Introduction
The validity and reliability of a research measure significantly determine the study’s quality. The two factors demonstrate how fitting a technique, method, or experiment measures the subject under investigation. Reliability connotes the constancy or uniformity of a measure, while validity regards the measure’s accuracy (Cooper et al., 2020). Reliability and validity exhibit unique aspects that a researcher must ascertain to guarantee a study’s quality. Features such as appropriateness, consistency, and reproducibility promote a tactic’s validity, according to Fisher (2021). Appropriateness arises when a researcher chooses a high-quality technique that exactly measures the intended study facet. The standardized questionnaire provides an excellent example of a highly binding or valid research tool for collecting subjects’ personality traits data (Cooper et al., 2020). On the other hand, standardization and consistency are the two primary elements promoting reliability (Cooper et al., 2020). Consistency connotes a measure’s application of similar steps in the same manner, while standardization concerns independence from external circumstances. Investigators ascertaining such elements’ presence in research measures guarantee validity and reliability, thus, high-quality investigations with applicable results and conclusions.
Differentiation of High Validity and Reliability vs. Low Validity and Reliability Psychological Measures
High Validity and Reliability Psychological Measures
Behavior analysts utilize different tactics to measure and investigate behavioral elements. Count or frequency, rate, and celeration are the three measurement approaches based on the repeatability element (Cooper et al., 2020). The frequency or count dimension quantifies the number of incidences of a given conduct, while the rate measurement enumerates the occurrences of a given behavioral trait within a set time. Similarly, the celeration (measurement) measures the proportion of responding vicissitudes over a specific period (Bordens & Abbott, 2020). These techniques’ test-retest reliability and face and content validities make them high reliability and validity measures.
Low Validity and Reliability Psychological Measures
Psychologists can measure response latency and inter-response time based on the temporal locus. Other measurement techniques applied by behavioral analysts include derivative and definitional measures (Fisher, 2021). Derivative measures include percentage and trials-to-criterion tactics, while definition measurements return reports concerning a behavior’s topography and magnitude. The various tactics’ frequent reliability on face validity gives them low reliability and validity. Equally, definitional measurements’ subjectivity to subjects and circumstances frequently makes them less valid and undependable relative to others.
Test-Retest Reliability, Parallel-Forms Reliability, and Split-Half Reliability Examination
Measurements’ reliability in the behavioral field takes different forms, including test-retests, parallel-forms, and split-half reliabilities. Test-retest reliability measures a dimension’s consistency across time (Bordens & Abbott, 2020). The facet checks the possibility of acquiring identical results after repeating the measurement for a given time. The test-retest aspect requires a population to fill out questionnaires on personality traits to offer similar responses even when the survey occurs days, weeks, or months apart (Cooper et al., 2020). The parallel-forms reliability measures different tests’ ability to return identical results. The tactic checks whether test scores remain the same when using different instruments. Measurements returning the same averages and variances constitute parallel reliability, while those lacking such belong to the alternate forms’ group (Fisher, 2021). Lastly, split-half reliability arises when the same class of respondents is divided into two groups (halves) and then undertakes identical tests, after which their means and variances are compared. Therefore, test-retest, parallel-forms, and split-half reliabilities are essential aspects determining a measure’s dependability or consistency, thus significantly helpful in behavioral investigations.
Accurate Scores’ Meaning
Psychology is a social science with a significant impact on humanity. The discipline uses research to impact people and shape positive behavior. Accuracy is a basic data quality facet necessary in psychological scores. The aspect generally denotes a data’s ability to reflect a real-world condition, often known as correctness (Cooper et al., 2020). Correct data mainly comes from the use of reliable and valid measures. Behavioral psychology requires that scores denoting a subject’s specific behavior match with existing evidence-based records concerning the matter. Accordingly, accuracy is a vital data quality trait in psychology because inaccurate evidence can lead to significant glitches with severe concerns. An error in the acquired scores indicates a mistake in measures and may lead to a whole study’s disqualification. Therefore, scores’ accuracy shows the absence of measurement errors, data completeness, reliability, relevance, and timeliness.
Validity Forms Examination: Face, Content, Criterion-Related, and Construct Validity
Validity arises when scores from a measurement characterize the feature of the aspect they are intended to represent. Determining a score’s reliability is hardly enough in the psychology world (Fisher, 2021). Judging people’s self-esteem based on their middle finder’s length can lead to an extremely excellent test-retest reliability but has zero validity. That is because a subject’s longer finger indicates nothing about one’s self-esteem. Validity exists in various forms, including face, criterion-related, content, and construct kinds. Face validity exists when a measurement technique appears to measure the concept of concern. The validity arises when the utilized method exhibits features generally accepted by the public, making a majority treat such features as accurate elements (Cooper et al., 2020). A self-esteem questionnaire containing inquiries concerning self-assessments appears correct to many people, who then attach face validity to the measure.
