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Methodology · LBL-DEP · v1.0

How the LBL Depression Test actually works.

Instrument selection, scoring algorithm, severity-band derivation, sub-dimension symptom profile, archetype framework, item-9 hard-escalation crisis modal architecture, validation evidence, and limitations — fully documented.

Developed by Abiot Y. Derbie, PhD — cognitive neuroscientist & founder. Reviewed by Eskezeia Y. Dessie, PhD — clinical reviewer. Browser-local. Nothing transmitted. No accounts. Source-cited methodology.

1. Instrument selection & naming

The screening questionnaire used in this tool was developed by Kroenke, Spitzer, and Williams in 2001, published in Journal of General Internal Medicine (16:606-613). It is a 9-item self-report instrument deriving directly from the 9 DSM-IV major depressive episode criteria, with each item rated 0-3 on a frequency scale over the past 2 weeks. It is the most widely-used brief depression screener in the world, with over 100,000 citations across psychology, sleep medicine, primary care, occupational health, and psychiatry.

Why this instrument over alternatives

  1. Brevity. 9 items completed in 2-3 minutes. Beck Depression Inventory has 21 items and is impractical for primary-care screening; Hamilton Depression Rating Scale is clinician-administered.
  2. Validation depth. Cronbach's α = 0.89 in original (Kroenke 2001). Sensitivity 88%, specificity 88% at cutoff ≥10 for major depression. Test-retest reliability r = 0.84.
  3. Standard cutpoints. 0-4 / 5-9 / 10-14 / 15-19 / 20-27 are used by NHS IAPT (Improving Access to Psychological Therapies), VA/DoD clinical practice guidelines, and APA major depressive disorder guidelines.
  4. Permissive licensing. Pfizer (which funded the original PRIME-MD project) explicitly grants "No permission required to reproduce, translate, display or distribute."
  5. Direct DSM mapping. Each of the 9 items corresponds to one of the 9 DSM major depressive episode criteria — symptom-by-symptom transparency.
  6. Built-in suicidality item. Item 9 captures self-harm ideation directly — this enables crisis-aware design that other depression screeners (HADS does not include this) cannot match.

Naming convention used in this tool

2. The 9 items + functional impairment item

The standard implementation includes the 9 symptom items (scored, sum 0-27) plus a 10th functional-difficulty question that is not added to the score but informs interpretation.

#ItemCluster (author choice)DSM-V criterion
1Little interest or pleasure in doing thingsAnhedonicA2 (anhedonia)
2Feeling down, depressed, or hopelessCognitive-emotionalA1 (depressed mood)
3Trouble falling or staying asleep, or sleeping too muchSomaticA4 (sleep)
4Feeling tired or having little energySomaticA6 (fatigue)
5Poor appetite or overeatingSomaticA3 (appetite)
6Feeling bad about yourself, or that you are a failureCognitive-emotionalA7 (worthlessness)
7Trouble concentratingCognitive-emotionalA8 (concentration)
8Moving/speaking slowly, or fidgety/restless (psychomotor)SomaticA5 (psychomotor)
9Thoughts that you would be better off dead, or of hurting yourselfSelf-harm (singleton)A9 (suicidality)

Functional impairment item (not added to score):

If you checked off any problems, how difficult have these problems made it for you to do your work, take care of things at home, or get along with other people?

Response options: Not difficult at all (0) / Somewhat difficult (1) / Very difficult (2) / Extremely difficult (3). This item is captured but not summed. It informs the results copy: a moderate-band score with "extremely difficult" functional impairment is interpreted as warranting more urgent follow-up than a moderate score with "not difficult at all."

Reference period: Past 2 weeks. Response options for items 1-9: 0 = Not at all, 1 = Several days, 2 = More than half the days, 3 = Nearly every day. Total score range: 0-27.

