Challenges in research data collection and mitigation interventions

This paper investigated the challenges that researchers in a health sciences university can experience, and ways to counterbalance the negative effects of these challenges. Focus was on the extent to which gatekeepers on higher education institutions (HEIs) can restrict research, and the way natural sciences researchers often experience gatekeeper biasness on denying them access as compared to the way health sciences researchers are treated. The method compared experiences of researchers for Master of Science (MSc) degrees in selected science subjects, and the projects undertaken by health sciences students. All the studies were based on students on campus as research subjects. The MSc ones were for students who were already academics teaching on campus. All the proposals received clearance certificates from the same ethics committee. Upon requiring the HEI registrar to grant permission to use the student as study participants, the health sciences were granted permission and the names of the students. For the science academics, they were denied permission to the student numbers, which were needed to request individual students to make on decisions whether they wanted to participate in the studies or not. Gatekeeping weaknesses were explored, and lawful interventions were used to collect research data. It was observed that in the science academic divisions of HEIs that are dominated by the health sciences, gatekeeper unfairness and power could offset creativities and innovations initiated by researchers. Recommendations have been made to limit this power. © 2024 by the authors. Licensee SSBFNET, Istanbul, Turkey. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).


Introduction
Most applied research use data to create information that is needed to answer research questions (Brown & Williams, 2019).However, in some research studies, Ellis (2023) explains that there are times when data collection becomes a nightmare with gatekeepers making it difficult to access the targeted responses, or the targeted respondents refusing to participate.If data in a data-reliant study cannot be collected, then a proper study cannot be undertaken.This means that the idea or ideas that were generated to undertake the study are wasted (Treffinger et al., 2023).The time to prepare the proposal has also been wasted.Other losses may be the resources and equipment used during the proposal development.There are also emotional and psychological effects that may not be notable, but there are possibilities that they go a long way to keep innovative people out of action due to the reaction they receive when they want to initiate change.
Generally, studies that pass the proposal stage and receive clearance certificates are worthy of being undertaken.They have value as observed and adjudged by the peers and reviewers who are usually experts in the field.That means, a proposal that goes through a peer-review process and gets accepted, is worthy of producing a research that can make a difference in people's lives, or that can add value to some aspects of development (Paltridge, 2017).Therefore, if a research proposal is accepted, and the clearance certificate is issued, then logically, a study based on that proposal should be undertaken.Failure to undertake that study is a lost opportunity.Development in the modern day depends on research, as the modern day is the information era.Data for research are often key to obtaining information.
Limiting conditions of entry: Another limitation could be a gatekeeper restricting on the conditions of entry to the premises in which the study takes place.When times of data collections are limited, the researcher has to collect data as stipulated.It can be the number of days that are being reduced, or even guidelines of undertaking the collection, and thus changing the initially proposed study design.
Limiting access to data and respondents: Some gatekeepers restrict the researchers on the amount of data that they can collect, and/or on the numbers of participants to use.These may lead to insufficient sample sizes, and the inadequacy of information obtainable.
Restricting the scope of analysis: Every research starts with a planned scope that is sufficient to address the research questions.Some gatekeepers would restrict the scope of the study.

Retaining rights and privileges with respect to publication:
The gatekeepers can have a clause that compels the researchers to submit rights and privileges to them, such as intellectual property.

Data quality issues
It is typical of raw data to include errors, inconsistencies and other issues.Data collection measures are designed to avoid or minimize such issues, but they are not immune to inaccuracies, and collected data usually needs to be put through data profiling to identify issues and data cleansing to fix them.

POPIA
Protection of Personal Information Act (POPIA) is South Africa's data protection decree signed into law in November 2013 and commenced on 1 July 2020 with a one-year grace period to comply ending on 30 June 2021 The act upholds the protection of personal information processed by public and private bodies, provide for the rights of persons regarding unsolicited electronic communications, and regulate the flow of personal information in the country.It sets the standards for accessing and processing personal information, and places several obligations on the responsible party that is responsible for the lawful processing of personal information (Bronstein & Nyachowe, 2023).

