Social factors and age play a significant role in cervical cancer and advanced-stage disease among Danish women.

BACKGROUND: For cervical cancer (CC), the implementation of preventive strategies has the potential to make cervical cancer occurrence and death largely avoidable. To better understand the factors possibly responsible for cervical cancer, we aimed to examine possible differences in age and social parameters as well as screening status between women with low- or high-stage cervical cancer and matched controls. METHODS: Through the Danish Cancer Registry (DCR), women diagnosed with cervical cancer in Denmark between 1987 and 2016 were included. These were age- and residence-matched in a 1:5 ratio with controls from the general female population. The study population was sub grouped into a low-stage subpopulation with women with early-stage cervical cancer and matched controls and a high-stage subpopulation with women with late-stage cervical cancer and matched controls. Age and social parameters were compared within the subpopulations as well as between low- and high-stage cases. For part of the study population, screening attendance was examined to compare differences in adherence. RESULTS: Overall, we found that the risk of cervical cancer is significantly increased in socially disadvantaged women and not least non-attenders in screening. Interestingly, the high-stage subpopulation was significantly older than the low-stage subpopulation (p < 0.001), and when examining the impact of age further, we found that for cervical cancer cases, the risk of having low-stage disease decreases significantly with increasing age, whereas the risk of having high-stage disease increases significantly with increasing age. In the screening cohort, significantly less cases than controls were attenders in screening with the most pronounced differences seen in the old subpopulation (women aged 50-64 years) and in the high-stage subpopulation (p-values all < 0.001). Interestingly, when examining the risk of CC for attenders and non-attenders, we demonstrated that many social parameters continue to influence the risk of cervical cancer, even in women attending screening. CONCLUSIONS: Older women, socially disadvantaged women, and non-attenders in screening are particularly vulnerable in terms of developing cervical cancer, especially high-stage disease. Therefore, improvements in the participating rate in screening as well as a revision of the current screening guidelines are needed.

Determinants of clinic absenteeism in a chemotherapy service of a cancer center located at Rio de Janeiro, Brazil.

INTRODUCTION: Clinic absenteeism promotes higher waiting lists for medical procedures and public resources waste. OBJECTIVES: The present work aimed to identify the reasons for clinic absenteeism from each cycle of the antineoplastic chemotherapy treatment, as well as to determine the socio-demographic, clinical and treatment profiles of this population. METHODS: This observational prospective work evaluated pediatric and adult patients which missed their chemotherapy cycle between May and October 2023 in a Cancer Center located in Rio de Janeiro, Brazil. Clinic absenteeism rate was calculated, and socio-demographic profile was described. Reasons for absenteeism, treatment protocol and most used drugs were also identified. RESULTS: This work analyzed data from 69 patients, the majority above 60 years old. Approximately 60% were male, 33.3% had little to no education and 63.8% lived outside the center city. Absenteeism average monthly rate was 1.73% for adults and 0.87% for children. The most related non-attendance reasons were patient feeling too ill to attend their chemotherapy session, failure to remember the cycle day and lack of means of transportation. Most prevalent neoplasms were from the digestive tract (46%). Fluorouracil, irinotecan, oxaliplatin and gemcitabine were the most discarded drugs due to absenteeism. CONCLUSIONS: Older patients and the ones residing far away from the Center tend to miss the scheduled chemotherapy cycles. However, most reasons for absenteeism could be avoided by confirmation calls or text messages. These procedures implementation could lead to a lower absenteeism rate and less resource waste.

Public health nurse perspectives on predicting nonattendance for cervical cancer screening through classification, ensemble, and deep learning models.

OBJECTIVES: Women's attendance to cervical cancer screening (CCS) is a major concern for healthcare providers in community. This study aims to use the various algorithms that can accurately predict the most barriers of women for nonattendance to CS. DESIGN: The real-time data were collected from women presented at OPD of primary health centers (PHCs). About 1046 women's data regarding attendance and nonattendance to CCS were included. In this study, we have used three models, classification, ensemble, and deep learning models, to compare the specific accuracy and AU-ROC for predicting non-attenders for CC. RESULTS: The current model employs 22 predictors, with soft voting in ensemble models showing slightly higher specificity (96%) and sensitivity (93%) than weighted averaging. Bagging excels with the highest accuracy (98.49%), specificity (97.3%), and ideal sensitivity (100%) with an AUC of 0.99. Classification models reveal Naive Bayes with higher specificity (97%) but lower sensitivity (91%) than Logistic Regression. Random Forest and Neural Network achieve the highest accuracy (98.49%), with an AUC of 0.98. In deep learning, LSTM has an accuracy of 95.68%, higher specificity (97.60%), and lower sensitivity (93.42%) compared to other models. MLP and NN showed the highest AUC values of 0.99. CONCLUSION: Employing ensemble and deep learning models proved most effective in predicting barriers to nonattendance in cervical screening.

