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Journal articles on the topic 'Health surveys'

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Published: 4 June 2021

Last updated: 29 July 2024

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1

Ferguson, TS, MK Tulloch-Reid, G. Gordon-Strachan, P. Hamilton, and RJ Wilks. "National Health Surveys and Health Policy: Impact of the Jamaica Health and Lifestyle Surveys and the Reproductive Health Surveys." West Indian Medical Journal 61, no. 4 (July 2012): 372–79. http://dx.doi.org/10.7727/wimj.2012.226.

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2

O'toole, Brian I. "Survey subjects and the quality of health surveys." Medical Journal of Australia 152, no. 4 (February 1990): 171–74. http://dx.doi.org/10.5694/j.1326-5377.1990.tb125140.x.

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3

Serraglio, Adrian, Norman Carson, and Zahid Ansari. "Comparison of health estimates between Victorian Population Health Surveys and National Health Surveys." Australian and New Zealand Journal of Public Health 27, no. 6 (December 2003): 645–48. http://dx.doi.org/10.1111/j.1467-842x.2003.tb00614.x.

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4

Anda, Robert F., Dennis L. Dodson, David F. Williamson, and Patrick L. Remington. "Health Promotion Data for State Health Departments: Telephone versus in-Person Survey Estimates of Smoking and Alcohol Use." American Journal of Health Promotion 4, no. 1 (September 1989): 32–36. http://dx.doi.org/10.4278/0890-1171-4.1.32.

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During 1988, more than 40 state health departments conducted telephone surveys to obtain state-specific population estimates of the prevalence of adult health behaviors and health practices. However, the comparability of estimates obtained from these telephone surveys with more expensive in-person surveys has not been assessed in an applied setting. This study compared the prevalence estimates of smoking and binge drinking obtained from a telephone survey (N = 1,492) with an in-person survey (N = 2,802) which were conducted by the state of Michigan during 1982–1983. Although the standard errors for the differences in the estimates for the two surveys were relatively large, the actual differences were consistently small within most age-, sex-, and education-specific groups. Despite certain limitations, telephone surveys provide a reasonable alternative to in-person surveys for estimating the prevalence of health behaviors. The data obtained from these surveys are being used to set state health objectives, to plan statewide health promotion programs, and to support public health legislation.

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5

Elliott, Michael. "Analysis of Health Surveys." Journal of the American Statistical Association 96, no. 453 (March 2001): 339–55. http://dx.doi.org/10.1198/jasa.2001.s382.

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6

Portnoy, Barry, Simon J. Craddock Lee, Jennifer Kincheloe, Nancy Breen, Jean L. Olson, Judy McCormally, and E. Richard Brown. "Independent State Health Surveys." Journal of Public Health Management and Practice 20, no. 5 (2014): E21—E33. http://dx.doi.org/10.1097/phh.0b013e3182a9c0ce.

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7

Lu, I.-Li. "Analysis of Health Surveys." Journal of Statistical Planning and Inference 100, no. 1 (January 2002): 89. http://dx.doi.org/10.1016/s0378-3758(01)00107-0.

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8

Dezateux, Carol. "Developments in health surveys." Lancet 341, no. 8850 (April 1993): 953. http://dx.doi.org/10.1016/0140-6736(93)91238-h.

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9

Nakano, Hironori, Kayoko Ishii, Aya Goto, Seiji Yasumura, Tetsuya Ohira, and Keiya Fujimori. "Development and Implementation of an Internet Survey to Assess Community Health in the Face of a Health Crisis: Data from the Pregnancy and Birth Survey of the Fukushima Health Management Survey, 2016." International Journal of Environmental Research and Public Health 16, no. 11 (June 1, 2019): 1946. http://dx.doi.org/10.3390/ijerph16111946.