3. Scoring algorithm

The scoring algorithm follows Kroenke 2001 directly. Pseudocode for the implementation:

// Inputs: responses[1..9] each in {0,1,2,3}; functional in {0,1,2,3,null} // Total score total = sum(responses[1] + responses[2] + ... + responses[9]) // Sub-dimension scores (author choice — see §7) cognitive = responses[2] + responses[6] + responses[7] // max 9 somatic = responses[3] + responses[4] + responses[5] + responses[8] // max 12 anhedonic = responses[1] // max 3 suicidality = responses[9] // singleton, not in profile // Band assignment if total <= 4: band = 'minimal' elif total <= 9: band = 'mild' elif total <= 14: band = 'moderate' elif total <= 19: band = 'mod-severe' else: band = 'severe' // Item-9 crisis modal — triggered immediately on any non-zero response on item_9_change(value): if value > 0: open_crisis_modal(tier = (2 if value >= 2 else 1)) // Functional impairment override if functional == 3 and total >= 5: show_functional_override_note() // Severe-band clinician prompt if total >= 20: show_severe_clinician_prompt()

The implementation is straightforward: integer addition with no weights, no missing-data imputation (the user must answer all 9 items to enable the submit button), and clear band cutoffs.

4. Five severity bands

The 5-band structure comes directly from Kroenke 2001 and is used by NHS IAPT, VA/DoD, and APA. We do not modify the cutpoints.

BandScoreLabelClinical interpretation
10-4Minimal depressionSymptoms unlikely clinically significant. Most adults score here.
25-9Mild depressionSome symptoms, subthreshold for major depressive episode (MDE). Watchful waiting + self-care typical.
310-14Moderate depressionProbable MDE per the standard ≥10 cutoff (sensitivity 88%, specificity 88%). Active treatment warranted.
415-19Moderately severe depressionActive treatment with therapy and/or medication usually appropriate.
520-27Severe depressionHigh symptom burden. Combined treatment (therapy + medication) often warranted. Professional consultation strongly recommended.

5. The cutoff debate: ≥10 vs ≥8

The standard cutoff of ≥10 has been validated repeatedly. Manea, Gilbody & McMillan's 2012 meta-analysis of 18 studies confirmed the ≥10 cutoff has the best balance of sensitivity (0.78-0.88) and specificity (0.85-0.94) across primary care populations.

CutoffSensitivitySpecificityTrade-off
≥80.93-0.960.71-0.78Maximizes detection at cost of false positives
≥10 (standard)0.78-0.880.85-0.94Best balance per Manea 2012
≥120.65-0.750.92-0.97Conservative — minimizes false positives at cost of missed cases

Some research contexts use ≥8 to maximize sensitivity in screening protocols where missing a case is more costly than over-flagging (e.g., perinatal depression screening). For most clinical and self-screen contexts, ≥10 remains the most-cited and clinically established cutpoint, and is what this tool uses for the moderate-band threshold.

6. Item 9 hard-escalation modal architecture

This is the single biggest design departure from the LBL Anxiety Test build. Documented here in detail because the architecture has clinical safety implications.

The item

Item 9 reads: "Thoughts that you would be better off dead, or of hurting yourself in some way." Response scale 0-3 (Not at all / Several days / More than half the days / Nearly every day).

Behavior specification

Rationale

Mann et al. 2005's systematic review of suicide prevention strategies concluded that means restriction and direct connection to crisis resources are among the most evidence-supported interventions. Surfacing crisis resources immediately upon any non-zero response on item 9 — and requiring explicit acknowledgment — is a deliberate friction designed to ensure the user encounters the resources, not to obstruct their use of the tool. The non-blocking design respects user autonomy: anyone can continue to results, but no one inadvertently dismisses the resource panel.

7. Sub-dimension symptom profile

Author choice The sub-dimension symptom profile is an interpretive framework added by LifeByLogic. The original instrument is largely unidimensional in factor analysis. This is documented transparently rather than presented as a validated subscale.

Three dimensions (3/4/1 split)

DimensionItemsMax scoreWhat it captures
Cognitive-emotional2, 6, 79Depressed mood, worthlessness/guilt, concentration
Physical / somatic3, 4, 5, 812Sleep, fatigue, appetite, psychomotor
Pleasure-motivation (anhedonic)13Anhedonia (loss of interest/pleasure)

Item 9 (self-harm ideation) is not included in any sub-dimension grouping. It triggers crisis escalation and is reported as a singleton in the results.