Predicting Kidney Transplant Evaluation Non-attendance.

Non-attendance to kidney transplant evaluation (KTE) appointments is a barrier to optimal care for those with kidney failure. We examined the medical and socio-cultural factors that predict KTE non-attendance to identify opportunities for integrated medical teams to intervene. Patients scheduled for KTE between May, 2015 and June, 2018 completed an interview before their initial KTE appointment. The interview assessed various social determinants of health, including demographic (e.g., income), medical (e.g. co-morbidities), transplant knowledge, cultural (e.g., medical mistrust), and psychosocial (e.g., social support) factors. We used multiple logistic regression analysis to determine the strongest predictor of KTE non-attendance. Our sample (N = 1119) was 37% female, 76% non-Hispanic White, median age 59.4 years (IQR 49.2-67.5). Of note, 142 (13%) never attended an initial KTE clinic appointment. Being on dialysis predicted higher odds of KTE non-attendance (OR 1.76; p = .02; 64% of KTE attendees on dialysis vs. 77% of non-attendees on dialysis). Transplant and nephrology teams should consider working collaboratively with dialysis units to better coordinate care, (e.g., resources to attend appointment or outreach to emphasize the importance of transplant) adjusting the KTE referral and evaluation process to address access issues (e.g., using tele-health) and encouraging partnership with clinical psychologists to promote quality of life for those on dialysis.

Appointment Non-attendance for Telehealth Versus In-Person Primary Care Visits at a Large Public Healthcare System.

BACKGROUND: Appointment non-attendance has clinical, operational, and financial implications for patients and health systems. How telehealth services are associated with non-attendance in primary care is not well-described, nor are patient characteristics associated with telehealth non-attendance. OBJECTIVE: We sought to compare primary care non-attendance for telehealth versus in-person visits and describe patient characteristics associated with telehealth non-attendance. DESIGN: An observational study of electronic health record data. PARTICIPANTS: Patients with primary care encounters at 23 adult primary care clinics at a large, urban public healthcare system from November 1, 2019, to August 31, 2021. MAIN MEASURES: We analyzed non-attendance by modality (telephone, video, in-person) during three time periods representing different availability of telehealth using hierarchal multiple logistic regression to control for patient demographics and variation within patients and clinics. We stratified by modality and used hierarchal multiple logistic regression to assess for associations between patient characteristics and non-attendance in each modality. KEY RESULTS: There were 1,219,781 scheduled adult primary care visits by 329,461 unique patients: 754,149 (61.8%) in-person, 439,295 (36.0%) telephonic, and 26,337 (2.2%) video visits. Non-attendance for telephone visits was initially higher than that for in-person visits (adjusted odds ratio 1.04 [95% CI 1.02, 1.07]) during the early telehealth availability period, but decreased later (0.82 [0.81, 0.83]). Non-attendance for video visits was higher than for in-person visits during the early (4.37 [2.74, 6.97]) and later (2.02 [1.95, 2.08]) periods. Telephone visits had fewer differences in non-attendance by demographics; video visits were associated with increased non-attendance for patients who were older, male, had a primary language other than English or Spanish, and had public or no insurance. CONCLUSIONS: Telephonic visits may improve access to care and be more easily adoptable among diverse populations. Further attention to implementation may be needed to avoid impeding access to care for certain populations using video visits.

Attendance at pre-pregnancy care clinics for women with type 1 diabetes: A scoping review.

