The authors have declared that no competing interests exist.
In this study, we examined the perceptual associations women hold with regard to cervical cancer testing and vaccination across two countries, the U.S. and Australia. In a large-scale online survey, we presented participants with ‘trigger’ words, and asked them to state sequentially other words that came to mind. We used this data to construct detailed term co-occurrence network graphs, which we analyzed using basic topological ranking techniques. The results showed that women hold divergent perceptual associations regarding trigger words relating to cervical cancer screening tools, i.e. human papillomavirus (HPV) testing and vaccination, which indicate health knowledge deficiencies with non-HPV related associations emerging from the data. This result was found to be consistent across the country groups studied. Our findings are critical in optimizing consumer education and public service announcements to minimize misperceptions relating to HPV testing and vaccination in order to maximize adoption of cervical cancer prevention tools.
Growing evidence has demonstrated that the human papillomavirus (HPV) is the most common sexually transmitted infection (STI) responsible in a range of cervical, anogenital and oropharyngeal cancer cases. Specifically, 83% of all cervical cancer cases worldwide are attributable to the HPV infection and are therefore preventable through vaccination and screening tools [
In contrast to cervical cytology, new evidence and technology has illustrated that HPV testing provides a cost-effective and more sensitive approach in detecting high-degree lesions [
Variation in cervical cancer cases has therefore been linked to the presence of adequate ECDP and other relevant resources within countries, as well as the population presence of the cervical HPV infection [
The sensitive, personal and private nature surrounding public health concerns and, in this context, cervical cancer and screening, has often resulted in participants being unwilling to answer direct questions [
Utilizing this data-driven approach, in this study we analyze the perceptual word associations women hold with regard to ECDP screening tools (i.e. cervical cancer testing and vaccination) across two countries, the United States and Australia. We examined these two countries as they use the ECDP screening tools in different ways, thus enabling us to see how informed women drawn from the general population are and to identify information gaps within each country. We undertook a semi-structured data-mining exercise, which enabled the construction of co-occurrence network graphs that were then analyzed using basic topological ranking techniques. To this end, we aimed to answer the following research questions:
What word associations surrounding HPV testing do women hold and are these associations consistent across similar country groups?
What word associations surrounding HPV vaccination do women hold and are these associations consistent across similar country groups?
What can the types of terms produced and the connections between them tell us about the usefulness of word-association research in the public health context?
ECDP screening, which until recently, was based solely on cytology, in the form of the Pap smear, is currently shifting to rely on HPV testing procedures instead (accompanied by a HPV vaccination program) [
Currently in Australia, the Pap test is the primary ECDP screening tool, with clinical guidelines recommending women aged 18 to 69 undergo a Pap test every two years [
In the United States, these cervical cancer clinical guidelines differ, with women aged 21 to 65 years recommended to undergo a Pap test every three years [
Based on the above discussion, Australia and the United States share similar ECDPs. However, a core difference between these two countries lies in their use of HPV vaccination and testing. Therefore, we aim to generate understanding of the perceptual associations that arise from women’s thinking about ECDP screening tools (i.e. Pap test, HPV testing and HPV vaccination) across these two countries. A key aspect of our work is that co-occurrence network graphs will enable greater understanding surrounding cervical cancer screening and, ultimately, work towards the optimization of consumer education and public service announcements.
Using the consumer database from a reputable marketing research firm (SurveyMonkey), a large-scale online survey was conducted December 18–21, 2015. Participants were randomly selected from SurveyMonkey’s U.S. and Australian databases, using this study’s pre-defined selection criteria of women aged 18 to 64 years. An email invitation was sent to potential participants outlining the purpose of the study, giving instructions to complete the survey and including the link to the online survey. Implied consent to the study was provided through participants’ registration with SurveyMonkey, as well as the anonymous completion of this study’s survey. Participants who completed the survey were compensated via non-monetary incentives including donations to their preferred charity, and were given entries into a draw to win sweepstakes [
A total sample of 1473 (68%) was achieved with 704 from the U.S. and 769 from Australia. The total number of incomplete responses was 697 accounting for 32% of the sample, with 346 of these, participants from the U.S. sample and 351 participants from the Australian sample. SurveyMonkey also provided basic demographic information from participants, such as age and household income brackets, which is summarized in
Sample Characteristics | Australia | U.S.A. | Total |
---|---|---|---|
769 (52%) | 704 (48%) | 1473 (100%) | |
18 to 29 | 190 (25%) | 161 (23%) | 351 (24%) |
30 to 44 | 270 (35%) | 225 (32%) | 495 (34%) |
45 to 59 | 270 (35%) | 278 (39%) | 548 (37%) |
60+ | 39 (5%) | 40 (6%) | 79 (5%) |
$0 to $9,999 | 88 (11%) | 112 (16%) | 200 (14%) |
$10,000 to $24,999 | 123 (16%) | 156 (22%) | 279 (19%) |
$25,000 to $49,999 | 121 (16%) | 122 (17%) | 243 (16%) |
$50,000 to $74,999 | 155 (20%) | 88 (13%) | 243 (16%) |
$75,000 to $99,999 | 35 (5%) | 63 (9%) | 98 (7%) |
$100,000 to $124,999 | 51 (7%) | 71 (10%) | 122 (8%) |
Not Provided | 196 (25%) | 92 (13%) | 288 (20%) |
Yes | 239 (31%) | 254 (36%) | 493 (34%) |
No | 530 (69%) | 450 (64%) | 980 (67%) |
Values are n (%).
