# Form: Preregistration Template for Qualitative and Quantitative Ethnographic Studies (v0.93)

This vignette shows the Preregistration Template for Qualitative and Quantitative Ethnographic Studies form. It can be initialized as follows:

initialized_preregQE_v0_93 <-
preregr::prereg_initialize(
"preregQE_v0_93"
);

After this, content can be specified with preregr::prereg_specify() or preregr::prereg_justify. To check the next field(s) for which content still has to be specified, use preregr::prereg_next_item().

The form is defined as follows (use preregr::form_show() to show the form in the console, instead):

preregr::form_knit(
"preregQE_v0_93"
);

## Preregistration Template for Qualitative and Quantitative Ethnographic Studies

### Instructions

#### Aims

A preregistration is a way to design your research project before you begin and to document your decisions, rationale. A template such as this one can be employed to think about what you want to do and how, and subsequently, if you wish, you can submit the finished preregistration to a registry, such as OSF’s (https://osf.io/registries). This template was developed to aid the preregistration of quantitative ethnographic studies, but due to its modular nature, it can be employed for qualitative studies as well.

#### Instructions

Fill it out. If any items don’t make sense for your project or you have not made a decision about them at this point, feel free to leave them blank or delete them.

Submit it. This webpage has detailed instructions on submitting a preregistration to OSF: https://help.osf.io/hc/en-us/articles/360019738834-Create-a-Preregistration

Please note: When you select a registration form, be sure to choose “Open-ended registration” if you are using this particular template.

### Sections and items

#### Section: Preparation

Title
title
Tentative title of project
Contributors
contributors
Please list the contributors and their roles. For the latter, you can use CRediT (Contributor Roles Taxonomy), for example.
Research aims
research_aims
Please state the aims of your research. Your aim may be different across different domains (e.g.: knowledge generation, policy development, community resourcing). If so, specify your aim for each domain that is relevant for your study.
Aim type
aim_type
Exploratory projects may not have any hypotheses or even specific research questions, their aim is to explore a general topic, community, or practice. Confirmatory studies have specific hypotheses and/or research questions, theories that are either proven or disproven. Other aims than “Exploratory” or “Confirmatory” may be specified, too, but in that case it is recommended that they are defined, too.
Research question
research_question
Please state your research question(s). Research questions are subject to change and/or elaboration. Some beneficial times to review these questions may be at, e.g.: 1) preregistration, 2) after the first instances of data collection, 3) when discussing the first results, 4) when starting write-up of findings
Theoretical framework
theoretical_framework
Please specify the role of theory in your research design. Are you planning to work primarily inductive (theory use mainly for purpose relevance of the research), inductive with deductive aspects (theory development using open theoretical concepts) or primarily deductive (mainly refining existing theory)? Some examples are “Primarily inductive”, “primarily deductive”, and “inductive with deductive aspects”.
Please elaborate if your research is conducted from a certain theoretical paradigm (for example, social constructionism, positivism, post-positivism, critical theory, etc.). How will this paradigm influence your research?
Basic data
basic_data
Please select whether you are working with original data, pre-existing data, or both.
Anticipated duration
anticipated_duration
How long do you imagine the study taking, from its preregistration to the final write-up of results?

#### Section: Sampling

Sampling strategy
sampling_strategy
Please describe your sampling strategy. Please provide a short rationale for why you selected this type of strategy. Describe inclusion and exclusion criteria. Some examples are convenience sampling, purposive sampling, snowball sampling, theoretical samlping, maximum variation sampling, proportional quota sampling, non-proportional quota sampling, random sampling, and mixed sampling.
Recruitment
recruitment
Please describe from where you are recruiting the participants for your study and how you will be getting in touch with them.
Sample size
sample_size
Planned number of participants (or providers of data or “cases”)

#### Section: Data collection

Data collection method
data_collection_method
Please indicate the data collection procedure(s) you will use. Some examples are “Semi-structured interview”, “Structured interview”, “Focus group”, “Enabling technique”, “Self-report”, “Field notes”, “Diary”, “Participant observation”, “Observation”, “Archival research”, “Log file”, and “Survey”.
Type of raw data
raw_data_type
In what form will you be collecting data for your study? Some examples are audio, video, audio-video, text, and numerical.
Data providers
data_providers
Your study may be conducted with individuals but data is recorded from a dyad or a group; individuals may not be considered separately (some examples are individual, dyad, group (=3), individual and group, etc). Thus, please indicate who/what you consider data providers in your study.
Data collection tools
data_collection_tools
Please describe or upload the tools, instruments or plans you will use in collecting or generating your data. Some examples are using a topic guide, interview structure, questionnaire, focus group guide, observation scheme, standardized prompts, protocol, and archival search interfaces and queries.
Stopping criteria
stopping_criteria
Please describe the criteria or rationale for stopping data generation or collection. These can differ for various aspects of the project. Some examples are data saturation (in that case, please explain how you operationalie this), when inclusion criteria are satisfied, resource constraints (e.g. time/funding), and when the analysis has produced an enriching answer to the research question(s).

Metadata = data about the data collection process or the data itself (interviewer, date of interview, timestamp, etc.)