INTRODUCTION: Type 1 diabetes mellitus occurs in one in every 275 pregnancies and can result in increased morbidity and mortality for both mother and baby. Several pregnancy complications can be reduced or prevented by attendance at pre-pregnancy care (PPC). Despite this, less than 40% of pregnant women with pre-gestational diabetes receive formal PPC. The aim of this scoping review is to identify the barriers to PPC attendance among women with type 1 diabetes. METHODS: We conducted a scoping review by searching five databases (Ebsco, Embase, Ovid and PubMed for literature and the ProQuest for any grey/unpublished literature) for studies in English between 2000 and 2022. Studies that evaluated attendance at PPC for women with type 1 diabetes were included. RESULTS: There are multiple barriers to PPC attendance, and many of these barriers have been unchanged since the 1990s. Identified barriers can be grouped under patient-centered and clinician-centered headings. Patient factors include knowledge and awareness, unplanned pregnancies, negative perceptions of healthcare and communication issues, unclear attendance pathways and logistical issues including time off work and childcare. Clinician factors include physician knowledge, time constraints and lack of comfort discussing pregnancy/contraception. CONCLUSION: This review highlights the ongoing problem of poor attendance at PPC and identifies key barriers to be addressed when developing and implementing PPC programs for women with type 1 diabetes.

Outpatient visit behavior in patients with epilepsy: Generalized Epilepsy is more frequently non-attendance than Focal Epilepsy.

BACKGROUND: Patients with epilepsy (PWE), especially those with Idiopathic Epilepsy (GE), are at a high risk of disadvantage caused by non-adherence. It has been suggested that medical visit behavior may be a surrogate indicator of medication adherence. We hypothesized that patients with IGE would adhere poorly to visits. METHODS: This was a retrospective study of PWE who visited the Department of Psychiatry and Neurology at Hokkaido University Hospital between January 2017 and December 2019. Demographic and clinical information on PWE were extracted from medical records and visit data from the medical information system. Non-attendance of outpatient appointments was defined as "not showing up for the day of an appointment without prior notice." Mixed-effects logistic regression analysis was conducted with non-attendance as the objective variable. RESULTS: Of the 9151 total appointments, 413 were non-attendances, with an overall non-attendance rate of 4.5%. IGE was a more frequent non-attendance than Focal Epilepsy (FE) (odds ratio (OR) 1.94; 95% confidence interval (CI) 1.17-3.21; p = 0.010). History of public assistance receipt was associated with higher non-attendance (OR 2.04; 95% CI 1.22-3.43; p = 0.007), while higher education (OR 0.64; 95% CI 0.43-0.93; p = 0.021) and farther distance to a hospital (OR 0.33; 95% CI 0.13-0.88; p = 0.022), and higher frequency of visits (OR 0.18; 95% CI 0.04-0.86; p = 0.031) were associated with fewer non-attendances. In a subgroup analysis of patients with GE, women were associated with fewer non-attendance (OR 0.31; 95% CI 0.14-0.72; p = 0.006). CONCLUSIONS: GE was more frequent in the non-attendance group than in the FE group. Among patients with GE, females were found to have non-attendance less frequently; however, there was no clear difference in the odds of non-attendance between Juvenile Myoclonic Epilepsy (JME) and IGE other than JME.

Risk Factors for Nonattendance in Delusional Infestation: A Multicenter Observational Study.

BACKGROUND: Nonattendance is common among patients suffering from delusional infestation (DI) with a risk factor for poorer patient outcomes. OBJECTIVE: The aim of this study was to determine the incidence rate and predictors of nonattendance among patients presenting to a psychodermatology department with DI and the subsequent effect on the success of prescribing new antipsychotics. METHODS: Data of 265 patients were reviewed of the Amsterdam UMC, the Erasmus University Medical Center, the Royal London Hospital, and the Liverpool School of Tropical Medicine between January 2008 and October 2019. RESULTS: We observed that among the patients who attended the first consultation, 57% (n = 144) did not attend their second visit. Recreational drug use was significantly higher in the nonattendance group compared to the attendance group (25% against 18%). Patients who had a history of previously prescribed antipsychotics at the time of the first consultation were less likely to get prescribed antipsychotics from the psychodermatology departments for DI; however, prescribing antipsychotic drugs by the psychodermatology department did not influence nonattendance significantly. CONCLUSIONS: People suffering from DI are at high risk of nonattendance, even in specialist settings. Patients with current illicit drug use and younger patients are particularly at risk of this.

Mapping out the arguments for and against patient non-attendance fees in healthcare: an analysis of public consultation documents.

