at the child level (aged 5 to 16 at census) (average of 940 children per round, total of 12,213 observations)2.1 Periodic survey (household): Panel dataset comprising 5 periodic surveys (census, baseline, midline 1, midline 2, endline) at the household level (average of 750 households per period, total of 3,762 observations)2.2 Periodic survey (child): Panel dataset comprising 4 periodic surveys (baseline, midline 1, midline 2, endline) at the child level (average of 3,100 children per period, total of 12,417 observations)3.0 Balurmat - North Gojmohol panel: Balanced panel dataset comprising 558 households in North Gojmohol and 773 households in Balurmath, observed both at 2020 census and 2023 endline (total of 2,662 observations)4.0 Questionnaires: Original questionnaires for all datasetsAll datasets are provided in Stata format (.dta) and Excel format (.xlsx) and are accompanied by their respective dictionary in Excel format (.xlsx).Qualitative DataThe qualitative study was conducted in three rounds: the first round of IDIs and FGDs took place between December 2022 and January 2023; the second round took place from April to May 2023; and the third round took place from November to December 2023. KIIs were taken during the 2nd round of study in May 2023.The sample size by round and instrument type is shown below:RoundsIDIs with childrenIDIs with parentsIDIs with CMsFGDsKIIs1st Round (12/2022 – 01/2023)3026-06-2nd Round ( 04/2023 – 05/2023)3023-06053rd Round (11/2023 – 12/2023)26250307-The files in this archive contain the qualitative data and include six types of transcripts:· 1.1 Interviews with children in case study households (IDI): 30 families in round 1, 30 in round 2, and 26 in round 3· 1.2 Interviews with parents in case study households (IDI): 26 families in round 1, 23 in round 2, and 25 in round 3· 1.3 Interviews with community mobiliser (IDI): 3 CM in round 3· 2.0 Key informant interviews (KII): 5 in round 2· 3.0 Focus group discussions (FGD): 6 in round 1, 6 in round 2, and 7 in round 3· 4.0 Community mobiliser micro-narratives (556 cases)Additionally, this repository includes a comprehensive list of all qualitative data files ("List of all qualitative data+MC.xlsx").

Numerous studies have demonstrated that citizen science can provide valuable data on physical, chemical, and biological aspects of water quality. These studies mainly used quantitative methods. Qualitative approaches have been used to describe water quality conditions for much longer, but remain largely overlooked. The color, odor, and presence of aquatic vegetation or garbage influence human perceptions of river water quality, the use of the water, and thus the relation between humans and waterbodies. Yet, few studies have assessed how visual water quality indicators and local knowledge of water quality or sources of pollution can be used in citizen science projects, despite recent studies calling for greater attention to qualitative data sources. Qualitative data can enhance the interpretation of quantitative data and deepen the understanding of human-water relations. This paper evaluates qualitative water quality descriptors collected through the citizen science smartphone app CrowdWater and analyses how citizen scientists perceive and assess water quality in the app. Our analysis not only indicates that some citizen scientists already take quantitative physical–chemical measurements of water quality (even though this is not part of the app) but also that they frequently report their perception of water quality based on visual indicators and local knowledge. Our study makes a methodological contribution to traditional approaches in citizen science and water quality studies, highlighting the need to explore less frequently used methods and data sources and less frequently studied aspects of water quality.

This is an Annotation for Transparent Inquiry (ATI) data project. The annotated article can be viewed on the Publisher's Website. Data Generation The research project engages a story about perceptions of fairness in criminal justice decisions. The specific focus involves a debate between ProPublica, a news organization, and Northpointe, the owner of a popular risk tool called COMPAS. ProPublica wrote that COMPAS was racist against blacks, while Northpointe posted online a reply rejecting such a finding. These two documents were the obvious foci of the qualitative analysis because of the further media attention they attracted, the confusion their competing conclusions caused readers, and the power both companies wield in public circles. There were no barriers to retrieval as both documents have been publicly available on their corporate websites. This public access was one of the motivators for choosing them as it meant that they were also easily attainable by the general public, thus extending the documents’ reach and impact. Additional materials from ProPublica relating to the main debate were also freely downloadable from its website and a third party, open source platform. Access to secondary source materials comprising additional writings from Northpointe representatives that could assist in understanding Northpointe’s main document, though, was more limited. Because of a claim of trade secrets on its tool and the underlying algorithm, it was more difficult to reach Northpointe’s other reports. Nonetheless, largely because its clients are governmental bodies with transparency and accountability obligations, some of Northpointe-associated reports were retrievable from third parties who had obtained them, largely through Freedom of Information Act queries. Together, the primary and (retrievable) secondary sources allowed for a triangulation of themes, arguments, and conclusions. The quantitative component uses a dataset of over 7,000 individuals with information that was collected and compiled by ProPublica and made available to the public on github. ProPublica’s gathering the data directly from criminal justice officials via Freedom of Information Act requests rendered the dataset in the public domain, and thus no confidentiality issues are present. The dataset was loaded into SPSS v. 25 for data analysis. Data Analysis The qualitative enquiry used critical discourse analysis, which investigates ways in which parties in their communications attempt to create, legitimate, rationalize, and control mutual understandings of important issues. Each of the two main discourse documents was parsed on its own merit. Yet the project was also intertextual in studying how the discourses correspond with each other and to other relevant writings by the same authors. Several more specific types of discursive strategies were of interest in attracting further critical examination: Testing claims and rationalizations that appear to serve the speaker’s self-interest Examining conclusions and determining whether sufficient evidence supported them Revealing contradictions and/or inconsistencies within the same text and intertextually Assessing strategies underlying justifications and rationalizations used to promote a party’s assertions and arguments Noticing strategic deployment of lexical phrasings, syntax, and rhetoric Judging sincerity of voice and the objective consideration of alternative perspectives Of equal importance in a critical discourse analysis is consideration of what is not addressed, that is to uncover facts and/or topics missing from the communication. For this project, this included parsing issues that were either briefly mentioned and then neglected, asserted yet the significance left unstated, or not suggested at all. This task required understanding common practices in the algorithmic data science literature. The paper could have been completed with just the critical discourse analysis. However, because one of the salient findings from it highlighted that the discourses overlooked numerous definitions of algorithmic fairness, the call to fill this gap seemed obvious. Then, the availability of the same dataset used by the parties in conflict, made this opportunity more appealing. Calculating additional algorithmic equity equations would not thereby be troubled by irregularities because of diverse sample sets. New variables were created as relevant to calculate algorithmic fairness equations. In addition to using various SPSS Analyze functions (e.g., regression, crosstabs, means), online statistical calculators were useful to compute z-test comparisons of proportions and t-test comparisons of means. Logic of Annotation Annotations were employed to fulfil a variety of functions, including supplementing the main text with context, observations, counter-points, analysis, and source attributions. These fall under a few categories. Space considerations. Critical discourse analysis offers a rich method...

