Indicadores Financieros y Económicos

The Delphi Method and Scientific Research

Juan Gaytán Cortés
Universidad de Guadalajara, México

The Delphi Method and Scientific Research

Mercados y Negocios, núm. 52, pp. 131-146, 2024

Universidad de Guadalajara

Science has evolved to think about space, time and the relations of subject and object, as a highly abstract regulatory idea and not just as a synonym for models and norms to be followed. The paths of science must guarantee all agreements, those based on procedures using philosophy and mathematical concepts for the explanation of reality (positivism) and also those based on principles to understand and interpret social phenomena in their reality, relationships, values, attitudes, beliefs, habits and representations.

Qualitative research deals with the level of reality that cannot or should not be quantified, it works with the universe of meanings, motives, aspirations, values and attitudes. This level of reality is not visible, it must be exposed by the researcher, (Minayo, 2009).

In the exact sciences, future events can be predicted objectively from existing explanations: explanation and prediction have the same logical structure. The future depends not only on the past, but also on the image of the future formed in the present by those who carry out actions. The Delphi method has been used for predictions in topics or areas that require the flexibility of well-informed human judgment, to process diverse and unstructured information.

The Delphi method has been used in various fields in defense, health, tourism, education, and business. Science in general requires a prediction methodology different from the one used to make explanations in the exact sciences, thus justifying the consideration of some methodological innovations for the realization of predictions, such as the systematic use of expert judgment, simulation processes and operational games.

The subjective judgment of experts in non-exact disciplines is justified in situations of uncertainty, when the problem is very complex, when the evidence is insufficient, unpublished, or when objective information is lacking (Jones & Hunter, 1995). The Delphi technique seeks to obtain the degree of consensus or agreement of specialists on the problem posed, using the results of previous research, instead of leaving the decision to a single profesional, (Varela-Ruiz, Díaz-Bravo & García-Durán, 2012).

The Delphi method is classified as one of the general methods of foresight, which seeks to approach the consensus of a group of experts based on the analysis and reflection of a defined problem. (Varela-Ruiz, Díaz-Bravo & García-Durán, 2012). The defined problem is presented in a formal proposal that should include a brief description of the project, the objectives it pursues, the expected number of rounds, and the estimated time of the process, (Gordon, 1994).

The Delphi method has proven to be a robust method of scientific research despite some limitations and difficulties being discussed in the literature. The development and dissemination of the Delphi method has been growing and exponential, reaching an outstanding projection in different areas of knowledge, (Cabero & Infante, 2014; Maxey & Kezar, 2015).

The Delphi method is a qualitative technique, although there are authors who argue that it is mixed and others believe that in its final phase it is quantitative (Sekayi & Kennedy, 2017). The method allows you to know the opinion of a group of experts, which is called a panel, addressing a specific problem in a structured way, the interaction between the different members is carried out through a questionnaire, (McMillan, King & Tully, 2016; Diamond, et al. 2014).

In the 1950s, in Santa Monica, United States, experts from the RAND Corporation, an acronym for Research and Development, sponsored by the U.S. Air Force in order to investigate the impact of technology on war, carried out the Delphi project, which consists of using the judgment of experts about specific events or topics. The name Delphi in English translation is Delphi, its name endorses its initial predictive use that alludes to the sanctuary of Apollo, a sacred and famous place, which functioned as an oracle, and where the fortune teller transmitted the answers of the god to the questions that were asked.

The results of the RAND research, presented in the report: On the epistemology of the inexact sciences, published by The Institute of Management Science, in which seven experts were asked about the future of the U.S. arsenal. The report concludes that prediction based on expert opinion is acceptable in disciplines that are not sufficiently developed to have scientific laws (Helmer & Rescher, 1959).

Methodological foundations of Delphi. The development of the Delphi method made its way into a landscape dominated by positivist thinking. The method must guarantee anonymity, establish an iterative process through feedback, and the group's response must be oriented towards a measure. The research carried out by Ernesto López-Gómez, (2018), mentions that the fundamental methodological parameters to be considered in its development are the following:

1. Selection and composition of the panel of experts

2. Number of experts

3. Panel Quality

4. Iterative process in rounds

5. The criteria of consensus and stability for the completion of the process

Selection and shaping. The selection and composition of the panel of experts guarantees the quality of the process and its results. The researcher must identify potential experts under inclusion criteria, since a random or unsubstantiated selection is not acceptable. The research problem and the very nature of the study condition the profile of the experts, specialists, or facilitators in the panel to be formed.

