FACTORS ASSOCIATED WITH TECHNOLOGY

ADOPTION IN CLINICAL PRACTICE

_________________________

A Doctoral Project

Presented to

The School of Graduate Studies

Department of Psychology

Indiana State University

Terre Haute, Indiana

_________________________

In Partial Fulfillment

Of the Requirements for the Degree

Doctor of Psychology

_________________________

by

Jennifer C. Salib, MS

August 2002

Abstract

The primary focus of the current study was the investigation of

technology use and related attitudes toward technology by psychologists in

clinical practice. In addition, this study served as the initial step in a larger

effort to develop a database, the Independent Practice Network (IP-Net),

which will allow for on-going investigation of patterns and trends in

independent practice. This study employed a survey method in which

participants chose to respond either via the Internet or by mail.

A random sample of 2,000 psychologists who are members of Division

42 (Psychologists in Independent Practice) of the American Psychological

Association were invited to participate in IP-Net. Two-hundred-and-sixty-five

volunteered and 161 subsequently responded. Despite the low response

rate, the characteristics of those who participated were very similar to those

in the random sample, as well as the entire membership of Division 42.

Psychologists with more positive attitudes toward technology, and

those in the online response group, reported significantly higher rates of

technology use, which supported one of our hypotheses. Our data also

indicated an increased rate of technology usage compared to previous

studies. Additionally, based upon our findings we were able to make

recommendations for a more comprehensive system of classification of

technology applications in clinical practice.

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Preface

This research study was completed with financial assistance from

Division 42 (Psychologists in Independent Practice) of the American

Psychological Association and the Indiana State University School of Graduate

Studies. This research study was also completed with the assistance of

Andrew P. Schneider, who donated his time to design and develop the Web

application and manage the online data collection.

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Table of Contents

ABSTRACT........................................................................................................2

PREFACE...........................................................................................................3

LIST OF TABLES................................................................................................8

CHAPTER 1 INTRODUCTION..............................................................................9

AREAS FOR TECHNOLOGY APPLICATIONS IN PRACTICE.............................................10

CATEGORIES OF TECHNOLOGY APPLICATIONS IN PRACTICE.......................................11

First-wave................................................................................................11

Second-wave...........................................................................................11

Third-wave..............................................................................................12

Critique of the Current System................................................................12

RATES OF TECHNOLOGY USE IN PRACTICE............................................................15

SPECIFIC TECHNOLOGY APPLICATIONS IN PRACTICE................................................18

LEGAL CONSIDERATIONS RELATED TO TECHNOLOGY USE IN PRACTICE.......................21

POSSIBLE REASONS FOR LOW RATES OF ADOPTION OF TECHNOLOGY APPLICATIONS IN

PRACTICE.......................................................................................................22

PSYCHOLOGISTS’ ATTITUDES TOWARD TECHNOLOGY USE.......................................23

Social Psychological Theory on Attitude Change.....................................24

Attitude Change Toward Computers as a Function of Experience...........25

Other Moderators of Computer Attitudes................................................28

Gender....................................................................................................28

Age..........................................................................................................29

PRACTICAL CONCERNS RELATED TO TECHNOLOGY USE IN PSYCHOLOGY....................30

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PROPOSED STUDY...........................................................................................32

CHAPTER 2 METHOD......................................................................................35

PARTICIPANTS.................................................................................................35

Random Sample Profile...........................................................................36

Study Sample Profile...............................................................................36

MEASURES.....................................................................................................37

PROCEDURES..................................................................................................39

CHAPTER 3 RESULTS......................................................................................41

Personal Characteristics of Study Participants........................................42

Practice Characteristics of Study Participants.........................................46

Practice Structure and Organization........................................................47

Average Number of Clinical Sessions per Patient....................................49

Current and Future Technology Applications in Practice.........................50

Average Time Spent per Week with Various Technology Applications....52

Attitudes Toward Technology..................................................................55

Hypotheses Testing and Predictor Variables...........................................57

First Hypothesis...................................................................................57

Third Hypothesis..................................................................................57

Second Hypothesis..............................................................................58

Additional Between Group differences for Online and Mail Responders. .59

Possible Subgroup Differences................................................................59

Use of the Internet for Data Collection....................................................60

CHAPTER FOUR DISCUSSION..........................................................................61

FINDINGS RELATED TO SURVEY METHOD.............................................................61

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Using the Internet in Research................................................................62

Additional Advantages to Internet Research...........................................63

Disadvantages to Internet Research.......................................................65

Issues Related to Participating in IP-Net..................................................66

Issues Related to Online Response Rates................................................66

Issues Related to Mail Response Rates...................................................67

Issues for Investigation in Subsequent Surveys......................................68

FINDINGS RELATED TO COMPARABILITY OF RESPONSE GROUPS................................69

Group Differences...................................................................................69

Generalizability.......................................................................................71

FINDINGS RELATED TO ATTITUDES TOWARD TECHNOLOGY AND TECHNOLOGY USE BY

INDEPENDENT PRACTITIONERS............................................................................72

Findings Related to Attitudes Toward Technology as a Function of

Response Group......................................................................................72

Findings Related to Technology Use as a Function of Response Group...73

Findings Related to Use of Technology in Practice Administration..........74

Findings Related to Use of Technology for Assessment..........................76

Findings Related to Use of Technology for Treatment.............................76

Findings Related to Technology for Communication and Information.....77

Discussion of Hypotheses Regarding Technology Use............................78

Trends in Technology Use.......................................................................80

CONCLUSIONS AND FUTURE DIRECTIONS..............................................................81

REFERENCES..................................................................................................86

APPENDIX A....................................................................................................94

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APPENDIX B....................................................................................................96

Appendix C...................................................................................................110

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List of Tables

Table 1. Comparison of Participant Characteristics from Total Volunteer

Sample, Random Sample and Entire Division 42 Membership................43

Table 2. Participant Characteristics from Responses to Surveys for Online and

Mail Groups.............................................................................................45

Table 3. Practice Characteristics from Responses to Surveys for Online, Mail,

and Total Sample....................................................................................47

Table 4. Person Responsible for Various Administrative Tasks from Responses

to Surveys for Online, Mail, and Total Sample.........................................48

Table 5. Average Number of Clinical Sessions per Patient by Percent from

Responses to Surveys for Online, Mail, and Total Sample.......................49

Table 6. Current and Anticipated Future Technology Use in Practice from

Responses to Surveys for Online, Mail, and Total Sample.......................52

Table 7. Average Weekly Telephone Use and Reimbursement in Practice from

Responses to Surveys for Online, Mail, and Total Sample.......................53

Table 8. Average Weekly E-mail Use and Reimbursement in Practice from

Responses to Surveys for Online, Mail, and Total Sample.......................54

Table 9. Attitudes Toward Computer Questionnaire Scores from Responses to

Surveys for Online, Mail, and Total Sample.............................................56

8

Chapter 1

Introduction

There are little systematic data available to psychologists about

important dimensions of the independent practice of psychology. However,

practitioners share information related to personal and practice

characteristics on a regular basis with managed care organizations for

credentialing and re-credentialing purposes, and on a more frequent basis

with submission of billing and utilization review materials. As a result, these

organizations have much more information about individual practices than

the psychologists themselves do, and a better grasp of important aspects of

practice than is available to any other group. Additionally, efficacy research

traditionally neglects experienced psychologists working in independent

practice settings, and instead focuses on university or clinic “laboratory”

settings. In response to these trends, Division 42’s Emerging Patterns of

Practice Committee provided the initial financial support for the development

of the Independent Practice Network (IP-Net). The development of the

research network was one purpose of this study. The primary focus of the

current study was the investigation of technology use and related attitudes

toward technology by psychologists in independent practice.

This chapter reviews the various areas where technology applications

can be introduced into psychotherapy, as well as the wave system of

classification for technology applications in practice. We then examine the

current literature describing the rates of technology use in practice, and

some legal and ethical considerations related to its use in practice. This

chapter ends with a discussion of possible reasons for the low rates of

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adoption of technology applications in practice, which leads to a description

of the current study.

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Areas for Technology Applications in Practice

Although computers have dropped in cost and in size, their power and

usage has greatly increased over the past decades. Specific to this paper,

there are many technologies now available that are designed to enhance and

simplify the work of practicing psychologists. These technologies are able to

do some tasks usually only performed by a psychologist. For example,

electronically tracking therapeutic progress by directly recording patient

homework assignments and changes in emotional and behavioral symptoms

can lead to time- and cost-efficient outcome research. These technologies

are also designed to make managing an office, maintaining patient files, and

communicating with patients and other professionals much easier and more

time- and cost-efficient tasks. However, there has been relatively little

movement in the field to incorporate these advances into the practice of

psychology (Marks, Shaw, & Parkin, 1998; McMinn et al., 1999). This raises

questions such as: what factors account for the low rates of adoption, what

can or should be done to increase usage, and how would an increase in usage

impact the practice and reimbursement of psychological services?

The adoption of technology by psychologists is affected by the nature

of the applications themselves and their relative cost effectiveness.

Technology applications must address a current need, or introduce an

approach to service delivery that is innovative and cost effective. The

application also needs to be easily assimilated into practice, in terms of

learning, cost, and maintenance, and it must be efficiently employed. For

this to occur, technology applications minimally must offer time and cost

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advantages over lower technology alternatives, and be readily available and

marketed.

In addition to these practical issues, the attitudes and values of

psychologists will affect adoption of technology applications. The focus of

this investigation was on identifying patterns of technology adoption among

practicing psychologists in the following areas: 1) office management (patient

files, billing, scheduling, word processing, marketing/advertising, referrals); 2)

assessment (testing, interviewing); 3) treatment (planning,

monitoring/documentation, outcome research, patient education, online

therapy, video therapy); 4) consultation; 5) supervision; and 6) training and

continuing education.

Categories of Technology Applications in Practice

McMinn et. al (1999) have divided the technologies available to

psychotherapists into three categories: (1) first-wave or well-established

practice technologies with minimal impact on service delivery; (2) second-

wave or partially established practice technologies with moderate impact on

service delivery; and (3) third-wave or emerging practice technologies with

direct impact on service delivery. While this system may help identify

developments in technology use, this system does not adequately categorize

and define the available practice technologies.

First-wave. First-wave/well established practice technologies are likely

to be used by most practicing therapists and include equipment that allows

for greater efficiency in maintaining records and running an office. These

types of technologies have minimal impact on the delivery of clinical services.

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Examples of such technologies include computer software for billing,

scheduling, and word processing, facsimile, and voice mail services.

Second-wave. Second-wave/partially established practice technologies

are likely to be used by many practicing therapists and include equipment

that allows for greater efficiency in assessment procedures, consultation

procedures, interviewing procedures, electronic mail, and maintaining clinical

databases. These types of technologies have moderate impact on the

delivery of clinical services. Examples of these technologies include

computer software for test administration and interpretation, telephone,

electronic mail, and Internet consultation, computer software for

interviewing, corresponding with patients via electronic mail, and maintaining

a database of clinical services for outcome research.

Third-wave. Third-wave/emerging technologies are likely to be used

by few practicing therapists and include equipment that allows for greater

efficiency in treatment and education. These types of technologies have

direct impact on the delivery of clinical services. Examples of these

technologies include virtual reality therapy for specific disorders (i.e., use of a

flight simulator as part of a treatment plan for fear of flying),

teleconferencing for patients in out-lying rural areas or consultation for

practitioners, Internet therapy (i.e., patients and providers logging onto a

Web site for treatment purposes), software packages for psychoeducational

purposes, and software to facilitate treatment (i.e., completing homework

assignments and assessments on a home computer and electronically

mailing them to the therapist’s office for progress tracking, which may also

facilitate outcome research).

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Critique of the Wave System. One consideration related to the above

classification system is that technology changes today are so rapid that the

classification system frequently needs to be revised as new products enter

the field, at minimum on an annual basis. Another consideration is that this

breakdown of technology into the three-wave system is unique to those in

the field of psychology. Other fields, such as financial institutions,

educational institutions, and even those in the medical profession, would

likely look at some technologies listed in the third-wave and consider them at

least second-wave, if not first-wave. Perhaps those of us in the field of

psychology need to reevaluate what is listed in the first-wave classification,

to determine if this so called first-wave should be eliminated entirely. When

one looks at the applications listed in the first-wave (i.e., fax machine,

voicemail, computer software for billing), it is doubtful that any modern office

can exist without them (Jerome, DeLeon, James, Folen, Earles, & Gedney,

2000).

Consideration should also be given to providing greater clarity on the

difference between using the Internet for obtaining information (second-

wave), versus using the Internet for e-commerce transactions (related to

health insurance claims or pharmacy transactions; second-wave), versus

using the Internet to connect consumers with mental health professionals

directly (either through appointment scheduling or direct online connections;

third-wave). This breakdown looks at the Internet in terms of being either a

passive source of information, or performing interactive transactions. The

interactive transactions will be guided by legal developments that protect

consumers and help ensure information integrity and privacy (specifically the

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Health Insurance Portability and Accountability Act of 1996, HIPAA), thus

further distinguishing them from passive information gathering.

The wave classification system does not discuss the importance of

outcome/effectiveness research and future participation in practice research

networks. Technology applications can be highly instrumental in the

collection and storage of outcome data, which can later be incorporated with

larger practice research network data. This paper does not go into detail in

the discussion of practice research networks, however, it should be noted

that these are becoming a popular new method for collecting real-time data

with high internal and external validity embraced by state organizations as

well as the American Psychological Association, and other health-related

associations (Borkovec, Echemendia, Ragusea, & Ruiz, 2001).

Also missing from this three-wave classification of technology

applications is a section for advertising and marketing. One could advertise

their services via the Web to attract potential clients, as well as post job

openings to recruit applicants. This application of technology could likely fit

into the first or second wave grouping since it is something that could be

adopted by a large number of practicing therapists, while having minimal

direct impact on treatment.

Lastly, also missing from this three-wave classification of technology

applications is a section related to training and continuing education

purposes. This application of technology could also likely fit into the first or

second wave grouping since it is something that could be adopted by a large

number of practicing therapists, while having minimal direct impact on

treatment. While training and continuing education are important aspects of

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our field, these areas are not discussed in detail because the focus of this

paper is on technology in practice. However, given the amount of

information available related to technology in education, and the likelihood

that educational institutions can more easily absorb the cost of incorporating

technology applications, perhaps this is the optimal entry point for

technology in the field of psychology, and should be researched in the future.

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Rates of Technology Use in Practice

The use of computers in mental health care has been studied, but

findings must be approached cautiously because of the rapid expansion in

the use of computers in the recent past (i.e., Bloom, 1992; Ghosh & Greist,

1988; Gould, 1996; Kenardy & Adams, 1993; Kirkby, 1996; Kirkby & Lambert,

1996; Lawrence, 1986; Marks et al., 1998; Oakley-Browne & Toole, 1994;

Plutchik & Karasu, 1991; Zarr, 1984). The main findings from these authors

indicate that, while most practicing psychologists are aware of the available

technologies, few have begun to incorporate them beyond the basic office

(billing and scheduling) and testing (administration and interpretation)

applications. Another important finding indicated that the majority of

practicing psychologists are uncertain about including the more advanced

technologies (beyond office and testing applications), such as those listed in

the 2nd and 3rd wave classification.

