Maloney Home Page  |  Alternatives to “good” in technical writing

This note is part of an ongoing series intended to ensure that readers focus on your research rather than on phrases that may not sound natural in English. During the manuscript review process, every reviewer has a limit to exposure to awkward wording; if this threshold is exceeded, reviewers tend to shift their focus to language differences and may even refuse to finish reading the manuscript! My goal is to suggest more natural phrases and strategies for communication to keep the focus on your high-quality study.

Precision is a crucial element of high-quality academic writing. In the academic literature, authors too often use the vague adjective “good” to describe the results of an analysis, the features of a device, or the performance of a technique. Unfortunately for the reader, “good” is nearly useless as a description. Does “good” mean simply “acceptable” (which is not so good), or does it mean “exceptional” (which is very good)? Does it mean “adequate” (in terms of being minimally sufficient)? Or “well-suited” (for a particularly environment or set of conditions)? Or “favorable” (in benefiting the outcome of our research)? Or “outstanding” (above other examples in its class)? Our readers seek our expert interpretation of hard-won data, but “good” doesn’t give them much to go on.

Word limits and the short attention spans of readers mean that every word of our paper counts. This condition is especially true for the abstract and the conclusions, those most valuable sections that present the broad implications of our work. In these shorter sections, little surrounding context exists for readers to interpret our message, and “good” can sound particularly awkward or dull. Even deep in the supplementary information, however, it always benefits us to replace “good” with a more precise word that better conveys the intended meaning. So let’s survey alternatives to “good” that will shift the precision of our descriptions from “good” toward “outstanding.”

The first question we might ask is whether “good” can be replaced with the exact property of interest. The literature is filled with, for example, papers describing materials with “good mechanical properties” when the authors actually mean “large tensile strength,” “low shear modulus,” “high fracture toughness,” “resistance to fatigue,” “low susceptibility to creep,” “strong corrosion resistance,” “minimal surface roughness,” “undetectable hysteresivity,” “negligible chronic inflammation results following implantation,” or some other precise reference to a well-defined characteristic. Even “good ductility” isn’t “good” enough; the requirements of different forming processes might necessitate a high or a low ductility, for example. Instead, let’s articulate to the reader exactly what we mean.
Vague: “In this study, we aimed to develop freestanding cellulose membranes with good mechanical properties.”
Better: “In this study, we aimed to develop freestanding cellulose membranes with a high burst pressure and a low dissolution rate in acidic aqueous environments.” (Later, we’ll specify exactly what we mean by these features, e.g., a burst pressure of 10 atm gauge.)
In some cases, we may be referring to a process that is convenient or efficient, i.e., one that uses relatively few resources to achieve a goal:
“…provide a convenient starting point to describe NC surface ligands.” Boles et al., Nature Materials 15, 141–153 (2016).
“For efficient light-to-heat conversion from a wider solar spectrum…” Bae et al., Nature Communications 6, 10103 (2015).
In other cases, a device or procedure may be consistent or reliable, i.e., largely free from the possibility of errors:
“…to ensure consistent operation at programmed time points, this protocol adopts…” McCall et al., Nature Protocols 12 2 (2017).
“…the development of reliable surveillance and risk assessment procedures…” Berendonk et al., Nature Reviews 13, 310–317 (2015).
(Alternatively, we might describe a technique associated with small errors as precise or accurate, although these terms are not synonymous; accurate means that your predictions are centered around the truth, whereas precise means that they are tightly clustered.)

Consistent can also refer to results that corroborate other results or agree with theoretical predictions:

“GST and QPT yield consistent results, with process fidelities of ≥86% for all gates.” Kim et al., Nature Nanotechnology 10, 243–247 (2015).
(Alternatively, we might describe a process that can be performed repeatedly with consistent results as reproducible or replicable.)