In the research carried out by Pill (1971), he mentions that in order to delimit the requirements and attributes, the possible expert candidate must have background, experience in the subject to be addressed and disposition. Steurer (2011) proposes nominating as experts those who have more than five publications on the chosen topic in a couple of journals during the last three years. However, authors such as Kennedy (2004) & Price (2005) consider it problematic to define an expert only as a specialist in his or her field, so it is also important to take into account practice-based knowledge and up-to-date experience.

Panel quality. Quality can be measured using different techniques, methods or procedures to estimate the level of expert knowledge (Landeta & Landeta Rodriguez, 1999; Blasco, López & Mengual, 2010), taking into account indirect indicators such as publications on the subject, citations received, years of experience, training, positions held, dedication and professional trajectory. The quality of the panel is justified based on the criteria applied in the process of selecting and forming experts. The group that makes up the panel endorses quality with the background of the experts, their professional training, the research carried out and the professional experience (López-Gómez, 2018).

Iterative process in rounds. The iterative process consists of the controlled exchange of information between the person applying the Delphi model and the experts who make up the panel. The iteration is organized in rounds, carrying out the study through interrogations through a questionnaire designed and elaborated, taking into account the object and objectives of the research. In most applications, the Delphi method is developed in two rounds, usually in three, and rarely in more, (Steurer, 2011).

Completion of the Delphi. The criteria for finalizing Delphi must consider the measure of consensus and stability in the panel's responses, which guide data analysis and decision-making. Consensus, in the study carried out by Esther Martínez Piñeiro (2003), mentions that consensus responds to the philosophy of the technique itself, since its main objective is, precisely, the convergence between the opinions of the participants. In achieving consensus of expert opinions, there is no universal reference, however, in the research carried out by (Pozo, Gutiérrez & Rodríguez, 2007), the degree of convergence of individual estimates must coincide at a minimum of 80%.

The Internet and the Delphi Method. The use of the internet facilitates the application of the method, eliminating geographical distance, facilitating and allowing the participation of a greater number of experts, maintaining the anonymity of the participants, also, avoiding the influence of the answers of any member of the panel, in addition to being economical, (Humphrey-Murto, et al. 2017).

Economic and financial indicators are useful tools that benefit organizations by facilitating timely and appropriate decision-making in relation to their corporate and financial strategies.

Next, the evolution of some economic and financial indicators of the Mexican environment is described and shown to facilitate decision-making related to personal and business strategies in an integral manner.

  1. 1. National Consumer Price Index (INPC, Spanish)
  2. 2. The Price and Quotation Index of the Mexican Stock Exchange (IPC, Spanish)
  3. 3. Exchange rate
  4. 4. Equilibrium interbank interest rate (TIIE, Spanish)
  5. 5. CETES rate of return
  6. 6. Investment units (UDIS, Spanish)

1. NATIONAL CONSUMER PRICE INDEX (INPC)

Born in 1995 and reflecting changes in consumer prices, it measures the general increase in prices in the country. It is calculated fortnightly by the Bank of Mexico and INEGI (2021). INPC is published in the Official Gazette of the Federation on the 10th and 25th of each month. The reference period is the second half of July 2018.

Table 1
Accumulated inflation in the year (Base: 2nd. half of July 2018=100 with data provided by Banco de México)
Period201320142015201620172018201920202021202220232024
January0.790.90-0.090.381.700.530.090.480.860.590.760.89
February1.461.150.090.822.290.910.060.901.501.431.240.99
March1.991.430.510.972.921.240.440.852.342.431.511.28
April1.811.240.250.653.040.900.50-0.172.672.981.49
May0.950.91-0.260.202.920.730.210.222.883.171.27
June1.121.09-0.090.313.181.120.270.763.434.041.37
July1.141.420.060.573.571.660.651.434.044.811.86
August1.311.730.270.864.082.260.631.824.245.542.42
September1.612.180.271.474.412.690.892.064.886.192.88
October2.772.741.162.095.063.221.442.685.766.793.27
November4.573.571.712.896.154.102.262.766.977.413.93
December5.214.082.133.366.774.832.833.157.357.824.66
Source: Own elaboration (INEGI, 2024). Route: Indicadores económicos de coyuntura > Índices de precios > Índice nacional de precios al consumidor. Base segunda quincena de julio de 2018=100 > Mensual > Índice > Índice general