Data available from McMinn, Buchanan, Ellens, and Ryan (1999)

indicated that psychology as a profession is lagging behind in terms of

making use of available technology. For example, when compared to similar

survey data from a decade ago (Farrell, 1989), McMinn et al. (1999), who

surveyed 420 independent practice psychologists across the country, found

that only 57% of psychologists reported using computer applications for

billing fairly often (compared to 63% who reported routinely using it in 1989),

only 26% reported using technology fairly often for test scoring (compared to

41% routinely using it in 1989), only 20% reported using technology for test

interpretation fairly often (compared to 29% routinely using it in 1989), and

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only 22% reported using technology for maintaining patient records fairly

often (compared to 20% routinely using it in 1989).

The October 2000 issue of Professional Psychology: Practice and

Research devoted a special section to issues related to technology use in

psychology. A study by Maheu and Gordon (2000) in that issue reported

results of a 40-item Web-based survey of 56 practicing psychologists

engaged in online behavioral healthcare. It looked at their backgrounds,

services, clinical interventions, fees, and types of technologies used. Survey

participants were recruited through Web postings on related e-mail lists. The

sample was 98% Caucasian, 65% male and 35% female, with 70% reporting

that they practiced in or near an urban area. Ninety-three percent of the

sample reported that they were licensed or certified to practice in their

respective fields in the United States, with 57% of the sample reporting that

they were licensed psychologists, 8% psychiatrists, 2% marriage and family

counselors, 17% social workers, and 5% other.

The majority of respondents (63%) described their services as

educational or advice-oriented in nature. Only 18% described their services

as therapy or counseling interventions. The majority of problems addressed

via technology applications were clinical in nature (i.e., related to mood,

anxiety, or sexual dysfunction disorders or relationship problems). The types

of technology applications most used were e-mail, Websites, and chat rooms,

or videoconferencing. The majority of respondents (55%) stated that they

provided their services at no charge. Those that did charge averaged 50 to

60 dollars per hour. A third of the sample reported only having single

sessions with consumers, whereas 50% of the sample reported between one

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and fifteen sessions. Half of the respondents reported that the duration of

services was less than a month, whereas 20% reported providing services

that lasted up to three months. Most respondents (78%) reported that they

also provided services to individuals living in a state other than where the

provider was licensed, despite the fact that 73% reported having legal and

ethical concerns related to this matter. Only 50% reported having made

arrangements to deal with a sudden crisis situation, and only 48% used a

consent form prior to providing services. Seventy-five percent of

respondents reported having to refer a consumer to a local mental health

professional. While the results from this study are limited by its sample size

and method in terms of generalizability, the results do raise important legal,

ethical, and practical issues that need to be addressed. Also, it would be

important for future studies to address how attitudes and practices would

differ, if the services were based on providing educational information at no

charge versus clinical services.

Also in the October 2000 special section was an article by VandenBos

and Williams that reported on the extent of health care service delivery via

the Internet. This survey had a 60% response rate (n=596), with a sample

composition of 96% Caucasian, 52% male and 48% female, median age of 50

with a range of 33 to 72. Eighty-eight percent held a Ph.D., 93% were

psychologists, 80% had over ten years experience, and approximately 70%

were employed in full time independent practice. Of the 596 practicing

psychologists who responded, only 2% of the sample reported that they had

used the Internet or satellite technology to deliver services. However, it

should be noted that telephone use for delivery of psychological services was

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nearly universal among those surveyed. While many studies in the literature

classify telephone use as part of the technology spectrum, we again question

the need to reclassify what is considered a true application of technology in

practice, given the discrepancy in usage rates depending on the type of

technology.

Incorporating greater usage of technological advances into the practice

of psychotherapy may not only prevent the field from becoming “outdated”,

but may also serve to benefit the profession in a number of ways. Wright and

Wright (1997) suggested that computers may reduce cost of treatment,

improve access to psychotherapy, promote engagement in the

psychotherapy process, provide psychoeducation, provide systematic

feedback to the user, promote self-monitoring, provide for rehearsal of coping

skills, encourage self-help, store, analyze, and display data, provide built-in

outcome measures, and function reliably without fatigue. However, research

is needed to demonstrate that these suggested advantages actually exist.

Additional research is also needed to determine current usage patterns, as

well as what factors are affecting adoption.

Specific Technology Applications in Practice

Studies have examined specific technology applications in

psychotherapy and provide more detailed information than discussed below.

Ghosh and Marks (1987) and Gosh, Marks, and Carr (1988) described the

results of a randomized controlled trial where eighty-four adult outpatients

diagnosed with either agoraphobia, panic disorder, social phobia, or specific

phobia were randomly assigned to perform self-exposure exercises under the

guidance of either a psychiatrist, self-help book, or computer-based self-help

20

program over a twelve week period. Results were compared against twenty

matched control subjects. At the end of the twelve week treatment period,

all three groups were equally satisfied with treatment, had a similar number

of drop outs, and had made significant improvements that continued through

a six month follow-up.

Semi, Klein, Greist, Sorrell, and Erdman (1990) describe the results of a

study that compared three groups of twelve of nonsuicidal depressed

patients recruited via newspaper on symptom relief based upon random

grouping: (1) computer-administered cognitive behavior treatment, (2)

therapist-administered cognitive behavior treatment, and (3) a wait list

control group. There were no drop-outs in the study. At the end of the six

week treatment period, and at a two month follow-up, both treatment groups

had improved significantly compared to the control group. The authors also

discuss the possibility that the novelty of the computer use as part of

treatment may have influenced the positive outcome in this group. This is an

area that requires additional research.

Schneider (1986) reported the results of a five week online patient

tailored smoking cessation computer program that allowed patients and

therapists to interact. At the end of treatment, approximately 35% of the

smokers were abstinent, and at a three month follow-up, 25% were still

abstinent. The authors stated that these results are similar to results found

using traditional face-to-face therapy techniques.

Agras, Taylor, Feldman, Losch, and Burnett (1990) described the use of

a hand-held computer as part of a twelve week treatment protocol for

nonbulimic mild to moderately obese females. Ninety females, average age

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45 years, who responded to a newspaper recruitment ad, were randomly

assigned to one of three groups, (1) use of a hand-held computer with one

introductory computer session, (2) computer therapy with four group support

sessions, and (3) a therapist conducted weight loss program. At the end of

the treatment period, all three groups had recorded similar weight loss

results that were maintained at a one year follow-up. The group that utilized

the hand-held computer and only one face-to-face session was the most cost-

effective, however, some added benefits were revealed through the addition

of group therapy support that could potentially provide longer-term cost and

patient benefits.

Two additional forms of technology reported in the literature are self-

treatment via interactive voice response and virtual reality programs (Marks,

Shaw, & Parkin, 1998). Interactive voice response is beneficial for those who

cannot access a computer, but have a touch tone telephone available.

Interactive voice systems would allow patients to respond to programmed

questions by using the touch pad on their telephone. This would provide a

similar exchange of data as if the patient typed in a response on a computer

keyboard. Virtual reality is mainly used as an aid to exposure therapy,

however, its cost can often be prohibitive for use in regular treatment.

It should be kept in mind that these studies likely suffer from limited

generalizability due to issues that affect all efficacy studies, such as a highly

screened patient population and specifically working with manualized

cognitive behavioral techniques. Therefore, additional research in natural

settings needs to be done to truly understand the impact of technology in

psychotherapy practice. For the most part, all of these studies reported fairly

22

small sample sizes, and a literature search did not produce more recently

published work. Given the rapid and widespread advances in technology, as

well as its presence in our daily lives, newer studies are needed. Also, a

thorough examination of both short- and long-term costs versus benefits is

needed with future studies.

It appears that researchers have moved from conducting efficacy

studies, to doing survey research for what is being incorporated into practice,

without ever being certain that what we are incorporating truly works. This is

in line with the argument presented by Stamm and Perednia (2000) stating

that research in the area of telehealth typically addresses the technology

aspects of the care provided and not the psychosocial implications of the

technology driven care. Therefore, absent in the research is knowledge

about what telehealth means in terms of quality of care versus simple

provision of care. This is likely the result of recent rapid technological growth

paired with financial pressures on the healthcare industry to be more cost-

effective. Based upon available descriptive studies (i.e., Burghgraeve &

DeMaeseneer, 1995) it was assumed that technology was a good and cost-

effective means of achieving an end. This led to the rapid growth of

technology applications and training in the health care systems, with

accompanying research studies assessing patient and provider usage. Again,

missing from this equation is research addressing the psychosocial impact, or

meaning, behind telehealth and its quality of care.

Stamm and Perednia (2000) call for future research to address the

human aspects of using technological applications in practice that underlie

the technical interface of telehealth. Technology refers to the “nuts and

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bolts” components of the telehealth systems, and the human part involves

the actual delivery or receiving of the service. After all, the authors remind

us that the human-technology interface is the most important aspect in the

telehealth equation, and that the best piece of computer equipment is only

as good as its trained and willing human user. A practice research network,

such as IP-Net described in the current study, could serve as a useful tool to

answer these questions.

Legal Considerations Related to Technology Use in Practice

Koocher and Morray (2000) discuss some of the legal aspects related

to the use of technology in psychotherapy practice. They surveyed all fifty

states’ Attorney Generals and the Attorney General of the District of

Columbia via paper-pencil and telephone between March 1999 and August

1999. Readers are cautioned that changes in state statutes and regulations

are constantly occurring and, therefore, some results reported in this study

may not be reliable after 1999. Attorney Generals from forty-two jurisdictions

participated in this study. All those who responded indicated that their

jurisdiction had statutes regulating the practice of psychiatry, psychology,

and social work. Eighty-six percent of those responding indicated that they

regulated marriage and family counseling, twelve percent regulated pastoral

counseling, 88% regulated psychiatric nursing, 33% regulated rehabilitation

counseling, and 38% regulated “other” areas such as licensed mental health

counseling, substance abuse counseling, art therapy, employee assistance

programs, occupational therapy, and school psychology. Only 7% of those

responding indicated that they had statutes specifically addressing telehealth

issues. Of the 93% indicating that they did not have such statutes in place,

24

only 17% of them indicated that such regulations were even contemplated.

Eighty-six percent responded that no charges had been brought against

licensed mental health practitioners engaging in therapy via electronic

methods, while less than 1% reported that such complaints had been filed in

their jurisdictions. However, 17% indicated that they had received

complaints about services being provided by electronic means across state

lines. Forty-five percent of those responding indicated that they claimed

regulatory authority over practitioners residing outside their jurisdiction, but

offering services via telephone or electronic means within that particular

jurisdiction.

Possible Reasons for Low Rates of Adoption of Technology Applications in

Practice

Designers of computer therapy programs hope that patients will use,

and therapists will accept, the computer as a therapy tool. As described

above, the research literature indicates that some patients have accepted

the computer in therapy. However, the literature also indicates that

therapists are just beginning to accept the computer in therapy as a

legitimate tool as evidenced by the low usage numbers reported by survey

studies (Gould, 1996; Marks et al., 1998). Some studies have reported

concerns by psychologists against the greater incorporation of technology

applications into practice: its influence on the therapeutic relationship, ethical

and confidentiality issues, organizational resistance (including issues of start-

up costs and lack of guidelines/standards for use), and patient resistance

(i.e., McMinn et al., 1999, Wright & Wright, 1997).

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Although there are studies reporting survey results of the extent of

technology use by psychologists in their practices, there are very few studies

explaining what factors influence adoption of various technology applications.

Those studies that do report explanations for this trend tend to focus on the

attitudes and values of psychologists (i.e., McMinn et al, 1999). It also

appears that the rapid and widespread technological advances taking place

in our society have outpaced the development of ethics and training

standards or guidelines for practicing psychologists. This lack of standards or

guidelines has left many psychologists uncertain about and unprepared to

incorporate these advances into practice, as well as leaving psychology as a

field lagging behind technologically. The concerns by psychologists then

appear to fall into two broad categories: issues related to attitudes/values of

psychologists, and practical/economic concerns.

Psychologists’ Attitudes Toward Technology Use

Despite the fact that there are reliable and valid measures available in

the literature to assess attitudes toward computers and other advanced

technologies (i.e., Attitudes Toward Computers Questionnaire (ATCQ), Jay,

1989; Computer Attitude Scale (CAS), Loyd & Gressard, 1984; Stages of

Concern Questionnaire (SoCQ), Hall, George, & Rutherford, 1977), there were

no studies found in the literature that used these measures to assess the

attitudes of psychologists in comparison to technology usage. This study

measured attitudes toward computers among practicing psychologists in

comparison with reported usage of technology applications in practice.

Social Psychological Theory on Attitude Change. Attitudes are defined

as “very general evaluations that people hold of themselves, other people,

26

objects, and issues” that can be based upon and impacted by affect,

cognitions, behaviors, or a combination of these variables (Petty, 1995, p.

196). While there are numerous ways to change one’s attitude about

something, the most common means is via persuasion. Persuasion is

achieved by presenting one with a message containing information about

their current attitude topic. This makes sense since the primary purpose of

attitudes is to serve a knowledge function (help one understand and make

sense of their world) and can broadly be viewed as an information-processing

model of attitude change. Additionally, it is presumed that once attitude

change has occurred, one will engage in behaviors that are consistent with

the attitude beliefs. Therefore, persuasion can be viewed as a means of

changing behavior as well as attitude (Petty, 1995).

Research in social psychology also states that attitudes are acquired

and changed through experience (Fishbein & Ajzen, 1975; McGuire, 1985).

Experience can either be direct (e.g., actual contact with a computer) or

indirect (e.g., observation of another using a computer or through media

exposure). Therefore information gained through these experiences forms

the basis for attitude formation and change. Since social psychology

research has also shown that attitudes are likely to guide behavior (Regan &

Fazzio, 1977), it can be expected that those having positive attitudes about

something (e.g., computer use in psychotherapy) are more likely to employ

or do the thing that they have the positive attitude about (e.g., actually make

use of computers in their psychotherapy practice) compared to a person

holding a less favorable or negative attitude about the same thing.

27

In order for this information-processing model of attitude change to be

effective, McGuire (1968, 1989) stated that the informational message

related to the attitude must be received, understood, and learned and then

the recipient of the message must yield or accept this information.

Therefore, factors such as message comprehensibility, amount of distraction,

individual differences among audience members (e.g., intelligence, mood,

etc.), credibility of the information source, relevance of the information to the

audience, priming of audience members, and motivation and ability to think

about the information, will all affect how the sender’s message impacts the

recipient of the message.

Attitude Change Toward Computers as a Function of Experience.

