Scientific writing and Communication: An alternative career option for PhDs and scientists outside research laboratories

Writing is recognized as a popular and esteemed career which existed ever since we could remember the existence of printed literature and books. There are various writing professionals working as writers and editors for media, publishing house, business communications, advertising, government and academic settings and freelance services. Until now, writing has always been considered as a promising opportunity for someone with a background in a language subject. People some time really wonder if scientists can be writers. Surprisingly, nowadays scientific writing is attracting many PhDs who really covet for a change from traditional research career to a better alternative which can be creative and challenging. Many scientists and PhDs now feel comfortable outside their laboratory zone because with time they have gained excellent communication skills while pursuing PhD through endless exercise of oral presentations, publications and thesis writing.

Can scientific writing and communication be pursued as a promising alternative career by PhDs?

Answer is yes! Writing and publishing are actually the essential components of most careers in science, particularly in an academic research setting. Many PhDs are now opting out for it as an alternative career outside routine research laboratories for a livelihood. A long history of scientific journals dated back to1665 proves that researchers have been unquestionably accepted as writers among scientific community. Not to forget that all the science and technology books are authored by scientists with a particular expertise on the subject. Scientific writing is an excellent way to apply one’s life science background to explore a relatively unconventional career track. If one possesses the knack for quality communication and passion for writing, then science credentials can makes him/her a much favored commodity in the media, research facilities, universities, hospitals and pharmaceutical industries. Scientific writing is in fact a broader term that covers a number of communication domains like science journalism, medical reporters, apart from medical writing, technical writing and science marketing writing.

Scientific writing offers a vibrant scope for PhDs in various disciplines, attracting them into an excellent alternative to a research based career:

The scope of scientific writing has been increasing such that many higher academic institutions like MIT, University of California, Santa Cruz, Johns Hopkins University and Boston University started offering a one-year graduate program in scientific writing. Many management institutions offered short-term courses on technical writing, mainly focusing on writing and editing highly specialized material for biotechnology, pharmaceutical and computer companies. Similar to a scientific writer, a medical writer with a MD or PhD in life or other basic sciences can work for hospitals, pharmaceutical companies, government agencies, medical schools, non-profit organizations or publishing houses. Typically science writers in these settings are known as Public Information Officers (PIO).

One can envision the following few selected options (as mentioned below).

Publishing house: In last few decades, the increased research funding and activities have led to the ever increasing number of scientists in both basic and applied sciences. The growing competition among scientists to perform quality research and avail research funding from government agencies have made it mandatory to publish in high quality journals. With the introduction of first peer review journal in early 17th century, the number of such quality journals has been increasing and so are the career prospects in publishing house where most scientists with PhDs would fit in according to their area of expertise. By combining vigorous research training and subject expertise with their excellent communication and writing ability, scientists can actually find good placements with reputed publishing house as reviewers, copy editors and proofreaders. Though still few in number, there are companies which hire scientists as in-house editors to ensure quality editing, proofreading and prepublication services to authors from non native English speaking countries.

 Regulatory affairs: Various pharmaceutical giants like Novartis, GlaxoSmithKline and Pfizer now exclusively hire scientific, technical and medical writers with excellent writing skills on various positions based on their qualification and experience. Great deal of accuracy is required to prepare the clinical study protocols, regulatory documents and brochures for investigative drugs and thus apart from the subject depth and expertise, rigorous training a PhD received during a five to six year period makes them a perfect fit for such job requirements.

Academics and Research Institutes: Universities and research institutes now specially requires PhDs for different writing tasks which involves helping faculties and scientists in writing research grants in correct format and ensure a quality check before it goes to the funding agency. Such positions include titles like Grant manager, which saves ample time of scientists in dealing with complexities of research grant applications. Many institutions have started elective course on “scientific writing and communications” to better prepare science and medical graduates for their future careers. Similarly, hospitals involved in clinical research, hires PhDs for clinical data writing and various other writing tasks.

Apart from these, one can also try their hands on in careers like freelancing, patent writing and science journalism, which requires a sound technical knowledge and subject expertise. These jobs ensure one’s career satisfaction by offering substantial job flexibilities and attractive salaries.

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Scale Classification Bases

Scale Classification Bases

The Scale Classification Bases can be categorized on the following bases.

