E-JOURNAL USER STUDY
REPORT OF FIRST SURVEY
APPENDIX I: SAMPLE METHODOLOGY
I.1. List of Participating Societies
Members of 20 professional societies in life sciences were sampled for the Scientific Journal User survey May 22 to June 20, 2001. The following table shows the names of societies and sample sizes per society.
|American Society for Microbiology
|Radiological Society of North America
|American Society for Biochemistry and Molecular Biology
|American Physiological Society
|The Endocrine Society
|American Society of Plant Physiologists
|American Association of Immunologists
|American Association for Clinical Chemistry
|Society for Study of Reproduction
|American College of Chest Physicians
|American Society for Pharmacology & Experimental Therapeutics
|American Society for Nutritional Sciences
|American Heart Association
|Botanical Society of America
|The Society of Investigative Dermatology
|Genetics Society of America
|American Psychosomatic Society
|American Society of Hematology
|Royal Society of Medicine Press
*The number exceeds total sample size (12,465) because some respondents belong to multiple societies
I.2. Sampling Methods:
The first survey was conducted online; data were collected from a Web-based questionnaire, recorded in the form of TSV files, by a third-party specialist firm called Perseus. The purpose of the survey (as described in greater detail elsewhere) was to uncover the perceptions of scientists about e-journals.
Life scientists and medical professionals who read life and medical science journals, especially HighWire journals in either paper or e-journal format (both users and nonusers of e-journals)
- Sampling: We contacted 70 scientific societies affiliated with HighWire Press to request membership information such as e-mail addresses. Twenty societies that broadly represent life sciencesbiological sciences, health sciences, and agricultural sciencesagreed to release their member information (limited to name, e-mail address, and membership statuse.g., active, student, retired) for the survey.
- Online questionnaire: This is best viewed (though not active for data collection) at http://ejust.stanford.edu/firstsurvey-linked.htm
- Solicitation methods: We sent 108,774 e-mail solicitations, requesting members to respond via the questionnaire on the Web. Approximately 13,903 addresses returned "undeliverable" or vacation messages, resulting in a contact group of approximately 94,871.
- Survey implementation and data collection period: May 22 to June 20, 2001
- Survey response rate: 12,453 net responses were received during the period; the survey response rate is 13.14%
- Sample size: The number of sample observations was 12,465
- Sample distribution (demographic characteristics):
- Gender: 30% of the respondents are female.
- Age: The average (mean) age of respondents is 47; the median age is 48.
- Research fields: 60% of respondents reported their research field as biological sciences, 34% health sciences, 4% agricultural, and 2% other research fields related to life sciences.
- Occupation: 38% of respondents are faculty members in academic institutions, 12% students and post-doctorate researchers, 11% researchers in academic institutions, 11% researchers in the private sector, 6% government agency, 17% medical doctors, and 3% retirees.
- Residence: Respondents are from 99 different countries. The majority reside in the United States (72%), and the rest are from Canada and countries in Europe, Asia, Africa, Latin America, and Australia.
APPENDIX II: MODELS AND RESULTS
II. 1. Econometric Models for Analyses
The study has three dependent variables to (1) e-journal usage; (2) scientists' preferences regarding printed copy versus online editions; (3) scientists' perception about the impact of e-journals on their research activities.
Ordered probit regression is used to measure equation (1), e-journals usage, and logistic regressions for equations (2) and (3), preference regarding journal formats and perception about e-journals.
P[EJU] = F (DEMO1, INTERNET, SUBS, PAPER1, FACILITY, ACCESS)|| (1)|
P[PREF]= F (DEMO2, INTERNET, SUBS, PAPER2, PP^[EJU] ) || (2)|
P[PEJ]=F (DEMO2, INTERNET, SUBS, PAPER2, P^[EJU] )|| (3)|
where EJU is a degree of e-journal usage with 5 categories (see Table 2); PREF is a dependent variable, preferences regarding journal format, printed copy vs online versions; and PEJ represents perception about the impact of e-journals on research activities. DEMO1 is a set of demographic characteristics such as AGE, MD, BIOLOGY, MALE, USA-CAN which represent respondents' age, whether a respondent is a medical doctor, whether a respondent's field of research is biology, whether a respondent is male, and an indicator that a respondent resides in either the U.S. or Canada, respectively (refer Table 1); INTERNET is a variable to measure Internet familiarityweekly hours spent on the Internet; SUBS represents the resources available through personal subscriptionsnumbers of journal subscriptions; FACILITY and ACCESS represent available resources such as PC, printers, and Internet access and scientific journal access through institutions; PAPER1, the numbers of papers submitted in the past year, PAPER2, the number of papers published or accepted in the journals during the past year, which measure respondents' research productivity. DEMO2 represents a set of variables in DEMO1 and JOBEXP, job experience measured by years (refer Table 1). P^[EJU] is a predicted probability of e-journal usage from equation (1).
