Explanation:

This scale helps evaluate the immediate danger of self-harm in patients in a psychiatric setting when assessing Suicidal intent.

Explanation:

Systematic reviews synthesize results from multiple RCTs or observational studies, applying rigorous methods to minimize bias. Because they integrate all high-quality evidence on a question, they sit at the top of the evidence pyramid. Individual RCTs come next, then cohort and case-control studies, with cross-sectional near the bottom.

Explanation:

A fixed-effect model treats all studies as estimating the same true effect size under identical conditions. That assumption only makes sense when subjects, interventions, and outcomes are sufficiently similar across studies—i.e., minimal heterogeneity. Thus, it's when Population and interventions are homogeneous.

Explanation:

The Median marks the 50th percentile and isn’t influenced by extreme values. In skewed distributions—where a few very large or small observations would drag the mean away from the center—the median remains the best single-value summary of the “typical” case.

Explanation:

Negative skew means the left tail extends farther than the right. That pulls the arithmetic mean below the mode (hence Mean < Mode), since extreme low values drag down the average more than the most common value.

Explanation:

Opportunity cost is the value of the next-best alternative you give up. By choosing the rural clinic, the physician sacrifices whatever salary, caseload, or career development they could have had in the city. Recognizing that forgone benefit is exactly the concept of Opportunity cost.

Explanation:

Concurrent validity checks how well a new measure correlates with an established “gold standard” when both are administered at the same time. Here, comparing the new tool’s scores directly against PHQ-9 results in the same sample assesses Concurrent validity.

Explanation:

The CAGE questionnaire gives one point for each “yes” answer across its four items. By raising the threshold from two affirmative responses to three, you make it harder to screen positive. As a result, fewer true cases of alcohol misuse will be flagged (sensitivity falls), but you also reduce the number of false positives (specificity rises). In other words, you miss more people who do have a problem but you’re less likely to wrongly label someone as disordered. This results in Decreased sensitivity, increased specificity.

Explanation:

A P-value of 0.04 means that if in reality there were no effect (the null hypothesis is true), you would obtain data at least as extreme as observed in only 4 out of 100 repeated experiments. It does not tell you the probability that the null hypothesis itself is true, nor does it speak to accuracy, effect size, or power directly. Therefore, there is a 4% chance of falsely rejecting the null hypothesis (Type I error rate if the null is true).

Explanation:

When researchers highlight favorable secondary outcomes (like sleep) despite a negative primary endpoint (depression scores), they risk giving a skewed picture of benefit. This selective emphasis—reporting only the “good news”—is classic Reporting bias. Other biases (confounding, selection, observer) involve design or measurement flaws, not selective presentation of results.

Explanation:

The positive likelihood ratio (LR+) equals sensitivity ÷ (1 – specificity). At a cutoff of two “yes” answers, the CAGE typically yields about 72% sensitivity and 75% specificity, giving an LR+ around 2.9. Lower cutoffs boost sensitivity but harm specificity, reducing LR+. Higher cutoffs improve specificity further but sacrifice too much sensitivity, again lowering LR+. Thus, a cutoff of 2 strikes the best overall balance for ruling in harmful use.

Explanation:

A Galbraith plot (also called a radial plot) graphs each study’s standardized effect size against its precision (the inverse of its standard error). Outlier studies will stand apart from the main cluster, flagging heterogeneity. While Forest plots summarize individual results and Funnel plots detect publication bias, only the Galbraith plot directly highlights between-study variability.

Explanation:

Galbraith plots are specifically designed to flag heterogeneity by showing which studies deviate most from the average effect size once you adjust for precision. They help reviewers decide whether a fixed-effect or random-effects model is more appropriate, thus their primary purpose is to Evaluate heterogeneity.

Explanation:

A total score of zero on the CAGE (three “No” answers plus one remaining, assuming the question implies only one "Yes" or zero "Yes" answers if 3 are "No") yields high specificity—meaning few healthy people will test positive—and so a negative result effectively rules out disorder. It doesn’t absolutely confirm sobriety, but it does make alcohol use disorder unlikely, indicating a Low probability of alcohol use disorder.

Explanation:

The Kruskal-Wallis test is the non-parametric equivalent of one-way ANOVA and is used to compare three or more independent groups when the outcome (e.g., pain scores) may not follow a normal distribution. It ranks all observations and tests whether the distributions of ranks differ across groups, making it ideal for skewed or ordinal data without assuming equal variances or normality.

Explanation:

Analysis of covariance (ANCOVA) combines ANOVA and regression: it compares means of a continuous outcome across groups while statistically controlling for one or more continuous or categorical covariates (e.g., age, sex). By including confounders in the model, ANCOVA isolates the effect of the main group factor on the outcome, reducing bias from imbalanced baseline characteristics.

Explanation:

When comparing the means of a continuous outcome between two independent groups at a single time point (e.g., post-intervention scores, or change scores if pre-subtracted), the two-sample (Unpaired t-test) is appropriate, provided the data are approximately normally distributed and variances are similar. It tests whether the difference in group means is statistically significant.

Explanation:

In a 2×2 contingency table, if the expected frequency in any cell is less than 5 (common when outcomes are rare), the chi-square approximation becomes unreliable. Fisher’s exact test computes the exact probability of observing the data under the null hypothesis and is the standard method for small sample or low-frequency tables.