Straightforward is appropriate when describing a process or analysis that can be completed with few complications or uncertainties:

“…a low solvent content crystal of 35% still allowed straightforward structure solution…” Weinert et al., Nature Methods 12, 131–133 (2015).
If a certain material, device, process, or analytical technique is advantageously paired (e.g., with a certain application or other component), we might describe it as suitable or, if the pairing is particularly apt, well-suited:
“…a battery system that combines a water-based electrolyte with an organic redox-active material and a suitable low-cost membrane.” Janoschka et al., Nature 527.7576 (2015).
“…AFM nanoindentation is a well-suited method to analyse local mechanical properties of small volumes…” Peisker et al., Nature Communications 4:1661 (2013).
Beneficial and advantageous have a field-specific meaning in genetics (namely, to provide an evolutionary benefit) but can also be used in a more generic sense when a benefit is conferred to practitioners (or humanity in general) by a certain result, process, or device, as in the following:
“These results indicate that the beneficial effects of diet on metabolic health may require…” Brüssow et al., Nature Biotechnology 32, 243–245 (2014).
“…the future design of heterogeneous catalysts with advantageous reaction capabilities for other important processes.” Fortea-Pérez et al., Nature Materials 16, 760–766 (2017).
Let’s now move in the other direction, away from excellence. Again, the reason that “good” is such a dull descriptor is that it spans such a broad range of quality. Techniques or devices that simply meet requirements might be more precisely described as adequate, acceptable, or sufficient:
“An annealing temperature of 65 °C, extension time of 8 min at 68 °C and 35 cycles provided adequate results for both Rb1 and Srgn.” Yong et al., Nature Communications 5: 5799 (2017).
“Many researchers neglect the fact that the high field needed to achieve acceptable charge collection efficiency (that is, an acceptable sensitivity) can also lead to an unacceptably large dark current.” Kasap et al., Nature Photonics 9, 420–421 (2015).
“Whole genome sequencing projects must produce a sufficient number of sequence ‘reads’ covering each nucleotide in the genome” Paterson Nature Technology 33, 491–493 (2015).
Satisfactory is an acceptable replacement for “good” but is nearly as vague:
“…indicated that the drug significantly (both statistically and clinically) improved the number of satisfactory sexual events…” Nappi et al., Nature Reviews Urology 13, 67–68 (2016).
Satisfactory is still better than “good,” however, because at least satisfactory implies that certain requirements were satisfied (and one hopes that the participants in Nappi et al.’s study agree).

In some cases, our measurements might feature a signal, spectral peak, or change in response that is easily distinguished and merits mention. Referring to such a feature as a “good peak” (for example) sounds too close to “a peak I was fortunate to find, because otherwise I was going to lose funding.” Prominent, unambiguous, or notable are better alternatives, as in the following:

“Interestingly, both UV-LDI MS and GCMS analysis of bonde03675 extract revealed a prominent signal at m/z 377…” Ng et al., Nature Communications 6: 8263 (2015).
“…the molecular fingerprints disappear, providing unambiguous evidence that the TERS signals…” Zhang et al., Nature 498.7452: 82–6 (2013).
“The notable peak at 287.3 eV (corresponding to aliphatic C–H and phenolic C–OH), apparent only in the planted biochar-amended soil, …” Nature Climate Change 7.5: 371 (2017).
Let’s note at this point that one of the reasons that “good” is (over)used is that it lets us avoid making a stand—who can say what a “good signal” really means? It strengthens our narrative (and adds refreshing variety) to more precisely refer to a “substantial increase in signal strength” or, better still, “a signal with a notably high signal-to-noise ratio of >40,” which is more effectively quantitative.

Of course, one of the implications of stating a conclusion is that a reviewer (and ultimately, scores of readers, if we’re lucky) will soon be evaluating that conclusion. Thus, when we describe a measurement as “unambiguous,” there truly must be no ambiguity. This caution is particularly important in the case of the next few qualitative descriptions, which are useful for summarizing our contributions in abstracts and conclusions but lose impact if used cavalierly. The following qualitative terms should not be strewn about to convince the reader without evidence but used rather to reinforce quantitative or otherwise objective findings.