Sampling issues
Sampling is a basis of many research methodologies that refers to selecting a subset of a population for study (Das, Jha, Sahu et al., 2022).However, the task of sampling has potential downsides such as sampling bias and inadequate sample size: i.

Research bias:
Research aims for a sample that represents the larger population, but even smallest of deviations can skew the research outcomes. ii.
Inadequate sample size: Sample size matter, as too few participants risk statistical insignificance.Determining an optimal sample size requires consideration of both the study scope and the resources available.

Data Accuracy and Reliability
Using inaccurate and unreliable data is worse than not doing research as resources and time are wasted and the results will be of no use to development (Chmielewski & Kucker, 2020).Accuracy and reliability reign supreme in research because errors and inconsistencies in the data cannot be of any beneficial use.

i.
Measurement errors: lack of standardization or validation of data collection instruments or poor recording of an interview can lead to mistakes.Even small mistakes can lead to major inaccuracies and regular standardization and training can mitigate such errors. ii.

Inconsistency in collection:
The case of two researchers observing the same event but noting down slightly different details can be a worry.These inconsistencies, even though ostensibly minor, can result in significant data disagreements. iii.
Recall bias: Specifically in relation to retrospective studies, recall bias is when participants' occasionally faulty memory of past events.Any bias can falsify historical data, necessitating the use of prompts or alternative data sources.

Data Integrity
Data for research should be honest and authentic because data without integrity lose essence (Jieyang, Kimmig, Dongkun et al., 2023).The cases may be some data missing, entries being duplicated and some values lying far away from the bulk of the data.These refer to: i.
Missing data: Incomplete datasets can pose the nuisance of data analysis.Data incompleteness may occur as a result of possibilities starting from participant withdrawal to malfunctioning sensors.A variety of reasons can lead to gaps in data.However, spaces can be handled with advanced statistical methods such as imputation techniques. ii.
Duplicate entries: Duplicating data lead to redundancies in data sets, but one possible drawback is to overemphasize certain data points to distort results.

iii.
Outliers: Outliers are data anomalies, which are data points that lie significantly from the majority of data.Outliers can sometimes represent genuine phenomena, but they can also be inaccuracies that skew averages and other metrics

Ethical Considerations
Modern research does not allow researches that lack morality.Aluko-Arowolo, Lawal, and Adedeji et al. (2023) point out that in an interconnected digital world, ethical considerations are compulsory, and they refer to: i.
Privacy concerns: Data breaches become increasingly rife, personal data sacrosanctity becomes continually threatened.Protection of data, especially sensitive information, is both a technical responsibility and a moral obligation. ii.
Informed consent: The requirement of respondents to fill in consent forms is based on the principle of respect for autonomy.Research participants need to be totally informed about the purpose, procedures, risks, and benefits of study. iii.
Potential data misuse: When data land in the wrong hands, they can be used to attach.Hence, ethical considerations should use extends beyond the collection phase, encompassing storage, analysis, and even post-study disposal.

Practical Challenges
There are times when the logistical aspects of data collection present some challenges preventing data collection (Sadoon, Venkatadri & Ghasemi, 2023;Veena & Gowrishankar, 2023): i.
High costs: Budgets can be strained when instruments of high-quality are used, trained personnel are recruited/hired, and robust data storage solutions are implemented. ii.
Time-consuming processes: Large-scale data efforts can extend over an unjustly long time.In this case interventions may lead to interim reviews and adjustments. iii.
Geographic or accessibility limitations: Remote areas, conflict zones, or restrictive regimes can pose formidable barriers to data collectors.

Technological Challenges
In this technology-driven age, according to Kim, Joines and Feng (2023), there may be technology-specific challenges related to collecting data: i.
Data storage issues: The emergence and widespread availability of large and complex data sets (or Big Data) lead researchers to struggle with storing massive amounts of information efficiently and cost-effectively.In order to manage these massive datasets, it is necessary to implement effective data collection methods.ii.
Interoperability: Different systems, products, or organizations are expected to work together and exchange information without a glitch.However, integration of data from dissimilar systems, each with its unique format and structure, can be a very difficult and enormous task. iii.
Data security concerns: Cybersecurity fears that include scams from hackers to phishing scams pose insistent challenges that necessitate security measures that are cutting-edge.

