Science topics: Research Social Validity
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Research Social Validity - Science topic

Evaluation of the degree of acceptance for the immediate variables associated with a procedure or program designed to change behavior. This includes the social significance of the goals of treatment, the social appropriateness of the treatment procedures, and the social importance of the effects of treatments.
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What is the validity of the use of reliability and validity criteria in content analysis? If that is systematically true, what method is appropriate?
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Hi Khalid for inter-coder reliability test, there are different formulas to use, like Scott's Pi, Krippendorff's alpha, Holsti's coefficient and Cohen's kappa. I recommend an online content analysis platform DiVoMiner® that you can do the reliability test with any of the above-mentioned formula. And there is free version if you don't have a large amount of data. Here are some video guides for every step: https://www.divominer.com/en/blog/2022/07/07/the-six-key-functions-of-divominer-2/
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Dear colleagues, dear participatory-action research practitioners,
I would like to open the discussion on the criteria for evaluating participatory research (whether it is action-research, participatory action research, CBPR, etc.).
How do you evaluate participatory research projects that are submitted for research grants and/or publications (papers) ? Do you apply the same criteria as when you evaluate non-participatory research projects? Or have you developed ways to evaluate non-scientific dimensions such as the impact of this research on communities, the quality of connections between co-researchers? And if so, how do you proceed ?
Thank you in advance for sharing your experiences and thoughts.
Pour les collègues francophones, n'hésitez pas à répondre en français ! Quels sont les critères que vous utilisez pour évaluer des projets de recherche participative ? Utilisez-vous les critères d'évaluation scientifique que vous appliquez aux autres types de recherche ou est-ce que vous avez des critères spécifiques et si oui, lesquels ?
Baptiste GODRIE, Quebec-based social science researcher & participatory action research practitioner
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the Health Research Board in Ireland has adopted the following approach to its evaluation of grant applications
...Until recently, public reviews have been used solely to provide direct feedback to applicant teams so they could take that feedback on board, and thereby gain experience of incorporating Public and Patient Involvement (PPI) into their research proposals.
From now on, integrating the public reviews into panel decision making will be the norm for calls which undergo public review, and this step is in line with our published plans to strengthen PPI input into HRB decision-making processes.
In addition to feedback on the scientific aspects from the international peer-reviewers, the HRB receives written feedback on the quality of Patient and Public Involvement (PPI) from two public reviewers for each application ahead of the panel meeting.
All of the reviewers’ comments (both public and scientific) are passed on to the applicants, who have the opportunity to respond. The reviews and the related applicant responses are made available to the panel before they meet....
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Pandemic has a huge impact on everything including human, organizations and government policies. If a research is designed before the on going pandemic it was assumed that when the data would be collected the usual business would be the same, however, it has been changed enormously affecting the normality. Would a model constructed before the pandemic will still be relevant, explaining the variation. Or it requires a different model incorporating the pandemic factor to better explain the variation?
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Data collection will be straightforward even for business research, as most people, customers, and managers are using online resources. Also, people are more familiar with the onoline tools, hence a higher chance to participate in survays, discussion, etc. The cost is also going to be reduced and from the participant perspective, most of the participants feel free to attend any meeting as they need not worry about the things they faced during a physical meeting
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The h-index is an author-level metric that attempts to measure both the productivity and citation impact of the publications of a scientist or scholar. The index is based on the set of the scientist's most cited papers and the number of citations that they have received in other publications. I want to know that in what way it will help a researcher ?
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Hindex numbers provide reasonably good information for the excellent work consistency of researchers.
For example, I currently have 8 Hindex (excluding self-quotes). This means that each of the eight has been cited at least eight times in my treatise. However, none of my publications (one author's treatise) states that there are 33 citations. The other author's treatises have been cited 26 times, joint papers have been cited 30 times, and so on. I expect 2020 Hindex to be 10 times (excluding self-quotes).
To have a relatively high Hindex, the average citation rate per treatise is about the same as the Hindex value.
