Comparison of color discrimination in chronic heavy smokers and healthy subjects

Thiago Monteiro de Paiva Fernandes; Natalia Leandro Almeida; Natanael Antonio dos Santos

doi:10.12688/f1000research.10714.2

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Research Article

Revised

Comparison of color discrimination in chronic heavy smokers and healthy subjects

[version 2; peer review: 1 approved, 1 approved with reservations]

Thiago Monteiro de Paiva Fernandes¹, Natalia Leandro Almeida¹, Natanael Antonio dos Santos^1,2

PUBLISHED 30 Mar 2017

Author details Author details

¹ Department of Psychology, Federal University of Paraíba, Joao Pessoa, Brazil
² Perception, Neuroscience and Behavior Laboratory, Federal University of Paraíba, Joao Pessoa, Brazil

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REVIEWER STATUS

This article is included in the Eye Health gateway.

Abstract

Background: Cigarette smoke is probably the most significant source of exposure to toxic chemicals for humans, involving health-damaging components, such as nicotine, hydrogen cyanide and formaldehyde. The aim of the present study was to assess the influence of chronic heavy smoking on color discrimination (CD). Methods: All subjects were free of any neuropsychiatric disorder, identifiable ocular disease and had normal acuity. No abnormalities were detected in the fundoscopic examination and in the optical coherence tomography exam. We assessed color vision for healthy heavy smokers (n = 15; age range, 20-45 years), deprived smokers (n = 15, age range 20-45 years) and healthy non-smokers (n = 15; age range, 20-45 years), using the psychophysical forced-choice method. All groups were matched for gender and education level. In this paradigm, the volunteers had to choose the pseudoisochromatic stimulus containing a test frequency at four directions (e.g., up, down, right and left) in the subtest of Cambridge Colour Test (CCT): Trivector. Results: Performance on CCT differed between groups, and the observed pattern was that smokers had lower discrimination compared to non-smokers. In addition, deprived smokers presented lower discrimination to smokers and non-smokers. Contrary to expectation, the largest differences were observed for medium and long wavelengths. Conclusions: These results suggests that cigarette smoke and chronic exposure to nicotine, or withdrawal from nicotine, affects CD. This highlights the importance of understanding the diffuse effects of nicotine either attentional bias on color vision.

Keywords

cigarette smoking, visual system, color discrimination, color vision, Cambridge Colour Test, Trivector, nicotinic receptors

Corresponding author: Thiago Monteiro de Paiva Fernandes

Competing interests: No competing interests were disclosed.

Grant information: National Counsel of Technological and Scientific Development (CNPq), Brazil (grant no., 303822/2010-4), CAPES and Federal University of Paraiba funded this paper
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2017 Fernandes TMdP et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Data associated with the article are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).

How to cite: Fernandes TMdP, Almeida NL and dos Santos NA. Comparison of color discrimination in chronic heavy smokers and healthy subjects [version 2; peer review: 1 approved, 1 approved with reservations]. F1000Research 2017, 6:85 (https://doi.org/10.12688/f1000research.10714.2) First published: 27 Jan 2017, 6:85 (https://doi.org/10.12688/f1000research.10714.1) Latest published: 01 Aug 2017, 6:85 (https://doi.org/10.12688/f1000research.10714.3)

Revised Amendments from Version 1

In order to meet the specifications and reviewers recommendations, substantial changes were made.

Introduction: We've added some information about smoking impairments/damages in visual processing. In addition, we bring the importance of our study and the use of visual psychophysics, more precisely of the Trivector test, to evaluate congenital or acquired impairments of conditions that affect the central nervous system (such as chronic heavy smoking).

Methods: We chose to include a subsection in the Methods where we detailed the cutoff points of the Trivector test (based on the average results of Trivector test in Brazilian studies and in a longitudinal study by Paramei et al.⁶⁶). Thus, we provided the reader with information about what value is considered normal and what value we can already consider as possible impairment in color discrimination.

Results: We changed the description of the results, facilitating the reading and avoiding dubious explanations. In this way, we inform that the lower the threshold, the better the discrimination. Therefore, when the group presents a higher threshold, being statistically significant, we can infer a possible impairment in color discrimination. Figure 1 was replaced with one at a higher resolution in order to improve reader viewing and interpretation of the data

Discussion: We corrected a few words in the discussion section and added a paragraph informing that our results for the control group are in agreement with most of the studies that use the Trivector, and that the differences found can be classified as losses in color discrimination, since they crossed the threshold of the normative data.

Natalia Leandro de Almeida was added as a co-author to the paper due to her substantial contributions, such as re-analysis, interpretation and correction of the manuscript.

See the authors' detailed response to the review by Marine Raquel Diniz da Rosa
See the authors' detailed response to the review by Goro Maehara

Introduction

Cigarette smoking is still a major source of exposure to chemicals that are toxic for humans. The compounds in cigarettes and cigarette smoke, such as nicotine, oxygen dioxide and formaldehyde, are highly harmful to health¹. Data from the World Health Organization (WHO) hypothesize that by 2030, cigarettes could kill nearly 9 million people a year around the world^2,3.

Cigarette nicotine deprivation in chronic users may impair cognitive and attentional abilities even after long time of cessation^4,5. The neurotoxic effects of chronic use and smoking abstinence on the nervous system have not been extensively studied^6–8. However, chronic cigarette smoking increases cardiovascular response⁹, which, in turn, affects retinal responses through altered blood flow¹⁰. In addition, tobacco compounds may increase free radical that would cause macular degeneration along with the action of ischemia¹¹. Whereas smoking effects on color vision are understudied, the existing data are controversial and highlights the importance of a rigorous testing procedure that measures color discrimination^12,13. Thus, to identify the mechanisms underlying neurotoxic smoking effects on multisensory integration, we need to understand how smoking may alter early visual processing.

A visual percept may consist of stimuli that vary over the space (spatial contrast), time (temporal contrast) or direction of motion, and vary in luminance (achromatic) and chromaticity (saturation and hue color)^12,14,15. Thus, chromatic contrast involves chromaticity differences, which can be expressed by the distance in the CIE 1976 uniform chromaticity scale diagram and assessed by thresholds of vectors on the Cambridge Color Test (CCT), for example^16,17. It has the advantage of being used to evaluate in detail whether these anomalies are due to congenital factors or acquired conditions^16,17.

We base our rationale on the premise that chronic exposure to nicotine will led to receptor desensitization and not suffer influence of arousal and increase in attentional resources in smokers¹⁸. The purpose of the present study was to assess the influence of chronic heavy smoking on color discrimination (CD).

Methods

Participants

In this study, 15 non-smokers (mean age = 32.5 years; SD = 9.1; 7 male), 15 cigarette smokers (mean age = 32.1 years; SD = 5.7; 7 male) and 15 deprived smokers (mean age = 31.9 years; SD = 6.3; 7 male) between the ages of 20 and 45 years, who were working as staff or were students at Federal University of Paraiba, were recruited through printed advertisements. Participants were excluded if they had any one of the following criteria: younger than 20 and older than 45 years (since the effects of the human visual system immaturation or aging could superestimate the results^19,20); current history of neurologic disorder; a history of head trauma, color blindness, current or previous drug abuse; drinking more than 10 alcoholic drinks per week or current use of medications that may affect visual processing and cognition. In addition, subjects were required to have a good ocular health: no abnormalities were detected in the fundoscopic examination and in the optical coherence tomography exam. All participants had normal or corrected-to-normal vision as determined by a visual acuity of at least 20/20.

Smokers reported a smoking history of at least 8 years, currently smoked more than 20 cigarettes/day and had a score of >5 on the Fagerstrom Test for Nicotine Dependence (FTND)²¹. Smokers and deprived smokers began smoking at an average of 16.5 years of age (SD = 3.25) and had been smoking for an average 15 years (SD = 6.45). Smokers were allowed to smoke until the beginning of experiment. Deprived smokers were not allowed to smoke 6 hours prior to testing and until the end of the experiment. Non-smokers had never smoked a cigarette. This research followed the ethical principles from the Declaration of Helsinki and was approved by the Committee of Ethics in Research of the Health Sciences Center of Federal University da Paraiba (CAAE: 60944816.3.0000.5188). Written informed consent was obtained from all participants.

Color discrimination test

Stimuli were presented on a 19 inch LG CRT monitor with 1024 × 786 resolution and a rate of 100 Hz. Stimuli were generated using a VSG 2/5 video card (Cambridge Research Systems), which was run on a microcomputer Precision T3500 with W3530 graphics card. All procedures were performed in a room at 26±1°C, with the walls covered in grey for better control of luminance during the experiments. All measurements were performed with binocular vision. Monitor luminance and chromatic calibrations were performed with a ColorCAL MKII photometer (Cambridge Research Systems).

The color vision test was performed using CCT, version 2.0, with Trivector subtest (Cambridge Research Systems; http://www.crsltd.com/tools-for-vision-science/measuring-visual-functions/cambridge-colour-test/). The CTT was performed in a darkened room with illumination provided only by the monitor used to present visual stimuli. Trivector provides a clinical assessment of color vision deficiencies as a rapid means screening of the existence of congenital or acquired deficits¹⁶. CCT uses pseudoisochromatic stimuli (Landolt C) defined by the test colors that are to be discriminated, on an achromatic background. The figure and the background are composed of grouped circles randomly varying in diameter and having no spatial structure (variation of 5.7° arcmin of external diameter and 2.8° arcmin of internal diameter). The luminance variation in each response avoids the existence of learning effect or use of tricks to respond correctly.

The four-alternative forced-choice^16,22 (4-AFC) method was used, and the subjects’ task was to identify, using a remote control response box, whether the Landolt ‘C’ stimulus was presented at the left, right, up or down side of the monitor screen. The participant was instructed to answer even if could not identify the stimulus gap¹⁶. After each correct answer, the chromaticity of the target proceeded closer to that of background, while each wrong answer or omission was followed by the presentation of the target at a greater chromatic distance from the background. The step on the staircase was doubled or divided by two after each incorrect or correct answer, respectively. This process took place throughout the experiment. The experiment ended after 11 reversals for each axis and the threshold was estimated from the six final reversals²³.

The trivector testing protocol estimates sensitivity for the short, medium and long wavelengths through the protanopic, deuteranopic, and tritanopic confusion axes, respectively^23,24. Trivector protocol uses vectors as central measurement. The advantage of this brief test is that it can be performed in about 5 minutes and provides a reliable result¹⁶. The three confusion axes converge at a point called ‘point of intersection’, and the xy coordinates used were: protan (0.6579, 0.5013), deutan (-1.2174, 0.7826) and tritan (0.2573, 0.0000) (for more details, see 17).

In general, we used a default setting where the Landolt ‘C’ had an opening at 1° of visual angle, minimum luminance of 8 cd/m², maximum luminance of 18 cd/m², 6 s of response time for each trial and distance of 269 cm between participant and monitor screen.

Most of these procedures were performed late in the morning or mid-afternoon.

Outcome cutoffs

Lower the threshold, the better the discrimination. Based on previous studies, cutoff points (median + IQR/2) for the trivector test were established to designate color vision impairment. Thus, values above the cut-off points are considered to be out of the normal range and, therefore, may represent visual losses. Baseline values for the confusion axes are as follows: Protan - 40.6 (7.8) / Deutan - 45.6 (9.3) / Tritan - 65.5 (10.5).

The normative values for the trivector can be found in Parameit et al.¹⁷ (mean + median + IQR + upper and lower limits)

Data analysis

The distributions for each group were compared with Shapiro-Wilk. Both groups showed non-normal distribution, thus non-parametric statistical methods were used to analyze the data. For group comparisons, the non-parametric univariate analysis was used, with pairwise comparisons by Mann-Whitney U test. Spearman’s rank correlation coefficients (rho) were conducted to assess the relationship between outcomes of color discrimination data and biosociodemographic variables, such as age, gender and education level. All the calculations were made using SPSS^®, version 21.0.

The effect size (r) estimation was used from the conversion of z-score^25,26:

r = \frac{z}{\sqrt{N}}

Results are presented as medians. Center lines show the medians; box limits indicate the 25th and 75th percentiles as determined by SPSS software; whiskers extend 1.5 times the interquartile range from the 25th and 75th percentiles (ends of the whiskers are the maximum and minimum values). When presented, errors bars represent standard deviations (SD) of the median based on 1000 bootstrap resamplings. Bonferroni correction was the method of adjusting the P-value that we used. P < 0.016 was accepted as statistically significant for multiple comparisons and P < 0.025 for pairwise comparisons.

Results

Color discrimination thresholds were obtained in u'v' units of the CIE 1976 color diagram, for protan, deutan, and tritan axes, respectively. Nonparametric analysis were carried out showing that there were significant differences in discrimination thresholds between groups along the protan (χ²(2) = 26.53, P < 0.001), deutan (χ²(2) = 22.40, P < 0.001) and tritan (χ²(2) = 14.93, P < 0.001) confusion axes. Thresholds for the smokers and deprived smokers were higher than the normative values observed in other studies. Therefore, there was a reduction in color discrimination in both groups. The results of the trivector measurements are shown in Figure 1.

Figure 1.

Trivector test: box-and-whiskers plots for protan (A), deutan (B) and tritan (C) confusion lines. Data are presented in 10^-4 u’v’ units. Each box-and-whiskers plot is based on results for 45 participants. * P < 0.05; ** P < 0.01; *** P < 0.001.

Along protan vectors (Figure 1A), pairwise comparisons showed that discrimination thresholds were higher in the group of smokers compared to non-smokers (U = 132, P = 0.002, r = -.61). In addition, deprived smokers had the highest thresholds compared to the group of non-smokers (U = 105, P < 0.001, r = -.85) and smokers (U = 136, P = 0.002, r = -.58).

Along deutan vectors (Figure 1B), when compared with the control group, smokers (U = 136, P = 0.001, r = -.58) and deprived smokers (U = 108, P < 0.001, r = -.83) presented higher discrimination thresholds, with high effect size. There was statistically significant differences between smokers and deprived smokers (U = 154, P = 0.024, r = -.43).