Explanation:

An unadjusted odds ratio may overestimate an association if a confounding variable (e.g., age) is unevenly distributed between groups and is associated with both the exposure and outcome. By including age as a covariate in a multivariable logistic regression model, the adjusted OR accounts for its effect, often attenuating the estimate when age was positively associated with both exposure and outcome. This is described as Confounding by age.

Explanation:

A prospective cohort study enrolls participants based on exposure status (e.g., different lithium levels) and follows them over time to measure subsequent outcomes (depression severity). This design establishes temporal sequence, reduces recall bias, and allows direct measurement of incidence and risk related to the exposure. Thus, a Cohort study is most appropriate.

Explanation:

A Case series describes and analyzes the clinical course of a small group of patients who share a specific exposure (here, 3 individuals on the new drug). It is a descriptive study useful for early identification of potential side effects before larger, more formal studies are undertaken.

Explanation (quick-revision points):

• Reliability deals with consistency; inter-rater reliability is consistency between observers rating the same cases.

• In psychometrics it is commonly quantified with κ (kappa) for categorical ratings or the intraclass correlation coefficient for continuous data.

• κ values ≥ 0.8 denote “almost perfect” agreement; lower values reflect increasing disagreement.

Explanation:

• Predictive validity asks: does today’s score forecast a later, clinically meaningful outcome?

• Criterion validity has two flavours – concurrent (same time-point) and predictive (future event).

• High scores that accurately anticipate later self-harm indicate sound predictive validity.

Explanation:

• AUC > 0.8 = excellent overall discrimination; a value of 0.86 is well inside this zone.

• Sensitivity 100 % means no diseased cases are missed. Where the curve hugs the top-left corner the test achieves its best balance.

• Specificity can still vary at different cut-offs, but the combination of very high sensitivity and high AUC reflects near-ideal screening performance, indicating Optimal screening accuracy.

Explanation:

This scale helps evaluate the immediate danger of self-harm in patients in a psychiatric setting when assessing Suicidal intent.

Explanation:

Systematic reviews synthesize results from multiple RCTs or observational studies, applying rigorous methods to minimize bias. Because they integrate all high-quality evidence on a question, they sit at the top of the evidence pyramid. Individual RCTs come next, then cohort and case-control studies, with cross-sectional near the bottom.

Explanation:

A fixed-effect model treats all studies as estimating the same true effect size under identical conditions. That assumption only makes sense when subjects, interventions, and outcomes are sufficiently similar across studies—i.e., minimal heterogeneity. Thus, it's when Population and interventions are homogeneous.

Explanation:

The Median marks the 50th percentile and isn’t influenced by extreme values. In skewed distributions—where a few very large or small observations would drag the mean away from the center—the median remains the best single-value summary of the “typical” case.

Explanation:

Negative skew means the left tail extends farther than the right. That pulls the arithmetic mean below the mode (hence Mean < Mode), since extreme low values drag down the average more than the most common value.

Explanation:

Opportunity cost is the value of the next-best alternative you give up. By choosing the rural clinic, the physician sacrifices whatever salary, caseload, or career development they could have had in the city. Recognizing that forgone benefit is exactly the concept of Opportunity cost.

Explanation:

Concurrent validity checks how well a new measure correlates with an established “gold standard” when both are administered at the same time. Here, comparing the new tool’s scores directly against PHQ-9 results in the same sample assesses Concurrent validity.

Explanation:

The CAGE questionnaire gives one point for each “yes” answer across its four items. By raising the threshold from two affirmative responses to three, you make it harder to screen positive. As a result, fewer true cases of alcohol misuse will be flagged (sensitivity falls), but you also reduce the number of false positives (specificity rises). In other words, you miss more people who do have a problem but you’re less likely to wrongly label someone as disordered. This results in Decreased sensitivity, increased specificity.

Explanation:

A P-value of 0.04 means that if in reality there were no effect (the null hypothesis is true), you would obtain data at least as extreme as observed in only 4 out of 100 repeated experiments. It does not tell you the probability that the null hypothesis itself is true, nor does it speak to accuracy, effect size, or power directly. Therefore, there is a 4% chance of falsely rejecting the null hypothesis (Type I error rate if the null is true).

Explanation:

When researchers highlight favorable secondary outcomes (like sleep) despite a negative primary endpoint (depression scores), they risk giving a skewed picture of benefit. This selective emphasis—reporting only the “good news”—is classic Reporting bias. Other biases (confounding, selection, observer) involve design or measurement flaws, not selective presentation of results.

Explanation:

The positive likelihood ratio (LR+) equals sensitivity ÷ (1 – specificity). At a cutoff of two “yes” answers, the CAGE typically yields about 72% sensitivity and 75% specificity, giving an LR+ around 2.9. Lower cutoffs boost sensitivity but harm specificity, reducing LR+. Higher cutoffs improve specificity further but sacrifice too much sensitivity, again lowering LR+. Thus, a cutoff of 2 strikes the best overall balance for ruling in harmful use.