Amount of direct computer experience has been found to be the most

consistent correlate of computer attitudes, with increased experience leading

to more positive attitudes (Jay, 1989). This is also a central hypothesis for

this study and therefore will be discussed in some detail below.

Related to computer usage, the research literature suggests that user

attitudes have important implications with respect to the acceptance and use

of technological innovations (Grudin & Markus, 1997). Mackie and Wylie

(1988) have outlined a model which demonstrates that user acceptance of

technology is affected by: (1) the user’s awareness of the technology and its

purpose; (2) the extent to which the features of the technology are consistent

with the user’s needs; (3) the user’s experience with the technology; and (4)

the availability of support when using the technology.

Czaja and Sharit (1998) examined whether attitudes toward computers

are influenced by direct computer experience and if these attitudes vary as a

28

function of age, gender, and computer task characteristics. Subjects for this

study were 384 men and women ranging in age from twenty years to

seventy-five years. Attitudes toward computers were measured before and

after the intervention using the Attitudes Toward Computers Questionnaire

(ATCQ; Jay & Willis, 1992). Findings from this study indicated that computer

attitudes are modifiable regardless of age or gender. These findings are

consistent with other reports in the research literature (i.e., Jay & Willis,

1992). Subjects’ attitudes significantly improved as a result of direct

experience with computers. Subjects also reported that their level of

comfort, feelings of competence, and feelings that computers are useful

increased as a result of the intervention. Subjects reported that the task that

required the most cognitive effort was least enjoyable. This has implications

for how computer training programs are structured. In order to maximize

attitude change and facilitate learning, it is important to employ tasks which

people find enjoyable as well as informative. This study demonstrated that

providing users with an opportunity to interact with technology that may be

unfamiliar to them is an effective means of attitude change.

Jegede, Okebukola, and Ajewole (1991) studied whether the attitudes

of students in a developing country, with little exposure to computers, would

be positively influenced by a computer-assisted learning program. This study

used 64 students enrolled in a preparatory course for the Nigerian Joint

Matriculation Examination in biology (41 boys, 23 girls, mean age = 16.4

years). Both attitude toward the use of the computer for learning biological

concepts and achievement in biology were measured before and after the

three month computer-assisted learning program. Subjects were randomly

29

assigned to one of three groups: computer used on an individual basis;

cooperative computer use; and traditional lecture-style classroom instruction.

Results indicated that both groups that used the computer had significantly

higher attitude scores at post-testing, in terms of liking the computer for

learning, compared to the classroom control group. There were no

differences found in terms of achievement. However, previous studies (i.e.,

Choi & Gennaro, 1987; Wainwright, 1989) have reported that students learn

better and achieve higher scores when working with computers as compared

to traditional classroom methods. While this study included a small sample

size and a very specific group of subjects who do not easily generalize to the

population being discussed in this paper, it is interesting to note that changes

in attitude toward computer use does not appear to be limited by culture or

socioeconomic status, gender, or age. Attitude change was again effectively

demonstrated via direct computer contact and experience.

Levine and Donitsa-Schmidt (1998) examined the extent and direction

that computer attitudes, experience, and belief are causally linked, as well as

the impact on one’s perceived level of knowledge regarding computers.

Study participants were 309 Israeli students in grades seven through twelve,

48% male and 52% female, who completed a self-report questionnaire

covering demographic factors, computer use and experience, computer

attitudes and confidence based on measures available in the literature, and

perceived computer knowledge. Results indicated that computer use

variables were significantly and positively related to computer attitudes, as

demonstrated in other research studies. Positive correlations were also found

between computer experience and computer confidence, with a significant

30

relationship between computer attitudes and computer confidence, as well as

between both computer experience and confidence compared to computer

knowledge. Study results supported the hypothesis of a causal model for

computer experience, computer confidence, computer attitudes, and

perceived computer knowledge.

Other Moderators of Computer Attitudes. Research studies have

reported that in addition to amount and quality of direct and indirect

experience, other moderators of attitudes toward computers include the

demographic characteristics of gender, age, and education and income.

Gender and age will be discussed in some detail below. Studies regarding

income and education have reported inconsistent results due to the fact that

various economic groups have differential access to computer technology.

Also, the sample used in the present study will be fairly homogenous in terms

of level of education and socioeconomic status.

Gender. Howard, Murphy, and Thomas (1987) investigated the

possibility of a gender difference in computer-related attitudes. Previous

research has demonstrated mixed results on this gender question, which may

be related to the use of different measures and different populations of

interest. For example, some studies have found significant gender

differences in computer attitudes, usually with males being more positive

(i.e., Abler & Sedlacek, 1989; Jay, 1985; Jordan & Stroup, 1982) while others

have found no gender difference (i.e., Glass & Knight, 1988; Koohnag, 1986;

Loyd & Gressard, 1984).

Subjects in the Howard et al. (1987) study were 194 undergraduate

and graduate students at a large Midwestern university. One hundred and

31

seven students took a computer training course (17 males, 90 females) and a

comparison group of 87 students (55 males, 32 females) received no

computer training. Both groups of subjects completed the Computer Attitude

Scale (Loyd & Loyd, 1985) during the first and last weeks of the sixteen week

semester. Results indicated that students who received the training were

less anxious and more confident and reported greater interest in using

computers compared to those who received no training. No significant

gender differences were found. Overall, attitudes toward computers in

general significantly improved with training, while those in the no training

group remained the same. A limitation of these findings is that the computer

training group had a significantly higher rate of female participants.

It is possible that these studies reported in the 1980’s are presenting

outdated gender information, and that more current studies would better

answer the question of gender differences, since there is greater equity in

access to computers for both genders today. However, it is also possible that

current studies would find the same mixed results or slightly higher positive

attitudes and greater experience among males. Any remaining gender

differences could be due to interest in computers and programming following

the traditional reported gender differences that is found in mathematics,

since computer programming is heavily reliant upon mathematical skills.

This is likely to be supported by base rates if one looks at the number of

female versus male computer professionals.

Age. As intuitively expected, several studies have reported results

demonstrating that younger people hold more positive attitudes towards

computers compared to older people. This holds true for comparisons of

32

young adults (twenties and thirties) to older adults (fifty plus) (Ansley &

Erber, 1988) and middle-aged adults (late thirties to mid-forties) to older

adults (fifty plus) (Kerschner & Chelsvig Hart, 1984). It should be noted that

these reported age differences may represent a cohort effect rather than a

true age difference, since younger cohorts have increased contact with

computer technology in their daily lives. It is likely that if more recent studies

were available using current cohorts of younger people, they would report

increased exposure to computer technologies at even earlier ages, which

likely impacts their amount and quality of experience with computers as well

as their attitudes toward computers. It is also possible that today’s cohort of

older people would report an increased positive attitude toward technology

use due to increased exposure in their daily lives.

Practical Concerns Related to Technology Use in Psychology

An additional area of concern related to adaptation of computer

technologies into the practice of psychotherapy, as discussed by Murphy

(2000), is that the task demands associated with psychological services do

not take advantage of the capabilities of computers, and reveal their

weaknesses compared to the human therapist. Additionally, the practical

and economic factors related to widespread adoption in clinical practice are

potential obstacles and reasons for the current under-usage of available

technologies. Thus, those in private practice settings may be less likely to

incorporate available technology applications.

For example, Murphy (2000) pointed out that although there are many

software programs available to handle the demands of file maintenance,

computerized files require the additional clinician step of entering the client

33

data into the computer, which can provide long-term cost and time-saving

benefits, but initially are non-reimbursable. It appears that the greatest

savings in cost and time are derived from the computerized scoring and

interpretation applications, which take advantage of a computer’s capacity to

calculate, apply decision rules, and display results in a variety of formats

accurately, reliably, and rapidly. Additionally, with the patient entering test

responses directly into the computer, this reduces the amount of time a

clinician must spend on scoring and interpreting the assessment tool.

Ultimately, these are also computerized clinical activities that generate

revenue.

In terms of computer applications for treatment interventions, Murphy

(2000) pointed out that the potential benefits of technology aids for therapy

are predicated on a different system of service delivery than what currently

exists. For example, issues related to development of rapport, clinical

assessment, problem formulation, and treatment planning as they exist do

not support computer interview applications. However, there is the potential

for various technology-based applications to develop in public clinics,

capitated systems, or Web-based telehealth or managed care systems. It

should also be noted that with the insertion of technology applications and

decreased therapist-patient interaction, we stand to lose valuable

observational data especially during assessment procedures, and must rely

more on a patient being aware and honest about issues.

Treatment modalities that are currently able to take advantage of

technology applications are highly structured behaviorally-based

interventions that typically promote self-monitoring, rehearsal of coping

34

skills, and provide feedback for outcome measures. However, it is possible to

incorporate these same interventions via self-help books and other workbook

type materials, at much less expense (Murphy, 2000). Additionally,

psychologists are much more likely to encounter problems dealing with self-

concept and interpersonal relationships, which are not easily treated via

structured behavioral interventions (Murphy, 2000).

Ultimately, in order for computer applications to become more widely

adopted in psychotherapy practice, Murphy (2000) argued that the

technology must offer a clear benefit over simpler and less expensive

alternatives, as well as help to generate income. The process of getting new

technologically-based services covered as reimbursable activities would thus

require considerable effort on the part of both government legislators and

third party payers in terms of reimbursement issues, licensure and

malpractice considerations, standards and guidelines for practice, and

protecting the consumer’s privacy and confidentiality (Murphy, 2000;

Nickelson, 1998).

Given this understanding from the research literature regarding

personal and practice characteristics, it appears that these areas are where

messages aimed at attitude change would need to be focused (Marks et al.,

1998). However, it is also possible that the significant under-usage of

technology in therapy may be due to psychologists’ lack of familiarity with

available technologies, or the idea that computers are impersonal,

impractical, and not cost-effective for many practices, especially solo or small

group practices. These are questions for which we do not yet have answers

35

to, but need to understand before training and practice guidelines can be

established for the use of technology in psychotherapy.

Current Study

This study measured current technology usage and attitude toward

usage among psychologists in independent practice. Technology usage was

measured via self-report, and attitudes toward technology usage was

assessed using The Attitudes Toward Computers Questionnaire (ATCQ) (Jay,

1989).

The three main hypotheses for this study stated that, (1) those who

are newer to the profession, as determined by number of years licensed,

would be more accepting and more likely to use available technology

applications; (2) those with more positive attitudes toward computers, as

determined by the total score on the Attitude Toward Computers

Questionnaire (ATCQ, Jay, 1989), would be more likely to use available

technology applications; and (3) those not in solo private practice would also

be more accepting and more likely to use available technology applications.

This initial recruitment for the present study was undertaken as part of

a larger project with the purpose of establishing the foundation for a research

database of participants for the Independent Practice Network (IP-Net).

Therefore, it was hoped that this project would not only look at technology

issues, but also provide demographic information on the composition of

participants and establish the degree of representativeness or

generalizability of the sample to practicing psychologists. This study was the

initial effort for IP-Net and therefore also served to work out methodological

issues.

36

Given the rapid and widespread technological advances taking place in

our society, it is important to determine current usage and related attitudes,

as well as the factors affecting adoption of technology by psychologists.

Otherwise, there is no basis for deciding which technology applications to

adopt or where to focus future training. Thus, the profession may be left

faced with uncertainty and a lack of preparation to incorporate these

technological advances, as well as allowing psychology as a field to lag

behind technologically.

It should be noted that this study concerns technology in a broad

sense, encompassing all technological advances, not just specific computer

hardware and software use. This is consistent with how the terms technology

and computer are referred to in the research literature in this area. For

example, the technology applications categorized as first-wave, include items

such as telephone voice-mail, fax machines, and computer software.

Technology applications listed in the second-and third waves include more

complex technologies such as the Internet, virtual reality programs, and

video equipment. However, various studies that include discussions of these

diverse forms of technology all list them as “computer use” or “technology

use” (i.e., Marks, 1998; McMinn, 1999; McMinn et al., 1998). Additionally,

these studies state that technology and/or computer use in relation to

practice, fall under the even broader categories of telemedicine and

telehealth. A telehealth system has been defined as including the use of

educational, administrative, clinical, and technological functions of

communications technology and computers in the delivery of health care

services (Stamm & Perednia, 2000). Therefore, the terms technology and

37

computer are often used interchangeably throughout the available research

literature as well as throughout this study.

38

Chapter 2

Method

This study employed a survey method in which participants recruited

for a research network were able to respond either via the Internet

(www.division42.org and clicking on the IP-Net link) or by mail, depending on

participant preference. Therefore, we examined two self-selected groups,

one of online participants and one of mail participants. The survey asked

participants to provide information about themselves, their professional

practices, characteristics about the communities where they practiced, and

technology use in practice. Participants also completed a measure on

attitudes toward technology.

Participants

A random sample of 2,000 psychologists who are members of Division

42 (Psychologists in Independent Practice) of the American Psychological

Association (APA) were invited by letter to participate in the study.

Inclusionary criteria included: primary employment providing clinical services,

being a United States resident, and practicing independently for a minimum

of two years. We required a minimum of two years of licensed practice to

ensure that the individual had time to adequately establish practice beliefs,

attitudes, procedures, and behaviors. We excluded from our sample those

who still practiced under the supervision of another licensed psychologist, as

this may significantly impact their attitudes toward and usage of available

technologies for practice. Once data were collected, we then further

excluded participants who worked in a practice setting where they had little

39

control over what equipment is purchased and used as determined by a

questionnaire item (Appendix B, question #26).

Issues of ethnicity and gender were not expected to be a factor since

the study involved a highly specific sample population that is basically

homogeneous in terms of education and socioeconomic status. Also,

previous research does not indicate strong conclusive differences based upon

either ethnicity or gender, especially in relation to the population of

psychologists used for this study. Although more recent graduates are likely

to be in a lower income category compared to well-established practitioners,

this should not greatly impact socioeconomic status as a variable because

even the lowest income reported is expected to be "middle class”.

Random Sample Profile. The composition of the random sample and

the entire Division 42 membership provided by the APA Research Office is

detailed in Appendix C, and includes information on participants’ gender,

race, age, geographic location, degree, number of years licensed, and

employment setting.

Study Sample Profile. Of the 2,000 Division 42 members who were

contacted to volunteer to participate in this Independent Practice Network

(IP-Net) study, 265 (13%) agreed. Of this number, 130 (49%) volunteered to

respond online and 135 (51%) by mail. These self-selected groups formed

the original IP-Net sample. It should be noted that this overall recruitment

rate (13%) is much lower compared to other studies conducted using Division

42 members, which tends to be between 30% and 40% (Michael J. Murphy,

Ph.D., personal communication June, 2002).

40

Questionnaires were mailed to the 265 volunteers and we received a

total of 161 (61%) responses, 75 (47%) online and 86 (53%) via mail over a

4-week period. Therefore, we ultimately ended up with only 161 participants

from the 2,000 contacted for a low response rate of 8%.