Along tritan vectors (Figure 1C), when compared with the control group, smokers (U = 140, P = 0.003, r = -.55) and deprived smokers (U = 126, P < 0.001, r = -.67) presented higher discrimination thresholds. There was no statistically significant differences among smokers vs. deprived smokers (P = 0.250).

Correlations

There is no relationship between color discrimination and gender (chi-square = 72, df = 39, P > 0.05). A spearman correlation showed no correlation between FTND and trivector data (P > 0.050), color discrimination and education years [rho = .078, P = 0.515], and color discrimination and age [rho = .096, P = 0.347].

Participants	Age	Group	Gender	Fagerstrom (FTND)	Schooling (years)	First age using a cigarette (years)	Cigar per day	TRIVECTOR_Protan	TRIVECTOR_Deutan	TRIVECTOR_Tritan
1	24	Non-Smokers	male	-	16	-	-	46	59	53
2	29	Non-Smokers	male	-	14	-	-	26	60	73
3	28	Non-Smokers	male	-	14	-	-	28	46	67
4	37	Non-Smokers	male	-	16	-	-	39	46	66
5	23	Non-Smokers	female	-	19	-	-	45	86	123
6	21	Non-Smokers	female	-	15	-	-	23	45	79
7	30	Non-Smokers	female	-	15	-	-	36	49	120
8	45	Non-Smokers	female	-	16	-	-	43	48	102
9	40	Non-Smokers	male	-	15	-	-	45	82	92
10	45	Non-Smokers	female	-	14	-	-	40	48	123
11	21	Non-Smokers	female	-	16	-	-	31	35	88
12	40	Non-Smokers	male	-	16	-	-	50	69	41
13	34	Non-Smokers	male	-	14	-	-	29	45	79
14	34	Non-Smokers	male	-	17	-	-	34	45	99
15	39	Non-Smokers	female	-	15	-	-	33	45	66
16	24	Smokers	female	7	17	18	23	43	60	93
17	23	Smokers	male	7	15	16	25	42	51	103
18	34	Smokers	male	7	13	15	21	57	106	102
19	31	Smokers	male	6	16	16	8	84	60	92
20	39	Smokers	male	6	16	19	9	59	69	190
21	33	Smokers	female	7	15	23	21	31	48	156
22	26	Smokers	female	7	15	16	19	88	144	160
23	35	Smokers	male	6	12	15	23	81	47	65
24	40	Smokers	male	6	15	16	19	44	155	105
25	26	Smokers	female	7	16	15	14	64	91	155
26	29	Smokers	male	8	14	17	16	46	140	194
27	39	Smokers	female	5	16	16	17	49	88	190
28	34	Smokers	female	8	15	15	20	66	93	149
29	33	Smokers	male	7	14	16	18	48	129	194
30	37	Smokers	male	7	15	15	21	75	65	155
31	31	Deprived Smokers	male	6	16	18	14	65	135	234
32	22	Deprived Smokers	male	6	13	17	20	69	93	101
33	29	Deprived Smokers	male	7	15	19	29	73	124	115
34	40	Deprived Smokers	male	7	16	16	20	93	147	265
35	34	Deprived Smokers	male	6	14	17	17	64	85	135
36	23	Deprived Smokers	female	6	15	16	16	61	165	139
37	26	Deprived Smokers	female	9	16	17	9	111	111	111
38	35	Deprived Smokers	female	6	19	15	8	115	92	242
39	37	Deprived Smokers	female	7	16	23	9	111	147	171
40	25	Deprived Smokers	female	7	11	14	12	61	85	107
41	37	Deprived Smokers	female	7	16	15	25	66	193	191
42	34	Deprived Smokers	male	8	11	14	30	90	229	163
43	34	Deprived Smokers	female	8	14	16	11	61	85	107
44	31	Deprived Smokers	male	7	18	15	19	161	133	180

Dataset 1.Patient demographics and Trivector results.

Discussion

The data indicated that smokers groups, as a whole, had higher discrimination thresholds when compared to non-smokers (P < 0.05), indicating the existence of a diffuse impairment in visual processing. Results showed good agreement between the normative data of control groups, being the protan and deutan thresholds lower than tritan thresholds, a pattern repeatedly observed in adults tested with the CCT¹⁷. Moreover, the higher thresholds observed in the group of smokers and deprived smokers are in agreement with the differences observed in other studies using CCT. The effect sizes reached medium to high values.

Small differences in blue-yellow color processing suggest that sensor neurons responsive to the short wavelength may differently operate from those responding to medium and long wavelengths²⁷. Indeed, the koniocelular pathway may not suffer from the influences of tobacco components.

Along the trivector protocol, smokers had more errors in protan and deutan confusion axes (Figure 1). An effect size analysis confirmed that smokers had the largest discrimination errors for protan (r = -85) and deutan (r = -82) confusion axes when comparing against non-smokers. As stated, this result does not support the idea of channel selectivity. However, we base our rational on the existence of diffuse processing impairment, which may include magno- and parvocellular pathways²⁸.

Nicotine enhances dopamine (DA) release through a balance of activation and desensitization of nicotinic acetylcholine receptors (nAChRs) located mainly in the ventral tegmental area and in the striatum^18,29. There are also nAChRs and DA receptors on the retina, so it is not hard to understand that the use of nicotine would enhance attentional resources^30–32. However, we did not observe improvements in color discrimination. So, is there any relationship between smoking and color discrimination? The answer may lie in desensitization, which is one of many brain changes caused by addiction³³. In addition, chronic nicotine exposure leads to nAChRs desensitization through brain upregulation^34,35. Another property of cigarettes is that the more exposure, the greater the need for it activate the receptors, which changes affinity and response properties of the nAChRs^36,37. Whereas nicotine enhancing effects decay and remain unchanged after chronic exposure, this may explain the lower discrimination, but the small similarity, between smokers and non-smokers in some of our data (Figure 1).

Then, why did the deprived smokers group have less discrimination? This can be explained by the withdrawal effect, which induces a hypofunctional effect of DA release^38,39, reflecting both visual processing^40–42 and brain reward function⁴³. Visual attention plays a role for detection of environmental stimuli⁴⁴.

As stated, impairments observed at color discrimination can occur due to cones saturation, amplification of the signals that reach visual cortex or by the action of nicotine in parvocelular pathway⁴⁵. In agreement with studies, color vision impairments may be related to ventral stream, which processes color⁴⁶. However, our tests used pseudoisochromatic stimuli. Thus, color discrimination may have occurred through dorsal and ventral stream²⁸. Maybe it is too soon to conclude anything, but there may be nAChRs in both dorsal and ventral stream⁴⁷. In addition, both streams may suffer from the action of DA hypofunction, affecting directly visual processing^39–41,43.

Knowing the existence of the expression of nAChRs in bipolar, amacrine and ganglionar cells^29,47,48, we suggest that smoking affects visual processing, regardless of deprivation. Although the differences between smokers and non-smokers were small, we could not ignore the existence of many harmful compounds to vision in cigarettes. As noted in others studies, exposure to cigarette smoking^49–55 and solvents^56,57 affects vision. Thus, smoking can be harmful even for passive smokers.

Our limitations need to be considered. We evaluated cigarette smoking as a whole, not the nicotine-only effects^51,52. Which brings us to the idea of further studies, using nicotine gum and the same paradigm used here. Clearly, further work is needed, but this study highlights the relationship between smoking and color discrimination, involving short, medium and long wavelengths²⁷. We conclude that cigarette compounds affect vision^54,55 more than nicotine separately^58–61.

Data availability

Dataset 1: Patient demographics and Trivector results. Raw data of the subjects biosociodemographic and trivector (protan, deutan and tritan) results. doi, 10.5256/f1000research.10714.d150059⁶²

Author contributions

TM: design of the work, data collection and interpretation, and drafting the article. NL: data reanalysis and interpretation and revision of the updated manuscript.

NA: design of the work, data analysis and interpretation, and critical revision of the article. All authors approved the final version to be published

Competing interests

No competing interests were disclosed.

Grant information

National Counsel of Technological and Scientific Development (CNPq), Brazil (grant no., 303822/2010-4), CAPES and Federal University of Paraiba funded this paper.

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Acknowledgments

We appreciate the participation of all who have provided time for this research.

Faculty Opinions recommended

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¹ Department of Psychology, Federal University of Paraíba, Joao Pessoa, Brazil
² Perception, Neuroscience and Behavior Laboratory, Federal University of Paraíba, Joao Pessoa, Brazil

Competing interests

No competing interests were disclosed.

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National Counsel of Technological and Scientific Development (CNPq), Brazil (grant no., 303822/2010-4), CAPES and Federal University of Paraiba funded this paper
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Fernandes TMdP, Almeida NL and dos Santos NA. Comparison of color discrimination in chronic heavy smokers and healthy subjects [version 2; peer review: 1 approved, 1 approved with reservations] F1000Research 2017, 6:85 (https://doi.org/10.12688/f1000research.10714.2)

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Reviewer Report 27 Apr 2017

Marine Raquel Diniz da Rosa, Neuroscience and Behavior Graduate Program , Federal University of Paraíba, João Pessoa, Brazil

Approved

https://doi.org/10.5256/f1000research.12149.r21404

From my point of view, the authors have made relevant changes to the paper and have met all the requests previously suggested. In a way that was reviewed by the authors, it was clarified the cut-off points used for the color discrimination, contributing to a better understanding of the results. In addition, the discussion has improved. Thus, I believe that now the paper should be accepted for publication.

Competing Interests: I am affiliated with The Federal University of Paraiba, where all 3 of the authors, Thiago Monteiro de Paiva Fernandes, Natalia Leandro Almeida and Natanael Antonio dos Santos are also affiliated.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

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Reviewer Report 03 Apr 2017

Goro Maehara, Department of Human Sciences, Kanagawa University, Yokohama, Japan

Approved with Reservations

https://doi.org/10.5256/f1000research.12149.r21405

I found the manuscript was improved but still have some concerns.

1. Outcome Cutoffs
There are some difficulties to understand the Outcome Cutoffs section. The authors should state clearly how they determined and calculated the cutoff points. I also suggest explaining what the values in parentheses represent and what IQR means (interquartile range). Although the authors mentioned ‘(mean + median + IQR + upper and lower limits)’, the plus signs in this phrase seem a bit odd.

2. The Results Section
Please clearly compare the thresholds with the cutoffs values. Not only the median thresholds for smokers, but those for normal observers also exceeds the cutoff values in the deutan and tritan tests, don’t they? I think that the cutoff values might be too strict (low).

Competing Interests: No competing interests were disclosed.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

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Author Response 05 Apr 2017

Thiago P Fernandes, Federal University of Paraiba, Brazil

05 Apr 2017

Author Response
Adding the cutoff values was just one way to meet the review specifications. If you take a brief look at all papers using Trivector as test, there are no specifications ... Continue reading
Adding the cutoff values was just one way to meet the review specifications. If you take a brief look at all papers using Trivector as test, there are no specifications for cut-off values. However, the paper of Paramei et al. (2012) compared the color discrimination across four life decades, and used data obtained in Brazil. If it is possible, at least briefly, to read this and other papers using Trivector, you will notice a little of what I am talking about.

In addition, when reading other articles about Trivector, you will observe a simple pattern: generally, both the control and the observed (experimental) conditions may have values below 100 for the protan or deutan (eg) confusion axes. The values obtained by Mollon & Reffin unfortunately do not match experimental practice. The reasons are more varied: type of computer, type of processor used at the time, condition of luminance or characteristic of the study. The following Mollon & Reffin studies used the commercial version called Cambridge Color Test, where we tried to standardize and avoid differences between studies. This standardization could be observed when Paramei et al. (2012) observed that there are not many differences in results for controls both in Brazil and around the world.

No matter how small the visual processing loss is, the differences that will be classified as impairments will be the statistically significant differences. If it was not clear, I will summarize. Conjecturing: If in one study, for the protan axis, the control group had 50 10^-4 u' v' units and the experimental one had 80 10^-4 u' v' units, having a value of p <.001, this is considered color impairment. Thus, the experimental group would present damage in color processing. This is what indicates most, if not 90% of all articles that used the Trivector as a measure.

I hope it has helped in understanding how the Trivector test works. Even so, i will try to answer your questions below:

1. Outcome Cutoffs

There are some difficulties to understand the Outcome Cutoffs section. The authors should state clearly how they determined and calculated the cutoff points.

This was explained. The mean or median (+ SD or + IQR) for the control group of all the studies that used the Trivector were summed and divided by the number of studies (a simple grand mean / median).

I also suggest explaining what the values in parentheses represent and what IQR means (interquartile range).

"Based on previous studies, cutoff points (median + IQR/2) for the trivector test were established to designate color vision impairment." As stated, median + IQR/2 was established by Paramei et al. (2012). This was also explained. In my opinion, there is no need to explain why using IQR/2 or IQR, since they are simply representing the standard deviation in a non-parametric data

Although the authors mentioned ‘(mean + median + IQR + upper and lower limits)’, the plus signs in this phrase seem a bit odd.

I understand your point of view. However, the reason for inserting this comment into the text was to explain to the reader that there are normative values for the Trivector. These values would be means, medians, tolerance values, etc. They can be observed in the reference article quoted in the cutoffs outcome section.

2. The Results Section

Please clearly compare the thresholds with the cutoffs values. Not only the median thresholds for smokers, but those for normal observers also exceeds the cutoff values in the deutan and tritan tests, don’t they? I think that the cutoff values might be too strict (low).

As explained, the use of cutoff values was only one way to meet the requests of the reviewers. However, in no study using trivector cutoff values are imposed. This is due to the fact that to consider impairment in color vision it is only necessary to have statistically significant differences and to have medium or high effect size.

Nevertheless, the medians of our results for the control group are "beating" with the cutoff values + IQR/2.

So, the purpose of this comment was to try to show how the trivector works. Just read one or two papers that made use of the test and you will note that the differences need not exceed the set values of 100, 100 and 150 10^-4 u' v 'units to prove impairments at color vision. Even differences observed in values smaller than 100 10^-4 u'v 'units are significant differences, since this is a robust and reliable test.