BACKGROUND: Patients not attending their appointments without giving notice burden healthcare services. To reduce non-attendance rates, patient non-attendance fees have been introduced in various settings. Although some argue in narrow economic terms that behavioural change as a result of financial incentives is a voluntary transaction, charging patients for non-attendance remains controversial. This paper aims to investigate the controversies of implementing patient non-attendance fees. OBJECTIVE: The aim was to map out the arguments in the Norwegian public debate concerning the introduction and use of patient non-attendance fees at public outpatient clinics. METHODS: Public consultation documents (2009-2021) were thematically analysed (n=84). We used a preconceived conceptual framework based on the works of Grant to guide the analysis. RESULTS: A broad range of arguments for and against patient non-attendance fees were identified, here referring to the acceptability of the fees' purpose, the voluntariness of the responses, the effects on the individual character and institutional norms and the perceived fairness and comparative effectiveness of patient non-attendance fees. Whereas the aim of motivating patients to keep their appointments to avoid poor utilisation of resources and increased waiting times was widely supported, principled and practical arguments against patient non-attendance fees were raised. CONCLUSION: A narrow economic understanding of incentives cannot capture the breadth of arguments for and against patient non-attendance fees. Policy makers may draw on this insight when implementing similar incentive schemes. The study may also contribute to the general debate on ethics and incentives.

Follow-up non-attendance after long-bone fractures in a low-resource setting: a prospective study of predictors and interventions to increase attendance rates.

BACKGROUND: While the majority of traumatic injuries occur in low- and middle-income countries, the published literature comes chiefly from high-income countries due to poor follow-up. Clinical and radiographic post-surgical trauma follow-up is essential to high-quality research and objective monitoring for healing and/or complications. This study aimed to identify the predictors of follow-up non-attendance in a low-resource setting and investigate the extent to which interventional efforts based on mobile phone technology (MPT) and home visits improved the follow-up rates for fractures treated with SIGN nails. METHODS: This was a prospective study of 594 patients with long-bone fractures. Socio-demographic (e.g. age, gender, marital status, education level, etc.) and clinical (e.g. fracture type, concomitant injuries, comorbidity, etc.) data were collected on each patient. Before discharge, the importance of follow-up was explained to patients and their relations. They were encouraged to attend even if they felt well. Their residential addresses and telephone numbers were validated and securely stored. Patients who missed their appointments were contacted by phone. Those who failed to honour 2 or 3 rescheduled appointments were visited in their home. The patients were divided into those who returned for the primarily scheduled follow-up without prompting (volition group) and those who did not come (non-attenders). Univariate analyses and binary logistic regression were conducted to determine the significant predictors of non-attendance. RESULTS: The proportion of patients in the volition group reduced from 96.1% at 6 weeks to 53.0% at 12 weeks and 39.2% at 6 months. However, interventional efforts increased these values to 98.5%, 92.5%, and 72.4% respectively. Walking unaided before the primarily scheduled 12-week appointment was the major reason for not attending the follow-up. Education, occupation, post-operative length of hospital stay (PLOS) and infection were significantly associated with non-attendance but younger age, long distances from the hospital, being separated or divorced, difficulty paying the in-patient care bill, closed fracture, having no (or a non-limb) concomitant injury, achieving painless weight bearing ≤ 6 weeks post-operatively and needing no additional surgery were independent predictors of non-attendance. CONCLUSIONS: Our study sheds light on the predictors of follow-up non-attendance and demonstrates how interventional efforts improved attendance rates in a low-resource setting. In addition, efforts that better the socio-economic status of people such as more-encompassing health insurance coverage and greater work flexibility can improve the follow-up attendance rates.

Factors determining non-attendance in breast cancer screening among women in the Netherlands: a national study.

Breast cancer is one of the most common types of cancer among women. National mammography screening programs can detect breast cancer early, but attendance rates have been decreasing in the Netherlands over the past decade. Non-attendees reported that overdiagnosis, the risk of false-negative results, x-ray exposure and mammography pain could be barriers to attendance, but it is not clear whether these disadvantages explain non-attendance and in which situations they are considered barriers. We conducted a national survey among 1227 Dutch women who did not attend mammography screening appointments in 2016. Logistic regression models were used to identify factors that influenced the likelihood of the abovementioned disadvantages leading to non-attendance. The results showed that the doctor's opinion increased the likelihood of the risk of false-negative being perceived as a reason for non-attendance. Moreover, opportunistic screening increased the likelihood that the risk of false-negative, overdiagnosis and x-ray exposure would lead to non-attendance. Women with lower education levels were less likely to consider overdiagnosis and x-ray exposure as reasons for non-attendance, while women who had not undergone mammography screening before were more likely to reject the screening invitation because of concerns about x-ray exposure and mammography pain. These findings indicate how we can address the specific concerns of different groups of women in the Netherlands to encourage them to attend potentially life-saving breast-screening appointments. Screening organizations could provide accurate and unbiased information on the effectiveness of mammography screening to GPs, putting them in a better position to advise their patients.

