Community management linked to low antipsychotic discontinuation in schizophrenia

A cross-sectional survey in Chengdu found a 4.1% discontinuation rate and flagged practical, modifiable risks.

A survey of 1,531 people with schizophrenia under community management in Chengdu, China found a low medication discontinuation rate of 4.1%. Discontinuation was more likely when illness stability was weaker, insight was poorer, side effects were noticeable, or follow-up was absent. The takeaway is straightforward: consistent, structured community follow-up plus active side-effect and insight work may help keep people on treatment.

Quick summary

What the study found: In a community-managed sample, stopping all antipsychotics for more than 15 days without medical advice was uncommon (4.1%) and was linked to weaker stability, low insight, noticeable side effects, and lack of follow-up.
Why it matters: Medication discontinuation in schizophrenia is tied to worse outcomes; this points to specific, actionable targets inside community care that may protect continuity.
What to be careful about: This was a cross-sectional design (a snapshot in time), so it cannot prove community management caused the low rate or that the risk factors caused discontinuation.

What was found

The journal article Community management: An effective model to reduce medication discontinuation rate in patients with schizophrenia examined medication discontinuation among people already enrolled in a community management model. The researchers surveyed 1,531 patients in Chengdu, China using face-to-face interviews and a multi-stage sampling approach.

They defined “treatment discontinuation” precisely: stopping all antipsychotic medications for more than 15 days without medical advice. Using univariate and multivariable logistic regression (a statistical method that estimates how strongly each factor is associated with an outcome while accounting for other factors), they tested which patient and service factors tracked with discontinuation.

The overall discontinuation rate was 4.1%. In multivariable analysis, four factors stood out as independently associated with discontinuation: weaker stable disease state, lack of insight, noticeable medication side effects, and absence of regular follow-up. “Adjusted odds ratio” means the association remained after accounting for other measured variables; for example, weaker stability was linked to higher odds of discontinuation (adjusted odds ratio 2.70, 95% confidence interval 1.34–5.24).

Insight showed a strong pattern. Insight here refers to the person’s awareness and understanding of having an illness and needing treatment. Compared with no insight, partial insight and full insight were associated with much lower odds of discontinuation (partial versus none: adjusted odds ratio 0.25, 95% confidence interval 0.08–0.80; full versus none: adjusted odds ratio 0.18, 95% confidence interval 0.05–0.65).

Service contact mattered too. Compared with having no follow-up, intermittent follow-up and regular follow-up were both associated with lower odds of discontinuation (intermittent versus none: adjusted odds ratio 0.38, 95% confidence interval 0.20–0.72; regular versus none: adjusted odds ratio 0.22, 95% confidence interval 0.10–0.44). Noticeable side effects were associated with higher odds of discontinuation (adjusted odds ratio 1.98, 95% confidence interval 1.05–3.64).

What it means

The practical meaning of these results is not subtle: continuity of care is not only about prescribing an antipsychotic medication, but also about keeping the person supported enough to stay on it. “Community management” in this study is treated as a real-world service context in which follow-up happens; within that context, discontinuation was low and strongly tied to follow-up presence and quality.

Two of the biggest levers are follow-up and side-effect management. Side effects are a common and concrete reason people stop medication; if side effects are “noticeable,” stopping may feel like a rational self-protection move, especially if the person does not have easy access to a clinician who can adjust dose, switch medications, or offer supportive treatments. Follow-up creates the opportunity for that rapid problem-solving before “I can’t tolerate this” becomes “I stopped.”

The insight finding is equally actionable. Low insight can be part of schizophrenia itself, not stubbornness. When someone genuinely does not believe they are ill or does not see medication as relevant, adherence becomes a daily negotiation with reality. Community services that repeatedly, respectfully reinforce illness education, collaborate on goals, and involve trusted supports can reduce that friction even when full insight is not achievable.

