Purpose
The Adelaide Driving Self-Efficacy Scale (ADSES) is a driving self-efficacy assessment. This scale has been developed to assess driving confidence on 12 typical driving tasks.
In-Depth Review
Purpose of the measure
The Adelaide Driving Self-Efficacy Scale (ADSES) is a driving self-efficacy assessment. This scale has been developed to assess driving confidence on 12 typical driving tasks such as parallel parking, driving at night and driving in unfamiliar areas.
Available versions
The ADSES was developed by Dr. Stacey George, Michael Clark and Maria Crotty at Flinders University Department of Rehabilitation Aged and Extended Care in South Australia and was published in 2007.
Features of the measure
Items:
The ADSES is composed of 12 items that measure the levels of confidence of the client towards typical driving behaviours:
- Driving in your local area
- Driving in heavy traffic
- Driving in unfamiliar areas
- Driving at night
- Driving with people in the car
- Responding to road signs/traffic signals
- Driving around a roundabout
- Attempting to merge with traffic
- Turning right across oncoming traffic
- PlanningPlanning ability involves anticipating future events, formulating a goal or endpoint, and devising a sequence of steps or actions that will achieve the goal or endpoint” (Anderson, 2008, p. 17)
travel to a new destination
- Driving in high speed areas
- Parallel parking
Scoring:
The ADSES is self-scored using a Likert scaleLikert scaling is one type of response to items in a questionnaire or tool. For example, Likert scaling would have you rate an item such as “I am satisfied with the care I received” on a scale using a 1-to-5 response scale where:
• 1 = strongly disagree
• 2 = disagree
• 3 = undecided
• 4 = agree
• 5 = strongly agree
You will find various options and scaling methods for the number of response choices (1-to-7, 1-to-9, 0-to-4). Odd-numbered scales usually have a middle value that is labelled Neutral or Undecided. Some tools used forced-choice Likert scaling with an even number of responses and no middle neutral or undecided choice. from 0 (no confidence) to 10 (completely confident). The score for each item can then be summed for a total possible score of 120, indicating the highest level of confidence.
Time:
Not reported.
Subscales:
None.
Equipment:
A pen and the test are needed to complete the ADSES.
Training:
No training requirements have been reported since the ADSES is intended to be self-administered.
Alternative forms of the Adelaide driving self-efficacy scale
ADSES–P: A by proxy version has been developed. The only change made from the original ADSES is the phrasing of the initial question: “How confident do you feel your family member can complete the following driving tasks safely?”, instead of: “How confident do you feel doing the following activitiesAs defined by the International Classification of Functioning, Disability and Health, activity is the performance of a task or action by an individual. Activity limitations are difficulties in performance of activities. These are also referred to as function.
?” (Stapleton, Connolly, & O’Neill, 2012).
A study by Stapleton et al. (2012) showed a significant correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
between the ADSES and ADSES-P among patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. at initial assessment (average 2 months post-stroke) and at six-month follow-up among the patients who successfully completed on-road driving assessments. These preliminary findings support the use of proxy ratings to identify the patients who are not ready for a formal driving assessment, although further research is needed to validate the use of a proxy version of the ADSES.
Client suitability
Can be used with:
Patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain..
Should not be used with:
Not reported.
In what languages is the measure available?
English
Summary
| What does the tool measure? |
Self-perceived driving confidence. |
| What types of clients can the tool be used for? |
Patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. |
Is this a screeningTesting for disease in people without symptoms.
or assessment tool? |
Assessment |
| Time to administer |
Not reported. |
| Versions |
ADSES, ADSES–P. |
| Other Languages |
None. |
| Measurement Properties |
ReliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
|
Internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency.:
One study reported excellent internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency..
Test-retest:
No studies have examined the test-retest reliabilityA way of estimating the reliability of a scale in which individuals are administered the same scale on two different occasions and then the two scores are assessed for consistency. This method of evaluating reliability is appropriate only if the phenomenon that the scale measures is known to be stable over the interval between assessments. If the phenomenon being measured fluctuates substantially over time, then the test-retest paradigm may significantly underestimate reliability. In using test-retest reliability, the investigator needs to take into account the possibility of practice effects, which can artificially inflate the estimate of reliability (National Multiple Sclerosis Society).
of the ADSES.
Intra-rater:
No studies have examined the intra-rater reliabilityThis is a type of reliability assessment in which the same assessment is completed by the same rater on two or more occasions. These different ratings are then compared, generally by means of correlation. Since the same individual is completing both assessments, the rater’s subsequent ratings are contaminated by knowledge of earlier ratings.
of the ADSES.
Inter-rater:
No studies have examined the inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
of the ADSES.
|
ValidityThe degree to which an assessment measures what it is supposed to measure.
|
Content:
One paper reported on content validityRefers to the extent to which a measure represents all aspects of a given social concept. Example: A depression scale may lack content validity if it only assesses the affective dimension of depression but fails to take into account the behavioral dimension.
of the ADSES and noted that items were generated from literature review, clinical experience and expert review.
