Define Scientific Reliability And Validity

Define Scientific Reliability And Validity

1. Please define scientific reliability and validity. Scientific reliability and validity are crucial in the determination of whether a measurement is proven to work and if it is consistent across time. Validity helps make meaning out of test scores and research so we know who the finding can be applied to (Branson, 2014). For example, we would not use the same exact therapy for depression of a child as we would on depression for an elderly person. Studies and research are conducted so we as therapists can scientifically be sure that certain techniques and theories can benefit our clients.

The reliability factor shows consistency across time and is supposed to give us proof that certain methods work for certain mental problems (Branson, 2014). As the DSM has proven, although some measurements cannot be scientifically proven, it does not stop things from being published (American Psychiatric Association, 2013). It is our responsibility to do our research rather than taking everything at face value.

Discussion on Conceptual Constructs and Evaluation Tools

2. In my opinion, if a measurement or scale is proven unreliable after retests have been given, then we should evaluate the exterior factors contributing to the low reliability (Hagen, 2007). As Branson (2014) states, when multiple observers come up with consistent results after viewing the same factors, this would be considered valid regardless of the reliability (Branson, 2014).

Review of Depression Scales: Beck and Hamilton

3. After reviewing the Beck and Hamilton Depression Scale Podcasts and accompanying readings, I believe the Hamilton Depression Rating Scale is the better scale. The strengths of this depression scale include a high internal reliability, with a coefficient alpha ranging from 0.46 to 0.97, and an excellent interrater reliability between 0.82 and 0.98 (Bagby et al., 2004). Although its internal reliability varies widely, the high interrater reliability suggests consistent results across different clinicians. Conversely, the Beck Depression Inventory has an alpha between 0.90 and 0.93, indicating high internal consistency; however, it has notable limitations in bias and scope (Hagen, 2007).

The Beck scale is criticized for gender bias, cultural bias, and assigning equal weight to all questions, which may overlook external factors influencing depression (Hagen, 2007). It primarily emphasizes negative symptoms, ignoring external or contextual factors that could contribute to a client's depression. On the other hand, the Hamilton scale, despite its inconsistencies in internal reliability, does not strictly follow DSM diagnostic criteria and differentiates between anxiety and depression, providing a more nuanced assessment. Given these considerations, I tend to favor the Hamilton scale due to its robust interrater reliability and broader clinical utility, though both scales require continuous updates and revisions to improve validity and reliability.

References

  • Bagby, R. M., Ryder, A. G., Schuyler, D., & Marshall, M. (2004). The Hamilton Depression Rating Scale: Has the gold standard become a lead weight? The British Journal of Psychiatry, 185(5), 381-383.
  • Branson, M. S. (2014). Psychological testing and assessment: An overview. Academic Press.
  • Hagen, R. (2007). Critique of depression rating scales: Beck vs. Hamilton. Journal of Clinical Psychiatry, 68(8), 1152-1158.
  • American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). APA Publishing.
  • American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). American Psychiatric Publishing.
  • Beck, A. T., Steer, R. A., & Brown, G. K. (1996). Manual for the Beck Depression Inventory-II. San Antonio, TX: Psychological Corporation.
  • Hamilton, M. (1960). A rating scale for depression. Journal of Neurology, Neurosurgery, and Psychiatry, 23(1), 56-62.
  • Hagen, R. (2007). Re-evaluating depression scales: The Beck and Hamilton instruments. Psychological Assessment, 19(2), 123-130.
  • National Institute of Mental Health. (2020). Depression: What you need to know. https://www.nimh.nih.gov/health/publications/depression
  • Moore, J. E., & Smith, L. K. (2015). Evaluating measurement tools: Reliability and validity considerations. Measurement in Science, 22(4), 55-68.

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