Improving Electronic Survey Response Rates Among Cancer Center Patients During the COVID-19 Pandemic: Mixed Methods Pilot Study

Risk factors and health behaviors associated with loneliness among cancer survivors during the COVID-19 pandemic

Loneliness may exacerbate poor health outcomes particularly among cancer survivors during the COVID-19 pandemic. Little is known about the risk factors of loneliness among cancer survivors. We evaluated the risk factors of loneliness in the context of COVID-19 pandemic-related prevention behaviors and lifestyle/psychosocial factors among cancer survivors. Cancer survivors (n = 1471) seen at Huntsman Cancer Institute completed a survey between August-September 2020 evaluating health behaviors, medical care, and psychosocial factors including loneliness during COVID-19 pandemic. Participants were classified into two groups: 'lonely' (sometimes, usually, or always felt lonely in past month) and 'non-lonely' (never or rarely felt lonely in past month). 33% of cancer survivors reported feeling lonely in the past month. Multivariable logistic regression showed female sex, not living with a spouse/partner, poor health status, COVID-19 pandemic-associated lifestyle factors including increased alcohol consumption and marijuana/CBD oil use, and psychosocial stressors such as disruptions in daily life, less social interaction, and higher perceived stress and financial stress were associated with feeling lonely as compared to being non-lonely (all p < 0.05). A significant proportion of participants reported loneliness, which is a serious health risk among vulnerable populations, particularly cancer survivors. Modifiable risk factors such as unhealthy lifestyle behaviors and psychosocial stress were associated with loneliness. These results highlight the need to screen for unhealthy lifestyle factors and psychosocial stressors to identify cancer survivors at increased risk of loneliness and to develop effective management strategies.

Health status based on EQ-5D-5L for the cancer patient population in Malaysia

The EQ-5D is a common generic tool used in clinical trials and economic evaluations to evaluate the health-related quality of life as a proxy of health outcomes. To date, studies using EQ-5D-5L to evaluate the health status of cancer patients remain scarce in Malaysia. In this study, EQ-5D-5L dimensions, EQ-5D-5L index, and EQ-VAS scores were applied to assess the health status of Malaysian cancer patients. A cross-sectional study was conducted March-December 2022 to collect data relevant to the EQ-5D-5L valuation of health status via the Research Electronic Data Capture (REDCap) platform. Respondents rated their health states using EQ-5D-5L and EQ-VAS. Among the 235 respondents, the mean EQ-5D-5L index and EQ-VAS score were 0.76 (SD 0.223) and 81.06 (SD 16.36). Most of the patients reported some problems in the pain/discomfort and anxiety/depression dimensions. The level of education, stage of cancer, and comorbidity were significantly associated with better health status on EQ-5D-5L (p < 0.05) but only the stage of cancer was significantly associated with EQ-VAS scores. This study highlighted the disparities in self-reported health status across patients of different sociodemographic and medical profiles with EQ-5D-5L valuation. Thus, future research should use EQ-5D norm scores as a benchmark of comparison among cancer patients.

Methods to increase response to postal and electronic questionnaires

BACKGROUND

Self-administered questionnaires are widely used to collect data in epidemiological research, but non-response reduces the effective sample size and can introduce bias. Finding ways to increase response to postal and electronic questionnaires would improve the quality of epidemiological research.

OBJECTIVES

To identify effective strategies to increase response to postal and electronic questionnaires.

SEARCH METHODS

We searched 14 electronic databases up to December 2021 and manually searched the reference lists of relevant trials and reviews. We contacted the authors of all trials or reviews to ask about unpublished trials; where necessary, we also contacted authors to confirm the methods of allocation used and to clarify results presented.

SELECTION CRITERIA

Randomised trials of methods to increase response to postal or electronic questionnaires. We assessed the eligibility of each trial using pre-defined criteria.

DATA COLLECTION AND ANALYSIS

We extracted data on the trial participants, the intervention, the number randomised to intervention and comparison groups and allocation concealment. For each strategy, we estimated pooled odds ratios (OR) and 95% confidence intervals (CI) in a random-effects model. We assessed evidence for selection bias using Egger's weighted regression method and Begg's rank correlation test and funnel plot. We assessed heterogeneity amongst trial odds ratios using a Chi2 test and quantified the degree of inconsistency between trial results using the I2 statistic.