1 Household income groups were defined by SurveyMonkey’s demographic information. Dollar amounts for the Australian sample are in AU and dollar amounts for the U.S. sample are in USD
In the survey, we randomly presented participants with several trigger words to which they were asked to provide, in sequential order, the first three words (i.e. response words) that came to mind. The trigger words shown to participants comprised “cervical cancer”, “cervical cancer testing” and “cervical cancer vaccination” in succession. We divided the network analysis of participants’ response words (and subsequent presentation of results) into “vaccination” (trigger words “HPV vaccination” and “cervical cancer vaccination”) and “testing” (trigger words “HPV (human papillomavirus) test” and “pap smear”), and then further divided the responses by country groups (U.S. and Australia). For example, an Australian participant shown the trigger word ‘HPV (Human papillomavirus) test’ provided the response words of “cervix”, “cancer” and “virus”.
We used the data from the surveys to construct detailed, weighted term co-occurrence network graphs. Co-occurrence is a fundamentally simple concept, with relevance in “hard-science” applications [
Co-occurrence between response words was computed by taking the n-gram (i.e. set of adjacent words) co-occurrence statistic data [
We also removed n-grams related to the terms “unknown” and “n/a” provided by participants as we took these to denote a non-response. We included all other n-grams. Edges were thus created connecting n-grams provided by the same unique participant, in response to the same trigger word. The co-occurrence data for each participant was then merged into separate network graphs according to each trigger word. When the participant-level data was combined, the nodes representing identical entries (in response to trigger words) were merged. Identical co-occurrence pairings (edges) were also merged. This approach enabled the most salient n-grams (i.e. nodes) to emerge as naturally as possible.
Having generated networks from the word co-occurrence data collected from participants, we then analyzed the topological properties of the resulting networks. This involved examining the sub-structures of the networks (i.e. groupings of nodes and patterns in connections between nodes), as well as ranking nodes using some basic topological measures [
Testing | |||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
U.S. | Australia | ||||||||||||||
U.S. HPV test | Deg | W Deg | EvC | U.S. Pap | Deg | W Deg | EvC | Aus HPV test | Deg | W Deg | EvC | Aus Pap | Deg | W Deg | EvC |
cancer | 96 | 175 | 1 | uncomfortable | 132 | 304 | 1 | cancer | 97 | 200 | 1 | uncomfortable | 154 | 446 | 1 |
necessary | 76 | 111 | 0.641 | necessary | 104 | 260 | 0.837 | doctor | 72 | 122 | 0.862 | necessary | 116 | 330 | 0.871 |
std | 69 | 103 | 0.675 | yearly | 80 | 146 | 0.7 | necessary | 71 | 116 | 0.642 | cancer | 69 | 158 | 0.645 |
new | 66 | 86 | 0.612 | test | 72 | 135 | 0.634 | new | 63 | 83 | 0.627 | doctor | 65 | 152 | 0.608 |
test | 61 | 83 | 0.637 | cancer | 66 | 126 | 0.639 | unsure | 58 | 78 | 0.512 | test | 63 | 128 | 0.542 |
good | 49 | 74 | 0.45 | painful | 65 | 124 | 0.575 | uncomfortable | 57 | 101 | 0.681 | invasive | 56 | 108 | 0.552 |
disease | 48 | 68 | 0.48 | doctor | 51 | 100 | 0.592 | important | 51 | 69 | 0.519 | awkward | 56 | 120 | 0.553 |
prevention | 47 | 66 | 0.516 | annual | 50 | 94 | 0.537 | good | 48 | 67 | 0.498 | vagina | 54 | 94 | 0.489 |
scary | 46 | 56 | 0.448 | routine | 45 | 56 | 0.455 | test | 48 | 93 | 0.537 | embarrassing | 53 | 124 | 0.504 |