Explanation:

A Galbraith plot (also called a radial plot) graphs each study’s standardized effect size against its precision (the inverse of its standard error). Outlier studies will stand apart from the main cluster, flagging heterogeneity. While Forest plots summarize individual results and Funnel plots detect publication bias, only the Galbraith plot directly highlights between-study variability.

Explanation:

Galbraith plots are specifically designed to flag heterogeneity by showing which studies deviate most from the average effect size once you adjust for precision. They help reviewers decide whether a fixed-effect or random-effects model is more appropriate, thus their primary purpose is to Evaluate heterogeneity.

Explanation:

A total score of zero on the CAGE (three “No” answers plus one remaining, assuming the question implies only one "Yes" or zero "Yes" answers if 3 are "No") yields high specificity—meaning few healthy people will test positive—and so a negative result effectively rules out disorder. It doesn’t absolutely confirm sobriety, but it does make alcohol use disorder unlikely, indicating a Low probability of alcohol use disorder.

Explanation:

The Kruskal-Wallis test is the non-parametric equivalent of one-way ANOVA and is used to compare three or more independent groups when the outcome (e.g., pain scores) may not follow a normal distribution. It ranks all observations and tests whether the distributions of ranks differ across groups, making it ideal for skewed or ordinal data without assuming equal variances or normality.

Explanation:

Analysis of covariance (ANCOVA) combines ANOVA and regression: it compares means of a continuous outcome across groups while statistically controlling for one or more continuous or categorical covariates (e.g., age, sex). By including confounders in the model, ANCOVA isolates the effect of the main group factor on the outcome, reducing bias from imbalanced baseline characteristics.

Explanation:

When comparing the means of a continuous outcome between two independent groups at a single time point (e.g., post-intervention scores, or change scores if pre-subtracted), the two-sample (Unpaired t-test) is appropriate, provided the data are approximately normally distributed and variances are similar. It tests whether the difference in group means is statistically significant.

Explanation:

In a 2×2 contingency table, if the expected frequency in any cell is less than 5 (common when outcomes are rare), the chi-square approximation becomes unreliable. Fisher’s exact test computes the exact probability of observing the data under the null hypothesis and is the standard method for small sample or low-frequency tables.

Explanation:

An unadjusted odds ratio may overestimate an association if a confounding variable (e.g., age) is unevenly distributed between groups and is associated with both the exposure and outcome. By including age as a covariate in a multivariable logistic regression model, the adjusted OR accounts for its effect, often attenuating the estimate when age was positively associated with both exposure and outcome. This is described as Confounding by age.

Explanation:

A prospective cohort study enrolls participants based on exposure status (e.g., different lithium levels) and follows them over time to measure subsequent outcomes (depression severity). This design establishes temporal sequence, reduces recall bias, and allows direct measurement of incidence and risk related to the exposure. Thus, a Cohort study is most appropriate.

Explanation:

A Case series describes and analyzes the clinical course of a small group of patients who share a specific exposure (here, 3 individuals on the new drug). It is a descriptive study useful for early identification of potential side effects before larger, more formal studies are undertaken.

Explanation (quick-revision points):

• Reliability deals with consistency; inter-rater reliability is consistency between observers rating the same cases.

• In psychometrics it is commonly quantified with κ (kappa) for categorical ratings or the intraclass correlation coefficient for continuous data.

• κ values ≥ 0.8 denote “almost perfect” agreement; lower values reflect increasing disagreement.

Explanation:

• Predictive validity asks: does today’s score forecast a later, clinically meaningful outcome?

• Criterion validity has two flavours – concurrent (same time-point) and predictive (future event).

• High scores that accurately anticipate later self-harm indicate sound predictive validity.

Explanation:

• AUC > 0.8 = excellent overall discrimination; a value of 0.86 is well inside this zone.

• Sensitivity 100 % means no diseased cases are missed. Where the curve hugs the top-left corner the test achieves its best balance.

• Specificity can still vary at different cut-offs, but the combination of very high sensitivity and high AUC reflects near-ideal screening performance, indicating Optimal screening accuracy.

Explanation: Dopamine D2 blockade from flupentixol causes hyperprolactinaemia, leading to galactorrhoea and sexual dysfunction. Aripiprazole, a partial D2 agonist, lowers prolactin levels while preserving antipsychotic efficacy, making it the intervention of choice for antipsychotic-induced hyperprolactinaemia.

Explanation: Orthostatic hypotension is primarily mediated by α1-adrenergic receptor antagonism. Aripiprazole has minimal α1-blocking activity and thus carries a lower risk of orthostatic hypotension compared to olanzapine and other antipsychotics with stronger α1 antagonism.

Explanation: Under ICD-10, “anorexia nervosa” requires weight loss plus amenorrhea in females, whereas “atypical anorexia nervosa” meets the psychological and behavioural criteria with significant weight loss but without the menstrual disturbance. This patient has the characteristic low BMI (<17.5), intense fear of weight gain, and body-image disturbance, yet continues to menstruate, fitting atypical anorexia nervosa.

Explanation: Severe hypokalemia predisposes to life-threatening ventricular arrhythmias (including torsades de pointes) by increasing myocardial excitability. While muscle weakness and metabolic alkalosis can also occur, the immediate risk is cardiac dysrhythmia.