  1. Subject orientation: In this, a scale is designed to measure the characteristics of the respondent who completes it or to estimate the stimulus object that is presented to the respondent.
  2. Response form: In this, the scales can be classified as categorical or comparative. Categorical scales (rating scales) are used when a respondent scores some object without direct reference to other objects. Comparative scales (ranking scales) are used when the respondent is asked to compare two or more objects.
  3. Degree of subjectivity: In this, the scale data is based on whether we measure subjective personal preferences or just make non-preference judgements. In the former case, the respondent is asked to select which person or solution he favors to be employed, whereas in the latter case he is simply asked to judge which person or solution will be more effective without reflecting any personal preference.
  4.  Scale properties: In this, the scales can be classified as nominal, ordinal, interval and ratio scales. Nominal scales merely classify without indicating order, distance or unique origin. Ordinal scales indicate magnitude relationships of ‘more than’ or ‘less than’, but indicate no distance or unique origin. Interval scales have both order and distance values, but no unique origin. Whereas, ratio scales possess all these features.
  5. Number of dimensions: In this, the scales are classified as ‘uni-dimensional’ or ‘multi-dimensional’. In the former, only one attribute of the respondent or object is measured, whereas multi-dimensional scaling recognizes that an object might be described better by using the concept of an attribute space of ‘n’ dimensions, rather than a single-dimension continuum.
  6. Scale construction techniques: This can be developed by the following five techniques.
  • Arbitrary approach: In this, the scales are developed on ad hoc basis. It is the most widely used approach.
  • Consensus approach: In this, a panel of judges evaluates the items chosen for inclusion in the instrument regarding whether they are relevant to the topic area and unambiguous in implication.
  • Item analysis approach: In this, a number of individual items are developed into a test that is given to a group of respondents. Post administering the test, total scores are evaluated, and the individual items are analyzed to determine which items discriminate between persons or objects with high and low total scores.
  • Cumulative scales: These are chosen on the basis of their conforming to some ranking of items with ascending and descending discriminating power.
  • Factor scales: This can be constructed on the basis of inter-correlations of items indicating a common factor accounts for the relationship between items.

 

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Scaling techniques for researcher

Scaling techniques for researcher

During research especially when the concepts we want to measure are complex and abstract and there are no standardized measurement tools available, we face problems of measurement. Alternatively, when we are measuring something which can lead to subject bias like attitudes and opinions, there is a problem of their valid measurement. A similar problem may be faced in a lesser degree while measuring physical or institutional concepts. Therefore, knowledge of some such procedures which may enable accurate measurement of abstract concepts is extremely essential.

Scaling techniques are immensely beneficial for a researcher.

Scaling is the process of assigning numbers to various degrees of attitudes, preferences, opinion, and other concepts. Scaling is defined as a procedure for the assignment of numbers (or other symbols) to a property of objects in order to impart some of the characteristics of numbers to the properties in question.

Scaling can be done in two ways: (i) making a judgement about an individuals characteristics and then placing him on a scale which is defined in terms of that characteristic, and (ii) constructing questionnaires where individual’s responses score assign them a place on a scale. A scale is a continuum, consisting of the highest point and the lowest point along with several intermediate points between these two extremities. These scale-point positions are hierarchically related to each other. Numbers for measuring the degree of differences in the attitudes or opinions are assigned to individuals corresponding to their positions in a scale. Therefore, the term ‘scaling’ implies procedures for determination of quantitative measures of subjective abstract concepts.

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Test of Practicality of a measuring instrument

Test of Practicality of a measuring instrument

The practicality attribute of a measuring instrument can be estimated regarding its economy, convenience and interpretability. From the operational point of view, the measuring instrument needs to be practical. In other words, it should be economical, convenient and interpreted.

Economy consideration suggests that some mutual benefit is required between the ideal research project and that which the budget can afford. The length of measuring instrument is an important area where economic pressures are swiftly felt. Even though more items give better reliability, in the interest of limiting the interview or observation time, we have to take only few items for the study purpose. Similarly, the data-collection methods, which are to be used, occasionally depend upon economic factors.

Convenience test suggests that the measuring instrument should be easily manageable. For this purpose, one should pay proper attention to the layout of the measuring instrument. For example, a questionnaire with clear instructions and illustrated examples is comparatively more effective and easier to complete than the questionnaire that lacks these features. Interpretability consideration is especially important when persons other than the designers of the test are to interpret the results. In order to be interpretable, the measuring instrument must be supplemented by the following:

  1. detailed instructions for administering the test,
  2. scoring keys,
  3. evidence about the reliability, and
  4. guides for using the test and interpreting results.
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Census And Sample Survey

A Universe or Population consists of all the items in a field of inquiry. A complete enumeration of all these items in the population is called a census inquiry. This inquiry is completely accurate with no element of probability. However, it is not practical as the element of bias cannot be examined in such an inquiry. Moreover, it is time-consuming, expensive, and exhaustive.