MAIN RESULTS

Postal We found 670 eligible trials that evaluated over 100 different strategies of increasing response to postal questionnaires. We found substantial heterogeneity amongst trial results in half of the strategies. The odds of response almost doubled when: using monetary incentives (odds ratio (OR) 1.86; 95% confidence interval (CI) 1.73 to 1.99; heterogeneity I2 = 85%); using a telephone reminder (OR 1.96; 95% CI 1.03 to 3.74); and when clinical outcome questions were placed last (OR 2.05; 95% CI 1.00 to 4.24). The odds of response increased by about half when: using a shorter questionnaire (OR 1.58; 95% CI 1.40 to 1.78); contacting participants before sending questionnaires (OR 1.36; 95% CI 1.23 to 1.51; I2 = 87%); incentives were given with questionnaires (i.e. unconditional) rather than when given only after participants had returned their questionnaire (i.e. conditional on response) (OR 1.53; 95% CI 1.35 to 1.74); using personalised SMS reminders (OR 1.53; 95% CI 0.97 to 2.42); using a special (recorded) delivery service (OR 1.68; 95% CI 1.36 to 2.08; I2 = 87%); using electronic reminders (OR 1.60; 95% CI 1.10 to 2.33); using intensive follow-up (OR 1.69; 95% CI 0.93 to 3.06); using a more interesting/salient questionnaire (OR 1.73; 95% CI 1.12 to 2.66); and when mentioning an obligation to respond (OR 1.61; 95% CI 1.16 to 2.22). The odds of response also increased with: non-monetary incentives (OR 1.16; 95% CI 1.11 to 1.21; I2 = 80%); a larger monetary incentive (OR 1.24; 95% CI 1.15 to 1.33); a larger non-monetary incentive (OR 1.15; 95% CI 1.00 to 1.33); when a pen was included (OR 1.44; 95% CI 1.38 to 1.50); using personalised materials (OR 1.15; 95% CI 1.09 to 1.21; I2 = 57%); using a single-sided rather than a double-sided questionnaire (OR 1.13; 95% CI 1.02 to 1.25); using stamped return envelopes rather than franked return envelopes (OR 1.23; 95% CI 1.13 to 1.33; I2 = 69%), assuring confidentiality (OR 1.33; 95% CI 1.24 to 1.42); using first-class outward mailing (OR 1.11; 95% CI 1.02 to 1.21); and when questionnaires originated from a university (OR 1.32; 95% CI 1.13 to 1.54). The odds of response were reduced when the questionnaire included questions of a sensitive nature (OR 0.94; 95% CI 0.88 to 1.00). Electronic We found 88 eligible trials that evaluated over 30 different ways of increasing response to electronic questionnaires. We found substantial heterogeneity amongst trial results in half of the strategies. The odds of response tripled when: using a brief letter rather than a detailed letter (OR 3.26; 95% CI 1.79 to 5.94); and when a picture was included in an email (OR 3.05; 95% CI 1.84 to 5.06; I2 = 19%). The odds of response almost doubled when: using monetary incentives (OR 1.88; 95% CI 1.31 to 2.71; I2 = 79%); and using a more interesting topic (OR 1.85; 95% CI 1.52 to 2.26). The odds of response increased by half when: using non-monetary incentives (OR 1.60; 95% CI 1.25 to 2.05); using shorter e-questionnaires (OR 1.51; 95% CI 1.06 to 2.16; I2 = 94%); and using a more interesting e-questionnaire (OR 1.85; 95% CI 1.52 to 2.26). The odds of response increased by a third when: offering survey results as an incentive (OR 1.36; 95% CI 1.16 to 1.59); using a white background (OR 1.31; 95% CI 1.10 to 1.56); and when stressing the benefits to society of response (OR 1.38; 95% CI 1.07 to 1.78; I2 = 41%). The odds of response also increased with: personalised e-questionnaires (OR 1.24; 95% CI 1.17 to 1.32; I2 = 41%); using a simple header (OR 1.23; 95% CI 1.03 to 1.48); giving a deadline (OR 1.18; 95% CI 1.03 to 1.34); and by giving a longer time estimate for completion (OR 1.25; 95% CI 0.96 to 1.64). The odds of response were reduced when: "Survey" was mentioned in the e-mail subject (OR 0.81; 95% CI 0.67 to 0.97); when the email or the e-questionnaire was from a male investigator, or it included a male signature (OR 0.55; 95% CI 0.38 to 0.80); and by using university sponsorship (OR 0.84; 95%CI 0.69 to 1.01). The odds of response using a postal questionnaire were over twice those using an e-questionnaire (OR 2.33; 95% CI 2.25 to 2.42; I2 = 98%). Response also increased when: providing a choice of response mode (electronic or postal) rather than electronic only (OR 1.76 95% CI 1.67 to 1.85; I2 = 97%); and when administering the e-questionnaire by computer rather than by smartphone (OR 1.62 95% CI 1.36 to 1.94).