Investment units 2013-2023 (At the end of the year)
Graph 11
Investment units 2013-2023 (At the end of the year)
Source: Own elaboration (BANXICO, 2024). https://www.banxico.org.mx/SieInternet/consultarDirectorioInternetAction.do?accion=consultarCua dro&idCuadro=CP150&locale=es

Inflation in Mexico (accumulated  January-March 2024)
Graph 2
Inflation in Mexico (accumulated January-March 2024)
Source: Own elaboration (INEGI, 2024). Route: Indicadores económicos de coyuntura > Índices de precios > Índice nacional de precios al consumidor. Base segunda quincena de julio de 2018=100 > Mensual > Índice > Índice general

2. THE PRICE AND QUOTATION INDEX OF THE MEXICAN STOCK EXCHANGE (IPC)

Represents the change in the values traded on the Mexican Stock Exchange concerning the previous day to determine the percentage of rising or falling of the most representative shares of the companies listed therein.

Table 2
The Price and Quotation Index of the Mexican Stock Exchange (Base: October 1978, 0.78=100)
Period201320142015201620172018201920202021202220232024
January45,27840,87940,95143,63147,00150,45643,98844,86242,98651,33154,56457,373
February44,12138,78344,19043,71546,85747,43842,82441,32444,59353,40152,75855,414
March44,07740,46243,72545,88148,54246,12543,28134,55447,24656,53753,90457,369
April42,26340,71244,58245,78549,26148,35444,59736,47048,01051,41855,12156,728
May41,58841,36344,70445,45948,78844,66342,74936,12250,88651,75352,736
June40,62342,73745,05445,96649,85747,66343,16137,71650,29047,52453,526
July40,83843,81844,75346,66151,01249,69840,86337,02050,86848,14454,819
August39,49245,62843,72247,54151,21049,54842,62336,84153,30544,91953,021
September40,18544,98642,63347,24650,34649,50443,01137,45951,38644,62750,875
October41,03945,02844,54348,00948,62643,94343,33736,98851,31049,92249,062
November42,49944,19043,41945,28647,09241,73342,82041,77949,69951,68554,060
December42,72743,14642,99845,64349,35441,64043,54144,06753,27248,46457,386
Source: Own elaboration (BANXICO, 2024). https://www.banxico.org.mx/SieInternet/consultarDirectorioInternetAction.do?sector=7&accion=consultarCuadro&idCuadro=CF57&locale=es

The Price and Quotation Index of the Mexican Stock Exchange, 2013 - 2023 (Score at the end of each year)
Graph 3
The Price and Quotation Index of the Mexican Stock Exchange, 2013 - 2023 (Score at the end of each year)
Source: Own elaboration (BANXICO, 2024). https://www.banxico.org.mx/SieInternet/consultarDirectorioInternetAction.do?sector=7&accion=consultarCuadro&idCuadro=CF57&locale=es

The Price and Quotation Index of the Mexican Stock Exchange, January-April 2024 (Score at the end of each month)
Graph 4
The Price and Quotation Index of the Mexican Stock Exchange, January-April 2024 (Score at the end of each month)
Source: Own elaboration (BANXICO, 2024). https://www.banxico.org.mx/SieInternet/consultarDirectorioInternetAction.do?sector=7&accion=consultarCuadro&idCuadro=CF57&locale=es

3. EXCHANGE RATE

It is the value of the Mexican peso concerning the dollar calculated with the daily average of the five most important banks in the country, which reflects the spot price (cash), negotiated between banks. It is highly related to Inflation, the interest rate, and the Mexican Stock Exchange.

