| Literature DB >> 25886641 |
Laura Elizabeth Downie1, Peter Richard Keller2.
Abstract
OBJECTIVE: The primary aim of this study was to examine the self-reported, routine clinical practice behaviors of Australian optometrists with respect to advice regarding smoking, diet and nutritional supplementation. The study also sought to assess the potential influence of practitioner age, gender, practice location (major city versus regional), therapeutic-endorsement status and personal nutritional supplementation habits upon management practices in these areas.Entities:
Mesh:
Year: 2015 PMID: 25886641 PMCID: PMC4401759 DOI: 10.1371/journal.pone.0124533
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Summary of the age and years of optometric experience of the survey respondents.
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| % respondents | 17.7 | 24.7 | 26.9 | 23.3 | 7.4 |
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| % respondents | 32.1 | 23.7 | 25.8 | 18.0 | 0.4 |
Predictors of practitioner behavior in relation to asking about patient smoking status.
| Univariate model | Multivariate model | ||
|---|---|---|---|
| Variable | p value | p value | Adjusted OR (95% CI) |
| Own smoking status | 0.383 | ||
| Taken dietary supplements in past year | 0.017 | 0.090 | |
| Own annual expenditure on dietary supplements | 0.282 | ||
| Gender | 0.171 | ||
| Age | 0.034 | 0.016 | 1.30 (1.05 to 1.61) |
| Therapeutic endorsement status | 0.230 | ||
| Years in practice | 0.116 | ||
| Practice location | 0.632 | ||
* indicates a statistically significant difference (p < 0.05).
Only those variables found to be statistically significant by multiple univariate modeling were included in the subsequent multivariate modeling. Smoking status was collapsed to become dichotomous, i.e., ever or never.
Summary of the proportion of survey respondents in each age bracket who indicated routinely asking their patients about smoking behaviors.
| Age (years) | 20–29 | 30–39 | 40–49 | 50–59 | 60+ |
|---|---|---|---|---|---|
| % respondents | 34.0 | 38.0 | 48.7 | 56.1 | 57.4 |
* indicates a significant difference (p < 0.05) compared with respondents in all other age brackets.
Predictors of practitioner behavior in relation to providing advice to patients about smoking cessation.
| Univariate model | |
|---|---|
| Variable | p value |
| Own smoking status | 0.982 |
| Taken dietary supplements in past year | 0.979 |
| Own annual expenditure on dietary supplements | 0.378 |
| Gender | 0.178 |
| Age | 0.178 |
| Therapeutic endorsement status | 0.565 |
| Years in practice | 0.366 |
| Practice location | 0.465 |
| Asks about patient smoking status | < 0.001* |
Except for whether a practitioner asks about smoking status, no variable was found to be statistically significant (*) by multiple univariate modeling and no multivariate modeling was applied.
Fig 1A ‘word cloud’ of the 25 most frequently reported words generated from free-text responses from optometrists (n = 52) to a question asking for the reason(s) why they do not counsel patients regarding smoking behaviors.
Predictors of practitioner behavior in relation to advising patients about their diet.
| Univariate model | Multivariate model | |
|---|---|---|
| Variable | p value | p value |
| Own smoking status | 0.659 | |
| Taken dietary supplements in past year | 0.050 | 0.086 |
| Own annual expenditure on dietary supplements | 0.123 | |
| Gender | 0.827 | |
| Age | 0.050 | 0.662 |
| Therapeutic endorsement status | 0.266 | |
| Years in practice | 0.004 | 0.485 |
| Practice location | 0.590 |
* indicates a statistically significant difference (p < 0.05).
Only those variables found to be statistically significant by multiple univariate modeling were included in the subsequent multivariate modeling. No variable was found to be statistically significant after multivariate modeling was applied.
Predictors of practitioner behavior in relation to asking patients about their use of nutritional supplements.
| Univariate model | ||
|---|---|---|
| Variable | p value | Unadjusted OR (95% CI) |
| Own smoking status | 0.406 | |
| Taken dietary supplements in past year | 0.606 | |
| Own annual expenditure on dietary supplements | 0.632 | |
| Gender (female) | 0.017 | 1.78 (1.11 to 2.86) |
| Age | 0.514 | |
| Therapeutic endorsement status | 0.952 | |
| Years in practice | 0.552 | |
| Practice location | 0.774 | |
* indicates a statistically significant difference (p < 0.05).
Only one variable was found to be statistically significant by multiple univariate modeling and no multivariate modeling was applied.
Predictors of practitioner behavior in relation to advising patients about the use of nutritional supplements.
| Univariate model | ||
|---|---|---|
| Variable | p value | Unadjusted OR (95% CI) |
| Own smoking status | 0.638 | |
| Taken dietary supplements in past year | 0.615 | |
| Own annual expenditure on dietary supplements | 0.195 | |
| Gender | 0.459 | |
| Age | 0.005 | 1.43 (1.11 to 1.84) |
| Therapeutic endorsement status | 0.981 | |
| Years in practice | 0. 11 | |
| Practice location | 0.290 | |
* indicates a statistically significant difference (p < 0.05).
Only one variable was found to be statistically significant by multiple univariate modeling and therefore no multivariate modeling was applied.
Summary of the proportion of survey respondents, of those who routinely recommended nutritional supplements to patients, who nominated each ocular or general health condition.
| Medical condition | % Respondents |
|---|---|
| AMD | 91.2 |
| Dry eye disease | 63.9 |
| Other | 7.1 |
| Eyelid twitching | 3.5 |
| Diabetic retinopathy | 1.3 |
| Anemia | 1.3 |
| Viral ocular infection | 1.3 |
AMD, age-related macular degeneration; ‘Other’ includes: arthritis, cataract, glare, glaucoma, hordeolum, hypercholesterolemia, myopia, nyctalopia, osteoporosis, scurvy and skin abnormalities.
Fig 2Stacked bar chart showing the proportion of survey respondents who ranked, in order of importance, the various sources of information or evidence that they used to guide their clinical decision making for recommending nutritional supplementation.