Methodological Issues
The methodology is the outline of any research (Bus, Monteiro-Soares, Game et al., 2023), but is not safe or free from challenges: i.
Poor survey design: Some factors that compromise data quality are confusing phrasing of questions, leading questions, or even the length of the survey, as these can influence participants' responses.ii.
Observer effects: Sometimes individuals modify an aspect of their behaviour in response to their awareness of being observed (the Hawthorne effect).iii.
Mode effects: The medium of data collection can influence outcomes.For instance, online surveys might attract a younger demographic compared to phone interviews.

Cultural and Linguistic Barriers
Cross-cultural research can enlarge challenges that confront data collection: i.
Translation inaccuracies: Verbatim translations from language of data collection participation to language used in the study can miss cultural hints and tones, leading to misinterpretations (Eisenhardt, 2000). ii.
Cultural misunderstandings: Norms and standards differ across cultures.A sign that is regarded to be respectful in one culture may appear offensive in another, impacting interpretation of data.

Changing Environments
When the environment changes, data collected about or around it may be no more relevant or applicable (Hirose & Creswell, 2023).That is, dynamic global settings mean that appropriate data of current may become outdated in future, including a near future.Other factors that can affect the relevance and context of data are political disruptions, economic recessions, and technological innovations.

Dependence on Third Parties
Secondary data may miss some points of validity, mainly because they were collected for other studies (Toll, Janssen, Vergouwe et al., 2008).The same can occur with outsourcing of data collection, or reliance on third-party data sources as they can present uncertainties, from legitimacy concerns to timing inconsistencies.As a result, it is crucial to establish reliable collaborations and rigorous data verification processes.

Interventions for Collecting Data
An intervention is an action or measure that is used to address or improve a situation of difficulty (Patuawa, Sinnema, Robinson et al., 2023).When gatekeepers block data collection for research, numerous possible interventions can be considered, which aim to engage gatekeepers, mitigate bias, and optimize decision-making.Some possible interventions are to engage organizations and their members; participant observation; negotiate access; and obtaining buy-in (Vinkenburg, 2017).They are explained next.
Engage organizations and their members: This involves engaging organizations, and their members up and down the ranks to question their own and others' intensely held assumptions and biases.
Participant observation: This is a more organic systemic intervention that puts less pressure on precious resources.It involves engaging in participant research grants, prizes, performance evaluation, promotion or tenure decisions, and appointments to optimize decision making.
Negotiate access: Researchers can negotiate access with gatekeepers in a complex and dynamic manner, recognizing the important roles that gatekeepers play in accessing hard-to-reach populations.
Obtaining buy-in: Researchers can sell the value of their research to gatekeepers and make them wish to support them by explaining how the research can contribute to knowledge and help the organization.

Intervention Media
Social medium: Social media can help bypass gatekeepers in several ways.Social media can allow them to bypass traditional media gatekeepers and directly reach their audience, especially in developing countries (Arjomand, 2021).According to Altschuler (2021), social media can be used to engage with gatekeepers through platforms like LinkedIn, where in-mail and direct messages can be effective in reaching decision-makers.Another way to avoid the gatekeeper is to ask for referrals from someone who already knows or trusts you, which can be facilitated through social media and professional networks like LinkedIn.Moreover, the internet and social media have made it feasible to go around traditional gatekeepers, and grow without necessarily having to rely on them.