Table 3
Exchange rate (National currency per US dollar, parity at the end of each period)
Period201320142015201620172018201920202021202220232024
January12.7113.3714.6918.4521.0218.6219.0418.9120.2220.7418.7917.23
February12.8713.3014.9218.1719.8318.6519.2619.7820.9420.6518.4017.06
March12.3613.0815.1517.4018.8118.3319.3823.4820.4419.9918.1116.68
April12.1613.1415.2219.4019.1118.8619.0123.9320.1820.5718.0717.16
May12.6312.8715.3618.4518.5119.7519.6422.1819.9219.6917.56
June13.1913.0315.5718.9117.9020.0619.2123.0919.9120.1317.07
July12.7313.0616.2118.8617.6918.5519.9922.2019.8520.3416.73
August13.2513.0816.8918.5817.8819.0720.0721.8920.0620.0916.84
September13.0113.4517.0119.5018.1318.9019.6822.1420.5620.0917.62
October12.8913.4216.4518.8419.1519.8019.1621.2520.5319.8218.08
November13.0913.7216.5520.5518.5820.4119.6120.1421.4519.4017.14
December13.0814.7217.2120.7319.7919.6818.8719.9120.4719.4716.89
Source: Own elaboration (BANXICO, 2024). https://www.banxico.org.mx/SieInternet/consultarDirectorioInternetAction.do?sector=6&accion=consultarCuadro&idCuadro=CF102&locale=es NOTE: Exchange rate FIX by The Banco de México, used for settling obligations denominated in foreign currency. Quote at the end

Exchange rate (National currency per US dollar, 2013-2024, (FIX parity at the end of each year)
Graph 5
Exchange rate (National currency per US dollar, 2013-2024, (FIX parity at the end of each year)
Source: Own elaboration (BANXICO, 2024). https://www.banxico.org.mx/SieInternet/consultarDirectorioInternetAction.do?sector=6&accion=consultarCuadro&idCuadro=CF102&locale=es

Exchange rate (National currency per US dollar, January-April 2024, FIX parity at the end of each month)
Graph 6
Exchange rate (National currency per US dollar, January-April 2024, FIX parity at the end of each month)
Source: Own elaboration (BANXICO, 2024). https://www.banxico.org.mx/SieInternet/consultarDirectorioInternetAction.do?sector=6&accion=co nsultarCuadro&idCuadro=CF102&locale=es

4. EQUILIBRIUM INTERBANK INTEREST RATE (TIIE)

On March 23, 1995, the Bank of Mexico, to establish an interbank interest rate that better reflects market conditions, released the Interbank Equilibrium Interest Rate through the Official Gazette of the Federation.

Table 4
Equilibrium interbank interest rate (28-day quote)
Period201320142015201620172018201920202021202220232024
January4.843.783.293.566.157.668.597.504.475.7210.8211.50
February4.803.793.294.056.617.838.547.294.366.0211.2711.50
March4.353.813.304.076.687.858.516.744.286.3311.4311.44
April4.333.803.304.076.897.858.506.254.286.7311.5411.25
May4.303.793.304.107.157.868.515.744.297.0111.51
June4.313.313.304.117.368.108.495.284.327.4211.49
July4.323.313.314.597.388.118.475.194.528.0411.51
August4.303.303.334.607.388.108.264.764.658.5011.51
September4.033.293.334.677.388.128.044.554.758.8911.50
October3.783.283.305.117.388.157.974.514.989.5611.50
November3.803.313.325.577.398.347.784.485.1310.0011.50
December3.793.313.556.117.628.607.554.495.7210.5311.50
Source: Own elaboration (BANXICO, 2024). https://www.banxico.org.mx/SieInternet/consultarDirectorioInternetAction.do?sector=18&accion=c onsultarCuadro&idCuadro=CF101&locale=es

Equilibrium interbank interest rate, 2013- 2023 (at the end of each year)
Graph 7
Equilibrium interbank interest rate, 2013- 2023 (at the end of each year)
Source: Own elaboration (BANXICO, 2024). https://www.banxico.org.mx/SieInternet/consultarDirectorioInternetAction.do?sector=18&accion=c onsultarCuadro&idCuadro=CF101&locale=es

Equilibrium interbank interest rate, January-April 2024 (28-day quote)
Graph 8
Equilibrium interbank interest rate, January-April 2024 (28-day quote)
Source: Own elaboration (BANXICO, 2024). https://www.banxico.org.mx/SieInternet/consultarDirectorioInternetAction.do?sector=18&accion=c onsultarCuadro&idCuadro=CF101&locale=es