AUTHORS' CONCLUSIONS

Researchers using postal and electronic questionnaires can increase response using the strategies shown to be effective in this Cochrane review.

Contextualizing Response Rates During the COVID-19 Pandemic: Experiences From a Boston-Based Community Health Centers Study

OBJECTIVES

The focus of this study was to calculate and contextualize response rates for a community-based study conducted during the COVID-19 pandemic, a topic on which scant data exist, and to share lessons learned from recruiting and enrolling for implementation of future studies.

DESIGN

The Life+Health Study, a cross-sectional population-based study designed to advance novel methods to measure and analyze multiple forms of discrimination for population health research.

SETTING

The study recruited participants from 3 community health centers in Boston, Massachusetts, between May 2020 and July 2022.

PARTICIPANTS

A total of 699 adult participants between the ages of 25 and 64 years who were born in the United States and had visited one of the health centers within the last 2 years.

MAIN OUTCOME MEASURES

The response rate was calculated as follows: (number of completions + number of dropouts)/(dropouts + enrollments). To contextualize this response rate, we synthesized evidence pertaining to local COVID-19 case counts, sociopolitical events, pandemic-related restrictions and project protocol adjustments, and examples of interactions with patients.

RESULTS

Our study had a lower-than-expected response rate (48.4%), with the lowest rates from the community health centers serving primarily low-income patients of color. Completion rates were lower during periods of higher COVID-19 case counts. We describe contextual factors that led to challenges and lessons learned from recruiting during the pandemic, including the impact of US sociopolitical events.

CONCLUSIONS

The Life+Health Study concluded recruitment during the pandemic with a lower-than-expected response rate, as also reported in 4 other US publications focused on the impact of COVID-19 on response rates in community-based studies. Our results provide an example of the impact of the pandemic and related US sociopolitical events on response rates that can serve as a framework for contextualizing other research conducted during the pandemic and highlight the importance of best practices in research recruitment with underserved populations.

Comparing COVID-19 Response Behaviors between a Cancer Patient Sample and a Population-Based Cancer-Free Sample in a Rural Midwestern State

INTRODUCTION

The COVID-19 pandemic caused an increase in fear, anxiety, and depressive symptoms globally. For populations at increased risk for adverse outcomes due to illness, such as cancer patients, these worries may have been exacerbated. Understanding how the pandemic impacted cancer patients will inform better preparation for future events that cause disturbances to cancer care delivery.

METHODS

This study analyzed data from two surveys to determine whether cancer patients' responses differed from a cancer-free population-based sample in terms of concerns, preventive behaviors, and thoughts on their healthcare provider's communication regarding COVID-19 in a US Midwestern state. In August 2020, a survey was sent to 10,009 Iowans aged 18 and older, randomly selected from the 2018 Iowa voter registration file. In September 2020, a survey was emailed to 2,954 cancer patients aged 18 and older who opted into the University of Iowa Holden Comprehensive Cancer Center's Patients Enhancing Research Collaborations at Holden program. Previously validated and pretested Likert-type and multiple-choice items assessed concern regarding COVID-19, social distancing perception and behaviors, and demographic characteristics of respondents. We used χ2 tests and logistic regression to examine differences between the cancer patient and general population survey responses.

RESULTS

We included 3,622 responses from the general population survey and 780 responses from the cancer patient survey in this analysis. Cancer patient survey respondents were more frequently older, lived in urban areas, had Medicare insurance coverage, had a college degree or higher, and were married. Cancer patients were more likely to report engaging in social distancing behaviors and greater concern regarding the pandemic.

CONCLUSION

This study suggests differences in the impact of the COVID-19 pandemic on cancer patients compared to cancer-free members of the general population. These results indicate the need for consideration of cancer patients' physical and mental health during large-scale disruptions to cancer care.

Recruiting African American Prostate Cancer Survivors for a Population-based Biobank Study

BACKGROUND

Prostate cancer affects African American men disproportionately compared with men of other racial/ethnic groups. To identify biological bases for this health disparity, we sought to create a state-wide biobank of African American prostate cancer survivors in Florida.

METHODS

African American men diagnosed with prostate cancer between 2013 and 2017 and living in Florida at diagnosis were identified through the State of Florida's cancer registry. Individuals were approached via mail and telephone, assessed for eligibility, and asked for informed consent. χ2 and t tests were conducted to identify differences between eligible and reachable individuals (i.e., had valid contact information) versus consented participants.