Explanation: About 70% of Prader-Willi cases arise from deletion or inexpression of paternal genes on 15q11–q13; maternal UPD accounts for most of the remainder.

Explanation: Both disorders involve the same chromosomal region (15q11–q13) but differ by parent-of-origin: Angelman syndrome results from maternal deletion or mutation, whereas Prader-Willi syndrome stems from paternal deletion.

Explanation: FASD encompasses growth restriction (low birth weight), microcephaly, neurocognitive deficits (including memory impairments), and behavioural problems secondary to in utero alcohol exposure.

Explanation: In about 95% of Down syndrome cases an extra chromosome 21 arises from maternal nondisjunction, but roughly 4% result from a Robertsonian translocation. Unlike full trisomy, these translocations can be carried in a balanced form by a parent and passed on to children, giving a recurrence risk of around 10% for future pregnancies.

Explanation: Twin and family studies consistently show that genetic factors account for about 90% of the liability to autism spectrum disorders, with environmental influences explaining the remainder.

Explanation: Lesch-Nyhan is caused by an X-linked HGPRT enzyme deficiency leading to uric acid overproduction (hyperuricemia) and severe, compulsive self-mutilation (biting of lips and fingers), often with choreoathetoid movements.

Explanation: Fragile X arises from a CGG expansion in the FMR1 gene and presents with an enlarged head, low muscle tone, language delays and autistic-like social impairments including gaze avoidance.

Explanation: Smith-Magenis results from a deletion of 17p11.2. It features broad facial structures (including a prominent jaw), developmental delay, and characteristic self-hugging stereotypies alongside severe self-injury and sleep disturbance.

Explanation: Prader-Willi is caused by loss of paternally expressed genes at 15q11. It presents in infancy with hypotonia and poor feeding, followed by onset of insatiable appetite in childhood leading to severe obesity and related complications.

Explanation: X-linked HGPRT deficiency causes uric acid accumulation, neurologic signs (choreoathetoid movements), and compulsive self-mutilation beginning in childhood.

Explanation: Rett syndrome is due to an X-linked MECP2 mutation, affects girls, and is characterized by normal development until 6–18 months followed by regression of motor and language skills, hand-wringing stereotypies, seizures, and autonomic instability.

Explanation: Cri-du-chat arises from a partial deletion of 5p15.2. Infants have a distinctive high-pitched, cat-like cry, pronounced microcephaly, a round face with hypertelorism, and severe learning disability.

Explanation: Rett syndrome is an X-linked dominant disorder caused by mutations in MECP2. After normal early development, girls develop microcephaly, lose purposeful hand movements (replaced by stereotyped hand-wringing), and exhibit autism-like symptoms and seizures.

Explanation: Tuberous sclerosis complex (TSC1/TSC2 mutations) causes cortical and retinal hamartomas, seizures, learning disability, and characteristic facial angiofibromas (adenoma sebaceum).

Explanation: Renal angiomyolipomas together with facial angiofibromas and variable learning disability are hallmarks of tuberous sclerosis complex.

Explanation: NF1 (autosomal dominant, NF1 gene on chromosome 17) is defined by ≥6 café-au-lait macules, axillary/inguinal freckling, and pigmented iris hamartomas (Lisch nodules).

Explanation: The trim-and-fill procedure imputes the “missing” smaller, negative studies and adds them back into the analysis so that the funnel plot regains symmetry. This corrects underrepresentation of negative results, enhancing the generalizability of the meta-analytic estimate.

Explanation: PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) is the evidence-based minimum checklist that replaced the earlier QUOROM statement in 2009. It outlines the items authors should include to ensure transparent, reproducible reporting of systematic reviews and meta-analyses.

Explanation: In the preparation stage, individuals acknowledge the need for change and begin to take practical steps—such as gathering supplies—to implement that change imminently. Stockpiling medications for withdrawal is a classic preparation behavior.

Explanation: Pre-contemplation is characterized by denial or ignorance of the problem and no intention to change within the near future. The statement “I don’t have a problem” typifies this stage.

Explanation: Maintenance follows action and focuses on sustaining the newly adopted behavior over time and avoiding relapse into old patterns.

Explanation: Binswanger’s disease is a subcortical (small-vessel) vascular dementia characterized by widespread leukoaraiosis—radial, periventricular and deep white matter hyperintensities—while the cortex remains relatively preserved.

Explanation: The hallmark pathology in Binswanger’s disease is multiple small (lacunar) infarcts of penetrating arterioles, producing microvascular ischemic lesions throughout the subcortical white matter.

Explanation: This triad—executive dysfunction, gait disturbance, urinary incontinence—combined with MRI evidence of subcortical white matter hyperintensities and lacunar infarcts, is classic for Binswanger’s (subcortical vascular) dementia.

Explanation: Periventricular leukoaraiosis accompanied by subcortical features (apathy, gait/apraxia, incontinence) defines Binswanger’s subcortical vascular dementia.

Explanation: Friedreich’s ataxia is an autosomal recessive disorder caused by GAA trinucleotide repeat expansions in the frataxin gene on chromosome 9. It produces cerebellar and posterior column degeneration (ataxia, nystagmus) and hypertrophic cardiomyopathy leading to early cardiac death.