Why these three dimensions specifically

Clinical depression treatment differentiates strongly between intervention classes:

Why this is presented as an author choice rather than a validated subscale

Factor analysis on the original instrument finds primarily a single-factor structure (Kroenke 2001, Cameron 2008). Some studies find a 2-factor solution (cognitive-affective + somatic), but no replicated 3-factor structure exists in the literature. The 3-dimension grouping in this tool is interpretive — useful for matching pattern to evidence-based intervention class, but not a validated psychometric subscale.

8. Asymmetric scaling for archetype matching

Author choice The 1.0 / 0.75 / 3.0 scaling factors used in archetype matching are author-derived to bring all three sub-dimensions to comparable theoretical maximum.

The three sub-dimensions have asymmetric maximum scores (cognitive-emotional max=9, somatic max=12, anhedonic max=3) because they have asymmetric item counts (3 / 4 / 1). For archetype matching to work — i.e., for any of the three dimensions to be capable of dominating when it is the leading edge — they need to be brought to comparable scale.

The scaling factors

Why asymmetric scaling is necessary

Without scaling, somatic dominance would be over-easy to achieve (4 items at max gets 12 vs cognitive's max of 9), and anhedonic dominance would be near-impossible to achieve (max 3 vs cognitive's 9). The result would be archetype assignment biased toward "Depleted" (somatic-dominant) and against "Disconnected" (anhedonic-dominant), even when the underlying symptom pattern doesn't warrant it.

Mathematical example

User scores: cognitive=6, somatic=8, anhedonic=2 (total=16).

The scaling reveals when the underlying symptom pattern is genuinely balanced vs genuinely dominated by one dimension. This is documented as an author choice because no published precedent for these specific scaling factors exists; they are derived from the asymmetric maximums alone.

9. Five-archetype framework

Author choice The 5 archetypes are LBL-derived interpretive frameworks, not a published clinical typology.

Five archetypes match symptom profile to evidence-based intervention pathways. Order matters — first match wins, more specific archetypes tested first.

ArchetypeTrigger conditionPrimary intervention classKey citations
The Steady total < 5 Maintenance practices, watchful waiting
The Inner Critic cognitive_scaled ≥ somatic_scaled AND ≥ anhedonic_scaled CBT for depression, cognitive restructuring, MBCT, IPT Cuijpers 2013, Kuyken 2016
The Depleted somatic_scaled > cognitive_scaled AND ≥ anhedonic_scaled Behavioral activation, exercise, sleep stabilization, SSRIs/SNRIs Cooney 2013, Hollon 2005
The Disconnected anhedonic_scaled ≥ cognitive_scaled AND ≥ somatic_scaled Behavioral activation, BATD, novel reward exposure Dimidjian 2006, Ekers 2014, Lejuez 2001
The Pervasive (default) — multidimensional, no single dimension dominates Combined therapy + medication, MBCT, integrated CBT-D Hollon 2005, Kuyken 2016

Pathway count per archetype

Each archetype carries 5-7 evidence-based pathway recommendations:

Total: 31 evidence-cited pathways across the 5 archetypes.

10. Diagnostic probability per band

Author choice The approximate confirmed-MDE rates per band (1/10/50/75/90 in 100) are derived from the Kroenke 2001 ROC data and rounded for intuitive interpretation.

BandScore rangeApproximate confirmed-MDE rate
Minimal0-4≈ 1 in 100
Mild5-9≈ 10 in 100
Moderate10-14≈ 50 in 100
Moderately severe15-19≈ 75 in 100
Severe20-27≈ 90 in 100

Derivation

Values derived from the Kroenke 2001 ROC analysis (sensitivity 88%, specificity 88% at ≥10 cutoff in n=580 with structured diagnostic interview). The approximate per-band rates assume a base rate of MDE consistent with the original primary-care validation sample (12-month prevalence ~5-9% per Kroenke 2007). They are explicitly labeled "approximate, derived from Kroenke 2001" on the tool page.