5. CETES RATE OF RETURN

Table 5
CETES rate of return (28-day)
Period201320142015201620172018201920202021202220232024
January4.153.142.673.085.837.257.957.044.225.5010.8011.28
February4.193.162.813.366.067.407.936.914.025.9411.0411.00
March3.983.173.043.806.327.478.026.594.086.5211.3410.90
April3.823.232.973.746.507.467.785.844.066.6811.2711.04
May3.723.282.983.816.567.518.075.384.076.9011.25
June3.783.022.963.816.827.648.184.854.037.5611.02
July3.852.832.994.216.997.738.154.634.358.0511.09
August3.842.773.044.246.947.737.874.504.498.3511.07
September3.642.833.104.286.997.697.614.254.699.2511.05
October3.392.903.024.697.037.697.624.224.939.0011.26
November3.392.853.025.157.027.837.464.285.059.7011.78
December3.292.813.145.617.178.027.254.245.4910.1011.26
Source: Own elaboration (BANXICO, 2024). https://www.banxico.org.mx/SieInternet/consultarDirectorioInternetAction.do?sector=22&accion=c onsultarCuadro&idCuadro=CF107&locale=es

CETES rate of return 2013- 2023 (at the end of each year)
Graph 9
CETES rate of return 2013- 2023 (at the end of each year)
Source: Own elaboration (BANXICO, 2024). https://www.banxico.org.mx/SieInternet/consultarDirectorioInternetAction.do?sector=22&accion=c onsultarCuadro&idCuadro=CF107&locale=es

CETES rate of return, January-April 2024 (at the end of each month)
Graph 10
CETES rate of return, January-April 2024 (at the end of each month)
Source: Own elaboration (BANXICO, 2024). https://www.banxico.org.mx/SieInternet/consultarDirectorioInternetAction.do?sector=22&accion=c onsultarCuadro&idCuadro=CF107&locale=es

6. INVESTMENT UNITS (UDIS)

The UDI is a unit of account of constant real value to denominate credit titles. It does not apply to checks, commercial contracts, or other acts of commerce.

Table 6
Investment units (value concerning pesos)
Period201320142015201620172018201920202021202220232024
January4.895.105.295.415.625.976.256.446.647.127.698.06
February4.925.135.295.435.696.006.256.466.707.187.748.11
March4.945.155.305.445.716.026.266.496.757.247.778.11
April4.975.155.325.455.756.036.286.436.797.317.788.13
May4.965.135.295.425.756.016.276.426.817.337.78
June4.955.135.285.425.756.016.266.446.837.367.77
July4.955.145.285.425.766.046.276.496.877.437.79
August4.955.165.295.445.796.076.296.526.907.477.83
Sep.4.975.185.315.455.826.116.296.556.927.537.87
Oct.4.995.205.335.495.846.136.316.576.977.577.90
Nov.5.025.235.365.535.896.176.356.607.047.627.94
Dec.5.065.275.385.565.936.236.396.617.117.657.98
Source: Own elaboration (BANXICO, 2024). https://www.banxico.org.mx/SieInternet/consultarDirectorioInternetAction.do?accion=consultarCua dro&idCuadro=CP150&locale=es

Investment units 2013-2023 (At the end of the year)
Graph 11
Investment units 2013-2023 (At the end of the year)
Source: Own elaboration (BANXICO, 2024). https://www.banxico.org.mx/SieInternet/consultarDirectorioInternetAction.do?accion=consultarCua dro&idCuadro=CP150&locale=es

Investment units, January-April 2024
Graph 12
Investment units, January-April 2024
Source: Own elaboration (BANXICO, 2024). https://www.banxico.org.mx/SieInternet/consultarDirectorioInternetAction.do?accion=consultarCua dro&idCuadro=CP150&locale=es

The Delphi method has not achieved a standardized consensus on its definitions, nor on the presentation of the final reports. In this method, as in all research methods, the results obtained depend to a large extent on its approach, the adequate review of the literature and the experience of the experts on the panel, which together with the systematization and adequate application of the process, as a whole, allow obtaining a product that facilitates the understanding and interpretation of social phenomena in their reality. relationships, values, attitudes, beliefs, habits, and representations, which cannot be obtained through traditional research methods.

In the social sciences, particularly in business, the application of the Delphi method makes it possible to analyze and carry out prospections that reflect the viability of the company's growth, as well as the trends of the sector to which it belongs and the evolution of its market, managing to anticipate the needs of its customers, allowing them to make better decisions and establishing measures according to the probable future scenarios.