Attributes = characteristics of data providers (e.g., age, sex, education of cases)

#### Section: Coding

Type of coding
type_of_coding
Please indicate whether you will be developing your own codes (inductively) or adopting codes from a previous study or theoretical framework (deductive). You may be using a combination of these, e.g., inductively developing codes through test coding and then deductively applying the final code structure.
Process of coding
process_of_coding
If there is more than one rater, are they coding with the same or a different set of codes? For example, all raters may employ different codes, all raters can employ the same codes, or it can be a mix.
Automated coding
automated_coding
Are you using automated or manual coding or a combination of both?
Code development
Please describe in detail the stages of code development. If applicable, you may upload different code structures developed before triangulation, as well as anything in the process of creating the final version.
Code structure
code_structure
Describe the final code structure, if you have it at the time of preregistration: If you are applying your codes deductively, how many levels of abstraction do you have? How many codes are at the lowest level? (If possible, please upload your final codebook with your preregistration or to your repository)
Classifiers
classifiers
Are you using classifiers for automated coding? If so, please elaborate your considerations in developing your classifiers. Provided you have them at the time of preregistration, please list your classifiers, upload them, or indicate that you will have them in your repository.
Types of raters
types_of_raters
Who or what is performing the coding? For example, human only, computer only, or human and computer.
Number of raters
number_of_raters
How many researchers are performing coding? If automated coding is (also) being used, please include the computer as a “rater”.
Coding tools
coding_tools
Are you planning on using any specific tools for performing coding? (e.g.: interface for the Reproducible Open Coding Kit (iROCK), nCoder, NVivo, Atlas.ti)
Inter-rater reliability
inter_rater_reliability
Are you planning to calculate IRR? (Can be simple, e.g. “yes”, “no”, “not applicable”, etc)

#### Section: Segmentation

Smallest unit of segmentation
smallest_unit_of_segmentation
Define the smallest meaningful unit of segmentation (one sentence, one log entry, one second, etc.)
Other levels of segmentation
other_levels_of_segmentation
Define any other level(s) of segmentation (intermediate, highest), for example: a topic, psychological proximity, recent temporal context, utterances from one participant during one session, an interview transcript, a focus group session transcript, log entries within the duration of 24 hours, observations from one group performing one task, etc.
Type of segmentation
type_of_segmentation
Please indicate whether you will be performing segmentation manually or automating it or a combination of both. This answer may differ depending on level of segmentation; please indicate separately for each level of segmentation you plan to perform. (e.g. “automated”, “manual”, “automated and manual”, “not applicable”, etc)
Coding and segmentation level
coding_and_segmentation_level
Please indicate on which level(s) of segmentation you will be performing coding. You may want to distinguish between coding a narrative and designating attributes or metadata.
Operationalization of source (codable or coded file)
operationalization_of_source
What data will your files contain? (e.g.: one interview, a series of interviews, all think-aloud entries from a participant)

#### Section: Analysis

Approach
approach
Please specify what type of analysis you are planning on conducting. (e.g.: Narrative analysis, Interpretative phenomenological analysis, Grounded theory, Thematic analysis, Content analysis, Process tracing, Comparative analysis, Discourse analysis)
Process
process
Please describe the process that your analysis approach requires and how you see this process manifesting in your study.
Data transformation
data_transformation
If you intend to do so, describe how you will change the grouping or representation of your data in order to perform analysis (e.g.: a higher order grouping of sources, cases, or attributes).
Analytical tools
analytical_tools
Are you planning on using any tools to perform analysis? If so, please specify them here. (e.g.: the Reproducible Open Coding Kit (ROCK), Epistemic Network Analysis (ENA), nCoder, Rho, Topic modelling)

#### Section: Epistemic Network Analysis (ENA)-Specific

ENA unit
ENA_unit
What will constitute “units”, i.e., for what will you be generating networks? If you know this ahead of time, please indicate it here.
ENA conversation
ENA_conversation
What will constitute “conversation”, i.e., how do you plan to aggregate (bounded sets of) utterances? If you know this ahead of time, please indicate it here.
ENA stanza window
ENA_stanza_window
How will code co-occurrences be accumulated? If you know this ahead of time, please indicate it here. For example, “moving window”, “whole conversation”, or “infinite stanza”.
ENA moving stanza window
ENA_moving_stanza_window
If you will be using a moving stanza window, what will be its length? If you know this ahead of time, please indicate it here along with a justification or rationale. If you don’t know, how do you plan on deciding its size?
Edge weights
edge_weights
What will the edge weight threshold be set to? Will there be any changes in the analytical process or among various networks? If you know this ahead of time, please indicate it here.
Means rotation
means_rotation
Will means rotation be performed? If you know this ahead of time, please indicate it here.
Assessing connections
assessing_connections
What constitutes a strong or weak connection? How will this be determined? If you know this ahead of time, please indicate it here.

#### Section: Positionality and Credibility

Positionality
positionality
Feel free to reflect on your relation to or association with the studied phenomenon and your position in the research setting/field, including your academic/personal standpoints, assumptions and values. In addition, if there is a potential conflict of interest that can arise, you may want to report that here.
Credibility strategies
credibility_strategies
Please indicate any strategies you will be employing to ensure better credibility of analyses and conclusions. (e.g.: member checking / respondent validation, triangulation with other data sources, asking different researchers to analyze the data, inter-rater reliability, negative case analysis, peer debriefing, cross-checks for rivalling explanations, bringing in an ‘auditor’, reflexivity)

#### Section: Open Science

Repository
repository
Do you currently have or are you planning to create a repository for making any aspects of your research process open (preregistration, data, code development, codebook, analysis, etc.)? If so, please indicate it here.