Population-dependence caveat

These probability values depend on the base rate of MDE in the user's population. In primary care (~5-9% 12-month prevalence per Kroenke 2007), they are roughly accurate. In psychiatric outpatient samples (much higher base rate, typically 50-70% per Beard 2016), the per-band rates would be higher. In low-base-rate populations (e.g., asymptomatic community samples), they would be lower. The values serve as an intuitive interpretation aid, not a precise probabilistic statement applicable to every user.

11. Population norms

The tool compares user score against two reference populations:

PopulationSampleMeanSDSource
General population (Germany)n = 5,0182.913.52Kocalevent et al. 2013
Female (Germany)n ≈ 2,6083.133.61Kocalevent et al. 2013
Male (Germany)n ≈ 2,4102.663.41Kocalevent et al. 2013
Primary care (US)n = 6,0003.33.8Kroenke et al. 2001
Psychiatric outpatientn = 50213.86.5Beard 2016

The general-population norm (Kocalevent 2013) anchors comparison against people not seeking help; the primary-care norm (Kroenke 2001) anchors against people who consulted a clinician about symptoms. Both are reported on the tool page with z-scores and percentiles computed via standard normal CDF.

12. Documented author choices summary

Three components of this tool are not directly derivable from published literature and are documented here as transparent author choices:

ComponentAuthor choiceRationale
Sub-dimension item assignments 3 cognitive-emotional / 4 somatic / 1 anhedonic Maps items to evidence-based intervention classes; original instrument is unidimensional in factor analysis
Asymmetric scaling factors 1.0 / 0.75 / 3.0 Brings sub-dimensions to comparable theoretical maximum (9) so any can dominate archetype matching
Approximate dx-prob values per band 1 / 10 / 50 / 75 / 90 in 100 Derived from Kroenke 2001 ROC data, rounded for intuitive interpretation; population-dependent
5-archetype framework Steady / Inner Critic / Depleted / Disconnected / Pervasive LBL-derived interpretive labels matched to evidence-based intervention classes; not a published clinical typology
Item 9 modal threshold Triggered at item 9 ≥ 1 (any non-zero) Clinical convention strongly favors over-flagging suicidality; cost of over-flagging is low (resources displayed), cost of under-flagging is potentially severe
Tier 2 escalation threshold Item 9 ≥ 2 (more than half the days) Distinguishes occasional ideation from sustained ideation; aligns with research distinguishing passive vs active ideation

13. Validation evidence

Internal consistency

Cronbach's α = 0.89 in the original Kroenke 2001 validation (n=580). Hinz et al. 2017 confirmed α = 0.88 in a German general-population sample (n=5,018). This is solid internal consistency for a 9-item instrument.

Test-retest reliability

Test-retest correlation r = 0.84 in Kroenke 2001 (n=300, ~48 hours between administrations).

Diagnostic accuracy at ≥10 cutoff

StudyPopulationSensitivitySpecificityNPV
Kroenke 2001Primary care (n=580)0.880.88≈ 0.99
Manea 2012 (meta-analysis)18 primary care studies0.78-0.880.85-0.94≈ 0.96-0.99
Beard 2016Psychiatric outpatient (n=502)0.850.78≈ 0.92

Convergent validity

The instrument correlates strongly with the Beck Depression Inventory (r = 0.73 in Kroenke 2001), the Hamilton Depression Rating Scale (r = 0.79 in Cameron 2008), and clinician-rated severity (r = 0.59 in Kroenke 2001). It correlates appropriately with anxiety (GAD-7 r ≈ 0.6 — high, reflecting genuine comorbidity, but distinct construct).

Cross-cultural validity

The instrument has been validated in dozens of cross-cultural studies (English, German, Spanish, Mandarin Chinese, Japanese, Arabic, Brazilian Portuguese, French, others). Cultural expression of depression varies, and somatic-vs-cognitive emphasis differs across cultures, but the instrument's basic psychometric properties hold across translations.