Disease stability also matters. The study points to a “weak stable disease state” as a risk factor. Clinically, a less stable course can mean more symptom fluctuation, higher stress, or impaired functioning—each of which can erode routines, reduce trust in treatment, and increase conflict around taking medication. Stability is not only a medical outcome; it is also a behavioral platform that makes consistent medication use more feasible.

Where it fits

This study aligns with a basic behavioral health principle: adherence improves when treatment is easier to do, feels more worthwhile, and is supported by a system that notices early problems. Regular contact lowers “activation energy” for help-seeking. It also increases accountability in a non-punitive way—someone will ask, notice, and respond.

It also fits with what clinicians see in schizophrenia care: adherence is often driven less by abstract knowledge and more by day-to-day experience. If medication produces distressing side effects, the immediate cost is obvious. If benefits are gradual (fewer relapses, less paranoia, better functioning over time), they may be harder to credit—especially when insight is limited. Follow-up is the mechanism that can translate long-term goals into near-term adjustments that make staying on treatment tolerable.

The low discontinuation rate reported (4.1%) is notable in its own right, but the stronger value is in the “map” of modifiable risks. Even if the absolute rate differs in other settings, the same friction points—insight, side effects, stability, and follow-up—are common targets for improving continuity.

How to use it

For community programs, the clearest operational takeaway is to treat follow-up cadence as a safety intervention, not an administrative step. The study’s pattern suggests that moving people from “none” to “intermittent” and from “intermittent” to “regular” follow-up could meaningfully shift discontinuation risk. Practically, that can mean setting a minimum contact standard and building tracking systems so missed visits trigger outreach.

Make side effects a first-class agenda item. Don’t wait for a crisis or assume patients will volunteer problems. Simple, repeated questions—“Any new stiffness, restlessness, sleep changes, weight changes, sexual side effects, or sedation?”—can surface “noticeable” issues early. Once identified, the key is fast response: medication adjustments or supportive strategies, plus an explanation of what is happening and why it is treatable.

Build an “insight-sensitive” approach. When insight is low, arguing about diagnosis often fails. More effective approaches usually focus on the person’s priorities (sleep, work, relationships, avoiding hospitalization) and link medication to those goals. Use clear, non-technical language, repeat key points over time, and check understanding. If the person agrees to treatment for a reason other than “I have schizophrenia,” that can still support adherence.

Support stability with routine scaffolding. When symptoms are less stable, adherence can fall apart for practical reasons: disorganization, forgetfulness, disrupted sleep, or substance use (not measured here, so not claimed—just an example of common real-world barriers). Tools like pill organizers, simplified dosing schedules, and involvement of family or community workers can make “taking medication” less dependent on perfect daily functioning.

Limits & what we still don’t know

This was a cross-sectional study, meaning all data were collected at one point in time. That design can identify associations but cannot establish cause and effect. Community management was “associated with” a low discontinuation rate, but the study cannot prove community management caused the low rate.

The sample included patients already under community management in Chengdu, China, and results may not generalize to places with different service structures or access barriers. The data came from face-to-face interviews, which can introduce reporting bias if people underreport discontinuation or side effects.

We also do not learn from the excerpt what the community management model specifically included beyond follow-up, nor how “stable disease state” and “insight” were assessed in detail. That matters because program designers need the exact components and measurement approaches to replicate results faithfully.

Closing takeaway

In this survey of 1,531 community-managed patients with schizophrenia, medication discontinuation—defined as stopping all antipsychotics for more than 15 days without medical advice—was low at 4.1%. The strongest signals point to tractable targets: keep follow-up consistent, treat side effects quickly, and tailor engagement to the person’s level of insight and stability. If you run community care, this is the checklist to prioritize when the goal is simple: fewer people quietly stopping their medication.

Data in this article is provided by PLOS.

Tagged Adverse reactions, Antipsychotics, Drug therapy, Drugs, Economics, Epidemiology, Health care, Health economics, Medical risk factors, Mental health and psychiatry, Mental health therapies, Pharmaceutics, Pharmacology, Schizophrenia