Eight respondents (6 from the online group and 2 from the mail group)

had to be eliminated from the study due to the exclusionary criterion that

they did not report even moderate control over what technology equipment

and applications were purchased or used in their place of employment. It is

interesting to note that more members of the online group reported less

control over what technology items were purchased and used in their

practice settings.

Measures

All participants were asked to complete a questionnaire addressing

personal information, practice characteristics, technology use, and attitudes

toward technology (Appendix B). Both the questionnaire instrument and the

Website were piloted to insure readability and that the Web Page loaded

correctly and without extensive delay. Ten local practicing psychologists,

who are Division 42 members, were asked to participate in the pilot session.

They did not participate in the actual study. Their feedback was incorporated

in terms of revising any grammatical or typographic errors and rewording

items to increase comprehension. It should be noted that several pilot

members commented on the “offensive” gender tone used in the Attitudes

Toward Computers Questionnaire (ATCQ, Jay, 1989, Appendix B #39).

However, since this is a standardized measure no changes were made.

41

Items addressing personal information included age, race, gender,

income, type of degree and graduate program, number of years licensed,

number of years at current setting, and theoretical orientation. The

Theoretical Orientation Profile Scale-Revised (TOPS-R; Worthington & Dillon,

2002) was used to assess participants’ identification with six different schools

of therapy: (1) psychodynamic/psychoanalytic, (2) humanistic/existential, (3)

cognitive-behavioral, (4) family systems, (5) multicultural, and (6) feminist

(see Appendix B question #16). This assessment tool was included for the

purposes of another research study affiliated with the Internet data collection

method used in this particular study. However, the TOPS-R itself has no

significance to the present study, and therefore it is not discussed in detail. It

is sufficient to state that the instrument was reported to have adequate

reliability and validity scores, and appropriately classifies therapists in their

approach to utilizing therapy techniques falling into one of the above listed

schools.

Items addressing practice characteristics included type of practice

setting, geographic location, community size where practice is located,

person responsible for various office tasks, level of control over office

equipment purchased, and the average number of sessions patients are

seen.

The questionnaire also included items addressing amount of current

use of technology in practice, reimbursement for use, and anticipated future

use of technology in practice. Finally, the Attitudes Toward Computers

Questionnaire (ATCQ, Jay, 1989) was included (Appendix B question #39).

42

The Attitudes Toward Computers Questionnaire (ATCQ, Jay, 1989) is a

multidimensional measure assessing seven dimensions of attitudes toward

computers, as identified by previous research with adult and student

populations: (1) comfort; (2) efficacy; (3) gender equality; (4) control; (5)

dehumanization; (6) interest; and (7) utility (i.e., Bear, Richards, & Lancaster,

1987; Elkins, 1985; Jay, 1989; Krauss & Hoyer, 1984; Richards, Johnson, &

Johnson, 1986).

The comfort dimension assesses feelings of comfort with the computer

and its use. The efficacy component assesses feelings of competence with

the computer. The gender equality dimension assesses the belief that

computers are important to both men and women. The control dimension

assesses the belief that people control computers. The interest component

assesses the extent to which participants are interested in learning about and

using computers. The dehumanization component assesses the belief that

computers are in some way dehumanizing to use or interact with. The utility

dimension assesses the belief that computers are useful. Each dimension or

component is assessed by five or six items scored on a five point Likert scale

format, with response options ranging from strongly disagree to strongly

agree. A higher score represents a more positive attitude, with the

dehumanization component being reverse scored. The total score across all

dimensions represents a person’s attitude in general (given the seven

dimensions identified by previous factor research) toward computers.

The author of the measure reported internal consistency coefficients of

0.66 to 0.84 for the seven factors (Jay, 1989). Previous research using the

measure also identified Cronbach alpha coefficients 0.63 for the comfort

43

dimension, 0.69 for gender equality, 0.54 for control, 0.82 for

dehumanization, 0.64 for interest, 0.67 for utility, and 0.78 for efficacy (Czaja

& Sharit, 1998).

Procedures

All participants were treated in accordance with the standards set forth

in the “Ethics in Research with Human Participants” (American Psychological

Association, 2000), which included maintaining confidentiality of participant

responses and providing informed consent (see Appendix A which contains a

copy of the informed consent letter).

Participants were mailed a letter on American Psychological

Association (APA) Division 42 (Psychologists in Independent Practice)

letterhead inviting them to take part in the study (Appendix A contains a

copy of this letter). Participants gave informed consent by (1) directly

logging on to the study Web site and submitting responses, or (2) sending the

enclosed postage-paid postcard indicating their agreement to participate, as

well as their preferred method of data collection (online or mail) and means

of contacting them. Those choosing the mail method were sent the study

materials. Those choosing the online method (1) had immediate access by

following detailed instructions provided in the invitation letter and on the

Website, or (2) had their initial username and password sent to the email

address they provided on their response postcard.

Those who chose to respond via the online method and experienced

difficulty accessing the Website or needed clarification on a particular

questionnaire item directed their questions to a “contact” link on the Web

page that sent an e-mail message to the researchers. All e-mail questions

44

were responded to immediately. Those choosing the mail method of

response did not have immediate contact information provided, and had to

refer back to the initial invitation letter that listed telephone, fax, and e-mail

contact information for the researchers.

Data collected online were automatically (via computer program)

placed into computer software programs that began the data analysis

procedure. Data collected by mail were hand entered to a spreadsheet

program, then transferred to statistical analysis software. All data,

regardless of method of entry, were checked for accuracy.

45

Chapter 3

Results

We first examined descriptive statistics for available demographic and

practice variables for the group from which the IP-Net sample was drawn as

well as the entire Division 42 membership, and then the descriptive statistics

drawn from the responses of participants responding online and by mail.

Statistics included measures of central tendency and measures of variability,

and are provided for all demographic and practice variables. These data

allowed assessment of the extent that the sample was similar to Division 42

members and provide a foundation for generalizing findings. These data also

allowed us to evaluate the extent that we were successful in recruiting

participants for the IP-Net and the usefulness of the sample in making

inferences about members of the Division and private practitioners in

general.

Comparison of the samples of participants who responded online and

by mail provided information about any systematic differences between

these self-selected groups and determined the extent that systematic

differences may affect generalizability of online data collection. The

descriptive statistics also clarified important aspects of clinical practice

assessed in the current study that will be built on in future studies employing

IP-Net. Finally, we examined the findings as they relate to the central focus

of the current study, which is factors related to the patterns of technology

use by psychologists, with particular emphasis on the effect of attitudes

toward technology.

46

Inferential statistics were utilized for determining relationships

between variables and examining group comparisons of the online versus

mail groups, to determine if the two groups varied significantly in their

attitudes toward computers and level of technology usage, as well as any

differences related to personal and practice demographic variables.

Specifically, chi-square analyses were utilized with categorical data, and

ANOVA or t-tests were utilized with continuous data and are discussed in

more detail below. These statistical methods were also utilized for

hypothesis testing to determine if predictions could be made regarding a

practitioner’s attitude toward computers or level of technology usage based

upon the following variables: (1) number of years licensed, (2) score on the

Attitude Toward Computers Questionnaire (ATCQ, Jay, 1989), and (3) practice

setting. Finally, we examined findings to determine if additional variables

might predict technology use, attitudes toward technology, or group

membership of online versus mail for response method. Chi-square analyses

were chosen because of a conservative judgment made to treat Likert

variables on the ATCQ as categorical data.

The study began with a random sample of 2,000 members of Division

42 (Psychologists in Independent Practice) of the American Psychological

Association (APA) obtained from the APA’s Research Office in the form of

mailing labels. Inclusion criteria specified by the APA Research Office for the

sample included United States residency, licensure to practice psychotherapy

as a psychologist, and a minimum of two-years in practice based upon a

special assessment fee levied the third year of licensure.

Personal Characteristics of Study Participants

47

Table 1 presents the composition of those who volunteered to

participate in our study. This composition is considered in terms of the data

presented in Appendix C. The composition of our study sample was very

similar to the random sample, as well as to the entire Division 42

membership, in terms of gender, race, age, geographic location, degree,

number of years licensed, and practice setting.

Table 1. Comparison of Participant Characteristics from Total Volunteer Sample, Random Sample and Entire Division 42 Membership

VariableTotal Volunteer

Sample Random SampleDivision 42

MembershipN: 153 2,000 6,166Gender: Male

65.0%60.0% 62.4%

Female 35.0% 40.0% 37.6%Race: Caucasian

98.0%95.0% 92.0%

Hispanic 1.3% 1.5% 1.4%American Indian 0.7% 0.5% 0.2%

Age: Mean

53.9not available 56.6

Median 54.5 52.7 not availableSD 6.2 6.7 10.6

Range 38.0-74.0 30.0-70.0+ not available*Region:

Middle Atlantic 27.0% 22.8% 25.2%South Atlantic 14.0% 17.1% 17.6%

Pacific 13.0% 16.9% 15.2%East North Central 15.0% 14.3% 14.0%

New England 8.0% 8.8% 8.2%West South Central 6.0% 6.1% 6.0%West North Central 7.0% 5.6% 4.6%

Mountain 5.0% 4.7% 5.2%East South Central 5.0% 3.9% 3.3%

Degree: Ph.D.

86.0%87.0% 83.2%

Psy.D 5.0% 7.0% 5.9%Ed.D 9.0% 5.0% 6.3%

Years Licensed:Mean 20.7 not available 23.5

Median 21.5 19.9 not availableSD 6.7 6.6 10.4

48

Range 8.0-45.0 3.0-25.0+ not availableEmployment

Setting:Independent Practice 89.0% 83.0% 75.5* Middle Atlantic (New Jersey, New York, Pennsylvania); South Atlantic (Delaware, District of Columbia, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, West Virginia); Pacific (Alaska, California, Hawaii, Oregon, Washington); East North Central (Illinois, Indiana, Michigan, Ohio, Wisconsin); New England (Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont); West South Central (Arkansas, Louisiana, Oklahoma, Texas); West North Central (Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, South Dakota); Mountain (Arizona, Colorado, Idaho, Montana, Nevada, New Mexico, Utah, Wyoming); East South Central (Alabama, Kentucky, Mississippi, Tennessee)

49

Given that our study participants are very similar to both those in the

random sample and the entire membership in terms of gender

(approximately 60% males and 40% females across all three groups), age

(approximately mid-fifties across all three groups), race (over 90% Caucasian

in all three groups), degree (over 80% hold a Ph.D. in all three groups), years

licensed (around 20 years for all three groups), practice setting (on average

83% independent practice across the three groups) and geographic

distribution, it can be stated that our study sample is representative of not

only the random sample of Division 42 members provided by the APA

Research Office, but also the entire Division 42 membership. This is very

important given that one goal of our study was to recruit a representative

volunteer sample of independent practitioners from Division 42 who would

become the foundation of the IP-Net for future research studies, and the

collection of longitudinal data on patterns and trends of those in independent

practice.

Table 2 examined the composition of those who volunteered to

participate in our study in terms of their response method of online versus

mail, and compared the two groups on the same characteristics as those

presented in the previous table. Although there are no significant differences

between the two groups, it is interesting to note that the online group

reported a smaller percentage of individuals working primarily in independent

practice settings (85%), compared to the mail group (93%). This difference

fits with information discussed in chapter 1 stating that it may be cost-

prohibitive to incorporate technology applications into an independent

practice setting, whereas if one is at a larger group practice, hospital, or

50

academic setting, it is more likely that funding will be available to support the

incorporation of various technology applications.

51

Table 2. Participant Characteristics from Responses to Surveys for Online and Mail Groups

ONLINE GROUP MAIL GROUPVARIABLE Number Percent Number Percent

Gender: Male 43.0 64.0% 55.0 66.0%

Female 24.0 36.0% 29.0 34.0%Race: Caucasian 66.0 96.0% 84.0 100.0%

Hispanic 2.0 3.0% 0.0 0.0%American Indian 1.0 1.0% 0.0 0.0%

Age: Mean 53.5   54.4  

Median 54.0   55.0  SD 6.0   6.4  

Range40.0-66.0   38.0-74.0  

*Region: Middle Atlantic 21.0 30.0% 21.0 25.0%

South Atlantic 8.0 12.0% 13.0 16.0%Pacific 12.0 17.0% 8.0 10.0%

East North Central 8.0 12.0% 14.0 17.0%New England 4.0 6.0% 9.0 11.0%

West South Central 6.0 9.0% 3.0 4.0%West North Central 5.0 7.0% 6.0 7.0%

Mountain 3.0 3.0% 4.0 5.0%East South Central 2.0 3.0% 5.0 6.0%

Degree: Ph.D. 59.0 87.0% 72.0 86.0%

Psy.D 6.0 9.0% 2.0 2.0%Ed.D 3.0 4.0% 10.0 12.0%

Years Licensed: Mean 20.0   21.4  

Median 21.0   22.0  SD 7.0   6.3  

Range 8.0-35.0   9.0-45.0  Employment Setting:      

Independent Practice 58.0 85.0% 76.0 93.0%Academic 4.0 6.0% 2.0 2.0%

Hospital 4.0 4.0% 2.0 2.0%Clinic 1.0 1.0% 0.0 0.0%

Other Human Service 2.0 3.0% 2.0 2.0%* Same regional distribution as Table 1

52

Practice Characteristics of Study Participants

In addition to data on participant’s personal characteristics, we also

collected information related to their practice of psychology, which is

presented in Tables 3-5. Table 3 presents information about how and where

the individual works, including number of years at the current practice

setting, income, theoretical orientation toward practice, if they measure

patient satisfaction or perform outcome research, and their community

demographics such as socioeconomic status and population size of the city

where they work.

Socioeconomic and geographic (population size of community)

information was based upon demographic data obtained from the United

States Census Bureau (United States Census Bureau) and ESRI Business

Information Solutions (ESRI Business Information Solutions) according to the

zip code listed by participants (note that individual zip codes were examined

in terms of city demographics; for example, a city like Manhattan is

represented by many individual zip codes).

Results of a t-test indicated that there was a significant difference

between the online and mail groups in terms of average income t (129) = -

3.18, p <.05 (one-tailed), d = -0.56. The average income reported by the

mail group ($107,000, SD = $48,696) was significantly higher than the

average income reported by the online group ($81,388, SD = $40,292).