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The Pregnancy and Birth Survey of the Fukushima Health Management Survey is a questionnaire survey that has been conducted annually since 2011 in Fukushima Prefecture. Since 2016, the survey has been available online as well as in paper form. This study aimed to determine whether making the survey available online improved response rates and to identify the characteristics of paper and online survey respondents and their results. Using LimeSurvey, we constructed an online survey environment that enabled responses via computer or mobile device. Respondents could choose whether to respond on paper or online. The response rate for the 2016 survey was 51.8%, an increase of 3.5% over the previous year. Of these responses, 15.8% were made online. Online respondents were mostly primiparous. Further, while there was no difference in the percentage of respondents who provided free responses, the amount written was higher in paper surveys than in online surveys. The combination of paper and online surveys increased convenience for respondents and contributed to improved response rates. In addition, paper surveys were superior in terms of allowing respondents to express their feelings and opinions.

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10

Kessler, Ronald C., Josep Maria Haro, Steven G. Heeringa, Beth-Ellen Pennell, and T. Bedirhan Üstün. "The World Health Organization World Mental Health Survey Initiative." Epidemiologia e Psichiatria Sociale 15, no. 3 (September 2006): 161–66. http://dx.doi.org/10.1017/s1121189x00004395.

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AbstractTo present an overview of the World Health Organization World Mental Health (WMH) Survey Initiative. The discussion draws on knowledge gleaned from the authors' participation as principals in WMH. WMH has carried out community epidemiological surveys in more than two dozen countries with more than 200,000 completed interviews. Additional surveys are in progress. Clinical reappraisal studies embedded in WMH surveys have been used to develop imputation rules to adjust prevalence estimates for within- and between-country variation in accuracy. WMH interviews include detailed information about sub-threshold manifestations to address the problem of rigid categorical diagnoses not applying equally to all countries. Investigations are now underway of targeted substantive issues. Despite inevitable limitations imposed by existing diagnostic systems and variable expertise in participating countries, WMH has produced an unprecedented amount of high-quality data on the general population cross-national epidemiology of mental disorders. WMH collaborators are in thoughtful and subtle investigations of cross-national variation in validity of diagnostic assessments and a wide range of important substantive topics. Recognizing that WMH is not definitive, finally, insights from this round of surveys are being used to carry out methodological studies aimed at improving the quality of future investigations.

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11

Aromaa, A. "Evaluation of Health Interview Surveys and Health Examination Surveys in the European Union." European Journal of Public Health 13, Supplement 1 (September 1, 2003): 67–72. http://dx.doi.org/10.1093/eurpub/13.suppl_1.67.

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12

Aromaa, A., P. Koponen, J. Tafforeau, and C. Vermeire. "Evaluation of Health Interview Surveys and Health Examination Surveys in the European Union." European Journal of Public Health 13, suppl 3 (September 1, 2003): 67–72. http://dx.doi.org/10.1093/eurpub/13.suppl_3.67.

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13

Ponce, Ninez A. "Centering Health Equity in Population Health Surveys." JAMA Health Forum 1, no. 12 (December 2, 2020): e201429. http://dx.doi.org/10.1001/jamahealthforum.2020.1429.

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14

Henderson, A. S., and A. F. Jorm. "Do mental health surveys disturb?" Psychological Medicine 20, no. 3 (August 1990): 721–24. http://dx.doi.org/10.1017/s0033291700017244.

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SynopsisWe have tested the assumption that mental health surveys do not cause distress. At the end of a two-wave community survey of psychiatric symptoms and personality factors, respondents were asked specific questions about how the interviews affected them. Being interviewed was distressing for some individuals, but it was seen as beneficial by a larger number. Those reporting distress were more likely to have had neurotic symptoms prior to both interviews and to have personality characteristics which would indicate proneness to distress. Whether the distress lasted beyond the interview situation is unknown. These results suggest that surveys of mental health should tell intended respondents about the possible effects of the interview, both positive and negative. Some studies should try to estimate the duration of any distress reported to have been induced.

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15

K., M., and Lu Ann Day. "Designing and Conducting Health Surveys." Population (French Edition) 47, no. 2 (March 1992): 498. http://dx.doi.org/10.2307/1533927.