virus | 46 | 98 | 0.461 | prevention | 44 | 78 | 0.497 | prevention | 45 | 76 | 0.614 | important | 49 | 82 | 0.471 |
important | 45 | 72 | 0.531 | cold | 44 | 78 | 0.439 | virus | 41 | 70 | 0.457 | painful | 47 | 95 | 0.531 |
sex | 45 | 63 | 0.488 | pain | 40 | 51 | 0.42 | warts | 39 | 65 | 0.496 | pain | 42 | 60 | 0.411 |
doctor | 41 | 57 | 0.458 | vagina | 40 | 56 | 0.379 | std | 39 | 60 | 0.506 | prevention | 39 | 70 | 0.452 |
safe | 39 | 48 | 0.417 | needed | 39 | 62 | 0.468 | smear | 35 | 48 | 0.515 | discomfort | 38 | 48 | 0.361 |
preventative | 34 | 40 | 0.442 | important | 35 | 62 | 0.42 | disease | 34 | 49 | 0.424 | speculum | 38 | 62 | 0.426 |
exam | 34 | 44 | 0.415 | health | 34 | 44 | 0.379 | preventative | 34 | 45 | 0.436 | regular | 33 | 56 | 0.403 |
helpful | 34 | 48 | 0.375 | invasive | 34 | 46 | 0.431 | women | 32 | 38 | 0.482 | cervix | 32 | 58 | 0.378 |
screening | 31 | 39 | 0.464 | exam | 33 | 42 | 0.392 | pap smear | 32 | 62 | 0.429 | safe | 32 | 40 | 0.354 |
easy | 30 | 38 | 0.304 | safe | 31 | 36 | 0.31 | herpes | 32 | 43 | 0.349 | scary | 28 | 34 | 0.38 |
needed | 29 | 38 | 0.42 | speculum | 30 | 46 | 0.363 | invasive | 30 | 43 | 0.409 | needed | 28 | 36 | 0.3 |
warts | 28 | 36 | 0.262 | good | 29 | 36 | 0.296 | safe | 28 | 38 | 0.381 | annoying | 27 | 38 | 0.281 |
women | 27 | 32 | 0.386 | swab | 28 | 30 | 0.286 | detection | 27 | 38 | 0.388 | cold | 26 | 36 | 0.328 |
yearly | 25 | 30 | 0.313 | easy | 26 | 28 | 0.209 | scary | 26 | 33 | 0.276 | yuck | 26 | 31 | 0.305 |
health | 24 | 28 | 0.298 | yuck | 26 | 44 | 0.314 | needed | 25 | 30 | 0.319 | ouch | 24 | 26 | 0.246 |
smart | 23 | 25 | 0.254 | vaginal | 26 | 38 | 0.354 | sex | 25 | 36 | 0.366 | quick | 23 | 34 | 0.193 |
painful | 22 | 23 | 0.271 | annoying | 25 | 36 | 0.304 | vagina | 24 | 42 | 0.387 | old | 23 | 34 | 0.245 |
young | 22 | 23 | 0.293 | ouch | 25 | 28 | 0.31 | hiv | 23 | 28 | 0.229 | essential | 23 | 32 | 0.254 |
teens | 21 | 24 | 0.249 | women | 24 | 28 | 0.269 | easy | 22 | 32 | 0.243 | health | 23 | 36 | 0.298 |
blood | 21 | 26 | 0.31 | stirrups | 24 | 32 | 0.283 | essential | 21 | 22 | 0.22 | yearly | 23 | 26 | 0.227 |
no | 21 | 30 | 0.08 | preventative | 24 | 38 | 0.377 | discomfort | 20 | 24 | 0.245 | women | 21 | 38 | 0.309 |
uncomfortable | 21 | 27 | 0.264 | gross | 23 | 38 | 0.294 | useful | 20 | 22 | 0.256 | examination | 21 | 28 | 0.264 |
unsure | 21 | 25 | 0.165 | awkward | 23 | 44 | 0.346 | cervix | 20 | 32 | 0.34 | embarrassing | 21 | 26 | 0.243 |
detection | 21 | 26 | 0.271 | screening | 23 | 38 | 0.374 | screening | 20 | 28 | 0.329 | good | 21 | 26 | 0.264 |
cervix | 20 | 28 | 0.322 | old | 21 | 22 | 0.174 | medical | 20 | 23 | 0.334 | annual | 21 | 22 | 0.254 |
pap | 19 | 27 | 0.291 | embarrassing | 21 | 30 | 0.306 | accurate | 19 | 22 | 0.19 | routine | 21 | 26 | 0.166 |
shot | 17 | 21 | 0.202 | helpful | 20 | 28 | 0.306 | better | 19 | 20 | 0.198 | preventative | 20 | 28 | 0.254 |
vaccine | 17 | 18 | 0.239 | normal | 20 | 24 | 0.185 | what | 18 | 19 | 0.13 | detection | 19 | 28 | 0.261 |
pap smear | 17 | 18 | 0.214 | smear | 19 | 44 | 0.201 | cervical | 18 | 30 | 0.244 | cells | 18 | 24 | 0.212 |
aids | 17 | 22 | 0.188 | gynecologist | 18 | 26 | 0.27 | prevent | 18 | 20 | 0.258 | unpleasant | 18 | 32 | 0.248 |
what | 17 | 19 | 0.091 | no | 18 | 20 | 0.121 | vaccine | 18 | 26 | 0.212 | vaginal | 18 | 22 | 0.257 |
expensive | 16 | 16 | 0.076 | detection | 18 | 24 | 0.214 | reliable | 18 | 18 | 0.231 | yuk | 17 | 18 | 0.148 |
youth | 16 | 18 | 0.169 | gyno | 16 | 16 | 0.236 | helpful | 18 | 27 | 0.265 | intrusive | 16 | 24 | 0.203 |
why | 16 | 18 | 0.116 | hurt | 16 | 16 | 0.132 | health | 17 | 18 | 0.252 | female | 16 | 18 | 0.236 |