Development and validation of nonattendance predictive models for scheduled adult outpatient appointments in different medical specialties.

INTRODUCTION: Nonattendance is a critical problem that affects health care worldwide. Our aim was to build and validate predictive models of nonattendance in all outpatients appointments, general practitioners, and clinical and surgical specialties. METHODS: A cohort study of adult patients, who had scheduled outpatient appointments for General Practitioners, Clinical and Surgical specialties, was conducted between January 2015 and December 2016, at the Italian Hospital of Buenos Aires. We evaluated potential predictors grouped in baseline patient characteristics, characteristics of the appointment scheduling process, patient history, characteristics of the appointment, and comorbidities. Patients were divided between those who attended their appointments, and those who did not. We generated predictive models for nonattendance for all appointments and the three subgroups. RESULTS: Of 2,526,549 appointments included, 703,449 were missed (27.8%). The predictive model for all appointments contains 30 variables, with an area under the ROC (AUROC) curve of 0.71, calibration-in-the-large (CITL) of 0.046, and calibration slope of 1.03 in the validation cohort. For General Practitioners the model has 28 variables (AUROC of 0.72, CITL of 0.053, and calibration slope of 1.01). For clinical subspecialties, the model has 23 variables (AUROC of 0.71, CITL of 0.039, and calibration slope of 1), and for surgical specialties, the model has 22 variables (AUROC of 0.70, CITL of 0.023, and calibration slope of 1.01). CONCLUSION: We build robust predictive models of nonattendance with adequate precision and calibration for each of the subgroups.

FACTORS ASSOCIATED WITH NON-ATTENDANCE TO OUTPATIENT CONSULTATION-LIAISON PSYCHIATRY APPOINTMENTS: A RETROSPECTIVE COHORT STUDY.

BACKGROUND: Non-attendance to outpatient mental health appointments is associated with adverse clinical and financial outcomes. The aim of this study was to investigate the rates of non-attendance to outpatient Consultation-Liaison Psychiatry (CLP) appointments and the factors associated with non-attendance. SUBJECTS AND METHODS: Retrospective cohort study, including two groups of data: 950 initial and 3503 follow-up appointments between 01/01/2015 and 31/12/2019. We employed descriptive statistics, parametric/non-parametric tests and logistic regression analysis. We used a range of environmental, socio-demographic and service-related characteristics as independent parameters and non-attendance as the dependent parameter. RESULTS: Initial and follow-up non-attendance rates were 27.5% and 18.8% respectively. Opting-out text message reminders was associated with both initial and follow-up non-attendance. Higher education was associated with initial non-attendance, whereas lower education with follow-up non-attendance. Other factors associated with non-attendance to initial appointments were: English being the participant's primary communication language, having an appointment with a psychiatrist as opposed to a trained nurse or Cognitive Behavioural Therapist, and longer waiting time. Follow-up non-attendance was also associated with younger age, shorter driving distance and higher income/employment. CONCLUSION: We suggest that improving opt-in rates through a combination of staff and patient education and promotion, improving waiting lists, reducing the stigma associated with seeing a psychiatrist, but also perhaps targeting different socio-economic groups of patients with different strategies should be the focus of policy making to tackle non-attendance. Further research into patient-related and environmental factors, such as day of the week, driving distance, language of primary communication, education, income and employment is warranted in order to design more effective policies and improve engagement with CLP, but also psychiatric services in general.

Discrete choice analysis of health worker job preferences in Ethiopia: Separating attribute non-attendance from taste heterogeneity.