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16

Phillips, Andrew W., Benjamin T. Friedman, Amol Utrankar, Andrew Q. Ta, Shalini T. Reddy, and Steven J. Durning. "Surveys of Health Professions Trainees." Academic Medicine 92, no. 2 (February 2017): 222–28. http://dx.doi.org/10.1097/acm.0000000000001334.

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17

Krauss, Marty Wyngaarden. "Designing and Conducting Health Surveys." Journal of Health Politics, Policy and Law 15, no. 3 (1990): 685–86. http://dx.doi.org/10.1215/03616878-15-3-685.

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18

Carroll-Pankhurst, Cindie. "Designing and Conducting Health Surveys." Medical Care 32, no. 6 (June 1994): 657. http://dx.doi.org/10.1097/00005650-199406000-00013.

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19

Tsakok, A. D. "Public health surveys in Singapore." Journal of Epidemiology & Community Health 52, no. 11 (November 1, 1998): 764. http://dx.doi.org/10.1136/jech.52.11.764.

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20

Aday, LU Ann. "Designing and Conducting Health Surveys." Journal For Healthcare Quality 20, no. 3 (May 1998): 41. http://dx.doi.org/10.1097/01445442-199805000-00015.

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21

Innes, John L. "Forest health surveys — A critique." Environmental Pollution 54, no. 1 (1988): 1–15. http://dx.doi.org/10.1016/0269-7491(88)90171-6.

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22

Andersen, Ronald. "Looking Back At Health Surveys." Health Affairs 27, no. 2 (March 2008): 585–86. http://dx.doi.org/10.1377/hlthaff.27.2.585-a.

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23

Choo, Vivien. "Health surveys in Latin America." Lancet 342, no. 8868 (August 1993): 429. http://dx.doi.org/10.1016/0140-6736(93)92837-j.

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24

Scott, Kenneth A., Emily Bacon, Emily McCormick Kraus, John F. Steiner, Gregory Budney, Jessica Bondy, L. Dean McEwen, and Arthur J. Davidson. "Evaluating Population Coverage in a Regional Distributed Data Network: Implications for Electronic Health Record–Based Public Health Surveillance." Public Health Reports 135, no. 5 (August 13, 2020): 621–30. http://dx.doi.org/10.1177/0033354920941158.

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Objective Electronic health records (EHRs) hold promise as a public health surveillance tool, but questions remain about how EHR patients compare with populations in health and demographic surveys. We compared population characteristics from a regional distributed data network (DDN), which securely and confidentially aggregates EHR data from multiple health care organizations in the same geographic region, with population characteristics from health and demographic surveys. Methods Ten health care organizations participating in a Colorado DDN contributed data for coverage estimation. We aggregated demographic and geographic data from 2017 for patients aged ≥18 residing in 7 counties. We used a cross-sectional design to compare DDN population size, by county, with the following survey-estimated populations: the county population, estimated by the American Community Survey (ACS); residents seeking any health care, estimated by the Colorado Health Access Survey; and residents seeking routine (eg, primary) health care, estimated by the Behavioral Risk Factor Surveillance System. We also compared data on the DDN and survey populations by sex, age group, race/ethnicity, and poverty level to assess surveillance system representativeness. Results The DDN population included 609 840 people in 7 counties, corresponding to 25% coverage of the general adult population. Population coverage ranged from 15% to 35% across counties. Demographic distributions generated by DDN and surveys were similar for many groups. Overall, the DDN and surveys assessing care-seeking populations had a higher proportion of women and older adults than the ACS population. The DDN included higher proportions of Hispanic people and people living in high-poverty neighborhoods compared with the surveys. Conclusion The DDN population is not a random sample of the regional adult population; it is influenced by health care use patterns and organizations participating in the DDN. Strengths and limitations of DDNs complement those of survey-based approaches. The regional DDN is a promising public health surveillance tool.