Explanation: The combination of cerebellar ataxia, dysarthria, nystagmus, and a pedigree suggesting cardiomyopathy (early MI in a relative) strongly points to Friedreich’s ataxia, linked to GAA expansions on chromosome 9.

Explanation:

• Acamprosate works on GABA/glutamate balance to reduce alcohol craving and is not an opioid antagonist, so it carries no risk of precipitating opioid withdrawal in patients using tramadol.

• By contrast, naltrexone blocks opioid receptors and would trigger acute withdrawal if given to someone on tramadol.

• Diazepam and buprenorphine are not indicated for alcohol relapse prevention, and disulfiram’s aversive reaction makes it unsuitable when opioid use is ongoing.

Explanation:

• Naltrexone is a pure opioid antagonist that, once initiated after a sufficient opioid-free interval, blocks the rewarding effects of any opioid taken and so helps sustain abstinence.

• Acamprosate is for alcohol dependence only; buprenorphine and methadone are opioid agonists used during maintenance rather than for abstinence‐focused relapse prevention; lofexidine is for withdrawal symptom relief.

Explanation:

• Anosognosia — unawareness or denial of one’s own neurological deficits — is a hallmark of right (non-dominant) parietal lesions, often manifesting as failure to recognize contralateral weakness.

• Finger agnosia and Gerstmann’s features localize to the dominant parietal lobe; expressive dysphasia to frontal language areas; dressing apraxia can accompany right parietal damage but is less pathognomonic.

Explanation:

• Right parietal (non-dominant) damage characteristically leads to unawareness of deficits (anosognosia) and neglect of the left side.

• Finger agnosia and agraphia reflect dominant-lobe involvement; expressive dysphasia to Broca’s area; visual agnosia to occipital/temporal lesions.

Explanation:

• In the semantic-variant of primary progressive aphasia (a form of FTD), speech remains grammatically fluent but shows loss of word meaning, naming errors, and use of nonspecific substitutes.

• Apraxia and rigidity are motor features of other neurodegenerative syndromes; visual hallucinations point to Lewy body dementia; bradykinesia to parkinsonian disorders.

Explanation:

• Semantic-variant PPA is marked by fluent output yet profound impairment in word meaning and object naming, with disproportionate anterior temporal atrophy.

• Non-fluent PPA causes effortful, halting speech; logopenic variant features word-finding pauses with preserved grammar; behavioral variant presents early personality change.

Explanation:

• Primary progressive aphasia (semantic type) in FTD presents similarly to Wernicke’s—fluent, jargon-filled speech with impaired comprehension—but evolves gradually and is linked to neurodegeneration rather than acute stroke.

Explanation:

• The non-fluent (agrammatic) variant of primary progressive aphasia is defined by halting, effortful speech and agrammatism, while comprehension of individual words remains relatively spared.

• Anomic aphasia involves isolated word-finding difficulty without apraxia; Wernicke’s spares fluency; conduction aphasia features impaired repetition with fluent speech; global aphasia is rare in gradual dementing illness.

Explanation: In older patients, delirium is often precipitated by use of multiple medications. Having more than four drugs increases anticholinergic and psychoactive burden, impairing cognition and precipitating acute confusional states.

Explanation: Metformin is the first-line pharmacotherapy for antipsychotic-induced weight gain. It has consistent evidence for attenuating weight increase without compromising psychiatric stability, whereas dose reduction risks relapse.

Explanation: Beta-blockers are the preferred initial pharmacologic intervention for neuroleptic-induced akathisia. Propranolol (10 mg tds) alleviates restlessness by blocking peripheral adrenergic receptors, whereas anticholinergics target dystonia, not akathisia.

Explanation: Acute akathisia presents as subjective inner restlessness plus motor agitation. Propranolol is more effective and faster-acting than benzodiazepines for this indication, while dose reduction alone may not be feasible immediately.

Explanation: Although bulimia is more common, anorexia nervosa has the highest psychiatric mortality—10–12 times greater than controls—driven by medical complications and suicide.

Explanation: Epidemiological studies consistently show bulimia’s point prevalence is roughly double that of anorexia, reflecting both higher incidence and underdiagnosis in anorexia.

Explanation: Bulimia’s higher prevalence reflects both greater symptom recognition and possibly cultural factors; eating-disorder rates also vary by gender and socioeconomic status.

Explanation: Behavioral activation breaks the cycle of triggers, maladaptive responses, and avoidance, systematically increasing engagement in reinforcing activities to improve mood.

Explanation: Systematic desensitization gradually exposes the patient to the bathing trigger in a controlled way, reducing avoidance–aggression cycles and teaching coping responses.

Explanation: Sleep terrors arise in NREM stages and patients have little or no memory of the episode, whereas nightmares from REM sleep are vividly recalled upon awakening.

Explanation: In Lewy body dementia, loss of normal REM atonia leads to dream enactment—violent movements during sleep that cause injury and falls.

Explanation: Dream enactment behavior with vocalizations and motor movements is characteristic of REM sleep behavior disorder, strongly linked to synucleinopathies.

Explanation: Imputing missing negative studies reduces bias from preferential publication of positive results, yielding a more accurate overall estimate of effect.