Alternatively, a sample of a population can be studied to obtain sufficiently accurate results. This method has practical applications and consumes less time and money. The respondents selected for the inquiry is termed as a sample and the selection process is called sampling technique. The survey is known as a sample survey. A researcher needs to prepare a sample design for his study that should represent the total population, i.e., he needs to plan how and what size of the sample should be selected for his study.

Implications of a sample design:

A sample design is a technique that a researcher adopts to select items for the sample that represents a given population. A researcher may prepare many sample designs, but he needs to choose the design that should be reliable and appropriate for his research study.

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Research Design

A research design can be defined as the preparation of conditions, for the collection and analysis of data in such a manner, which aims at combining relevance to the research purpose with economy in procedure. In other words, the design arrangement of a research project is commonly known as the “research design”. Besides, the decisions like what, where, when, how, etc., in regard to a research study, creates a research design. In fact, the research design is the conceptual structure within which a research is conducted. Moreover, it comprises the outline for the collection, measurement and analysis of data. Hence, the design carries a blueprint of what the researcher will do, from composing the hypothesis and its operational implications to the final analysis of data. Overtly, the design decisions happen to be in respect of:

1)  What is the research?

2)  Where and why will the research be conducted?

3)  What data is required for the research?

4)  Where can be the data found?

5)  What will be the time period of the research?

6)  What will be the sample design?

7)  What methods will be used for data collection?

8)  How will be the data analysed?

9)  In which style will be the research report prepared?

Based on the above mentioned design decisions, the complete research design may be divided into the following parts:

(a)  Sample design: this deals with the technique of selecting items and thus requires careful observation for the given research study.

(b)  Observational design: this relates to the conditions under which the experiments are to be conducted.

(c)  Statistical design: this concerns the question of how many items are to be observed, and how are the collected data and information going to be analysed.

(d)  Operational design: this deals with the methods by which the procedures specified in the sample, observational and statistical designs can be conducted.

The essential characteristics of a research design are as the following.

(a)  It is a plan, which specifies the sources and types of data relevant to the research problem.

(b)  It is a strategy, which decides the approach that will be used to collect and analyse the data.

(c)  Since most of the research studies are conducted under these two controls, it also includes the time and cost budgets.

In short, the research design must contain the followings.

(i)  A clear and concise statement of the research problem,

(ii)  The population to be studied, and

(iii)  The various procedures, methods, and techniques to be used for collecting and analysing the data.

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Techniques Involved in Defining a Problem

As a researcher, you must have often read that defining a problem is the first step in a research process. But, have you ever wondered what is meant by defining a problem. Well, it simply means that the researcher has to lay down certain boundaries within which he/she has to study the problem with a pre-defined objective in mind.

Defining a problem is a herculean task, and this must be done intelligently to avoid confusions that arise in the research operation. Try to follow the below steps systematically to best define a problem:

 i.  State the problem in a general way:

First state the problem in general terms with respect to some practical, scientific or intellectual interest. For this, the researcher may himself read the concerned subject matter thoroughly or take the help of the subject expert. Often, the guide states the problem in general terms; it depends on the researcher if he/she wants to narrow it down to operational terms. The problem stated should also be checked for ambiguity and feasibility.

ii.  Understand the nature of the problem:

The next step is to understand the nature and origin of the problem. The researcher needs to discuss the problem with those related to the subject matter in order to clearly understand the origin of the problem, its nature, objectives, and the environment in which the problem is to be studied.

iii. Survey the available literature:

All available literature including relevant theories, reports, records, and other relevant literature on the problem needs to be reviewed and examined. This would help the researcher to identify the data available, the techniques that might be used, types of difficulties that may be encountered during the study, possible analytical shortcomings, and even new methods of approach to the present problem.

iv.  Go for discussions for developing ideas:

The researcher may discuss the problem with his/her colleagues and others related to the concerned subject. This helps the researcher to generate new ideas, identify different aspects on the problem, gain suggestions and advices from others, and sharpen his focus on certain aspects within the field. However, discussions should not be limited to the problem only, but should also be related to the general approach to the problem, techniques that might be used, possible solutions, etc.

v.  Rephrase the research problem into a working proposition:

Finally, the researcher must rephrase the problem into a working proposition. Rephrasing the problem means putting the problem in specific terms that is feasible and may help in the development of working hypotheses. Once the researcher has gone through the above steps systematically, it is easy to rephrase the problem into analytical and operational terms.