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25

Dawson, Julie. "Health and lifestyle surveys: beyond health status indicators." Health Education Journal 53, no. 3 (September 1994): 300–308. http://dx.doi.org/10.1177/001789699405300308.

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26

Evers, Silvia M. A. A. "Health for all indicators in health interview surveys." Health Policy 23, no. 3 (March 1993): 205–18. http://dx.doi.org/10.1016/0168-8510(93)90058-w.

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27

Kars-Marshall, Cri, Yvonne W. Spronk-Boon, and Marjan C. Pollemans. "National health interview surveys for health care policy." Social Science & Medicine 26, no. 2 (January 1988): 223–33. http://dx.doi.org/10.1016/0277-9536(88)90243-2.

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28

Comino, Elizabeth J., Oshana Hermiz, Jeff Flack, Elizabeth Harris, Gawaine Powell Davies, and Mark F. Harris. "Using population health surveys to provide information on access to and use of quality primary health care." Australian Health Review 30, no. 4 (2006): 485. http://dx.doi.org/10.1071/ah060485.

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Objective: Currently, primary health care (PHC) is under-represented in health statistics due to the lack of a comprehensive PHC data collection. This research explores the utility of population health surveys to address questions relating to access to and use of PHC, using diabetes as an example. Methods: Drawing on published material relating to diabetes management, we developed a conceptual framework of access to and use of quality PHC. Using this framework we examined three recent population-based health surveys ? the 2001 National Health Survey, 2002?03 NSW Health Survey, and AusDiab ? to identify relevant information collection. Results: We identified seven domains comprising aspects of quality PHC for people with diabetes. For each domain we proposed associated indicators. In critiquing the three population health surveys in relation to these indicators, we identified strengths and weaknesses of the data collections. Conclusion: This approach could inform the development of questions and extension of population health surveys to provide a better understanding of access to and use of quality PHC in Australia. The additional information would complement other data collections with a communitybased perspective and contribute to the develop- ment of PHC policy.

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29

Evans, William N., Helen Levy, and Kosali I. Simon. "Data Watch: Research Data in Health Economics." Journal of Economic Perspectives 14, no. 4 (November 1, 2000): 203–16. http://dx.doi.org/10.1257/jep.14.4.203.

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In this paper, we discuss some important data sets that can be used by economists interested in conducting research in health economics. We describe six types of data sets: health components of data sets traditionally used by economists; longitudinal surveys of health and economic behavior; data on employer-provided insurance; cross-sectional surveys of households that focus on health; data on health care providers; and vital statistics. We summarize some of the leading surveys, discuss the availability of the data, identify how researchers have utilized these data and when possible, include a web address that contains more detailed information about each survey.

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30

Eickhoff-Shemek, JoAnn M., and Kay F. Ryan. "A Comparison of Omaha Worksite Health Promotion Activities to the 1992 National Survey with a Special Perspective on Program Intervention." American Journal of Health Promotion 10, no. 2 (November 1995): 132–39. http://dx.doi.org/10.4278/0890-1171-10.2.132.

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Purpose. The purpose of this study was to compare the results from a survey of Omaha worksite health promotion activities with the results of a 1992 national survey. Comparisons were made on: (1) the kinds of health promotion activities offered, (2) progress toward the Healthy People 2000 worksite objectives, (3) types of program intervention offered, and (4) administrative factors. Design. A one-time, written, mail-out/mail-back survey design was used. Setting. The study took place in Omaha, Nebraska. Subjects. All area public and private worksites with 250 or more employees were sent surveys. Individuals who were preselected and identified as the best qualified within the company completed the survey instrument. Of the 176 worksites surveyed, 86 completed the survey (49%). Measures. Descriptive statistics (percentages) were used to compare the two surveys on kinds of programs offered, progress toward Healthy People 2000 related to worksite health promotion, the types of program intervention offered, and administrative factors. Results. Generally, a greater percentage of respondent worksites from the national survey are offering more health promotion activities and have made more progress toward the Healthy People 2000 worksite objectives than the Omaha worksites. Results from both surveys showed that low levels of intervention are more prevalent than high levels of intervention, and that health promotion activities in most worksites are coordinated by human resources departments and not by someone professionally prepared in health education. Conclusions. Traditionally, major goals of worksite health promotion programs have focused on important organizational outcomes such as improved productivity/morale, reduction in absenteeism, and health care cost-containment. It is important to recognize, however, that low levels of intervention have less impact than more intensive programs on these desired outcomes. Future goals for local and national worksite health promotion programs may need to encourage implementation of more intensive intervention programs.