So
We do not compensate for unpaid treatises. While some researchers can spend several years on research treatises, other researchers in the same field produce several treatises in the same period. The latter group can have a much higher hintex for more treatises.
Does not distinguish between one author's treatise and multiple author's treatises. Another prank on the definition.
Does not distinguish between citations and actual developments of the subject, review papers and books. The latter two are generally the majority of people. This is why people with books and review papers generally have a lot of people and potentially high hints (but not always).
It is impossible to compare Hindex for researchers in other areas of human knowledge.
You can use self-quoting to increase the number of posterior words using artificial methods that are not ethically sound. This is why many prestigious institutions are only considering hindex. Exclude self-citations. Their argument is simple. Your own research is evaluated when it is recognized by others.
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Hi everybody,
I was running a model in SmartPLS 3.
1. 40 indicators' outer loadings (out of 101 indicators) are between 0.4-0.7. Not all of them are too low.
2. AVE results for 5 variables (out of 11) are below 0.5.
3. Fornell-Larcker criterion for two correlations is not established.
4. All HTMT results are below 0.85.
According to Hair (2011): Generally, indicators with outer loadings between 0.40 and 0.70 should be considered for removal from the scale only when deleting the indicator leads to an increase in the composite reliability (or the average variance extracted;) above the suggested threshold value.
Here are the results after eliminating 13 indicators with the lowest outer loadings:
1. All the AVE becomes more than 0.5.
2. Fornell-Larcker criterion isn't still established for two correlations.
4. On the other hand, the results for HTMT changes, and the HTMT for one correlation is upper than 0.9.
I am aware that the elimination of items purely on statistical grounds can have adverse consequences for the construct measures’ content validity (e.g., Hair et al. 2014). Therefore, researchers should carefully scrutinize the scales (either based on prior research results or on those from a pretest in case of the newly developed measures) and determine whether all the construct domain facets have been captured. At least two expert coders should conduct this judgment independently to ensure a high degree of objectivity (Diamantopoulos et al. 2012).
I do not know about the theoretical support for eliminating some indicators. I would be really thankful if you'd help me what I can do in this situation.
Many thanks
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Therefore, researchers should carefully scrutinize the scales (either based on prior research results or on those from a pretest in case of the newly developed measures) and determine whether all the construct domain facets have been captured.
Yes, this is an important point because statistical grounds alone may not be sufficient. You can justify retaining constructs based on theoretical grounds even though it is not statistically significant.
The theoretical grounds will depend on your research questions and the literature review of other people's study and what their findings are like. This is not provided above.
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Hi
A school in Jordan is doing an impact study on its alumni. The variables are a list of traits and values (innovation, leadership, empathy, etc…). I’m responsible for preparing the questionnaire.
My methodology is:
1- For each value/trait, find an inventory or scale that measures it.
2- Choose three items from the inventory/scale.
3- Combine the three items from all the inventories/scales to create the new questionnaire (about 60 items).
I need an expert who can review the final questionnaire and give an approval and recommendations to improve the questionnaire.
Any volunteers?
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Do you mean someone has already reviewed it or it is done and needs to be reviewed? if it needs a review, you can send me. You're welcome.
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Thinking in terms of a social setting such as a dance, a concert, a meal, if an experiment were to be designed in such a way, how can the method be validated? Similarly, what role would reliability play in an experiment set in a social setting? How can you recreate social settings for further empirical study?
I would love to read some examples of studies if you are familiar with any!
Many thanks.
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You asked about the validity and reliability. These are the critical points. If you chose your subject from very dissimilar groups and settings there is a greater chance to get reliable data as well as external validity which is important for researcher who want to repeat the experiment. Check this out if it gives you advice: https://pdfs.semanticscholar.org/6462/54a1698a66aacb6eceb66c126309c3311997.pdf
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Can I do an Incremental validity analyses with variables drawn from the same raw data? For example, imagine a researcher is interested in how a person's sociability is related to their mental well being. As a data source, the researcher records group conversations among 10 people interacting in a room. Imagine that a standard way to measure sociability is to simply total the number of "chats" made by a participant in the discussion. But lets say I wanted to test if actually a better (i.e., having stronger predictive validity) way to measure sociability is to take the proportion of a person's chats, relative to all other chats made in the group. Could I do an incremental validity analysis where I treat the total number of chats as one variable and the proportion of chats as another? And if not, what would be the proper way to establish the superior predictive validity of the proportion based measure of sociability?