14. Functional impairment override

The 10th item (functional difficulty) is captured but not added to the score. It influences the results in two ways:

Functional override note

If functional difficulty = "extremely difficult" (value 3) AND total score ≥ 5 (any band above minimal), the results panel surfaces a contextual note:

"You indicated these symptoms have been extremely difficult to live with. That impairment level — regardless of the precise band score — warrants a conversation with a clinician. Difficulty functioning is itself a clinical signal, separate from the symptom-frequency score."

Rationale

Functional impairment is a separate clinical signal from symptom frequency. DSM-5 MDE criteria require "clinically significant distress or functional impairment" — not just symptom presence. A user with mild symptom-frequency but extreme functional difficulty is in a clinically more concerning state than a user with the same symptom score and minimal functional difficulty. The override note surfaces this without modifying the underlying severity-band assignment.

15. Care-aware infrastructure

Depression carries higher absolute mortality risk than anxiety, primarily through suicide. The care-aware infrastructure is consequently more prominent than in the LBL Anxiety Test:

Always-on (independent of any score)

Score-triggered

Item-9 specific (the key escalation path)

Functional impairment override

16. Privacy & data handling

Completely browser-local. Specifically:

17. Limitations

  1. Snapshot, not trajectory. The instrument measures last-2-weeks symptoms. Depression naturally fluctuates with life events. A high score during a difficult period doesn't necessarily mean MDE; a low score during a calm period doesn't mean you've never had a depression problem.
  2. Self-report dependent. Honest self-report is the foundation. Strong self-criticism, alexithymia, denial, or recall bias can all distort scores in either direction.
  3. Not diagnostic. MDE diagnosis requires DSM-5 or ICD-11 clinical interview by a qualified professional. The screen is sensitive (88% per Kroenke 2001) but not diagnostic.
  4. Cultural variation. The instrument was developed in US/European primary care. Validation in non-Western populations exists but cultural expression of depression varies.
  5. Differential diagnosis ignored. A high score may reflect bipolar depression rather than unipolar, persistent depressive disorder rather than MDE, adjustment disorder, or grief. The screen flags "depression symptoms present" not "the source or kind of depression."
  6. Sub-dimension scoring is interpretive, not validated. The 3-dimension profile is an author-derived interpretive aid. Use as a conversation starter, not a clinical typology.
  7. Archetypes are interpretive frameworks. The 5 archetypes are LBL author-derived. They are not a published clinical typology.
  8. Functional impairment item is captured but not summed. The 10th question informs interpretation but does not change the 0-27 score.
  9. Validation in adolescents and children is separate. The instrument has separate adolescent validation (PHQ-A, n=403, Richardson 2010) but the cutoffs differ. This tool is not validated for users under 18.
  10. Documented author choices. Three components are author-derived (sub-dimension assignments, asymmetric scaling factors, approximate dx-prob values per band). All are documented in §12.

18. Frequently asked questions

Why use the 9-item Kroenke 2001 instrument and not something longer like the Beck Depression Inventory?

The 9-item depression screener developed by Kroenke, Spitzer & Williams in 2001 is purpose-built for primary-care screening contexts where time is limited. Its brevity (2-3 minutes), strong validation (Cronbach α=0.89; sensitivity 88%, specificity 88% at cutoff ≥10 per the original validation), and direct mapping to all 9 DSM major depressive episode criteria make it the most widely-used brief depression screener in the world, with over 100,000 citations. The Beck Depression Inventory has 21 items; the Hamilton Depression Rating Scale is clinician-administered. Both have their place, but neither is appropriate for a 2-3 minute self-screen.

How were the severity bands chosen?

Directly from Kroenke et al. 2001: 0-4 minimal, 5-9 mild, 10-14 moderate, 15-19 moderately severe, 20-27 severe. These cutpoints are used by NHS IAPT (Improving Access to Psychological Therapies), VA/DoD clinical practice guidelines, and the APA major depressive disorder treatment guidelines. The standard ≥10 cutoff was confirmed by Manea, Gilbody & McMillan's 2012 meta-analysis of 18 studies as having the best sensitivity/specificity balance across primary care populations (sensitivity 0.78-0.88, specificity 0.85-0.94).