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31

Mavis, Brian E., and Joseph J. Brocato. "Postal Surveys versus Electronic Mail Surveys." Evaluation & the Health Professions 21, no. 3 (September 1998): 395–408. http://dx.doi.org/10.1177/016327879802100306.

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32

Husain, Marium, Audra Phillips, Gabriel Tinoco, James Lin Chen, and David A. Liebner. "Patient-reported global health predicts adverse health outcomes in a cohort of patients with advanced sarcoma." Journal of Clinical Oncology 38, no. 15_suppl (May 20, 2020): e23547-e23547. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e23547.

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e23547 Background: Given the rare nature of sarcoma cancers and the sometimes severe treatment-related effects of chemotherapy, many patients with sarcoma face quality of life issues during treatment. Unplanned hospital admission and emergency room (ER) visits can occur from uncontrolled symptoms and ultimately delay treatment regimens and negatively impact quality of life. The PROMIS Global Health v1.2 (PROMIS-10) surveys are validated tools to assess patients’ physical and mental well-being at the time of the survey. We sought to evaluate the correlation between PROMIS-10 scores and adverse outcomes of interest, including unplanned admissions/ED visits and patient mortality. Methods: All patients currently seen in the Sarcoma Clinics at Ohio State University routinely complete the PROMIS-10 survey at each clinic visit. For this pilot study, we collected the raw and normalized t-scores for PROMIS-10 surveys for all patients consented to The Ohio State University Sarcoma Registry (OSU-14242) from 6/1/2018 to 11/20/2019. We also collected data on unplanned hospital admission/ED visits and mortality data for each patient. Results: A total of 864 surveys for 112 patients were collected for the study period. The median number of surveys answered per patient was 6. Mean global physical t-scores (43.7 ± 8.5) and mental t-scores (47.9 ± 9.2) were lower than reference scores for the general US population (p < 0.001). 109 of 112 patients experienced an unplanned admission or ED visit during the study, with a total of 270 such encounters during the study period. PROMIS-10 scores were slightly but significantly lower for patients experiencing an admission or ED visit within 30 days of taking the survey (physical: 41.9 vs 44.1, p = 0.006; mental: 46.4 vs 48.2, p = 0.035). A total of 26 patients died during the study period; surveys completed prior to death were consistent with a greater level of physical and mental distress, with the median physical t-score = 34.9 (range: 23.5 – 50.8) and mental t-score = 43.5 (range: 33.8 – 67.6). Conclusions: We showed that we are able to obtain worthwhile data to objectively evaluate patients’ physical and mental well-being through survey data during cancer treatment. We are currently performing additional confirmatory analysis of the predictive value of the PROMIS-10 survey for adverse events and for treatment-related complications.

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33

MATZON, KNUD BRAGH. "Health profile surveys in the context of healthy city development." Health Promotion International 4, no. 2 (1989): 145–48. http://dx.doi.org/10.1093/heapro/4.2.145.

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34

Narring, Fran�oise, and Pierre-Andr� Michaud. "Methodological issues in adolescent health surveys: The case of the Swiss multicenteradolescent survey on health." Sozial- und Pr�ventivmedizin SPM 40, no. 3 (May 1995): 172–82. http://dx.doi.org/10.1007/bf01318638.