accurate | 16 | 18 | 0.207 | scary | 16 | 20 | 0.156 | cervical cancer | 17 | 24 | 0.272 | hpv | 15 | 16 | 0.159 |
unfamiliar | 15 | 15 | 0.128 | pap | 16 | 40 | 0.162 | pain | 16 | 18 | 0.132 | smear | 15 | 30 | 0.153 |
early | 15 | 18 | 0.187 | cervix | 15 | 24 | 0.231 | check | 16 | 20 | 0.293 | easy | 14 | 22 | 0.086 |
useful | 15 | 19 | 0.179 | unpleasant | 15 | 22 | 0.198 | pap | 15 | 22 | 0.251 | no | 14 | 21 | 0.064 |
sick | 15 | 16 | 0.122 | ugh | 15 | 18 | 0.178 | results | 15 | 16 | 0.211 | time | 14 | 14 | 0.081 |
informative | 15 | 16 | 0.181 | testing | 14 | 14 | 0.173 | yuck | 14 | 16 | 0.218 | gross | 13 | 16 | 0.188 |
hiv | 15 | 20 | 0.128 | healthy | 14 | 22 | 0.233 | great | 14 | 14 | 0.102 | useful | 13 | 16 | 0.185 |
contagious | 15 | 18 | 0.186 | discomfort | 14 | 14 | 0.167 | human | 14 | 29 | 0.237 | check | 13 | 16 | 0.16 |
need | 14 | 16 | 0.086 | check up | 13 | 13 | 0.088 | awkward | 14 | 20 | 0.187 | horrible | 13 | 16 | 0.17 |
preventable | 14 | 14 | 0.213 | hurts | 13 | 16 | 0.238 | cells | 14 | 16 | 0.201 | avoid | 12 | 14 | 0.166 |
effective | 14 | 18 | 0.214 | dread | 13 | 16 | 0.159 | sti | 14 | 16 | 0.246 | results | 12 | 14 | 0.107 |
speculum | 14 | 14 | 0.159 | quick | 13 | 20 | 0.184 | female | 14 | 17 | 0.222 | hurts | 12 | 14 | 0.197 |
dirty | 14 | 18 | 0.167 | fast | 12 | 12 | 0.115 | life saving | 14 | 14 | 0.174 | woman | 11 | 12 | 0.135 |
gross | 14 | 14 | 0.118 | nervous | 12 | 14 | 0.151 | blood | 14 | 16 | 0.154 | doctors | 11 | 12 | 0.144 |
better | 14 | 18 | 0.147 | preventive | 12 | 16 | 0.174 | blood test | 13 | 14 | 0.154 | cervical | 11 | 22 | 0.134 |
knowledge | 14 | 16 | 0.183 | required | 12 | 12 | 0.172 | how | 13 | 15 | 0.067 | 2 years | 11 | 12 | 0.167 |
cervical | 13 | 18 | 0.206 | hate | 12 | 12 | 0.195 | vaccination | 13 | 15 | 0.202 | required | 11 | 14 | 0.111 |
cervical cancer | 13 | 14 | 0.132 | female | 11 | 14 | 0.163 | same | 13 | 16 | 0.118 | cervical cancer | 11 | 12 | 0.195 |
pain | 12 | 12 | 0.085 | cervical | 11 | 14 | 0.126 | painful | 12 | 20 | 0.166 | helpful | 11 | 12 | 0.164 |
safety | 12 | 14 | 0.134 | same | 11 | 12 | 0.124 | examination | 12 | 13 | 0.166 | pap | 11 | 21 | 0.079 |
routine | 12 | 12 | 0.102 | informative | 11 | 14 | 0.178 | needle | 12 | 16 | 0.155 | screening | 11 | 12 | 0.153 |
swab | 12 | 12 | 0.116 | woman | 11 | 12 | 0.212 | quick | 11 | 14 | 0.108 | necessary | 10 | 12 | 0.117 |
preventive | 12 | 12 | 0.132 | yucky | 11 | 12 | 0.163 | yes | 11 | 16 | 0.084 | embarrassing | 10 | 16 | 0.179 |
results | 12 | 12 | 0.206 | embarrassing | 11 | 16 | 0.118 | early | 11 | 16 | 0.163 | reliable | 10 | 12 | 0.094 |
annual | 12 | 12 | 0.155 | check | 10 | 10 | 0.091 | embarrassing | 11 | 20 | 0.166 | precaution | 10 | 12 | 0.165 |
ok | 11 | 12 | 0.045 | smart | 10 | 12 | 0.121 | protection | 11 | 14 | 0.186 | embarrassment | 10 | 12 | 0.129 |
smear | 11 | 14 | 0.113 | reliable | 10 | 12 | 0.152 | no | 11 | 22 | 0.04 | inconvenient | 10 | 12 | 0.173 |
human | 11 | 42 | 0.134 | standard | 10 | 10 | 0.157 | ouch | 10 | 10 | 0.145 | scrape | 10 | 12 | 0.15 |
Visualization was performed using Gephi [
In the following sections, the network properties and structures of each of the developed ‘trigger word’ network graphs are discussed. The results show that the HPV and Pap smear testing networks illustrated similarities with the salient n-grams (i.e. “necessary”) that arose, whilst negative n-grams (i.e. “uncomfortable”) were most apparent in the Pap smear testing networks. Furthermore, upon visual inspection of the HPV and cervical cancer vaccination networks across both country groups, the preventative and beneficial nature of the trigger word “vaccination” was exhibited through the identified n-grams.
