Donation frequency and its association with demographic characteristics – a 1‐year observational study

Ou, Yangjiang; Yau, Kelvin K. W.; Poon, Chin Man; Hui, Yi; Lee, S. S.; Lee, C. K.

doi:10.1111/tme.12267

Cited by 14 publications

(19 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…First, current results corroborate previous findings (Volken et al, 2013;Ou et al, 2015) that males are more likely to be blood donors than females. Moreover, our findings distinguish the higher likelihood of males to be occasional donors (8.95 points) than regular donors (7.93 points).…”

Section: Discussion and Concluding Remarkssupporting

confidence: 82%

“…In these studies, males often exhibit higher likelihoods of donating and being frequent donors than females (Volken et al, 2013;Ou et al, 2015). Nevertheless, while it is important to recognise that donor frequency should be gender adjusted as the maximum number of donations permitted annually may be different for adult males (four) and females (three), other reasons may account for lower donation rates among women too.…”

Section: Insights From the Literaturementioning

confidence: 99%

“…For instance, Marantidou et al (2007) note that young people are less likely to donate in Greece, while Kasraian (2010), Volken et al (2013), and Ou et al (2015) report higher response rates among older donors in Iran, Germany, and Hong Kong, respectively. Meanwhile, Boulware et al (2002), Wiwanitkit (2002), and Shenga et al (2010) find no discerning association between age and knowledge or actual blood donation in U.S., Thailand, and India, respectively.…”

Section: Insights From the Literaturementioning

confidence: 99%

“…This study augments the literature by examining the association between such factors and blood donation status based on data from the state of Pulau Pinang, Malaysia. Second, studies have employed the conventional binary logistic or probabilistic models to examine the dichotomous decisions of donors and non-donors (Veldhuizen et al, 2009;Volken et al, 2013;Ou et al, 2015;Ou-Yang et al, 2017), thus compromising the information on occasional and regular donors. We extend the analysis to multi-level outcomes using an ordered probit model to study the donation statuses of non-, occasional-, and regulardonors.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Determinants of Blood Donation Status in Malaysia: Profiling the Non-Donors, Occasional Donors and Regular Donors

Ling¹,

Hui²,

G.³

et al. 2018

View full text Add to dashboard Cite

show abstract

Section: Discussion and Concluding Remarkssupporting

confidence: 82%

Section: Insights From the Literaturementioning

confidence: 99%

Section: Insights From the Literaturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Determinants of Blood Donation Status in Malaysia: Profiling the Non-Donors, Occasional Donors and Regular Donors

Ling¹,

Hui²,

G.³

et al. 2018

View full text Add to dashboard Cite

show abstract

“…A conceptual framework for analysis was developed by referring to the above-mentioned previous studies exploring motivating and inhibiting factors of blood donation [1][2][3][4][5][6][7][8][9][10] and data availability in the JRC's Unified System for Blood Services Database. Eleven analysis items were extracted from the database: five basic attributes (age, sex, blood type, occupation and region), three donationrelated items (side-effects, intention of future donation and blood centre) and three items related to health conditions and lifestyle habits [body mass index (BMI), systolic blood pressure and sleep duration].…”

Section: Survey Itemsmentioning

confidence: 99%

Who returns and becomes a regular blood donor? Analysis of a donor database in Fukushima, Japan

Kashimura

Goto

Nollet

et al. 2017

ISBT Science Series

View full text Add to dashboard Cite

Background and Objective A Frequent Blood Donor Club has been established by the Japanese Red Cross Society to ensure a steady supply of safe blood. This study investigated the characteristics of club members. Materials and Methods Database information on 50 954 donors in FukushimaPrefecture was extracted, and 1907 club members and random selections of 2030 first-time and 2137 returning donors were enroled (sampling proportions of 40% and 5%, respectively). Eleven survey items were compared between the first-time to returning donors and returning donors to club members, using logistic regression analysis.Results While 78Á9% of first-time and 86Á9% of returning donors donated whole blood, 60Á2% of club members donated platelet concentrate. Median number of previous donations was 7 for returning donors and 60 for club members. Eight factors were significantly associated with either donors' return or registration in the donor club: three basic characteristics (age, sex, occupation and region), two blood donation items (no intention of future donation and donation at a fixed location) and three health and lifestyle items (BMI, systolic blood pressure and sleep duration).Conclusions Club members were characterised by higher numbers of previous donations and a preference for component donations. Young people and women were less likely to be returning donors. Directed efforts to recruit and retain donors considering their donation sites and health status are recommended to ensure a stable blood supply now and in the future.

show abstract

A Markov jump process approach to modeling blood donor status: Donor retention and attrition rates at a blood service center in Zimbabwe

Chikobvu

Chideme

2022

Health Science Reports

View full text Add to dashboard Cite

Background: Blood service agencies depend upon the availability of regular blood donors for sustainability. The knowledge and understanding of the stochastic behavior of donors is the first step toward sustaining the blood supply. Analyzing the changes in the donor status within the donor pool will help the blood service authorities to manage the blood donation process.Objectives: The study presents a multistate Markov jump model in analyzing the changes in blood donor status during their blood donation career. Relevant covariates are used to aid in explaining the transitions. Materials and Methods:The status of a blood donor i that can be in one of four states S = {1; 2; 3; 4}. A new donor (s = 1), repeat/regular donor (s = 2), occasional donor (s = 3), and lapsed donor (s = 4). A Continuous-time Markov model was used to estimate blood donor progression during their blood donation career. Frequencies of blood donations made in a given time interval determines the state occupied.Results: In the early years of blood donation career, first-time donors have a higher likelihood of becoming regular donors. Donor attrition increases with time whilst donor retention decreases with time. The results show that when the jump process is currently in an occasional state, the probability that it moves into lapsed state when it leaves the occasional state is given as 69.06%. Similarly, donors are forecasted to spend 21.193 months (1.8 years) in the occasional state before lapsing.Repeat donors can spend 39.342 months (3.3 years) in the regular state before the transition to other states. The study established that donor-specific demographic factors such as age and gender are critical in donor status transitions.Conclusions: With the passage of time, donor status evolves, with trend inclined towards reduction in the frequency of blood donations as more donors become inactive or lapsed. The transition of donors in various states can be described by a time homogeneous Markov model.

show abstract

Donation frequency and its association with demographic characteristics – a 1‐year observational study

Cited by 14 publications

References 20 publications

Determinants of Blood Donation Status in Malaysia: Profiling the Non-Donors, Occasional Donors and Regular Donors

Determinants of Blood Donation Status in Malaysia: Profiling the Non-Donors, Occasional Donors and Regular Donors

Who returns and becomes a regular blood donor? Analysis of a donor database in Fukushima, Japan

A Markov jump process approach to modeling blood donor status: Donor retention and attrition rates at a blood service center in Zimbabwe

Contact Info

Product

Resources

About