According to Trivector's studies, there is no large or small differences, there is statistically significant differences, with large or small effect sizes. And this was what we observed in our study.

Thank you for the review.
Kind Regards,
Adding the cutoff values was just one way to meet the review specifications. If you take a brief look at all papers using Trivector as test, there are no specifications for cut-off values. However, the paper of Paramei et al. (2012) compared the color discrimination across four life decades, and used data obtained in Brazil. If it is possible, at least briefly, to read this and other papers using Trivector, you will notice a little of what I am talking about.

In addition, when reading other articles about Trivector, you will observe a simple pattern: generally, both the control and the observed (experimental) conditions may have values below 100 for the protan or deutan (eg) confusion axes. The values obtained by Mollon & Reffin unfortunately do not match experimental practice. The reasons are more varied: type of computer, type of processor used at the time, condition of luminance or characteristic of the study. The following Mollon & Reffin studies used the commercial version called Cambridge Color Test, where we tried to standardize and avoid differences between studies. This standardization could be observed when Paramei et al. (2012) observed that there are not many differences in results for controls both in Brazil and around the world.

No matter how small the visual processing loss is, the differences that will be classified as impairments will be the statistically significant differences. If it was not clear, I will summarize. Conjecturing: If in one study, for the protan axis, the control group had 50 10^-4 u' v' units and the experimental one had 80 10^-4 u' v' units, having a value of p <.001, this is considered color impairment. Thus, the experimental group would present damage in color processing. This is what indicates most, if not 90% of all articles that used the Trivector as a measure.

I hope it has helped in understanding how the Trivector test works. Even so, i will try to answer your questions below:

1. Outcome Cutoffs

There are some difficulties to understand the Outcome Cutoffs section. The authors should state clearly how they determined and calculated the cutoff points.

This was explained. The mean or median (+ SD or + IQR) for the control group of all the studies that used the Trivector were summed and divided by the number of studies (a simple grand mean / median).

I also suggest explaining what the values in parentheses represent and what IQR means (interquartile range).

"Based on previous studies, cutoff points (median + IQR/2) for the trivector test were established to designate color vision impairment." As stated, median + IQR/2 was established by Paramei et al. (2012). This was also explained. In my opinion, there is no need to explain why using IQR/2 or IQR, since they are simply representing the standard deviation in a non-parametric data

Although the authors mentioned ‘(mean + median + IQR + upper and lower limits)’, the plus signs in this phrase seem a bit odd.

I understand your point of view. However, the reason for inserting this comment into the text was to explain to the reader that there are normative values for the Trivector. These values would be means, medians, tolerance values, etc. They can be observed in the reference article quoted in the cutoffs outcome section.

2. The Results Section

Please clearly compare the thresholds with the cutoffs values. Not only the median thresholds for smokers, but those for normal observers also exceeds the cutoff values in the deutan and tritan tests, don’t they? I think that the cutoff values might be too strict (low).

As explained, the use of cutoff values was only one way to meet the requests of the reviewers. However, in no study using trivector cutoff values are imposed. This is due to the fact that to consider impairment in color vision it is only necessary to have statistically significant differences and to have medium or high effect size.

Nevertheless, the medians of our results for the control group are "beating" with the cutoff values + IQR/2.

So, the purpose of this comment was to try to show how the trivector works. Just read one or two papers that made use of the test and you will note that the differences need not exceed the set values of 100, 100 and 150 10^-4 u' v 'units to prove impairments at color vision. Even differences observed in values smaller than 100 10^-4 u'v 'units are significant differences, since this is a robust and reliable test.

According to Trivector's studies, there is no large or small differences, there is statistically significant differences, with large or small effect sizes. And this was what we observed in our study.

Thank you for the review.
Kind Regards,
Competing Interests: None Close
Report a concern
Reviewer Response 06 Jun 2017

Goro Maehara, Department of Human Sciences, Kanagawa University, Yokohama, Japan

06 Jun 2017

Reviewer Response
Dear Thiago,

The authors have solved the major concern in my 1st response through the revision process. Mollon & Regan (2000) set the cutoff values relatively high probably because the test ... Continue reading
Dear Thiago,

The authors have solved the major concern in my 1st response through the revision process. Mollon & Regan (2000) set the cutoff values relatively high probably because the test was originally designed for detecting color blindness.
Here we need to tackle the issues about the present cutoff values.

I agree with another reviewer in that the standard of normality is useful for making a comparison between the present and previous studies. Any analysis in a paper must be logical even if authors think a specific analysis is not very important. In the present study, not only the thresholds for the smoker, but also those for normal controls exceeded the cutoff values for the tritan test (and deutan test, too?). The authors need to somehow solve this logical problem.

Thank you for the explanations on the cutoff values. That is, the cutoff values were defined as the average of normal observers’ (median threshold + IQR/2) reported by the previous studies (or only by Paramei?). It will be helpful for readers to rewrite the Outcome Cutoff section as the authors commented above.

The cutoff values of (median threshold + IQR/2) mean that 25 % of the population is classified as abnormal. It seems reasonable for me to increase the cutoff values because 25 % of the population is too much. This might be a possible solution.

Another possible solution could be discussing why the thresholds for normal observers exceeded the cutoff values in the Discussion section. The authors could also emphasize the importance of statistical differences there.

If the authors have any idea for workable solutions, please feel free to let me know.

Minor concerns,

My previous comment on IQR was misleading. I would like to suggest inserting ‘( interquartile range)’ just after IQR when the authors first use the abbreviation.

If the authors used data reported by researchers other than Paramei (2012) for the cutoff value calculation, I suggest including the citations of the studies.

Best wishes,

Goro
Dear Thiago,

The authors have solved the major concern in my 1st response through the revision process. Mollon & Regan (2000) set the cutoff values relatively high probably because the test was originally designed for detecting color blindness.
Here we need to tackle the issues about the present cutoff values.

I agree with another reviewer in that the standard of normality is useful for making a comparison between the present and previous studies. Any analysis in a paper must be logical even if authors think a specific analysis is not very important. In the present study, not only the thresholds for the smoker, but also those for normal controls exceeded the cutoff values for the tritan test (and deutan test, too?). The authors need to somehow solve this logical problem.

Thank you for the explanations on the cutoff values. That is, the cutoff values were defined as the average of normal observers’ (median threshold + IQR/2) reported by the previous studies (or only by Paramei?). It will be helpful for readers to rewrite the Outcome Cutoff section as the authors commented above.

The cutoff values of (median threshold + IQR/2) mean that 25 % of the population is classified as abnormal. It seems reasonable for me to increase the cutoff values because 25 % of the population is too much. This might be a possible solution.

Another possible solution could be discussing why the thresholds for normal observers exceeded the cutoff values in the Discussion section. The authors could also emphasize the importance of statistical differences there.

If the authors have any idea for workable solutions, please feel free to let me know.

Minor concerns,

My previous comment on IQR was misleading. I would like to suggest inserting ‘( interquartile range)’ just after IQR when the authors first use the abbreviation.

If the authors used data reported by researchers other than Paramei (2012) for the cutoff value calculation, I suggest including the citations of the studies.

Best wishes,

Goro
Competing Interests: No competing interests were disclosed. Close
Report a concern
Respond or Comment

COMMENTS ON THIS REPORT

Author Response 05 Apr 2017

Thiago P Fernandes, Federal University of Paraiba, Brazil

05 Apr 2017

Author Response
Adding the cutoff values was just one way to meet the review specifications. If you take a brief look at all papers using Trivector as test, there are no specifications ... Continue reading
Adding the cutoff values was just one way to meet the review specifications. If you take a brief look at all papers using Trivector as test, there are no specifications for cut-off values. However, the paper of Paramei et al. (2012) compared the color discrimination across four life decades, and used data obtained in Brazil. If it is possible, at least briefly, to read this and other papers using Trivector, you will notice a little of what I am talking about.

In addition, when reading other articles about Trivector, you will observe a simple pattern: generally, both the control and the observed (experimental) conditions may have values below 100 for the protan or deutan (eg) confusion axes. The values obtained by Mollon & Reffin unfortunately do not match experimental practice. The reasons are more varied: type of computer, type of processor used at the time, condition of luminance or characteristic of the study. The following Mollon & Reffin studies used the commercial version called Cambridge Color Test, where we tried to standardize and avoid differences between studies. This standardization could be observed when Paramei et al. (2012) observed that there are not many differences in results for controls both in Brazil and around the world.

No matter how small the visual processing loss is, the differences that will be classified as impairments will be the statistically significant differences. If it was not clear, I will summarize. Conjecturing: If in one study, for the protan axis, the control group had 50 10^-4 u' v' units and the experimental one had 80 10^-4 u' v' units, having a value of p <.001, this is considered color impairment. Thus, the experimental group would present damage in color processing. This is what indicates most, if not 90% of all articles that used the Trivector as a measure.

I hope it has helped in understanding how the Trivector test works. Even so, i will try to answer your questions below:

1. Outcome Cutoffs

There are some difficulties to understand the Outcome Cutoffs section. The authors should state clearly how they determined and calculated the cutoff points.

This was explained. The mean or median (+ SD or + IQR) for the control group of all the studies that used the Trivector were summed and divided by the number of studies (a simple grand mean / median).

I also suggest explaining what the values in parentheses represent and what IQR means (interquartile range).

"Based on previous studies, cutoff points (median + IQR/2) for the trivector test were established to designate color vision impairment." As stated, median + IQR/2 was established by Paramei et al. (2012). This was also explained. In my opinion, there is no need to explain why using IQR/2 or IQR, since they are simply representing the standard deviation in a non-parametric data

Although the authors mentioned ‘(mean + median + IQR + upper and lower limits)’, the plus signs in this phrase seem a bit odd.

I understand your point of view. However, the reason for inserting this comment into the text was to explain to the reader that there are normative values for the Trivector. These values would be means, medians, tolerance values, etc. They can be observed in the reference article quoted in the cutoffs outcome section.

2. The Results Section

Please clearly compare the thresholds with the cutoffs values. Not only the median thresholds for smokers, but those for normal observers also exceeds the cutoff values in the deutan and tritan tests, don’t they? I think that the cutoff values might be too strict (low).

As explained, the use of cutoff values was only one way to meet the requests of the reviewers. However, in no study using trivector cutoff values are imposed. This is due to the fact that to consider impairment in color vision it is only necessary to have statistically significant differences and to have medium or high effect size.

Nevertheless, the medians of our results for the control group are "beating" with the cutoff values + IQR/2.

So, the purpose of this comment was to try to show how the trivector works. Just read one or two papers that made use of the test and you will note that the differences need not exceed the set values of 100, 100 and 150 10^-4 u' v 'units to prove impairments at color vision. Even differences observed in values smaller than 100 10^-4 u'v 'units are significant differences, since this is a robust and reliable test.

According to Trivector's studies, there is no large or small differences, there is statistically significant differences, with large or small effect sizes. And this was what we observed in our study.

Thank you for the review.
Kind Regards,
Adding the cutoff values was just one way to meet the review specifications. If you take a brief look at all papers using Trivector as test, there are no specifications for cut-off values. However, the paper of Paramei et al. (2012) compared the color discrimination across four life decades, and used data obtained in Brazil. If it is possible, at least briefly, to read this and other papers using Trivector, you will notice a little of what I am talking about.

In addition, when reading other articles about Trivector, you will observe a simple pattern: generally, both the control and the observed (experimental) conditions may have values below 100 for the protan or deutan (eg) confusion axes. The values obtained by Mollon & Reffin unfortunately do not match experimental practice. The reasons are more varied: type of computer, type of processor used at the time, condition of luminance or characteristic of the study. The following Mollon & Reffin studies used the commercial version called Cambridge Color Test, where we tried to standardize and avoid differences between studies. This standardization could be observed when Paramei et al. (2012) observed that there are not many differences in results for controls both in Brazil and around the world.

No matter how small the visual processing loss is, the differences that will be classified as impairments will be the statistically significant differences. If it was not clear, I will summarize. Conjecturing: If in one study, for the protan axis, the control group had 50 10^-4 u' v' units and the experimental one had 80 10^-4 u' v' units, having a value of p <.001, this is considered color impairment. Thus, the experimental group would present damage in color processing. This is what indicates most, if not 90% of all articles that used the Trivector as a measure.

I hope it has helped in understanding how the Trivector test works. Even so, i will try to answer your questions below:

1. Outcome Cutoffs

There are some difficulties to understand the Outcome Cutoffs section. The authors should state clearly how they determined and calculated the cutoff points.

This was explained. The mean or median (+ SD or + IQR) for the control group of all the studies that used the Trivector were summed and divided by the number of studies (a simple grand mean / median).

I also suggest explaining what the values in parentheses represent and what IQR means (interquartile range).

"Based on previous studies, cutoff points (median + IQR/2) for the trivector test were established to designate color vision impairment." As stated, median + IQR/2 was established by Paramei et al. (2012). This was also explained. In my opinion, there is no need to explain why using IQR/2 or IQR, since they are simply representing the standard deviation in a non-parametric data

Although the authors mentioned ‘(mean + median + IQR + upper and lower limits)’, the plus signs in this phrase seem a bit odd.

I understand your point of view. However, the reason for inserting this comment into the text was to explain to the reader that there are normative values for the Trivector. These values would be means, medians, tolerance values, etc. They can be observed in the reference article quoted in the cutoffs outcome section.

2. The Results Section

Please clearly compare the thresholds with the cutoffs values. Not only the median thresholds for smokers, but those for normal observers also exceeds the cutoff values in the deutan and tritan tests, don’t they? I think that the cutoff values might be too strict (low).

As explained, the use of cutoff values was only one way to meet the requests of the reviewers. However, in no study using trivector cutoff values are imposed. This is due to the fact that to consider impairment in color vision it is only necessary to have statistically significant differences and to have medium or high effect size.

Nevertheless, the medians of our results for the control group are "beating" with the cutoff values + IQR/2.

