GP information (4)

GP information (4)

Documentation first General Practitioner data collection (1992-1993)
Documentation second General Practitioner data collection (2000-2001)
Documentation third General Practitioner data collection (2005-2006)
Documentation fourth General Practitioner data collection (2010)
Documentation fifth General Practitioner data collection (2016)

†: the dates mentioned refer to the investigation period in which the corresponding GP data were collected, not to the respondent cycles involved.
LASAFg01, LASAFg00 (nonresponse)

Contact:  Sascha de Breij

Background

This is the fourth data collection at general practitioners (GPs). The first data collection was done in 1992/1993 by D. Kriegsman and B. Penninx (LASABg01.sav and LASABg01_docu 2008.doc). The second data collection was done in 2000/2001 by B. Schalk. (Data can be found in LASACg01.sav, LASACg01_nonresponsbestand.sav and LASACg01_nonresponslabels.doc). The third was done in 2005 by L. Schaap (Data can be found in LASAEg01.sav, LASAEg01_nonresponsbestand.sav and LASAEg01_nonresponslabels.doc).

Measurement instruments in LASA

GPs were approached if:
– respondents had joined the main interview in 2005/2006 (F-cycle) (N=2165) and had given informed consent (2066).
There were 10 respondents of whom no information on GPs was known. Therefore, a number of 561 GPs were approached, providing information about 2056 respondents.

Data collection

The data collection procedures are shown in figure 1 (pdf). The GPs were asked to fill in a questionnaire for each respondent. All GPs with less than 20 respondents were sent an introduction letter and a number of questionnaire corresponding with the number of respondents in their practice. GPs with 20 or more respondents were sent an introduction letter together with an example of the questionnaire. These GPs were called one week later. They were asked whether they wanted to fill in the questionnaires themselves or if they wanted to let a researcher fill in the questionnaires at their practice. The GPs had the option to receive a voucher of €7,50 for each completed questionnaire or to donate € 7,50 to charity (WorldGranny) for each completed questionnaire.
If the questionnaires were not returned after four weeks the GPs were reminded with a letter (when the GPs had less than 20 respondents) or by a phone call (when the GPs had 20 or more respondents). The second reminder was another four weeks later and the last reminder was two weeks later. After receiving completed questionnaires the GPs received a thank you letter, accompanied by vouchers of €7,50 if this option was chosen.

Results

In total 1444 questionnaires were completed (70.2% of the 2056 respondents). The results of the data collection can be found here.

Information about the data collection

This current questionnaire is similar to the previous questionnaires used during the third GP data collection in 2005, except for the questions about weight problems (now specifically asked for overweight and undernutrition) and the more in-depth questions on osteoarthritis which were added to the current questionnaire.

Use of data

To increase reliability of the presence of chronic diseases, algorithms (decision trees) have been developed using data on chronic diseases in the main interview (self report of chronic diseases), the medical interview (inspections of medicine bottles) and through the medical records of general practitioners. Algorithms have been developed for diabetes, rheumatoid arthritis and cardiovascular diseases.

Questionnaires

Under Construction

Variable information

LASAFg01
(pdf, under construction)

Availability of information per wave
1

 BCDE
2B*
FGH

3B*
MB*IJK*
GP-information

XX-XXX-XX---

1 More information about the LASA data collection waves is available here.

* 2B=baseline second cohort;
3B=baseline third cohort;
MB=migrants: baseline first cohort;
K=future wave 2021-2022

Previous use in LASA

Kriegsman et al. (1996) state that patients’ self-reports on selected chronic diseases are fairly accurate, with the exceptions of atherosclerosis and arthritis. Overreporting and underreporting of specific diseases was associated with several personal characteristics. The results suggested that the tendency to overreport or underreport may be explained by denial by the patient, the tendency of patients to label symptoms or inaccuracy of GP records.

Galenkamp et al. (2014) compared self-reports with GP reported diseases in 2009 and examined how the prevalence of overreporting and underreporting had changed since 1992. Results showed that overreporting of chronic diseases became significantly more common over time, whereas under-reporting became less common. Agreement and change in agreement over time differed across the specific diseases. Underreporting was associated with male gender; over-reporting with female gender, worse self-rated health, and worse physical functioning. Older adults were less accurate in their self-reports than younger adults.

Studies that used the GP data were amongst others:

  • Kleipool, E.E.F., Hoogendijk, E.O., Trappenburg, M.C., Handoko, M.L., Huisman, M., Peters, M.J.L., Muller, M.J. (2018). Frailty in Older Adults with Cardiovascular Disease: Cause, Effect or Both? Aging and Disease, 9, 489-497.
  • Licht-Strunk, E., Bremmer, M.A., Van Marwijk, H.W.J., Deeg, D.J.H., Hoogendijk, W.J.G., De Haan, M., Van Tilburg, W., Beekman, A.T.F. (2004). Depression in older persons with versus without vascular disease in the open population: Similar depressive symptom patterns, more disability. Journal of Affective Disorders, 83, 155-160.
  • Marijnissen, R.M., Wouts, L., Schoevers, R.A., Bremmer, M.A., Beekman, A.T.F., Comijs, H.C., Oude Voshaar, R.C. (2014). Depression in context of low neuroticism is a risk factor for stroke A 9-year cohort study. Neurology, 83, 1692-1698.
  • Pouwer, F., Beekman, A.T.F., Nijpels, G., Dekker, J.M., Snoek, F.J., Kostense, P.J., Heine, R.J., Deeg, D.J.H. (2003). Rates and risks for co-morbid depression in patients with Type 2 diabetes mellitus: Results from a community-based study. Diabetologia, 46, 892-898.
  • Schram, M.T., Frijters, D.H.M., Van de Lisdonk, E.H., Ploemacher, J., De Craen, A.J.M., De Waal, M.W.M., Van Rooij, F.J., Heeringa, J., Hofman, A., Deeg, D.J.H., Schellevis, F.G. (2008). Setting and registry characteristics affect the prevalence and nature of multimorbidity in the elderly. Journal of Clinical Epidemiology, 61, 1104-1112.
  • Verweij, L.M., Van Schoor , N.M., Deeg, D.J.H., Dekker, J., Visser, M. (2009). Physical activity and incident clinical knee osteoarthritis in older adults. Arthritis & Rheumatism (Arthritis Care & Research), 61, 2, 152-157.
  • Yoneda, T.B., Rush, J., Graham, E.K., Berg, Al, Comijs, H.C., Katz, M.J., Lipton, R.B., Johansson, B., Mroczek, D.K., Piccinin, A.M. (2020). Increases in Neuroticism May Be an Early Indicator of Dementia: A Coordinated Analysis. The Journals of Gerontology: Series B, Volume 75, 2, 251-262.


References

  1. Galenkamp H, Huisman M, Braam AW, Schellevis FG, Deeg DJH. Disease prevalence based on older people’s self-reports increased, but patient-general practitioner agreement remained stable, 1992-2009.  Journal of Clinical Epidemiology. 2014, 67 (7): 773-780.
  2. Kriegsman, DM, Penninx BW, van Eijk JT, Boeke AJ, Deeg DJ. Self-reports and general practitioner information on the presence of chronic diseases in community-dwelling elderly. A study on the accuracy of patients’ self-reports and on determinants of inaccuracy. J Clin Epidemiol. 1996 Dec; 49 (12):1407-17.


Date of last update: April 20, 2020 (LvZ)