Why is the sub-dimension symptom profile considered an author choice?

The original 9-item screener is largely unidimensional in factor analysis (Kroenke 2001 confirmed single-factor structure; Cameron 2008 replicated). Splitting items into cognitive-emotional, physical/somatic, and pleasure-motivation dimensions is an interpretive aid added by LifeByLogic to surface action-relevant patterns. It is presented transparently as an author choice rather than a validated subscale, and the methodology section documents the item assignments and asymmetric scaling factors used.

Why does item 9 trigger an immediate crisis modal that cannot be dismissed casually?

Item 9 captures self-harm ideation. Mann et al. 2005's systematic review of suicide prevention strategies concluded that means restriction and direct connection to crisis resources are among the most evidence-supported interventions. Surfacing crisis resources immediately upon any non-zero response on item 9 — and requiring explicit acknowledgment to dismiss — is a deliberate friction designed to ensure the user encounters the resources, not to obstruct their use of the tool. The modal is non-blocking; the user can continue to results after acknowledging.

How were the 5 archetypes derived?

The 5 archetypes (The Steady, The Inner Critic, The Depleted, The Disconnected, The Pervasive) are LBL author-derived interpretive frameworks that match symptom profile to evidence-based intervention classes. Each archetype maps to interventions with strong meta-analytic or RCT support — CBT for cognitive-emotional dominance (Cuijpers 2013), behavioral activation for anhedonic dominance (Dimidjian 2006, Ekers 2014), exercise/sleep stabilization for somatic dominance (Cooney 2013). Archetypes are explicitly named as interpretive frameworks, not a published clinical typology.

Why are the diagnostic probability values labeled 'approximate'?

The values (1/10/50/75/90 in 100 across the 5 bands) are derived from the Kroenke 2001 ROC data showing 88% sensitivity and 88% specificity at ≥10 cutoff in a primary care sample of n=580. They are population-dependent — the actual confirmed-MDE rate in any individual user's case depends on the base rate of major depression in their context. They serve as an intuitive interpretation aid, not a precise probabilistic statement, and the methodology page documents the derivation transparently.

Why include a functional impairment item if it's not added to the score?

The 10th item asking 'how difficult have these problems made it' is part of the original Kroenke 2001 instrument and is captured for the same reason: functional impairment is a separate clinical signal from symptom frequency. A user with moderate symptom-frequency but extreme functional difficulty may need more urgent follow-up than a user with the same symptom score and minimal functional difficulty. This tool surfaces a 'functional override' note in the results when functional difficulty is reported as 'extremely difficult' alongside any symptom score above minimal.

How does this tool handle privacy?

Completely browser-local. The 9 responses, the functional impairment response, computed scores, archetype, and any optional inputs (such as sex for sex-stratified norms) never leave the device. No transmission, no storage, no logging. Closing the tab clears the session. The tool uses Google Analytics 4 in a privacy-respecting manner for aggregate page-level metrics only — never individual responses.

What is this tool not for?

Not a diagnosis. Not a treatment plan. Not a substitute for clinical judgment. Not appropriate for users currently in psychiatric crisis (the crisis modal will surface the relevant resources immediately, but anyone in active crisis should call 988 or local emergency services). Not validated for use under age 18 (the original instrument was validated in adult primary care). Not a longitudinal tracking tool — this is a self-screen at a single moment in time.

How does this differ from the LBL Anxiety Test?

The Anxiety Test uses the 7-item GAD-7 (Spitzer 2006) and produces a 0-21 score with 4 severity bands. The Depression Test uses the 9-item depression screener (Kroenke 2001) and produces a 0-27 score with 5 severity bands. The Depression Test adds an item-9 hard-escalation crisis modal because of the self-harm ideation item, which has no parallel in the GAD-7. Anxiety and depression are highly comorbid (40-60% overlap in clinical samples per Kroenke 2007); both screens together give a fuller picture than either alone.