So, the purpose of this comment was to try to show how the trivector works. Just read one or two papers that made use of the test and you will note that the differences need not exceed the set values of 100, 100 and 150 10^-4 u' v 'units to prove impairments at color vision. Even differences observed in values smaller than 100 10^-4 u'v 'units are significant differences, since this is a robust and reliable test.

According to Trivector's studies, there is no large or small differences, there is statistically significant differences, with large or small effect sizes. And this was what we observed in our study.

Thank you for the review.
Kind Regards,
Competing Interests: None Close
Report a concern
Reviewer Response 06 Jun 2017

Goro Maehara, Department of Human Sciences, Kanagawa University, Yokohama, Japan

06 Jun 2017

Reviewer Response
Dear Thiago,

The authors have solved the major concern in my 1st response through the revision process. Mollon & Regan (2000) set the cutoff values relatively high probably because the test ... Continue reading
Dear Thiago,

The authors have solved the major concern in my 1st response through the revision process. Mollon & Regan (2000) set the cutoff values relatively high probably because the test was originally designed for detecting color blindness.
Here we need to tackle the issues about the present cutoff values.

I agree with another reviewer in that the standard of normality is useful for making a comparison between the present and previous studies. Any analysis in a paper must be logical even if authors think a specific analysis is not very important. In the present study, not only the thresholds for the smoker, but also those for normal controls exceeded the cutoff values for the tritan test (and deutan test, too?). The authors need to somehow solve this logical problem.

Thank you for the explanations on the cutoff values. That is, the cutoff values were defined as the average of normal observers’ (median threshold + IQR/2) reported by the previous studies (or only by Paramei?). It will be helpful for readers to rewrite the Outcome Cutoff section as the authors commented above.

The cutoff values of (median threshold + IQR/2) mean that 25 % of the population is classified as abnormal. It seems reasonable for me to increase the cutoff values because 25 % of the population is too much. This might be a possible solution.

Another possible solution could be discussing why the thresholds for normal observers exceeded the cutoff values in the Discussion section. The authors could also emphasize the importance of statistical differences there.

If the authors have any idea for workable solutions, please feel free to let me know.

Minor concerns,

My previous comment on IQR was misleading. I would like to suggest inserting ‘( interquartile range)’ just after IQR when the authors first use the abbreviation.

If the authors used data reported by researchers other than Paramei (2012) for the cutoff value calculation, I suggest including the citations of the studies.

Best wishes,

Goro
Dear Thiago,

The authors have solved the major concern in my 1st response through the revision process. Mollon & Regan (2000) set the cutoff values relatively high probably because the test was originally designed for detecting color blindness.
Here we need to tackle the issues about the present cutoff values.

I agree with another reviewer in that the standard of normality is useful for making a comparison between the present and previous studies. Any analysis in a paper must be logical even if authors think a specific analysis is not very important. In the present study, not only the thresholds for the smoker, but also those for normal controls exceeded the cutoff values for the tritan test (and deutan test, too?). The authors need to somehow solve this logical problem.

Thank you for the explanations on the cutoff values. That is, the cutoff values were defined as the average of normal observers’ (median threshold + IQR/2) reported by the previous studies (or only by Paramei?). It will be helpful for readers to rewrite the Outcome Cutoff section as the authors commented above.

The cutoff values of (median threshold + IQR/2) mean that 25 % of the population is classified as abnormal. It seems reasonable for me to increase the cutoff values because 25 % of the population is too much. This might be a possible solution.

Another possible solution could be discussing why the thresholds for normal observers exceeded the cutoff values in the Discussion section. The authors could also emphasize the importance of statistical differences there.

If the authors have any idea for workable solutions, please feel free to let me know.

Minor concerns,

My previous comment on IQR was misleading. I would like to suggest inserting ‘( interquartile range)’ just after IQR when the authors first use the abbreviation.

If the authors used data reported by researchers other than Paramei (2012) for the cutoff value calculation, I suggest including the citations of the studies.

Best wishes,

Goro
Competing Interests: No competing interests were disclosed. Close
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Version 1

VERSION 1

PUBLISHED 27 Jan 2017

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Reviewer Report 17 Mar 2017

Marine Raquel Diniz da Rosa, Neuroscience and Behavior Graduate Program , Federal University of Paraíba, João Pessoa, Brazil

Approved with Reservations

https://doi.org/10.5256/f1000research.11553.r20562

The article investigates and compares color discrimination in chronic smokers and healthy individuals. The authors found a lower significant color discrimination in chronic smokers.

However, I believe that in order to clarify the cut-off point of color discrimination, authors should write in Methods the standard of normality used to rate low or high color discrimination. In addition, in the description of the results, for better understanding, the authors should explain better the results (which are below the expected) and then the significance of them.

The results suggest a possible, even small, important change to the color discrimination of smokers which deserves attention and should be better studied. Therefore, I believe that the paper should be accepted for publication with the aforementioned suggestions.

References

1. Mollon JD, Regan BC: Cambridge Colour Test Handbook. Cambridge Research Systems Ltd.2000.
2. Goulart PRK: A computer-controlled color vision test for children and non-verbal subjects based on the Mollo-Reffin color discrimination test. Doctoral Dissertation,Universidade Federal do Pará. 2008. 75
3. Oliveira A.R: Chromatic and achromatic psychophysical evaluations of men and women exposed to organic solvents. Master Dissertation Universidade Federal da Paraíba. 2015. 75
4. Goulart PR, Bandeira ML, Tsubota D, Oiwa NN, et al.: A computer-controlled color vision test for children based on the Cambridge Colour Test.Vis Neurosci. 25 (3): 445-50 PubMed Abstract | Publisher Full Text

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Author Response 30 Mar 2017

Thiago P Fernandes, Federal University of Paraiba, Brazil

30 Mar 2017

Author Response
Dear Marine,
First of all, many thanks for the reading and suggestions for our manuscript.

We will try to answer your questions below:
- However, I believe
... Continue reading
Dear Marine,
First of all, many thanks for the reading and suggestions for our manuscript.

We will try to answer your questions below:

However, I believe that in order to clarify the cut-off point of color discrimination, authors should write in Methods the standard of normality used to rate low or high color discrimination.

We appreciate the suggestion. These changes were made. We stand by calculating the average of the control group of all studies using Trivector in Brazil and using the normative data for age groups used by Paramei et al.¹

In addition, in the description of the results, for better understanding, the authors should explain better the results (which are below the expected) and then the significance of them.

We appreciate the suggestion. Although the description of Trivector's results is quite directive (for details, see ^2-5), we agreed that the way the results were presented was below expectations.These changes were made.

The results suggest a possible, even small, important change to the color discrimination of smokers which deserves attention and should be better studied.

In agreement. Based on this suggestion, we added a few paragraphs on the importance of the present study, see Introduction and Discussion.

References:

Paramei GV. Color discrimination across four life decades assessed by the Cambridge Colour Test. J Opt Soc Am A Opt Image Sci Vis. 2012;29(2):A290-297.

Lacerda EM da CB, Ventura DF, Silveira LC de L: Visual assessment by psychophysical methods of people subjected to occupational exposure to organic solvents. Psicol USP. 2011;22(1):117–145. 10.1590/S0103-65642011005000011

Oliveira AR: Avaliações psicofísicas cromática e acromática de homens e mulheres expostos a solventes orgânicos.2015. Reference Source

Goulart PRK, Bandeira ML, Tsubota D, Oiwa NN, Costa MF, Ventura DF. A computer-controlled color vision test for children based on the Cambridge Colour Test. Vis Neurosci. 2008;25(3):445-450. doi:10.1017/S0952523808080589.

Costa MF, Oliveira AGF, Feitosa-Santana C, Zatz M, Ventura DF. Red-Green Color Vision Impairment in Duchenne Muscular Dystrophy. Am J Hum Genet. 2007;80(6):1064-1075
Dear Marine,
First of all, many thanks for the reading and suggestions for our manuscript.

We will try to answer your questions below:

However, I believe that in order to clarify the cut-off point of color discrimination, authors should write in Methods the standard of normality used to rate low or high color discrimination.

We appreciate the suggestion. These changes were made. We stand by calculating the average of the control group of all studies using Trivector in Brazil and using the normative data for age groups used by Paramei et al.¹

In addition, in the description of the results, for better understanding, the authors should explain better the results (which are below the expected) and then the significance of them.

We appreciate the suggestion. Although the description of Trivector's results is quite directive (for details, see ^2-5), we agreed that the way the results were presented was below expectations.These changes were made.

The results suggest a possible, even small, important change to the color discrimination of smokers which deserves attention and should be better studied.

In agreement. Based on this suggestion, we added a few paragraphs on the importance of the present study, see Introduction and Discussion.

References:

Paramei GV. Color discrimination across four life decades assessed by the Cambridge Colour Test. J Opt Soc Am A Opt Image Sci Vis. 2012;29(2):A290-297.

Lacerda EM da CB, Ventura DF, Silveira LC de L: Visual assessment by psychophysical methods of people subjected to occupational exposure to organic solvents. Psicol USP. 2011;22(1):117–145. 10.1590/S0103-65642011005000011

Oliveira AR: Avaliações psicofísicas cromática e acromática de homens e mulheres expostos a solventes orgânicos.2015. Reference Source

Goulart PRK, Bandeira ML, Tsubota D, Oiwa NN, Costa MF, Ventura DF. A computer-controlled color vision test for children based on the Cambridge Colour Test. Vis Neurosci. 2008;25(3):445-450. doi:10.1017/S0952523808080589.

Costa MF, Oliveira AGF, Feitosa-Santana C, Zatz M, Ventura DF. Red-Green Color Vision Impairment in Duchenne Muscular Dystrophy. Am J Hum Genet. 2007;80(6):1064-1075
Competing Interests: None. Close
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COMMENTS ON THIS REPORT

Author Response 30 Mar 2017

Thiago P Fernandes, Federal University of Paraiba, Brazil

30 Mar 2017

Author Response
Dear Marine,
First of all, many thanks for the reading and suggestions for our manuscript.

We will try to answer your questions below:
- However, I believe
... Continue reading
Dear Marine,
First of all, many thanks for the reading and suggestions for our manuscript.

We will try to answer your questions below:

However, I believe that in order to clarify the cut-off point of color discrimination, authors should write in Methods the standard of normality used to rate low or high color discrimination.

We appreciate the suggestion. These changes were made. We stand by calculating the average of the control group of all studies using Trivector in Brazil and using the normative data for age groups used by Paramei et al.¹

In addition, in the description of the results, for better understanding, the authors should explain better the results (which are below the expected) and then the significance of them.

We appreciate the suggestion. Although the description of Trivector's results is quite directive (for details, see ^2-5), we agreed that the way the results were presented was below expectations.These changes were made.

The results suggest a possible, even small, important change to the color discrimination of smokers which deserves attention and should be better studied.

In agreement. Based on this suggestion, we added a few paragraphs on the importance of the present study, see Introduction and Discussion.

References:

Paramei GV. Color discrimination across four life decades assessed by the Cambridge Colour Test. J Opt Soc Am A Opt Image Sci Vis. 2012;29(2):A290-297.

Lacerda EM da CB, Ventura DF, Silveira LC de L: Visual assessment by psychophysical methods of people subjected to occupational exposure to organic solvents. Psicol USP. 2011;22(1):117–145. 10.1590/S0103-65642011005000011

Oliveira AR: Avaliações psicofísicas cromática e acromática de homens e mulheres expostos a solventes orgânicos.2015. Reference Source

Goulart PRK, Bandeira ML, Tsubota D, Oiwa NN, Costa MF, Ventura DF. A computer-controlled color vision test for children based on the Cambridge Colour Test. Vis Neurosci. 2008;25(3):445-450. doi:10.1017/S0952523808080589.

Costa MF, Oliveira AGF, Feitosa-Santana C, Zatz M, Ventura DF. Red-Green Color Vision Impairment in Duchenne Muscular Dystrophy. Am J Hum Genet. 2007;80(6):1064-1075
Dear Marine,
First of all, many thanks for the reading and suggestions for our manuscript.

We will try to answer your questions below:

However, I believe that in order to clarify the cut-off point of color discrimination, authors should write in Methods the standard of normality used to rate low or high color discrimination.

We appreciate the suggestion. These changes were made. We stand by calculating the average of the control group of all studies using Trivector in Brazil and using the normative data for age groups used by Paramei et al.¹

In addition, in the description of the results, for better understanding, the authors should explain better the results (which are below the expected) and then the significance of them.

We appreciate the suggestion. Although the description of Trivector's results is quite directive (for details, see ^2-5), we agreed that the way the results were presented was below expectations.These changes were made.

The results suggest a possible, even small, important change to the color discrimination of smokers which deserves attention and should be better studied.

In agreement. Based on this suggestion, we added a few paragraphs on the importance of the present study, see Introduction and Discussion.

References:

Paramei GV. Color discrimination across four life decades assessed by the Cambridge Colour Test. J Opt Soc Am A Opt Image Sci Vis. 2012;29(2):A290-297.

Lacerda EM da CB, Ventura DF, Silveira LC de L: Visual assessment by psychophysical methods of people subjected to occupational exposure to organic solvents. Psicol USP. 2011;22(1):117–145. 10.1590/S0103-65642011005000011

Oliveira AR: Avaliações psicofísicas cromática e acromática de homens e mulheres expostos a solventes orgânicos.2015. Reference Source

Goulart PRK, Bandeira ML, Tsubota D, Oiwa NN, Costa MF, Ventura DF. A computer-controlled color vision test for children based on the Cambridge Colour Test. Vis Neurosci. 2008;25(3):445-450. doi:10.1017/S0952523808080589.