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Necessity of Defining the Problem

The old adage, A problem well-defined is a problem half-solved, holds strong even today. Proper definition of a research problem is an important prerequisite for any research study. Often, the formulation of a problem holds more significance than its solution. The manner in which the problem is defined decides the direction for the entire research. The problem that has to be analyzed should be defined unambiguously, which will help to discriminate between the relevant and irrelevant data. A careful scrutiny of the research problem will help in working out the research design. This will ensure smooth coordination of all the consequential steps involved in the research. Lots of questions may arise during the course of the research: What data needs to be collected? What characteristics of that data are relevant and need to be studied? What relations have to be explored? What techniques have to be used for the purpose? The researcher can find answers to all these questions only if the problem has been properly defined. A proper definition of the problem helps to improve the overall efficiency and quality of the study. It is the foundation for further development of the research proposal. It enables the researcher to systematically point out as to why the proposed research should be undertaken and what can be achieved with the research findings. A carefully defined research problem ensures that the researcher does not stray from the research path that has to be followed.

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Selecting the Problem/Subject of Research

The undertaken research problem must be thoroughly selected. For this purpose, the help of a research guide can also be taken. However, since research problems cannot be usually borrowed, each and every researcher must therefore strive to find out his research problem for the study. While buying a new pair of spectacles, we need to cooperate with the optician along with our own preferences in deciding the power of lens. Similarly, a research guide can, at the most, only help the researcher to choose a subject. However, the following points can be observed by the researcher while selecting a research problem/subject:

i.  Generally, the subject, which is overdone, is avoided, as it will be a hard and complex task to throw any new light on such a case that has already been done. Controversial subject should not become the choice of an average researcher. Moreover, too narrow or too vague problems should be avoided.

ii.   The selected research subject should be practical and realistic, so that the related research material/sources are easily available within one’s reach. However, sometimes, even after this it remains still quite difficult to supply absolute ideas regarding how a researcher should acquire the necessary ideas for his research. Thus, for this purpose the researcher should definitely contact an expert or a professor, in the University, who is already occupied in a research. Besides, he may read articles on the subject published in literature and may also get the notions about how the techniques/ideas discussed therein might be functional in obtaining the solutions of other problems. Moreover, he may discuss what he has in his mind, concerning a problem, with others as well. By this way, he should be absolutely successful in selecting a problem by putting his best efforts.

iii.   Some of the other criteria, which must also be considered while selecting a problem, are: importance of the subject, qualifications and training of the researcher, costs involved, and the time factor. In other words, before selecting a problem, the researcher must ask himself the following questions:

  1. Is he well equipped, concerning his background, to conduct the research?
  2. Does the research/study come within the budget he can afford?
  3. Can the necessary cooperation be obtained from those who must participate in the research as subjects?

In case, the answers to all of the above mentioned questions are positive, one may become confident concerning the practicability of the study.

iv.  A preliminary study should most certainly precede the selection of a problem. However, this won’t be necessary regarding the problem needs the conduct of a research closely similar to the one, which has already been conducted. But, usually a brief feasibility study must be undertaken, when the field of inquiry is reasonably new and lacks the availability of a set of well developed techniques.

In conclusion, when the research subject is selected appropriately, by conforming to the above mentioned points, the research will, most probably, not be a boring drudgery. Rather, it will be exciting and educating. The selected subject/problem must involve the researcher and be the prime priority in his mind, so that he may give his best shot required for the study.

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What is a Research Problem?

The first and foremost step in a research process is to select and properly define a research problem. In order to define a problem correctly, a researcher must know: what a problem is?

What is a research problem?

A research problem refers to any difficulty which a researcher experiences either in a theoretical or practical situation and, thus, wants to obtain its solution. Generally, a research problem requires the following conditions:

-  An individual or a group having some difficulty or problem.

-   Some objective(s) to attain. Without any objective, one cannot have a problem.

-   Alternative means (or courses of action) to obtain the objective(s). This means that at least two means should be available to a researcher because if he has no options, he cannot have a problem.

-  The researcher should have some doubts related to the selection of alternatives. This means that the research should be able to answer questions regarding the possible alternatives.

-   Some environment(s) to which the difficulty pertains.

Thus, a research problem helps a researcher to find out the best solution for any given problem, i.e., the course of action that can help attain the objective optimally in the context of a given environment.

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