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35

Zimmermann, Polly Gerber. "Health care customer satisfaction surveys still running amok: Surveys degrade nurses." Journal of Emergency Nursing 26, no. 2 (April 2000): 174–77. http://dx.doi.org/10.1016/s0099-1767(00)90066-7.

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36

Kasprzyk, Daniel, Brenda G. Cox, and Steven B. Cohen. "Methodological Issues for Health Care Surveys." Contemporary Sociology 15, no. 4 (July 1986): 631. http://dx.doi.org/10.2307/2069329.

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37

Boyce, Cheryl A., and Virginia S. Cain. "Disentangling Health Disparities Through National Surveys." American Journal of Public Health 97, no. 1 (January 2007): 10. http://dx.doi.org/10.2105/ajph.2006.103960.

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38

White, Edward, and Charles Brooker. "Community mental health nursing: national surveys." Mental Health Practice 2, no. 2 (October 1, 1998): 8–16. http://dx.doi.org/10.7748/mhp.2.2.8.s12.

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39

Link, Michael W., and Ali H. Mokdad. "Alternative Modes for Health Surveillance Surveys." Epidemiology 16, no. 5 (September 2005): 701–4. http://dx.doi.org/10.1097/01.ede.0000172138.67080.7f.

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40

Holle, Rolf, Matthias Hochadel, Peter Reitmeir, Christa Meisinger, and H. Erich Wichmann. "Prolonged Recruitment Efforts in Health Surveys." Epidemiology 17, no. 6 (November 2006): 639–43. http://dx.doi.org/10.1097/01.ede.0000239731.86975.7f.

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41

Lepkowski, Jim. "Book Review: Analysis of Health Surveys." Field Methods 13, no. 2 (May 2001): 216–20. http://dx.doi.org/10.1177/1525822x0101300208.

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42

Ricketts, Tom. "Consumer satisfaction surveys in mental health." British Journal of Nursing 1, no. 10 (September 24, 1992): 523–27. http://dx.doi.org/10.12968/bjon.1992.1.10.523.

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43

Todorov, Alexander. "Context Effects in National Health Surveys." Public Opinion Quarterly 64, no. 1 (2000): 65–76. http://dx.doi.org/10.1086/316760.

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44

Kelleher, Kelly J., and Jeff Bridge. "National Surveys of Child Mental Health." Journal of Developmental & Behavioral Pediatrics 33, no. 1 (January 2012): 75. http://dx.doi.org/10.1097/dbp.0b013e3182404b5a.

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45

Corsi, D. J., M. Neuman, J. E. Finlay, and S. Subramanian. "Demographic and health surveys: a profile." International Journal of Epidemiology 41, no. 6 (November 12, 2012): 1602–13. http://dx.doi.org/10.1093/ije/dys184.

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Cho, Young Ik, Timothy P. Johnson, and Jonathan B. VanGeest. "Enhancing Surveys of Health Care Professionals." Evaluation & the Health Professions 36, no. 3 (August 23, 2013): 382–407. http://dx.doi.org/10.1177/0163278713496425.

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47

JAGGER, CAROL, and KAREN RITCHIE. "A Census of European Health Surveys." International Journal of Epidemiology 25, no. 1 (1996): 227. http://dx.doi.org/10.1093/ije/25.1.227.

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48

Jagger, Carol, and Karen Ritchie. "A Census of European Health Surveys." European Journal of Public Health 5, no. 4 (1995): 297. http://dx.doi.org/10.1093/eurpub/5.4.297.

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49

Davis, R. E., M. P. Couper, N. K. Janz, C. H. Caldwell, and K. Resnicow. "Interviewer effects in public health surveys." Health Education Research 25, no. 1 (September 17, 2009): 14–26. http://dx.doi.org/10.1093/her/cyp046.

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50

Brogan, Donna, Brenda G. Cox, and Steven B. Cohen. "Methodological Issues for Health Care Surveys." Journal of the American Statistical Association 82, no. 400 (December 1987): 1189. http://dx.doi.org/10.2307/2289414.

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