Costa MF, Oliveira AGF, Feitosa-Santana C, Zatz M, Ventura DF. Red-Green Color Vision Impairment in Duchenne Muscular Dystrophy. Am J Hum Genet. 2007;80(6):1064-1075
Competing Interests: None. Close
Report a concern

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Reviewer Report 10 Mar 2017

Goro Maehara, Department of Human Sciences, Kanagawa University, Yokohama, Japan

Not Approved

https://doi.org/10.5256/f1000research.11553.r20559

The authors measured color discrimination thresholds in chronic smokers and non-smokers using the Cambridge Color Test. The color discrimination thresholds were significantly higher for chronic smokers than non-smokers. Although their methods were scientifically sound, the thresholds for chronic smokers were not high enough to conclude that smoking impairs their color discrimination abilities.

Major concern

1. The thresholds for chronic smokers
According to Mollon & Regan (2000)¹, “normal limits for performance for first examination on the basic “Trivector” test are 100 (protan), 100 (deutan) and 150 (tritan).” The threshold medians for chronic smokers were lower than those values, except for the deutan threshold median for deprived smokers.
Although there were statistically significant difference between chronic smokers and non-smokers, the thresholds for non-smokers were very low (about 40, 50, and 80 in 10⁻⁴ u’ v’ units for protan, deutan, and tritan, respectively). In addition, the differences in thresholds (about 60) make little change in color appearance.
Taken together, it seems difficult to conclude that smoking impairs color discrimination abilities.

Minor concern

1. Equation 1
I am not sure why Weber contrast (equation 1) needs to be explained in the Methods section. The authors should state clearly how they used the equation in their experiment.

2. Results
The authors just listed the statistical results in the Results section. I suggest describing the results in the more detailed way (ex. thresholds were higher for smokers than non-smokers, U = 132, P = 0.002, r = -.61).

3. 3rd paragraph in the Discussion section
The authors stated that “smokers were more sensitive to protanopic and deutanopic confusion axes.” This sentence is confusing. Which does this sentence mean, “more sensitive than non-smokers” or “more sensitive than to tritanopic axes”?

References

1. Mollon JD, Regan BC: Cambridge Colour Test Handbook (version 1.1). Cambridge Research Systems Ltd.2000. Reference Source

Competing Interests: No competing interests were disclosed.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

CITE

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Author Response 13 Mar 2017

Thiago P Fernandes, Federal University of Paraiba, Brazil

13 Mar 2017

Author Response
Dear Goro Maehara,

We respectfully thank you for the reading and responding to our manuscript.

If I may contest your decision of this manuscript, we respectfully do not ... Continue reading
Dear Goro Maehara,

We respectfully thank you for the reading and responding to our manuscript.

If I may contest your decision of this manuscript, we respectfully do not agree that it can not be accepted as an acceptable scientific standard. We believe that the data contribute in terms of scientific validity, and because we know that there are few studies on color vision in chronic smoking (and abstinence).

We will try to answer your questions below:

"Although their methods were scientifically sound, the thresholds for chronic smokers were not high enough to conclude that smoking impairs their color discrimination abilities."

Although we did not observe large differences between the thresholds of the control group and the group of smokers, we agree with Lakens (2013) and Field (2013) noting that the statistically significant differences are consonant with the related effect sizes which fluctuated between mid-to-high values (r values between .50 and .61; chronic smokers x controls). Moreover, when comparing the group of smokers with deprived smokers, we observed that these differences were not so large (r values reaching .50). We do not know if the smoking habit, cigarette compounds or smoking per se, are responsible for the decrease in color discrimination.

But there was a loss of color discrimination, suggesting the idea that visual color processing may be diffusely impaired in smokers (Besson et al., 2007; Vallejo, Buisson, Bertrand, & Green, 2005; Zhang, Dong, Doyon, & Dani, 2012). We base this hypothesis on the fact that the many cigarette compounds, including organic solvents in the cigarette smoke, impairs color processing per se.

Major Concern

'The threshold medians for chronic smokers were lower than those values, except for the deutan threshold median for deprived smokers. Although there were statistically significant difference between chronic smokers and non-smokers, the thresholds for non-smokers were very low (about 40, 50, and 80 in 10−4 u’ v’ units for protan, deutan, and tritan, respectively). In addition, the differences in thresholds (about 60) make little change in color appearance. Taken together, it seems difficult to conclude that smoking impairs color discrimination abilities.'

Many thanks for the review.

Based on our expertise in the use of Cambridge Colour Test: the minor the threshold, better discrimination. If a group (in this case, smokers group) has a higher threshold, this means that they needed more chromatic contrast to detect the stimuli. Thus, higher thresholds means lower discriminiation along confusion axes (Hasrod & Rubin, 2015).

After the publication of Mollon and Reffin's about the CCT (2000), several studies using Trivector have been published. Including preliminary norms for the use of CCT (Ventura et al., 2003), which was considered by the creators of the CCT on the software website (http://www.crsltd.com/tools-for-vision-science/measuring-visual-functions/cambridge-colour-test/)

We re-checked our Trivector data and compared to several studies and we observed that we're with similar values for control groups. If another group (such smokers or deprived smokers) had higher thresholds, it means that they differ from the standard values and are likely to have color vision impairments.

As shown in the other studies, values for control subjects have fluctuated precisely in the values that we obtained in our data (Costa et al., 2007; Goulart et al., 2008; Paramei, 2012, 2014; Ventura et al., 2002).

Thus, the raising of the threshold of smokers is possibly connected with smoking conditions, since we've matched all possibly intervenient variables.

Taken together, we can not ignore that, although not as large, the differences were significant in this sample. Based on previous studies, even though there are small differences, they need to be punctuated, since we agree that this is an important area that requires further research.

Minor concern

1. Equation 1; I am not sure why Weber contrast (equation 1) needs to be explained in the Methods section. The authors should state clearly how they used the equation in their experiment.

Ops! Many thanks! Since CCT already uses this default setting, we strongly agreed with your review. These changes will be in the second version of the manuscript (we will remove it).

2. Results; The authors just listed the statistical results in the Results section. I suggest describing the results in the more detailed way (ex. thresholds were higher for smokers than non-smokers, U = 132, P = 0.002, r = -.61).

Many thanks again. We believe that the way you suggested will facilitate the reader's understanding and will enhance the scientific level of our writing. We fixed it. They will be more descriptive in the next version

3. 3rd paragraph in the Discussion section; The authors stated that “smokers were more sensitive to protanopic and deutanopic confusion axes.” This sentence is confusing. Which does this sentence mean, “more sensitive than non-smokers” or “more sensitive than to tritanopic axes”?

We appreciate the suggestion and agree that the use of two forms of explanation may actually confuse the reader. We will correct this.

However, when we mention that the smoking group was more sensitive to the protanopic or deutanopic axes, we simply mean that they made more errors than the control group, for example. That is, they needed more chromatic contrast (they were more sensitive) than the comparison group. The confusion axes refer to the red (protanopic), green (deutanopic) and blue (tritanopic) axes. Thus, if any group was more sensitive to the red confusion axis, forr example, it means that they possibly had impairments in the processing of this wavelength.

In this way, based on the apointments above, the 'not approved' status is honestly inconsistent with the content of the work. We ask you to reconsider your decision and we are grateful for the comment, reading, and review of the manuscript.

References

1. Lakens D. Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Front. Psychol. [Internet]. 2013 [cited 2017 Mar 10];4. Available from: http://journal.frontiersin.org/article/10.3389/fpsyg.2013.00863/abstract

2. Field A. Discovering Statistics Using IBM SPSS Statistics. SAGE; 2013.

3. Besson M, Granon S, Mameli-Engvall M, Cloëz-Tayarani I, Maubourguet N, Cormier A, et al. Long-term effects of chronic nicotine exposure on brain nicotinic receptors. Proc. Natl. Acad. Sci. 2007;104:8155–60.

4. Vallejo YF, Buisson B, Bertrand D, Green WN. Chronic Nicotine Exposure Upregulates Nicotinic Receptors by a Novel Mechanism. J. Neurosci. Off. J. Soc. Neurosci. 2005;25:5563–72.

5. Zhang L, Dong Y, Doyon WM, Dani JA. Withdrawal from Chronic Nicotine Exposure Alters Dopamine Signaling Dynamics in the Nucleus Accumbens. Biol. Psychiatry. 2012;71:184–91.

6. Mollon JD, Regan BC. Cambridge Colour Test Handbook [Internet]. 2000. Available from: https://sites.oxy.edu/clint/physio/article/CAMBRIDGECOLOURTESTHandbook.pdf

7. Ventura DF, Silveira LC de L, Rodrigues A, Costa MF. Preliminary Norms for the Cambridge Colour Test. 2003;331–9.

8. Costa MF, Oliveira AGF, Feitosa-Santana C, Zatz M, Ventura DF. Red-Green Color Vision Impairment in Duchenne Muscular Dystrophy. Am. J. Hum. Genet. 2007;80:1064–75.

9. Feitosa-Santana C, Barboni MTS, Oiwa NN, Paramei GV, Simões ALAC, Da Costa MF, et al. Irreversible color vision losses in patients with chronic mercury vapor intoxication. Vis. Neurosci. 2008;25:487–91.

10. Goulart PRK, Bandeira ML, Tsubota D, Oiwa NN, Costa MF, Ventura DF. A computer-controlled color vision test for children based on the Cambridge Colour Test. Vis. Neurosci. 2008;25:445–50.

11. Paramei GV. Color discrimination across four life decades assessed by the Cambridge Colour Test. J. Opt. Soc. Am. A Opt. Image Sci. Vis. 2012;29:A290-297.

12. Paramei GV, Oakley B. Variation of color discrimination across the life span. JOSA A. 2014;31:A375–84.

13. Pelli DG, Bex P. Measuring contrast sensitivity. Vision Res. 2013;90:10–4.

14. Hogg RE, Chakravarthy U. Visual function and dysfunction in early and late age-related maculopathy. Prog. Retin. Eye Res. 2006;25:249–76.

15. DeValois KK, Webster MA. Color vision. Scholarpedia. 2011;6:3073.
Dear Goro Maehara,

We respectfully thank you for the reading and responding to our manuscript.

If I may contest your decision of this manuscript, we respectfully do not agree that it can not be accepted as an acceptable scientific standard. We believe that the data contribute in terms of scientific validity, and because we know that there are few studies on color vision in chronic smoking (and abstinence).

We will try to answer your questions below:

"Although their methods were scientifically sound, the thresholds for chronic smokers were not high enough to conclude that smoking impairs their color discrimination abilities."

Although we did not observe large differences between the thresholds of the control group and the group of smokers, we agree with Lakens (2013) and Field (2013) noting that the statistically significant differences are consonant with the related effect sizes which fluctuated between mid-to-high values (r values between .50 and .61; chronic smokers x controls). Moreover, when comparing the group of smokers with deprived smokers, we observed that these differences were not so large (r values reaching .50). We do not know if the smoking habit, cigarette compounds or smoking per se, are responsible for the decrease in color discrimination.

But there was a loss of color discrimination, suggesting the idea that visual color processing may be diffusely impaired in smokers (Besson et al., 2007; Vallejo, Buisson, Bertrand, & Green, 2005; Zhang, Dong, Doyon, & Dani, 2012). We base this hypothesis on the fact that the many cigarette compounds, including organic solvents in the cigarette smoke, impairs color processing per se.

Major Concern

'The threshold medians for chronic smokers were lower than those values, except for the deutan threshold median for deprived smokers. Although there were statistically significant difference between chronic smokers and non-smokers, the thresholds for non-smokers were very low (about 40, 50, and 80 in 10−4 u’ v’ units for protan, deutan, and tritan, respectively). In addition, the differences in thresholds (about 60) make little change in color appearance. Taken together, it seems difficult to conclude that smoking impairs color discrimination abilities.'

Many thanks for the review.

Based on our expertise in the use of Cambridge Colour Test: the minor the threshold, better discrimination. If a group (in this case, smokers group) has a higher threshold, this means that they needed more chromatic contrast to detect the stimuli. Thus, higher thresholds means lower discriminiation along confusion axes (Hasrod & Rubin, 2015).

After the publication of Mollon and Reffin's about the CCT (2000), several studies using Trivector have been published. Including preliminary norms for the use of CCT (Ventura et al., 2003), which was considered by the creators of the CCT on the software website (http://www.crsltd.com/tools-for-vision-science/measuring-visual-functions/cambridge-colour-test/)

We re-checked our Trivector data and compared to several studies and we observed that we're with similar values for control groups. If another group (such smokers or deprived smokers) had higher thresholds, it means that they differ from the standard values and are likely to have color vision impairments.

As shown in the other studies, values for control subjects have fluctuated precisely in the values that we obtained in our data (Costa et al., 2007; Goulart et al., 2008; Paramei, 2012, 2014; Ventura et al., 2002).

Thus, the raising of the threshold of smokers is possibly connected with smoking conditions, since we've matched all possibly intervenient variables.

Taken together, we can not ignore that, although not as large, the differences were significant in this sample. Based on previous studies, even though there are small differences, they need to be punctuated, since we agree that this is an important area that requires further research.

Minor concern

1. Equation 1; I am not sure why Weber contrast (equation 1) needs to be explained in the Methods section. The authors should state clearly how they used the equation in their experiment.

Ops! Many thanks! Since CCT already uses this default setting, we strongly agreed with your review. These changes will be in the second version of the manuscript (we will remove it).

2. Results; The authors just listed the statistical results in the Results section. I suggest describing the results in the more detailed way (ex. thresholds were higher for smokers than non-smokers, U = 132, P = 0.002, r = -.61).

Many thanks again. We believe that the way you suggested will facilitate the reader's understanding and will enhance the scientific level of our writing. We fixed it. They will be more descriptive in the next version

3. 3rd paragraph in the Discussion section; The authors stated that “smokers were more sensitive to protanopic and deutanopic confusion axes.” This sentence is confusing. Which does this sentence mean, “more sensitive than non-smokers” or “more sensitive than to tritanopic axes”?

We appreciate the suggestion and agree that the use of two forms of explanation may actually confuse the reader. We will correct this.

However, when we mention that the smoking group was more sensitive to the protanopic or deutanopic axes, we simply mean that they made more errors than the control group, for example. That is, they needed more chromatic contrast (they were more sensitive) than the comparison group. The confusion axes refer to the red (protanopic), green (deutanopic) and blue (tritanopic) axes. Thus, if any group was more sensitive to the red confusion axis, forr example, it means that they possibly had impairments in the processing of this wavelength.