Network A, seeded from the trigger word “HPV Testing” for the U.S. country group comprised, 794 nodes connected by 1974 edges with an average degree of 4.904 (
U.S. HPV Test network visualization.
In reference to Network B, which was seeded from the trigger word “Pap smear testing”, the U.S. country group is comprised of 667 nodes connected by 1790 edges with an average degree of 5.367 (
U.S. Pap smear test network visualization.
In comparison to the U.S. country networks, the findings from the Australian network groups demonstrate similar n-grams. Specifically, Network C, seeded from the trigger words “HPV testing”, comprised 718 nodes connected by 1703 edges with an average degree of 5.136 (
Australia HPV test network visualization.
Network D, seeded from the trigger word “Pap smear testing” within the Australian sample, comprised 625 nodes connected by 1703 edges with an average degree of 5.45 (
Australia pap network graph.
Conversely, the n-grams from the HPV test network graphs (see Figs
Within the U.S. sample, Network E, seeded from the trigger words “HPV vaccination”, comprised 833 nodes connected by 1972 edges with an average degree of 4.735 (
U.S. HPV vaccination network visualization.
U.S. cervical vaccination network visualization.
Vaccination | |||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
U.S. | Australia | ||||||||||||||
U.S. HPV Vac | Deg | W Deg | EvC | U.S. C Vac | Deg | W Deg | EvC | AUS HPV Vac | Deg | W Deg | EvC | AUS C Vac | Deg | W Deg | EvC |
shot | 122 | 224 | 1 | shot | 103 | 185 | 1 | prevention | 111 | 210 | 0.96 | prevention | 119 | 246 | 0.992 |
prevention | 100 | 204 | 0.918 | prevention | 90 | 166 | 0.866 | needle | 108 | 215 | 1 | needle | 112 | 223 | 1 |
good | 69 | 102 | 0.692 | good | 80 | 119 | 0.796 | necessary | 80 | 126 | 0.737 | good | 83 | 139 | 0.815 |
new | 60 | 72 | 0.513 | new | 69 | 83 | 0.614 | good | 73 | 117 | 0.657 | necessary | 81 | 129 | 0.886 |
necessary | 56 | 80 | 0.535 | cancer | 69 | 137 | 0.663 | cancer | 67 | 132 | 0.762 | cancer | 60 | 141 | 0.642 |
cancer | 55 | 90 | 0.544 | necessary | 69 | 103 | 0.701 | easy | 56 | 90 | 0.554 | preventative | 55 | 76 | 0.572 |
important | 52 | 64 | 0.464 | helpful | 61 | 93 | 0.692 | preventative | 53 | 74 | 0.541 | important | 55 | 77 | 0.677 |
preventative | 51 | 70 | 0.472 | important | 57 | 81 | 0.574 | injection | 52 | 76 | 0.506 | easy | 54 | 92 | 0.552 |
painful | 46 | 55 | 0.467 | hpv | 56 | 94 | 0.599 | unsure | 47 | 56 | 0.441 | hpv | 54 | 83 | 0.569 |
needed | 44 | 58 | 0.431 | preventative | 48 | 80 | 0.583 | safe | 46 | 70 | 0.458 | great | 46 | 56 | 0.491 |
needle | 43 | 54 | 0.422 | painful | 45 | 55 | 0.548 | important | 46 | 59 | 0.537 | safe | 45 | 71 | 0.549 |
helpful | 42 | 63 | 0.415 | scary | 41 | 51 | 0.492 | virus | 45 | 86 | 0.461 | injection | 45 | 70 | 0.462 |
young | 41 | 60 | 0.472 | needed | 35 | 45 | 0.473 | doctor | 44 | 69 | 0.538 | doctor | 39 | 57 | 0.562 |
safe | 40 | 54 | 0.417 | needle | 33 | 44 | 0.422 | new | 42 | 55 | 0.408 | women | 33 | 50 | 0.433 |
std | 39 | 57 | 0.419 | pain | 33 | 42 | 0.396 | protection | 40 | 50 | 0.461 | protection | 32 | 42 | 0.448 |
virus | 36 | 70 | 0.362 | safe | 32 | 38 | 0.448 | needles | 37 | 46 | 0.348 | helpful | 32 | 42 | 0.396 |
teens | 31 | 36 | 0.378 | death | 32 | 36 | 0.376 | great | 32 | 34 | 0.301 | pain | 32 | 44 | 0.314 |
