Determinants of cancer screening awareness and participation among Indonesian women

PILAR Research 0 Comments

Sumadi L. Anwar1,2, Gindo Tampubolon3, Mieke Van Hemelrijck4, Susanna H. Hutajulu5, Johnathan Watkins2, Wahyu Wulaningsih2,6, for the PILAR Research Network


1Division of Surgical Oncology Department of Surgery, Faculty of Medicine Universitas Gadjah Mada, Yogyakarta 55281, Indonesia

2PILAR Research and Education, 20 Station Road, Cambridge CB1 2JD, UK

3Cathie Marsh Institute for Social Research, University of Manchester, Manchester M13 9PL, UK

4Translational Oncology and Urology Research, King’s College London UK SE1 9RT

5Division of Medical Haematology and Oncology Department of Internal Medicine, Faculty of Medicine Universitas Gadjah Mada, Yogyakarta 55281, Indonesia

5MRC Unit for Lifelong Health and Ageing, University College London, London WC1B 5JU, UK

Corresponding author:

Wahyu Wulaningsih

MRC Unit for Lifelong Health and Ageing

University College London

33 Bedford Place London WC1B 5JU, UK

Phone: +44(0)20 7670 5726



E-mail address co-authors:;;,


Running title: Cancer screening awareness and participation in women

Conflict of interest: All authors declare no conflict of interest exists.


Word count: 275 (Abstract), 3,680 (Text)


Background: Cancer screening awareness and participation may vary in low- and middle-income countries lacking established national screening programmes. We evaluated potential determinants of awareness about and participation in breast and cervical cancer screening and breast self-examination (BSE) in older women in a large survey in Indonesia.

Methods: From the fifth Indonesian Family Life Survey (2014-2015), a total of 5,397 women aged 40 and older without any history of cancer who responded to questionnaires concerning Pap smear, mammography, and BSE were included. Multilevel modelling was used to assess potential determinants in relation to awareness about Pap smear and mammography, and participation in Pap smear and BSE practice. Multivariable analyses were performed to identify independent predictors of cancer screening and participation.

Results: Of the 5,397 respondents, 1,058 (20%) women were aware of Pap smears, and 297 among them ever had the procedure. Only 251 (5%) participants were aware of mammography. A total of 605 (12%) of women reported they performed BSE. Higher education and household expenditure were consistently associated with higher odds of awareness about Pap smear and mammography (e.g. odds ratio [OR] of being aware of Pap smear and mammography: 7.22 (95% CI: 5.84-8.94) and 2.55 (1.81-3.59), respectively, for high school graduates compared to women with less educational attainment in the multivariable models), and participation in Pap smear and BSE. We also identified enabling factors linked with greater cancer screening awareness and participation, including health insurance, shorter distance to health services, and social participation.

Conclusion: There are socioeconomic disparities in cancer screening awareness and participation among Indonesian women. Our findings may help inform targeted health promotion and screening for cancer in the presence of limited infrastructure.


Keywords: breast cancer, screening, cervical cancer, Pap smear, breast self-examination



The overall burden of cancer has continuously increased in developing countries.[1] The World Health Organization (WHO) International Agency for Research on Cancer (IARC) estimated that the cancer burden will grow up to 21.7 million new cancer cases and 13 million related deaths in 2030, with 70% of cases predicted to be found in low- to middle-income countries (LMICs).[2–4] Although cancer mortality rates have declined in high-income countries, LMICs have seen elevated cancer-related mortality [5], owing to a lack of cancer prevention and screening programmes and limited infrastructure.[4,6]


In LMICs such as Indonesia, cancers are mostly diagnosed at advanced stages, in which curable treatment is no longer an option.[7] For female cancers, breast and cervical cancers remain the leading causes of cancer mortality in Indonesia (21% and 10%, respectively).[5] Yet, affordable cervical cancer screening is only available in eight of 34 provinces in Indonesia,[5,8] with low awareness and uptake of breast and cervical cancer screening.[5,8,9] The low uptake may be attributable to a range of barriers including the lack of knowledge about cancer prevention, early detection, and treatment, poverty, cultural and religious beliefs.[10] Widespread misconceptions and fears about cancer and its treatment[9] also further contribute to the late presentation of disease.[11] In addition, there are often inequalities of distribution of healthcare workers throughout the country, resulting in wide gaps of overall healthcare access especially between urban and rural areas.[12] Nonetheless, the extent of inequalities in cancer screening awareness and participation in LMICs such as Indonesia is often not clear. Additionally, breast self-examination (BSE) as a tool to screen for breast cancer is common in these countries, despite evidence suggesting its lack of benefit.

We performed a cross-sectional study of 5,397 cancer-free Indonesian women aged 40 and older, which are the target group for breast and cervical cancer screening based on the American Cancer Society Guidelines.[13] In this population, we used multilevel regression analyses to identify potential determinants of cervical and breast cancer screening awareness and participation to gain further insight into predisposing, enabling, and need factors which could potentially inform targeted prevention programmes in low-resource settings.


Study population

The Indonesian Family Life Survey (IFLS) is a longitudinal household survey in Indonesia containing information from questionnaires, as well as physical and laboratory examinations. Data were collected at individual, household, and community levels. The first IFLS (IFLS1) used a stratified sampling scheme based on provinces and urban/rural location. For cost-effectiveness, 14 of the then existing 27 provinces were excluded [14]. The resulting sample included 13 of Indonesia’s 27 provinces, containing 83% of the population: four provinces on Sumatra (North Sumatra, West Sumatra, South Sumatra, and Lampung), all five of the Javanese provinces (DKI Jakarta, West Java, Central Java, DI Yogyakarta, and East Java), and four provinces covering the remaining major island groups (Bali, West Nusa Tenggara, South Kalimantan, and South Sulawesi). Within each province, enumeration areas (EAs) were randomly chosen from a nationally representative sample frame used in a socioeconomic survey of about 60,000 households in 1993 [14]. Within a selected EA, households were randomly selected. Interviews were carried out with the household head and the spouse, and up to 4 randomly selected other household members as interviewing all members of the household would have been too costly. All members of the original household have been followed up through four subsequent IFLS waves. The present study was based on the fifth wave of IFLS (IFLS5), conducted in 2014-2015. Both original and split-off households were tracked in the IFLS5, resulting in a 76% re-contact rate (including death) for the original IFLS1 household members, and 82% for IFLS1 main respondents. From the IFLS5, we included a total of 5,397 women aged 40 and older who responded to the questions on Pap smear, mammography, and BSE without self-reported history of cancer (Figure S1).

Cancer screening participation and behaviour

The outcomes of the present study measured awareness of Pap smear and mammography, and participation in Pap smear and BSE practice. All responses were self-reported and dichotomous (yes, no). First, during the interview, respondents were asked if they ever heard of Pap smear. Those who responded positively to this question were further asked whether they ever had any Pap smear in their life, and when the examination took place. Participants were also asked whether they ever heard about mammography, and those who responded positively were asked whether they had any mammography in the past year. All study participants were asked whether they ever performed BSE in the past year.


Potential determinants of screening

The Anderson model of healthcare use behaviour [15] was used to identify potential determinants of cancer screening awareness and participation. This model included three domains: predisposing, enabling, and need factors, which interact in determining one’s health-related behaviour. From IFLS5 (Figure 1), predisposing sociodemographic and lifestyle characteristics of the patients were collected including age, ethnicity, urban or rural residence, marital status, education, monthly household expenditure, smoking status, physical activity and personality traits. Ethnicity was categorised into Javanese, which comprises the majority of Indonesians, and non-Javanese. Education was categorised based on the highest level (less than high school, high school, higher education). Household expenditure was calculated based on the total of food, non-food and education expenditure.[16] Smoking history was used to classify individuals into current, former and never smokers. Participants were defined as vigorously active if they reported participating in more than two vigorous physical activities in the past week for at least 10 minutes each,[17] moderately active if they participated more than 4 times in the past week in moderate to vigorous physical activities of which no more than two could be considered vigorous. Lightly active was defined as activities which were not vigorous or moderate, or walking at least 30 minutes each time, for more than 2 times in the past week. Those who reported no moderate or vigorous physical activity and walked less than 3 times a week were categorised as sedentary. Personality traits were assessed with a short (15-item) Big Five Inventory (BFI-15) questionnaire [18], with scores ranging from 1-5 for openness, conscientiousness, extroversion, agreeableness, and neuroticism.

