Association between titles of healthcare articlesand inclusion in the Altmetric Top 100

Nicola Di GirolamoDMV, MSc(EBHC), PhD

Reint M. ReyndersDDS, MSc, MSc(EBHC)

nicoladiggi@gmail.com

EBMVET

The title

• Key objectives

• Summarise the content

• Trigger reader’s curiosity

• Improve indexing

• Indicative vs declarative

• “Attract” busy clinicians

• Goal-based research?

Introduction Methods Results Discussion

Title length and impact?

Introduction Methods Results Discussion

R Soc Open Sci. 2015 Aug 26;2(8):150266.

The advantage of short paper titles.Letchford A et al

Jamali HR, Nikzad M. Scientometrics 2011; 88, 653–661.

Jacques TS, Sebire NJ. JRSM Short Rep. 2010; 1(1):2.

Longer titles > citations

Letchford. R Soc Open Sci 2015; 2, 150266.

Shorter titles > citations

No title effect on citations

Effect of the journal

Alternative-level metrics• Measure the dissemination of

scientific findings in social media

• Altmetric score: how oftenarticles are mentioned online

• blogs

• wikipedia

• social media platforms

• facebook

• twitter

• google plus

• Altmetric scores are alsoassociated with citations

Introduction Methods Results Discussion

Thelwall et al. PLoS One. 2013;8(5):e64841.Eysenbach et al. J Med Internet Res. 2011;13:e123.

• Published every year since 2013

• 100 most shared articles

Assess whether specific title characteristics couldinfluence the likelihood of being included in the

“Altmetric Top 100”

Introduction Methods Results Discussion

Objective of the study

Study design and outcomes

Matched case-control study

• Cases:

• Controls:

Introduction Methods Results Discussion

Outcomesassociation between

• type of title -primary-• presence of uncommon words -secondary-• title length -secondary-

and inclusion in the top 100 Altmetric list

• “Medical & Health Sciences” included in the top100 Altmetric lists (2013-2015)

• Randomly selected health care articles matchedfor journal and year of publication

Control articles matching

Introduction Methods Results Discussion

1

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4

5

6

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Data extraction1. Title length (in characters)

2. Declarative/indicative

• Two operators independently categorized whether a title was ‘declarative’ or ‘indicative’

• The definition of a declarative title according to McGowan [9] and Gjersvik [10] was adopted

• (1) gave the results or main message of the conclusion(s)

and/or

• (2) used a verb (usually past tense or present tense) that declared a certain action.

• Disagreements were resolved through discussions. In case of persisting disagreement(s), athird operator was consulted

3. Number of uncommon words

• Software included 21300 common words (Custom 9300 - custom 7000 + 5000 from Wikipedia)

• Repeatability of the software was pilot tested on an independent sample of 20 titles thatcontained similar words in a different order

Introduction Methods Results Discussion

Statistical analysisSample size calculation

• 90% power, 5% alpha

• 25% declarative titles […]

• 20% increase in the ratio of declarative titles in the case group(i.e., Altmetric Top 100) would be practically significant

• 1:2 enrolment adjustment

• 88 in case group, 176 control group

Data analysis

• Conditional logistic regression

• Adjustment for an a priori specified confounder (open-access)

Introduction Methods Results Discussion

Population summary

• 108 articles from 2013 to 2015 classified as“Medical and health sciences”

• 216 matched articles

• Categorization of titles as ‘declarative’ and‘indicative’: only 11 disagreements on 324articles

• All disagreements were resolved throughdiscussions

Introduction Methods Results Discussion

Title characteristics

Introduction Methods Results Discussion

Introduction Methods Results Discussion

Introduction Methods Results Discussion

Multivariate adjustment

Introduction Methods Results Discussion

Declarative titles had 2.8 times the odds of being in the Altmetric Top 100

OR: 2.8; 95%CI: 1.2 to 6.4

For each additional uncommon word in the title there was an 1.4 increase in

the odds of not being in the Altmetric top 100

OR: 1.4; 1.2 to 1.6

Introduction Methods Results Discussion

Limitations and future aims

• Lack of matching by the exact topic (only by journal)• Lack of knowledge if an article was press-released or “pushed” by authors/institutions

However, the present study showed that title characteristicsexplained a part of the variability between articles that are

highly discussed and those that are not.

• Controlling by press-release• Including additional years• “Who” is sharing the articles?

Introduction Methods Results Discussion

ConclusionsThere is an association between certain title

characteristics of healthcare articles andinclusion in the “Altmetric Top 100”

An easy-to-understand, informative title maybridge the gap between academia and social

media.

Is plain language key for successful dissemination insocial media?

Acknowledgments

Reint M. Reynders

nicoladiggi@gmail.com

EBMVET

- Annette Pluddemann- Luisa Ladu- Nia Roberts- Federica Repossi