doctor | 30 | 38 | 0.404 | health | 31 | 40 | 0.443 | painful | 31 | 41 | 0.297 | painful | 31 | 34 | 0.252 |
no | 30 | 44 | 0.165 | great | 31 | 35 | 0.357 | health | 29 | 43 | 0.373 | health | 30 | 46 | 0.359 |
health | 28 | 38 | 0.373 | easy | 31 | 40 | 0.352 | young | 27 | 36 | 0.345 | unsure | 30 | 32 | 0.195 |
disease | 28 | 42 | 0.323 | women | 30 | 36 | 0.39 | teenagers | 27 | 33 | 0.348 | new | 30 | 41 | 0.347 |
vaccine | 28 | 40 | 0.34 | doctor | 24 | 28 | 0.314 | effective | 25 | 32 | 0.345 | needles | 29 | 36 | 0.361 |
protection | 27 | 30 | 0.289 | no | 24 | 40 | 0.056 | std | 25 | 32 | 0.354 | needed | 28 | 36 | 0.321 |
easy | 25 | 34 | 0.258 | expensive | 24 | 24 | 0.231 | vaccine | 24 | 36 | 0.317 | girls | 28 | 38 | 0.471 |
girls | 24 | 32 | 0.441 | need | 21 | 22 | 0.266 | girls | 24 | 36 | 0.306 | young | 27 | 34 | 0.411 |
unnecessary | 24 | 26 | 0.194 | unsure | 21 | 25 | 0.139 | pain | 22 | 28 | 0.268 | essential | 25 | 30 | 0.345 |
sex | 24 | 33 | 0.366 | prevent | 20 | 26 | 0.256 | warts | 21 | 28 | 0.277 | vaccine | 25 | 38 | 0.311 |
preventive | 23 | 30 | 0.245 | side effects | 19 | 20 | 0.255 | uncomfortable | 21 | 25 | 0.275 | prevent | 24 | 32 | 0.329 |
smart | 23 | 28 | 0.35 | young | 19 | 24 | 0.321 | what | 21 | 24 | 0.192 | ouch | 23 | 30 | 0.32 |
prevent | 22 | 32 | 0.24 | ouch | 19 | 25 | 0.339 | useful | 21 | 23 | 0.272 | effective | 22 | 28 | 0.319 |
vaccination | 22 | 29 | 0.255 | treatment | 19 | 24 | 0.243 | test | 21 | 30 | 0.275 | lifesaving | 20 | 25 | 0.345 |
scary | 20 | 22 | 0.179 | cervix | 19 | 26 | 0.2 | essential | 20 | 22 | 0.163 | excellent | 20 | 24 | 0.19 |
shots | 20 | 28 | 0.221 | smart | 19 | 28 | 0.357 | ouch | 20 | 24 | 0.252 | fantastic | 19 | 20 | 0.202 |
human | 20 | 46 | 0.179 | protection | 18 | 18 | 0.243 | prevent | 20 | 27 | 0.321 | cure | 18 | 22 | 0.263 |
dangerous | 19 | 20 | 0.044 | cure | 18 | 24 | 0.222 | quick | 19 | 28 | 0.247 | awesome | 18 | 22 | 0.202 |
effective | 19 | 22 | 0.211 | unnecessary | 18 | 18 | 0.097 | school | 19 | 26 | 0.288 | free | 18 | 22 | 0.275 |
needles | 19 | 20 | 0.204 | shots | 18 | 20 | 0.17 | helpful | 18 | 22 | 0.265 | scary | 18 | 21 | 0.15 |
ouch | 18 | 22 | 0.216 | preventive | 18 | 20 | 0.259 | sex | 18 | 22 | 0.259 | no | 18 | 31 | 0.119 |
expensive | 18 | 18 | 0.239 | risky | 17 | 18 | 0.113 | better | 18 | 20 | 0.196 | safety | 16 | 22 | 0.259 |
side effects | 18 | 19 | 0.214 | safety | 17 | 20 | 0.249 | women | 18 | 26 | 0.286 | life | 16 | 18 | 0.2 |
three | 18 | 20 | 0.215 | effective | 17 | 20 | 0.282 | cervical cancer | 18 | 18 | 0.205 | school | 16 | 18 | 0.248 |
pain | 17 | 22 | 0.253 | injection | 17 | 20 | 0.228 | safety | 18 | 19 | 0.207 | breakthrough | 16 | 18 | 0.237 |
great | 17 | 21 | 0.151 | what | 17 | 18 | 0.118 | simple | 17 | 20 | 0.214 | teenagers | 16 | 21 | 0.246 |
quick | 17 | 20 | 0.148 | test | 17 | 21 | 0.231 | free | 17 | 20 | 0.238 | cervix | 15 | 28 | 0.279 |
teenagers | 16 | 18 | 0.227 | female | 17 | 18 | 0.289 | disease | 16 | 24 | 0.215 | vagina | 15 | 18 | 0.273 |
women | 16 | 18 | 0.256 | bad | 16 | 16 | 0.151 | herpes | 16 | 20 | 0.232 | yes | 15 | 19 | 0.161 |
unsure | 16 | 19 | 0.113 | vaccine | 16 | 22 | 0.297 | cervical | 16 | 26 | 0.291 | useful | 14 | 17 | 0.228 |
useful | 15 | 16 | 0.169 | awesome | 15 | 16 | 0.288 | no | 16 | 23 | 0.094 | female | 14 | 18 | 0.236 |