The set of tools and their alignment to objectives and sources of data.

Data consists of interview excerpts utilized for the analysis of a paper submitted for publication entitled "Exploring sources of insecurity for Ethiopian Oromo and Somali women who have given birth in Kakuma Refugee Camp: A Qualitative Study." Project Summary Background: According to the United Nations High Commissioner for Refugees, 44,000 people are forced to flee their homes everyday due to conflict or persecution. Although refugee camps are designed to provide a safe temporary location for displaced persons, increasing evidence demonstrates that the camps themselves have become stressful and dangerous long-term places—especially for women. However, there is limited literature focused on the refugee women’s perspective on their insecurity. This qualitative study sought to better understand the ways in which women experienced insecurity at one refugee camp in Kenya. Methods and Findings: Between May 2017 and June 2017, ethnographic semi-structured interviews accompanied by observations were conducted with a snowball sampling of 20 Somali (n=10) and Oromo Ethiopian (n=10) women, 18 years and older, who have had at least one pregnancy while living in Kakuma Refugee Camp. The interviews were orally translated, transcribed, entered into Dedoose software for coding, and analyzed utilizing an ethnographic approach. Four sources of insecurity became evident: Tension between refugees and the host community, intra/intercultural conflicts between the refugee community, direct abuse and/or neglect by camp staff and security, and unsafe situations in accessing healthcare both in transportation and in mistreatment in facilities. Potential limitations include nonrandom sampling, focus on a specific population, inability to record interviews and possible subtle errors in translation. Conclusion:In this study, we observed women felt insecure in almost every area of the camp, with no place in the camp where the women felt safe. As it is well documented that insecure and stressful settings may have deleterious effects on health, understanding the sources of insecurity that are faced by women in refugee camps can help to guide services for health care in displaced settings. By creating a safer environment for these women in private, in public, and in the process of accessing care in refugee camps, we can improve health for them and their babies. Data Generation Sampling:The population of the study was limited to Somali and Oromo women over the age of 18 with no upper age limit who had given birth at least once in Kakuma Refugee Camp. Due to both the infeasibility of collecting a random sample within the camp and the sensitivity of the topic, participants of interviews were selected through a snowball sampling approach through contacts used in previous research, including a hired mobilizer with previous experience in similar research. The mobilizer was responsible for recruiting women fitting the criteria outlined above who were willing to talk about their pregnancy experiences and stressors. Interviews:The interviews lasted between 30-60 minutes each. They were conducted in a place of each participant’s choosing, typically their own homes, with the assistance of a translator. The interviews were all carried out by the same female researcher (AL) and the same female translator. The researcher was a trained interviewer with previous interview experience in rural settings and was enrolled in the Master of Science in Global Health Program at the University of Notre Dame during the time of study. The translator was a refugee of Oromo Ethiopian descent living in Kakuma Refugee Camp herself. Twenty interviews were conducted in total. After the initial interviews, twelve of the twenty interviews were identified that required further clarification. These twelve interviews were repeated with the corresponding interviewee to cross-verify that the relevant meaning had been captured and to expand details within the respondents’ interviews. Children were usually present during the interviews, and at times, men were also present during the interviews. The researcher asked the questions in English and the translator translated the question as close to verbatim as possible for the participant. Due to IRB constraints and in order to maintain rapport with the participants, interviews were not recorded; however, detailed and verbatim notes from the translator were taken during the interview and typed up within twenty-four hours. Data Analysis Analysis: One researcher (AL) developed a codebook organically through reading over interviews and notes. Typed and de-identified interview notes were uploaded to Dedoose a qualitative analysis program, and given codes and sub-codes from the aforementioned codebook. Codes included insecurity, health, pregnancy experiences, healthcare facilities, stressors, income, coping, and support. The subcodes of insecurity include general insecurity, host community, refugee community, healthcare facilities,...