53

Table 3. Practice Characteristics from Responses to Surveys for Online, Mail, and Total Sample

VARIABLE ONLINE GROUP MAIL GROUP TotalYrs @ Current Setting:            

Average 16.4   16.6   16.5  Median 17.0   17.0   17.0  

SD 7.5   7.3   7.4  Range 1.0-31.0   0.5-35.0   0.5-35.0  

*Income:      Average 81,388 107,000 94,194Median 100,000   100,000   100,000  

SD 40,292   48,696   44,494  

Range30K-200K  

16K-250K  

16K-250K  

Theoretical Orientation:            

Psychodynamic 9.0 13% 15.0 18% 24.0 16%Humanistic 6.0 9% 4.0 5% 10.0 7%

CBT 24.0 36% 30.0 37% 54.0 36%Family Systems 9.0 13% 7.0 8% 16.0 11%

Feminist 3.0 4% 1.0 1% 4.0 3%Multicultural 3.0 4% 2.0 2% 5.0 3%

Eclectic 14.0 21% 24.0 29% 38.0 24%Measure Patient Satisfaction:            

Yes 17.0 28% 16.0 21% 33.0 25%No 44.0 72% 59.0 79% 103.0 75%

Perform Outcome Research:            

Yes 8.0 13% 7.0 10% 15.0 11%No 55.0 87% 66.0 90% 121.0 89%

SES of Community: High 31.0 45% 30.0 36% 61.0 40%

Middle 32.0 46% 47.0 57% 79.0 52%Low 6.0 9% 6.0 7% 12.0 8%

Population Size:            Under 10000 –

50,000 29.0 44% 34.0 41% 63.0 42%50,001 – 500,000 26.0 37% 32.0 39% 58.0 38%500,001 – over 1

million 13.0 19% 17.0 20% 30.0 20%*Denotes significant difference (p <.05) between online and mail groups

Practice Structure and Organization

Data collected on how participants structure and organize their

practice are presented in Table 4. We inquired how the following

administrative tasks were managed: billing, scheduling, accounts payable,

54

answering the telephone, and word processing. Specifically, we asked

participants to rate who in their practice was primarily responsible for

managing these tasks. Participants had a choice of responding in the

following manner: self, employee, contracted out and significant other. There

were no significant between group differences for any of the tasks. However,

it can be noted that the online group reported performing scheduling,

accounts payable, phone, and word processing tasks themselves more often

compared to the mail group, who reported more often that an employee

handled the task. The mail group reported managing the billing tasks

themselves more often as compared to the online group, who reported more

often that an employee handled the billing tasks.

Table 4. Person Responsible for Various Administrative Tasks from Responses to Surveys for Online, Mail, and Total Sample

ONLINE GROUP MAIL GROUP TotalVARIABLE Number Percent Number Percent Number Percent

Billing:            Self 32 48% 43 52% 75 50%

Employee 25 37% 24 29% 49 33%Contracted Out 7 11% 13 15% 20 13%

Significant Other 3 4% 3 4% 6 4%Scheduling:            

Self 51 75% 56 68% 107 71%Employee 16 24% 25 30% 41 27%

Contracted Out 0 0% 0 0% 0 0%Significant Other 1 1% 1 1% 2 1%

Accts Payable:            Self 47 70% 45 54% 92 61%

Employee 14 21% 28 34% 42 28%Contracted Out 2 3% 7 8% 9 6%

Significant Other 4 6% 3 4% 7 5%Phone:            

Self 45 66% 44 54% 89 59%Employee 20 29% 34 41% 54 36%

Contracted Out 2 3% 3 4% 5 3%Significant Other 1 1% 1 1% 2 1%

Word Processing:            

Self 44 65% 39 48% 83 55%

55

Employee 16 24% 29 35% 83 30%Contracted Out 6 9% 9 11% 15 10%

Significant Other 2 3% 5 6% 7 5%

56

Average Number of Clinical Sessions per Patient

Data collected on the average number of sessions a patient was seen

by participants at their respective practices are in Table 5. Overall,

respondents reported that on average 6.5% of their caseload was seen for

only one session, 12.8% of their caseload was seen for 2-5 sessions, 23.5%

was seen for 6-10 sessions, 18.9% was seen for 12-15 sessions, 17.4% were

seen for 16-20 sessions, and 30.9% were seen for over 21 sessions. There

were no significant between group differences for average number of patient

sessions.

Table 5. Average Number of Clinical Sessions per Patient by Percent from Responses to Surveys for Online, Mail, and Total Sample

Avg Sessions ONLINE GROUP MAIL GROUP TOTAL

Per Patient Percent Percent Percent1      

Average 6.70% 6.25% 6.48%Range 1.00-30.00% 1.00-20.00% 1.00-50.00%

2-5  Average 11.80% 13.74% 12.77%

Range 2.00-30.00% 1.00-35.00% 1.00-40.00%6-10  

Average 23.30% 23.65% 23.48%Range 5.00-70.00% 4.00-64.00% 4.00-70.00%

11-15  Average 19.50% 18.30% 18.90%

Range 1.00-50.00% 1.00-40.00% 1.00-50.00%16-20  

Average 17.02% 17.80% 17.41%Range 1.00-40.00% 1.00-45.00% 1.00-45.00%

21+  Average 29.59% 32.14% 30.87

Range 1.00-95.00% 1.00-100.00% 1.00-100.00%

57

Current and Future Technology Applications in Practice

Specific to this study and its hypotheses, data were collected on

participants’ use of technology applications in practice. Table 6 details data

collected from participants regarding the rates of current use and anticipated

future use of various technology applications in practice. For future use,

participants were asked to indicate the technology applications they thought

they might add to their practice, but not count continued use of applications

currently being employed in their practice. The technology applications

inquired about in this study were those most frequently reported in the

literature. Additionally, the present study inquired about the following

Internet categories that were absent from previous studies: Internet for

continuing education credits, Internet for marketing, and Internet for job

recruitment. The results reported in this study demonstrate increased use

compared to the most recent studies available in the literature.

Examination of Table 6 revealed that in terms of current technology

use in practice, respondents in the online group reported overall higher rates

compared to the mail group for billing, scheduling, maintaining files, outcome

research, recording patient homework, testing, word processing, e-mail with

other professionals, e-mail with patients, e-mail with supervisees, use of the

Internet to obtain information, use of the Internet for therapy, use of the

Internet for marketing and advertising, and use of the Internet for job

recruitment. The only technology application that the online and mail groups

reported equal rates of endorsement was use of the Internet for obtaining

continuing education credits. It should be noted that no participants

endorsed current or anticipated future use of technology applications for an

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intake interview, which is the only category with no endorsement across both

groups.

Chi-square analyses for between group comparisons on technology

use, as determined by participant’s yes or no response, revealed that the

online group was significantly more likely to use technology applications for

the following tasks: maintaining files X2(1, N = 46) = 8.02, p = .01), outcome

research X2(1, N = 13) = 5.60, p = .02), recording patient homework X2(1, N

= 12) = 7.44, p = .01), e-mail with professionals X2(1, N = 83) = 8.88, p =

<.01), e-mail with patients X2(1, N = 40) = 12.95, p = <.01), and use of the

Internet for information X2(1, N = 95) = 8.44, p = <.01).

Overall for both groups, in terms of anticipated future technology use

in practice, the only areas reporting a slight increase were an additional 6%

for billing, 6% for recording patient homework, 6% for testing, and 10% for

using the Internet to obtain continuing education credits. It should also be

noted that both groups reported no anticipated future use of e-mail with

patients, however, members of both the online and mail groups did report

current use of this technology application. There were no significant between

group differences related to anticipated future technology use. The question

for future technology use specifically asked for those individuals not currently

using a particular application, if they anticipated using it in the near future

(approximately 6 months). Therefore, the potential rates of future use were

limited by those already reporting current use.

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Table 6. Current and Anticipated Future Technology Use in Practice from Responses to Surveys for Online, Mail, and Total Sample

ONLINE GROUP MAIL GROUP TotalVARIABLE Number Percent Number Percent Number Percent

Current Tech Use:            Billing 58 84% 63 75% 121 80%

Scheduling 21 30% 16 19% 37 25%*Maintaining Files 29 42% 17 20% 46 31%

*Outcome Research 11 15% 2 2% 13 8%*Recording Pt HW 12 17% 0 0% 12 7%

Testing 34 49% 36 43% 70 46%Intake Interview 0 0% 0 0% 0 0%Word Processing 58 84% 62 74% 120 79%

*E-mail Professionals 47 68% 36 43% 83 55%

*E-mail Patients 29 42% 11 13% 40 27%E-mail Supervisees 8 12% 3 4% 11 8%

*Internet for Info 52 75% 43 52% 95 63%Internet for Therapy 6 9% 3 4% 9 7%

Internet for CEUs 5 7% 6 7% 11 7%Internet for

Mktg/Ads 8 12% 6 7% 14 10%Internet for Job

Recruit 1 1% 1 1% 2 1%Future Tech Use:            

Billing 5 7% 3 4% 8 6%Scheduling 1 1% 1 1% 2 1%

Maintaining Files 1 1% 2 2% 3 2%Outcome Research 3 4% 4 5% 7 5%

Recording Pt HW 4 6% 4 5% 8 6%Testing 2 3% 7 8% 9 6%

Intake Interview 0 0% 0 0% 0 0%Word Processing 0 0% 1 1% 1 1%

E-mail Professionals 3 4% 3 4% 6 4%E-mail Patients 0 0% 0 0% 0 0%

E-mail Supervisees 3 4% 1 1% 4 3%Internet for Info 0 0% 4 5% 4 3%

Internet for Therapy 3 4% 0 0% 3 2%Internet for CEUs 8 12% 7 8% 15 10%

Internet for Mktg/Ads 3 4% 5 6% 8 5%

Internet for Job Recruit 1 1% 1 1% 2 1%

*Denotes significant difference (p <.05) between online and mail groups

Average Time Spent per Week with Various Technology Applications

We also asked for detailed information on the average amount of time

per week participants spent using the telephone, e-mail, Internet, and video

60

applications, and if they were reimbursed for these services. Results detailed

in Tables 7 and 8 show the number of participants who stated they used an

application, as well as the average number of hours per week (broken down

into minute increments) they used the application.

Previous research studies reported in the literature have identified the

telephone as “universally accepted” in terms of its use in practice. This is

also the category for which the highest rates of average weekly use were

reported by our sample. The only significant difference noted between the

online and mail groups was in terms of the average amount of time per week

spent doing telephone referrals, with the online group reporting a higher

amount t (41) = 2.19, p <.05 (one-tailed), d = 0.68.

Table 7. Average Weekly Telephone Use and Reimbursement in Practice from Responses to Surveys for Online, Mail, and Total Sample

ONLINE GROUP MAIL GROUP TotalVARIABLE Number Percen

tNumber Percen

tNumber Percen

tTelephone Consultation:

N=31 45% N=32 38% N=63 41%

Hours Per Week Mean

1.30 1.30 1.30

Median 1.00 1.00 1.00SD 0.65 0.82 0.74

Range 0.10-3.00 0.10-3.50 0.10-3.50Reimbursed N=14 41% N=17 51% N=21 33%

Telephone Therapy: N=23 33% N=33 39% N=56 37%Hours Per Week

Mean 1.30 1.25 1.23

Median 1.00 1.00 1.00SD 0.94 0.72 0.83

Range 0.05-2.00 0.25-3.00 0.05-3.00Reimbursed N=22 85% N=13 38% N=35 63%

Telephone Supervision:

N=4 6% N=7 8% N=11 7%

Hours Per Week Mean

0.90 1.00 0.95

Median 1.00 1.00 1.00SD 0.25 0.50 0.38

Range 0.50-1.00 0.50-2.00 0.50-2.00

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Reimbursed N=4 100% N=3 43% N=7 64%

* Telephone Referrals:

N=22 32% N=21 25% N=43 28%

Hours Per Week Mean

1.30 0.98 1.14

Median 1.00 1.00 1.00SD 0.52 0.43 0.48

Range 0.25-4.00 0.25-2.00 0.25-4.00Reimbursed N=2 9% N=1 3% N=3 7%

*Denotes significant difference (p <.05) between online and mail groups

Table 8. Average Weekly E-mail Use and Reimbursement in Practice from Responses to Surveys for Online, Mail, and Total Sample

VARIABLE ONLINE GROUP MAIL GROUP TOTALE-mail

Consultation:N=7 10.0% N=7 8.0% N=14 0.9%

Hours Per Week Mean

0.75 0.80 0.78

Median 1.00 1.00 1.00SD 0.32 0.31 0.31

Range 0.25-1.00 0.25-1.00 0.25-1.00Reimbursed N=2 29.0% 1.00 14.0% N=3 21.0%

E-mail Therapy: N=2 3.0% N=1 1.0% N=3 0.2%Hours Per Week Mean

0.75 0.50 0.63

Median 0.75 0.50SD 0.35

Range 0.50-1.00 0.50-1.00Reimbursed N=0 0.0% N=00 0.0% N=0 0.0%

E-mail Supervision: N=2 3.0% N=0 N=2 3.0%Hours Per Week Mean

0.55 0.55

Median 0.55 0.55SD 0.63 0.63

Range 0.10-1.00 0.10-1.00Reimbursed N=2 100.0

%N=2 100.0%

E-mail Referrals: N=4 6.0% N=3 4.0% N=7 0.5%Hours Per Week Mean

0.75 0.50 0.63

Median 1.00 0.25 0.63SD 0.43 0.43 0.43

Range 0.25-1.00 0.25-1.00 0.25-1.00Reimbursed N=0 N=0 N=0 0.0%

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Although reporting some endorsement, the other categories of e-mail,

use of the Internet, and video technologies in clinical practice were still low in

comparison to results reported for the use of the telephone in practice.

Reported use for Internet and video applications were near zero, and

therefore are not presented in table format. Additionally, it should be noted

that analyses were not run for the e-mail category due to the low rate of

endorsement by participants.

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Attitudes Toward Technology

Also specific to this study and its hypotheses are the results from the

Attitudes Toward Computers Questionnaire (Jay, 1989) with its seven

dimensions of (1) comfort, (2) efficacy, (3) gender equality, (4) control, (5)

dehumanization, (6) interest, (7) utility, and a total score. Fifty-four out of 69

people from the online group (78%) and 76 out of 84 people from the mail

group (90%) responded to the measure. It should be noted that the ATCQ

measure appeared as the last item on the questionnaire. It is likely that the

lower response rate from online group participants is due to the placement of

this item, since the questionnaire had to be answered in one sitting for the

online group with data submitted thru the Web site, and the online session

could not be saved for completion at a later time. Given the overall long

length of our questionnaire (an issue noted by many respondents in terms of

feedback), it is probable that members in the online group may have tired or

not had the extra time to respond to this last item, but also did not want to

wait to complete the questionnaire at a later time and lose all of their current

data responses. Not allowing participants to save responses to complete at a

later time was done as a security measure to protect participant

confidentiality. However, it appears that this may have been done at the

expense of an increased response rate. A shorter length questionnaire would

have likely remedied this issue and should be considered for future studies

using the Internet for data collection.

As predicted, results of analyses indicated that the online group

reported significantly more positive attitudes as determined by higher scores

on the ATCQ in all areas, with the exception of gender equality, where there

64

was no significant difference between the online and mail groups. See Table

9 below for a summary of statistical results.