Enabling factors identified in the population included insurance ownership and travel distance in minutes to nearest healthcare centres, and participation in any social activities within the past year. On 1 January 2014, the Indonesian government launched a compulsory national health insurance which covers Pap smear [19], although this scheme has yet to cover mammography. However, unequal access issues for healthcare was reported within the first year the scheme was implemented (2014-2015) [20], the period in which the present study took place. Therefore, we took into account self-reported insurance coverage in our analysis. Factors representing needs for cancer screening included information on reproductive factors: menopausal status and age at menarche, co-morbidities, parental history of cancer death, diabetes medication, hypertension or dyslipidaemia, body mass index (BMI) calculated from measured weight and height during physical examination and blood pressure. Systolic and diastolic blood pressures were measured with sphygmomanometer and the average between the first and second measurements was used. Co-morbidities were assessed as a comorbidity score similar to the Charlson co-morbidity index, where each co-morbid condition available (hypertension, diabetes, asthma, heart disease, liver disease, stroke, cancer, arthritis, kidney disease, stomach or digestive disease, and memory-related disease) contributed one point to the composite index with additional points given for older age. Finally, to assess the role of mental health, depression was measured with a short version (10-item) of Center for Epidemiologic Studies Depression Scale (CES-D),[14] and a cut-off of 8 was used for a screening of depressive symptoms.[18]


Statistical analysis

We analysed each determinant as exposure for the following binary outcomes: awareness of Pap smear, awareness of mammography, ever Pap smear, and ever BSE. We did not assess use of mammography as an outcome given the small number of participants with positive response. To take into account IFLS sampling design, we performed multilevel logistic regression analyses to obtain odds ratios (ORs) and their 95% CI for associations between each determinant and outcome. Community clustering was used as a random effect in a two-level multivariable model whereas household clustering was not included to maximise numbers of samples analysed in each category. However, findings between models using both community and household clusters and those with only community clusters were similar for factors which allowed use of both clustering such as continuous age and household expenditure. Univariate analyses were conducted for all potential determinants of cancer screening awareness and practice. These factors comprised different components of the Anderson model [15], ranging from predisposing factors such as sociodemographic characteristics (e.g. marital status, education, income), enabling factors which included healthcare access, to predisposing factors such as family history of cancer. We additionally included comorbid conditions (e.g. diabetes, obesity as measured by BMI) given the evidence linking comorbidity to cervical and breast cancer screening participation in Western populations [21]. A multivariable model was subsequently performed which included all of these individual determinants. We performed a series of sensitivity analyses including using a different cut-off for BSE, including only systolic or diastolic blood pressure categories in the multivariable models instead of both, and assessing systolic or diastolic blood pressure while excluding participants who received any hypertension drugs. Dataset was prepared with SAS release 9.3 (SAS Institute, Cary, NC). Logistic regression with multilevel modelling was performed with lme4 package in R version 3.3.2 (R Foundation for Statistical Computing, Vienna, Austria).



Characteristics of study participants (N=5,397) are presented in Table 1. The mean age of participants was 52.9 years. The majority of women were of Javanese ethnicity, married, lived in urban area, and did not complete high school. Nearly a quarter (23%) of women had 3 or more co-morbidities, and a similar proportion were overweight (BMI ≥ 25kg/m2). Only 1,058 (20%) women were aware of Pap smear and 297  among them had undergone at least one Pap smear in their lifetime. A total of 251 (5%) participants were aware of mammography, among which five had mammogram in the previous year. Twelve percent of women reported they ever performed BSE in the past year. We additionally present demographic characteristics of women who did not respond to questions on cancer screening (Table S1), which comprised of 9.6% women aged 40 and older. Compared to those who provided response, this group was older and had lower household expenditure, less educated, and more likely to be non-Javanese and unmarried.

Determinants of awareness to Pap smear

Table 2 shows potential determinants of awareness to Pap smear identified in univariable regressions, grouped according to the Anderson model. Some categories, for instance education levels, were merged in the analysis due to the limited numbers of participants. In the multivariable analysis, being Javanese, living in urban area, greater education levels, household expenditure, physical activity, agreeable and neuroticism traits, having insurance and participating in social activities corresponded to higher likelihood of being aware of Pap smear. As shown in Figure 2 and detailed in Table 4, a decrease in odds of Pap smear awareness was shown for farther distance to health service, higher systolic blood pressure and CESD score. The strongest association was observed for education, with those who finished high school having over 7 times greater odds (95% CI: 5.84-8.94) of being aware of Pap smear compared to those less educated.


Determinants of awareness to mammography

Similar patterns of associations between potential predictors and awareness of Pap smear were observed for awareness of mammography (Table 2). When all predictors were included in the same model, we found higher odds of being aware of mammography in women living in urban area, having high school degree, higher household expenditure, physical activity and greater neuroticism trait, and having insurance (Figure 2, Table 4). The association was also strongest for education, with a 2.55 higher odds (95% CI: 1.81-3.59) of being aware of mammography with graduating compared to not graduating high school.


Determinants of Pap smear participation

We assessed factors associated with participation in ever having a Pap smear in lifetime (Table 3). Unlike cancer screening awareness, no association was observed with living in urban area (Table S2). Women were more likely to have had a Pap smear if they had high school degree, higher household expenditure, insurance, two or more co-morbidities, and diabetes medication (Figure 2, Table 4). Odds of having had a Pap smear doubled in women who had diabetes medication compared to no medication (OR: 2.40, 95% CI: 1.07-5.39), although this analysis was limited by the small number of participants.


Determinants of BSE practice

A number of factors were associated with ever performing BSE in the past year in univariable analyses (Table 3). Among those factors, those associated with higher odds of practicing BSE were Javanese ethnicity, urban residence, higher education and household expenditure, physical activity, higher agreeable trait, having insurance and social participation, and if any of their parents died from cancer (Figure 2, Table 4). Women were less likely to practice BSE if they were postmenopausal. A borderline association was shown for having menarche at age 14 or older (OR for BSE practice: 0.95, 95% CI: 0.90-1.00 compared to at younger ages).


Sensitivity analyses

For systolic and diastolic blood pressure categories, we repeated our multivariable models only including either of the two blood pressure measures to avoid collinearity, and excluded those receiving hypertension medications (N=358). These analyses did not alter our results. Results were also similar when we used BSE at least twice (N=723) instead of once a year (N=796) to define women who practiced BSE as the outcome, but this did not alter our findings (data not shown).



Our study identified predisposing, enabling, and need factors associated with awareness of cancer screening and participation in Indonesian women. Strongest associations were observed for socio-economic determinants, particularly higher education, household expenditure, and ownership of health insurance, which were associated with higher awareness of Pap smear and mammography, and higher odds of participating in Pap smear and BSE. A similar positive association was observed for social activity participation and awareness of Pap smear and BSE practice, whereas distance to nearest health centres was inversely associated with awareness of Pap smear. Our findings also uncovered associations between personality traits and pap smear awareness and participation and BSE practice which remained when taking into account other determinants.


Most developed nations have guidelines for screening and early detection of breast and cervical cancers. The guidelines describe target population, methods and interval of screening, as well as recommended interventions according to the screening results.[22–24] It is estimated that the implementation of screening programmes has successfully decreased the incidence of cervical cancer up to 80% in developed nations.[25] Despite the increasing cancer burden, most of LMICs are yet to have national guidelines for screening and early detection of breast and cervical cancers.[5,26] In other LMICs in which national cancer screening programmes have been introduced, participation rates remain a challenge, for instance cancer screening in the Middle East and North Africa (2-70%).[27] In Sub-Saharan Africa, only less than 5% of women at risk are estimated to have been screened for cervical cancer.[28,29] Population-based cervical cancer screening programmes have been introduced for more than 10 years in India, however, participation rates are also relatively low.[30,31] The Indonesian Ministry of Health has recently released new regulations for management of cervical and breast cancer (PERMENKES RI No.34/2015).[32] Approximately 34.5 million Indonesian women of the target group are expected to participate in this breast and cervical cancer screening program.[32] According to the government program, health promotion is conducted through public events, media, through religious communities and other societies, whereas preventive measures include mass screening, mainly for cervical cancer using visual inspection with acetic acid and are organised as public events. Women within target age groups may also request for early detection at healthcare facilities. However, no formal invitation for screening is sent to individuals, and there is a lack of clear guidelines regarding use of mammography. In 2015, only 904,099 (4.94%) women had completed screening and early detection for breast and cervical cancer, a similar figure as observed in this study. It is planned that the coverage is targeted to reach 50% as of 2019.[32]


Most women in developing countries seek medical care after they develop symptoms. For instance, more than 70% of cervical cancer patients in developing countries came to a hospital when cancer has already infiltrated the parametrium.[33,34] A population based-study conducted in Indonesia demonstrated that implementation of small-scale cervical cancer screening project can reach 24% coverage of total females in the targeted group, indicating relatively low coverage in the population base although the project had implemented mobile screening service to attain hard-to-reach urban areas.[35] We did not find any report evaluating breast cancer screening program using either breast self-examination, clinical breast examination, mammography or sonography in Indonesia. In addition, breast self-examination (BSE) is the most common practice for screening in Indonesia albeit considered lacking in efficacy.[36] In fact, mammography and sonography were not generally accessible and the national universal health insurance only covers such procedures in particular health facilities.