In this way, based on the apointments above, the 'not approved' status is honestly inconsistent with the content of the work. We ask you to reconsider your decision and we are grateful for the comment, reading, and review of the manuscript.

References

1. Lakens D. Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Front. Psychol. [Internet]. 2013 [cited 2017 Mar 10];4. Available from: http://journal.frontiersin.org/article/10.3389/fpsyg.2013.00863/abstract

2. Field A. Discovering Statistics Using IBM SPSS Statistics. SAGE; 2013.

3. Besson M, Granon S, Mameli-Engvall M, Cloëz-Tayarani I, Maubourguet N, Cormier A, et al. Long-term effects of chronic nicotine exposure on brain nicotinic receptors. Proc. Natl. Acad. Sci. 2007;104:8155–60.

4. Vallejo YF, Buisson B, Bertrand D, Green WN. Chronic Nicotine Exposure Upregulates Nicotinic Receptors by a Novel Mechanism. J. Neurosci. Off. J. Soc. Neurosci. 2005;25:5563–72.

5. Zhang L, Dong Y, Doyon WM, Dani JA. Withdrawal from Chronic Nicotine Exposure Alters Dopamine Signaling Dynamics in the Nucleus Accumbens. Biol. Psychiatry. 2012;71:184–91.

6. Mollon JD, Regan BC. Cambridge Colour Test Handbook [Internet]. 2000. Available from: https://sites.oxy.edu/clint/physio/article/CAMBRIDGECOLOURTESTHandbook.pdf

7. Ventura DF, Silveira LC de L, Rodrigues A, Costa MF. Preliminary Norms for the Cambridge Colour Test. 2003;331–9.

8. Costa MF, Oliveira AGF, Feitosa-Santana C, Zatz M, Ventura DF. Red-Green Color Vision Impairment in Duchenne Muscular Dystrophy. Am. J. Hum. Genet. 2007;80:1064–75.

9. Feitosa-Santana C, Barboni MTS, Oiwa NN, Paramei GV, Simões ALAC, Da Costa MF, et al. Irreversible color vision losses in patients with chronic mercury vapor intoxication. Vis. Neurosci. 2008;25:487–91.

10. Goulart PRK, Bandeira ML, Tsubota D, Oiwa NN, Costa MF, Ventura DF. A computer-controlled color vision test for children based on the Cambridge Colour Test. Vis. Neurosci. 2008;25:445–50.

11. Paramei GV. Color discrimination across four life decades assessed by the Cambridge Colour Test. J. Opt. Soc. Am. A Opt. Image Sci. Vis. 2012;29:A290-297.

12. Paramei GV, Oakley B. Variation of color discrimination across the life span. JOSA A. 2014;31:A375–84.

13. Pelli DG, Bex P. Measuring contrast sensitivity. Vision Res. 2013;90:10–4.

14. Hogg RE, Chakravarthy U. Visual function and dysfunction in early and late age-related maculopathy. Prog. Retin. Eye Res. 2006;25:249–76.

15. DeValois KK, Webster MA. Color vision. Scholarpedia. 2011;6:3073.
Competing Interests: No competing interests were disclosed. Close
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Reviewer Response 20 Mar 2017

Goro Maehara, Department of Human Sciences, Kanagawa University, Yokohama, Japan

20 Mar 2017

Reviewer Response

Dear Thiago,

I am happy to review the revised manuscript.
Please make it clear that the thresholds of normal observers were comparable with those reported by previous studies using ... Continue reading Dear Thiago,

I am happy to review the revised manuscript.
Please make it clear that the thresholds of normal observers were comparable with those reported by previous studies using the Cambridge color test.

According to Thornton, Edwards, Mitchell, Harrison, Buchan & Kelly (2005), there is a strong association between current smoking and age-related macular degeneration. This line of studies could strengthen your paper.

Regards,

Goro

Dear Thiago,

I am happy to review the revised manuscript.
Please make it clear that the thresholds of normal observers were comparable with those reported by previous studies using the Cambridge color test.

According to Thornton, Edwards, Mitchell, Harrison, Buchan & Kelly (2005), there is a strong association between current smoking and age-related macular degeneration. This line of studies could strengthen your paper.

Regards,

Goro
Competing Interests: No competing interests were disclosed. Close
Report a concern
Author Response 30 Mar 2017

Thiago P Fernandes, Federal University of Paraiba, Brazil

30 Mar 2017

Author Response

Dear Goro,
Many thanks for the quick answer.

Based on your suggestions, substantial changes were made.

We inserted a subsection in the methods where we explained the cutoff ... Continue reading Dear Goro,
Many thanks for the quick answer.

Based on your suggestions, substantial changes were made.

We inserted a subsection in the methods where we explained the cutoff points (where the results would be normal and where the discrimination losses would be).

In addition, we better describe the results section, making it clear to the reader that the higher the threshold, the lower the color discrimination. Also, based on your last suggestion, we added a few paragraphs about the relationship between the harmful cigarette compounds and the damage they cause to the retina, and consequently, visual processing.

I hope we have answered the suggestions. Again, we ask you to reconsider your decision about the status of our work.

Best regards,
Dear Goro,
Many thanks for the quick answer.

Based on your suggestions, substantial changes were made.

We inserted a subsection in the methods where we explained the cutoff points (where the results would be normal and where the discrimination losses would be).

In addition, we better describe the results section, making it clear to the reader that the higher the threshold, the lower the color discrimination. Also, based on your last suggestion, we added a few paragraphs about the relationship between the harmful cigarette compounds and the damage they cause to the retina, and consequently, visual processing.

I hope we have answered the suggestions. Again, we ask you to reconsider your decision about the status of our work.

Best regards,
Competing Interests: None. Close
Report a concern
Respond or Comment

COMMENTS ON THIS REPORT

Author Response 13 Mar 2017

Thiago P Fernandes, Federal University of Paraiba, Brazil

13 Mar 2017

Author Response
Dear Goro Maehara,

We respectfully thank you for the reading and responding to our manuscript.

If I may contest your decision of this manuscript, we respectfully do not ... Continue reading
Dear Goro Maehara,

We respectfully thank you for the reading and responding to our manuscript.

If I may contest your decision of this manuscript, we respectfully do not agree that it can not be accepted as an acceptable scientific standard. We believe that the data contribute in terms of scientific validity, and because we know that there are few studies on color vision in chronic smoking (and abstinence).

We will try to answer your questions below:

"Although their methods were scientifically sound, the thresholds for chronic smokers were not high enough to conclude that smoking impairs their color discrimination abilities."

Although we did not observe large differences between the thresholds of the control group and the group of smokers, we agree with Lakens (2013) and Field (2013) noting that the statistically significant differences are consonant with the related effect sizes which fluctuated between mid-to-high values (r values between .50 and .61; chronic smokers x controls). Moreover, when comparing the group of smokers with deprived smokers, we observed that these differences were not so large (r values reaching .50). We do not know if the smoking habit, cigarette compounds or smoking per se, are responsible for the decrease in color discrimination.

But there was a loss of color discrimination, suggesting the idea that visual color processing may be diffusely impaired in smokers (Besson et al., 2007; Vallejo, Buisson, Bertrand, & Green, 2005; Zhang, Dong, Doyon, & Dani, 2012). We base this hypothesis on the fact that the many cigarette compounds, including organic solvents in the cigarette smoke, impairs color processing per se.

Major Concern

'The threshold medians for chronic smokers were lower than those values, except for the deutan threshold median for deprived smokers. Although there were statistically significant difference between chronic smokers and non-smokers, the thresholds for non-smokers were very low (about 40, 50, and 80 in 10−4 u’ v’ units for protan, deutan, and tritan, respectively). In addition, the differences in thresholds (about 60) make little change in color appearance. Taken together, it seems difficult to conclude that smoking impairs color discrimination abilities.'

Many thanks for the review.

Based on our expertise in the use of Cambridge Colour Test: the minor the threshold, better discrimination. If a group (in this case, smokers group) has a higher threshold, this means that they needed more chromatic contrast to detect the stimuli. Thus, higher thresholds means lower discriminiation along confusion axes (Hasrod & Rubin, 2015).

After the publication of Mollon and Reffin's about the CCT (2000), several studies using Trivector have been published. Including preliminary norms for the use of CCT (Ventura et al., 2003), which was considered by the creators of the CCT on the software website (http://www.crsltd.com/tools-for-vision-science/measuring-visual-functions/cambridge-colour-test/)

We re-checked our Trivector data and compared to several studies and we observed that we're with similar values for control groups. If another group (such smokers or deprived smokers) had higher thresholds, it means that they differ from the standard values and are likely to have color vision impairments.

As shown in the other studies, values for control subjects have fluctuated precisely in the values that we obtained in our data (Costa et al., 2007; Goulart et al., 2008; Paramei, 2012, 2014; Ventura et al., 2002).

Thus, the raising of the threshold of smokers is possibly connected with smoking conditions, since we've matched all possibly intervenient variables.

Taken together, we can not ignore that, although not as large, the differences were significant in this sample. Based on previous studies, even though there are small differences, they need to be punctuated, since we agree that this is an important area that requires further research.

Minor concern

1. Equation 1; I am not sure why Weber contrast (equation 1) needs to be explained in the Methods section. The authors should state clearly how they used the equation in their experiment.

Ops! Many thanks! Since CCT already uses this default setting, we strongly agreed with your review. These changes will be in the second version of the manuscript (we will remove it).

2. Results; The authors just listed the statistical results in the Results section. I suggest describing the results in the more detailed way (ex. thresholds were higher for smokers than non-smokers, U = 132, P = 0.002, r = -.61).

Many thanks again. We believe that the way you suggested will facilitate the reader's understanding and will enhance the scientific level of our writing. We fixed it. They will be more descriptive in the next version

3. 3rd paragraph in the Discussion section; The authors stated that “smokers were more sensitive to protanopic and deutanopic confusion axes.” This sentence is confusing. Which does this sentence mean, “more sensitive than non-smokers” or “more sensitive than to tritanopic axes”?

We appreciate the suggestion and agree that the use of two forms of explanation may actually confuse the reader. We will correct this.

However, when we mention that the smoking group was more sensitive to the protanopic or deutanopic axes, we simply mean that they made more errors than the control group, for example. That is, they needed more chromatic contrast (they were more sensitive) than the comparison group. The confusion axes refer to the red (protanopic), green (deutanopic) and blue (tritanopic) axes. Thus, if any group was more sensitive to the red confusion axis, forr example, it means that they possibly had impairments in the processing of this wavelength.

In this way, based on the apointments above, the 'not approved' status is honestly inconsistent with the content of the work. We ask you to reconsider your decision and we are grateful for the comment, reading, and review of the manuscript.

References

1. Lakens D. Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Front. Psychol. [Internet]. 2013 [cited 2017 Mar 10];4. Available from: http://journal.frontiersin.org/article/10.3389/fpsyg.2013.00863/abstract

2. Field A. Discovering Statistics Using IBM SPSS Statistics. SAGE; 2013.

3. Besson M, Granon S, Mameli-Engvall M, Cloëz-Tayarani I, Maubourguet N, Cormier A, et al. Long-term effects of chronic nicotine exposure on brain nicotinic receptors. Proc. Natl. Acad. Sci. 2007;104:8155–60.

4. Vallejo YF, Buisson B, Bertrand D, Green WN. Chronic Nicotine Exposure Upregulates Nicotinic Receptors by a Novel Mechanism. J. Neurosci. Off. J. Soc. Neurosci. 2005;25:5563–72.

5. Zhang L, Dong Y, Doyon WM, Dani JA. Withdrawal from Chronic Nicotine Exposure Alters Dopamine Signaling Dynamics in the Nucleus Accumbens. Biol. Psychiatry. 2012;71:184–91.

6. Mollon JD, Regan BC. Cambridge Colour Test Handbook [Internet]. 2000. Available from: https://sites.oxy.edu/clint/physio/article/CAMBRIDGECOLOURTESTHandbook.pdf

7. Ventura DF, Silveira LC de L, Rodrigues A, Costa MF. Preliminary Norms for the Cambridge Colour Test. 2003;331–9.

8. Costa MF, Oliveira AGF, Feitosa-Santana C, Zatz M, Ventura DF. Red-Green Color Vision Impairment in Duchenne Muscular Dystrophy. Am. J. Hum. Genet. 2007;80:1064–75.

9. Feitosa-Santana C, Barboni MTS, Oiwa NN, Paramei GV, Simões ALAC, Da Costa MF, et al. Irreversible color vision losses in patients with chronic mercury vapor intoxication. Vis. Neurosci. 2008;25:487–91.

10. Goulart PRK, Bandeira ML, Tsubota D, Oiwa NN, Costa MF, Ventura DF. A computer-controlled color vision test for children based on the Cambridge Colour Test. Vis. Neurosci. 2008;25:445–50.

11. Paramei GV. Color discrimination across four life decades assessed by the Cambridge Colour Test. J. Opt. Soc. Am. A Opt. Image Sci. Vis. 2012;29:A290-297.

12. Paramei GV, Oakley B. Variation of color discrimination across the life span. JOSA A. 2014;31:A375–84.

13. Pelli DG, Bex P. Measuring contrast sensitivity. Vision Res. 2013;90:10–4.

14. Hogg RE, Chakravarthy U. Visual function and dysfunction in early and late age-related maculopathy. Prog. Retin. Eye Res. 2006;25:249–76.

15. DeValois KK, Webster MA. Color vision. Scholarpedia. 2011;6:3073.
Dear Goro Maehara,

We respectfully thank you for the reading and responding to our manuscript.

If I may contest your decision of this manuscript, we respectfully do not agree that it can not be accepted as an acceptable scientific standard. We believe that the data contribute in terms of scientific validity, and because we know that there are few studies on color vision in chronic smoking (and abstinence).

We will try to answer your questions below:

"Although their methods were scientifically sound, the thresholds for chronic smokers were not high enough to conclude that smoking impairs their color discrimination abilities."

