Evidence-Based Practice in Allied Health

Importance of Evidence in Allied Health

• Research informs clinical decision making and supports high-quality, ethical care.
• Evidence-based practice (EBP) is a dynamic process incorporating research, patient needs, clinical expertise, and service context.

EBP Frameworks and Processes

• EBP/E^4^BP Framework: emphasizes key components like patient values and needs, service context, clinical expertise, and research findings.
• 5 Steps of the EBP Process: P (Problem/Patient), I (Intervention/interest), C (Comparison), O (Outcome) framework helps structure clinical questions for effective research.

Understanding Research

• Quantitative research: focuses on numerical data, investigating relationships, cause-and-effect, frequency, course/prognosis, and population/sample characteristics.
• Qualitative research: explores quality, themes, and experiences, providing deeper insights into phenomena.

Critical Appraisal

• CASP Critical Appraisal Checklist: helps systematically evaluate research by ensuring important factors and considerations are taken into account.
• Consistency in decision-making is promoted by using a structured appraisal framework.

Knowledge Translation

• Knowledge translation (KT): bridges the gap between research evidence and clinical practice through strategies that enhance awareness and encourage behavior change aligned with research findings.
• KT phases: Knowledge creation, integration, implementation, and dissemination to promote effective knowledge use and improve services by engaging clinicians, the public, and consumers.

Week 1 Assignment

• Article: "Sharing and valuing older Aboriginal people's voices about social and emotional wellbeing services: a strength-based approach for service providers" by Gibson et al. (2020)
• Focus: Analyze Methods and Results sections (pp. 482-485) to address the following:
  • How do the methods reflect the AH&MRC principles?
  • Discuss the research approval process and its importance.
  • Identify the three themes and how subthemes relate to the main themes.

Information Retrieval and Sources

• Bibliographic databases: CINAHL and PubMed offer access to peer-reviewed literature.
• Grey literature: Includes government reports, statistics, and non-peer-reviewed research that informs practice and guides additional research needs.
• Unpublished research: May not be peer-reviewed or rigorously evaluated.

Measurement

• Measurement in allied health: involves assigning numerals to variables influencing people's characteristics and behavior.
• Constructs: Represent underlying concepts and traits influencing behavior.

Assessment

• Different Assessment Types:
  • Discriminative: Differentiates between individuals with and without a condition (e.g., diagnostic or screening tools).
  • Evaluation: Measures changes over time (e.g., outcome assessment).
  • Predictive: Forecasts future ability.

Validity and Reliability

• Validity: Determines if an assessment measures what it intends to, allowing for meaningful interpretation.
• Reliability: Focuses on the consistency of scores and minimization of errors, ensuring confidence in data collection and analysis.
  • Systematic error: Predictable, consistent, and modifiable error.
  • Random error: Occurs due to chance, influencing accuracy.

Types of Reliability

• Test-Retest Reliability: Measures the consistency of results across repeated administrations of the same test.
  • Considerations: time between administrations, test environment consistency, carryover effects.
  • Statistics used: Intraclass Correlation Coefficient (ICC), Kappa Statistic, % Agreement, Standard Error of Measurement, Pearson or Spearman Correlation (ICC preferred).
• Rater Reliability: Evaluates the consistency of ratings among different raters.
  • Intrarater Reliability: Stability of results by one rater across multiple trials.
  • Interrater Reliability: Agreement between two or more raters assessing the same subject.
  • Statistics used: Intraclass Correlation Coefficient (ICC), Kappa Statistic, % Agreement, Standard Error of Measurement, Pearson or Spearman Correlation (ICC preferred).
• Internal Consistency: Examines the extent to which items on an assessment measure various aspects of the same characteristic.
  • Statistics: Cronbach’s Alpha (α), item-to-total correlations (Pearson product-moment), Spearman-Brown prophecy statistic (for split-half reliability).

Content Validity

• Content validity: Ensures that the assessment items reflect the intended domain of measurement.

Rules of Measurement

• Measurement requires established criteria for assigning values and clear definitions of attributes.

Descriptive Statistics

• Population and Samples:
  • Population: Entire group of interest.
  • Sample: Subset of the population, used to draw conclusions about the population.
  • Sampling error: Occurs because a sample may not perfectly reflect the entire population.
• Descriptive statistics: Summarize and describe data characteristics.
  • Central tendency: Measures the typical or average value (mean, median, mode).
  • Spread and variance: Show the variability of data (range, minimum/maximum values, quartiles/interquartile range, standard deviations).