Only a few studies have addressed the role of mental health and personality in cancer screening awareness and participation,[37,38] especially in LMICs. In our study, a higher CES-D score was associated with low awareness of Pap smear, but higher BSE practicing. Stress and depression, which are generally more common in low SES[39], have also been associated with health related behaviour.[38] Since knowledge can be overridden by cultural and personal belief as well as debilitating depression, community support might be required to achieve the desirable level of awareness and participation in cancer screening especially in women with psychological comorbidities. We found associations between higher agreeableness and higher awareness of Pap smear and BSE practice, whereas higher neuroticism was linked with higher cancer screening awareness. Using a similar tool, two studies also reported associations between personality traits and cancer, with higher conscientiousness associated with higher participation in bowel and prostate cancer screenings [40,41]. The positive correlation between conscientiousness and cancer screening awareness did not reach statistical significance in this study. However, our findings point towards the role of personality traits, which may indicate the usefulness of tailored approaches in encouraging cancer screening awareness and participation in women.


We demonstrated that existing comorbidities were associated with awareness of and participation in screening of breast and cervical cancers. Limited availability of mammography might reduce participation of screening in women who are aware of breast cancer risk. In several studies, some determinants including household socio-economic status, ethnicities[42], rural residence, country health expenditure, and healthcare access[42] are associated with participation in breast and cervical cancer screening.[43] Our study presents the current cancer screening practices as well as determinants associated with low participation among Indonesian women. Multiple strategies of health policy are required to improve public cancer awareness and healthcare infrastructures to enhance Pap smear participation and breast clinical consultation as well as examination of symptomatic patients. Interventions may also be needed to advance skills of primary care caregivers for detection of breast and cervical cancer, education, and prompt referral, strengthen capacity for diagnostic imaging, cytology, and histopathology, and multimodal breast and cervical cancer treatment. Moreover, a nationwide cancer registry needs to be well established to map the cancer incidence and provide a basis for screening coordination and evaluation.


The main strength of this study lies in the large number of participants, who lived in areas covering 83% of the population in Indonesia. We were able to account for community clustering and various potential determinants of cancer screening awareness and participation in women. A limitation of this study was that cancer screening awareness only relied on dichotomous responses of questionnaires, without any additional responses allowing for cross-validation and potentially more qualitative work. Additionally, most information was self-reported. However, any misclassification is likely to have been non-differential. We were unable to assess participation in mammography due to the small numbers of study participants. We did not use specific cancer questionnaires to measure awareness such as the UK Cancer Awareness Measure [1], since the survey was not originally designed for this particular purpose. Development and validation of a cancer awareness measurement tool which is socioculturally relevant to the Indonesian population is therefore necessary to refine our understanding of the variability in awareness of cancer screening in Indonesia. Additionally, we were only able to capture mammography use in the past year due to the available data, and this may be a subject of further investigations. Spurious correlations may be of concern when performing multiple comparisons as shown in our study. However, we planned our analyses based on a priori models and our results are explicable by potential socioeconomic and health-related mechanisms and confirmed by findings from other studies. Therefore, the observed association is unlikely to be spurious [44], although a discrepancy with the strength of the true association is possible due to the lack of participants. Women who responded to screening questionnaires may have different characteristics compared to all women aged 40 and older. Furthermore, although IFLS5 covered most respondents from the original IFLS1 survey, there have been rapid demographic changes in Indonesia such as an increased proportion of older populations [4]. These patterns may reduce the generalisability of the findings. However, demographic transition is well-reflected in the study population, such as the greater number of women living in urban areas in IFLS5 as opposed to the majority living in rural areas in 1993 [4]. Furthermore, this cohort effect is unlikely to affect the internal validity of the results. Finally, our analyses were cross-sectional and only imply associations. Untangling causal associations is necessary to identify key modifiable factors which improve or worsen awareness of and participation in cancer screening.



We identified a number of factors associated with cervical and breast cancer screening awareness and practice in Indonesia. Improvement of enabling factors such as access to healthcare and social participation may help enhance cancer screening in low-resource settings, particularly among subgroups of women who are socio-economically susceptible to low awareness of cancer screening. The different associations observed with different personality traits support the potential benefit of employing a range of strategies to promote cancer awareness and participation in Indonesia and potentially other LMICs without long-established cancer screening programmes.



The authors would like to thank Mr Eric Hookom for reviewing and commenting on the manuscript draft.



Ethics approval and consent

The research has been performed in accordance with the Declaration of Helsinki. The IFLS surveys and their procedures were reviewed and approved by the following ethics committees: IRBs (Institutional Review Boards) in the United States (at RAND) and in Indonesia at the Universitas Gadjah Mada (UGM) for IFLS5. Informed consent was obtained from all participants.


Consent to publish

All authors have provided their consent for publication of the manuscript.


Availability of data and materials

The dataset is publicly available at the RAND Corporation’s website (


Competing interest

All authors declare no competing interests.



WW is employed by grants from the UK Medical Research Council [MC_UU_12019/2] and [MC_UU_12019/4]. GT is funded by the UK Medical Research Council [G1001375/1], UK Economic & Social Research Council [ES/L001772/1], and EU Horizon 2020 [668648]. Funding for IFLS5 was provided by the National Institute on Aging (NIA), grant 2R01 AG026676-05, the National Institute for Child Health and Human Development (NICHD), grant 2R01 HD050764-05A1 and grants from the World Bank, Indonesia and GRM International, Australia from DFAT, the Department of Foreign Affairs and Trade, Government of Australia.


Authors’ contribution

SLA and WW conceptualised the study. SLA, GT, JW and WW prepared the data used for the analysis. SLA and WW performed the analysis with critical feedback from GT and MVH. All authors interpreted the results of the analysis. SLA wrote the first draft. All authors reviewed and edited the draft and agreed on the final version of the manuscript.




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Table 1. Characteristics of study participants (N=5,397)Potential determinants

N (%)
Age 40-60 4098 (75.93)
≥60 1299 (24.07)
Ethnicity Not Javanese 2900 (43.73)
Javanese 2497 (46.27)
Residence Rural 2339 (43.34)
Urban 3058 (56.66)
Marital status Not married 1423 (26.37)
Married 3974 (73.63)
Education Less than high school 3534 (65.48)
High school 1529 (28.33)
Higher education 334 (6.19)
Monthly household expenditure Tertile 1-2 3561 (65.98)
Tertile 3 1836 (34.02)
Tobacco smoking Never 5157 (95.55)
Former 63 (1.17)
Ever 177 (3.28)
Physical activity Sedentary 1627 (30.15)
Lightly active 1793 (33.22)
Moderately active 1460 (27.05)
Vigorously active 517 (9.58)
Openness <4 4715 (87.36)
≥4 682 (12.64)
Conscientiousness <4 4690 (86.90)
≥4 707 (13.10)
Extroversion <4 3203 (59.35)
≥4 2194 (40.65)
 Agreeableness <4 1771 (32.81)
≥4 3626 (67.19)
Neuroticism <4 3191 (59.13)
≥4 2206 (40.87)
Insured No 2754 (51.03)
Yes 2643 (48.97)
Travel time <10 min 4503 (83.44)
≥10 min 894 (16.56)
Participating in social activities No 806 (14.93)
Yes 4591 (85.07)
Menopausal status Premenopausal 2300 (42.61)
Postmenopausal 3097 (57.38)
Age at menarche <14 2133(39.52)
≥ 14 3264 (60.48)
Co-morbidity score 0 1476 (27.35)
1 1506 (27.90)
2 1162 (21.53)
3 and more 1253 (23.22)
Parent died from cancer No 5264 (97.54)
Yes 133 (2.46)
Diabetes drug No 5269 (97.63)
Yes 128 (2.37)
Hypertension drug No 5039 (93.37)
Yes 358 (6.63)
Lipid-lowering drug No 5288 (97.98)
Yes 109 (2.02)
BMI < 25kg/m2 2879 (53.34)
≥ 25kg/m2 2518 (46.66)
Systolic blood pressure <140 mmHg 3087 (57.20)
≥ 140 mmHg 2310 (42.80)
Diastolic blood pressure <90 mmHg 3903 (72.32)
≥ 90 mmHg 1494 (27.68)
CES-D <8 5097 (94.44)
≥ 8 300 (5.66)