19. References & citations

  1. Kroenke, K., Spitzer, R. L., & Williams, J. B. W. (2001). The PHQ-9: Validity of a brief depression severity measure. Journal of General Internal Medicine, 16(9), 606–613. doi.org/10.1046/j.1525-1497.2001.016009606.x
  2. Manea, L., Gilbody, S., & McMillan, D. (2012). Optimal cut-off score for diagnosing depression with the Patient Health Questionnaire (PHQ-9): a meta-analysis. CMAJ, 184(3), E191–E196. doi.org/10.1503/cmaj.110829
  3. Kocalevent, R. D., Hinz, A., & Brähler, E. (2013). Standardization of the depression screener Patient Health Questionnaire (PHQ-9) in the general population. General Hospital Psychiatry, 35(5), 551–555. doi.org/10.1016/j.genhosppsych.2013.04.006
  4. Beard, C., Hsu, K. J., Rifkin, L. S., Busch, A. B., & Björgvinsson, T. (2016). Validation of the PHQ-9 in a psychiatric sample. Journal of Affective Disorders, 193, 267–273. doi.org/10.1016/j.jad.2015.12.075
  5. Hasin, D. S., Sarvet, A. L., Meyers, J. L., et al. (2018). Epidemiology of adult DSM-5 major depressive disorder and its specifiers in the United States. JAMA Psychiatry, 75(4), 336–346. doi.org/10.1001/jamapsychiatry.2017.4602
  6. Cuijpers, P., Berking, M., Andersson, G., Quigley, L., Kleiboer, A., & Dobson, K. S. (2013). A meta-analysis of cognitive-behavioural therapy for adult depression. Canadian Journal of Psychiatry, 58(7), 376–385. doi.org/10.1177/070674371305800702
  7. Cooney, G. M., Dwan, K., Greig, C. A., et al. (2013). Exercise for depression. Cochrane Database of Systematic Reviews, (9), CD004366. doi.org/10.1002/14651858.CD004366.pub6
  8. Dimidjian, S., Hollon, S. D., Dobson, K. S., et al. (2006). Randomized trial of behavioral activation, cognitive therapy, and antidepressant medication in the acute treatment of adults with major depression. Journal of Consulting and Clinical Psychology, 74(4), 658–670. doi.org/10.1037/0022-006X.74.4.658
  9. Ekers, D., Webster, L., Van Straten, A., Cuijpers, P., Richards, D., & Gilbody, S. (2014). Behavioural activation for depression: an update of meta-analysis. PLOS ONE, 9(6), e100100. doi.org/10.1371/journal.pone.0100100
  10. Hollon, S. D., DeRubeis, R. J., Shelton, R. C., et al. (2005). Prevention of relapse following cognitive therapy vs medications. Archives of General Psychiatry, 62(4), 417–422. doi.org/10.1001/archpsyc.62.4.417
  11. Kuyken, W., Warren, F. C., Taylor, R. S., et al. (2016). Efficacy of mindfulness-based cognitive therapy in prevention of depressive relapse. JAMA Psychiatry, 73(6), 565–574. doi.org/10.1001/jamapsychiatry.2016.0076
  12. Mann, J. J., Apter, A., Bertolote, J., et al. (2005). Suicide prevention strategies: a systematic review. JAMA, 294(16), 2064–2074. doi.org/10.1001/jama.294.16.2064
  13. American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental Disorders (5th ed.). DSM-5. APA Publishing.
  14. Lejuez, C. W., Hopko, D. R., & Hopko, S. D. (2001). A brief behavioral activation treatment for depression: Treatment manual. Behavior Modification, 25(2), 255–286. doi.org/10.1177/0145445501252005
  15. Kroenke, K., Spitzer, R. L., Williams, J. B. W., Monahan, P. O., & Löwe, B. (2007). Anxiety disorders in primary care: prevalence, impairment, comorbidity, and detection. Annals of Internal Medicine, 146(5), 317–325.

Read the LBL Depression Test tool itself, or browse the depression screener glossary entry.