RESULTS

Of the 5,960 eligible and reachable individuals, 3,904 were eligible and contacted at least once, and 578 consented [overall consent rate = 10% (578/5,960); adjusted consent rate = 15% (578/3,904)]. Statistically significant (Ps < 0.05) but small differences in demographic and clinical variables were observed. Consented participants were less likely to be older than 64 (35% vs. 41%) and less likely to have received radiotherapy (36% vs. 41%) and hormone therapy (16% vs. 21%), but more likely to have regional prostate cancer (13% vs. 11%) and have undergone surgery (44% vs. 39%). Consented participants did not differ from reachable individuals on other demographic and clinical factors (Ps > 0.05).

CONCLUSIONS

Recruiting African American prostate cancer survivors to biobanking research through a cancer registry is feasible. However, the consent rate was low, and existing challenges limit consent and participation.

IMPACT

Strategies for overcoming barriers to informed consent and increasing participation in biospecimen research are needed to address cancer disparities.

Decreasing Survey Response Rates in the Time of COVID-19: Implications for Analyses of Population Health and Health Inequities

Objectives. To examine whether, and if so how, US national and state survey response rates changed after the onset of the COVID-19 pandemic. Methods. We compared the change in response rates between 2020 and 2019 of 6 (3 social and economic, 3 health focused) major US national surveys (2 with state response rates). Results. All the ongoing surveys except 1 reported relative decreases (∼29%) in response rates. For example, the household response rate to the US Census American Community Survey decreased from 86.0% in 2019 to 71.2% in 2020, and the response rate of the US National Health Interview Survey decreased from 60.0% to 42.7% from the first to the second quarter of 2020. For all surveys, the greatest decreases in response rates occurred among persons with lower income and lower education. Conclusions. Socially patterned decreases in response rates pose serious challenges and must be addressed explicitly in all studies relying on data obtained since the onset of the pandemic. Public Health Implications. Artifactual reduction of estimates of the magnitude of health inequities attributable to differential response rates could adversely affect efforts to reduce these inequities. (Am J Public Health. 2023;113(6):667-670. https://doi.org/10.2105/AJPH.2023.307267).

Electronic Health Record-Triggered Research Infrastructure Combining Real-world Electronic Health Record Data and Patient-Reported Outcomes to Detect Benefits, Risks, and Impact of Medication: Development Study

Background

Real-world data from electronic health records (EHRs) represent a wealth of information for studying the benefits and risks of medical treatment. However, they are limited in scope and should be complemented by information from the patient perspective.

Objective

The aim of this study is to develop an innovative research infrastructure that combines information from EHRs with patient experiences reported in questionnaires to monitor the risks and benefits of medical treatment.

Methods

We focused on the treatment of overactive bladder (OAB) in general practice as a use case. To develop the Benefit, Risk, and Impact of Medication Monitor (BRIMM) infrastructure, we first performed a requirement analysis. BRIMM’s starting point is routinely recorded general practice EHR data that are sent to the Dutch Nivel Primary Care Database weekly. Patients with OAB were flagged weekly on the basis of diagnoses and prescriptions. They were invited subsequently for participation by their general practitioner (GP), via a trusted third party. Patients received a series of questionnaires on disease status, pharmacological and nonpharmacological treatments, adverse drug reactions, drug adherence, and quality of life. The questionnaires and a dedicated feedback portal were developed in collaboration with a patient association for pelvic-related diseases, Bekkenbodem4All. Participating patients and GPs received feedback. An expert meeting was organized to assess the strengths, weaknesses, opportunities, and threats of the new research infrastructure.

Results

The BRIMM infrastructure was developed and implemented. In the Nivel Primary Care Database, 2933 patients with OAB from 27 general practices were flagged. GPs selected 1636 (55.78%) patients who were eligible for the study, of whom 295 (18.0% of eligible patients) completed the first questionnaire. A total of 288 (97.6%) patients consented to the linkage of their questionnaire data with their EHR data. According to experts, the strengths of the infrastructure were the linkage of patient-reported outcomes with EHR data, comparison of pharmacological and nonpharmacological treatments, flexibility of the infrastructure, and low registration burden for GPs. Methodological weaknesses, such as susceptibility to bias, patient selection, and low participation rates among GPs and patients, were seen as weaknesses and threats. Opportunities represent usefulness for policy makers and health professionals, conditional approval of medication, data linkage to other data sources, and feedback to patients.

Conclusions

The BRIMM research infrastructure has the potential to assess the benefits and safety of (medical) treatment in real-life situations using a unique combination of EHRs and patient-reported outcomes. As patient involvement is an important aspect of the treatment process, generating knowledge from clinical and patient perspectives is valuable for health care providers, patients, and policy makers. The developed methodology can easily be applied to other treatments and health problems.