Table 2. Univariable associations of potential determinants with cancer screening awareness among women 40 years and older without known history of any cancer


Potential determinants Aware of Pap smear (N=5397) Aware of mammography (N=5397)
N (%) OR (95% CI) N (%) OR (95% CI)
Age 40-60 919 (22.42) Ref 220 (5.37) Ref
≥60 139 (10.70) 0.32 (0.25-0.40) 31 (2.39) 0.44 (0.43-0.45)
Ethnicity Not Javanese 478 (16.48) Ref 146 (5.03) Ref
Javanese 580 (23.23) 1.49 (1.18-1.88) 105 (4.21) 0.85 (0.59-1.22)
Residence Rural 166 (7.09) Ref 54 (2.31) Ref
Urban 892 (29.16) 7.74 (5.77-10.37) 197 (6.44) 3.57 (2.34-5.44)
Marital status Not married 193 (13.56) Ref 43 (3.02) Ref
Married 865 (21.77) 2.14 (1.74-2.62) 208 (5.23) 1.93 (1.34-2.75)
Education Less than high school 223 (5.31) Ref 70 (1.98) Ref
High school or higher education 835 (44.82) 14.01 (11.44-17.16) 181 (9.72) 5.08 (3.75-6.90)
Monthly household expenditure Tertile 1-2 446 (12.52) Ref 95 (2.67) Ref
Tertile 3 612 (33.33) 3.66 (3.08-4.35) 156 (8.50) 3.29 (2.49-4.33)
Tobacco smoking Never 1019 (19.76) Ref 241 (4.67) Ref
Ever 39 (16.25) 0.78 (0.50-1.21) 10 (4.17) 0.87 (0.43-1.76)
Physical activity Active 268 (16.47) Ref 51 (3.13) Ref
Sedentary 790 (20.95) 1.49 (1.23-1.80) 200 (5.31) 1.85 (1.32-2.60)
Openness <4 957 (20.30) Ref 226 (4.79) Ref
≥4 101 (14.81) 0.77 (0.59-1.00) 25 (3.67) 0.94 (0.62-1.44)
Conscientiousness <4 929 (19.81) Ref 218 (4.64) Ref
≥4 129 (18.25) 1.00 (0.78-1.28) 33 (4.67) 1.02 (0.69-1.53)
Extroversion <4 688 (21.48) Ref 167 (5.21) Ref
≥4 370 (16.86) 0.75 (0.63-0.88) 84 (3.83) 0.76 (0.57-1.00)
 Agreeableness <4 199 (11.24) Ref 50 (2.82) Ref
≥4 859 (23.69) 2.53 (2.08-3.08) 201 (5.54) 1.91 (1.37-2.64)
Neuroticism <4 528 (16.55) Ref 111 (3.48) Ref
≥4 530 (24.03) 1.65 (1.40-1.95) 140 (6.35) 1.88 (1.87-1.89)
Insured No 340 (12.35) Ref 82 (2.98) Ref
Yes 718 (27.17) 2.52 (2.11-3.01) 169 (6.39) 2.10 (1.57-2.82)
Travel time <10 min 952 (21.14) Ref 232 (5.15) Ref
≥10 min 106 (11.86) 0.48 (0.37-0.62) 19 (2.12) 0.42 (0.26-0.70)
Participating in social activities No 65 (8.06) Ref 20 (2.48) Ref
Yes 993 (21.63) 3.27 (2.39-4.47) 231 (5.03) 2.25 (1.35-3.75)
Menopausal status Premenopausal 641 (27.87) Ref 160 (6.96) Ref
Postmenopausal 417 (13.46) 0.36 (0.30-0.42) 91 (2.94) 0.41 (0.31-0.54)
Age at menarche <14 472 (22.13) Ref 115 (5.39) Ref
≥ 14 586 (17.95) 0.77 (0.65-0.91) 136 (4.17) 0.73 (0.56-0.95)
Co-morbidity score 0-1 692 (23.21) Ref 179 (6.00) Ref
≥ 2 366 (15.15) 0.53 (0.45-0.63) 72 (2.98) 0.54 (0.40-0.72)
Parent died from cancer No 1009 (19.17) Ref 238 (4.52) Ref
Yes 49 (36.84) 2.58 (1.62-4.11) 13 (9.77) 2.25 (1.15-4.41)
Diabetes drug No 1021 (19.38) Ref 244 (4.63) Ref
Yes 37 (28.91) 1.31 (0.80-2.13) 7 (5.47) 1.10 (0.47-2.55)
Hypertension drug No 971 (19.27) Ref 233 (4.62) Ref
Yes 87 (24.30) 1.07 (0.78-1.47) 18 (5.03) 0.99 (0.57-1.70)
Lipid-lowering drug No 1015 (19.19) Ref 247 (4.67) Ref
Yes 43 (39.45) 2.01 (1.21-3.31) 4 (3.67) 0.70 (0.24-2.02)
BMI < 25kg/m2 457 (15.87) Ref 121 (4.20) Ref
≥ 25kg/m2 601 (23.87) 1.49 (1.26-1.76) 130 (5.12) 1.12 (0.85-1.48)
Systolic blood pressure <140 mmHg 725 (23.49) Ref 165 (5.34) Ref
≥ 140 mmHg 333 (14.42) 0.48 (0.41-0.58) 86 (3.72) 0.67 (0.50-0.90)
Diastolic blood pressure <90 mmHg 801 (20.52) Ref 191 (4.89) Ref
≥ 90 mmHg 257 (17.20) 0.77 (0.64-0.94) 60 (4.02) 0.80 (0.59-1.12)
CES-D <8 820 (21.42) Ref 190 (4.96) Ref
≥ 8 238 (15.18) 0.73 (0.60-0.88) 61 (3.89) 0.86 (0.63-1.17)



Table 3. Univariable associations of potential determinants with cancer screening practice among women 40 years and older without known history of any cancer