Criterion:
Predictive:
Two studies examined predictive validityA form of criterion validity that examines a measure’s ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
of the ADSES and reported that the ADSES was predictive of on-road driving assessment outcome, as measured by a standardized on-road assessment, the Jewish Rehabilitation Hospital Road Evaluation Form (JRHREF) and the Test Ride for Investigating Practical Fitness to Drive (TRIP) – Belgian version.
Construct:
Convergent/Discriminant:
– One study reported a significant relationship between the ADSES and the Driving Habits Questionnaire (DHQ) driving space, number of kilometers driven per week and self-limiting driving.
– One study reported an excellent correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
between the ADSES and the ADSES-P at initial assessment and at 6-month follow-up.
Known groups:
Two studies have examined known-group validityThe degree to which an assessment measures what it is supposed to measure.
of the ADSES: one study reported differentiation between healthy individuals and those with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.; the second study reported no significant difference in ADSES scores between drivers following strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. and those who have not had a strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain..
|
| Floor/Ceiling Effects |
One paper reported a ceiling effectA ceiling effect occurs when test items aren’t challenging enough for a group of individuals. Thus, the test score will not increase for a subsample of people who may have clinically improved because they have already reached the highest score that can be achieved on that test. In other words, because the test has a limited number of difficult items, the most highly functioning individuals will score at the highest possible score. This becomes a measurement problem when you are trying to identify changes – the person may continue to improve but the test does not capture that improvement. Example: A memory test that assesses how many words a participant can recall has a total of five words that each participant is asked to remember. Because most individuals can remember all five words, this measure has a ceiling effect. See also “floor effect.” for all items of the ADSES and the ADSES-P. |
SensitivitySensitivity refers to the probability that a diagnostic technique will detect a particular disease or condition when it does indeed exist in a patient (National Multiple Sclerosis Society). See also “Specificity.”
/Specificity |
Not reported. |
| Does the tool detect change in patients? |
Not reported. |
| Acceptability |
The ADSES is intended to be self-administered and a proxy version has been developed. |
| Feasibility |
The ADSES is a self-report scale and does not require any formal training. |
| How to obtain the tool? |
ADSES is available as a Appendix in the following article:
George S, Clark M, Crotty M (2007). Development of the Adelaide driving self-efficacy scale. Clin Rehabil. Jan;21(1):56-61.
|
Psychometric Properties
Overview
We conducted a literature search to identify all relevant publications examining the psychometric properties of the Adelaide Driving Self-Efficacy Scale. Only two studies have been identified (Stapleton, Connolly & O’Neill, 2012; George, Clark & Crotty, 2007). Additional research on the psychometric properties of this scale is required as most information currently available originates from the authors of the scale.
Floor/Ceiling Effects
Stapleton, Connolly & O’Neill (2012) recruited 46 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. (average 2 months post-stroke) to examine use of the ADSES and the proxy version of the ADSES (ADSES-P) to assess driving post-stroke. The authors noted a ceiling effectA ceiling effect occurs when test items aren’t challenging enough for a group of individuals. Thus, the test score will not increase for a subsample of people who may have clinically improved because they have already reached the highest score that can be achieved on that test. In other words, because the test has a limited number of difficult items, the most highly functioning individuals will score at the highest possible score. This becomes a measurement problem when you are trying to identify changes – the person may continue to improve but the test does not capture that improvement. Example: A memory test that assesses how many words a participant can recall has a total of five words that each participant is asked to remember. Because most individuals can remember all five words, this measure has a ceiling effect. See also “floor effect.” for all individual items on the ADSES and ADSES-P. The authors explained this effect by the fact that most participants were at an early stage of strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. and may not have been aware of the impact of the strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. on their driving.
Reliability
Internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency.:
George, Clark and Crotty (2007) examined the internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. of the ADSES in a sample of 81 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. and 79 non-stroke individuals, using Cronbach’s alpha coefficient. Internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. of the scale was excellent (α = 0.98), and remained unchanged across all items.
Inter-rater:
No studies have examined the inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
of the ADSES.
Intra-rater:
No studies have examined the intra-rater reliabilityThis is a type of reliability assessment in which the same assessment is completed by the same rater on two or more occasions. These different ratings are then compared, generally by means of correlation. Since the same individual is completing both assessments, the rater’s subsequent ratings are contaminated by knowledge of earlier ratings.
of the ADSES.
Test-retest:
No studies have examined the test-retest reliabilityA way of estimating the reliability of a scale in which individuals are administered the same scale on two different occasions and then the two scores are assessed for consistency. This method of evaluating reliability is appropriate only if the phenomenon that the scale measures is known to be stable over the interval between assessments. If the phenomenon being measured fluctuates substantially over time, then the test-retest paradigm may significantly underestimate reliability. In using test-retest reliability, the investigator needs to take into account the possibility of practice effects, which can artificially inflate the estimate of reliability (National Multiple Sclerosis Society).
of the ADSES.