cure | 15 | 20 | 0.219 | ok | 15 | 18 | 0.167 | medical | 15 | 17 | 0.192 | innovative | 14 | 14 | 0.195 |
safety | 15 | 18 | 0.181 | insurance | 15 | 16 | 0.23 | needed | 15 | 18 | 0.13 | death | 14 | 16 | 0.171 |
gardasil | 14 | 14 | 0.175 | gardasil | 14 | 16 | 0.193 | yes | 14 | 15 | 0.095 | compulsory | 14 | 14 | 0.207 |
cervix | 14 | 22 | 0.202 | needles | 14 | 14 | 0.119 | doctors | 14 | 16 | 0.189 | cost | 14 | 16 | 0.122 |
questionable | 14 | 14 | 0.111 | useful | 14 | 16 | 0.268 | human | 14 | 34 | 0.076 | quick | 14 | 22 | 0.179 |
what | 14 | 15 | 0.101 | hope | 13 | 14 | 0.172 | youth | 14 | 14 | 0.198 | pap smear | 13 | 14 | 0.132 |
warts | 14 | 16 | 0.158 | yes | 13 | 18 | 0.154 | immunity | 14 | 16 | 0.223 | relief | 13 | 14 | 0.216 |
ok | 14 | 18 | 0.102 | teens | 13 | 16 | 0.254 | immunisation | 14 | 16 | 0.227 | positive | 13 | 16 | 0.198 |
risky | 14 | 16 | 0.103 | painless | 12 | 16 | 0.125 | cost | 14 | 18 | 0.239 | simple | 13 | 16 | 0.172 |
injection | 14 | 16 | 0.171 | really? | 12 | 12 | 0.107 | smart | 13 | 14 | 0.136 | precaution | 13 | 14 | 0.246 |
hurt | 14 | 16 | 0.235 | medicine | 12 | 16 | 0.171 | easier | 13 | 14 | 0.163 | youth | 13 | 14 | 0.174 |
test | 13 | 14 | 0.131 | interesting | 11 | 11 | 0.112 | life saving | 13 | 14 | 0.279 | expensive | 12 | 12 | 0.096 |
need | 12 | 14 | 0.134 | none | 11 | 32 | 0.089 | female | 13 | 14 | 0.195 | uncomfortable | 12 | 14 | 0.203 |
healthy | 12 | 14 | 0.179 | disease | 11 | 12 | 0.123 | innovative | 12 | 12 | 0.141 | good idea | 12 | 14 | 0.194 |
beneficial | 12 | 12 | 0.134 | hopeful | 11 | 12 | 0.153 | beneficial | 12 | 12 | 0.147 | age | 12 | 12 | 0.114 |
youth | 12 | 15 | 0.165 | pap | 11 | 11 | 0.096 | vaccination | 12 | 16 | 0.135 | teenager | 12 | 16 | 0.235 |
yes | 12 | 19 | 0.06 | help | 10 | 10 | 0.14 | not sure | 11 | 17 | 0.095 | smart | 11 | 12 | 0.166 |
teenager | 11 | 14 | 0.186 | questionable | 10 | 10 | 0.065 | healthy | 11 | 12 | 0.181 | unnecessary | 11 | 13 | 0.068 |
female | 11 | 12 | 0.15 | not | 10 | 10 | 0.024 | expensive | 11 | 11 | 0.072 | immunisation | 11 | 12 | 0.171 |
aids | 11 | 12 | 0.111 | innovative | 10 | 10 | 0.183 | teenager | 11 | 14 | 0.196 | when | 11 | 12 | 0.157 |
controversial | 11 | 12 | 0.135 | relief | 10 | 10 | 0.135 | breakthrough | 10 | 12 | 0.094 | vital | 11 | 12 | 0.203 |
wonderful | 11 | 12 | 0.107 | wonderful | 10 | 10 | 0.137 | hiv | 10 | 10 | 0.185 | how | 11 | 12 | 0.096 |
precaution | 11 | 14 | 0.147 | lifesaving | 10 | 12 | 0.145 | vital | 10 | 10 | 0.167 | life saving | 10 | 12 | 0.198 |
hiv | 11 | 12 | 0.147 | cost | 10 | 10 | 0.108 | interesting | 10 | 11 | 0.031 | ||||
interesting | 10 | 10 | 0.081 | effectiveness | 10 | 10 | 0.126 | ||||||||
untested | 10 | 10 | 0.075 | worthwhile | 10 | 10 | 0.033 | ||||||||
early | 10 | 10 | 0.122 | ||||||||||||
good idea | 10 | 10 | 0.06 | ||||||||||||
medicine | 10 | 12 | 0.17 | ||||||||||||
cost | 10 | 10 | 0.027 | ||||||||||||
everyone | 10 | 12 | 0.244 | ||||||||||||
herpes | 10 | 10 | 0.187 |
Note: Deg denotes Degree; WDeg denotes weighted degree, and EVC denotes eigenvector centrality
In reference to the Australian country group, Network G, which was seeded from the trigger words “HPV vaccination”, comprised 777 nodes connected by 1923 edges with an average degree of 4.95 (
Australia HPV vaccination network visualization.