Potential determinants Ever Pap smear (N=1058) Ever BSE (N=5397)
N (%) OR (95 CI) N (%) OR (95 CI)
Age 40-60 254 (27.64) Ref 538 (13.13) Ref
≥60 43 (30.94) 1.06 (0.55-2.03) 67 (5.16) 0.33 (0.25-0.43)
Ethnicity Not Javanese 133 (27.82) Ref 302 (10.41) Ref
Javanese 164 (28.28) 0.58 (0.72-1.33) 303 (12.13) 1.20 (0.96-1.51)
Residence Rural 50 (30.12) Ref 129 (5.52) Ref
Urban 247 (27.69) 0.85 (0.56-1.28) 476 (15.56) 3.54 (2.74-4.58)
Marital status Not married 52 (26.94) Ref 99 (6.96) Ref
Married 245 (28.32) 1.10 (0.76-1.60) 506 (12.73) 2.06 (1.62-2.61)
Education Less than high school 48 (21.52) Ref 141 (3.99) Ref
High school or higher education 249 (29.82) 1.70 (1.16-2.50) 464 (24.91) 8.24 (6.67-10.18)
Monthly household expenditure Tertile 1-2 92 (20.63) Ref 265 (7.44) 1.70 (1.54-1.88)
Tertile 3 205 (33.50) 2.08 (2.07-2.09) 340 (18.52)
Tobacco smoking Never 286 (28.07) Ref 580 (11.25) Ref
Ever 11 (28.21) 1.06 (0.50-2.26) 25 (10.42) 0.95 (0.60-1.51)
Physical activity Active 72 (26.87) Ref 157 (9.64) Ref
Sedentary 225 (28.48) 1.12 (0.80-1.56) 448 (11.88) 1.30 (1.06-1.60)
Openness <4 272 (28.42) Ref 544 (11.54) Ref
≥4 25 (24.75) 0.89 (0.55-1.45) 61 (8.94) 0.79 (0.59-1.07)
Conscientiousness <4 264 (28.42) Ref 531 (11.32) Ref
≥4 33 (25.58) 0.83 (0.53-1.29) 74 (10.47) 0.95 (0.72-1.25)
Extroversion <4 199 (28.92) Ref 400 (12.49) Ref
≥4 98 (26.49) 0.96 (0.72-1.30) 205 (9.34) 0.74 (0.61-0.90)
 Agreeableness <4 59 (29.65) Ref 107 (6.04) Ref
≥4 238 (27.71) 0.97 (0.69-1.39) 498 (13.73) 2.48 (1.98-3.11)
Neuroticism <4 135 (25.57) Ref 294 (9.21) Ref
≥4 162 (20.57) 1.31 (0.99-1.74) 311 (14.09 1.61 (1.34-1.93)
Insured No 76 (22.35) Ref 217 (7.87) Ref
Yes 221 (30.78) 1.70 (1.23-2.37) 388 (14.68) 1.97 (1.63-2.39)
Travel time <10 min 275 (28.87) Ref 545 (12.10) Ref
≥10 min 22 (20.75) 0.61 (0.36-1.02) 60 (6.71) 0.52 (0.39-0.70)
Participating in social activities No 13 (20.00) Ref 38 (4.71) Ref
Yes 284 (28.60) 1.56 (0.81-3.00) 567 (12.35) 2.85 (1.99-4.08)
Menopausal status Premenopausal 163 (25.42) Ref 403 (17.52) Ref
Postmenopausal 134 (32.13) 1.38 (1.04-1.85) 202 (6.52) 0.32 (0.26-0.38)
Age at menarche <14 138 (29.24) Ref 274 (12.85) Ref
≥ 14 159 (27.13) 0.87 (0.65-1.15) 331 (10.14) 0.80 (0.66-0.96)
Co-morbidity score 0-1 73 (25.29) Ref 412 (13.82) Ref
≥ 2 58 (33.33) 1.58 (1.18-2.12) 193 (7.99) 0.52 (0.43-0.63)
Parent died from cancer No 281 (27.85) Ref 573 (10.89) Ref
Yes 16 (32.65) 1.30 (0.68-2.50) 32 (24.06) 2.42 (1.54-3.83)
Diabetes drug No 280 (27.42) Ref 589 (11.18) Ref
Yes 17 (45.95) 0.96 (0.54-1.70) 16 (12.50) 0.96 (0.54-1.70)
Hypertension drug No 266 (27.39) Ref 551(10.93) Ref
Yes 31 (35.63) 2.50 (1.22-5.16) 54 (15.08) 1.32 (0.94-1.83)
Lipid-lowering drug No 277 (27.29) Ref 585 (11.06) Ref
Yes 20 (46.51) 1.60 (0.81-2.63) 20 (18.35) 1.46 (0.85-2.52)
BMI < 25kg/m2 119 (26.04) Ref 264 (9.17) Ref
≥ 25kg/m2 178 (29.62) 1.18 (0.89-1.58) 341 (13.54) 1.44 (1.20-1.74)
Systolic blood pressure <140 mmHg 200 (27.59) Ref 396 (12.83) Ref
≥ 140 mmHg 97 (29.13) 1.10 (0.81-1.49) 209 (9.05) 0.67 (0.55-0.81)
Diastolic blood pressure <90 mmHg 224 (27.97) Ref 447 (11.45) Ref
≥ 90 mmHg 73 (28.40) 1.02 (0.73-1.42) 158 (10.58) 0.92 (0.75-1.14)
CES-D <8 235 (28.66) Ref 439 (11.47) Ref
≥ 8 62 (26.05) 0.91 (0.65-1.28) 166 (10.59) 0.99 (0.81-1.22)



Table 4. Multivariable associations of potential determinants with cancer screening awareness among women 40 years and older without known history of any cancer.

Potential determinants1   OR (95% CI)  
Aware of pap smear Aware of mammography Ever pap smear Ever BSE
Age 0.77 (0.56-1.07) 1.13 (0.65-1.95) 0.77 (0.44-1.35) 0.83 (0.58-1.20)
Javanese 1.92 (1.54-2.40)* 0.83 (0.60-1.14) 1.08 (0.78-1.51) 1.27 (1.04-1.55)*
Urban residence 4.28 (3.17-5.50)* 2.00 (1.35-2.95)* 0.72 (0.46-1.13) 1.91 (1.50-2.43)*
Married 1.07 (0.84-1.37) 1.16 (0.79-1.72) 1.15 (0.75-1.75) 1.10 (0.85-1.44)
High school or higher education 7.22 (5.84-8.94)* 2.55 (1.81-3.59)* 1.60 (1.03-2.49)* 4.25 (3.38-5.34)*
Monthly household expenditure – higher tertile 2.29 (1.90-2.77)* 2.24 (1.67-3.02)* 1.94 (1.39-2.72)* 1.70 (1.39-2.06)*
Ever smokers 0.89 (0.54-1.46) 1.00 (0.49-2.05) 0.98 (0.43-2.23) 1.11 (0.69-1.82)
Physically active 1.51 (1.23-1.86)* 1.76 (1.25-2.48)* 1.23 (0.85-1.76) 1.22 (0.98-1.51)
Openness ≥4 0.87 (0.64-1.18) 0.87 (0.54-1.41) 0.90 (0.51-1.56) 0.93 (0.68-1.29)
Conscientiousness ≥4 1.07 (0.80-1.43) 1.12 (0.72-1.72) 0.83 (0.51-1.37) 0.83 (0.70-1.27)
Extroversion ≥4 0.86 (0.71-1.05) 0.86 (0.63-1.17) 0.98 (0.71-1.37) 0.83 (0.68-1.27)
Agreeableness ≥4 1.61 (1.29-2.01)* 1.26 (0.87-1.80) 0.74 (0.50-1.37) 1.59 (1.25-2.03)*
Neuroticism ≥4 1.22 (1.01-1.48)* 1.47 (1.10-1.96)* 1.35 (0..98-1.84) 1.19 (0.98-1.44)
Have insurance 2.04 (1.68-2.47)* 1.64 (1.22-2.22)* 1.59 (1.12-2.25)* 1.43 (1.18-1.75)*
Travel ≥10 min to health service 0.72 (0.54-0.96)* 0.54 (0.90-2.52) 0.56 (0.32-0.98) 0.77 (0.57-1.05)
Participating in social activities 2.05 (1.46-2.88)* 1.51 (0.90-2.52) 1.32 (0.66-2.66) 1.91 (1.32-2.75)*
Postmenopausal 0.75 (0.60-0.94)* 0.74 (0.52-1.06) 1.44 (0.98-2.12) 0.57 (0.45-0.73)*
Age at menarche ≥14 0.98 (0.93-1.02) 0.95 (0.88-1.02) 0.89 (0.81-0.98) 0.95 (0.90-1.00)*
Co-morbidity score ≥2 1.19 (0.92-1.53) 0.67 (0.44-1.02) 1.52 (1.00-2.32)* 1.03 (0.79-1.34)
Parent died from cancer 1.43 (0.86-2.38) 1.52 (0.76-3.02) 1.31 (0.64-2.68) 1.61 (1.01-2.57)*
Diabetes drug 1.44 (0.84-2.48) 1.55 (0.64-3.74) 2.40 (1.07-5.39)* 0.99 (0.54-1.82)
Hypertension drug 1.18 (0.81-1.72) 1.10 (0.61-2.00) 1.08 (0.60-1.95) 1.45 (0.99-2.11)
Lipid-lowering drug 1.69 (0.97-2.93) 0.55 (0.18-1.66) 1.92 (0.91-4.04) 1.21 (0.67-2.15)
BMI ≥ 25kg/m2 1.16 (0.96-1.39) 0.86 (0.65-1.15) 1.09 (0.79-1.49) 1.06 (0.87-1.28)
Systolic blood pressure ≥ 140 mmHg 0.63 (0.48-0.81)* 1.09 (0.73-1.63) 0.92 (0.59-1.42) 1.02 (0.78-1.33)
Diastolic blood pressure ≥ 90 mmHg 1.19 (0.91-1.56) 0.94 (0.62-1.42) 1.03 (0.65-1.63) 1.03 (0.78-1.36)
CES-D ≥8 0.66 (0.53-0.83)* 0.84 (0.60-1.18) 0.85 (0.57-1.25) 1.02 (0.82-1.27)

All potential determinants were included in the multivariable model.

1For categorical factors, odds ratios (ORs) were shown for categories displayed in the left-hand column in comparison with the remaining categories as the reference (see Table 2-3)





Figure Legends

Figure 1. Potential determinants of cancer screening awareness and participation in IFLS5 based on the Anderson model of health behaviour.

Figure 2. Independent predictors of cancer screening awareness and participation in multivariable analyses. All potential determinants were included in the multivariable model. BP=blood pressure. Full results are presented in Table S2, Supplementary Information.