65

Table 9. Attitudes Toward Computer Questionnaire Scores from Responses to Surveys for Online, Mail, and Total Sample

ONLINE GROUP

MAIL GROUP TOTAL STATISTICAL

VARIABLE N=54 N=76 N=130 Results

(df=128)*Comfort:    

Mean 3.9 3.3 3.6 t = 3.92Median 4.0 3.0 3.5 d = 0.69

SD 0.8 0.9 0.9*Efficacy:    

Mean 4.4 4.1 4.3 t = 3.01Median 5.0 4.0 4.5 d = 0.53

SD 0.5 0.6 0.6Gender Equality:    

Mean 4.5 4.3 4.4 t = 1.80Median 5.0 4.0 4.5 d = 0.32

SD 0.5 0.7 0.6*Control:    

Mean 4.3 4.0 4.2 t = 3.37Median 4.0 4.0 4.0 d = 0.60

SD 0.5 0.5 0.5*Dehumanization:    

Mean 1.9 2.3 2.1 t = -3.21Median 2.0 2.0 2.0 d = -0.57

SD 0.7 0.7 0.7*Interest:    

Mean 4.3 3.9 4.1 t = 3.75Median 4.0 4.0 4.0 d = 0.66

SD 0.6 0.6 0.6*Utility:    

Mean 4.2 4.0 4.1 t = 2.07Median 4.0 4.0 4.0 d = 0.37

SD 0.6 0.5 0.6*Total:    

Mean 4.3 3.9 4.1 t = 4.87Median 4.0 4.0 4.0 d = 0.86

SD 0.4 0.5 0.5*Denotes significant difference (p <.05) between online and mail groups

Note: Range of scores = 1 to 5 (1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, and 5 = Strongly Agree). The Dehumanization dimension is reverse scored. Higher scores indicate increased levels of comfort using computers, increased feelings of efficacy using computers, increased feelings that computers are important for both genders, increased belief that people are in control of computers, increased belief that computers cannot operate without human interaction, increased interest in using computers, and increased belief that computers are useful. The total score is the overall average of the other seven dimensions.

66

Hypotheses Testing and Predictor Variables

The three main hypotheses for this study were that, (1) those who are

newer to the profession, as determined by number of years licensed, would

be more accepting and more likely to use available technology applications;

(2) those with more positive attitudes toward computers, as determined by a

total score of 4 or above on the Attitude Toward Computers Questionnaire

(ATCQ, Jay, 1989), would be more likely to use available technology

applications; and (3) those not in solo private practice would also be more

accepting and more likely to use available technology applications.

Technology use was examined in terms of overall reported use, taken as the

sum total of the number of categories endorsed as presented in Table 6.

First Hypothesis. ANOVA revealed that number of years licensed was

found to be unrelated to amount of technology use reported F (17, 133) =

0.95, p=0.51). Attitudes toward technology were also found to be unrelated

to number of years licensed F (3, 149) = 2.04, p = 0.11. Therefore, we must

reject the alternative hypothesis and accept the null hypothesis that number

of years licensed is independent of technology use and attitudes toward

technology.

ANOVA measures were also performed to determine if age would have

better predicted amount of technology use and attitudes toward technology.

Age was also found to be unrelated to amount of technology use F (17, 133)

= 1.55, p=.09) or attitudes toward technology F (3, 149) = 1.10, p=.35.

Third Hypothesis. Chi-square analyses were used to examine

differences in technology use and attitudes based upon practice setting

(independent practice, academic, hospital, clinic, and other). Practice setting

67

was found to be unrelated to amount of technology use X2(10, N = 128) =

7.30, p = .70) or attitudes toward technology X2(33, N = 153) = 35.32, p

= .36). Therefore, we must reject the alternative hypothesis and accept the

null hypothesis that practice setting is independent of technology use and

attitudes toward technology.

Second Hypothesis. Our second hypothesis concerning attitudes

towards technology and use of technology applications, tested using chi-

square analyses, was partly supported in terms of certain technology

applications. Those with more positive attitudes toward technology (as

measured by their total score on the ATCQ of 4 or higher, given that a score

of 3 or below represented neutral or negative attitudes), reported

significantly higher levels of current technology use (measured by the total

number of technology applications endorsed as being used by participants) in

the following areas: scheduling X2(4, N = 130) = 23.92, p = <.01),

maintaining patient files X2(4, N = 130) = 13.06, p = .01), performing

outcome research X2(4, N = 130) = 9.99, p = .04), testing X2(4, N = 130) =

13.41, p = .01), using the Internet to obtain information X2(4, N = 130) =

22.19, p = <.01), using the Internet for therapy X2(4, N = 130) = 12.85, p

= .01), using the Internet to obtain continuing education credits X2(4, N =

130) = 9.36, p = .05), using the Internet for marketing/advertising X2(4, N =

130) = 10.64, p = .03), and using the Internet for job recruitment X2(4, N =

130) = 82.86, p = <.01). It should be noted that use of the Internet for job

recruitment had an overall very low reported rate of use (1%). Therefore, we

can reject the null hypothesis and accept the alternative hypothesis that use

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of the technology applications listed above is related to attitudes toward

technology.

Chi-square analyses also revealed that no significant differences were

noted for billing X2(4, N = 130) = 8.61, p = .07), recording patient homework

X2(4, N = 130) = 4.13, p = .39), word processing X2(4, N = 130) = 4.70, p

= .32), e-mail with other professionals X2(4, N = 130) = 1.58, p = .81), e-mail

with patients X2(4, N = 130) = 2.14, p = .71), and e-mail with supervisees

X2(4, N = 130) = 3.32, p = .51). Therefore, we must reject the alternative

hypothesis and accept the null hypothesis that use of the technology

applications listed above is independent of attitudes toward technology. It

should be noted that billing and word processing were the two technology

applications with the highest total rates of reported use in this study (80%

and 79%, respectively), which may be related to the absence of significant

findings. Additional chi-square analyses determined that gender, degree,

theoretical orientation, geographic location, nor population size were related

to technology use or attitudes toward technology.

Additional Between Group Differences for Online and Mail Responders

In looking at between group differences, results of chi-square analyses

determined that type of graduate degree and theoretical orientation were

both independent of choice of response mode (online versus mail). Results of

ANOVA tests determined that number of years licensed and age were also

independent of response group (online versus mail). Therefore none of these

variables can be used as predictor variables for response method group

categorization.

Possible Subgroup Differences

69

In looking at the possibility of various subgroups emerging from our

sample, chi-square analyses determined that neither population size nor

geographic location were related to gender, technology use, attitudes toward

technology, and the office tasks reported in Table 4 above (billing,

scheduling, accounts payable, phone, and word processing). ANOVA

determined that neither population size nor geographic location was related

to income or the average number of sessions per patient. It should be noted

that the relationship between population size and income approached

statistical significance F (9, 143) = 1.85, p=.06, with those practicing in

locations with larger populations reporting larger incomes, but we cannot

reject the null hypothesis that the two are independent. In terms of gender

differences, results of chi-square analyses determined that there is no

relationship between gender and amount of technology use or attitudes

toward technology.

Use of the Internet for Data Collection

For those who responded via the Internet, 23% reported that this was

their first Web survey, 29% reported that our Web survey was easier to use

compared to past Web surveys, 44% rated the difficulty level to be the same,

and 4% rated it as more difficult to use compared to other Web surveys.

Forty-two percent of those responding stated that the option to participate

via the Web increased their desire to participate, and 62% reported that had

the survey only been available via the Web, they still would have

participated. This is an important consideration for future IP-Net studies

employing the same methods of data collection.

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Chapter Four

Discussion

The primary focus of the current study was the investigation of

technology use and related attitudes toward technology by psychologists in

independent practice. In addition, this study served as the initial step in a

larger effort to develop a database, IP-Net, which will allow for on-going

investigation of patterns and trends in independent practice. While this

paper does not go into detail discussing practice research networks, as stated

earlier, it should be noted that these are becoming a popular new method for

collecting real-time data with high internal and external validity, embraced by

state organizations as well as the American Psychological Association, and

other health related associations (Borkovec, Echemendia, Ragusea, & Ruiz,

2001).

In this chapter we will first discuss the methodological factors related

to the present study and the overall IP-Net project. We will then turn to an

examination of the two response groups and the characteristics of

independent practitioners and their practices. Next, we look at the findings

related to technology use in practice and the relationships between

participants’ attitudes toward technology and the use of technology

applications in the administrative and clinical aspects of practice, as related

to the study’s hypotheses. Finally, we end with a discussion of conclusions

and future directions based upon the findings of the present study.

Findings Related to Survey Method

Collection of data by online surveys offers many potential advantages

to investigators and is discussed below. In relation to using the Internet to

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collect data for a practice research network, online data collection facilitates

repeatedly surveying the same participants. However, research has not yet

provided conclusive information about important dimensions of this approach

to data collection. Therefore, we do not know if there are systematic

differences between respondents who respond online and those who respond

by mail. We also do not know if the approach we have taken to repeatedly

survey the same participants through IP-Net will yield usable data. This study

provides initial findings to help clarify these issues. In the course of our study

we encountered some practical and procedural issues that arise from the use

of this fairly new methodology, which are also addressed below.

Using the Internet in Research. A study by Mehta and Sivadas (1995)

compared response rates and response content in mail versus electronic mail

surveys. Study results indicated that (1) e-mail survey responses were

received more quickly (2-3 days) compared to mail surveys (3 weeks); (2) e-

mail surveys were much less expensive (free) compared to mail surveys

(minimum cost of $0.58 each piece); (3) these first two findings become even

more important when considering contacting international respondents (i.e.,

Mehta & Sivadas, 1995 had 150 respondents from outside the USA); (4) e-

mail survey allowed for quick clarification (respondents could email the

researchers questions regarding the survey as they were working on it (i.e.,

some European respondents did not know what the term “significant other”

meant and were able to question the researchers via e-mail before

responding incorrectly to the question); and (5) e-mail responses to open-

ended questions were judged to be qualitatively more informative and

detailed compared to mail responses.

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Similar results were found with the present study in certain areas. For

example, Internet responses were logged quicker than receipt of mail

response, however we were unable to do a true comparison test due to the

fact the mail materials were mailed out from APA Division 42’s office in

Arizona without keeping record of exact dates of mailing. The cost savings

were substantial compared to the mail survey. For those who did not directly

log on to the Website, we incurred the cost of their reply postcard

(approximately $0.20), as well as the cost of the mailing of the actual study

materials (approximately $0.90) plus the cost of printing the mail materials

and the envelopes.

The online method in this study also allowed for a quick response time

for questions e-mailed through the Web page by participants, versus those

who wrote in the margins of the mail instruments and never received a

response. The online method created a natural “paper trail” which allowed

for automatic tracking of who had responded to the survey and who needed

to receive a follow-up reminder e-mail, versus having to manually track the

mail method.

Results reported by Mehta and Sivadas (1995) are similar to results

reported in related studies (i.e., Stanton, 1998; Schmidt, 1997; Schaefer &

Dillman, 1998). Studies incorporating data collection via the Internet are

becoming popular for those in health professions, as evidenced by the

increasing number of practice research networks (i.e., Zarin, Pincus, West, &

McIntyre, 1997; Zarin et al., 1998; Pincus et al., 1999; Wasserman, Croft, &

Brotherton, 1992; Green et al., 1984; Barlow, 1996).

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Additional Advantages to Internet Research. Other advantages to

using a Web-based survey method of data collection include supply of a wider

diversity of participants, reduction of the influence of demand characteristics,

and efficient administration of survey protocols (Hewson, Laurent, & Vogel,

1996). Surveys that employ the Internet for data collection provide access to

a wider diversity of participants, and also allows for targeting of specific

groups in a more efficient way than mail surveys.

Internet surveys also provide greater anonymity than mail surveys,

which has been found to reduce the effects of confounding factors due to

demand characteristics, different treatment due to biopsychosocial

attributes, and social conformity, thus encouraging greater honesty and

cooperation from participants (Esposito, Agard, & Rosnow, 1984; Rosenthal,

1967). To ensure confidentiality, responses submitted via the Internet or e-

mail must have any identifying information removed and replaced with a

random subject identification number. This is how online data were managed

in our study, and participants were informed of this in the informed consent

letter (Appendix A). Additionally, password information should be stored in a

separate database to protect participant’s confidentiality. This particular

study also used password protections, and protected participant

confidentiality by storing any identifying information in a separate database

and assigning random subject identification numbers to participants.

Another advantage with online research is that survey data that are

directly entered via the Web by participants eliminates the data entry step

for the researcher. Data entered this way can also eliminate the potential for

unwanted responses, by forcing a choice for participants (i.e., only allowing a

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numerical response to be entered thus avoiding participants from providing

unwanted information). These types of checks that avoid unwanted response

types, duplicate submissions, and other potential problems must be put in

place by a computer programmer, which can significantly add to the cost of a

research study, and therefore is not always a viable option. This particular

study was fortunate to have had a professional computer programmer that

worked on the project at no cost. Therefore many of these checks were

employed, but not all possible checks, due to the fact that the programmer

designed the Website on a voluntary basis in his spare time.

Disadvantages to Internet Research. In terms of negative aspects to

collecting data via this method, study results from Mehta and Sivadas (1995)

indicated that (1) not everyone has access to the Internet or e-mail or uses

it; (2) it may be more appropriate to use Internet or e-mail surveys with

middle to upper-middle class respondents, or respondents that belong to a

targeted population with narrowly defined interests; (3) Internet and e-mail

users are sensitive about their accounts and receiving unsolicited messages;

(4) most Internet and e-mail users have to pay to receive their messages

(e.g., monthly fees for having an Internet service provider) unlike getting

their mail for “free” from their mailbox; (5) because of the annoyance

associated with receiving unsolicited e-mail messages, the researchers in the

Mehta and Sivadas (1995) study had to eliminate their “unsolicited group”

from data analyses, because so many of the members of this group

requested to be removed from the mailing list (therefore it is a good idea to

obtain permission from respondents to send an e-mail survey, but this may

also leave the researcher with a self-selected sample); and (6) cannot provide

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the same type of incentives as with a mail survey (i.e., cannot send money

via e-mail) therefore you may have lower response rates but those who do

respond will be more motivated (a possible issue of sample bias). Another

consideration to keep in mind when designing a Web-based survey is that not

all browsers have the same functional capacities nor do all Internet service

providers allow for similar speed connections. Therefore, having minimal

graphics and testing on various browsers will help to eliminate potential

problems. This consideration was taken into account when designing the

Web page for our study.

Issues Related to Participating in IP-Net. Of the 2,000 Division 42

members who were contacted to volunteer to participate in this IP-Net study,

265 (13%) agreed to be part of the study. This is much lower compared to

other studies conducted using Division 42 members, which tends to be

between 30% and 40% (Michael J. Murphy, Ph.D., personal communication

June, 2002). Of those who agreed to participate, ultimately only 161 actually

participated, resulting in a low response rate of only 8%.

A potential reason for the overall low response rate may be the result

of budgetary constraints, which did not allow for an incentive to participate

(such as reduced membership fees, etc.) to be offered. Also, we were asking

respondents to sign up to participate in a series of future studies, in addition

to the present study involved, which may have been more of a commitment

than participants were willing to make at this time, especially without extra

incentive.