When measuring preferences, discrete choice experiments (DCEs) typically assume that respondents consider all available information before making decisions. However, many respondents often only consider a subset of the choice characteristics, a heuristic called attribute non-attendance (ANA). Failure to account for ANA can bias DCE results, potentially leading to flawed policy recommendations. While conventional latent class logit models have most commonly been used to assess ANA in choices, these models are often not flexible enough to separate non-attendance from respondents' low valuation of certain attributes, resulting in inflated rates of ANA. In this paper, we show that semi-parametric mixtures of latent class models can be used to disentangle successfully inferred non-attendance from respondent's "weaker" taste sensitivities for certain attributes. In a DCE on the job preferences of health workers in Ethiopia, we demonstrate that such models provide more reliable estimates of inferred non-attendance than the alternative methods currently used. Moreover, since we find statistically significant variation in the rates of ANA exhibited by different health worker cadres, we highlight the need for well-defined attributes in a DCE, to ensure that ANA does not result from a weak experimental design.

Factors Associated with Nonattendance to a Geriatric Clinic among Mexican Older Adults.

INTRODUCTION: Outpatient appointment nonattendance (NA) represents a public health problem, increasing the risk of unfavorable health-related outcomes. Although NA is significant among older adults, little is known regarding its correlates. This study aimed to identify the correlates (including several domains from the geriatric assessment) of single and repeated NA episodes in a geriatric medicine outpatient clinic, in general and in the context of specific comorbidities. METHODS: This is a cross-sectional study including data from 3,034 older adults aged ≥60 years with ≥1 scheduled appointments between January 1, 2016, and December 31, 2016. Appointment characteristics as well as sociodemographic, geographical, and environmental information were obtained. Univariate and multivariate multinomial regression analyses were carried out. RESULTS: The mean age was 81.8 years (SD 7.19). Over a third (37.4%) of participants missed one scheduled appointment, and 14.4% missed ≥2. Participants with a history of stroke (OR 1.336, p = 0.041) and those with a greater number of scheduled appointments during the study time frame (OR 1.182, p < 0.001) were more likely to miss one appointment, while those with Parkinson's disease (OR 0.346, p < 0.001), other pulmonary diseases (OR 0.686, p = 0.008), and better functioning for activities of daily living (ADL) (OR 0.883, p < 0.001) were less likely to do so. High socioeconomic level (OR 2.235, p < 0.001), not having a partner (OR 1.410, p = 0.006), a history of fractures (OR 1.492, p = 0.031), and a greater number of scheduled appointments (OR 1.668, p < 0.001) increased the risk of repeated NA, while osteoarthritis (OR 0.599, p = 0.001) and hypertension (OR 0.680, p = 0.002) decreased it. In specific comorbidity populations (hypertension, type 2 diabetes mellitus, and cancer), better ADL functioning protected from a single NA, while better mobility functioning protected from repeated NA in older patients with hypertension and cancer. DISCUSSION/CONCLUSION: Identifying geriatric factors linked to an increased probability of NA may allow one to anticipate its likelihood and lead to the design and implementation of preventive strategies and to an optimization of the use of available health resources. The impact of these factors on adherence to clinical visits requires further investigation.

Poor Attendance for bone densitometry in patients at high risk of subsequent fragility fractures.

Fracture Liaison Services (FLS) are considered the most effective model for the prevention of subsequent fractures however, the uptake of these services has shown to be suboptimal. 6,528 patients were identified and referred on for bone densitometry assessment over a 6 yr period, however, 21% of these patients did not attend, with a trend towards a higher re-fracture rate in those that did not attend compared to those that did. The presence of a fragility fracture increases the risk of further fractures. Fracture Liaison Services (FLS) are considered the most effective model for the prevention of subsequent fractures, although the uptake amongst patients invited for bone densitometry assessment has shown to be suboptimal. The UK has one of the most comprehensive numbers of FLS, however the proportion and characteristics of patients identified through the FLS that do not respond to bone densitometry invitation, in the UK, remains unclear. We report the 6 yr. findings from the Nottingham FLS. The Nottingham Fracture Liaison Service (N-FLS) systematically identifies those adults aged 50 yr. and older with fragility fractures presenting to the fracture clinic and where appropriate, arranges referral for bone densitometry assessment. Routine clinical data is collected onto the N-FLS database. Patient characteristics, between January 2012 and December 2017, were examined of those referred for bone densitometry examination, comparing those that attended to those that did not attend (DNA). Deprivation scores for each patient were calculated using the English indices of deprivation 2015 (1-Most deprived; 5- Least deprived). Follow up data was available for those attending from 2016 onwards, which allowed an assessment of re-fracture. Over the 6 yr period, 6,528 patients as identified by the N-FLS were referred on for bone densitometry assessment. 1,386 patients (21%) did not attend (DNA) for bone densitometry assessment. The proportion was similar for each of the years. High prevalence of non-attendance was in females [1032 patients (74%)] and the most deprived individuals [398 patients (29%), which were significant when compared to those that did attend, p=0.042]. 826 patients were referred in 2016. Median follow-up time was 2.46 yr. (IQR 0.16-3.00 yr.). 52 (7%) patients, in this group, sustained a subsequent fracture (35 patients in the group that did not attend for bone density assessment and 17 in those that attend, p=0.092). Nottingham FLS have identified patients with fragility fractures that are at high-risk of further fractures. Despite a dedicated FLS, 21% of those invited for bone densitometry assessment, did not attend for their appointment, over the 6 yr. period, similar proportion each year. There was a significantly higher proportion of those identified as 'most deprived' not attending for a bone densitometry, compared to those who attended. Sub-analysis in those aged 75 yr. and over, showed a high non-attendance in this group. Further qualitative studies are necessary to explore this patient group in detail, who remain at high risk of re-fracture.