International Conference on Diabetes and Metabolism 2017

PILAR Research 0 Comments

Here is an article from Dian C. Sulistyoningrum from the Department of Nutrition and Health Faculty of Medicine Universitas Gadjah Mada. Dian received a travel grant of $1,000 from the Korean Diabetes Association for submitting an outstanding abstract, and this in turn gave her the opportunity to attend the event they hosted in South Korea. 

At the end of September this year, I was invited to attend the International Congress of Diabetes and Metabolism 2017 which was held in  to present my abstract entitled: Associations of serum leptin with vitamin D in American adults: The third National Health and Nutrition Survey. Along with the abstract submission, an application for a travel grant was done and I was fortunate to have received one.

My abstract was received as a poster and the viewing time was about 15 minutes for the two-day event. There were a handful of attendees, and despite the numbers not being as high as I wanted it to be, there was quite an interest on the oral presentation and it ended with a question or comment from the chairman or audience. In addition, I also did an oral presentation of a collaborative study which I was also involved in, in lieu of a colleague who wasn’t able to attend the conference.

In addition to the two-day congress, I joined a course on Diabetes Education in Asia. We learned about diabetes epidemiology and management in Asia from an internist, dietician, and nurses. The course was complimentary for the congress attendants. It was attended by healthcare professionals from various countries in Asia including: Korea, Mongolia, Cambodia, The Philippines, China and Indonesia.

My group for the Comprehensive Education Course for Asian Diabetes Educators

The overall event went quite well. There were many international speakers who shared their research. I would recommend young scientists doing research relating to diabetes to attend this conference. In addition, Seoul, South Korea is a beautiful city. Rich in culture, beautiful in landscape and delicious food.


Preparing for an Oral Presentation on your Research Paper

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Research papers can take months or years to move from the idea generation all the way to completion. Despite the long and task intensiveness of preparing a research paper, many researchers still find the oral presentations in conferences which could last from five minutes to an hour the most daunting.

Many researchers get nervous when asked to do a presentation on their findings. With so much information gathered over months or years, it is important to only deliver the most important information that is relevant to the audience. Therefore, it is handy to have a process in place when preparing for a presentation so the delivery can become easier.

Please see below for some tips on how to prepare a successful presentation.

  1. Find the purpose of presenting.

It is important to find out the main reason why you were asked to deliver the presentation. Find out if they want you to talk about a method or approach, or if it is only about the findings. Understanding the scope of what they want from you is important before crafting a presentation. Without a scope, you might be confused on finding out which parts of your research is important to the audience.

  1. Ask who the audience will be.

Whether you are presenting to your own department or to a vast audience of doctors, it is important to find out who your audience will be before drafting a presentation. It is good to know how much prior knowledge in your field your audience has. Are they familiar with the recent research in the area you will be presenting about? How much technical knowledge do they have? Will technical terms need to be defined?

  1. Creating the structure.

Normally when you get asked to do a presentation, the timing will be defined already. Once you understand how much time you are given, you can start structuring your presentation around it. For example, if you were given 20 minutes to present, you need to start thinking how much time you want for the introduction, a brief description about your research, the body, conclusion and allocated time for questions and answers. It is important not to exceed your allotted time or even worse, have no time to finish your presentation. Therefore, it is important to be selective with the information you plan on delivering to your audience which would be gained based on the scope the organizers have given you.

  1. Making data presentations visually appealing.

When presenting data, some presenters bombard the audience with so many findings that the information delivered to the audience gets overwhelming. This is when it is important for the presenter to figure out which data is most relevant and appealing to the audience. It is better the audience remembers a key takeaway from your presentation than nothing at all. Thus it is important to keep the charts or graphs simple and visually appealing. Aside from visually appealing charts and graphs, it is also important that the data is ethically presented and could not be easily misinterpreted.

  1. Handling questions.

For new researchers, being asked questions about their research can be intimidating. However, it is good to take note that a good presentation naturally gets good discussion and interesting questions. To prepare for this, it is good to assume what types of questions your audience might be asking. Is your method or approach uncommon? Could your findings be a little controversial? What are the practical applications to your research, if any?

When asked a question, listen attentively to the person asking the question. If you do not understand, try to repeat the question and paraphrase it in your own words if you are not sure you understand it correctly.

If you cannot answer the question, you can offer the audience to answer, or tell the person asking the question that you do not have an answer for that question in this given time, but happy to get back to them when you have an answer.

To sum this up, you should feel great about all the hard work you have gone through if you get invited to present about your research paper. Presenting your research paper is also a great opportunity to learn from others, and share information that you find very important. So enjoy it while you are at it!



Empowering Research for Better Healthcare (EMBRACE) Workshop

PILAR Research 0 Comments

PILAR Research and Education, in collaboration with the Clinical Epidemiology Department at University of the Philippines Manila organized the Empowering Research for Better Healthcare (EMBRACE) Workshop last August 10, 2017. This event took place in Hotel Kimberly, Manila, Philippines.

The workshop gave an overview of how modern day health research and data analysis can provide evidence to ensure best practice of healthcare. The workshop combined fundamentals of research data analysis in non-communicable disease, an overview of modern methodological techniques, as well as in-depth discussions about practical issues and feasibility of conducting research in the Philippines.

There were over 70 attendees in the workshop, with a mix of lectures, interactive sessions and practical demonstrations of statistical analysis with discussions. Some participants were also able to have one-on-one discussions with our key speakers to discuss their own research projects.

The workshop was opened by Dr. Marissa M. Alejandria from the Department of Clinical Epidemiology, College of Medicine and Dr. Johnathan Watkins, Director of PILAR Research & Education. The workshop proper started with Dr. Carlo Irwin A. Panelo giving a lecture on Trends in non-communicable disease in the Philippines and the role of research. Dr. Panelo is an Associate Professor at the Department of Clinical Epidemiology of the University of the Philippines College of Medicine.

One of the guest speakers from Loyola University, US, Professor Timothy O'Brien, followed right after and gave an Overview of data analysis. His second presentation that morning was on Design and analysis of experimental research. Professor Timothy is a Graduate Program Director (Statistics) from Loyola University, Chicago, USA.

Dr. Paul Ferdinand M. Reganit, a Clinical Associate Professor of Medicine, Section of Cardiology from the UP-Philippine General Hospital discussed the Design and analysis of observational research: experience from a community-based cohort study in the Philippines. Dr. Watkins ended the last session in the morning and gave a lecture on Projecting the rates of chronic disease outcomes.

The afternoon sessions were a little more hands on with the attendees required to stay in their designated groups for the small group activity on Planning a health research analysis. Attendees were spread out so they can mingle and learn from other attendees from other industries.

After the interactive group activities, Professor Timothy presented on Dealing with complex data: modern practice and practical considerations. That was the last presentation before the final closing. Overall, the event was very successful. Pilar Research & Education is looking forward to collaborating with the Department of Clinical Epidemiology at University of the Philippines Manila for more events and collaboration.

How to Apply for Research Funding

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Getting funded for your research ideas is not easy. Some researchers have to abandon their projects because they have difficulties finding additional funding to carry on their research. Some researchers assume that searches for funding are something that everyone knows about, while the reality is that preparing a successful grant application is a skill that everyone can learn.

Many research grants are awarded on a competitive basis, but having the most relevant research idea is not the only requirement to getting a better chance of having your project funded. Scientists and academics who have big ideas which can potentially help the health and medical fields should not immediately let go of their idea because their grant proposals got rejected.

This article will cover some basic strategies on how you can get your research idea funded.

  1. Learn about grant writing.

Before applying for grants, it would be helpful to acquaint yourself with grant writing. Get samples of application drafts from your fellow researchers, or research for samples online. Even if you do not have a research project in mind, it is important to start researching early so you can get funding grants when they are available.

  1. Decide what you need the money for.

When asking for a grant, you need to know the scope of your project so you understand where you will need the funding for. Will it be to help pay for the travel for the archival research or fieldwork, will it be to cover for the time you need to do the project? Or will it be for the expenses to bring experts together to hold a workshop? If necessary, get quotes from suppliers to ensure your budget is reasonable.

  1. Read the eligibility criteria.

It is important to see if there is a match on what you want funded, and what types of research falls within the scope of what the funders are interested in. Reading the rules can save you application time if there is no match between what you are looking for and what the funder is looking to sponsor

  1. Talk to other researchers or university professionals who have experienced getting their grants approved.

Talking to other researchers can give you a better understanding on what they did to prepare themselves for their research idea to get granted. It would be even more helpful to get acquainted with researchers who have won funding from the organization you are applying to.