Australia cervical vaccination network visualization.
In review of
We structure our discussion around each of the research questions outlined at the beginning of this study. First, in spite of the differences between the ECDP across both countries, the associations regarding the trigger words HPV testing produced positive perceptual associations by female participants in the U.S. and Australian samples studied. We also found that negative connotations were raised by participants relating to the uncomfortable nature of the Pap test.
The overarching theme representing this particular form of testing was signified across both country samples by n-grams such as “uncomfortable”, “awkward” and “invasive”. This theme encapsulates the negative connotations that participants have associated with the Pap smear test, implied by the terms “discomfort”, “painful” and “awkward”. Although, the Pap smear network graphs within each country sample highlight the necessary and preventative nature of the test in identifying cervical cancer, this form of cervical cancer testing engenders negative perceptions, which may function to inhibit preventative action amongst women. Consequently, better education of health professionals is required to make the testing process and service environment less uncomfortable, which may work to increase the participation rate.
The results show that both the U.S. and Australian country samples drew links between the trigger words “HPV and cervical vaccination” and sexually transmitted infections (STIs), with the terms “sex”, “std”, “virus” and “disease” reported by the participants. Both country samples also identified a correct association between the triggers word “HPV vaccination” and the n-grams “warts”. This shows that there is knowledge in each country sample that HPV can cause genital warts and is an STI. However, both country samples identified incorrect STI associations between these trigger words (“HPV vaccination”) and the n-grams “HIV”, “herpes” and “AIDS”. Such findings might indicate that women across both country samples do not differentiate between STIs, as well as holding false assumptions about HPV testing using the same medical procedures as HIV testing (a ‘simple blood test’). Therefore, this finding illustrates potential health themes for educational public service announcements and intervention programs that encourage adoption of the HPV vaccine and preventative sexual behaviors.
Taken collectively, these findings are significant based on the explicit word choices of negative connotations toward this form of cervical cancer screening may function to inhibit women’s decision-making with regard to the adoption of preventative health behavior actions (i.e. undergoing regular Pap smear tests). Consequently, it is advisable that cervical screening education programs are designed to inform the public as to the precise details of HPV vaccination and screening schedules as well as mitigate flawed assumptions and misconceptions regarding the nature of the procedures. By addressing concerns on the part of women about timing and comfort, such action may improve HPV and Pap smear-testing goals.
Second, regarding associations surrounding HPV vaccination, we found across both country samples that women hold correct and favorable associations relating to the preventative and beneficial nature of the vaccination. For example, participants consistently referred to the n-grams “school”, “teens” and “young”. This finding signifies that participants across both country samples are aware that the vaccination is administered to pre-teen females via doctors or school immunization programs [
Third, in terms of broad relevance for public health research, this study reveals a number of interesting insights. In particular, the approach used in this paper allowed us to assess the diversity and variation in vocabularies used by patients to describe their perceptions and associations across two country samples. We then showed a simple method for identifying the relative importance of terms to specific trigger words.
In this study, we have demonstrated the usefulness of our approach in identifying community groups and sub-structures within networked patient associations across each country sample. Further clarity can be achieved with targeted filtering of the networks to examine network sub-structures more closely.
We have also demonstrated how easily words pertaining to specific topics, content, or sentiment types can be compared.
Our study has several limitations. First, the data set used in this study may not be representative of the female population aged 18+ in the targeted countries, as the algorithm for selecting participants is not disclosed and the pool of potential participants as a whole may be inherently biased. Second, the survey was conducted in a very narrow timeframe (4 days, just before the Christmas holidays), which may have introduced some bias but would also have excluded any bias from perception shifts that might have occurred in the targeted population over an extended time. Third, we based our analysis on exact string matches without any pre-processing such as stemming, lemmatization or fuzzy matching. Thus, the relevance of some concepts may be underestimated.
A number of research directions arise from this study. Using a more representative sample of the population, future research could consider deeper analysis focused on semantics [
Future research will consider applying similar approaches to unstructured data (e.g. health discussions on social media [
The survey presented to the probands.
(PDF)
The data file (.xlsx) with the survey responses and metadata.
(XLSX)
The authors acknowledge Dr Ben Lucas, Maastricht University, Netherlands for the constructive comments and support in data analysis for this paper.