Colposcopy non-attendance following an abnormal cervical cancer screening result: a prospective population-based cohort study.

BACKGROUND: A considerable proportion of cervical cancer diagnoses in high-income countries are due to lack of timely follow-up of an abnormal screening result. We estimated colposcopy non-attendance, examined the potential factors associated and described non-attendance reasons in a population-based screening study. METHODS: Data from the MARZY prospective cohort study were analysed. Co-test screen-positive women (atypical squamous cells of undetermined significance or worse [ASC-US+] or high-risk human papillomavirus [hrHPV] positive) aged 30 to 65 years were referred to colposcopy within two screening rounds (3-year interval). Women were surveyed for sociodemographic, HPV-related and other data, and interviewed for non-attendance reasons. Logistic regression was used to examine potential associations with colposcopy attendance. RESULTS: At baseline, 2,627 women were screened (screen-positive = 8.7%), and 2,093 again at follow-up (screen-positive = 5.1%; median 2.7 years later). All screen-positives were referred to colposcopy, however 28.9% did not attend despite active recall. Among co-test positives (ASC-US+ and hrHPV) and only hrHPV positives, 19.6% were non-attendees. Half of only ASC-US+ screenees attended colposcopy. Middle age (adjusted odds ratio [aOR] = 1.55, 95% CI 1.02, 4.96) and hrHPV positive result (aOR = 3.04, 95% CI 1.49, 7.22) were associated with attendance. Non-attendance was associated with having ≥ 3 children (aOR = 0.32, 95% CI 0.10, 0.86). Major reasons for non-attendance were lack of time, barriers such as travel time, need for childcare arrangements and the advice against colposcopy given by the gynaecologist who conducted screening. CONCLUSIONS: Follow-up rates of abnormal screening results needs improvement. A systematic recall system integrating enhanced communication and addressing follow-up barriers may improve screening effectiveness.

Attribute nonattendance in COVID-19 vaccine choice: A discrete choice experiment based on Chinese public preference.

OBJECTIVES: The global coronavirus disease 2019 (COVID-19) pandemic has not been well controlled, and vaccination could be an effective way to prevent this pandemic. By accommodating attribute nonattendance (ANA) in a discrete choice experiment (DCE), this paper aimed to examine Chinese public preferences and willingness to pay (WTP) for COVID-19 vaccine attributes, especially the influence of ANA on the estimated results. METHODS: A DCE was designed with four attributes: effectiveness, protection period, adverse reactions and price. A random parameter logit model with an error component (RPL-EC) was used to analyse the heterogeneity of respondents' preferences for COVID-19 vaccine attributes. Two equality constraint latent class (ECLC) models were used to consider the influence of ANA on the estimated results in which the ECLC-homogeneity model considered only ANA and the ECLC-heterogeneity model considered both ANA and preference heterogeneity. RESULTS: Data from 1,576 samples were included in the analyses. Effectiveness had the highest relative importance, followed by adverse reactions and protection period, which were determined by the attributes and levels presented in this study. The ECLC-heterogeneity model improved the goodness of fit of the model and obtained a lower probability of ANA. In the ECLC-heterogeneity model, only a small number of respondents (29.09%) considered all attributes, and price was the most easily ignored attribute (64.23%). Compared with the RPL-EC model, the ECLC-homogeneity model obtained lower WTPs for COVID-19 vaccine attributes, and the ECLC-heterogeneity model obtained mixed WTP results. In the ECLC-heterogeneity model, preference group 1 obtained higher WTPs, and preference groups 2 and 3 obtained lower WTPs. CONCLUSIONS: The RPL-EC, ECLC-homogeneity and ECLC-heterogeneity models obtained inconsistent WTPs for COVID-19 vaccine attributes. The study found that the results of the ECLC-heterogeneity model considering both ANA and preference heterogeneity may be more plausible because ANA and low preference may be confused in the ECLC-homogeneity model and the RPL-EC model. The results showed that the probability of ANA was still high in the ECLC-heterogeneity model, although it was lower than that in the ECLC-homogeneity model. Therefore, in future research on DCE (such as the field of vaccines), ANA should be considered as an essential issue. PUBLIC CONTRIBUTION: Chinese adults from 31 provinces in mainland China participated in the study. All participants completed the COVID-19 vaccine choice questions generated through the DCE design.