Aside from researchers, you can also approach university professionals; they can be senior advisors or professors who have experience in the field of getting funding. They can help you develop your project description, help you with budgets, and advice and assist with grant applications.

  1. Learn to answer the questions asked

One common mistake done by applicants is not answering the questions being asked by the funders. Most applications are given asset of guidelines such as limited word count, so it is important to focus on what is important about your proposed research and clearly lay out your proposal according to the required formats.

  1. If you’re unsure, ask.

It is highly recommendable to get in contact with the funders if you are unsure about something or have particular questions about the application.

  1. Ask other people outside the research circle to read your application.

The people who read your application are not necessarily technically as knowledgeable as you in the topic you are planning to research about. It would really help if you get friends, family or other people outside the academic circle to read and comment on your application. This way, your application would be more understandable by the panel who will be reviewing your application.

  1. Revise, revise, and revise.

Quality is better than quantity. You are better off working hard on one research proposal and keep revising it until you are ready to submit a high quality application rather than cutting yourself too thin and sending several different proposals with little preparation for each. Give yourself time to read, prepare, write and review your application before sending it through.

  1. Don’t let rejection stop you.

Do not let one rejection disappoint you. A lot of researchers had to apply many times before they received a grant. Being rejected does not mean that your idea is not worth pursuing. It may just mean that you may need a different approach, or it might mean that there was not enough funding available in the round you were in.

If you get rejected, it is very important to ask for feedback as to why you got rejected. Most likely you will be getting suggestions from the reviewers which can add value to your next application.

  1. Be proactive about finding more opportunities.

When you have a clearer understanding about what kind of funding you will be needing for your research idea, it would be easier to start matching it with the different grants available.

Collaboration is the Key to the Medtech Industry

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In any field, there is always that big question – how do we innovate?

Associations and organizations are always thinking of ways to enhance their outputs, whether it is through new technology or more research. One thing often overlooked in this matter is the role of fostering collaboration between the different stakeholders to create progressive change.

The medical technology in Denmark, for example, has a tradition of collaboration between universities, hospitals and the industry. Their philosophy on ‘We’re in this together’ – shows that no single participant comes up with a solution, but through collaboration, coaching and an open approach will the country be able to develop and thrive on innovation (MedTech Engine).

Tine Hartmann Nielsen, Life Sciences team leader at Invest in Denmark, stated that:

‘The reason why the Danish medtech industry is so quick to develop new and user-friendly solutions is linked to a close collaboration between universities, hospitals and the business community that facilitates a conducive business environment. The medical devices industry is sustained by innovation and product R&D, and companies in Denmark benefit from an array of well-established innovation centres distributed throughout the country,’.

Collaboration may seem challenging for some organizations. It can be difficult meeting eye-to-eye because of different organizational cultures and goals. It may almost seem like the counterparts are speaking different languages because of the different backgrounds and expertise. Thus the importance of building bridges at earlier stages with relevant parties.

Earlier Engagement to Improve Patient Outcomes

Expert Leslie Levin, the founder and chief scientific officer of the Excellence in Clinical Innovation and Technology Evaluation (EXCITE) at Canada’s innovation hub would argue that a more collaborative approach among medical device developers, payers and patients through the use of evidence would be the right approach to rapidly enhance the approach to innovation (The Australian Business Review).

Early engagement and socialization of technology are important to significantly improve patient outcomes. Payers for example, need to be involved in the early processes even before it has been approved by regulators. This way, the payers can help with the evaluation of the technology and help pull it into the health system.

Some start-ups and smaller medtech companies without the right funding in place are having difficulties partnering with larger companies to foster innovation in the digital health market. For academias, they are heavily reliant on the traditional model of asking for competitive grants to move innovation along (Medical Device Daily).

All these are slowly changing. There is more interest on the academic side and industry to do some sort of sponsored research or collaboration. For start-up companies and smaller medtech companies who are looking to partner with larger companies, they have to engage with large companies at earlier stages of their product development or conceptualization as most large companies aren’t looking to reinvent the wheel, but to find a company that could help them fill the gaps.

Finding Partners for Medtech Collaboration

As technology continues to evolve, companies will continuously search for innovative partners. Knowing when to approach an external expert is a challenging but crucial skill. The industry will constantly be evolving and with every new disruptive change, there may be a need for a new partner. Companies need to be creative in terms of partnerships instead of trying to do everything on their own.

Andy Fry of Team Consulting stated that most organizations approach partners when they have already made all their decisions and they have concluded their formulation. This has resulted in communication failures and would have been more feasible for all parties if the discussions have taken place during earlier stages (Drug Delivery Business News).

It is imperative to find a partner to understand your company’s end-goal, and also understand theirs to see if your goals are aligned.

Time Management for Researchers

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It may be easy to lose track of time while doing a research project because the time allocated to complete the project seems a long way off. It would appear like there is a lot of time to get the research finished and thesis completed, but in reality, the amount of time given is normally just enough to complete the required task. For any study to be well researched, it needs to be given the ample time it needs.

Time management is important for a research paper, or preparing applications for research funding. One of the main skills employers look for is how well one can demonstrate their ability to manage time and submit deliverables by a fixed deadline. Time management is important if you want to be successful in different walks of life.

People tend to start creating a time management “system” when they are already falling behind with their work, and start using tools to help them “catch-up”. This results in a lot of cramming and spending more time on a project because of disorganization. This habit may also result in lower quality of work.

It is important to have a system in place early in the academic year. Normally, a system would include a goal, a time tracking tool and a plan on how you would approach time management. And lastly, it normally includes a self-monitoring system. Self-monitoring includes a review on how well you are doing over a certain time, and how precise you are with tracking your deliverables based on the time you have allocated.

The purpose of this article is to share with 5 tips on how to manage your time so you can improve your academic and personal performance.

  1. List down all the things you need to do.

It would be hard to create a plan if you do not know how much work is required to complete the research. Plot down deliverables, deadlines and list them based on priority and learn to complete the most important tasks first.

  1. Give time for planning.

Once you have the list of things you need to do, you need to find out how much time is needed for each task. Some tasks may require you to visit different libraries, or speak to different people. It is important to plan so you can save time instead of running around back and forth to different places.

Some people give 30-minutes before they start their day to planning. Some people prefer doing this just before they go to bed so they are ready for the next day. Either way, planning is important on a daily and weekly basis.

  1. Create a schedule.

Some people like to look at their schedule in detail one day at a time, some weekly, some monthly. Do whatever you feel comfortable with but the importance is plotting it down into a calendar. Some people like to have a pin-up planner by their work desk, some prefer to have it on an e-calendar that could be accessed anytime, and some carry around a diary with their schedules on it.

A schedule is not only about plotting deliverables for the day, but also finding out how much time you will dedicate into completing the tasks. It gets easy to lose track of time if you have a short task and allocate the whole day for it. So plotting the amount of time you will need to complete it is also significant so you can dedicate the rest of the day into other things. This also allows you to figure out how much time you require per task.

  1. Avoid unnecessary distractions.

With social media usage on the rise, it is so easy to get distracted. Learn to not answer the phone just because it is ringing. Disconnect from instant messaging and don’t reply to e-mails just because it pops up. The time you have allocated should be used to focus on the task at hand.

Aside from your phone, it is also important to find a location that can help you focus better. Some people like to work or study in coffee shops, but some coffee shops can be very noisy and productivity can be low.

  1. Give buffer time and be flexible sometimes.

Every now and then you may come across an important task that is not related to your research paper and it needs to be attended to even if it clashes with your schedule. That is why it is important to give yourself buffer time for most tasks, just in case you get caught up doing something else, or you get stuck in traffic longer than expected, or your meeting with your lecturer ended up longer than you scheduled.

Allocate personal time or dead-time in your schedule so you can either spend this time building your network, socializing, working out or relaxing. If your schedule went out of hand, you may use this time to cover the time lost doing other tasks.

The important thing about time management is being able to measure the amount of time spent per task, and reflecting on how well you have done for the day or week. This way, deliverables can be constantly adjusted if you are falling behind schedule. Most importantly, it is necessary to have a balanced life for maximum productivity – so it is always better to work smarter than working harder!

Academic Networking for Researchers: Why is it important?

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Doing research on a topic only few can relate to may have its downside. Apart from the challenges in conducting scientific research or the difficulties in attaining research funding, there may be times you will feel isolated because you spend so much time working alone in a library or in a laboratory. Maybe sometimes, it gets easier to lose track and prioritize other things when you don’t have a support person or team. Or maybe you end up mingling in the same group of people that are helping you succeed in your research circle and don’t take time to expand out from that.