Explanation: Funnel plots display effect size against study precision; symmetry suggests low publication bias, while asymmetry indicates missing small negative studies.

Explanation:

This scale helps evaluate the immediate danger of self-harm in patients in a psychiatric setting when assessing Suicidal intent.

Explanation:

Systematic reviews synthesize results from multiple RCTs or observational studies, applying rigorous methods to minimize bias. Because they integrate all high-quality evidence on a question, they sit at the top of the evidence pyramid. Individual RCTs come next, then cohort and case-control studies, with cross-sectional near the bottom.

Explanation:

A fixed-effect model treats all studies as estimating the same true effect size under identical conditions. That assumption only makes sense when subjects, interventions, and outcomes are sufficiently similar across studies—i.e., minimal heterogeneity. Thus, it's when Population and interventions are homogeneous.

Explanation:

The Median marks the 50th percentile and isn’t influenced by extreme values. In skewed distributions—where a few very large or small observations would drag the mean away from the center—the median remains the best single-value summary of the “typical” case.

Explanation:

Negative skew means the left tail extends farther than the right. That pulls the arithmetic mean below the mode (hence Mean < Mode), since extreme low values drag down the average more than the most common value.

Explanation:

Opportunity cost is the value of the next-best alternative you give up. By choosing the rural clinic, the physician sacrifices whatever salary, caseload, or career development they could have had in the city. Recognizing that forgone benefit is exactly the concept of Opportunity cost.

Explanation:

Concurrent validity checks how well a new measure correlates with an established “gold standard” when both are administered at the same time. Here, comparing the new tool’s scores directly against PHQ-9 results in the same sample assesses Concurrent validity.

Explanation:

The CAGE questionnaire gives one point for each “yes” answer across its four items. By raising the threshold from two affirmative responses to three, you make it harder to screen positive. As a result, fewer true cases of alcohol misuse will be flagged (sensitivity falls), but you also reduce the number of false positives (specificity rises). In other words, you miss more people who do have a problem but you’re less likely to wrongly label someone as disordered. This results in Decreased sensitivity, increased specificity.

Explanation:

A P-value of 0.04 means that if in reality there were no effect (the null hypothesis is true), you would obtain data at least as extreme as observed in only 4 out of 100 repeated experiments. It does not tell you the probability that the null hypothesis itself is true, nor does it speak to accuracy, effect size, or power directly. Therefore, there is a 4% chance of falsely rejecting the null hypothesis (Type I error rate if the null is true).

Explanation:

When researchers highlight favorable secondary outcomes (like sleep) despite a negative primary endpoint (depression scores), they risk giving a skewed picture of benefit. This selective emphasis—reporting only the “good news”—is classic Reporting bias. Other biases (confounding, selection, observer) involve design or measurement flaws, not selective presentation of results.

Explanation:

The positive likelihood ratio (LR+) equals sensitivity ÷ (1 – specificity). At a cutoff of two “yes” answers, the CAGE typically yields about 72% sensitivity and 75% specificity, giving an LR+ around 2.9. Lower cutoffs boost sensitivity but harm specificity, reducing LR+. Higher cutoffs improve specificity further but sacrifice too much sensitivity, again lowering LR+. Thus, a cutoff of 2 strikes the best overall balance for ruling in harmful use.

Explanation:

A Galbraith plot (also called a radial plot) graphs each study’s standardized effect size against its precision (the inverse of its standard error). Outlier studies will stand apart from the main cluster, flagging heterogeneity. While Forest plots summarize individual results and Funnel plots detect publication bias, only the Galbraith plot directly highlights between-study variability.

Explanation:

Galbraith plots are specifically designed to flag heterogeneity by showing which studies deviate most from the average effect size once you adjust for precision. They help reviewers decide whether a fixed-effect or random-effects model is more appropriate, thus their primary purpose is to Evaluate heterogeneity.

Explanation:

A total score of zero on the CAGE (three “No” answers plus one remaining, assuming the question implies only one "Yes" or zero "Yes" answers if 3 are "No") yields high specificity—meaning few healthy people will test positive—and so a negative result effectively rules out disorder. It doesn’t absolutely confirm sobriety, but it does make alcohol use disorder unlikely, indicating a Low probability of alcohol use disorder.

Explanation:

The Kruskal-Wallis test is the non-parametric equivalent of one-way ANOVA and is used to compare three or more independent groups when the outcome (e.g., pain scores) may not follow a normal distribution. It ranks all observations and tests whether the distributions of ranks differ across groups, making it ideal for skewed or ordinal data without assuming equal variances or normality.

Explanation:

Analysis of covariance (ANCOVA) combines ANOVA and regression: it compares means of a continuous outcome across groups while statistically controlling for one or more continuous or categorical covariates (e.g., age, sex). By including confounders in the model, ANCOVA isolates the effect of the main group factor on the outcome, reducing bias from imbalanced baseline characteristics.

Explanation:

When comparing the means of a continuous outcome between two independent groups at a single time point (e.g., post-intervention scores, or change scores if pre-subtracted), the two-sample (Unpaired t-test) is appropriate, provided the data are approximately normally distributed and variances are similar. It tests whether the difference in group means is statistically significant.