Although we did not observe large differences between the thresholds of the control group and the group of smokers, we agree with Lakens (2013) and Field (2013) noting that the statistically significant differences are consonant with the related effect sizes which fluctuated between mid-to-high values (r values between .50 and .61; chronic smokers x controls). Moreover, when comparing the group of smokers with deprived smokers, we observed that these differences were not so large (r values reaching .50). We do not know if the smoking habit, cigarette compounds or smoking per se, are responsible for the decrease in color discrimination.

But there was a loss of color discrimination, suggesting the idea that visual color processing may be diffusely impaired in smokers (Besson et al., 2007; Vallejo, Buisson, Bertrand, & Green, 2005; Zhang, Dong, Doyon, & Dani, 2012). We base this hypothesis on the fact that the many cigarette compounds, including organic solvents in the cigarette smoke, impairs color processing per se.

Major Concern

'The threshold medians for chronic smokers were lower than those values, except for the deutan threshold median for deprived smokers. Although there were statistically significant difference between chronic smokers and non-smokers, the thresholds for non-smokers were very low (about 40, 50, and 80 in 10−4 u’ v’ units for protan, deutan, and tritan, respectively). In addition, the differences in thresholds (about 60) make little change in color appearance. Taken together, it seems difficult to conclude that smoking impairs color discrimination abilities.'

Many thanks for the review.

Based on our expertise in the use of Cambridge Colour Test: the minor the threshold, better discrimination. If a group (in this case, smokers group) has a higher threshold, this means that they needed more chromatic contrast to detect the stimuli. Thus, higher thresholds means lower discriminiation along confusion axes (Hasrod & Rubin, 2015).

After the publication of Mollon and Reffin's about the CCT (2000), several studies using Trivector have been published. Including preliminary norms for the use of CCT (Ventura et al., 2003), which was considered by the creators of the CCT on the software website (http://www.crsltd.com/tools-for-vision-science/measuring-visual-functions/cambridge-colour-test/)

We re-checked our Trivector data and compared to several studies and we observed that we're with similar values for control groups. If another group (such smokers or deprived smokers) had higher thresholds, it means that they differ from the standard values and are likely to have color vision impairments.

As shown in the other studies, values for control subjects have fluctuated precisely in the values that we obtained in our data (Costa et al., 2007; Goulart et al., 2008; Paramei, 2012, 2014; Ventura et al., 2002).

Thus, the raising of the threshold of smokers is possibly connected with smoking conditions, since we've matched all possibly intervenient variables.

Taken together, we can not ignore that, although not as large, the differences were significant in this sample. Based on previous studies, even though there are small differences, they need to be punctuated, since we agree that this is an important area that requires further research.

Minor concern

1. Equation 1; I am not sure why Weber contrast (equation 1) needs to be explained in the Methods section. The authors should state clearly how they used the equation in their experiment.

Ops! Many thanks! Since CCT already uses this default setting, we strongly agreed with your review. These changes will be in the second version of the manuscript (we will remove it).

2. Results; The authors just listed the statistical results in the Results section. I suggest describing the results in the more detailed way (ex. thresholds were higher for smokers than non-smokers, U = 132, P = 0.002, r = -.61).

Many thanks again. We believe that the way you suggested will facilitate the reader's understanding and will enhance the scientific level of our writing. We fixed it. They will be more descriptive in the next version

3. 3rd paragraph in the Discussion section; The authors stated that “smokers were more sensitive to protanopic and deutanopic confusion axes.” This sentence is confusing. Which does this sentence mean, “more sensitive than non-smokers” or “more sensitive than to tritanopic axes”?

We appreciate the suggestion and agree that the use of two forms of explanation may actually confuse the reader. We will correct this.

However, when we mention that the smoking group was more sensitive to the protanopic or deutanopic axes, we simply mean that they made more errors than the control group, for example. That is, they needed more chromatic contrast (they were more sensitive) than the comparison group. The confusion axes refer to the red (protanopic), green (deutanopic) and blue (tritanopic) axes. Thus, if any group was more sensitive to the red confusion axis, forr example, it means that they possibly had impairments in the processing of this wavelength.

In this way, based on the apointments above, the 'not approved' status is honestly inconsistent with the content of the work. We ask you to reconsider your decision and we are grateful for the comment, reading, and review of the manuscript.

References

1. Lakens D. Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Front. Psychol. [Internet]. 2013 [cited 2017 Mar 10];4. Available from: http://journal.frontiersin.org/article/10.3389/fpsyg.2013.00863/abstract

2. Field A. Discovering Statistics Using IBM SPSS Statistics. SAGE; 2013.

3. Besson M, Granon S, Mameli-Engvall M, Cloëz-Tayarani I, Maubourguet N, Cormier A, et al. Long-term effects of chronic nicotine exposure on brain nicotinic receptors. Proc. Natl. Acad. Sci. 2007;104:8155–60.

4. Vallejo YF, Buisson B, Bertrand D, Green WN. Chronic Nicotine Exposure Upregulates Nicotinic Receptors by a Novel Mechanism. J. Neurosci. Off. J. Soc. Neurosci. 2005;25:5563–72.

5. Zhang L, Dong Y, Doyon WM, Dani JA. Withdrawal from Chronic Nicotine Exposure Alters Dopamine Signaling Dynamics in the Nucleus Accumbens. Biol. Psychiatry. 2012;71:184–91.

6. Mollon JD, Regan BC. Cambridge Colour Test Handbook [Internet]. 2000. Available from: https://sites.oxy.edu/clint/physio/article/CAMBRIDGECOLOURTESTHandbook.pdf

7. Ventura DF, Silveira LC de L, Rodrigues A, Costa MF. Preliminary Norms for the Cambridge Colour Test. 2003;331–9.

8. Costa MF, Oliveira AGF, Feitosa-Santana C, Zatz M, Ventura DF. Red-Green Color Vision Impairment in Duchenne Muscular Dystrophy. Am. J. Hum. Genet. 2007;80:1064–75.

9. Feitosa-Santana C, Barboni MTS, Oiwa NN, Paramei GV, Simões ALAC, Da Costa MF, et al. Irreversible color vision losses in patients with chronic mercury vapor intoxication. Vis. Neurosci. 2008;25:487–91.

10. Goulart PRK, Bandeira ML, Tsubota D, Oiwa NN, Costa MF, Ventura DF. A computer-controlled color vision test for children based on the Cambridge Colour Test. Vis. Neurosci. 2008;25:445–50.

11. Paramei GV. Color discrimination across four life decades assessed by the Cambridge Colour Test. J. Opt. Soc. Am. A Opt. Image Sci. Vis. 2012;29:A290-297.

12. Paramei GV, Oakley B. Variation of color discrimination across the life span. JOSA A. 2014;31:A375–84.

13. Pelli DG, Bex P. Measuring contrast sensitivity. Vision Res. 2013;90:10–4.

14. Hogg RE, Chakravarthy U. Visual function and dysfunction in early and late age-related maculopathy. Prog. Retin. Eye Res. 2006;25:249–76.

15. DeValois KK, Webster MA. Color vision. Scholarpedia. 2011;6:3073.
Competing Interests: No competing interests were disclosed. Close
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Reviewer Response 20 Mar 2017

Goro Maehara, Department of Human Sciences, Kanagawa University, Yokohama, Japan

20 Mar 2017

Reviewer Response

Dear Thiago,

I am happy to review the revised manuscript.
Please make it clear that the thresholds of normal observers were comparable with those reported by previous studies using ... Continue reading Dear Thiago,

I am happy to review the revised manuscript.
Please make it clear that the thresholds of normal observers were comparable with those reported by previous studies using the Cambridge color test.

According to Thornton, Edwards, Mitchell, Harrison, Buchan & Kelly (2005), there is a strong association between current smoking and age-related macular degeneration. This line of studies could strengthen your paper.

Regards,

Goro

Dear Thiago,

I am happy to review the revised manuscript.
Please make it clear that the thresholds of normal observers were comparable with those reported by previous studies using the Cambridge color test.

According to Thornton, Edwards, Mitchell, Harrison, Buchan & Kelly (2005), there is a strong association between current smoking and age-related macular degeneration. This line of studies could strengthen your paper.

Regards,

Goro
Competing Interests: No competing interests were disclosed. Close
Report a concern
Author Response 30 Mar 2017

Thiago P Fernandes, Federal University of Paraiba, Brazil

30 Mar 2017

Author Response

Dear Goro,
Many thanks for the quick answer.

Based on your suggestions, substantial changes were made.

We inserted a subsection in the methods where we explained the cutoff ... Continue reading Dear Goro,
Many thanks for the quick answer.

Based on your suggestions, substantial changes were made.

We inserted a subsection in the methods where we explained the cutoff points (where the results would be normal and where the discrimination losses would be).

In addition, we better describe the results section, making it clear to the reader that the higher the threshold, the lower the color discrimination. Also, based on your last suggestion, we added a few paragraphs about the relationship between the harmful cigarette compounds and the damage they cause to the retina, and consequently, visual processing.

I hope we have answered the suggestions. Again, we ask you to reconsider your decision about the status of our work.

Best regards,
Dear Goro,
Many thanks for the quick answer.

Based on your suggestions, substantial changes were made.

We inserted a subsection in the methods where we explained the cutoff points (where the results would be normal and where the discrimination losses would be).

In addition, we better describe the results section, making it clear to the reader that the higher the threshold, the lower the color discrimination. Also, based on your last suggestion, we added a few paragraphs about the relationship between the harmful cigarette compounds and the damage they cause to the retina, and consequently, visual processing.

I hope we have answered the suggestions. Again, we ask you to reconsider your decision about the status of our work.

Best regards,
Competing Interests: None. Close
Report a concern

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Version 3

VERSION 3 PUBLISHED 27 Jan 2017

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Goro Maehara, Kanagawa University, Yokohama, Japan
Marine Raquel Diniz da Rosa, Federal University of Paraíba, João Pessoa, Brazil

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Goro Maehara, Department of Human Sciences, Kanagawa University, Yokohama, Japan

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The authors have addressed all my concerns. Thanks.

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Marine Raquel Diniz da Rosa, Neuroscience and Behavior Graduate Program , Federal University of Paraíba, João Pessoa, Brazil

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I am affiliated with The Federal University of Paraiba, where all 3 of the authors, Thiago Monteiro de Paiva Fernandes, Natalia Leandro Almeida and Natanael Antonio dos Santos are also affiliated.

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Goro Maehara, Department of Human Sciences, Kanagawa University, Yokohama, Japan

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Author Response

05 Apr 2017

Thiago P Fernandes, Federal University of Paraiba, Brazil

Adding the cutoff values was just one way to meet the review specifications. If you take a brief look at all papers using Trivector as test, there are no specifications for cut-off values. However, the paper of Paramei et al. (2012) compared the color discrimination across four life decades, and used data obtained in Brazil. If it is possible, at least briefly, to read this and other papers using Trivector, you will notice a little of what I am talking about.

In addition, when reading other articles about Trivector, you will observe a simple pattern: generally, both the control and the observed (experimental) conditions may have values below 100 for the protan or deutan (eg) confusion axes. The values obtained by Mollon & Reffin unfortunately do not match experimental practice. The reasons are more varied: type of computer, type of processor used at the time, condition of luminance or characteristic of the study. The following Mollon & Reffin studies used the commercial version called Cambridge Color Test, where we tried to standardize and avoid differences between studies. This standardization could be observed when Paramei et al. (2012) observed that there are not many differences in results for controls both in Brazil and around the world.

No matter how small the visual processing loss is, the differences that will be classified as impairments will be the statistically significant differences. If it was not clear, I will summarize. Conjecturing: If in one study, for the protan axis, the control group had 50 10^-4 u' v' units and the experimental one had 80 10^-4 u' v' units, having a value of p <.001, this is considered color impairment. Thus, the experimental group would present damage in color processing. This is what indicates most, if not 90% of all articles that used the Trivector as a measure.

I hope it has helped in understanding how the Trivector test works. Even so, i will try to answer your questions below:

1. Outcome Cutoffs

There are some difficulties to understand the Outcome Cutoffs section. The authors should state clearly how they determined and calculated the cutoff points.

This was explained. The mean or median (+ SD or + IQR) for the control group of all the studies that used the Trivector were summed and divided by the number of studies (a simple grand mean / median).

I also suggest explaining what the values in parentheses represent and what IQR means (interquartile range).

"Based on previous studies, cutoff points (median + IQR/2) for the trivector test were established to designate color vision impairment." As stated, median + IQR/2 was established by Paramei et al. (2012). This was also explained. In my opinion, there is no need to explain why using IQR/2 or IQR, since they are simply representing the standard deviation in a non-parametric data

Although the authors mentioned ‘(mean + median + IQR + upper and lower limits)’, the plus signs in this phrase seem a bit odd.

I understand your point of view. However, the reason for inserting this comment into the text was to explain to the reader that there are normative values for the Trivector. These values would be means, medians, tolerance values, etc. They can be observed in the reference article quoted in the cutoffs outcome section.

2. The Results Section

Please clearly compare the thresholds with the cutoffs values. Not only the median thresholds for smokers, but those for normal observers also exceeds the cutoff values in the deutan and tritan tests, don’t they? I think that the cutoff values might be too strict (low).

As explained, the use of cutoff values was only one way to meet the requests of the reviewers. However, in no study using trivector cutoff values are imposed. This is due to the fact that to consider impairment in color vision it is only necessary to have statistically significant differences and to have medium or high effect size.

Nevertheless, the medians of our results for the control group are "beating" with the cutoff values + IQR/2.

So, the purpose of this comment was to try to show how the trivector works. Just read one or two papers that made use of the test and you will note that the differences need not exceed the set values of 100, 100 and 150 10^-4 u' v 'units to prove impairments at color vision. Even differences observed in values smaller than 100 10^-4 u'v 'units are significant differences, since this is a robust and reliable test.

According to Trivector's studies, there is no large or small differences, there is statistically significant differences, with large or small effect sizes. And this was what we observed in our study.