Being the best in academics is not the only way to create the best research material. Apart from performance and productivity, it is important to have good network relations to ensure better results in your studies and post research career.

Here are some tips which can help you enhance your academic life while completing a research:

  1. Start with your supervisor or research mentor.

Your supervisor may be the person who understands the goal of your research paper. They may have been in the industry longer than you and can link you with the right people in the field. You may be able to tap on your supervisor or research mentor’s existing network of contacts.

  1. Find a professional group.

There are many professional groups, and most of them already have an online presence where you can inquire about membership or just generally joining in to get information and exchange ideas. You can search through directories for local associations or groups where you can join and mingle with other like-minded researchers, or you can have a look online in platforms such as Linkedin or Meet-Up to discuss ideas and hear about frequently asked questions. The only downside to joining too many associations or groups is the overwhelming amount of information that you can get from them. So it is important to find the right groups or associations and vet them based on the members and the amount of dedication required from you to join.

  1. Attend seminars and conferences.

Face-to-face interactions are always one of the best and fastest ways to expand your network of contacts. Meeting people in person is also more memorable compared to speaking to someone over the phone or sending them an e-mail. Seminars and conferences may be minimal in one city, so opening up your options to travel to other seminars and conferences in other cities should also be in your agenda. Some of these meetings also provide funding to contribute towards your travel. Read our members’ stories about getting travel grants to attend conferences in South Korea and the UK.

  1. Talk to other professionals.

It’s important to network outside your academic circle. Not only will this give you the opportunity to pick the brains of individuals coming from the commercial and public sector, but it can also open our mind and possibly gain more connections which may be beneficial for your research study or your future career. Some areas in research, particularly medical research, require multidisciplinary approach to ensure the right approach to cure patients or prevent certain diseases.

  1. Request introductions to new contacts.

Now you have a web of sources while doing your research paper, don’t let the networking end there. Don’t be shy to ask your current contacts for introductions to other people. Most of the people you will meet have their own network of contacts. You need to work out your goals and see how each person can help you achieve these goals.

  1. Cold call.

Networking should not be limited only to the people you know and meet personally. If the topic you are researching on is highly technical, it may be hard for you to find enough references and sources in your own city or country, and you may find a good set of expertise from someone at the other side of the world. Don’t be shy to send a cold e-mail or pick up the phone and speak to someone in another part of the world – these might lead to opportunities to gain research experience in other countries.

These are only some advice which could help you build your network.  Just remember that when networking, you should always be prepared. First impressions last, and you wouldn’t want to give a mediocre first impression. Prepare a short spiel about yourself and the project you are working on. Also, find out what it is you are looking for. This way, it will be easier to create a conversation with someone, and you can create memorable encounters with people who may be your future partners or help you enhance your academic life while doing research.

Collaboration towards healthy ageing in Indonesia

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Professor Rebecca Hardy (MRC Unit for Lifelong Health and Ageing at University College London; LHA UCL) and Dr Wahyu Wulaningsih (LHA UCL, PILAR) visited Faculty of Medicine, Universitas Gadjah Mada between May 1-5, 2017 to explore collaboration opportunities which involve the UK and Indonesia. This visit was funded by the UCL Global Engagement Fund and Faculty of Medicine, Universitas Gadjah Mada (FoM UGM).

Rebecca Hardy is a Professor in Epidemiology and Medical Statistics with over 20 years of

experience investigating how individual characteristics and our environment since birth, childhood, through adulthood that influence healthy ageing in later life. During the visit, she delivered a lecture at FoM UGM, in which she spoke to Indonesian students, clinicians and researchers about her experience in studying the process of ageing. Healthy ageing, according to Hardy, is not just about how long you live, or being free from disease, but also about functioning well in old age. Being able to care for oneself and participate in social activities, for instance, are part of healthy ageing.

A life course approach to study healthy ageing

Ageing is a complex process and starts from birth. To find out how we can achieve healthy ageing in old age, scientists have started to evaluate what events could influence the decline of bodily function as we age. In addition, it is necessary to tease out when precisely these events adversely influence the ageing process. For some events, an occurrence in adulthood may be less hazardous on one’s health compared to if they occur in childhood. This ‘life course’ approach can help policymakers and practitioners identify subgroups such as specific age groups in the population who are more susceptible to experience adverse effects of ageing in old age, and therefore, can inform precision prevention.

Insight into challenges in research in Indonesia

Hardy and Wulaningsih visited Sardjito Hospital to engage with clinicians and discuss important issues in lifelong health, such as childhood growth and development. They also took part in a workshop on academic writing for publication organised by FoM UGM at Swiss Bel-In Hotel in Solo, where they exchanged expertise and experience on getting their research published with local researchers. The workshop is particularly aimed to boost research productivity of local researchers, by providing them allotted time and space to fully concentrate on writing for publication. In this workshop, PILAR had a chance to administer a questionnaire about the experience in conducting research in Indonesia to the selected group of researchers. When being asked about what challenges they experience in conducting research in Indonesia, four among the fourteen local researchers mentioned the lack of funding and infrastructure or equipment as the main challenge. Three researchers pointed out difficulties with bureaucracy as the main challenge, with one of them said, “Sometimes we had problems in the bureaucracy when we make multidisciplinary research”. Other issues mentioned included the incompleteness of local data, time limitation, and language.

How to overcome these challenges to do research?

We also asked these researchers how they think these challenges should be addressed. Responses vary and included suggestions for changes at the national level such as improving policies and bureaucracy, with one of them mentioned that, “The national health research and development agency should be more open to researchers from academic institutions”. The remaining responses focused on solutions at individual level, for instance better research plan, communication and collaboration. One researcher in particular advised to “be innovative and be creative”.

What’s next?

A lack of infrastructure and funding is still a major challenge in research in Indonesia and perhaps other low- to middle-income countries. This visit and workshop are only the beginning of a budding international collaboration to improve healthy ageing in Indonesia. In near future, both universities aim to collaborate in research projects and to maintain knowledge exchange in the field of healthy ageing. We will keep reporting how this collaboration progresses. If you are interested to take part, get in touch with us.

Precision Medicine in Lower Middle Income Countries

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There has been a big amount of interest by stakeholders in the field of precision medicine compared to other medical studies in the past (Jama Network). Although a lot of funding has been allocated to this field, low-to-middle-income countries (LMICs) have not had the same amount of financial backing to develop proper research and development. Aside from financial barriers, LMICs have had minimal participation in the research because of other factors including lack of coherent national policies, limited number of well-trained scientists, poor research infrastructure, and local economic and cultural challenges (NCBI).  This is adding to the inequities in health and disparities in access to health care for patients in LMIC countries.

For example, if there is an estimated 234 million surgical procedures performed worldwide, only 4 percent of the poorest one-third of the world’s population undergoes such procedures. What is alarming is there is more surgical need per person in LMICs such as Africa and Southeast Asia compared to North and South America (Jama Network). Health inequities occur not only in surgery, but in maternal and neonatal health, chronic noncommunicable diseases, and cancer.

The health disparity between developed countries and LMICs are alarming. In one country, one person can die from a basic sickness such as diarrhea, while in another country, a patient can have enough financial backing to pay for a 1 year treatment of cystic fibrosis which costs approximately $300,000 (Jama Network).

Investing in Precision Medicine in LMICs

Since the introduction of precision medicine, research and development in the field has been progressing steadily. The research holds promise to improve the understanding of medicine and find ways to cure diseases at a global level. The ultimate goal is to improve the precision of the practice of medicine at individual levels and to inform and educate public health bodies.

Research and development in precision medicine presents a tremendous promise for LMICs because at this time, morbidity and mortality cost of common diseases is disproportionally high. Therefore, an early investment into genomic research has a big potential for returning long-term benefits.

For an LMIC to have a functional precision medicine program, there needs to be investment in biotechnology. There also needs to be a pool of trained medical geneticists, genetic counselors, genetic epidemiologists, bioinformaticians and computational biologists (NCBI).

At a legislative level, LMIC governments should begin to develop national policies that will address human and technology capacity development within the context of their national economic and socio-cultural uniqueness (NCBI). In parallel, an ethical and legal framework needs to be established to protect the confidential information of the patients. The policies curated by the governmental bodies should encourage international collaboration and promote links between public health programs and researchers.

LMIC’s can maximize the impact of available resources by sharing resources and pooling funds to enhance the research results. There needs to be a push from the different government agencies, the private sector, educational institutions and philanthropists. A more robust engagement of LMICs in research and technological innovations will enable these countries to gain the benefits of the discoveries and improve the health of the population.