REFERENCES

BANXICO. (2024). Sistema de Información Económica. Mexico: Banco de México. Link: https://www.banxico.org.mx/

Blasco, J. E., López, A., & Mengual, S. A. (2010). Validation by Delphi method of a questionnaire to know the experiences and interest towards water activities with special attention to windsurfing. Agora for Physical Education and Sport, 12(1), 75-94.

Cabero, J., & Infante, A. (2014). Use of the Delphi method and its use in communication and education research. Edutec. Electronic Journal of Educational Technology, (48), a272. https://doi.org/10.21556/edutec.2014.48.187

Diamond, I. R., Grant, R. C., Feldman, B. M., Pencharz, P. B., Ling, S. C., Moore, A. M., & Wales, P. W. (2014). Defining consensus: A systematic review recommends methodologic criteria for reporting of delphi studies. Journal of Clinical Epidemiology, 67(4), 401-9. http://dx.doi.org/10.1016/j.jclinepi.2013.12.002.8

Gordon, T. J. (1994). The Delphi method. Washington D. C: United Nations University.

Helmer, O. & Rescher. N. (1959). On the Epistemology of the Inexact Sciences. The Institute of Management Science. 6, 25-52. https://doi.org/10.1287/mnsc.6.1.25

Humphrey-Murto, S., Varpio, L., Wood, T. J., Gonsalves, C., Ufholz, L. A., Mascioli, K., Wang, C. & Foth, T. (2017). The Use of the Delphi and Other Consensus Group Methods in Medical Education Research: A Review. Acad Med. 92(10):1491-1498. https://10.1097/ACM.0000000000001812.PMID: 28678098

INEGI. (2024). Banco de Información Económica. Mexico: Instituto Nacional de Geografía y Estadística. Link: http://www.inegi.org.mx/sistemas/bie/

Jones, J. & Hunter D. (1995). Qualitative Research: Consensus methods for medical and health services research. BMJ. 311-376. https://10.1136/bmj.311.7001.376.PMID:7640549

Kennedy, H. (2004). Enhancing Delphi research: methods and results. Journal of Advanced Nursing, 45, 504-511. https://doi.org/10.1046/j.1365-2648.2003.02933.x

Landeta, J., & Landeta Rodríguez, J. (1999). The Delphi Method: A Forecasting Technique for Uncertainty. Ariel.

López-Gómez, E. (2018). The Delphi Method in Current Research in Education: A Theoretical and Methodological Review. Education XX1, 21(1):17-40 https://10.5944/educXX1.15536

Martinez, E. (2003). The Delphi Technique as a strategy for consulting those involved in the evaluation of programmes. Journal of Educational Research, 21(2), 449-463.

Maxey, D. & Kezar, A. (2016). Leveraging the Delphi Technique to Enrich Knowledge and Engage Educational Policy Problems. Educational Policy, 30(7), 1042-1070. https://doi.org/10.1177/0895904815586856

McMillan S. S., King M, Tully M. P. (2016). How to use the nominal groupand Delphi techniques. Int J Clin Pharm. 38, http://dx.doi.org/10.1007/s11096-016-0257-x.

Minayo, M. C. S. (2009). The craftsmanship of qualitative research. Buenos Aires: Lugar Editorial.

Pill, J. (1971). The Delphi method: substance, context, a critique and an annotated bibliography. Socioecon Plan Sci. 5(1):5 7-71.

Pozo, M. T., Gutiérrez, J., & Rodríguez, C. (2007). The use of the Delphi method in the definition of the criteria for quality training in socio-cultural animation and free time. Journal of Educational Research, 25(2), 351-366. Retrieved from: https://doi.org/10.6018/rie.25.2.96831

Price, B. (2005). Delphi survey research and older people. Nursing Older People, 17 (3), 25-31. https://doi.org/10.7748/cnp2012.03.1.2.c2373

Sekayi, D., y Kennedy, A. (2017). Qualitative Delphi Method: A Four Round Process with a Worked Example. The Qualitative Report, 22(10), 2755-2763. https://doi.org/10.46743/2160-3715/2017.2974

Steurer, J. (2011). The Delphi method: an efficient procedure to generate knowledge. Skeletal Radiol, 40, 959-961. https://10.1007/s00256-011-1145-z

Varela-Ruiz, M., Díaz-Bravo, L. & García-Durán, R. (2012). Description and uses of the Delphi method in health sciences research. Investigación en Educación Médica. 1(2):90-95. https://10.22201/fm.20075057e.2012.02.00007

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