Thank you for the review.
Kind Regards,

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Competing Interests

None

Reviewer Response

06 Jun 2017

Goro Maehara, Department of Human Sciences, Kanagawa University, Yokohama, Japan

Dear Thiago,

The authors have solved the major concern in my 1st response through the revision process. Mollon & Regan (2000) set the cutoff values relatively high probably because the test was originally designed for detecting color blindness.
Here we need to tackle the issues about the present cutoff values.

I agree with another reviewer in that the standard of normality is useful for making a comparison between the present and previous studies. Any analysis in a paper must be logical even if authors think a specific analysis is not very important. In the present study, not only the thresholds for the smoker, but also those for normal controls exceeded the cutoff values for the tritan test (and deutan test, too?). The authors need to somehow solve this logical problem.

Thank you for the explanations on the cutoff values. That is, the cutoff values were defined as the average of normal observers’ (median threshold + IQR/2) reported by the previous studies (or only by Paramei?). It will be helpful for readers to rewrite the Outcome Cutoff section as the authors commented above.

The cutoff values of (median threshold + IQR/2) mean that 25 % of the population is classified as abnormal. It seems reasonable for me to increase the cutoff values because 25 % of the population is too much. This might be a possible solution.

Another possible solution could be discussing why the thresholds for normal observers exceeded the cutoff values in the Discussion section. The authors could also emphasize the importance of statistical differences there.

If the authors have any idea for workable solutions, please feel free to let me know.

Minor concerns,

My previous comment on IQR was misleading. I would like to suggest inserting ‘( interquartile range)’ just after IQR when the authors first use the abbreviation.
If the authors used data reported by researchers other than Paramei (2012) for the cutoff value calculation, I suggest including the citations of the studies.

Best wishes,

Goro

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Competing Interests

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Reviewer Report

20 Views

17 Mar 2017 | for Version 1

Marine Raquel Diniz da Rosa, Neuroscience and Behavior Graduate Program , Federal University of Paraíba, João Pessoa, Brazil

20 Views Cite this report Responses(1)

Approved With Reservations

References

Competing Interests

I am affiliated with The Federal University of Paraiba, where all 3 of the authors, Thiago Monteiro de Paiva Fernandes, Natalia Leandro Almeida and Natanael Antonio dos Santos are also affiliated.

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Responses (1)

Author Response

30 Mar 2017

Thiago P Fernandes, Federal University of Paraiba, Brazil

Dear Marine,
First of all, many thanks for the reading and suggestions for our manuscript.

We will try to answer your questions below:

However, I believe that in order to clarify the cut-off point of color discrimination, authors should write in Methods the standard of normality used to rate low or high color discrimination.

We appreciate the suggestion. These changes were made. We stand by calculating the average of the control group of all studies using Trivector in Brazil and using the normative data for age groups used by Paramei et al.¹

In addition, in the description of the results, for better understanding, the authors should explain better the results (which are below the expected) and then the significance of them.

We appreciate the suggestion. Although the description of Trivector's results is quite directive (for details, see ^2-5), we agreed that the way the results were presented was below expectations.These changes were made.

The results suggest a possible, even small, important change to the color discrimination of smokers which deserves attention and should be better studied.

In agreement. Based on this suggestion, we added a few paragraphs on the importance of the present study, see Introduction and Discussion.

References:

Paramei GV. Color discrimination across four life decades assessed by the Cambridge Colour Test. J Opt Soc Am A Opt Image Sci Vis. 2012;29(2):A290-297.
Lacerda EM da CB, Ventura DF, Silveira LC de L: Visual assessment by psychophysical methods of people subjected to occupational exposure to organic solvents. Psicol USP. 2011;22(1):117–145. 10.1590/S0103-65642011005000011
Oliveira AR: Avaliações psicofísicas cromática e acromática de homens e mulheres expostos a solventes orgânicos.2015. Reference Source
Goulart PRK, Bandeira ML, Tsubota D, Oiwa NN, Costa MF, Ventura DF. A computer-controlled color vision test for children based on the Cambridge Colour Test. Vis Neurosci. 2008;25(3):445-450. doi:10.1017/S0952523808080589.
Costa MF, Oliveira AGF, Feitosa-Santana C, Zatz M, Ventura DF. Red-Green Color Vision Impairment in Duchenne Muscular Dystrophy. Am J Hum Genet. 2007;80(6):1064-1075

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Competing Interests

None.

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Reviewer Report

29 Views

10 Mar 2017 | for Version 1

Goro Maehara, Department of Human Sciences, Kanagawa University, Yokohama, Japan

29 Views Cite this report Responses(3)

Not Approved

References

1. Mollon JD, Regan BC: Cambridge Colour Test Handbook (version 1.1). Cambridge Research Systems Ltd.2000. Reference Source

Competing Interests

No competing interests were disclosed.

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Responses (3)

Author Response

13 Mar 2017

Thiago P Fernandes, Federal University of Paraiba, Brazil

Dear Goro Maehara,

We respectfully thank you for the reading and responding to our manuscript.

If I may contest your decision of this manuscript, we respectfully do not agree that it can not be accepted as an acceptable scientific standard. We believe that the data contribute in terms of scientific validity, and because we know that there are few studies on color vision in chronic smoking (and abstinence).

We will try to answer your questions below:

"Although their methods were scientifically sound, the thresholds for chronic smokers were not high enough to conclude that smoking impairs their color discrimination abilities."

Although we did not observe large differences between the thresholds of the control group and the group of smokers, we agree with Lakens (2013) and Field (2013) noting that the statistically significant differences are consonant with the related effect sizes which fluctuated between mid-to-high values (r values between .50 and .61; chronic smokers x controls). Moreover, when comparing the group of smokers with deprived smokers, we observed that these differences were not so large (r values reaching .50). We do not know if the smoking habit, cigarette compounds or smoking per se, are responsible for the decrease in color discrimination.

But there was a loss of color discrimination, suggesting the idea that visual color processing may be diffusely impaired in smokers (Besson et al., 2007; Vallejo, Buisson, Bertrand, & Green, 2005; Zhang, Dong, Doyon, & Dani, 2012). We base this hypothesis on the fact that the many cigarette compounds, including organic solvents in the cigarette smoke, impairs color processing per se.

Major Concern

'The threshold medians for chronic smokers were lower than those values, except for the deutan threshold median for deprived smokers. Although there were statistically significant difference between chronic smokers and non-smokers, the thresholds for non-smokers were very low (about 40, 50, and 80 in 10−4 u’ v’ units for protan, deutan, and tritan, respectively). In addition, the differences in thresholds (about 60) make little change in color appearance. Taken together, it seems difficult to conclude that smoking impairs color discrimination abilities.'

Many thanks for the review.

Based on our expertise in the use of Cambridge Colour Test: the minor the threshold, better discrimination. If a group (in this case, smokers group) has a higher threshold, this means that they needed more chromatic contrast to detect the stimuli. Thus, higher thresholds means lower discriminiation along confusion axes (Hasrod & Rubin, 2015).

After the publication of Mollon and Reffin's about the CCT (2000), several studies using Trivector have been published. Including preliminary norms for the use of CCT (Ventura et al., 2003), which was considered by the creators of the CCT on the software website (http://www.crsltd.com/tools-for-vision-science/measuring-visual-functions/cambridge-colour-test/)

We re-checked our Trivector data and compared to several studies and we observed that we're with similar values for control groups. If another group (such smokers or deprived smokers) had higher thresholds, it means that they differ from the standard values and are likely to have color vision impairments.

As shown in the other studies, values for control subjects have fluctuated precisely in the values that we obtained in our data (Costa et al., 2007; Goulart et al., 2008; Paramei, 2012, 2014; Ventura et al., 2002).

Thus, the raising of the threshold of smokers is possibly connected with smoking conditions, since we've matched all possibly intervenient variables.

Taken together, we can not ignore that, although not as large, the differences were significant in this sample. Based on previous studies, even though there are small differences, they need to be punctuated, since we agree that this is an important area that requires further research.

Minor concern

1. Equation 1; I am not sure why Weber contrast (equation 1) needs to be explained in the Methods section. The authors should state clearly how they used the equation in their experiment.

Ops! Many thanks! Since CCT already uses this default setting, we strongly agreed with your review. These changes will be in the second version of the manuscript (we will remove it).

2. Results; The authors just listed the statistical results in the Results section. I suggest describing the results in the more detailed way (ex. thresholds were higher for smokers than non-smokers, U = 132, P = 0.002, r = -.61).

Many thanks again. We believe that the way you suggested will facilitate the reader's understanding and will enhance the scientific level of our writing. We fixed it. They will be more descriptive in the next version

3. 3rd paragraph in the Discussion section; The authors stated that “smokers were more sensitive to protanopic and deutanopic confusion axes.” This sentence is confusing. Which does this sentence mean, “more sensitive than non-smokers” or “more sensitive than to tritanopic axes”?

We appreciate the suggestion and agree that the use of two forms of explanation may actually confuse the reader. We will correct this.

However, when we mention that the smoking group was more sensitive to the protanopic or deutanopic axes, we simply mean that they made more errors than the control group, for example. That is, they needed more chromatic contrast (they were more sensitive) than the comparison group. The confusion axes refer to the red (protanopic), green (deutanopic) and blue (tritanopic) axes. Thus, if any group was more sensitive to the red confusion axis, forr example, it means that they possibly had impairments in the processing of this wavelength.

In this way, based on the apointments above, the 'not approved' status is honestly inconsistent with the content of the work. We ask you to reconsider your decision and we are grateful for the comment, reading, and review of the manuscript.

References

1. Lakens D. Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Front. Psychol. [Internet]. 2013 [cited 2017 Mar 10];4. Available from: http://journal.frontiersin.org/article/10.3389/fpsyg.2013.00863/abstract

2. Field A. Discovering Statistics Using IBM SPSS Statistics. SAGE; 2013.

3. Besson M, Granon S, Mameli-Engvall M, Cloëz-Tayarani I, Maubourguet N, Cormier A, et al. Long-term effects of chronic nicotine exposure on brain nicotinic receptors. Proc. Natl. Acad. Sci. 2007;104:8155–60.

4. Vallejo YF, Buisson B, Bertrand D, Green WN. Chronic Nicotine Exposure Upregulates Nicotinic Receptors by a Novel Mechanism. J. Neurosci. Off. J. Soc. Neurosci. 2005;25:5563–72.

5. Zhang L, Dong Y, Doyon WM, Dani JA. Withdrawal from Chronic Nicotine Exposure Alters Dopamine Signaling Dynamics in the Nucleus Accumbens. Biol. Psychiatry. 2012;71:184–91.

6. Mollon JD, Regan BC. Cambridge Colour Test Handbook [Internet]. 2000. Available from: https://sites.oxy.edu/clint/physio/article/CAMBRIDGECOLOURTESTHandbook.pdf

7. Ventura DF, Silveira LC de L, Rodrigues A, Costa MF. Preliminary Norms for the Cambridge Colour Test. 2003;331–9.

8. Costa MF, Oliveira AGF, Feitosa-Santana C, Zatz M, Ventura DF. Red-Green Color Vision Impairment in Duchenne Muscular Dystrophy. Am. J. Hum. Genet. 2007;80:1064–75.

9. Feitosa-Santana C, Barboni MTS, Oiwa NN, Paramei GV, Simões ALAC, Da Costa MF, et al. Irreversible color vision losses in patients with chronic mercury vapor intoxication. Vis. Neurosci. 2008;25:487–91.

10. Goulart PRK, Bandeira ML, Tsubota D, Oiwa NN, Costa MF, Ventura DF. A computer-controlled color vision test for children based on the Cambridge Colour Test. Vis. Neurosci. 2008;25:445–50.

11. Paramei GV. Color discrimination across four life decades assessed by the Cambridge Colour Test. J. Opt. Soc. Am. A Opt. Image Sci. Vis. 2012;29:A290-297.

12. Paramei GV, Oakley B. Variation of color discrimination across the life span. JOSA A. 2014;31:A375–84.

13. Pelli DG, Bex P. Measuring contrast sensitivity. Vision Res. 2013;90:10–4.

14. Hogg RE, Chakravarthy U. Visual function and dysfunction in early and late age-related maculopathy. Prog. Retin. Eye Res. 2006;25:249–76.

15. DeValois KK, Webster MA. Color vision. Scholarpedia. 2011;6:3073.

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Competing Interests

No competing interests were disclosed.

Reviewer Response

20 Mar 2017

Goro Maehara, Department of Human Sciences, Kanagawa University, Yokohama, Japan

Dear Thiago,

I am happy to review the revised manuscript.
Please make it clear that the thresholds of normal observers were comparable with those reported by previous studies using the Cambridge color test.

According to Thornton, Edwards, Mitchell, Harrison, Buchan & Kelly (2005), there is a strong association between current smoking and age-related macular degeneration. This line of studies could strengthen your paper.

Regards,

Goro

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Competing Interests

No competing interests were disclosed.

Author Response

30 Mar 2017

Thiago P Fernandes, Federal University of Paraiba, Brazil

Dear Goro,
Many thanks for the quick answer.

Based on your suggestions, substantial changes were made.

We inserted a subsection in the methods where we explained the cutoff points (where the results would be normal and where the discrimination losses would be).

In addition, we better describe the results section, making it clear to the reader that the higher the threshold, the lower the color discrimination. Also, based on your last suggestion, we added a few paragraphs about the relationship between the harmful cigarette compounds and the damage they cause to the retina, and consequently, visual processing.

I hope we have answered the suggestions. Again, we ask you to reconsider your decision about the status of our work.

Best regards,

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Competing Interests

None.

Alongside their report, reviewers assign a status to the article:

Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions

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Comparison of color discrimination in chronic heavy smokers and healthy subjects

Abstract

Keywords

Revised Amendments from Version 1

Introduction

Methods

Participants

Color discrimination test

Outcome cutoffs

Data analysis

Results

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Correlations

Discussion

Data availability

Author contributions

Competing interests

Grant information

Acknowledgments

References

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