Trajectories of depression in psychotherapy: How client characteristics predict clinical improvement

Lin, Tao; Farber, Barry A.

doi:10.1002/jclp.23119

Cited by 10 publications

(9 citation statements)

References 70 publications

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“…However, the result should be interpreted with caution. Other studies have found superior fit with different classes (see Lin & Farber, 2021; Palmer et al, 2021 [two classes] and Ellis et al, 2017 [four classes]) and it is possible that a model with four or more classes would be a better fit had the models terminated normally. Lastly, see Table 4 for the Reliable Change Index (RCI) for the full sample and the three latent classes…”

Section: Resultsmentioning

confidence: 99%

“…Researchers have further utilized treatment trajectory studies to understand the symptom changes for patients suffering from specific diagnostic issues, such as depression. Most recently, Lin and Farber (2021) conducted a LGMM to identify change trajectories for individuals suffering from depression and receiving outpatient psychotherapy. Results indicated two trajectories—those whose depression symptoms improved and those who did not.…”

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confidence: 99%

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A latent trajectory analysis of inpatient depression treatment.

Ulvenes

Soma²,

Melsom

et al. 2022

Psychotherapy

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Patients seeking psychotherapy may progress through treatment in varying ways. Modeling multiple treatment trajectories through growth mixture modeling provides a comprehensive way of understanding a patient population. Multiple trajectories may additionally help researchers describe complexities within a patient population, such as those with severe and persistent disorders and comorbid symptoms, to understand characteristics of patients that may be struggling during treatment. We analyzed the depression symptom outcome measures (PHQ-9) for 246 patients receiving inpatient depression treatment. We constructed a growth mixture model of depression symptom changes, allowing the number of treatment trajectories to emerge through the data, and utilized goodness-of-fit indices to select the superior model. Results indicated three classes was the best fitting model, with patients either (a) patients started above the clinical cutoff score for depression and had significant linear change over time, ending therapy just above the clinical cutoff—“Improvement-leveling off-improvement”; (b) patients started therapy well above the clinical cutoff, showed symptom alleviation at the beginning of therapy before the trajectory started to level off—“High symptom pressure”; or (c) patients started therapy just below the clinical cutoff, had steady change throughout therapy, ending well below the clinical cutoff—“continuous improvement.” Implications of the study may include altering the length of treatment based on patient presenting symptoms in order to best serve patients and utilize hospital resources.

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Section: Resultsmentioning

confidence: 99%

mentioning

confidence: 99%

A latent trajectory analysis of inpatient depression treatment.

Ulvenes

Soma²,

Melsom

et al. 2022

Psychotherapy

View full text Add to dashboard Cite

show abstract

“…While these findings consistently demonstrate that session frequency is associated with treatment outcome based on the average level of change for the entire sample, it should not be assumed that all clients respond to psychotherapy of a certain frequency in a similar manner. Since clients fall into heterogeneous trajectories of change even when receiving the same treatment (Lin & Farber, 2021; Owen et al, 2015; Palmer et al, 2021), the average outcome may fail to capture individual differences in treatment responses. Although weekly therapy results in a faster improvement trajectory than biweekly therapy on average (Erekson et al, 2015), the average trajectories may not apply to each individual.…”

Section: Session Frequencymentioning

confidence: 99%

Trajectories of change in weekly and biweekly therapy.

Lin,

Anderson,

Erekson

et al. 2024

Journal of Counseling Psychology

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Higher therapy session frequency has been found to result in faster recovery, but few studies have considered that clients follow diverse trajectories of change in psychotherapy. It is unknown how session frequency may affect the sizes and shapes of change trajectories. The present study examined clients' change trajectories in weekly and biweekly therapy in a naturalistic setting, as well as predictors of these trajectories. Using a sample of 5,102 clients receiving 3-10 therapy sessions at a university counseling center, we identified 886 clients attending approximately weekly therapy and 1,753 clients attending approximately biweekly therapy. We examined the change trajectories of the weekly and biweekly samples using latent growth mixture modeling (LGMM). Three trajectories were identified in weekly therapy: slow change (78.33%), early improvement (17.61%), and worse before better (4.06%), and in biweekly therapy: slow change (80.38%), early improvement (13.52%), and worse before better (6.1%). The worse before better subgroup in weekly therapy experienced greater deterioration than those in biweekly therapy. The slow change and early improvement subgroups in weekly therapy showed treatment outcome comparable to those of their respective counterparts in biweekly therapy. Clients' intake symptoms, including eating concerns, frustration/anger, depression, and academic concerns, significantly predicted change trajectories. Compared to biweekly therapy, weekly therapy leads to higher chances of early improvement and shortens the duration of suffering but results in greater deterioration for individuals who deteriorate in therapy. The impact of session frequency on treatment outcome varies across clients, and session frequency should be adjusted individually. Public Significance StatementThe study suggests that clients fall into three trajectories of change in both weekly and biweekly therapy and that increasing session frequency can increase the chances of achieving early improvement and shortens the duration of suffering but may intensify the negative effects of therapy. Individualizing session frequency can increase treatment efficacy and save clinical resources.

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“…The treatment outcome package (TOP) used by Nordberg et al, the same instrument as used by Jankowski et al (2019), was also used in this study. Last, Lin and Farber (2021) used the TOP depression subscale to model change trajectories, using a sample of outpatient clients, some of whom received psychodynamic treatment. They found two subgroups: a moderate symptom subgroup of improvers and a high symptom subgroup of non-improvers.…”

Section: Introductionmentioning

confidence: 99%

A constructive replication of client change during psychodynamic treatment in an outpatient setting

Jankowski,

Sandage,

Crabtree

et al. 2023

Couns and Psychother Res

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We responded to the need for replication in psychotherapy research by extending a prior naturalistic study documenting the effectiveness of long‐term psychodynamic treatment. We employed three novel analytic strategies and evaluated their influence on substantive interpretations offered in the prior study. The sample consisted of clients (N = 387; Mage = 31.61; SD = 11.13; 58.9% female; 79.1% Caucasian/White) receiving outpatient treatment at a psychodynamic training clinic. Results replicated the original two‐class solutions for social functioning, depression and life satisfaction. Novel to the replication analyses, each trajectory for social functioning and depression exhibited nonlinear change and results advanced research on a theorised mechanism of effective psychodynamic treatment. Results showed that change in experiential avoidance was a possible mechanism between early‐treatment change in social functioning and later‐treatment changes in depression symptoms and life satisfaction. Clinical implications focus on the influence that initial levels of symptoms and well‐being may have on early and later phases of treatment, monitoring progress throughout treatment, and how to promote symptom and well‐being improvement.

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Trajectories of depression in psychotherapy: How client characteristics predict clinical improvement

Cited by 10 publications

References 70 publications

A latent trajectory analysis of inpatient depression treatment.

A latent trajectory analysis of inpatient depression treatment.

Trajectories of change in weekly and biweekly therapy.

A constructive replication of client change during psychodynamic treatment in an outpatient setting

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