Persistent follow-up:
There are cases where gatekeepers deliberately delay positive responses on giving researchers the permission to undertake the data collection.In other cases it may be due to work overload, and gatekeepers struggle to find time to respond or they even forget.Whichever way, when gatekeepers do not assist with the passage to the data collection stage, especially when they do not offer updates, one way can be to overbearingly ask for updates, regularly (Cheema, Khan, Liaqat et al., 2023).Use of email helps to track and trace the correspondence.If necessary, copying supervisors or superiors of one's own and those of the gatekeeper can embarrass a gatekeeper who deliberately sabotages the researcher's progress.In other cases, when the superiors realize the existing struggle of the subordinate, they may offer help to enable the permission letters to be issued for data collection.
Persuasive appeals: Persuasive appeals are methods of persuasion used in writing and speaking to convince an audience.The three main persuasive appeals are ethos, pathos, and logos (Gagich & Zickel, 2018;Higgins & Walker, 2012;Leeds, 2003).The case of ethos refers to the ethical appeal, which involves convincing the audience of the author's credibility or character.It is achieved by demonstrating good sense, good will, and good character.Pathos is the emotional appeal, which aims to evoke an emotional response from the audience, such as fear, anger, or sympathy.Ethos is the logical appeal, which involves using reason and evidence to support an argument.In order to persuade an effectively, according to Demirdöğen (2010, all the three appeals should be utilized.Opening with ethos would establish credibility, with logos following to build the argument, and closing with pathos to appeal to the audience's emotions.

Some Specific Examples
This section provides specific examples to illustrate natural science researchers in health sciences data collection.Natural science researchers in health sciences tend to face various challenges when collecting data.These challenges highlight the complexity of data collection in health sciences research and the need for innovative solutions to ensure accurate, secure, and comprehensive data collection processes.Mihai et al. (2022) insinuate some of the specific primary challenges examples that include shattered data, everchanging data, privacy and security regulations, expectations of the patient, lack of quality assurance parties.They are: Shattered data: Health care data originate from miscellaneous sources with varying formats, making assimilation and drawing out extremely difficult.This results in disjointed and often incomplete health profiles, hampering insights into patients' health journeys.
Ever-changing data: Patient and clinician movements, organizational changes, and evolving treatments make it hard to maintain complete and current health data.This impacts patient experiences and business sustainability.
Privacy and security regulations: Ensuring data security is crucial in healthcare due to regulatory requirements like HIPAA.Meeting these regulations while maintaining data quality poses a significant challenge.
Expectations of the patient: Patients expect high-quality service, pushing healthcare organizations to adapt to changing preferences and demographics.
Lack of quality assurance parties: Challenges in confirming information, record-keeping system issues, and reliance on staff availability for data review contribute to incomplete or inaccurate data collection.

Counterbalancing Challenges of Data Collection
Some common challenges faced during data collection include issues with data quality, finding relevant data, deciding what data to collect, dealing with big data environments, and low response rates in research studies (Oussous et al., 2028).To overcome these challenges, Gudivada et al. (2027) suggests that researchers can implement strategies such as data profiling and cleansing for data quality issues, utilizing data curation techniques to find relevant data, carefully selecting data to collect, and establishing rapport with participants to improve response rates, though still hinting sub-optimality issues in the results.In addition, in times of the pandemic, researchers face unique challenges like participants' reluctance to participate and conducting interviews on sensitive topics.Lobe et al. (2021) counsel that sn, explaining the research purpose clearly to participants, dressing formally during interviews, and establishing rapport with participants by showing genuine interest and ensuring confidentiality.With respect to the gatekeepers, policy should guide assistance and entry.There should be ways to punish gatekeepers who do not allow research that obtained permission through clearance certificates.

Ensuing Emotional and Psychological Outbursts
In the context of data collection, researchers who are being refused access to data collection sites may view this as a form of rejection, leading to emotional responses that may include anger, sadness, frustration, and even aggression (Roseman, 2028).These emotions can arise when people perceive that their relational value to others is low or in potential jeopardy.Thus, these emotional responses could indicate interpersonal rejection.