It is possible that given our small sample size we may not have been

able to detect differences or support our hypotheses. Additionally, our

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sample was restricted in range in terms of age, race, practice setting, and

number of years licensed, which also may have detracted from our ability to

detect differences and support our hypotheses. However, given that our

sample is very similar to the membership of Division 42, it is much more

likely that our findings are accurate and representative of this population.

Issues Related to Online Response Rates. A procedural issue that

directly impacted online responders was related to the placement of the “IP-

Net” research link on the Division 42 Homepage (means by which the survey

was made available to participants as stated in their invitation letter). The

link was not prominently placed on the page, and initially could only be seen

via Microsoft’s Internet Explorer, but not Netscape/Mozilla. This problem was

immediately corrected once the researchers were contacted via e-mail by

several study participants, but may have led to the loss of participants willing

to answer the survey online or subsequently request a mail version of the

survey. Additionally, related to online participation, it may be that seeing the

visual mail materials on one’s desk is more motivating than trying to

remember to log on to complete a survey.

Issues Related to Mail Response Rates. A procedural issue that may

have affected mail participants is the fact that some of the response

envelopes were received by the researchers as postage due. This only

happened from certain areas of the country, despite the envelopes all

containing the same number of pages and therefore being the same weight.

Some participants actually put an additional stamp on the envelope, whereas

others may have been discouraged by this and simply not returned the

envelope, despite having completed the survey.

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Ultimately the two response groups were very similar and yielded few

significant between group differences in terms of personal and practice

characteristics, with both composed of participants representative of Division

42. However, it should also be noted that 62% of those who responded

reported that had the survey only been available via the Web, they still would

have participated, and 42% actually stated that the option to participate on

the Web increased their desire to respond. Also, the majority (73%) of those

who responded online indicated that our Web survey was easier or the same

level of difficulty as compared to previous Web surveys. Only 4% indicated

that they found our Web survey to be more difficult compared to others.

Therefore, it appears that by incorporating what was learned from this initial

Web effort, utilizing the Internet for future IP-Net studies would be a viable

and efficient option.

Issues for Investigation in Subsequent Surveys. We received feedback

from a few non-respondents that the survey simply appeared too long for

them to even consider completing. A few participants also gave feedback at

the end of the survey stating that the instrument had taken them longer than

anticipated to complete. As the second stage of this larger IP-Net project is

implemented, the length of the questionnaire will be considerably shortened.

Feedback from both participants and non-participants is important at this

stage in the development of IP-Net to ensure that we are able to retain a

foundation sample, as well as increase the membership with newly recruited

volunteers. The ability to retain and recruit a representative pool of

volunteer participants will ultimately determine the effectiveness of IP-Net as

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a research tool to study patterns and trends among independent

practitioners.

As with most survey method studies, issues arose related to omissions

and errors with the questionnaire instrument. However, a strong advantage

to longitudinal research such as IP-Net is that these issues can be corrected

through later studies if needed. Issues related to the present study that

require additional clarification include a question about full versus part-time

employment status, which impacted other data interpretations such as

income differences among subgroups. Another point of clarification related

to income is whether reported income was based upon total annual income or

total household income versus income solely from what was earned in clinical

practice, which again impacts the understanding of other personal and

practice characteristics. Due to the omission of these clarification questions,

we were unable to make conclusive statements regarding the income

differences of various subgroups (such as by gender, population size of

community, etc.). We also must view our finding of significant between

group differences for online and mail responders related to income level

cautiously, since it is possible that this difference could be accounted for by

factors such as part time employment and income from sources outside of

clinical practice.

Related to the practice characteristic of the average number of

sessions a patient was seen, future studies should clarify if those included in

the one session only category were seen exclusively for assessment

purposes, versus those who did not follow through with therapy. Another

point of clarification would be to inquire if those patients who were seen for

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over 21 sessions were private pay versus third party payment. Finally,

further clarification regarding the reasoning behind the average number of

sessions reported (such as restrictions by managed care, theoretical

orientation, etc.) should be investigated.

Related to technology use, this study also attempted to examine

reasons why participants did not endorse certain technology applications for

various practice tasks. However, the method in which the question was

phrased (Appendix B, last column of #34) did not produce meaningful data.

Specifically, participants tended to respond with “yes” to the open-ended

question rather than specifying their reasons for not using the various

technology applications. Therefore, we were unable to answer if people were

either not familiar with technology, believed it to be unethical, dehumanizing,

not cost-effective, the opportunity never presented, or additional factors. If

additional IP-Net studies continue to examine adoption of technology

applications in practice, then this will be an important issue to address.

Findings Related to Comparability of Response Groups

Group Differences. The two response method groups, online and mail,

were very similar in terms of number of participants, gender, race, age,

geographic region, degree, years licensed, and employment setting.

Although the online group contained more individuals who reported their

primary work setting to be academic (6%) compared to the mail group (2%),

the mail group contained more individuals who reported their primary work

setting to be independent practice (93%) compared to the online group

(85%). It should be noted that the category of independent practice was

composed of individuals reporting a primary work setting of: sole practicing

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alone, sole practicing in a group, employee of a group, partner in a limited

liability partnership, and part of a limited liability corporation. Future

research should address if working in an academic setting contributed to the

choice to respond online versus an independent practice setting contributing

to responding via mail. However statistical tests ultimately determined that

group (online versus mail) category was unrelated to practice setting. It is

possible that a sample with a less restricted range in terms of practice setting

might reveal different results.

The online and mail groups were also very similar in terms of years at

current setting, theoretical orientation, size of communities where they

worked, and the socioeconomic status of the communities where they

worked. The only significant between group difference in terms of personal

and practice characteristics was that of income, with the mail group reporting

significantly higher income compared to the online group. Future research

needs to address this difference. However, as noted earlier in this chapter,

these results must be viewed cautiously due to the lack of clarification

related to reported compensation in terms of full versus part-time

employment and household versus clinical income.

Statistical analyses determined that with the exception of income, the

personal and practice characteristics listed above were independent of group.

Therefore these characteristics cannot be used as predictor variables for

response method group categorization, and our groups can be viewed as

equivalent. This is an important consideration for future IP-Net studies that

wish to continue to recruit and survey participants via the Internet as well as

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through the mail. This is also important in terms of our initial recruitment

sample being considered representative of the overall Division 42.

Generalizability of Sample. The absence of group differences could

possibly be related to a lower than expected response rate or to a restricted

range of variables in terms of age, race, degree, number of years licensed,

and practice setting. While the present study examined patterns among

those in independent practice, perhaps future studies should seek to include

a wider diversity of participants, which would likely increase the range of

variables.

However, given that our study sample was very similar to those in the

random sample, as well as the entire membership of Division 42, in terms of

gender (approximately 60% males and 40% females across all three groups),

age (approximately mid-fifties across all three groups), race (over 90%

Caucasian in all three groups), degree (over 80% hold a Ph.D. in all three

groups), years licensed (around 20 years for all three groups), practice

setting (on average 83% independent practice across the three groups) and

geographic distribution, it can be stated that our study sample is

representative of not only the random sample of Division 42 members

provided by the APA Research Office, but also the entire Division 42

membership. As stated previously, one goal of our study was to recruit a

volunteer sample of independent practitioners from Division 42 who would

provide data that would allow for generalizations of findings based upon the

representativeness of the sample. This was an important first step in

establishing the foundation of the IP-Net for future research studies, which

will attempt to increase the number of participants.

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Findings Related to Attitudes Toward Technology and Technology Use by

Independent Practitioners

Findings Related to Attitudes Toward Technology as a Function of

Response Group. A specific goal of this study was to examine results from

the Attitudes Toward Computers Questionnaire (Jay, 1989) with its seven

dimensions of (1) comfort, (2) efficacy, (3) gender equality, (4) control, (5)

dehumanization, (6) interest, (7) utility, and a total score, as it related to

group differences and technology use. As predicted, the online group

reported significantly more positive attitudes in all areas, with the exception

of gender equality, where there was no significant difference between the

online and mail groups. This indicated that neither the online nor mail group

endorsed sexist attitudes related to computers being more important for

males to understand and use. It is interesting to note that the ATCQ used

strong “anti-female” language (i.e., “Working with computers is more for men

than for women.”; “More men than women have the ability to become

computer scientists.”).

In addition to the between group differences related to attitude, those

with more positive attitudes toward technology reported significantly higher

levels of current technology use for scheduling, maintaining patient files,

performing outcome research, testing, using the Internet to obtain

information, using the Internet for therapy, using the Internet for

marketing/advertising, and using the Internet for job recruitment. Using the

Internet for obtaining continuing education credits and billing approached

significance.

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These findings are consistent with social psychology research that

states attitudes are likely to guide behavior (Regan & Fazzio, 1977). Amount

of direct computer experience has been found to be the most consistent

correlate of computer attitudes, with increased experience leading to more

positive attitudes (Jay, 1989). The research literature has also suggested that

user attitudes have important implications with respect to the acceptance

and use of technological innovations (Grudin & Markus, 1997). This is an

important consideration given that a literature review conducted in June,

2002 determined that this is the first study to specifically measure

psychologist’s attitudes toward technology, and then make comparisons to

reported technology use.

Findings Related to Technology Use as a Function of Response Group.

Another specific goal of this study was to determine factors related to levels

of adoption of technology in practice, as well as rates of adoption. Our

results detailing current and anticipated future use of the technology

applications were consistent with those reported in previous studies, with the

addition of Internet categories. As predicted, participants in the online group

reported higher rates of use compared to those in the mail group. The only

category with zero current or future endorsement across both groups was the

use of technology applications for intake interview procedures. Reasons for

the lack of current or future use in this specific category should be

investigated in subsequent studies addressing technology use in practice. It

may be that the initial intake appointment is considered too important in

terms of diagnosing and establishing rapport, and that introducing

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technology applications would sacrifice the ability to effectively establish a

therapeutic relationship and treatment plan.

Data were also collected on the average amount of time per week

participants spent using the telephone, e-mail, Internet, and video

applications for provision of clinical services, and if they were reimbursed for

these services. Previous research identified the telephone as “universally

accepted” in terms of its use in practice, and this was the category that

reported the highest rates of average weekly use in our study. The

remaining categories of e-mail, Internet, and video, reported very low rates in

comparison. Overall, the data collected yielded only one significant group

difference, with the online group reporting a greater amount of time spent

per week making telephone referrals. Future research should look to clarify if

this is significant in terms of how the two groups differ in their approaches to

practice issues. Overall, there were few differences between the two groups,

which may suggest that method of data collection, online or via the mail,

yields similar results. Future studies can continue to address this question.

Additional statistical analyses determined that various personal and

practice variables such as age, gender, degree, theoretical orientation,

geographic location, population size of city, number of years licensed, or

practice setting were not related to amount of technology use. Further

discussion of the various categories of technology and their reported use will

be presented in subsections below.

Findings Related to Use of Technology in Practice Administration. The

mail group reported handling billings tasks themselves more often when

compared to the online group. However, the online group reported that they

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handled the scheduling, accounts payable, phone, and word processing tasks

themselves more often when compared to the mail group. The fact that the

online group reported performing the majority of office tasks themselves

more often compared to the mail group, who reported more often that an

employee handled these tasks, could be due to several factors and needs to

be addressed by future research. For example, the online group may

perform more of the tasks themselves due to being more comfortable with

the technology applications involved or enjoying the work more (i.e. using the

computer to type documents or using the computer to run a scheduling

program). Therefore, the online group may not have the need to hire an

employee to serve in the type of clerical role. On the other hand, since the

mail group reported significantly higher income compared to the online

group, it may not be financially possible for the online group to hire an

employee to do these tasks or to contract them out. Again, future research

should clarify the issue related to income differences between groups, as well

as the differences in how these administrative tasks are performed.

In terms of current technology use in practice, billing and word

processing were the two tasks most frequently reported by participants, with

overall rates of 80% and 79%, respectively. This is consistent with other

studies reported in the literature (i.e., McMinn et al., 1999). Future research

needs to address if technology-based billing was done on a voluntary basis,

or as a result of reimbursement practices by third party payers.

Thirty-one percent of participants reported that they utilize technology

applications to maintain patient files. Future research needs to clarify to

what extent a computer is actually used to maintain patient files (i.e.,

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paperless files versus typed progress notes). Twenty-five percent of the

participants reported using technology applications for scheduling. Future

research should clarify if this rate of use is accounted for by calendar

programs on a desktop computer versus hand-held personal digital assistants

(PDAs) or some other type of software program. Finally, 10% of participants

reported that they utilized the Internet for marketing or advertising, and 1%

for recruiting job applicants. It will be interesting to note if these rates

increase as the Internet becomes a more popular method for reaching

potential consumers and employees. These two categories have not been

assessed by previous studies found in the literature.

Findings Related to Use of Technology for Assessment. Forty-six

percent of participants reported the use of technology applications for

assessment purposes. This rate is higher than that reported by McMinn et al.

(1999), but still lower than expected given the time efficiency offered by

computerized test programs. Future research needs to address whether this

is due to the fact that many practices are operating without performing

testing services, hand scoring, contracting out for scoring, or other factors,

such as the rates of reimbursement for psychological testing.

Findings Related to Use of Technology for Treatment. The use of the

Internet for therapy was reported by 7% of participants. However, the survey

instrument did not clarify exactly what was meant by Internet therapy (i.e.,

chat room discussions, accepting fees for services, live exchanges, or

questions submitted over an Website that were answered by a psychologist,

etc.). Future research needs to clarify these points to better understand how

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the application is being utilized by practitioners, as was done in the study by

Maheu and Gordon (2000).

Recording patient homework was reported at a frequency of 5%.

Future research needs to determine if what is being reported as technology

use to record patient homework is the simple word processing of patient

assignments, or if it is the interactive use of technology either through the

Internet or computer programs and e-mail to actively engage the patient and

therapist in monitoring behaviors.

Measuring patient satisfaction and performing outcome research had

overall low rates (25% and 11%, respectively). Of those performing outcome

research, 8% reported that they used technology applications as part of this

task. Perhaps in the future as practice research networks in psychology

grow, these rates will increase. This may also be an area where software

developers can look to build packages that combine tools for maintaining

files, schedules, patient accounts, treatment plans, homework assignments,

as well as patient satisfaction scales and outcome measures.

Once we can clarify the exact manner in which practitioners are

incorporating the various technology applications endorsed in this study, we

can then determine a more useful classification system of technology use in

practice than the system presented by McMinn (1999), which is discussed in

more detail later in this chapter. This is a benefit of a research method such

as IP-Net, which has easy access to a database of participants who can be

contacted in the future for follow-up studies.

In terms of reported weekly use of various technology applications, the

only significant between group difference was in terms of telephone referrals

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with the online group reporting a higher amount compared to the mail group.

Future research needs to address the reason for this difference. Perhaps

online participants follow a different screening method, and therefore have

more potential patients to refer out.