Validity
Content:
George, Clark and Crotty (2007) conducted a literature review regarding self-efficacy and older drivers, then combined this information with their own clinical experience to generate a list of driving behaviours that can be influenced by medical conditions such as a strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. Content validityRefers to the extent to which a measure represents all aspects of a given social concept. Example: A depression scale may lack content validity if it only assesses the affective dimension of depression but fails to take into account the behavioral dimension.
was tested by an expert group composed of (i) mobility instructors of the Guide Dogs Association of South Australia and Northern Territory Inc.; (ii) driver-trained occupational therapists; and (iii) the project steering committee, and resulted in a final list of 12 items.
Criterion:
Concurrent:
No studies have examined the concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
of the ADSES.
Predictive:
Stapleton et al. (2012) recruited 46 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. (average 2 months post-stroke) to compare ADSES and ADSES-P scores with on-road driving assessments, using Spearman’s rho. On-road driving assessments were conducted with 35 participants using the Jewish Rehabilitation Hospital Road Evaluation Form (JRHREF) and the Test Ride for Investigating Practical Fitness to Drive (TRIP) – Belgian version. Results showed adequate correlations between the ADSES and on-road driving assessments (JRHREF, r=0.497; TRIP, r=0.433) and adequate to excellent correlations between the ADSES-P and on-road driving assessments (JRHREF, r=0.614; TRIP, r=0.507).
George, Clark and Crotty (2007) examined criterion validityExamines the extent to which a measure provides results that are consistent with a gold standard . It is typically divided into concurrent validity and predictive validity .
of the ADSES by comparing ADSES scores with a standardized on-road assessment, in a sample of 45 participants with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. (n=34), traumatic brain injury/other condition and older drivers. An independent samples t-test was used to examine the relationship between ADSES scores and pass/fail results of an on-road driving assessment. Results showed a significant relationship between total ADSES scores and on-road driving performance for the whole cohort and the strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. subgroup (p˂0.01, p˂0.05 respectively), whereby people who failed the on-road driving assessment obtained a lower ADSES total score. These results demonstrated that driving self-efficacy as measured by the ADSES was predictive of on-road driving assessment outcome.
Construct:
Convergent/Discriminant:
McNamara, Walker, Ratcliffe & George (2015) examined the convergent validityA type of validity that is determined by hypothesizing and examining the overlap between two or more tests that presumably measure the same construct. In other words, convergent validity is used to evaluate the degree to which two or more measures that theoretically should be related to each other are, in fact, observed to be related to each other.
of the ADSES and the Driving Habits Questionnaire (DHQ) in a sample of 40 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. who returned to driving in the previous 3 years, using Pearson’s correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
coefficient. There was a significant relationship between ADSES and three aspects of the DHQ: (i) driving space (r=0.35); (ii) number of kilometers driven per week (r=0.43); and (iii) self-limiting driving (r=0.63).
Stapleton, Connolly & O’Neill (2012) examined convergent validityA type of validity that is determined by hypothesizing and examining the overlap between two or more tests that presumably measure the same construct. In other words, convergent validity is used to evaluate the degree to which two or more measures that theoretically should be related to each other are, in fact, observed to be related to each other.
of the ADSES and ADSES-P in a sample of 46 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. (average 2 months post-stroke), using Spearman’s rho. Results showed an excellent correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
at initial assessment (r=0.707) and at 6-month follow-up (r=0.927). While there was no significant difference in ADSES scores from initial assessment to 6-month follow-up, there was a significant difference in ADSES-P scores between the two time-points (p=0.028).
Known groups:
McNamara, Ratcliffe & George (2014) examined known group validityThe degree to which an assessment measures what it is supposed to measure.
of the ADSES in a sample of 40 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. who returned to driving and 114 older drivers who have not had a strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain., using Mann–Whitney U-test. There was no significant difference in ADSES scores between drivers following strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. and those who have not had a strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. (t(153) = 0.32, P = 0.58).
George, Clark and Crotty (2007) examined known group validityThe degree to which an assessment measures what it is supposed to measure.
of the ADSES by comparing ADSES scores of participants with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. (n=81) and a normative sample of individuals who had not had a strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. (n=79), using an independent samples t-test. There was a significant difference in ADSES scores between groups (p˂0.05).
Responsiveness
No studies have examined the responsivenessThe ability of an instrument to detect clinically important change over time.
of the ADSES.
References
- George, S., Clark, M., & Crotty, M. (2007). Development of the Adelaide driving self-efficacy scale. Clinical Rehabilitation, 21(1), 56-61.
- McNamara, A., Ratcliffe, J., & George, S. (2014). Evaluation of driving confidence in post‐stroke older drivers in South Australia.Australasian Journal on Ageing, 33(3), 205-207.
- McNamara, A., Walker, R., Ratcliffe, J., & George, S. (2015). Perceived confidence relates to driving habits post-stroke.Disability and Rehabilitation, 37(14), 1228-1233.
- Stapleton, T., Connolly, D., & O’Neill, D. (2012). Exploring the relationship between self‐awareness of driving efficacy and that of a proxy when determining fitness to drive after stroke. Australian Occupational Therapy Journal, 59(1), 63-70.
See the measure
How to obtain the Adelaide Driving Self-Efficacy Scale
The ADSES is available as a Appendix in the following article:
George S, Clark M, Crotty M (2007). Development of the Adelaide driving self-efficacy scale. Clin Rehabil. Jan;21(1):56-61.