Moreover, content rationality is the degree to which a measure covers the targeted hypothesis. The aspect denotes a study’s comprehensiveness in measuring all the possible aspects related to the investigation’s subject (Bordens & Abbott, 2020). Criterion-related validity measures the correlation between subjects’ scores and other variables known or expected to correlate with them (Shepley & Grisham-Brown, 2019). For example, a test on learners’ anxiety is anticipated to return scores depicting low academic performance on subjects towards which the students exhibit negative attitudes. Lastly, a measure that yields scores that adhere to a prevailing model and facts possesses construct validity (Shepley & Grisham-Brown, 2019). All these forms of validity are crucial in psychological research, and scholars should strive to realize them to deliver authoritative results and conclusions.
Ethical Considerations Relating to Choosing a Psychological Measure
Ethical considerations ensure that psychological researchers’ actions remain morally correct. Confidentiality, informed consent, and the right to withdraw are examples of ethical considerations necessary in this discipline. The former facet (confidentiality) connotes the need to maintain participants’ anonymity (Cooper et al., 2020). Privacy or secrecy prevents bias by ensuring that investigators do not identify specific data belonging to particular participants. Informed consent connotes the communication of the study’s genuine objectives to the participants before and during the study. Respondents participating in the investigation should freely accept to do that after understanding the conditions, without feeling pressure or compulsion (Alves et al., 2020). Related to the informed consent aspect is the right to withdraw, where participants have the freedom to quit the study without the obligation to explain the move.
Identification and Description of a Psychological Measure
A Psychological Measure in ABA
Momentary time sampling is an excellent test applied by psychologists in the applied behavior domain. The method involves making transient observations of a specific behavior at particular moments in time (Alves et al., 2020). A behavioral analysis investigating an autistic child’s behavior can use this approach by making momentary visits to a classroom to check whether a child is engaged in the same activity to test attention issues.
The Construction Measures
Momentary time sampling is a repeatability-based measure excellent for measuring attention spans among subjects. The tactic differs significantly from the permanent product and whole interval methods in that it tests both commitment and independence. Instead of watching a behaviorally challenged subject every five minutes, the momentary time sampling approach takes time to ensure minimal interruption and optimum trait depiction. This aspect makes the measurement appropriate in a wider range of behavioral investigations.
The Format of the Measure
Momentary time sampling involves giving the subject a specific task requiring commitment and focus. The measure often requires a natural setting where the participant feels no pressure. The investigator then engages in other activities, frequently away from the study’s venue, and then makes transitorily visits to make observations. The visits may occur within a specific time interval or apply irregular timing. The approach works excellently in determining subjects with problems staying on task.
Strengths and Limitations of the Measure
Momentary time sampling is an intermediate measure suitable for investigating challenged behavioral variations. The approach works similarly to the partial and whole interval measurements that target parallel behavioral issues. A crucial benefit of the momentary time sampling tactic is the investigator’s ability to engage in other activities during the study or engage several subjects simultaneously. Momentary time sampling’s frequency nature provides researchers with a direct ability to acquire quantitative figures, thus facilitating easy quantitative analysis methods’ utilization. Similarly, the method gives participants adequate freedom from the investigator’s interference, thus boosting a laidback study scene. However, momentary time sampling does not fit subjects with highly challenged behaviors requiring constant observation.
Conclusion
Momentary time sampling is suitable for an investigation involving children struggling with remaining on task when performing chores or homework. As the behavioral analyst in charge of such a problem, I would use this method to measure an ADHD subject’s attention span. I would work with the child’s parent inside their typical home setting to momentarily measure commitment and focus on a specific task. Adjusting the time interval to match the participant’s special condition would promote the ability to acquire reliable, valid, and accurate results.
References
Alves, F. J., De Carvalho, E. A., Aguilar, J., De Brito, L. L., & Bastos, G. S. (2020). Applied behavior analysis for the treatment of autism: A systematic review of assistive technologies. IEEE Access, 8, 118664-118672. Web.
Bordens, K. S. & Abbott, B. B. (2020). Research designs and methods: A process approach. McGraw Hill.
Cooper, J. O., Heron, T. E., & Heward, W. L. (2020). Applied behavior analysis. Pearson.
Fisher, W. W. (2021). Handbook of applied behavior analysis. Guilford Publications.
Shepley, C., & Grisham-Brown, J. (2019). Applied behavior analysis in early childhood education: An overview of policies, research, blended practices, and the curriculum framework. Behavior Analysis in Practice, 12(1), 235-246. Web.