Favorable and strong are utility players that can be used broadly to describe positive potentials, outcomes, and capabilities. Witness:

“…we found that the scaffolds had favorable biophysical and structural properties and that scaffold immunization of rhesus macaques induced RSV-neutralizing activity.” Correia et al., Nature 507 (7491): 201 (2014).
“Resistive random access memory based on the resistive switching phenomenon is emerging as a strong candidate for next generation non-volatile memory” Lee et al., Scientific Reports 3: 1704 (2013).
In addition, the terms effective and enabling (along with useful and valuable) highlight capabilities that move the field forward:
“These results indicate that ion-mobility mass spectrometry is an effective tool for the analysis of complex carbohydrates.” Hofmann et al., Nature 526.7572 (2015).
“…microfabrication is an enabling technique for cellular studies…” Hao et al., Scientific Reports 7: 43390 (2017).
If a result is eagerly sought, it might be described as desirable; if consensus favors it, it is preferred:
“Chemical cross-linking with formaldehyde leads to desirable cross-links not only between proteins (intermolecular cross-links) but also between…” Mohammed et al., Nature Protocols 11, 316–326 (2016).
“Whereas extinction of a target population may be the preferred outcome in the case of pathogens, …” Lindsey et al., Nature 494.7438 (2013).
Improved or enhanced (or augmented when capability is concerned) is a fitting choice as long as evidence of improvement is thoroughly documented:
“This study demonstrates how utilizing unique hierarchical structures in artificial materials can yield improved performance.” Plummer, Nature Materials 14.11 (2015).
“We also demonstrate the enhanced capabilities of this instrument through the analysis of several challenging protein–nucleic acid assemblies.” van de Waterbeemd et al., Nature Methods 14, 283 (2017).
Let’s now move to even more assertive language for promoting our work. The terms excellent and outstanding (or exceptional) require solid evidence to support the implied strong claims:
“Fluorinated dendrimers achieve excellent gene transfection efficacy in several cell lines…” Wang et al., Nature Communications 5: 3053 (2014).
(Wang et al. justified this claim with several figures showing substantial improvements in transfection efficacy relative to controls.)
“Several new materials with outstanding properties have been fabricated with this new technique: nanoporous Si for battery anodes with extremely long cycle fatigue, ultra-high surface area non-porous Nb for electrolytic capacitors and Cu–Ta nanocomposites with outstanding material properties.” Geslin et al., Nature Communications 6: 8887 (2015).
(Note that Geslin et al. are referring to others’ accomplishments when they use this term.)
We now come to superior, which—used perhaps once in the abstract or conclusion—is extremely effective. When we use superior, however, there should be no doubt in the reader’s mind of the difference we describe:
“Our box model results (Fig. 4c) provide superior data prediction of the deep-water aragonite saturation isopleths” Luo et al., Nature Communication 12821 (2016).
(Note the reference to quantitative results in the figure.)
“…we obtained superior product separation from crude reaction-mixture samples using a loading flow of 1 mL/min.” He, Scientific Reports 7: 8867 (2017).
(The body of He’s paper presents quantitative comparisons to support this claim.)
Finally, let’s emphasize that certain alternatives to “good” are inappropriate for our research papers. Terms such as “tip-top,” “first-class,” and “first-rate” are colloquial; that is, they’re too informal for the academic literature. Others, such as “fantastic,” “satisfying,” or “marvelous,” have a strong emotional component that sounds out of place. Even the style guide of our specific journal of interest may side against certain words (such as “obvious,” “interesting” or “novel”) that the journal’s editorial staff might consider self-apparent, subjective, or overused. Regardless, the other terms surveyed in this note provide a variety of alternatives to ensure that our message is accurately conveyed.

About the author: John M. Maloney received his Ph.D. in 2012 in the area of biological cell chemomechanics from MIT’s Department of Materials Science and Engineering, where he most recently held a full-time appointment as Research Scientist. He has published research reports in Nature Biotechnology and Nature Materials and holds 10 patents in the area of microfabrication and medical device design. As a freelance technical editor, certified by the Board of Editors in the Life Sciences, he has edited thousands of manuscripts, focusing on helping non-native English speakers articulate their research results with sophistication and technical precision.


© Copyright John M. Maloney