Explanation:

In a 2×2 contingency table, if the expected frequency in any cell is less than 5 (common when outcomes are rare), the chi-square approximation becomes unreliable. Fisher’s exact test computes the exact probability of observing the data under the null hypothesis and is the standard method for small sample or low-frequency tables.

Explanation:

An unadjusted odds ratio may overestimate an association if a confounding variable (e.g., age) is unevenly distributed between groups and is associated with both the exposure and outcome. By including age as a covariate in a multivariable logistic regression model, the adjusted OR accounts for its effect, often attenuating the estimate when age was positively associated with both exposure and outcome. This is described as Confounding by age.

Explanation:

A prospective cohort study enrolls participants based on exposure status (e.g., different lithium levels) and follows them over time to measure subsequent outcomes (depression severity). This design establishes temporal sequence, reduces recall bias, and allows direct measurement of incidence and risk related to the exposure. Thus, a Cohort study is most appropriate.

Explanation:

A Case series describes and analyzes the clinical course of a small group of patients who share a specific exposure (here, 3 individuals on the new drug). It is a descriptive study useful for early identification of potential side effects before larger, more formal studies are undertaken.

Explanation (quick-revision points):

• Reliability deals with consistency; inter-rater reliability is consistency between observers rating the same cases.

• In psychometrics it is commonly quantified with κ (kappa) for categorical ratings or the intraclass correlation coefficient for continuous data.

• κ values ≥ 0.8 denote “almost perfect” agreement; lower values reflect increasing disagreement.

Explanation:

• Predictive validity asks: does today’s score forecast a later, clinically meaningful outcome?

• Criterion validity has two flavours – concurrent (same time-point) and predictive (future event).

• High scores that accurately anticipate later self-harm indicate sound predictive validity.

Explanation:

• AUC > 0.8 = excellent overall discrimination; a value of 0.86 is well inside this zone.

• Sensitivity 100 % means no diseased cases are missed. Where the curve hugs the top-left corner the test achieves its best balance.

• Specificity can still vary at different cut-offs, but the combination of very high sensitivity and high AUC reflects near-ideal screening performance, indicating Optimal screening accuracy.

Explanation:

Pearson’s correlation coefficient (r) ranges from –1 to +1, with values nearer ±1 indicating stronger linear relationships. An r of 0.38 falls in the moderate range, signifying that higher loneliness scores tend to occur alongside higher depression scores, but causality cannot be inferred from correlation alone.

Explanation:

Values of r near –1 indicate strong inverse linear associations. An r of –0.85 means that as sleep hours decrease, cognitive performance tends to decrease in a strongly linear fashion. Pearson’s r quantifies both direction (sign) and strength (magnitude) of linear relationships.

Explanation:

Spearman’s rho measures the strength of a monotonic association between two ranked variables without assuming normality. A ρ of 0.8 indicates a strong positive correlation, meaning both scales track the same construct closely—but it says nothing about validity, reliability, or replacement of one by the other.

Explanation:

A Spearman’s rho of 0.81 denotes a strong positive monotonic relationship between the two instruments, indicating they yield very similar rankings of depressive severity across subjects.

Explanation:

A Pearson r of –1 signifies a perfect inverse linear relationship: every increase in X corresponds to a proportional decrease in Y, and all data points lie exactly on a downward-sloping line.

Explanation:

An r of –0.9 is very close to –1, reflecting a very strong negative linear association. Here, higher alcohol intake is strongly linked with higher liver enzyme levels in an inverse coding scheme (e.g., if enzymes were scored inversely).

Explanation:

An R (Pearson’s correlation) of 0.7 indicates a strong positive linear association in the chosen coding: as one variable increases, so does the other. The closer |R| is to 1, the stronger the linear link.

Explanation:

Kendall’s tau-b ranges from –1 to +1, with values around 0.4–0.6 indicating moderate associations between ordinal variables. A τ of 0.45 therefore reflects a clear, moderate positive relationship.

Explanation:

Unlike Spearman’s rho—which assumes equal spacing between ranks—Kendall’s tau-b does not require equidistant ranking and properly accounts for tied observations in ordinal data.

Explanation:

Pearson’s r quantifies the linear association between two interval/ratio-scale variables under normality assumptions, providing both direction and magnitude of the relationship.

Explanation:

Kendall’s tau is a non-parametric measure of association suited to ordinal variables or small sample sizes, offering a robust alternative when rank distributions aren’t equidistant.

Explanation:

A p-value <0.05 confirms a real association unlikely due to chance, but correlation does not establish cause–effect and may reflect confounders. Correlation quantifies strength/direction, not causation.

Explanation:

For within-subject comparisons at ≥3 timepoints on a continuous measure, repeated-measures ANOVA accounts for the correlation between repeated observations and tests for overall change over time.

Explanation:

Continuous outcomes modeled against continuous predictors at multiple timepoints are examined via linear regression, which provides β coefficients and p-values for each predictor–outcome relationship.

Explanation:

Multiple linear regression allows estimation of the independent effect of BP on cognitive scores while statistically controlling for confounders like age by including them in the model.

Explanation:

Cox regression is the standard survival-analysis technique for modeling the hazard (instantaneous risk) of an event over time while allowing adjustment for covariates.

