The main idea is a therapy approach that is non-directive and grounded in humanistic psychology, guiding the client toward self-directed growth. In client-centered therapy, the clinician does not steer the conversation toward specific interpretations or solutions. Instead, the client leads, and the therapist provides a supportive environment through unconditional positive regard, empathic understanding, and genuineness. This stance helps the client explore feelings and experiences openly, moving toward greater alignment between self-concept and reality. The underlying belief is that people have the inner resources to grow, and the therapist’s role is to reflect and facilitate rather than direct. This stands in contrast to more structured or interpretive approaches, such as cognitive-behavioral therapy (which is directive and skills-focused), biomedical therapy (which relies on medical interventions), or psychodynamic therapy (which emphasizes interpreting unconscious factors and past conflicts).

Understanding grief as described by Kubler-Ross, the final stage is acceptance. After moving through denial, anger, bargaining, and depression, a person reaches a point where they acknowledge the reality of the loss and begin to adjust their life accordingly. Acceptance involves integrating the loss into one’s life and finding a way to move forward, rather than denying or resisting it. It's also worth noting that not everyone experiences every stage or in a linear order, but acceptance is regarded as the concluding stage in the model.

Effect size is about the magnitude of the difference or the strength of a relationship, which tells you how big the observed effect is in practical terms. This matters alongside p-values because statistical significance alone doesn’t tell you how important the finding is in real-world terms. A result can be statistically significant with a very small but detectable effect if the sample is large, or it can be non-significant with a substantial effect if the sample is small. Reporting the effect size helps you judge practical significance, compare results across studies, plan future research with power analyses, and synthesize evidence in meta-analyses. Common measures include Cohen’s d for differences between groups, correlation coefficients like r for relationships, and odds ratios for binary outcomes. The p-value, by contrast, indicates how unlikely the observed data would be if there were no true effect, not how big that effect is. It does not convey magnitude. It also isn’t a measure of the probability that the null hypothesis is true, which is a different interpretation often confused with p-values. And it doesn’t reflect the rate of Type I error—that's set by the alpha level and relates to the frequency of false positives over many tests, not to how large an effect is.

Substance use disorder is diagnosed when there is a pattern of problematic substance use that causes clinically significant impairment or distress, and this pattern is identified by meeting at least two of the diagnostic criteria within a 12-month period. There are 11 criteria in total, including needing more of the substance to achieve the same effect (tolerance), experiencing withdrawal, using more or for longer than intended, unsuccessful attempts to cut down, spending a lot of time obtaining, using, or recovering, strong cravings, failure to fulfill major role obligations, continued use despite social or interpersonal problems, giving up important activities, using in hazardous situations, and recurrent legal problems. The number of criteria met determines severity: two to three is mild, four to five moderate, and six or more severe. This threshold captures a pattern over time rather than a single episode, and it emphasizes the impairment or distress side of the disorder, not just isolated use.