EJU variable consists of five categorical values (question 2 in Table 2), while values of both PREF (questions 4 and 5 in Table 3 and Table 4) and PEJ variables (questions 17, 14, 15, and 16 in Table 5, Table 6, and Table 7) are binary. Five categories for EJU are yesterday or today, within last week, within a month, longer than a month, and never. A binary value for PREF and PEJ is "Agree" and "Disagree." The binary value has created by recoding four categories, "Strongly Agree," "Somewhat Agree," "Somewhat Disagree," and "Strongly Disagree," into two categories, "Agree" and "Disagree." Table 2 shows a question on EJU and responses per category. Many different questions were used to analyze preferences regarding formats including reasons of preference. Table 3 and Table 4 describe questions for PREF variable. We measured a predicted probability of whether they prefer online to printed editions. Questions in Table 4 are analyzed condition on their responses to whether they prefer online journals to printed versions (Table 3). Equation (3) has been used to measure respondents' perception about the impact of e-journals on their research activities (questions in Table 5, Table 6, and Table 7).
II. 2. How to Read the Regression Tables
The signs of the four cut off points (a1, a2, a3, and a4) listed at the top of the column titled P[EJU] in Table 8 change from negative to positive, and their values increase. This first overall test tells us that e-journal usage frequency can be adequately "explained" by the set of independent variables we chose for the ordered probit model: demographic variables (age, occupation, fields of research, country of residence), Internet familiarity, number of subscriptions, number of papers submitted last year, and institutional access to scientific journals (see second column, Table 8).
Moving down the column to the detailed results of this regression analysis, we can see that certain groups of people use e-journals more frequently than others. Because 5 = never and 1 = yesterday or today, the EJU variable actually represents how little respondents use e-journals. Thus a positive coefficient for any of the categorical independent variables means that that category uses e-journals less often than the rest of the sample, while a negative coefficient means that that category uses e-journals more often. For continuous variables such as age or the number of subscriptions, if they are positive, then as they increase, e-journal usage frequency decreases; if they are negative, then as they increase, e-journal usage frequency increases.
If a variable is not marked with asterisks, then its relationship with e-journal usage frequency was not large enough to be statistically significant. Because all the variables are entered into the regression equation at once, each effect "controls for" all of the other variables. Consequently, we can say that a statistically significant variable has an "independent effect" on a person's e-journal usage frequency, regardless of that person's other characteristics.
II. 3. Tables
|Table 1: || Definitions of Selected Variables for Analyses|
|Table 2: || E-Journal Usage Behavior|
|Table 3: || Preference for Format (Printed Copy versus Online)|
|Table 4: ||Reasons for Format Preference|
|Table 5: || Perception about the Future of Peer-Reviewed Journals|
|Table 6: ||Perception about E-Journals and Online Searching|
|Table 7: || Perception about the Impacts of E-Journals on
|Table 8: || Predicted Probabilities of E-Journal Usage, Preference for Format, and
Perceptions about Whether E-Journals Affect Research Activities|
|Table 9: ||Logistic Regression Analyses: Probability of Various Motives for Favoring or Disfavoring
Online Journal Editions over Printed Journal Editions|
|Table 10: || Logistic Analyses of Probabilities of Perceptions about the Impact of E-Journals
on Research Activities (among Those Who Answered "Yes" to Q15)|
|Table 11: || Perception about E-Journals and Online Searching|
|Tables 1-8 |
|Tables 9-11 |
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Last updated: 03-29-02