Explanation:

Logistic regression estimates the probability of a dichotomous event (e.g., diabetic vs. non-diabetic), yielding odds ratios for predictors without requiring normally distributed residuals.

Explanation:

Inter-rater reliability quantifies agreement between different observers rating the same subjects using the same instrument, ensuring consistency across raters.

Explanation:

Predictive validity is established when a measure accurately forecasts later outcomes—in this case, tool scores predicting subsequent suicide attempts.

Explanation:

Concurrent validity is a subtype of criterion validity, determined by correlating a new measure with an established “gold standard” at the same point in time (here, the PHQ-9).

Explanation:

Content validity assesses whether a measure includes all the important domains of its intended construct (anxiety) as defined by expert consensus.

Explanation:

By comparing the new instrument against the Structured Clinical Interview for DSM (SCID) at the same time, one evaluates concurrent validity—a form of criterion validity.

Explanation:

Divergent (discriminant) validity is violated when a tool correlates strongly with measures of unrelated constructs—in this case, autism traits—indicating poor discrimination.

Explanation:

Concurrent validity refers to the degree to which a new measure correlates with an established “gold-standard” instrument when both are administered at the same time.

Explanation:

By measuring agreement with a gold-standard diagnosis at the same time point, the study is assessing concurrent validity rather than future prediction or content coverage.

Explanation:

Direct comparison with an existing validated scale at the same time establishes concurrent validity. Predictive validity would require following participants forward to see who develops an outcome later.

Explanation:

Predictive validity assesses how well an instrument forecasts future outcomes. Here, early cognitive scores are used to predict later academic performance.

Explanation:

The World Health Organization–recommended Alcohol Use Disorders Identification Test (AUDIT) is a 10-item questionnaire validated in primary-care settings, demonstrating superior sensitivity and specificity compared to brief biochemical markers or single‐question screens.

Explanation:

DBT includes scheduled telephone coaching between sessions to help patients apply emotion‐regulation and distress‐tolerance skills in real‐life crises.

Explanation:

Early models of family therapy (e.g., Bowenian) were rooted in psychodynamic principles, emphasizing unconscious conflicts and transgenerational dynamics.

Explanation:

CAT is delivered in three phases—initial problem‐formulation (reformulation), patient insight and identification of reciprocal‐role patterns (recognition), and development of new behavioural strategies (revision).

Explanation:

These steps guide the CAT process: first reformulate the problem in diagram form, then help the patient recognize maladaptive scripts, and finally revise them into healthier patterns.

Explanation:

Revision is the active phase where the patient experiments with and adopts new, adaptive ways of relating, replacing old problematic scripts.

Explanation:

DBT was specifically developed to teach emotion‐regulation, distress‐tolerance, interpersonal‐effectiveness, and mindfulness skills, and has the strongest evidence for reducing self‐harm and emotional dysregulation in BPD.

Explanation:

MI works by helping patients perceive the gap between their current behaviors and broader goals/values, thereby enhancing intrinsic motivation to change.

Explanation:

MI is a client‐centred, directive style focused on resolving ambivalence; it does not include external contingency‐management techniques like tangible rewards.

Explanation:

Psychodynamic psychotherapy explores early family relationships and unconscious conflicts that shape current emotions and behaviors.

Explanation:

Standard IPT for depression is delivered in 12–16 weekly, 1-hour sessions, targeting current interpersonal issues rather than historical trauma.

Explanation:

IPT works on four problem areas—bereavement, role disputes, role transitions, and interpersonal deficits—with grief and disputes being central for depressive symptoms.

Explanation:

Grief‐focused IPT strengthens social networks and communication to help patients process loss and regain social functioning.

Explanation:

Transference occurs when a patient unconsciously redirects feelings about significant others onto the therapist.

Explanation:

Countertransference is the therapist’s own unconscious emotional response to the patient’s material.

Explanation:

By definition, countertransference comprises all of the therapist’s emotional reactions—both conscious and unconscious—to the patient’s transference and material.

Explanation:

Hypocalcaemia prolongs phase 2 of the cardiac action potential, lengthening the QT interval. It is one of the key metabolic risk factors for QTc prolongation, alongside hypokalaemia and hypomagnesaemia.

Explanation:

Donepezil, an acetylcholinesterase inhibitor, enhances vagal tone and can lead to sinus bradycardia, sometimes resulting in syncope in older patients.

Explanation:

Bradycardia is a well-recognized vagotonic effect of cholinesterase inhibitors like donepezil, reflecting increased parasympathetic activity on the sinoatrial node.

Explanation:

Gastrointestinal and vestibular side effects of donepezil are dose-related and often transient. The first-line approach is to lower the dose before switching agents or adding other medications.

Explanation:

At levels ≥1.5 mmol/L, lithium toxicity begins to manifest with gastrointestinal upset and central nervous system effects such as coarse tremor, ataxia, drowsiness, confusion, and muscle twitching (myoclonus). Myoclonic jerks signal severe neurotoxicity and warrant immediate intervention.

Explanation:

Lithium neurotoxicity produces hyperactive neurological signs—coarse tremor, ataxia, dysarthria, nystagmus, confusion, and even seizures—rather than diminished reflexes. Hyporeflexia would be atypical in this context.