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Technically in an OLS as the residual error will be accounted for, however I zero-order correlations will inflate your estimate.
Hope this helps,
Matt
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Hello everyone,
I'm looking for some advice on my study design. In short, I want to study the impact of mobile VR on a specific skill in an engineering course (are students who study with VR do better as measured by a pre-post test + psychological assessments, such as self-efficacy?). I have 3 classrooms (undergraduate college level), two of which will have about 30 students and one - probably around 15. The semester- long VR intervention is integrated with the existing curriculum (which means we have certain constraints on the order of topics that we do in VR). We have overall 10 modules, all of them can be potentially taught in VR, but we can also teach less than 10. So the treatment is the use of VR (as opposed to using 2D materials for instruction).
Now, the problem is - I would typically use a between-subject design, comparing Classroom 1 to Classroom 2. However, I'm not sure what to do with Classroom 3 AND the problem is that one classroom is likely to be formed by students from a non-engineering program (who tend to be in the same class due to their scheduling), while the other classroom will have engineering students. In other words, there is a problem of baseline equivalence of the two conditions (if one class does VR and the second class does 2D).
If I use within-subject design, then there is a big problem with counterbalancing; some modules have to go first, and alternative VR vs. 2D in other modules between classes causes problems in interpreting the unique contribution of the VR in the outcome variable (which is a test measuring the skill of interest) because the test can only be administered twice (due to the practice effect).
Which design would be more appropriate? Between-subject design is what I would do, but then there is the selection threat to the internal validity; in the within-subject design, teasing apart the effect of VR as opposed to the order of topics and the content of topics is almost impossible. I would appreciate any thoughts about this issue.
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My initial suggestion would be:
ignore classroom 3.
classroom 1 (VR used) determine post - pre level of skill for each class member; calculate mean and SD of post - pre across all students.( M1)
clasroom 2 (no VR used) determine post - pre level of skill for each class member; calculate mean and SD of post - pre across all students .(M2)
do t test of difference between M1 and M2
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what is nomological validity? can anybody explain it in detail?
thanks in advance
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Hi,
The term "nomological" is derived from Greek and means "lawful". Briefly, the nomological network was Cronbach and Meehl's view of construct validity (Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological bulletin, 52(4), 281). That is, in order to provide evidence that your proposed measure has construct validity, Cronbach and Meehl argued that you had to develop a nomological network for your measure. This network would include the theoretical framework for what you are trying to measure, an empirical framework for how you are going to measure it, and specification of the linkages among and between these two frameworks.
Hope this helps!
Best regards,
Qin Xiang
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When it comes to conducting quality research and effecting meaningful projects, it indeed becomes crucial to understand the various parameters which should be considered while finalizing the topic of the project as unlike a short-term assignment like writing a research paper, the dimensions of the project might change mid-way on the virtue of the sheer scale and time-factor associated with the same. Question is, how the same could be ensured, that is, finalization of an effective topic for a research project? The question has been asked with reference to executing a project in management and social sciences
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Dear Amit,
Following questions may be useful for finalizing a topic:
•Is it short?
•Is it clear?
•Is it relevant to the field of interest to the researcher?
•Is it representing what is being proposed to study or what has been studied?
•Is it not a sentence?
•Does it have a substantial body of literature associated with it?
•Has it captured your interest seriously?
Best wishes!
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I'm trying to develop a scale to measure effects of social networking sites usage on children's attitudes towards family relationships, do you have ideas?
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 thanks a lot, Rafael