How Natural Science Research Impact Health Sciences
Natural science research has a major impact on health sciences by influencing the evolution of professional knowledge in the field.Biological science research plays a crucial role in shaping the understanding and advancements within health sciences (Pettersen, 2005).Moreover, Sonnenwald and McLaughlin (2005) enlighten that interdisciplinary collaboration in natural science research is vital for addressing complex health-related issues by bringing together diverse scientific knowledge to tackle challenging problems and questions.This collaboration enhances the capacity to address health challenges effectively through the combination of different expertise and skills from various scientific backgrounds.Some easy-to-see benefits of natural sciences in health sciences include physics application in the tools used in the health systems, and statistical applications in information pursuing and decision-making.

Methodology
The methodology started with submission of the research proposal to the Faculty Research Committee for technical checks, which were passed after proposal review.This was followed by application for ethical clearance which is done by the university research and ethics committee.It was granted, and the clearance reference number is SMUREC/S/252/2023: PG.The process led to requesting for use of the respondents who were students of the university through the office of the registrar.The registrar did not easily grant permission despite submission of the clearance certificate.Rather, he solicited the advice of the legal office, citing the Protection of Personal Information Act (often called the POPI Act or POPIA).Another possible authority that was approached to assist with data collection was the university Information Communication and Technology Division (ICT), which has the emails of all the registered students.They asked for a formal letter requesting emails of the students and the clearance certificate.These two authorities did not assist with data collection.Instead, each of them referred the researcher to the other.Over a month passed with no progress on the issuing of the response or the emails of the students.An alternative was found to use social media, which is a free medium of communication.

Challenges Experienced
The findings regarding gatekeeper challenges include denial of access, a long process before being granted access, failure by gatekeepers to update the applicant, the POPI Act, restricting entry conditions, limiting access to data and respondents, restricting scope of the study, and retaining rights and privileges on the publication.
Access denial: Access denial by gatekeepers refers to the power of gatekeepers to prevent or grant access to certain resources or individuals.Gatekeepers control access to benefits that they do not own.The challenges caused by gatekeepers in data collection include the potential denial of access, which can be a deliberate way to punish the researcher or to.It is expected of gatekeepers to ensure that researchers gain access to potential participants and sites for research.However, gatekeeping can be problematic with researchers having limited or no access to sites.Researchers who participated in this study found the gatekeepers to be unreasonable, as they try to influence a negative verdict.They ended up not granting permission at the time that the researchers requested.In this study, the permission was never granted.
Lengthy process: The process of gatekeepers has shown to be long in some instances before permission is granted to collect data.The gatekeepers approach of taking long to submit an application, pretending to be reviewing the application even when they have no authority to do so, extend the application time.
No updates: The researcher experiences were the lack of updates from the gatekeepers regarding their application.The lack of updates include gatekeepers not voluntarily offering the updates, not responding to emails requesting updates, and promising to call back with updates when caught on a landline phone and not calling back as they promised.

POPIA:
The researchers find the use of the POPI Act as inconsistent.Their experience was the granting of one researcher the names of students while the same gatekeeper refused to provide emails of the same student participants to the researchers/authors of this paper.The researchers of this manuscript were assisting group that received student names with data analysis, and that is how they knew about it.The emails were not even in names, but in numbers provided by the institution.

Intervention
Persistent follow and persuasive appeals did not help the authors of this manuscript in the gatekeeper's decision to grant permission or emails to contact the students.
Group charts: Since the researcher was not granted permission to contact students who were the study subjects, the researcher, who was also a student in the same HEI, decided to leverage on the student group charts and other social media that the students have.She used the group charts mostly to communicate with fellow students, and snowballed the request to participate through friends, friends of the friends of the friends . . . of the friends and so on, through a chain pattern.
Residences: Many students of this HEI stay on university residences and consider one another as 'family'.They therefore have a general understanding.They would then want their peers to progress.The researcher the approached the residence leaders and narrated her predicament.She was requested to produce the clearance certificate for the study.The student leaders were mostly impressed that the study wanted to help with their welfare, they shared with the residence wardens and they decided to assist with communication to other students in residences.Based on the merits of the study, many students agreed to participate to share their experiences.Some of them even hinted that they share hoping that the university would incorporate their inputs in student induction programmes.