Evaluating the reasons for nonattendance to outpatient consultations: is waiting time an important factor?

BACKGROUND: Nonattendance is a common problem worldwide. Important factors for nonattendance are a queue or the waiting time until the planned service. AIMS: The aims of this study were to identify the reasons for nonattendance to planned consultations, assess the waiting time from registration to access to an outpatient specialist consultation, and identify the associations between the reasons for nonattendance and the waiting time until the planned outpatient specialist consultation. METHODS: A cross-sectional study based on a phone questionnaire was conducted among patients not attending a planned consultation at the outpatient department of the Lithuanian University of Health Sciences Kaunas Hospital in Kaunas, Lithuania. A total of 972 phone calls were made, and 389 telephone surveys were completed. RESULTS: The mean respondents' waiting time until the planned outpatient consultation was 15.13 ± 10 days. The highest proportion of nonattendance was observed when the wait time was between 6 and 17 days. More often, the patients did not attend the planned outpatient consultation due to worsened health status (24.69%), unidentified personal problems (14.91%), work-related problems (13.62%) and being unaware about the appointment (11.82%). A longer waiting time was significantly associated with the following reasons for nonattendance: work-related problems, health problems solved at another health care institution, unidentified personal problems and unknown reasons for nonattendance. The highest proportions of nonattending patients had consultations registered with neurologists (17.0%), traumatologists (11.3%) and cardiologists (10.5%). CONCLUSIONS: Patients did not identify the long waiting time until outpatient specialist consultation among the main reasons for nonattendance. The issue of waiting time is not an important aspect of nonattendance.

A qualitative study exploring the barriers to attending structured education programmes among adults with type 2 diabetes.

BACKGROUND: Diabetes self-management education, a universally recommended component of diabetes care, aims to support self-management in people with type 2 diabetes. However, attendance is low (approx. 10%). Previous research investigating the reasons for low attendance have not yet linked findings to theory, making it difficult to translate findings into practice. This study explores why some adults with type 2 diabetes do not attend diabetes self-management education and considers how services can be adapted accordingly, using Andersen's Behavioural Model of Health Service Utilisation as a framework. METHODS: A cross-sectional semi-structured qualitative interview study was carried out. Semi-structured interviews were conducted by telephone with 14 adults with type 2 diabetes who had verbally declined their invitation to attend diabetes self-management education in Bath and North East Somerset, UK, within the last 2 years. Data were analysed using inductive thematic analysis before mapping the themes onto the factors of Andersen's Behavioural Model. RESULTS: Two main themes were identified: 'perceived need' and 'practical barriers'. The former theme explored participants' tendency to decline diabetes education when they perceived they did not need the programme. This perception tended to arise from participants' high self-efficacy to manage their type 2 diabetes, the low priority they attributed to their condition and limited knowledge about the programme. The latter theme, 'practical barriers', explored the notion that some participants wanted to attend but were unable to due to other commitments and/or transportation issues in getting to the venue. CONCLUSIONS: All sub-themes resonated with one or more factors of Andersen's Behavioural Model indicating that the model may help to elucidate attendance barriers and ways to improve services. To fully understand low attendance to diabetes education, the complex and individualised reasons for non-attendance must be recognised and a person-centred approach should be taken to understand people's experience, needs and capabilities.