Future research also needs to clarify whether the amount of weekly

telephone therapy reported was done in response to a crisis situation, or if it

was scheduled in place of an office therapy appointment. And if it was

scheduled, was it due to geographic restrictions or patient disability, etc.

versus preferred by the therapist and patient?

Findings Related to Use of Technology for Communication and

Information. The third and fourth most frequently reported technology

applications were the use of the Internet to obtain information (64%) and e-

mail with other professionals (57%), which corresponds with the number of

“online” individuals in the US today. Even with the dramatic increase in the

number of individuals “online” in the US, it was still notable that 29% of

participants reported using e-mail with patients, especially given the

significantly lower rates reported in previous studies. By mid-2001, the

Telecommunications Report International (CyberAtlas Staff) reported that

there were 70.7 million online subscribers in the United States, up 16 million

from 2000. Future research needs to clarify exactly what is meant by e-

mailing patients (i.e., for the purpose of appointment times or containing

clinical content). For example, a local community mental health center puts

the e-mail addresses of its psychologists on their business cards, which are

handed out to patients at the end of each appointment because they list

future appointment dates on the back. This has been taken, whether

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mistakenly or otherwise, as an invitation by many patients to use the e-mail

address as a means of contact. Also, the present study did not clarify if e-

mail was used to discuss clinical or treatment content, or just to verify

appointment times and other administrative issues.

Discussion of Hypotheses Regarding Technology Use and Related

Attitudes. In terms of looking at number of years licensed, our original

hypothesis stated that the number of years licensed would be related to

attitudes toward technology, with newer practitioners having more positive

attitudes and reporting greater amounts of technology use. Analyses were

also performed to determine if age would have better predicted amount of

technology use and attitudes toward technology. Both hypotheses were

unsupported; the variables were found to be unrelated to attitudes toward

technology and amount of technology use. It may be that research studies

need to wait for a new cohort of individuals who were part of the “digital age”

to detect differences. Additionally, our sample was restricted in terms of age

range, with two-thirds between the ages of 47 and 60 years; and none below

age 40 in the online group.

In terms of looking at practice setting, it was hypothesized that those

not in independent practice would be greater users of technology

applications and have more positive attitudes. This was also unsupported,

but may be related to the fact that we had a very restricted range in terms of

practice setting, with 88% reporting independent practice. Future research

needs to address this question by looking at a sample with a greater diversity

of practice settings. Future research also needs to clarify the practical and

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economic constraints involved with a private practice, and how these would

affect the decision or desire to incorporate technology applications.

Our second hypothesis, which predicted that those with more positive

attitudes toward technology, as measured by the ATCQ (Jay, 1989), would

report using technology applications to a greater extent, was supported for

several areas of technology use. This corresponds with data from social

psychology studies related to attitudes being directly impacted by amount

and level of experience, as discussed earlier. Amount of direct computer

experience has been found to be the most consistent correlate of computer

attitudes, with increased experience leading to more positive attitudes (Jay,

1989). Future research should inquire about participant’s experience with

technology applications in order to determine the fit with Mackie and Wylie’s

model (1988), which states that attitudes are determined by: (1) the user’s

awareness of the technology and its purpose; (2) the extent to which the

features of the technology are consistent with the user’s needs; (3) the user’s

experience with the technology; and (4) the availability of support when

using the technology.

Trends in Technology Use and the Need for Reclassification. The

results obtained in our present study demonstrate higher rates of technology

usage than those reported by McMinn et al. (1999) who reported 57% use for

billing (versus 80% in this study), 23% use for testing (versus 46% in this

study), and 22% use for maintaining patient files (versus 31% in this study).

Results of this survey also showed a higher rate of reported use of the

Internet for therapy (7%), compared to the 2% use reported by VandenBos

and Williams (2000).

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As stated earlier, the wave classification system proposed by McMinn

(1999) does not appear to adequately and efficiently categorize available

technologies. At best, it is suggested that this system be reevaluated in

terms of what is listed in the first-wave classification to determine if this so

called first-wave should be eliminated entirely, since it is doubtful that any

modern office can exist without those particular technologies (Jerome,

DeLeon, James, Folen, Earles, & Gedney, 2000). This would reduce the three-

wave system to two waves by moving what is currently listed as second-wave

technologies to the first-wave, and third-wave technologies to second-wave.

However, this suggestion only attempts to clarify a system that we do not

believe to be parsimonious and comprehensive. Instead, we would propose a

system of classification based upon the presentation of our results in chapter

3, with the addition of a category for education and training purposes. Such

a classification system would appear as follows:

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I. Use of Technology in Practice AdministrationII. Use of Technology in for AssessmentIII. Use of Technology for TreatmentIV. Use of Technology for Communication and InformationV. Use of Technology for Education and Training

It is our belief that this five-tier system that labels the specific use of

the application and not merely the type of technology, would offer greater

parsimony and better account for the different modes of technology

utilization in practice. For example, with this system the use of e-mail could

potentially be listed under any and all of the five tiers, but its function would

be clearly defined, thus eliminating the confusion inherent in McMinn’s (1999)

proposed system as discussed earlier in this paper. Therefore, if e-mail was

used strictly to remind patients of an upcoming appointment, this could be

classified under the first tier, as use of technology in practice administration

similar to how a reminder telephone call might be labeled. However, if e-mail

were utilized to discuss clinical content with a patient, this would be classified

as use of technology in treatment. Therefore, we have a clear understanding

of the function of the technology application in treatment, rather than a mere

listing of the wave of technology based upon expected rates of use and

assumptions about its impact on therapy.

Conclusions and Future Directions

This study was undertaken for two purposes. The first was to examine

factors associated with technology adoption in clinical practice, since others

have argued that there are many technologies now available to enhance and

simplify the work of practicing psychologists (i.e., Marks, Shaw, & Parkin,

1998; McMinn et al., 1999), yet there has been little movement in the field to

incorporate these advances. This study measured current technology usage

93

and attitude toward usage among psychologists in independent practice.

Two of the hypotheses regarding factors associated with attitudes and

technology use were unsupported. Thus, the number of years in practice and

practice setting did not predict technology use. However, a third hypothesis

was supported in that attitudes toward technology did impact technology

use. As reported earlier, this is consistent with both social psychology

research on attitudes and behaviors in general, as well as with other studies

reported in the literature specific to attitudes and technology. Based upon a

literature review conducted in June, 2002, this is the first study to specifically

measure psychologist’s attitudes toward technology and compare with

reported technology use. It was also interesting to note that our sample

reported higher levels of technology use for e-mail and Internet therapy

compared to previous research found in the available literature. It is not

clear if this is simply related to the passage of two years since the last

reported survey found in the available literature and the continued

technology boom, or if it is true movement within the field to consciously

increase technology usage.

However, it may be that the increased usage found on the present

study may be more related to practical factors as discussed by Murphy

(2000). It may be that the areas with the greatest increase in use are those

that provide the greatest savings in cost and time, or are activities that

generate revenue. Furthermore, there would need to be incentives for

application developers. The argument presented by Murphy (2000) was that

ultimately, in order for technology applications to become more widely

adopted in psychotherapy practice, the technology must offer a clear benefit

94

over simpler and less expensive alternatives, as well as provide significant

economic benefit to users and developers. Additionally, it should be noted

that very few participants in our study reported that they anticipated an

increase in future use of technology applications in practice (based upon

responses of those not currently using a particular application, and

anticipating use of that application in the near future). It may be that areas

where those in clinical practice intend to use technology applications are

saturated, and therefore manufacturers of technology applications will have

to carefully aim at marketing new products that specifically match the needs

of those in clinical practice.

The second purpose of this study was to perform an initial recruitment,

as part of a larger project, and establish a research database of participants

for the IP-Net (Independent Practice Network). Therefore, it was hoped that

this project would not only look at technology issues, but also provide

demographic information on the composition of participants and establish the

degree of representativeness or generalizability for the sample to practicing

psychologists, as described by our descriptive statistics. This study was the

initial effort for IP-Net, and therefore also served to workout methodological

issues. The present study did in fact meet this second purpose.

In closing, I think that an important future direction for this line of

research will be to look at the question raised by Stamm and Perednia

(2000), as well as some other researchers, as to what we really know about

the meaning of technology in mental health. Again, we are reminded that

the best piece of computer equipment is only as good as its trained and

willing human user. Researchers and practitioners still do not fully

95

understand what aspects of treatment make therapy “work,” therefore how

can we successfully begin to incorporate aspects of technology. Thus far,

research in the area of telehealth typically addresses the technology aspects

of the care provided and not the psychosocial implications of the technology

driven care. Most likely this is in part due to recent rapid technological

growth paired with financial pressures on the healthcare industry to be more

cost-effective. Also, if research continues to support the argument that the

therapeutic relationship itself is the most important factor in terms of

treatment success (Stiles, Agnew-Davies, Hardy, Barkham, & Shapiro, 1998),

then technology may not have a place in actual treatment, but it can still find

a place in the management of an office, the Internet for information and

continuing education, as well as in graduate training.

Another important future direction will be the adoption of a more

precise system of classification supported by on-going research tracking

patterns and trends in practice, such as what can be done through IP-Net.

Future IP-Net studies can also incorporate what was learned from this initial

effort in terms of procedural issues, and clarify points still unanswered by the

present study, which is a real strength and benefit of a system such as IP-Net.

Reed, McLaughlin, and Milholand (2000) warn that if we continue to let

the technology market drive the development of applications, rather than

being developed in response to the needs of its users, we could end up with

costly technology systems that are useless to practitioners and patients.

Therefore, it is up to practitioners and patients to request what is needed,

and to evaluate, and advocate for new technologies in keeping with already

existing standards and ethics. If we as psychologists leave this task up to

96

technology companies, health care systems, or government agencies, we run

the risk of products and guidelines that we neither want nor need. Again, this

leads us to consider the more practical issues related to the widespread

adoption of technology applications in practice, such as that the technology

must offer a clear benefit over simpler and less expensive alternatives, as

well as help to generate income (Murphy, 2000).

These issues can be addressed through the continued development of

practice research networks and the collection of real time data, such as the

one that the present study helped to lay the foundation for, the Independent

Practice Network (IP-Net).

97

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Appendix A: Invitation Letter/Informed Consent

Dear Division 42 Member:

I am writing to ask you to assist Division 42 conduct research on independent practice by participating in the Division 42 Independent Practice Network (IP-Net). The simple fact is there is little systematic data available to psychologists about important dimensions of independent practice. We regularly provide data about ourselves and our practices to managed care organizations for credentialing and re-credentialing. We provide information even more frequently when we submit billing and utilization review material. The fact is that these organizations have much more information about individual practices than the psychologists themselves and a better grasp of important aspects of practice than is available to us. In addition, research into effectiveness of psychological services seldom focuses on experienced psychologists working in independent practice settings. We have developed IP-Net to conduct research on psychologists in independent practice.

Participants in IP-Net will provide information on: Practice organization and management Service delivery and payment systems Local practice and market conditions Career paths Services Attitudes about practice and public policy issues

With additional development the system will allow process and outcome research with experienced professionals in private practice settings.

As an initial participant you will be in the reference sample and may respond by Internet or by postage-paid mail. Later participants will respond only to IP-Net’s Website. All participants will be asked to respond to no more than eight surveys each year. Each survey will be designed to be completed in 15-minutes. Responses are confidential and all information identifying individual participants is kept in a separate database and the only interaction between databases is to identify non-respondents to a survey. Participants will receive feedback on the results of each survey.

The questionnaires can be completed through our Website or by mail method. Internet response is preferred but the mail option is offered to insure that all can participate. After the initial registration, Internet based participants will receive emails instructing them how to access the Website and respond to the survey. Reminders will be sent to those who do not respond. Mail based participants receive a packet with the survey

107

and a postage-paid envelope. There will be follow-up of those who do not respond in a two-week period. More detailed information is included below.

If you wish to participate, you can either

Complete the enclosed postage-paid cardor

Access the Division 42 Website (http://www.division42.org/) and click on the IP-Net button. This will take you to the IP-NET Website and follow the instructions.

Mailing the postcard or responding on the Website indicates your consent to participate in the surveys. You can withdraw your consent at any time by informing IP-Net at any of the contacts below.

The APA Practice Directorate is developing a similar program with a different focus. We have coordinated our efforts with their project and will continue to consult with Practice Directorate staff. We believe that that participation in one network does not preclude participating in the other.

In the next months the IP-Net will be recruiting volunteer participants for the research network. The data for volunteers will be examined separately from that of the random sample and you will serve a key role in insuring the representativeness of the volunteer sample.

I am confident that your participation in the Practice Research Network will provide important information about trends in private practice and will lay the foundation for a system that can investigate the effectiveness of services provided in independent practice. I hope you will lend us your voice.

Cordially,

Michael J. Murphy, Ph.D.Division Secretary and Chair,Emerging Patterns of Practice Committee

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Appendix B: Questionnaire

109

110

111

112

113

114

115

116

117

118

119

120

121

122

Appendix C: Characteristics of the Random Sample and Division 42 Membership Provided by the APA Research Office on Variables Available from APA’s Database

VARIABLERandom Sample

Number PercentDivision 42

MembershipNumber Percent

Gender: Male Female

1,201799

60%40%

3,8462,320

62.0%38.0%

Race: Caucasian

Hispanic African American

Asian American Indian

1,8913317169

95.0%1.5%1.0%0.5%0.5%

5,67187694115

92.0%1.4%1.1%0.7%0.2%

Age: Mean

Median SD

Range

not available

52.76.7

30-70+

56.6not available

10.6not available

*Region: Middle Atlantic

South Atlantic Pacific

East North Central New England

West South Central

West North Central

Mountain East South

Central

456341338285175122111

9478

22.8%17.1%16.9%14.3%

8.8%6.1%5.6%4.7%3.9%

1,5511,086

935865504367286319203

25.2%17.6%15.2%14.0%

8.2%6.0%4.6%5.2%3.3%

Degree: Ph.D.

Psy.D. Ed.D

1,743140

98

87%7%5%

5,133387366

83.2%6.3%5.9%

Years Licensed: Mean

Median SD

Range

not available

19.96.6

3-25+

23.5not available

10.4not available

Employment Setting: Independent Practice

Academic Hospital

Clinic Other Human Service

School Government

Business

1,0786656262423215

83.0%5.0%4.0%2.0%2.0%2.0%2.0%

>1.0%

1,942160109

706751439

75.5%6.2%4.2%2.7%2.6%2.0%1.7%0.3%

* Middle Atlantic (New Jersey, New York, Pennsylvania); South Atlantic (Delaware, District of Columbia, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, West Virginia); Pacific (Alaska, California, Hawaii, Oregon, Washington); East North Central (Illinois, Indiana,

123

Michigan, Ohio, Wisconsin); New England (Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont); West South Central (Arkansas, Louisiana, Oklahoma, Texas); West North Central (Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, South Dakota); Mountain (Arizona, Colorado, Idaho, Montana, Nevada, New Mexico, Utah, Wyoming); East South Central (Alabama, Kentucky, Mississippi, Tennessee)

124